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National Cancer Institute Director Neil Sharpless says mortality from delays in cancer screenings due to COVID19 pandemic could result in tens of thousands of extra deaths in next decade

Reporter: Stephen J Williams, PhD

UPDATED: 08/14/2023

A Cross Sectional Study Reveals What Oncologists Had Feared: Cancer Screenings During Pandemic Has Decreased, leading to Decreased Early Detection

As discussed in many articles here on COVID-19 and cancer, during the pandemic many oncologists were worried that people slowed getting their cancer screenings due to health risks due to the COVID-19 outbreak.  Governmental agencies went as far to project upticks in future cancer rates, as preventative screening rates were down due to closed hospitals, shuttered services, or patient trepidation during the height of the pandemic.  As many oncologists voiced, a decrease in cancer screenings might lead to missing out on the early stages of the disease, when most treatable. Now, reported in a Lancet cross-sectional analysis by investigators at ACS and University of Texas Southwest (1), we have the first indication of the effects of this decrease in preventative screening, namely decreased early detection and diagnosis.

The authors used data from the US National Cancer Database, a nationwide hospital-based cancer registry, to perform a cross sectional nationwide assessment of the prevalence of new cancer diagnosis before, during, and after the height of the pandemic (March 1 2020 to December 31, 2020).  Newly diagnosed cases of first primary malignant cancer between Jan1, 2018 to Dec 31, 2020 were identified and monthly and annual counts and stage distributions were caluculated andpresented as adjusted odds ratios (aORs).  They also used the period from 2018 to Jan 2020 as a baseline or prepandemic level of newly diagnosed cancer.

Results of this analysis identified 2,404,050 adults with newly diagnosed cancer during study period 2018 to 2020.  The monthly number of new cancer diagnoses (all stages) decreased significantly after the start of the COVID-19 pandemic in March 2020.  However new cancer diagnosis returned to pre-pandemic levels by end of 2020.  The decrease in diagnosis was largest for stage I diseases however the odds of being diagnosed with late stage IV disease were higher in 2020 than in 2019.  When the authors stratified the cohorts based on sociodemographic groups, interestingly those most affected (with lowest diagnosis rates during the pandemic) were those living in socioeconomic deprived areas, hispanics, asian americans, pacific Islanders, and uninsured individuals.

The authors’ interpretations are a warning: Substantial cancer underdiagnosis and decreases in the proportion of early stage diagnoses occurred during 2020 in the USA, particularly among medically underserved individuals. Monitoring the long-term effects of the pandemic on morbidity, survival, and mortality is warranted.

 

 

Evidence before this study

We searched PubMed using the terms “COVID”, “pandemic”, and “cancer” for studies published in English between

March 1, 2020, and Nov 30, 2022. Health care was disrupted during the emergence of the COVID-19 pandemic. In the USA, rapid decreases in screening were reported for nearly all types of cancer screening services after the declaration of the COVID-19 national emergency. Decreased screening, and delayed and forgone routine check-ups or health-care visits, can lead to underdiagnosis of cancer, especially for early stage disease for which treatment is most effective. Several studies have identified reduced use of diagnostic procedures and decreases in the number of newly diagnosed patients during 2020 in the USA. However, these studies were done in selected populations, in specific geographical areas, or for only a single cancer type, limiting understanding of the COVID-19 pandemic on cancer burden nationally.

Added value of this study

Using a recently released nationwide cancer registry dataset, we comprehensively evaluated changes in cancer diagnoses and stage distribution during the first year of the COVID-19 pandemic by cancer type and key sociodemographic factors in the USA.

Implications of all the available evidence

Along with existing evidence, our findings should help to inform future policy and cancer care delivery interventions to improve access to care for underserved populations. Research is warranted to monitor the long-term effects of the underdiagnosis of early stage cancer identified in this study on morbidity, mortality, and disparities in health outcomes.

Results

The main results from the paper are summarized below:

 

Between 2020 and 2019, annual stage I diagnoses decreased by 17·2% (95% CI 16·8–17·6), and annual stage IV diagnoses decreased 9·8% (9·2–10·5). Notably, by race and ethnicity, the largest percentage reduction in stage I diagnoses was among Hispanic individuals and Asian American and Pacific Islander individuals, and the largest percentage reduction in stage IV diagnoses was among non-Hispanic Black and non-Hispanic White individuals. Diagnoses of lung cancer, colorectal cancer, melanoma, and non-Hodgkin lymphoma had the largest percentage reduction among both stage I (>18%) and stage IV (>10%) diagnoses; cancers of the prostate, cervix, liver, oesophagus, stomach, and thyroid also had large percentage reductions in stage I diagnoses (>20).

After adjusting for sociodemographic and clinical factors, the stage distribution of new diagnoses changed in 2020 compared with 2019 (table 3). Specifically, the aOR for being diagnosed with stage I disease versus stage II–IV disease in 2020 compared with 2019 was 0·946 (95% CI 0·939–0·952), and the aOR for being diagnosed with stage IV disease versus stage I–III disease in 2020 compared with 2019 was 1·074 (1·066–1·083).

These results also confirmed results seen in other studies coming from Europe (2,3, 4).

References

  1. Han X, Yang NN, Nogueira L, Jiang C, Wagle NS, Zhao J, Shi KS, Fan Q, Schafer E, Yabroff KR, Jemal A. Changes in cancer diagnoses and stage distribution during the first year of the COVID-19 pandemic in the USA: a cross-sectional nationwide assessment. Lancet Oncol. 2023 Aug;24(8):855-867. doi: 10.1016/S1470-2045(23)00293-0. PMID: 37541271.
  2. Kuzuu K, Misawa N, Ashikari K, et al. Gastrointestinal cancer stage at diagnosis before and during the COVID-19 pandemic in Japan. JAMA Netw Open 2021; 4: e2126334. DOI: 10.1001/jamanetworkopen.2021.26334
  3. Linck PA, Garnier C, Depetiteville MP, et al. Impact of the COVID-19 lockdown in France on the diagnosis and staging of breast cancers in a tertiary cancer centre. Eur Radiol 2022; 32: 1644–51. DOI: 10.1007/s00330-021-08264-3
  4. Mynard N, Saxena A, Mavracick A, et al. Lung cancer stage shift as a result of COVID-19 lockdowns in New York City, a brief report. Clin Lung Cancer 2022; 23: e238–42.  DOI: 10.1016/j.cllc.2021.08.010

 

 

UPDATED: 10/11/2021

Source: https://cancerletter.com/articles/20200619_1/

NCI Director’s Report

Sharpless: COVID-19 expected to increase mortality by at least 10,000 deaths from breast and colorectal cancers over 10 years

By Matthew Bin Han Ong

This story is part of The Cancer Letter’s ongoing coverage of COVID-19’s impact on oncology. A full list of our coverage, as well as the latest meeting cancellations, is available here.

The COVID-19 pandemic will likely cause at least 10,000 excess deaths from breast cancer and colorectal cancer over the next 10 years in the United States.

Scenarios run by NCI and affiliated modeling groups predict that delays in screening for and diagnosis of breast and colorectal cancers will lead to a 1% increase in deaths through 2030. This translates into 10,000 additional deaths, on top of the expected one million deaths resulting from these two cancers.

“For both these cancer types, we believe the pandemic will influence cancer deaths for at least a decade,” NCI Director Ned Sharpless said in a virtual joint meeting of the Board of Scientific Advisors and the National Cancer Advisory Board June 15. “I find this worrisome as cancer mortality is common. Even a 1% increase every decade is a lot of cancer suffering.

“And this analysis, frankly, is pretty conservative. We do not consider cancers other than those of breast and colon, but there is every reason to believe the pandemic will affect other types of cancer, too. We did not account for the additional non-lethal morbidity from upstaging, but this could also be significant and burdensome.”

An editorial by Sharpless on this subject appears in the journal Science.

The early analyses, conducted by the institute’s Cancer Intervention and Surveillance Modeling Network, focused on breast and colorectal cancers, because these are common, with relatively high screening rates.

CISNET modelers created four scenarios to assess long-term increases in cancer mortality rates for these two diseases:

  1. The pandemic has no effect on cancer mortality
  1. Delayed screening—with 75% reduction in mammography and, colorectal screening and adenoma surveillance for six months
  1. Delayed diagnosis—with one-third of people delaying follow-up after a positive screening or diagnostic mammogram, positive FIT or clinical symptoms for six months during a six-month period
  1. Combination of scenarios two and three

Treatment scenarios after diagnosis were not included in the model. These would be: delays in treatment, cancellation of treatment, or modified treatment.

“What we did is show the impact of the number of excess deaths per year for 10 years for each year starting in 2020 for scenario four versus scenario one,” Eric “Rocky” Feuer, chief of the NCI’s Statistical Research and Applications Branch in the Surveillance Research Program, said to The Cancer Letter.

Feuer is the overall project scientist for CISNET, a collaborative group of investigators who use simulation modeling to guide public health research and priorities.

“The results for breast cancer were somewhat larger than for colorectal,” Feuer said. “And that’s because breast cancer has a longer preclinical natural history relative to colorectal cancer.”

Modelers in oncology are creating a global modeling consortium, COVID-19 and Cancer Taskforce, to “support decision-making in cancer control both during and after the crisis.” The consortium is supported by the Union for International Cancer Control, The International Agency for Research on Cancer, The International Cancer Screening Network, the Canadian Partnership Against Cancer, and Cancer Council NSW, Australia.

A spike in cancer mortality rates threatens to reverse or slow down—at least in the medium term—the steady trend of reduction of cancer deaths. On Jan. 8, the American Cancer Society published its annual estimates of new cancer cases and deaths, declaring that the latest data—from 2016 to 2017—show the “largest ever single-year drop in overall cancer mortality of 2.2%.” Experts say that innovation in lung cancer treatment and the success of smoking cessation programs are driving the sharp decrease (The Cancer LetterFeb. 7, 2020).

The pandemic is expected to have broader impact, including increases in mortality rates for other cancer types. Also, variations in severity of COVID-19 in different regions in the U.S. will influence mortality metrics.

“There’s some other cancers that might have delays in screening—for example cervical, prostate, and lung cancer, although lung cancer screening rates are still quite low and prostate cancer screening should only be conducted on those who determine that the benefits outweigh the harms,” Feuer said. “So, those are the major screening cancers, but impacts of delays in treatment, canceling treatment or alternative treatments—could impact a larger range of cancer sites.

“This model assumes a moderate disruption which resolves after six months, and doesn’t consider non-lethal morbidities associated with the delay. One thing I think probably is occurring is regional variation in these impacts,” Feuer said. “If you’re living in New York City where things were ground zero for some of the worst impact early on, probably delays were larger than other areas of the country. But now, as we’re seeing upticks in other areas of the country, there may be in impact in these areas as well”

How can health care providers mitigate some of these harms? For example, for people who delayed screening and diagnosis, are providers able to perform triage, so that those at highest risk are prioritized?

“From a strictly cancer control point of view, let’s get those people who delayed screening, or followup to a positive test, or treatment back on schedule as soon as possible,” Feuer said. “But it’s not a simple calculus, because in every situation, we have to weigh the harms and benefits. As we come out of the pandemic, it tips more and more to, ‘Let’s get back to business with respect to cancer control.’

“Telemedicine doesn’t completely substitute for seeing patients in person, but at least people could get the advice they need, and then are triaged through their health care providers to indicate if they really should prioritize coming in. That helps the individual and the health care provider  weigh the harms and benefits, and try to strategize about what’s best for any individual.”

If the pandemic continues to disrupt routine care, cancer-related mortality rates would rise beyond the predictions in this model.

“I think this analysis begins to help us understand the costs with regard to cancer outcomes of the pandemic,” Sharpless said. “Let’s all agree we will do everything in our power to minimize these adverse effects, to protect our patients from cancer suffering.”

UPDATED: 10/11/2021

Patients with Cancer Appear More Vulnerable to SARS-CoV-2: A Multicenter Study during the COVID-19 Outbreak

Source:

Mengyuan DaiDianbo LiuMiao LiuFuxiang ZhouGuiling LiZhen ChenZhian ZhangHua YouMeng WuQichao ZhengYong XiongHuihua XiongChun WangChangchun ChenFei XiongYan ZhangYaqin PengSiping GeBo ZhenTingting YuLing WangHua WangYu LiuYeshan ChenJunhua MeiXiaojia GaoZhuyan LiLijuan GanCan HeZhen LiYuying ShiYuwen QiJing YangDaniel G. TenenLi ChaiLorelei A. MucciMauricio Santillana and Hongbing Cai. Patients with Cancer Appear More Vulnerable to SARS-CoV-2: A Multicenter Study during the COVID-19 Outbreak

Abstract

The novel COVID-19 outbreak has affected more than 200 countries and territories as of March 2020. Given that patients with cancer are generally more vulnerable to infections, systematic analysis of diverse cohorts of patients with cancer affected by COVID-19 is needed. We performed a multicenter study including 105 patients with cancer and 536 age-matched noncancer patients confirmed with COVID-19. Our results showed COVID-19 patients with cancer had higher risks in all severe outcomes. Patients with hematologic cancer, lung cancer, or with metastatic cancer (stage IV) had the highest frequency of severe events. Patients with nonmetastatic cancer experienced similar frequencies of severe conditions to those observed in patients without cancer. Patients who received surgery had higher risks of having severe events, whereas patients who underwent only radiotherapy did not demonstrate significant differences in severe events when compared with patients without cancer. These findings indicate that patients with cancer appear more vulnerable to SARS-CoV-2 outbreak.

Significance: Because this is the first large cohort study on this topic, our report will provide much-needed information that will benefit patients with cancer globally. As such, we believe it is extremely important that our study be disseminated widely to alert clinicians and patients.

Introduction

A new acute respiratory syndrome coronavirus, named SARS-CoV-2 by the World Health Organization (WHO), has rapidly spread around the world since its first reported case in late December 2019 from Wuhan, China (1). As of March 2020, this virus has affected more than 200 countries and territories, infecting more than 800,000 individuals and causing more than 40,000 deaths (2).

With more than 18 million new cases per year globally, cancer affects a significant portion of the population. Individuals affected by cancer are more susceptible to infections due to coexisting chronic diseases, overall poor health status, and systemic immunosuppressive states caused by both cancer and anticancer treatments (3). As a consequence, patients with cancer who are infected by the SARS-CoV-2 coronavirus may experience more difficult outcomes than other populations. Until now, there is still no systematic evaluation of the effects that the SARS-CoV-2 coronavirus has of patients with cancer in a representative population. A recent study reported a higher risk of severe events in patients with cancer when compared with patients without cancer (4); however, the small sample size of SARS-CoV-2 patients with cancer used in the study limited how representative it was of the whole population and made it difficult to conduct more insightful analyses, such as comparing clinical characteristics of patients with different types of cancer, as well as anticancer treatments (5, 6).

Using patient information collected from 14 hospitals in Hubei Province, China, the epicenter of the 2019–2020 COVID-19 outbreak, we describe the clinical characteristics and outcomes [death, intensive care unit (ICU) admission, development of severe/critical symptoms, and utilization of invasive mechanical ventilation] of patients affected by the SARS-CoV-2 coronavirus for 105 hospitalized patients with cancer and 536 patients without cancer. We document our findings for different cancer types and stages, as well as different types of cancer treatments. We believe the information and insights provided in this study will help improve our understanding of the effects of SARS-CoV-2 in patients with cancer.

Results

Patients Characteristics

In total, 105 COVID-19 patients with cancer were enrolled in our study for the time period January 1, 2020, to February 24, 2020, from 14 hospitals in Wuhan, China. COVID-19 patients without cancer matched by the same hospital, hospitalization time, and age were randomly selected as our control group. Our patient population included 339 females and 302 males. Patients with cancer [median = 64.00, interquartile range (IQR) = 14.00], when compared with those without cancer (median = 63.50, IQR = 14.00) had similar age distributions (by design), experienced more in-hospital infections [20 (19.04%) of 105 patients vs. 8 (1.49%) of 536 patients;P < 0.01], and had more smoking history [36 (34.28%) of 105 patients vs. 46 (8.58%) of 536 patients; P < 0.01], but had no significant differences in sex, other baseline symptoms, and other comorbidities (Table 1). With respect to signs and symptoms upon admission, COVID-19 patients with cancer were similar to those without cancer except for a higher prevalence of chest distress [15 (14.29%) of 105 patients vs. 36 (6.16%) of 536 patients; P = 0.02].

Table 1.

Characteristics of COVID-19 patients with and without cancer

Clinical Outcomes

Compared with COVID-19 patients without cancer, patients with cancer had higher observed death rates [OR, 2.34; 95% confidence interval (CI), (1.15–4.77); P = 0.03], higher rates of ICU admission [OR, 2.84; 95% CI (1.59–5.08); P < 0.01], higher rates of having at least one severe or critical symptom [OR, 2.79; 95% CI, (1.74–4.41); P < 0.01], and higher chances of needing invasive mechanical ventilation (Fig. 1A). We also conducted survival analysis on occurrence of any severe condition which included death, ICU admission, having severe symptoms, and utilization of invasive mechanical ventilation (see cumulative incidence curves in Fig. 1B). In general, patients with cancer deteriorated more rapidly than those without cancer. These observations are consistent with logistic regression results (Supplementary Fig. S1), after adjusting for age, sex, smoking, and comorbidities including diabetes, hypertension, and chronic obstructive pulmonary disease (COPD). According to our multivariate logistic regression results, patients with cancer still had an excess OR of 2.17 (P = 0.06) for death (Supplementary Fig. S1A), 1.99 (P < 0.01) for experiencing any severe symptoms (Supplementary Fig. S1B), 3.13 (P < 0.01) for ICU admission (Supplementary Fig. S1C), and 2.71 (P = 0.04) for utilization of invasive mechanical ventilation (Supplementary Fig. S1D; Supplementary Table S1). The consistency of observed ORs between the multivariate regression model and unadjusted calculation reassures the association between cancer and severe events even in the presence of other factors such as age differences.

Figure 1.

Severe conditions in patients with and without cancer, and patients with different types, stages, and treatments of cancer. Severe conditions include death, ICU admission, having severe/critical symptoms, and usage of invasive mechanical ventilation. Incidence and survival analysis of severe conditions among COVID-19 patients with cancer and without cancer (A and B), among patients with different types of cancer (C and D), among patients with metastatic and nonmetastatic cancers (E and F), among patients with lung cancer, other cancers than lung with lung metastasis, and other cancers than lung without lung metastasis (G and H), and patients receiving different types of cancer treatments (I and J). P values indicate differences between cancer subgroups versus patients without cancer. For ACEGI, *, P < 0.05; **, P < 0.01. OR, 95% CI, and P values between different subgroups are listed in Supplementary Table S2. For BDFHJ, HR, 95% CI, and P values are listed in Supplementary Table S3.

Cancer Types

Information regarding potential risks of severe conditions in SARS-CoV-2 associated with each type of cancer was calculated. We compared different conditions among cancer types (Table 2). Lung cancer was the most frequent cancer type [22 (20.95%) of 105 patients], followed by gastrointestinal cancer [13 (12.38%) of 105 patients], breast cancer [11 (10.48%) of 105 patients], thyroid cancer [11 (10.48%) of 105 patients], and hematologic cancer [9 (8.57%) of 105 patients]. As shown in Fig. 1C and D and Supplementary Table S2, patients with hematologic cancer including leukemia, lymphoma, and myeloma have a relatively high death rate [3 (33.33%) of 9 patients], high ICU admission rate [4 (44.44%) of 9 patients], high risks of severe/critical symptoms [6 (66.67%) of 9 patients], and high chance of utilization of invasive mechanical ventilation [2 (22.22%) of 9 patients]. Patients with lung cancer had the second-highest risk levels, with death rate [4 (18.18%) of 22 patients], ICU admission rate [6 (27.27%) of 22 patients], risks of severe/critical symptoms [11 (50.00%) of 22 patients], and the chance of utilization of invasive mechanical ventilation [4 (18.18%) of 22 patients; Table 2].

Table 2.

Severe events in 105 patients with cancer for each type of cancer

Cancer Stage

We found that patients with metastatic cancer (stage IV) had even higher risks of death [OR, 5.58; 95% CI (1.71–18.23); P = 0.01], ICU admission [OR, 6.59; 95% CI (2.32–18.72); P < 0.01], having severe conditions [OR, 5.97; 95% CI (2.24–15.91); P < 0.01], and use of invasive mechanical ventilation [OR, 55.42; 95% CI (13.21–232.47); P < 0.01]. In contrast, patients with nonmetastatic cancer did not demonstrate statistically significant differences compared with patients without cancer, with all P > 0.05 (Fig. 1E and F; Supplementary Tables S2 and S3). In addition, when compared with patients without cancer, patients with lung cancer or other cancers with lung metastasis also showed higher risks of death, ICU admission rates, higher critical symptoms, and use of invasive mechanical ventilation, with all P values below 0.01, but other cancers without lung metastasis had no statistically significant differences (all P values > 0.05; Fig. 1G and H; Supplementary Table S3) when compared with patients without cancer.

Cancer Treatments

Among the 105 COVID-19 patients with cancer in our study, 13 (12.26%) had radiotherapy, 17 (14.15%) received chemotherapy, 8 (7.62%) received surgery, 4 (3.81%) had targeted therapy, and 6 (5.71%) had immunotherapy within 40 days before the onset of COVID-19 symptoms. All of the targeted therapeutic drugs were EGFR–tyrosine kinase inhibitors for treatment of lung cancer, and all of the immunotherapy drugs were PD-1 inhibitors for the treatment of lung cancer. A patient with cancer may have more than one type of therapy. Our observation suggested that patients who received immunotherapy tended to have high rates of death [2 (33.33%) of 6 patients] and high chances of developing critical symptoms [4 (66.67%) of 6 patients]. Patients who received surgery demonstrated higher rates of death [2 (25.00%) of 8 patients], higher chances of ICU admission [3 (37.50%) of 8 patients], higher chances of having severe or critical symptoms [5 (62.50%) of 8 patients], and higher use of invasive ventilation [2 (25.00%) of 8 patients] than other treatments excluding immunotherapy. However, patients with cancer who received radiotherapy did not show statistically significant differences in having any severe events when compared with patients without cancer, with all P values > 0.10 (Fig. 1I and J). Clinical details on the cancer diagnoses and cancer treatments are summarized in Supplementary Table S4.

Timeline of Severe Events

To evaluate the time-dependent evolution of the disease, we conducted the timeline of different events for COVID-19 patients with cancer (Fig. 2A) and COVID-19 patients without cancer (Fig. 2B) with death and other severe events marked in the figure. COVID-19 patients with cancer had a mean length of stay of 27.01 days (SD 9.52) and patients without cancer had a mean length of stay of 17.75 days (SD 8.64); the difference is significant (Wilcoxon test, P < 0.01). To better clarify the contributing factors that might influence outcomes, we also included logistic regression of COVID-19 patients with cancer adjusted by immunosuppression levels in Supplementary Table S5. However, no significant association between immunosuppression and severe outcomes was observed from the analysis (with all P > 0.05).

Figure 2.

Timeline of events for COVID-19 patients. A, Timeline of events in COVID-19 patients with cancer. B, Timeline of events in COVID-19 patients without cancer. For visualization purposes, patients without timeline information are excluded and only 105 COVID-19 patients without cancer are shown.

Discussion

The findings in this study suggest that patients with cancer infected with SARS-CoV-2 tend to have more severe outcomes when compared with patients without cancer. Patients with hematologic cancer, lung cancer, and cancers in metastatic stages demonstrated higher rates of severe events compared with patients without cancer. In addition, patients who underwent cancer surgery showed higher death rates and higher chances of having critical symptoms.

The SARS-CoV-2 virus has spread rapidly globally; thus, many countries have not been ready to handle the large volume of people affected by this outbreak due to a lack of knowledge about how this coronavirus affects the general population. To date, reports on the general population infected with SARS-CoV-2 suggest elderly males have a higher incidence and death rate (7, 8). Limited information is known about the outcome of patients with cancer who contract this highly communicable disease. Cancer is among the top causes of death. Asia, Europe, and North America have the highest incidence of cancer in the world (9), and at the moment of the writing of this study the SARS-CoV-2 virus is mainly spreading in these three areas (referred from https://www.cdc.gov/media/releases/2020/s0226-Covid-19-spread.htmlhttps://www.nytimes.com/2020/02/27/world/coronavirusnews.html). Although COVID-19 patients with cancer may share some epidemiologic features with the general population with this disease, they may also have additional clinical characteristics. Therefore, we conducted this study on patients with cancer with coexisting COVID-19 disease to evaluate the potential effect of COVID-19 on patients with cancer.

On the basis of our analysis, COVID-19 patients with cancer tend to have more severe outcomes when compared with the noncancer population. Although COVID-19 is reported to have a relatively low death rate of 2% to 3% in the general population (10), patients with cancer and COVID-19 not only have a nearly 3-fold increase in the death rate than that of COVID-19 patients without cancer, but also tend to have much higher severity of their illness. Altogether, these findings suggest that patients with cancer are a much more vulnerable population in the current COVID-19 outbreak. Our findings are consistent with those presented in a previous study based on 18 patients with cancer (4). Because of the limited number of patients with cancer in the previous study, the authors concluded that among patients with cancer, age is the only risk factor for the severity of the illness. On the basis of our data on 105 patients with cancer, we have discovered additional risk factors, including cancer types, cancer stage, and cancer treatments, which may contribute to the severity of the disease among patients with cancer.

Our data demonstrate that the severity of SARS-CoV-2 infection in patients is significantly affected by the types of tumors. From our analysis, patients with hematologic cancer have the highest severity and death rates among all patients with cancer, and lung cancer follows second. Patients with hematologic cancer in our study include patients with leukemia, myeloma, and lymphoma, who have a more compromised immune system than patients with solid tumors (11). These patients all had a rapidly deteriorating clinical course once infected with COVID-19. Because malignant or dysfunctional plasma cells, lymphocytes, or white blood cells in general in hematologic malignancies have decreased immunologic function (12–14), this could be the main reason why patients with hematologic cancer have very high severity and death rates. All patients with hematologic cancer are prone to the complications of serious infection (12–14), which can exacerbate the condition which could have worsened in patients with COVID-19. In our study, 55.56% of patients with hematologic cancer had severe immunosuppression, which may be the main reason for deteriorated outcomes. Although the small sample size limits representativity of the observation, we believe our finding can serve as an informative starting point for further investigation when a larger cohort from a wide range of healthcare providers becomes available. Among solid tumors, lung cancer is the highest risk category disease in patients with SARS-CoV-2 infection (Fig. 1C). Decreased lung function and severe infection in patients with lung cancer could contribute to the worse outcome in this subpopulation (15, 16).

In our analysis, we classified the SARS-CoV-2 infection–related high risk factors based on death, severe or critical illness, ICU admission, and the utilization of invasive mechanical ventilation. Using these parameters, we detected a multi-fold increase in risk in the cancer population, in contrast to the noncancer population. If there were primary or metastatic tumors in the lungs, patients were more prone to a deteriorated course in a short time. Intriguingly, when patients with cancer had only early-stage disease without metastasis, we did not observe any difference between the cancer and noncancer population in terms of COVID-19–related death rate or severity (Fig. 1E). The stage of cancer diagnosis seemed to play a significant role in the severity and death rate of COVID-19.

Patients with cancer received a wide range of treatments, and we also found that different types of treatments had different influences on severity and death when these patients contracted COVID-19. Recently, immunotherapy has assumed a very important role in treating tumors, which aids in treatment of cancer by blocking the immune escape of cancer cells. But in our study, in contrast to patients with cancer with other treatments, patients with immunotherapy had the highest death rate and the highest severity of illness, a very puzzling finding. According to pathologic studies on the patients with COVID-19, there were desquamation of pneumocytes and hyaline membrane formation, implying that these patients had acute respiratory distress syndrome (ARDS; ref. 17). ARDS induced by cytokine storm is reported to be the main reason for death of SARS-CoV-2–infected patients (18). It is possible that in this setting, immunotherapy induces the release of a large amount of cytokines, which can be toxic to normal cells, including lung epithelial cells (19–21), and therefore lead to a more severe illness. However, in this study the number of patients with immunotherapy was too small; further research with a large case population needs to be conducted in the future.

In addition, COVID-19 patients with cancer who are under active treatment or not under active treatment do not show differences in their outcomes, and there is a significant difference between COVID-19 patients with cancer but not with active treatment and patients without cancer (Supplementary Table S2). These results indicate that COVID-19 patients with both active treatment and just cancer history have a higher risk of developing severe events than noncancer COVID-19 patients. The possible reasons could be due to some known cancer-related complications, for example, anemia, hypoproteinaemia, or dyspnea in early phase of COVID-19 (22). We considered that cancer had a lifetime effect on patients and that cancer survivors always need routine follow-up after primary resection. Therefore, in clinical COVID-19 patient management, equivalent attention needs to be paid to those with cancer whether they are under active therapeutics or not during the outbreak of COVID-19.

This study has several limitations. Although the cohort of COVID-19 patients with cancer is one of the largest in Hubei province, China, the epicenter of the initial outbreak, a larger cohort from the whole country or even from multiple countries will be more representative. Large-scale national and international research collaboration will be necessary to achieve this. At the initial stage of the outbreak, data collection and research activities were not a priority of the hospitals. Therefore, it was not possible to record and collect some data that are potentially informative for our analysis in a timely manner. In addition, due to the urgency of clinical treatment, medical data used in this study were largely disconnected from the patients’ historical electronic medical records, which are mostly stored with a different healthcare provider than the medical center providing COVID-19 care. This left us with limited information about each patient.

Our study is the midsize cohort study on this topic and will provide much-needed information on risk factors of this population. We hope that our findings will help countries better protect patients with cancer affected by the ongoing COVID-19 pandemic.

Methods

Study Design and Patients

We conducted a multicenter study focusing on the clinical characteristics of confirmed cases of COVID-19 patients with cancer in 14 hospitals in Hubei province, China; all of the 14 hospitals served as government-designated hospitals for patients diagnosed with COVID-19. SARS-CoV-2–infected patients without cancer matched by the same hospital and hospitalization time were randomly selected as our control group. In addition, as age is one of the major predictors of severity of respiratory diseases like COVID-19 (4), we excluded from our analysis 117 younger COVID-19 patients without cancer so that median ages of patients with cancer (median = 64.0, IRQ = 14.00) and patients without cancers (median = 63.5, IQR = 14.00) would be comparable.

End Points and Assessments

There were four primary outcomes analyzed in this study: death, admission into the ICU, development of severe or critical symptoms, and utilization of invasive mechanical ventilation. The clinical definition of severe/critical symptoms follows the 5th edition of the 2019Novel Coronavirus Disease (COVID-19) Diagnostic Criteria published by the National Health Commission in China, including septic shock, ARDS, acute kidney injury, disseminated intravascular coagulation, and rhabdomyolysis.

Case Fatality Rate of Cancer Patients with COVID-19 in a New York Hospital System

Source:

Vikas MehtaSanjay GoelRafi KabarritiDaniel ColeMendel GoldfingerAna Acuna-VillaordunaKith PradhanRaja ThotaStan ReissmanJoseph A. SparanoBenjamin A. GartrellRichard V. SmithNitin OhriMadhur GargAndrew D. RacineShalom KalnickiRoman Perez-SolerBalazs Halmos and Amit Verma. Case Fatality Rate of Cancer Patients with COVID-19 in a New York Hospital System

Abstract

Patients with cancer are presumed to be at increased risk from COVID-19 infection–related fatality due to underlying malignancy, treatment-related immunosuppression, or increased comorbidities. A total of 218 COVID-19–positive patients from March 18, 2020, to April 8, 2020, with a malignant diagnosis were identified. A total of 61 (28%) patients with cancer died from COVID-19 with a case fatality rate (CFR) of 37% (20/54) for hematologic malignancies and 25% (41/164) for solid malignancies. Six of 11 (55%) patients with lung cancer died from COVID-19 disease. Increased mortality was significantly associated with older age, multiple comorbidities, need for ICU support, and elevated levels of D-dimer, lactate dehydrogenase, and lactate in multivariate analysis. Age-adjusted CFRs in patients with cancer compared with noncancer patients at our institution and New York City reported a significant increase in case fatality for patients with cancer. These data suggest the need for proactive strategies to reduce likelihood of infection and improve early identification in this vulnerable patient population.

Significance: COVID-19 in patients with cancer is associated with a significantly increased risk of case fatality, suggesting the need for proactive strategies to reduce likelihood of infection and improve early identification in this vulnerable patient population.

Introduction

The novel coronavirus COVID-19, or severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has spread rapidly throughout the world since its emergence in December 2019 (1). The virus has infected approximately 2.9 million people in more than 200 countries with more than 200,000 deaths at the time of writing (2). Most recently, the United States has become the epicenter of this pandemic, reporting an estimated 956,000 cases of COVID-19 infection, with the largest concentration in New York City (NYC) and its surrounding areas (approximately >203,000 cases or 35% of all U.S. infections; ref. 3).

Early data suggests that 14% to 19% of infected patients will develop significant sequelae with acute respiratory distress syndrome, septic shock, and/or multiorgan failure (1, 4, 5), and approximately 1% to 4% will die from the disease (2). Recent meta-analyses have demonstrated an almost 6-fold increase in the odds of mortality for patients with chronic obstructive pulmonary disease (COPD) and a 2.5-fold increase for those with diabetes, possibly due to the underlying pulmonary and immune dysfunction (6, 7). Given these findings, patients with cancer would ostensibly be at a higher risk of developing and succumbing to COVID-19 due to immunosuppression, increased coexisting medical conditions, and, in cases of lung malignancy, underlying pulmonary compromise. Patients with hematologic cancer, or those who are receiving active chemotherapy or immunotherapy, may be particularly susceptible because of increased immunosuppression and/or dysfunction.

According the NCI, there were approximately 15.5 million cancer survivors and an estimated 1,762,450 new cases of cancer diagnosed in the United States in 2019 (8). Early case series from China and Italy have suggested that patients with malignancy are more susceptible to severe infection and mortality from COVID-19 (9–12), a phenomenon that has been noted in other pandemics (13). Many of these descriptive studies have included small patient cohorts and have lacked cancer site–specific mortality data or information regarding active cancer treatment. As New York has emerged as the current epicenter of the pandemic, we sought to investigate the risk posed by COVID-19 to our cancer population with more granular data regarding cancer type and active treatment, and identify factors that placed patients with cancer at highest risk of fatality from COVID-19.

Results

Outcomes of 218 Cancer Patients with COVID-19 Show High Overall Mortality with Tumor-Specific Patterns

A total of 218 patients with cancer and COVID-19 were treated in Montefiore Health System (New York, NY) from March 18, 2020, to April 8, 2020. These included 164 (75%) patients with solid tumors and 54 (25%) with hematologic malignancies. This cohort included 127 (58%) males and 91 (42%) females. The cohort was predominantly composed of adult patients (215/218, 98.6%) with a median age of 69 years (range 10–92 years).

Sixty-one (28%) patients expired as a result of COVID-19disease at the time of analysis (Table 1). The mortality was 25% among all patients with solid tumors and was seen to occur at higher rates in patients with lung cancers (55%), gastrointestinal (GI) cancers [colorectal (38%), pancreatic (67%), upper GI (38%)], and gynecologic malignancies (38%). Genitourinary (15%) and breast (14%) cancers were associated with relatively lower mortality with COVID-19 infection.

Table 1.

Outcomes in patients with cancer and COVID-19

Hematologic malignancies were associated with higher rate of mortality with COVID-19 (37%). Myeloid malignancies [myelodysplastic syndromes (MDS)/acute myeloid leukemia (AML)/myeloproliferative neoplasm (MPN)] showed a trend for higher mortality compared with lymphoid neoplasms [non-Hodgkin lymphoma (NHL)/chronic lymphoid leukemia (CLL)/acute lymphoblastic leukemia (ALL)/multiple myeloma (MM)/Hodgkin lymphoma; Table 1]. Rates of ICU admission and ventilator use were slightly higher for hematologic malignancies than solid tumors (26% vs. 19% and 11% vs. 10%, respectively), but this did not achieve statistical significance.

Disease Characteristics of Cancer Patients with COVID-19 Demonstrate the Effect of Age, Comorbidities, and Laboratory Biomarkers on Mortality

Analysis of patient characteristics with mortality did not show any gender bias (Table 2). Older age was significantly associated with increased mortality, with median age of deceased cohort at 76 years when compared with 66 years for the nondeceased group (P = 0.0006; Cochran-Armitage test). No significant associations between race and mortality were seen.

Table 2.

Disease characteristics of patients with cancer with COVID-19 and association with mortality

COVID-19 disease severity, as evident from patients who needed ICU care and ventilator support, was significantly associated with increased mortality. Interestingly, active disease (<1 year) and advanced metastatic disease showed a trend for increased mortality, but the association did not achieve statistical significance (P = 0.09 and 0.06, respectively). Active chemotherapy and radiotherapy treatment were not associated with increased case fatality. Very few patients in this cohort were on immunotherapy, and this did not show any associations with mortality.

Analysis of comorbidities demonstrated increased risk of dying from COVID-19 in patients with cancer with concomitant heart disease [hypertension (HTN), coronary artery disease (CAD), and congestive heart failure (CHF)] and chronic lung disease (Table 2). Diabetes and chronic kidney disease were not associated with increased mortality in univariate analysis (Table 2).

We also analyzed laboratory values obtained prior to diagnosis of COVID-19 and during the time of nadir after COVID-19 positivity in our cancer cohort. Relative anemia pre–COVID-19 was associated with increased mortality, whereas pre-COVID platelet and lymphocyte counts were not (Table 3).Post–COVID-19 infection, lower hemoglobin levels, higher total white blood cell (WBC) counts, and higher absolute neutrophil counts were associated with increased mortality (Table 3). Analysis of other serologic biomarkers demonstrated that elevated D-dimer, lactate, and lactate dehydrogenase (LDH) in patients were significantly correlated with dying (Table 3).

Table 3.

Laboratory values of cancer patients with COVID-19 and association with mortality

Next, we conducted multivariate analyses and used variables that showed a significant association with mortality in univariate analysis (P < 0.05 in univariate was seen with age, ICU admission, hypertension, chronic lung disease, CAD, CHF, baseline hemoglobin, nadir hemoglobin, WBC counts, D-dimer, lactate, and LDH). Gender was forced in the model and we used a composite score of comorbidities from the sum of indicators for diabetes mellitus (DM), HTN, chronic lung disease, chronic kidney disease, CAD, and CHF capped at a maximum of 3. In the multivariate model (Supplementary Table S1), we observed that older age [age < 65; OR, 0.23; 95% confidence interval (CI), 0.07–0.6], higher composite comorbidity score (OR, 1.52; 95% CI, 1.02–2.33), ICU admission (OR, 4.83; 95% CI, 1.46–17.15), and elevated inflammatory markers (D-dimer, lactate, and LDH) were significantly associated with mortality after multivariate comparison in patients with cancer and COVID-19.

Interaction with the Healthcare Environment was a Prominent Source of Exposure for Patients with Cancer

A detailed analysis of deceased patients (N = 61; Supplementary Table S2) demonstrated that many were either nursing-home or shelter (n = 22) residents, and/or admitted as an inpatient or presented to the emergency room within the 30 days prior to their COVID-19 positive test (21/61). Altogether, 37/61 (61%) of the deceased cohort were exposed to the healthcare environment at the outset of the COVID-19 epidemic. Few of the patients in the cohort were on active oncologic therapy. The vast majority had a poor Eastern Cooperative Oncology Group performance status (ECOG PS; 51/61 with an ECOG PS of 2 or higher) and carried multiple comorbidities.

Patients with Cancer Demonstrate a Markedly Increased COVID-19 Mortality Rate Compared with Noncancer and All NYC COVID-19 Patients

An age- and sex-matched cohort of 1,090 patients at a 5:1 ratio of noncancer to cancer COVID-19 patients from the same time period and from the same hospital system was also obtained after propensity matching and used as control to estimate the increased risk posed to our cancer population (Table 4). We observed case fatality rates (CFR) were elevated in all age cohorts in patients with cancer and achieved statistical significance in the age groups 45–64 and in patients older than 75 years of age.

Table 4.

Comparison of cancer and COVID-19 mortality with all NYC cases (official NYC numbers up to 5 p.m., April 12, 2020) and a control group from the same healthcare facility

To also compare our CFRs with a larger dataset from the greater NYC region, we obtained official case numbers from New York State (current up to April 12, 2020; ref. 3). In all cohorts, the percentage of deceased patients was found to rise sharply with increasing age (Table 4). Strikingly, CFRs in cancer patients with COVID-19 were significantly, many-fold higher in all age groups when compared with all NYC cases (Table 4).

Discussion

To our knowledge, this is the first large report of COVID-19 CFRs among patients with cancer in the United States. The overall case fatality among COVID-19–infected patients with cancer in an academic center located within the current epicenter of the global pandemic exceeded 25%. In addition, striking tumor-specific discrepancies were seen, with marked increased susceptibility for those with hematologic malignancies and lung cancer. CFRs were 2 to 3 times the age-specific percentages seen in our noncancer population and the greater NYC area for all COVID-19 patients.

Our results seem to mirror the typical prognosis of the various cancer types. Among the most common malignancies within the U.S. population (lung, breast, prostate, and colorectal), there was 55% mortality among patients with lung cancer, 14% for breast cancer, 20% for prostate cancer, and 38% for colorectal cancer. This pattern reflects the overall known lethality of these cancers. The percent annual mortality (ratio of annual deaths/new diagnosis) is 59.3% for lung cancer, 15.2% for breast cancer, 17.4% for prostate cancer, and 36% for colorectal cancer (8). This suggests that COVID-19 infection amplifies the risk of death regardless of the cancer type.

Patients with hematologic malignancies demonstrate a higher mortality than those with solid tumors. These patients tend to be treated with more myelosuppressive therapy, and are often severely immunocompromised because of underlying disease. There is accumulating evidence that one major mechanism of injury may be a cytokine-storm syndrome secondary to hyperinflammation, which results in pulmonary damage. Patients with hematologic malignancy may potentially be more susceptible to cytokine-mediated inflammation due to perturbations in myeloid and lymphocyte cell compartments (14).

Many of the predictive risk factors for mortality in our cancer cohort were similar to published data among all COVID-19 patients. A recent meta-analysis highlighted the association of chronic diseases including hypertension (OR, 2.29), diabetes (OR, 2.47), COPD (OR, 5.97), cardiovascular disease (OR, 2.93), and cerebrovascular disease (OR, 3.89) with a risk for developing severe COVID-19 infection among all patients (15). In our cancer patient dataset, a large proportion of patients had at least one of these concurrent risk factors. In a univariate model, we observed significant associations of death from COVID-19 infection in patients with hypertension, chronic lung disease, coronary heart disease, and congestive heart failure. Serologic predictors in our dataset predictive for mortality included anemia at time of infection, and elevated LDH, D-dimer, and lactic acid, which correlate with available data from all COVID-19 patients.

Rapidly accumulating reports suggest that age and race may play a role in the severity of COVID-19 infection. In our cancer cohort, the median age of the patients succumbing to COVID-19 was 76 years, which was 10 years older than patients who have remained alive. The CDC has reported a disproportionate number of African Americans are affected by COVID-19 in the United States, accounting for 33% of all hospitalized patients while constituting only 13% of the U.S. population (15). However, the racial breakdown of our patients was proportional to the Bronx population as a whole, and race was not a significant predictor of mortality in our univariate or multivariate models. Our data might argue that the increased mortality noted in the larger NYC populations might also likely be driven by socioeconomic and health disparities in addition to underlying biological factors. Overall mortality with COVID-19 has been higher in the Bronx, which is a socioeconomically disadvantaged community with a mean per capita income of $19,721 (16, 17). Our patients with cancer were predominantly from the Bronx and potentially had increased mortality in part due to socioeconomic factors and comorbidities. Even after accounting for the increased mortality seen in COVID-19 in the Bronx, the many-fold magnitude increase in death rates within our cancer cohort can potentially be attributed to the vulnerability of oncology patients. This was evident in the comparison with a control group from the same hospital system that demonstrated a significant association of cancer with mortality in patients between 45 and 64 years of age and older than 75 years of age.

Interaction with the healthcare environment prior to widespread knowledge of the epidemic within NYC was a prominent source of exposure for our patients with cancer. Many of those who succumbed to COVID-19 infection were older and frail with significant impairment of pulmonary and/or immunologic function. These findings could be utilized to risk-stratify patients with cancer during this pandemic, or in future viral airborne outbreaks, and inform mitigation practices for high-risk individuals. These strategies could include early and aggressive social distancing, resource allocation toward more outpatient-based care and telemedicine, testing of asymptomatic high-risk patients, and institution of strict infection-control measures. Indeed, such strategies were implemented early in the pandemic at our center, possibly explaining the relatively low number of infected patients on active therapy.

There were several limitations to our study. Data regarding do not resuscitate or intubate orders were not included in the analysis and could have significantly affected the decision-making and mortality surrounding these patients. Although an attempt was made to control for those receiving active cancer treatment or with additional comorbidities, we could not fully account for the patients’ preexisting health conditions prior to COVID-19 infection. Differential treatment paradigms for COVID-19 infection and sequelae were not controlled for in our analysis. Because of the limited follow-up, the full clinical course of these patients may not be included. Future comparative studies to noncancer patients will be needed to fully ascertain the risk posed to oncology patients. Finally, though our data does include those who were tested and discharged within our health system, we cannot fully account for those who were tested in nonaffiliated outpatient settings, which may potentially bias our study to more severe cases. We also acknowledge that the mortality rate is highly dependent on the breadth of testing, and therefore understand that more widespread detection of viral infection would likely alter the results.

Our data suggest significant risk posed to patients with cancer infected with COVID-19, with an observed significant increase in mortality. The highest susceptibility appears to be in hematologic or lung malignancies, suggesting that proactive strategies to reduce likelihood of infection and improve early identification of COVID-19 positivity in the cancer patient population are clearly warranted. Overall, we hope and expect that our data from the current epicenter of the COVID-19 epidemic will help inform other healthcare systems, patients with cancer, and the public about the particular vulnerability of patients with cancer to this disease.

For more Articles on COVID-19 please see our Coronavirus Portal at

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Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Session on Early Detection and ctDNA 1:35 – 3:55 PM

Reporter: Stephen J. Williams, PhD

Introduction
Alberto Bardelli

  • circulating tumor DNA has been around but with NGS now we can have more specificity in analyzing ctDNA
  • interest lately in using liquid biopsy to gain insight on tumor heterogeneity versus single needle biopsy of the solid tumor
  • these talks will however be on ctDNA as a diagnostic and therapeutic monitoring modality

Prediction of cancer and tissue of origin in individuals with suspicion of cancer using a cell-free DNA multi-cancer early detection test
David Thiel 

@MayoClinic

  • test has a specificity over 90% and intended to used along with guideline
  • The Circulating  Cell-free Genome Atlas Study (clinical trial NCT02889978) (CCGA) study divided into three substudies: highest performing assay, refining assay, validation of assays
  • methylation based assays worked better than sequencing (bisulfite sequencing)
  • used a machine learning algorithm to help refine assay
  • prediction was >90%; subgroup for high clinical suspicion of cancer
  • HCS sensitivity was 100% and specificity very high; but sensitivity on training set was 40% and results may have been confounded by including kidney cancer
  • TOO tissue of origin was predicted in greater than 99% in both training and validation sets

A first-of-its-kind prospective study of a multi-cancer blood test to screen and manage 10,000 women with no history of cancer

  • DETECT-A study: prospective interventional study; can multi blood test be used prospectively and can lead to a personalized care; can the screen be used to complement current therapy?
  • 10,000 women aged 65-75;  these women could not have previous cancer and conducted through Geisinger Health Network; multi test detects DNA and protein and standard of care screening
  • the study focused on safety so a committee was consulted on each case, and used a diagnostic PET-CT
  • blood test alone not good but combined with protein and CT scans much higher (5 fold increase) detection for breast cancer

Nickolas Papadopoulos

@HopkinsMedicine

Discussant
David Huntsman

  • there are mutiple opportunities yet at same time there are still challenges to utilize these cell free tests in therapeutic monitoring, diagnostic, and screening however sensitivities for some cancers are still too low to use in large scale screening however can supplement current screening guidelines
  • we have to ask about false positive rate and need to concentrate on prospective studies
  • we must consider how tests will be used, population health studies will need to show improved survival

 

Phylogenetic tracking and minimal residual disease detection using ctDNA in early-stage NSCLC: A lung TRACERx study
Chris Abbosh @ucl

  • TRACERx study in collaboration with Charles Swanton.
  • multiplex PCR to track 200 SNVs: correlate tumor tissue biopsy with ctDNA
  • spike in assay shows very good sensitivity and specificity for SNVs variants tracked, did over 400 TRACERx libraries
  • sensitivity increases when tracking more variants but specificity does go down a bit
  • tracking variants can show evidence of subclonal dynamics and evolution and copy number deletion events;  they also show neoantigen editing or changing of their neoantigens
  • this assay can detect low variants in a reproducible manner

The TRACERx (TRAcking Cancer Evolution through therapy (Rx)) lung study is a multi-million pound research project taking place over nine years, which will transform our understanding of non-small cell lung cancer (NSCLC) and take a practical step towards an era of precision medicine. The study will uncover mechanisms of cancer evolution by analysing the intratumour heterogeneity in lung tumours from approximately 850 patients and tracking its evolutionary trajectory from diagnosis through to relapse. At £14 million, it’s the biggest single investment in lung cancer research by Cancer Research UK, and the start of a strategic UK-wide focus on the disease, aimed at making real progress for patients.

Led by Professor Charles Swanton at UCL, the study will bring together a network of experts from different disciplines to help integrate clinical and genomic data and identify patients who could benefit from trials of new, targeted treatments. In addition, it will use a whole suite of cutting edge analytical techniques on these patients’ tumour samples, giving unprecedented insight into the genomic landscape of primary and metastatic tumours and the impact of treatment upon this landscape.

In future, TRACERx will enable us to define how intratumour heterogeneity impacts upon cancer immunity throughout tumour evolution and therapy. Such studies will help define how the clinical evaluation of intratumour heterogeneity can inform patient stratification and the development of combinatorial therapies incorporating conventional, targeted and immune based therapeutics.

Intratumour heterogeneity is increasingly recognised as a major hurdle to achieve improvements in therapeutic outcome and biomarker validation. Intratumour genetic diversity provides a substrate for tumour adaptation and evolution. However, the evolutionary genomic landscape of non-small cell lung cancer (NSCLC) and how it changes through the disease course has not been studied in detail. TRACERx is a prospective observational study with the following objectives:

Primary Objectives

  • Define the relationship between intratumour heterogeneity and clinical outcome following surgery and adjuvant therapy (including relationships between intratumour heterogeneity and clinical disease stage and histological subtypes of NSCLC).
  • Establish the impact of adjuvant platinum-containing regimens upon intratumour heterogeneity in relapsed disease compared to primary resected tumour.

Key Secondary Objectives

  • Develop and validate an intratumour heterogeneity (ITH) ratio index as a prognostic and predictive biomarker in relation to disease-free survival and overall survival.
  • Infer a complete picture of NSCLC evolutionary dynamics – define drivers of genomic instability, metastatic progression and drug resistance by identifying and tracking the dynamics of somatic mutational heterogeneity, and chromosomal structural and numerical instability present in the primary tumour and at metastatic sites. Individual tumour phylogenetic tree analysis will:
    • Establish the order of somatic events in relation to genomic instability onset and metastatic progression
    • Decipher genetic “bottlenecking” events following metastasis and drug therapy
    • Establish dynamics of tumour evolution during the disease course from early to late stage NSCLC.
  • Initiate a longitudinal biobank of circulating tumour cells (CTCs) and circulating-free tumour DNA (cfDNA) to develop analytical methods for the early detection and monitoring of tumour evolution over time.
  • Develop a longitudinal tissue resource to serve as a platform to assess the relationship between genetic intratumour heterogeneity and the host immune response.
  • Define relationships between intratumour heterogeneity and targeted/cytotoxic therapeutic outcome.
  • Use a lung cancer specific gene panel in a certified Good Clinical Practice (GCP) laboratory environment to define clonally dominant disease drivers to address the role of clonal driver dominance in targeted therapeutic response and to guide stratification of lung cancer treatment and future clinical study inclusion (paired primary-metastatic site comparisons in at least 270 patients with relapsed disease).

 

 

Utility of longitudinal circulating tumor DNA (ctDNA) modeling to predict RECIST-defined progression in first-line patients with epidermal growth factor receptor mutation-positive (EGFRm) advanced non-small cell lung cancer (NSCLC)
Martin Johnson

 

Impact of the EML4-ALK fusion variant on the efficacy of lorlatinib in patients (pts) with ALK-positive advanced non-small cell lung cancer (NSCLC)
Todd Bauer

 

From an interview with Dr. Bauer at https://www.lungcancernews.org/2019/08/14/making-headway-with-lorlatinib/

Lorlatinib, a smallmolecule inhibitor of ALK and ROS1, was granted accelerated U.S. Food and Drug Administration approval in November 2018 for patients with ALK-positive metastatic NSCLC whose disease has progressed on crizotinib and at least one other ALK inhibitor or whose disease has progressed on alectinib or ceritinib as the first ALK inhibitor therapy for metastatic disease. Todd M. Bauer, MD, a medical oncologist and senior investigator at Sarah Cannon Research Institute/Tennessee Oncology, PLLC, in Nashville, has been very involved with the development of lorlatinib since the beginning. In the following interview, Dr. Bauer discusses some of lorlatinib’s unique toxicities, as well as his first-hand experiences with the drug.

For further reading: Solomon B, Besse B, Bauer T, et al. Lorlatinib in Patients with ALK-positive non-small-cell lung cancer: results from a global phase 2 study. Lancet. 2018;19(12):P1654-1667.

Abstract

BACKGROUND: Lorlatinib is a potent, brain-penetrant, third-generation inhibitor of ALK and ROS1 tyrosine kinases with broad coverage of ALK mutations. In a phase 1 study, activity was seen in patients with ALK-positive non-small-cell lung cancer, most of whom had CNS metastases and progression after ALK-directed therapy. We aimed to analyse the overall and intracranial antitumour activity of lorlatinib in patients with ALK-positive, advanced non-small-cell lung cancer.

METHODS: In this phase 2 study, patients with histologically or cytologically ALK-positive or ROS1-positive, advanced, non-small-cell lung cancer, with or without CNS metastases, with an Eastern Cooperative Oncology Group performance status of 0, 1, or 2, and adequate end-organ function were eligible. Patients were enrolled into six different expansion cohorts (EXP1-6) on the basis of ALK and ROS1 status and previous therapy, and were given lorlatinib 100 mg orally once daily continuously in 21-day cycles. The primary endpoint was overall and intracranial tumour response by independent central review, assessed in pooled subgroups of ALK-positive patients. Analyses of activity and safety were based on the safety analysis set (ie, all patients who received at least one dose of lorlatinib) as assessed by independent central review. Patients with measurable CNS metastases at baseline by independent central review were included in the intracranial activity analyses. In this report, we present lorlatinib activity data for the ALK-positive patients (EXP1-5 only), and safety data for all treated patients (EXP1-6). This study is ongoing and is registered with ClinicalTrials.gov, number NCT01970865.

FINDINGS: Between Sept 15, 2015, and Oct 3, 2016, 276 patients were enrolled: 30 who were ALK positive and treatment naive (EXP1); 59 who were ALK positive and received previous crizotinib without (n=27; EXP2) or with (n=32; EXP3A) previous chemotherapy; 28 who were ALK positive and received one previous non-crizotinib ALK tyrosine kinase inhibitor, with or without chemotherapy (EXP3B); 112 who were ALK positive with two (n=66; EXP4) or three (n=46; EXP5) previous ALK tyrosine kinase inhibitors with or without chemotherapy; and 47 who were ROS1 positive with any previous treatment (EXP6). One patient in EXP4 died before receiving lorlatinib and was excluded from the safety analysis set. In treatment-naive patients (EXP1), an objective response was achieved in 27 (90·0%; 95% CI 73·5-97·9) of 30 patients. Three patients in EXP1 had measurable baseline CNS lesions per independent central review, and objective intracranial responses were observed in two (66·7%; 95% CI 9·4-99·2). In ALK-positive patients with at least one previous ALK tyrosine kinase inhibitor (EXP2-5), objective responses were achieved in 93 (47·0%; 39·9-54·2) of 198 patients and objective intracranial response in those with measurable baseline CNS lesions in 51 (63·0%; 51·5-73·4) of 81 patients. Objective response was achieved in 41 (69·5%; 95% CI 56·1-80·8) of 59 patients who had only received previous crizotinib (EXP2-3A), nine (32·1%; 15·9-52·4) of 28 patients with one previous non-crizotinib ALK tyrosine kinase inhibitor (EXP3B), and 43 (38·7%; 29·6-48·5) of 111 patients with two or more previous ALK tyrosine kinase inhibitors (EXP4-5). Objective intracranial response was achieved in 20 (87·0%; 95% CI 66·4-97·2) of 23 patients with measurable baseline CNS lesions in EXP2-3A, five (55·6%; 21·2-86·3) of nine patients in EXP3B, and 26 (53·1%; 38·3-67·5) of 49 patients in EXP4-5. The most common treatment-related adverse events across all patients were hypercholesterolaemia (224 [81%] of 275 patients overall and 43 [16%] grade 3-4) and hypertriglyceridaemia (166 [60%] overall and 43 [16%] grade 3-4). Serious treatment-related adverse events occurred in 19 (7%) of 275 patients and seven patients (3%) permanently discontinued treatment because of treatment-related adverse events. No treatment-related deaths were reported.

INTERPRETATION: Consistent with its broad ALK mutational coverage and CNS penetration, lorlatinib showed substantial overall and intracranial activity both in treatment-naive patients with ALK-positive non-small-cell lung cancer, and in those who had progressed on crizotinib, second-generation ALK tyrosine kinase inhibitors, or after up to three previous ALK tyrosine kinase inhibitors. Thus, lorlatinib could represent an effective treatment option for patients with ALK-positive non-small-cell lung cancer in first-line or subsequent therapy.

  • loratinib could be used for crizotanib resistant tumors based on EML4-ALK variants present in ctDNA

Reference:
1. Updated efficacy and safety data from the global phase III ALEX study of alectinib (ALC) vs crizotinib (CZ) in untreated advanced ALK+ NSCLCJ Clin Oncol 36, 2018 (suppl; abstr 9043).

Discussion

Corey Langer

 

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Google AI improves accuracy of reading mammograms, study finds

Reporter: Stephen J. Williams, PhD

Updated on 12/7/2022

AI system beats doctors at scrutinizing breast cancer scans

AI learned to identify a protein targeted in immunotherapy in a process that could make doctors’ work faster, simpler and more precise.

SOURCE

https://www.israel21c.org/ai-system-beats-doctors-at-scrutinizing-breast-cancer-scans/

 

Google AI improves accuracy of reading mammograms, study finds

Google CFO Ruth Porat has blogged about twice battling breast cancer.

Artificial intelligence was often more accurate than radiologists in detecting breast cancer from mammograms in a study conducted by researchers using Google AI technology.

The study, published in the journal Nature, used mammograms from approximately 90,000 women in which the outcomes were known to train technology from Alphabet Inc’s DeepMind AI unit, now part of Google Health, Yahoo news reported.

The AI system was then used to analyze images from 28,000 other women and often diagnosed early cancers more accurately than the radiologists who originally interpreted the mammograms.

In another test, AI outperformed six radiologists in reading 500 mammograms. However, while the AI system found cancers the humans missed, it also failed to find cancers flagged by all six radiologists, reports The New York Times.

The researchers said the study “paves the way” for further clinical trials.

Writing in NatureEtta D. Pisano, chief research officer at the American College of Radiology and professor in residence at Harvard Medical School, noted, “The real world is more complicated and potentially more diverse than the type of controlled research environment reported in this study.”

Ruth Porat, senior vice president and chief financial officer Alphabet, Inc., wrote in a company blog titled “Breast cancer and tech…a reason for optimism” in October about twice battling the disease herself, and the importance of her company’s application of AI to healthcare innovations.

She said that focus had already led to the development of a deep learning algorithm to help pathologists assess tissue associated with metastatic breast cancer.

“By pinpointing the location of the cancer more accurately, quickly and at a lower cost, care providers might be able to deliver better treatment for more patients,” she wrote.

Google also has created algorithms that help medical professionals diagnose lung cancer, and eye disease in people with diabetes, per the Times.

Porat acknowledged that Google’s research showed the best results occur when medical professionals and technology work together.

Any insights provided by AI must be “paired with human intelligence and placed in the hands of skilled researchers, surgeons, oncologists, radiologists and others,” she said.

Anne Stych is a staff writer for Bizwomen.
Industries:

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False-Positive Mammogram Results May Be Linked to Higher Risk Later in Life

While screening mammograms aren’t perfect, they are the best way we have right now to detect breast cancer early, when it’s most treatable.

When a screening mammogram shows an abnormal area that looks like a cancer but turns out to be normal, it’s called a false positive. Ultimately the news is good: no breast cancer. But the suspicious area usually requires follow-up with more than one doctor, extra tests, and extra procedures, including a possible biopsy.

A large study suggests that women with false-positive mammogram results have a slightly higher risk of developing invasive breast cancer within the next 10 years.

The research was published online on Dec. 2, 2015 by the journal Cancer Epidemiology, Biomarkers & Prevention. Read the abstract of “Increased Risk of Developing Breast Cancer after a False-Positive Screening Mammogram.”

To do the study, the researchers looked at information from nearly 1.3 million women ages 40 to 70 with no family history of breast cancer who had screening mammograms from 1994 to 2009. The information came from the Breast Cancer Surveillance Consortium database, which is maintained by the National Cancer Institute.

The researchers found that the 1,297,906 women had a total of 2,207,942 screening mammograms. There were:

  • 159,448 false-positive results with a recommendation for more imaging
  • 22,892 false-positive results with a recommendation for biopsy
  • 2,025,602 negative mammograms

Women ages 40 to 49 made up the largest percentage of false-positive mammogram results with a recommendation for more imaging (33.1%). Women with dense breasts also were more likely to have false-positive results.

The researchers then compared the rates of invasive breast cancer between women who had false-positive mammogram results and women who had negative mammogram results:

  • there were 3.91 invasive breast cancers per 1,000 person-years of follow-up among women with negative mammogram results
  • there were 5.51 invasive breast cancers per 1,000 person-years of follow-up among women with false-positive mammogram results with a recommendation for more imaging
  • there were 7.01 invasive breast cancers per 1,000 person-years of follow-up among women with false-positive mammogram results with a recommendation for biopsy

The researchers said the 10-year risk of invasive breast cancer was:

  • 39% higher in women with false-positive results with a recommendation for more imaging
  • 76% higher in women with false-positive results with a recommendation for biopsy

compared to women with negative results.

It’s important to know that the increases above are increases in relative risk — the risk of a woman with a false-positive result relative to the risk of a woman with a negative result.

In terms of absolute risk, the increase is small:

  • women with false-positive results have about a 2% risk of developing invasive disease in the 10 years after the false-positive result
  • women with negative results have about a 1% risk of developing invasive disease in the 10 years after the negative result

The researchers didn’t offer an explanation about why false-positive mammogram results appear to be linked to a slightly higher risk of invasive disease. Many experts think that the subtle changes suggested on the mammogram may be an early clue to cancer before actual cancer exists.

It’s also important to know that this association has been suggested in other studies. But the large number of women in the study and the length of follow-up add more evidence that the link between false-positive results and a somewhat higher risk of invasive disease actually exists.

“The power of this study to show the association is very strong, particularly when you combine it with the results of the other studies that have been done,” said Richard Wender, M.D., chief of cancer control at the American Cancer Society, in an interview. “I think we can now say with confidence that women who have had a previous false-positive mammogram are at somewhat higher risk for breast cancer.”

The researchers who did this study want to incorporate false-positive mammogram results into models that predict breast cancer risk.

“Now that we have this information, our hope is that we can add it into existing risk-prediction models to improve their ability to discriminate between women who will go on to develop breast cancer and those who won’t,” said Louise Henderson, Ph.D., of the University of North Carolina Lineberger Comprehensive Cancer Center, who was the lead author of the study. “We should accept that a false-positive mammogram is a risk factor for predicting future risk of breast cancer.

“In clinical terms, that means women who have a false-positive mammogram need to be particularly vigilant about keeping up with regular mammographic screening,” she continued. “The clinicians caring for these women should have a way to track women who have had a false-positive and make sure that every effort is made to keep up to date with mammography.”

It’s important to know that a false-positive mammogram result doesn’t mean you will be diagnosed with breast cancer.

“Having any history of breast biopsies is associated with a higher risk,” said Breastcancer.org President and Founder Marisa Weiss, M.D. “Breast tissue that is dense or has proliferative changes tends to lead to questions on the breast imaging. Sometimes it leads to biopsies. In contrast, breast tissue that is boring, without any extra activity, rarely leads to any kind of biopsy. That kind of inactive breast tissue is less likely to develop breast cancer.”

“This study doesn’t suggest that having a false-positive leads to breast cancer,” said Brian Wojciechowski, M.D., Breastcancer.org’s medical adviser. “Rather, it reflects an association between breast cancer risk and abnormal breast imaging. Women should not worry that getting mammograms will increase their risk of breast cancer in the future.”

There’s only one of you and you deserve the best care possible. Don’t let any obstacles get in the way of your regular screening mammograms, especially if you’ve had a false-positive result.

  • If you’re worried about cost, talk to your doctor, a local hospital social worker, or staff members at a mammogram center. Ask about free programs in your area.
  • If you’re having problems scheduling a mammogram, call the National Cancer Institute (800-4-CANCER) or the American College of Radiology (800-227-5463) to find certified mammogram providers near you.
  • If you find mammograms painful, ask the mammography center staff members how the experience can be as easy and as comfortable as possible for you.
  • If you’re concerned about unknown results or being called back for more testing, talk to your doctor about what happens when mammogram results are unclear, as well as what to expect if you’re called back for more testing.

For more information on mammograms and other tests to detect and diagnose breast cancer, visit the Breastcancer.org Screening and Testing section.


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Recent comprehensive review on the role of ultrasound in breast cancer management

Writer, reporter and curator: Dror Nir, PhD

Breast Cancer Imaging

Word Cloud Created by Noam Steiner Tomer 8/10/2020

The paper below by R Hooley is a beautifully written review on how ultrasound could (and should) be practiced to better support breast cancer screening, staging, and treatment. The authors went as well into the effort of describing the benefits from combining ultrasonography with the other frequently used imaging modalities; i.e. mammography, tomosynthesis and MRI. Post treatment use of ultrasound is not discussed although this is a major task for this modality.

I would like to recommend giving attention to two very small (but for me very important) paragraphs: “Speed of Sound Imaging” and “Lesion Annotation”

Enjoy…

Breast Ultrasonography: State of the Art

Regina J. Hooley, MDLeslie M. Scoutt, MD and Liane E. Philpotts, MD

Department of Diagnostic Radiology, Yale University School of Medicine, 333 Cedar St, PO Box 208042, New Haven, CT 06520-8042.

Address correspondence to R.J.H. (e-mail: regina.hooley@yale.edu).

Ultrasonography (US) has become an indispensable tool in breast imaging. Breast US was first introduced in the 1950s by using radar techniques adapted from the U.S. Navy (1). Over the next several decades, US in breast imaging was primarily used to distinguish cystic from solid masses. This was clinically important, as a simple breast cyst is a benign finding that does not require further work-up. However, most solid breast lesions remained indeterminate and required biopsy, as US was not adequately specific in differentiating benign from malignant solid breast masses. However, recent advances in US technology have allowed improved characterization of solid masses.

In 1995, Stavros et al (2) published a landmark study demonstrating that solid breast lesions could be confidently characterized as benign or malignant by using high-resolution grays-cale US imaging. Benign US features include few (two or three) gentle lobulations, ellipsoid shape, and a thin capsule, as well as a homogeneously echogenic echotexture. Malignant US features include spiculation, taller-than-wide orientation, angular margins, microcalcifications, and posterior acoustic shadowing. With these sonographic features, a negative predictive value of 99.5% and a sensitivity of 98.4% for the diagnosis of malignancy were achieved. These results have subsequently been validated by others (3,4) and remain the cornerstone of US characterization of breast lesions today. These features are essential in the comprehensive US assessment of breast lesions, described by the Breast Imaging and Reporting Data System (BI-RADS) (5).

US is both an adjunct and a complement to mammography. Advances in US technology include harmonic imaging, compound imaging, power Doppler, faster frame rates, higher resolution transducers, and, more recently, elastography and three-dimensional (3D) US. Currently accepted clinical indications include evaluation of palpable abnormalities and characterization of masses detected at mammography and magnetic resonance (MR) imaging. US may also be used as an adjuvant breast cancer screening modality in women with dense breast tissue and a negative mammogram. These applications of breast US have broadened the spectrum of sonographic features currently assessed, even allowing detection of noninvasive disease, a huge advance beyond the early simplistic cyst-versus-solid assessment. In addition, US is currently the primary imaging modality recommended to guide interventional breast procedures.

The most subtle US features of breast cancers are likely to be best detected by physicians who routinely synthesize findings from multiple imaging modalities and clinical information, as well as perform targeted US to correlate with lesions detected at mammography or MR imaging. Having a strong understanding of the technical applications of US and image optimization, in addition to strong interpretive and interventional US skills, is essential for today’s breast imager.

 

Optimal Imaging Technique

US is operator dependent, and meticulous attention to scanning technique as well as knowledge of the various technical options available are imperative for an optimized and accurate breast US examination. US is an interactive, dynamic modality. Although breast US scanning may be performed by a sonographer or mammography technologist, the radiologist also benefits greatly from hands-on scanning (Fig 1). Berg et al (6) demonstrated that US interpretive performance was improved if the radiologist had direct experience performing breast US scanning, including rescanning after the technologist. Real-time scanning also provides the opportunity for thorough evaluation of lesions and permits detailed lesion analysis compared with analyzing static images on a workstation. Subtle irregular or indistinct margins, artifacts, and architectural distortions may be difficult to capture on static images. Real-time scanning also allows the operator to assess lesion mobility, location, and relationship to adjacent structures and allows direct assessment of palpable lesions and other clinical findings. Moreover, careful review of any prior imaging studies is imperative to ensure accurate lesion correlation.

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The US examination is generally well tolerated by the patient. Gentle but firm transducer pressure and optimal patient positioning are essential, with the patient’s arm relaxed and flexed behind the head. Medial lesions should generally be scanned in the supine position, and lateral lesions, including the axilla, should usually be scanned with the patient in the contralateral oblique position. This allows for elimination of potential artifact secondary to inadequate compression of breast tissue.

 

Gray-Scale Imaging

Typical US transducers used in breast imaging today have between 192 and 256 elements along the long axis. When scanning the breast, a linear 12–5-MHz transducer is commonly used. However, in small-breasted women (with breast thickness < 3 cm) or when performing targeted US to evaluate a superficial lesion, a linear 17–5-MHz transducer may be used. Such high-frequency transducers provide superb spatial and soft-tissue resolution, permitting substantially improved differentiation of subtle shades of gray, margin resolution, and lesion conspicuity in the background of normal breast tissue (Fig 2). However, the cost of such a high insonating frequency is decreased penetration due to attenuation of the ultrasound beam, making visualization of deep posterior tissue difficult (ie, greater than 3 cm in depth by using a linear 17–5-MHz transducer or greater than 5 cm in depth by using a linear 12–5-MHz transducer).

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During the initial US survey of the region of interest in the breast, the depth should be set so that the pectoralis muscle is visualized along the posterior margin of the field of view. Initial gain settings should be adjusted so that fat at all levels is displayed as a midlevel gray. Simple cysts are anechoic. Compared with breast fat, most solid masses are hypoechoic, while the skin, Cooper ligaments, and fibrous tissue are echogenic. Time gain compensation, which adjusts image brightness at different depths from the skin to compensate for attenuation of the ultrasound beam as it penetrates into the breast tissue, may be set manually or, with appropriate equipment, may be adjusted automatically during real-time scanning or even during postprocessing of the image.

When searching for a lesion initially identified at mammography or MR imaging, careful correlation with lesion depth and surrounding anatomic structures is imperative. Lesion location may be affected by the patient’s position, which differs during mammography, US, and MR imaging examinations. Attention to surrounding background tissue may assist in accurate lesion correlation across multiple modalities. If a mass identified at mammography or MR imaging is surrounded entirely by fat or fibroglandular tissue, at US it should also be surrounded by hypoechoic fat or echogenic fibroglandular tissue, respectively. Similarly, careful attention to the region of clinical concern is necessary when scanning a palpable abnormality to ensure that the correct area is scanned. The examiner should place a finger on the palpable abnormality and then place the transducer directly over the region. Occasionally, the US examination may be performed in the sitting position if a breast mass can only be palpated when the patient is upright.

After a lesion is identified, or while searching for a subtle finding, the depth or field of view may be adjusted as needed. The depth should be decreased to better visualize more superficial structures or increased to better visualize deeper posterior lesions. The use of multiple focal zones also improves resolution at multiple depths simultaneously and should be used, if available. Although this reduces the frame rate, the reduction is typically negligible when scanning relatively superficial structures within the breast. If a single focal zone is selected to better evaluate a single lesion, the focal zone should be centered at the same level as the area of interest or minimally posterior to the area of interest, for optimal visualization.

 

Spatial Compounding, Speckle Reduction, and Harmonic Imaging

Spatial compound imaging and speckle reduction are available on most high-end US units and should be routinely utilized throughout the breast US examination. Unlike standard US imaging, in which ultrasound pulses are transmitted in a single direction perpendicular to the long axis of the transducer, spatial compounding utilizes electronic beam steering to acquire multiple images obtained from different angles within the plane of imaging (79). A single composite image is then obtained in real-time by averaging frames obtained by ultrasound beams acquired from these multiple angles (10). Artifactual echoes, including speckle and other spurious noise, as well as posterior acoustic patterns, including posterior enhancement (characteristic of simple cysts) and posterior acoustic shadowing (characteristic of some solid masses), are substantially reduced. However, returning echoes from real structures are enhanced, providing improved contrast resolution (9) so that ligaments, edge definition, and lesion margins, including spiculations, echogenic halos, posterior and lateral borders, as well as microcalcifications, are better defined. Speckle reduction is a real-time postprocessing technique that also enhances contrast resolution, improves border definition, is complementary to spatial compounding, and can be used simultaneously.

When a lesion is identified, harmonic imaging may also be applied—usually along with spatial compounding—to better characterize a cyst or a subtle solid mass. The simultaneous use of spatial compounding and harmonic imaging may decrease the frame rate, although this usually does not impair real-time evaluation. Harmonic imaging relies on filtering the multiple higher harmonic frequencies, which are multiples of the fundamental frequencies. All tissue is essentially nonlinear to sound propagation and the ultrasound pulse is distorted as it travels through breast tissue, creating harmonic frequencies (9). The returning ultrasound signal therefore contains both the original fundamental frequency and its multiples, or harmonics. Harmonic imaging allows the higher harmonic frequencies to be selected and used to create the gray-scale images (89). Lower-frequency superficial reverberation echoes are thereby reduced, allowing improved characterization of simple cysts (particularly if small) through the elimination of artifactual internal echoes often seen in fluid. Harmonic imaging also improves lateral resolution (10) and may also improve contrast between fatty tissue and subtle lesions, allowing better definition of subtle lesion margins and posterior shadowing (Fig 3).

 

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Speed of Sound Imaging

Conventional US systems set the speed of sound in tissue at a uniform 1540 m/sec (10). However, the speed of sound in tissues of different composition is variable and this variability may compromise US image quality. Breast tissue usually contains fat, and the speed of sound in fat, of approximately 1430–1470 m/sec, is slower than the assumed standard (11). Accurate speed of sound imaging, in which the US transducer may be optimized for the presence of fat within breast tissue, has been shown to improve lateral resolution (12). Additionally, it can be used to better characterize tissue interfaces, lesion margins, and microcalcifications (13) and may also be useful to identify subtle hypoechoic lesions surrounded by fatty breast tissue. Speed of sound imaging is available on most high-end modern US units and is an optional adjustment, depending on whether predominately fatty, predominately dense, or mixed breast tissue is being scanned.

 

 Lesion Annotation

When a mass is identified and the US settings are optimized, the mass should be scanned with US “sweeps” through the entire lesion in multiple planes. Images of the lesion in the radial and antiradial views should be captured and annotated with “right” or “left,” clock face position, and centimeters from the nipple. Radial and anti-radial scanning planes are preferred over standard transverse and sagittal scanning planes because scanning the breast along the normal axis of the mammary ducts and lobar tissues allows improved understanding of the site of lesion origin and better visualization of ductal extension and helps narrow the differential diagnosis (14). Images should be captured with and without calipers to allow margin assessment on static images. Lesion size should be measured in three dimensions, reporting the longest horizontal diameter first, followed by the anteroposterior diameter, then the orthogonal horizontal.

 

 Extended-Field-of-View Imaging

Advanced US technology permits extended-field-of-view imaging beyond the footprint of the transducer. By using a freehand technique, the operator slides the transducer along the desired region to be imaged. The resultant images are stored in real-time and, by applying pattern recognition, a single large-field-of-view image is obtained (7). This can be helpful in measuring very large lesions as well as the distance between multiple structures in the breast and for assessing the relationship of multifocal disease (located in the same quadrant as the index cancer or within 4–5 cm of the index cancer, along the same duct system) and/or multicentric disease (located in a different quadrant than the index cancer, or at a distance greater than 4–5 cm, along a different duct system).

 

 Doppler US

Early studies investigating the use of color, power, and quantitative spectral Doppler US in the breast reported that the presence of increased vascularity, as well as changes in the pulsatility and resistive indexes, showed that these Doppler findings could be used to reliably characterize malignant lesions (15,16). However, other investigators have demonstrated substantial overlap of many of these Doppler characteristics in both benign and malignant breast lesions (17). Gokalp et al (18) also demonstrated that the addition of power Doppler US and spectral analysis to BI-RADS US features of solid breast masses did not improve specificity. While the current BI-RADS US lexicon recommends evaluation of lesion vascularity, it is not considered mandatory (5).

Power Doppler is generally more sensitive than color Doppler to low-flow volumes typical of breast lesions. Light transducer pressure is necessary to prevent occlusion of slow flow owing to compression of the vessel lumen. Currently both power and color Doppler are complementary tools to gray-scale imaging, and power Doppler may improve sensitivity in detecting malignant breast lesions (18,19). Demonstration of irregular branching central or penetrating vascularity within a solid mass raises suspicion of malignant neovascularity (20). Recently, the parallel artery and vein sign has been described as a reliable feature that has the potential to enable prediction of benignity in solid masses so that biopsy may be avoided. In a single study, a paired artery and vein was present in 13.2% of over 1000 masses at US-guided CNB and although an infrequent finding, the specificity for benignity was 99.3% and the false-negative rate was only 1.4%, with two malignancies among 142 masses in which the parallel artery and vein sign was identified (21).

Color and power Doppler US are also useful to evaluate cysts and complex cystic masses that contain a solid component. High-grade invasive cancer and metastatic lymph nodes may occasionally appear anechoic. Demonstration of flow within an otherwise simple appearing cyst, a complicated cyst, or a complex mass confirms the presence of a suspicious solid component, which requires biopsy. In addition, twinkle artifact seen with color Doppler US is useful to identify a biopsy marker clip or subtle echogenic microcalcifications (Fig 4). This Doppler color artifact occurs secondary to the presence of a strong reflecting granular surface and results in a rapidly changing mix of color adjacent to and behind the reflector (22). Care must be taken to avoid mistaking twinkle artifact for true vascular flow and, if in doubt, a spectral Doppler tracing can be obtained, as a normal vascular waveform will not be seen with a twinkle artifact.

 

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Elastography

At physical examination, it has long been recognized that malignant tumors tend to feel hard when compared with benign lesions. US elastography can be used to measure tissue stiffness with the potential to improve specificity in the diagnosis of breast masses. There are two forms of US elastography available today: strain and shear wave. With either technique, acoustic information regarding lesion stiffness is converted into a black-and-white or color-scaled image that can also be superimposed on top of a B-mode gray-scale image.

Strain elastography requires gentle compression with a US probe or natural motion (such as heart beat, vascular pulsation, or respiration) and results in tissue displacement, or strain. Strain (ie, tissue compression and motion) is decreased in hard tissues compared with soft tissue (23). The information obtained with strain elastography provides qualitative information, although strain ratios may be calculated by comparing the strain of a lesion to the surrounding normal tissue. Benign breast lesions generally have lower ratios in comparison to malignant lesions (24,25).

Shear-wave elastography is based on the principle of acoustic radiation force. With use of light transducer pressure, transient automatic pulses can be generated by the US probe, inducing transversely oriented shear waves in tissue. The US system captures the velocity of these shear waves, which travel faster in hard tissue compared with soft tissue (26). Shear-wave elastography provides quantitative information because the elasticity of the tissue can be measured in meters per second or in kilopascals, a unit of pressure.

Elastography features such as strain ratios, size ratios, shape, homogeneity, and maximum lesion stiffness may complement conventional US in the analysis of breast lesions. Malignant masses evaluated with elastography tend to be more irregular, heterogeneous, and typically appear larger at elastography than at grayscale imaging (Fig 5) (27,28). Although malignant lesions generally also exhibit maximum stiffness greater than 80–100 kPa (28,29), caution is necessary when applying these numerical values to lesion analysis. Berg et al (28) reported three cancers among 115 masses with maximum stiffness between 20 and 30 kPa, for a 2.6% malignancy rate; 25 cancers among 281 masses with maximum stiffness between 30 and 80 kPa, for an 8.9% malignancy rate; and 61 cancers among 153 masses with maximum stiffness between 80 and 160 kPa, for a 39.9% malignancy rate (28). Invasive cancers with high histologic grade, large tumor size, nodal involvement, and vascular invasion have also been shown to be significantly correlated with high mean stiffness at shear-wave elastography (30).

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Elastography may be useful in improving the specificity of US evaluation of BI-RADS 3 and 4A lesions, including complicated cysts. Berg and colleagues (28) showed that by using qualitative shear-wave elastography and color assessment of lesion stiffness, oval shape, and a maximum elasticity value of less than 80 kPa, unnecessary biopsy of low-suspicion BI-RADS 4A masses could be reduced without a significant loss in sensitivity. Several investigators have proposed a variety of imaging classifications using strain elastography, mostly based on the color pattern (27,31,32). A “bull’s eye” artifact has also been described as a characteristic feature present in benign breast cysts, which may appear as a round or oval lesion with a stiff rim associated with two soft spots, one located centrally and the other posteriorly (33).

Despite these initial promising studies regarding the role of US elastography in the analysis of breast lesions, limitations do exist. Strain and shear-wave elastography are quite different methods of measuring breast tissue stiffness, and the application of these methods varies across different commercial manufacturers. Inter- and intraobserver variability may be relatively high because the elastogram may be affected by differences in degree and method of compression. With strain elastography, a quality indicator that is an associated color bar or numerical value may be helpful to ensure proper light compression. Shear-wave elastography has been shown to be less operator-dependent, as tissue compression is initiated by the US probe in a standard, reproducible fashion (34) and only light transducer pressure is necessary. In addition, there is currently no universal color-coding standard and, depending on the manufacturer and/or operator preference, stiff lesions may be arbitrarily coded to appear red while soft lesions appear blue, or vice versa. Some elastography features such as the “bull’s eye” artifact are only seen on specific US systems. Lesions deeper than 2 cm are less accurately characterized by means of elastography. Moreover, one must be aware that soft cancers and hard benign lesions exist. Therefore, careful correlation of elastography with B-mode US features and mammography is essential. Future studies and further technical advances, including the creation of more uniformity across different US manufacturers, will ultimately determine the usefulness of elastography in clinical practice.

Three-dimensional US

Both handheld and automated high-resolution linear 3D transducers are now available for use in breast imaging. With a single pass of the ultrasound beam, a 3D reconstructed image can be formed in the coronal, sagittal, and transverse planes, potentially allowing more accurate assessment of anatomic structures and tumor margins (Fig 6). Few studies regarding the performance of 3D US in the breast exist, but a preliminary study demonstrated improved characterization of malignant lesions (35). Automated supine whole-breast US using 3D technology is now widely available for use in the screening setting (see section on screening breast US). Three-dimensional US may also be used in addition to computed tomography for image-guided radiation therapy (36) and has a potential role in assessing tumor response to neoadjuvant chemotherapy.

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US Features of Benign and Malignant Breast Lesions

Cysts

Although for many years the main function of breast US was to differentiate cysts from solid masses, this differentiation can at times be problematic, particularly if the lesion is small or located deep in the breast. Simple cysts are defined as circumscribed, anechoic masses with a thin imperceptible wall and enhanced through transmission (provided spatial compounding is not used). By convention, simple cysts may also contain up to a single thin septation. Simple cysts are confidently characterized with virtually 100% accuracy at US (14,37), provided that they are not very small (< 5 mm in size) or not located in deep tissue. Complicated cysts are hypoechoic with no discernable Doppler flow, contain internal echoes, and may also exhibit indistinct margins, and/or lack posterior acoustic enhancement. Clustered microcysts consist of a cluster of tiny (<2–3 mm in size) anechoic foci with thin (< 0.5 mm in thickness) intervening septations.

Complicated cysts are very common sonographic findings and the majority are benign. In multiple studies, which evaluated over 1400 complicated cysts and microcysts, the malignancy rate ranged from 0% to 0.8% (3844). Most complicated cysts and clustered microcysts with a palpable or mammographic correlate are classified as BI-RADS 3 and require short-interval imaging follow-up or, occasionally, US-guided aspiration. However, in the screening US setting, if multiple and bilateral complicated and simple cysts are present (ie, at least three cysts with at least one cyst in each breast), these complicated cysts can be assessed as benign, BI-RADS 2, requiring no additional follow-up (38).

Complicated cysts should never demonstrate internal vascularity at color Doppler interrogation. The presence of a solid component, mural nodule, thickened septation, or thickened wall within a cystic mass precludes the diagnosis of a benign complicated cyst. These complex masses require biopsy, as some cancers may have cystic components. The application of compound imaging and harmonics, color Doppler, and potentially elastography may help differentiate benign complicated cysts from malignant cystic-appearing masses and reduce the need for additional follow-up or biopsy.

Solid Masses

Sonographic features of benign-appearing solid masses include an oval or ellipsoid shape, “wider-than-tall” orientation parallel to the skin, circumscribed margins, gentle and smooth (less than three) lobulations, as well as absence of any malignant features (2,45) (Fig 2b). Lesions with these features are commonly fibroadenomas or other benign masses and can often be safely followed, even if the mass is palpable (4648). Malignant features of solid masses include spiculations, angular margins, marked hypoechogenicity, posterior acoustic shadowing, microcalcifications, ductal extension, branching pattern, and 1–2-mm microlobulations (2,45) (Figs 1b,56). These are also often taller-than-wide lesions with a nonparallel orientation to the skin and may occasionally be associated with thickened Cooper ligaments and/or or skin thickening. Most cancers have more than one malignant feature, spiculation being the most specific and angular margins the most common (2).

There is, however, considerable overlap between these benign and malignant US features and careful scanning technique, as well as direct correlation with mammography, is essential. For example, some high-grade invasive ductal carcinomas with central necrosis, as well as the well-differentiated mucinous and medullary subtypes, may present as circumscribed, oval, hypoechoic masses that may look like complicated cysts with low-level internal echoes at US. Benign focal fibrous breast tissue or postoperative scars can appear as irregular shadowing masses on US images. Furthermore, while echogenic lesions are often benign and frequently represent lipomas or fibrous tissue, echogenic cancers do rarely occur (Figs 78) (49,50). The presence of a single malignant feature, despite the presence of multiple benign features, precludes a benign classification and mandates biopsy, with the exception of fat necrosis and postoperative scars exhibiting typical benign mammographic features. Likewise, a mass with a benign US appearance should be biopsied if it exhibits any suspicious mammographic features.

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 Ductal Carcinoma in Situ

Ductal carcinoma in situ (DCIS) is characteristically associated with microcalcifications detected at mammography, but may also be detected at US since they are often associated with a subtle hypoechoic mass, which may indicate an invasive mammographically occult component. US features associated with DCIS most commonly include a hypoechoic mass with an irregular shape, microlobulated margins, no posterior acoustic features, and no internal vascularity. Ductal abnormalities, intracystic lesions, and architectural distortions may also be present (5153). Noncalcified DCIS manifesting as a solid mass at US is more frequently found in non–high-grade than high-grade DCIS, which is more often associated with microcalcifications and ductal changes (54). US can depict microcalcifications, particularly those in clusters greater than 10 mm in size and located in a hypoechoic mass or a ductlike structure (Fig 9) (55). Malignant calcifications are more likely to be detected sonographically than are benign calcifications, which may be obscured by surrounding echogenic breast tissue (55,56). Although US is inferior to mammography in the detection of suspicious microcalcifications, the main benefit of US detection of DCIS is to identify the invasive component and guide biopsy procedures.

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Breast US in Clinical Practice

Current indications for breast US as recommended by the American College of Radiology Practice Guidelines include the evaluation of palpable abnormalities or other breast symptoms, assessment of mammographic or MR imaging–detected abnormalities, and evaluation of breast implants (57). Additionally, US is routinely used for guidance during interventional procedures, treatment planning for radiation therapy, screening in certain groups of women, and evaluation of axillary lymph nodes. Much literature has been written on these uses and a comprehensive discussion is beyond the scope of this article. A few important and timely topics, however, will be reviewed.

 

 

BI-RADS US

The BI-RADS US lexicon was introduced in 2003, and subsequently, there have been several studies assessing the accuracy of BI-RADS US classification of breast lesions. Low to moderate interobserver agreement has been found in the description of margins (especially noncircumscribed margins), echogenicity, and posterior acoustic features. Abdullah et al (58) reported low interobserver agreement especially for small masses and for malignant masses. Given the importance of margin analysis in the characterization of benign and malignant lesions, this variability is potentially problematic. Studies have also shown variable results in the use of the final assessment categories. In clinical settings, Raza et al (46) showed inconsistent use of the BI-RADS 3 (probably benign) category in 14.0% of cases when biopsy was recommended. Abdullah et al also demonstrated fair and poor interobserver agreement for BI-RADS 4 (suspicious for malignancy) a, b, and c subcategories (58). However, Henig et al (59) reported more promising results, with malignancy rates in categories 3, 4, and 5 to be similar to those seen with mammographic categorization (1.2%, 17%, and 94%, respectively).

 

 Evaluation of Mammographic Findings

Targeted US is complementary to diagnostic mammography because of its ability to differentiate cystic and solid lesions.US is also useful in the work up of subtle asymmetries, as it can help identify or exclude the presence of an underlying mass. True hypoechoic lesions can often be differentiated from prominent fat lobules by scanning in multiple planes, because true lesions usually do not blend or elongate into adjacent tissue. With the introduction of digital breast tomosynthesis for mammographic imaging, US will play yet another important role. As mammographic lesions can often be detected, localized, and have adequate margin assessment on 3D images, patients with lesions detected on digital breast tomosynthesis images at screening may often be referred directly to US, avoiding additional mammographic imaging and its associated costs and radiation exposure (Fig 10). This will place an even greater importance on high-quality US.

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Evaluation of the Symptomatic Patient:Palpable Masses, Breast Pain, and Nipple Discharge

US is essential in the evaluation of patients with the common clinical complaint of either a palpable mass or focal persistent breast pain. Unlike focal breast pain, which may be occasionally associated with benign or malignant lesions, diffuse breast pain (bilateral or unilateral), as well as cyclic breast pain, requires only clinical follow-up, as it is usually physiologic with an extremely low likelihood of malignancy (60,61). In patients with isolated focal breast pain, the role of sonography may be limited to patient reassurance (61). In women younger than 30 years of age, with a palpable lump or focal breast pain, US is the primary imaging test, with a sensitivity and negative predictive value of nearly 100% (62). Symptomatic women older than 30 years usually require both US and mammography, and in these patients, the negative predictive value approaches 100% (63,64). Lehman et al (65) demonstrated that in symptomatic women aged 30–39 years, the risk of malignancy was 1.9% and the added value of adjunct mammography in addition to US was low. Identification of a benign-appearing solid lesion at US in a symptomatic woman can negate the need for needle biopsy, as many of these masses can safely be monitored with short-interval follow-up US (4648), usually performed at 6 months. A suspicious mass identified at US can promptly undergo biopsy with US guidance.

US can also be used as an alternative or an addition to ductography in patients who present with unilateral, spontaneous bloody, clear, or serosanguinous nipple discharge (66). Among women with worrisome nipple discharge, ductography can demonstrate an abnormality in 59%–82% of women (67,68), MR imaging may demonstrate a suspicious abnormality in 34% of women (68), and US has been shown to demonstrate a subareolar mass or an intraductal mass or filling defect in up to 14% of women (67). If US can be used to identify a retroareolar mass or an intraductal mass, US-guided biopsy can be performed and ductography may be avoided (Fig 11). US may be limited, however, as small peripherally located intraductal masses or masses without an associated dilated duct may not be identified. Therefore, galactography, MR imaging, and/or major duct excision may still be necessary in the symptomatic patient with a negative US examination.

Picture11

Finally, in the pregnant or lactating patient who presents with a palpable breast mass, focal breast pain, or bloody nipple discharge, US is also the initial imaging modality of choice. Targeted US examination in these patients can be used to identify most benign and malignant masses, including fibroadenomas, galactocoeles, lactating adenomas, abscesses, and invasive carcinomas. In a recent study by Robbins et al (69), a negative predictive value of 100% was found among 122 lesions evaluated with US in lactating, pregnant, or postpartum women. This is much higher than the pregnancy-associated breast cancer sensitivity of mammography, which has been reported in the range of 78%–87% (70,71). The diminished sensitivity of mammography is likely due to increased parenchymal density seen in these patients. However, since lactating breast parenchyma is more echogenic than most breast masses, hypoechoic breast cancers are more readily detected at US in pregnant patients.

 

 

Supplemental Screening Breast US

Because of the known limitations of mammography, particularly in women with dense breast tissue, supplemental screening with whole-breast US, in addition to mammography, is increasingly gaining widespread acceptance. Numerous independent studies have demonstrated that the addition of a single screening or whole-breast US examination in women with dense breast tissue at mammography will yield an additional 2.3–4.6 mammographically occult cancers per 1000 women (7280). Mammographically occult cancers detected on US images are generally small node-negative invasive cancers (Fig 12) (81). However, few studies have investigated the performance of incident screening breast US, and the optimal screening US interval is unknown. Berg and colleagues (82) recently demonstrated that incident annual supplemental screening US in intermediate- and high-risk women with mammographically dense breast tissue enabled detection of an additional 3.7 cancers per 1000 women screened.

Picture12

Handheld screening breast US is highly operator-dependent and the majority of screening breast US studies have relied on physician-performed examinations. As per the ACRIN 6666 protocol, a normal screening US examination should consist of a minimum of one image in each quadrant and one behind the nipple (83). Two studies have also demonstrated that technologist-performed handheld screening breast US can achieve similar cancer detection rates (76,78).

Automated whole-breast US is a recently developed alternative to traditional handheld screening breast US, in which standardized, uniform image sets may be readily obtained by a nonradiologist. Automated whole-breast US systems may utilize a standard US unit and a linear-array transducer attached to a computer-guided mechanical arm or a dedicated screening US unit with a 15-cm wide transducer (84,85). With these systems, over 3000 overlapping sagittal, transverse, and coronal images are obtained and available for later review by the radiologist, with associated 3D reconstruction. The advantages include less operator dependence, increased radiologist efficiency, and increased reproducibility, which could aid in follow-up of lesions.

A multi-institutional study has shown that supplemental automated whole-breast US can depict an additional 3.6 cancer per 1000 women screened, similar to physician-performed handheld screening US (85). However, disadvantages include the limited ability to scan the entire breast, particularly posterior regions in large breasts, time-consuming review of a large number of images by the radiologist, and the need to recall patients for a second US examination to re-evaluate indeterminate findings. Moreover, few investigators have compared the use of handheld with automated breast US screening. A single small recent study by Chang et al (86) demonstrated that of 14 cancers initially detected at handheld screening, only 57%–79% were also detected by three separate readers on automated whole-breast US images, with the two cancers missed by all three readers at automated whole-breast US, each less than 1 cm in size.

The use of supplemental screening breast US, performed in addition to mammography, remains controversial despite proof of the ability to detect small mammographically occult cancers. US has limited value for the detection of small clustered microcalcifications without an associated mass lesion. Low positive predictive values of biopsies performed of less than 12% have been consistently reported (77,87). No outcome study has been able to demonstrate a direct decrease in patient mortality due to the detection of these additional small and mammographically occult cancers. This would require a long, randomized screening trial, which is not feasible. Rationally, however, the early detection and treatment of additional small breast cancers should improve outcomes and reduce overall morbidity and mortality. Many insurance companies will not reimburse for screening breast US and historically, this examination has not been widely accepted in the United States.

Nevertheless, because of both the known efficacy of supplemental screening breast US and overall increased breast cancer awareness, more patients and clinicians are requesting this examination. In fact, some states now mandate that radiologists inform women of their breast density and advise them to discuss supplemental screening with their doctors. Although supplemental screening breast MR imaging is usually preferred for women who are at very high risk for breast cancer (ie, women with a lifetime risk of over 20%, for example those women who are BRCA positive or have multiple first-degree relatives with a history of premenopausal breast cancer), screening breast US should be considered in women at very high risk for breast cancer who cannot tolerate breast MR imaging, as well as those women with dense breast tissue and intermediate risk (ie, lifetime risk of 15%–20%, for example those women whose only risk factor is a personal history of breast cancer or previous biopsy of a high-risk lesion), or even average risk. Future studies are needed to establish strategies to reduce false-positive results and continue to optimize both technologist-performed handheld screening US and automated whole-breast US in women with mammographically dense breast tissue.

 

 Use of US for MR Imaging–depicted Abnormalities

MR imaging of the breast is now an integral part of breast imaging, most commonly performed to screen high-risk women and to further assess the stage in patients with newly diagnosed breast cancers. While MR has a higher sensitivity than mammography for detecting breast cancer, the specificity is relatively low (88). Lesions detected on MR images are often mammographically occult, but many can be detected with targeted US (Fig 13). Besides further US characterization of an MR imaging–detected lesion, US may be used to guide intervention for lesions initially detected at MR imaging. US-guided biopsies are considerably less expensive, less time consuming, and more comfortable for the patient than MR imaging–guided biopsies.

Picture13a

Picture13b

Some suspicious lesions detected at MR imaging will represent invasive ductal or lobular cancers, but many may prove to be intraductal disease, which can be challenging to detect at US. Meticulous scanning technique is required for an MR imaging–directed US examination, with knowledge of subtle sonographic signs and close correlation with the MR imaging findings and location. Precontrast T1 images are helpful to facilitate localization of lesions in relation to fibroglandular tissue (89). Because MR imaging abnormalities tend to be vascular, increased vascularity may also assist in detection of a subtle sonographic correlate (90). Having the MR images available for simultaneous review while performing the US examination will ideally permit such associative correlation. At the authors’ facility, computer monitors displaying images from the picture archiving and communication system are available in all US rooms for this purpose.

Recent studies have shown that 46%–71% of lesions at MR imaging can be detected with focused US (9094). Enhancing masses detected on MR images are identified on focused US images in 58%–65% of cases compared with nonmass enhancement, which is identified on focused US images in only 12%–32% of cases (9092). Some studies have shown that US depiction of an MR imaging correlate was independent of size (91,93,95). However, Meissnitzer et al (92) showed that size dependence is also important: For masses 5 mm or smaller, only 50% were seen, versus 56% for masses 6–10 mm, 73% for masses 11–15 mm, and 86% for masses larger than 15 mm. Likewise, this study also demonstrated that for nonmass lesions, a US correlate was found for 13% of those measuring 6–10 mm, 25% of those 11–15 mm, and 42% of those larger than 15 mm (92). In addition, many of these studies determined that when a sonographic correlate was discovered, the probability of malignancy was increased (9092). Since typical US malignant features such as spiculation and posterior shadowing may be absent and the pretest probability is higher for MR imaging–detected lesions, a lower threshold for biopsy should be considered when performing MR imaging–directed US compared with routine targeted US (90) or screening US.

Because lesions are often very subtle at MR-directed US examination and because of differences in patient positioning during the two examinations, careful imaging–histologic correlation is required when performing US-guided biopsy of MR imaging–detected abnormalities. For lesions sampled with a vacuum-assisted device and US guidance, Sakamoto et al (96) found a higher rate of false-negative biopsy results for MR imaging–detected lesions than for US-detected lesions, suggesting that precise US-MR imaging correlation may not have occurred. Meissnitzer et al (92) showed that although 91% of MR imaging–detected lesions had an accurate US correlate, 9% were found to be inaccurate. With ever-improving techniques and experience in breast US, the US visualization of MR imaging–detected abnormalities will likely continue to improve. Nevertheless, if a suspicious lesion is not identified sonographically, MR imaging–guided biopsy should still be performed, because the malignancy rate of sonographically occult MR imaging–detected lesions has been shown to range from 14% to 22% (91,95).

 

 

Preoperative Staging of Cancer with US

Breast MR imaging has been shown to be more sensitive than US in the detection of additional foci of mammographically occult disease in women with newly diagnosed breast cancer (9799). Nevertheless, when a highly suspicious mass is identified at mammography and US, immediate US evaluation of the remainder of the ipsilateral breast, the contralateral breast, and the axilla should be considered. If additional lesions are identified, preoperative staging with MR imaging can be avoided and US-guided biopsy can be promptly performed, saving the patient valuable time and expense (100). In a study by Moon et al (101), of 201 patients with newly diagnosed breast cancer, staging US demonstrated mammographically occult multifocal or multicentric disease in 28 patients (14%) and contralateral breast cancers in eight patients (4%), resulting in a change in therapy in 32 patients (16%).

US can also be used to identify abnormal axillary, supraclavicular, and internal mammary lymph nodes. Abnormal lymph nodes characteristically demonstrate focal or diffuse cortical thickening (≥3 mm in thickness), a round (rather than oval or reniform) shape, loss of the echogenic fatty hilum and/or nonhilar, disorganized, irregular blood vessels (102,103) (Fig 14). A positive US-guided CNB or fine-needle aspiration of a clinically abnormal axillary lymph node in a patient with a known breast cancer can aid patient management, by avoiding the need for sentinel node biopsy and allowing the patient instead to proceed directly to axillary lymph node dissection or neoadjuvant chemotherapy.

Picture14

 

 Interventional Breast US

US-guided interventional procedures have increased in volume in recent years and US is now the primary biopsy guidance technique used in many breast imaging centers. Most palpable lesions, as well as lesions detected at mammography, MR imaging, or screening US, can be sampled with US. With current high-resolution transducers, even suspicious intraductal microcalcifications may be detected and sampled.

While US-guided procedures require technical skills that must be developed and can be challenging, once mastered this technique allows precise real-time sampling of the lesion, which is not possible with either stereotactic or MR imaging–guided procedures. US-guided procedures do not require ionizing radiation or intravenous contrast material. US procedures are more tolerable for patients than stereotactic (104) or MR imaging–guided procedures because US-guided procedures are faster and more comfortable, as breast compression and uncomfortable biopsy coils or tables are not necessary and the procedure may be performed with the patient supine (104106).

Most literature has shown that automated 14-gauge CNB devices are adequate for the majority of US-guided biopsies (107115). Image-guided CNB is preferable to fine-needle aspiration cytology of breast masses because of superior sensitivity, specificity, and diagnostic accuracy (116). DCIS, malignant invasion, and hormone receptor status of invasive breast cancers can be determined with CNB samples, but not with fine-needle aspiration cytology. Fine-needle aspiration may be performed, however, in complicated cysts and symptomatic simple cysts. In these cases, the cyst aspirate fluid can often be discarded; cytology is usually only necessary if the fluid is frankly bloody (117).

The choice of performing fine-needle aspiration or CNB of a suspicious axillary lymph node depends on radiologist preference and the availability of an experienced cytopathologist, although CNB is usually more accurate than fine-needle aspiration biopsy (118,119). Fine-needle aspiration may be preferred for suspicious deep lymph nodes in proximity to the axillary vessels, whereas CNB may be preferred in large nodes with thickened cortices, particularly if determination of hormone receptor status or immunohistochemistry is desired, since more tissue is required for these assays. If lymphoma is suspected, a core should be placed in saline and also in conventional formalin.

While the underestimation rate of malignancy can be considerable for high-risk lesions such as atypical hyperplasia, such histology is not commonly found in lesions undergoing US-guided CNB. Multiple studies have shown a false-negative rate for US CNB biopsy of around 2%–3% (107115). Although the contiguous and larger samples obtained with a vacuum-assisted biopsy device undoubtedly reduce sampling error, the vacuum-assisted biopsy is a more expensive and more invasive procedure (109). In the authors’ experience, vacuum-assisted US biopsy is to be considered for small masses, intraductal or intracystic lesions, or lesions with subtle microcalcifications. These may be difficult to adequately sample with a spring-loaded automatic firing device. Alternatively, for more accurate sampling of such challenging cases, as well as some axillary lymph nodes and masses smaller than 1 cm in size, automated CNB needles designed to place the inner trough of the needle within a lesion before firing can be utilized (Fig 15). With this technique, the sampling trough of the CNB needle can be clearly visualized within the lesion before the overlying outer sheath is fired. Regardless of needle choice, a postbiopsy clip marker should be placed followed by a postbiopsy mammogram to document clip position. This will assist with follow-up imaging, facilitating mammography and/or MR imaging correlation.

Picture15a

 

Picture15b

There has been recent interest in the percutaneous removal of benign breast lesions by using US-guided vacuum-assisted biopsy. While in general, proved benign concordant lesions can safely remain in the breast, some patients desire removal. Percutaneous US-guided removal with a vacuum-assisted biopsy device can replace surgical removal in some cases, particularly for small lesions (1 cm in size or less). Several reports have shown promising results demonstrating rates of complete lesion excision, varying from 61% to 94% (120124). Dennis et al (125) demonstrated that vacuum-assisted US-guided biopsy could be used to excise intraductal lesions resulting in resolution of problematic nipple discharge in 97% of patients. Even on long-term follow-up, most studies show low rates of residual masses, more commonly observed in larger fibroadenomas.

 

 Intraoperative Breast US

The use of two-dimensional and 3D intraoperative US may decrease the incidence of positive margins and decrease re-excision rates (126130) particularly in the setting of lumpectomy for palpable cancers, when US is used to assess the adequacy of surgical margins to determine the need for additional tissue removal. Similarly, intraoperative US has also been utilized to improve detection and removal of metastatic lymph nodes during sentinel lymph node assessment (131).

 

Future Directions

Intravenous US microbubble contrast agents have been used to enhance US diagnosis by means of analysis, enhancement patterns, the rates of uptake and washout, and identification of tumor angiogenesis. In addition, preliminary research has shown that intravenous US contrast agents may be able to depict tissue function with the potential to deliver targeted gene therapy to selected tumor cells (132). However, there are currently no intravenous US contrast agents approved for use in breast imaging by the U.S. Food and Drug Administration. Other potential advances in breast US include fusion imaging, which involves the direct overlay of correlative MR imaging with targeted US. Another evolving area is that of US computer-aided detection, which may be of particular benefit when combined with automated whole-breast screening US.

 

 Summary

Technical advances in US now allow comprehensive US diagnosis, management, and treatment of breast lesions. Optimal use of US technology, meticulous scanning technique with careful attention to lesion morphology, and recognition and synthesis of findings from multiple imaging modalities are essential for optimal patient management. In the future, as radiologists utilize US for an ever-increasing scope of indications, become aware of the more subtle sonographic findings of breast cancer, and apply newly developing tools, the value of breast US will likely continue to increase and evolve.

 

Essentials

  • • Breast US is operator dependent; knowledge and understanding of the various technical options currently available are important for image optimization and accurate diagnosis.
  • • US is an interactive, dynamic modality and real-time scanning is necessary to assess subtle findings associated with malignancy.
  • • Ability to synthesize the information obtained from the breast US examination with concurrent mammography, MR imaging, and clinical breast examination is necessary for accurate diagnosis.
  • • The use of screening breast US in addition to mammography, particularly in women with dense breast tissue, is becoming more widely accepted in the United States.
  • • Breast US guidance is the primary biopsy method used in most breast imaging practices, and the radiologist should be familiar with various biopsy devices and techniques to adequately sample any breast mass identified at US.

 

Disclosures of Conflicts of Interest: R.J.H. No relevant conflicts of interest to disclose. L.M.S. Financial activities related to the present article: none to disclose. Financial activities not related to the present article: educational consultant in vascular US to Philips Healthcare; payment for lectures on breast US from Educational Symposia; payment for development of educational presentations from Philips Healthcare. Other relationships: none to disclose. L.E.P. Financial activities related to the present article: none to disclose. Financial activities not related to the present article: consultant to Hologic. Other relationships: none to disclose.

Abbreviations:

BI-RADS = Breast Imaging and Reporting Data System

CNB = core needle biopsy

DCIS = ductal carcinoma in situ

3D = three dimensional

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    . Sonographic, mammographic, and histopathologic correlation of symptomatic ductal carcinoma in situ. AJR Am J Roentgenol2004;182(1):101–110.

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    . US of mammographically detected clustered microcalcifications. Radiology 2000;217(3):849–854.

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Follow-up on Tomosynthesis

Writer & Curator: Dror Nir, PhD

Tomosynthesis, is a method for performing high-resolution limited-angle (i.e. not full 3600 rotation but more like ~500) tomography. The use of such systems in breast-cancer screening is steadily increasing following the clearance of such system by the FDA on 2011; see my posts – Improving Mammography-based imaging for better treatment planning and State of the art in oncologic imaging of breast.

Many radiologists expects that Tomosynthesis will eventually replace conventional mammography due to the fact that it increases the sensitivity of breast cancer detection. This claim is supported by new peer-reviewed publications. In addition, the patient’s experience during Tomosynthesis is less painful due to a lesser pressure that is applied to the breast and while presented with higher in-plane resolution and less imaging artifacts the mean glandular dose of digital breast Tomosynthesis is comparable to that of full field digital mammography. Because it is relatively new, Tomosynthesis is not available at every hospital. As well, the procedure is recognized for reimbursement by public-health schemes.

A good summary of radiologist opinion on Tomosynthesis can be found in the following video:

Recent studies’ results with digital Tomosynthesis are promising. In addition to increase in sensitivity for detection of small cancer lesions researchers claim that this new breast imaging technique will make breast cancers easier to see in dense breast tissue.  Here is a paper published on-line by the Lancet just a couple of months ago:

Integration of 3D digital mammography with tomosynthesis for population breast-cancer screening (STORM): a prospective comparison study

Stefano Ciatto†, Nehmat Houssami, Daniela Bernardi, Francesca Caumo, Marco Pellegrini, Silvia Brunelli, Paola Tuttobene, Paola Bricolo, Carmine Fantò, Marvi Valentini, Stefania Montemezzi, Petra Macaskill , Lancet Oncol. 2013 Jun;14(7):583-9. doi: 10.1016/S1470-2045(13)70134-7. Epub 2013 Apr 25.

Background Digital breast tomosynthesis with 3D images might overcome some of the limitations of conventional 2D mammography for detection of breast cancer. We investigated the effect of integrated 2D and 3D mammography in population breast-cancer screening.

Methods Screening with Tomosynthesis OR standard Mammography (STORM) was a prospective comparative study. We recruited asymptomatic women aged 48 years or older who attended population-based breast-cancer screening through the Trento and Verona screening services (Italy) from August, 2011, to June, 2012. We did screen-reading in two sequential phases—2D only and integrated 2D and 3D mammography—yielding paired data for each screen. Standard double-reading by breast radiologists determined whether to recall the participant based on positive mammography at either screen read. Outcomes were measured from final assessment or excision histology. Primary outcome measures were the number of detected cancers, the number of detected cancers per 1000 screens, the number and proportion of false positive recalls, and incremental cancer detection attributable to integrated 2D and 3D mammography. We compared paired binary data with McNemar’s test.

Findings 7292 women were screened (median age 58 years [IQR 54–63]). We detected 59 breast cancers (including 52 invasive cancers) in 57 women. Both 2D and integrated 2D and 3D screening detected 39 cancers. We detected 20 cancers with integrated 2D and 3D only versus none with 2D screening only (p<0.0001). Cancer detection rates were 5·3 cancers per 1000 screens (95% CI 3.8–7.3) for 2D only, and 8.1 cancers per 1000 screens (6.2–10.4) for integrated 2D and 3D screening. The incremental cancer detection rate attributable to integrated 2D and 3D mammography was 2.7 cancers per 1000 screens (1.7–4.2). 395 screens (5.5%; 95% CI 5.0–6.0) resulted in false positive recalls: 181 at both screen reads, and 141 with 2D only versus 73 with integrated 2D and 3D screening (p<0·0001). We estimated that conditional recall (positive integrated 2D and 3D mammography as a condition to recall) could have reduced false positive recalls by 17.2% (95% CI 13.6–21.3) without missing any of the cancers detected in the study population.

Interpretation Integrated 2D and 3D mammography improves breast-cancer detection and has the potential to reduce false positive recalls. Randomised controlled trials are needed to compare integrated 2D and 3D mammography with 2D mammography for breast cancer screening.

Funding National Breast Cancer Foundation, Australia; National Health and Medical Research Council, Australia; Hologic, USA; Technologic, Italy.

Introduction

Although controversial, mammography screening is the only population-level early detection strategy that has been shown to reduce breast-cancer mortality in randomised trials.1,2 Irrespective of which side of the mammography screening debate one supports,1–3 efforts should be made to investigate methods that enhance the quality of (and hence potential benefit from) mam­mography screening. A limitation of standard 2D mammography is the superimposition of breast tissue or parenchymal density, which can obscure cancers or make normal structures appear suspicious. This short coming reduces the sensitivity of mammography and increases false-positive screening. Digital breast tomosynthesis with 3D images might help to overcome these limitations. Several reviews4,5 have described the development of breast tomosynthesis technology, in which several low-dose radiographs are used to reconstruct a pseudo-3D image of the breast.4–6

Initial clinical studies of 3D mammography, 6–10 though based on small or selected series, suggest that addition of 3D to 2D mammography could improve cancer detection and reduce the number of false positives. However, previous assessments of breast tomosynthesis might have been constrained by selection biases that distorted the potential effect of 3D mammography; thus, screening trials of integrated 2D and 3D mammography are needed.6

We report the results of a large prospective study (Screening with Tomosynthesis OR standard Mammog­raphy [STORM]) of 3D digital mammography. We investi­gated the effect of screen-reading using both standard 2D and 3D imaging with tomosynthesis compared with screening with standard 2D digital mammography only for population breast-cancer screening.

  

Methods

Study design and participants

STORM is a prospective population-screening study that compares mammography screen-reading in two sequential phases (figure)—2D only versus integrated 2D and 3D mammography with tomosynthesis—yielding paired results for each screening examination. Women aged 48 years or older who attended population-based screening through the Trento and Verona screening services, Italy, from August, 2011, to June, 2012, were invited to be screened with integrated 2D and 3D mammography. Participants in routine screening mammography (once every 2 years) were asymptomatic women at standard (population) risk for breast cancer. The study was granted institutional ethics approval at each centre, and participants gave written informed consent. Women who opted not to participate in the study received standard 2D mammography. Digital mammography has been used in the Trento breast-screening programme since 2005, and in the Verona programme since 2007; each service monitors outcomes and quality indicators as dictated by European standards, and both have published data for screening performance.11,12

 

study design

Procedures

All participants had digital mammography using a Selenia Dimensions Unit with integrated 2D and 3D mammography done in the COMBO mode (Hologic, Bedford, MA, USA): this setting takes 2D and 3D images at the same screening examination with a single breast position and compression. Each 2D and 3D image consisted of a bilateral two-view (mediolateral oblique and craniocaudal) mammogram. Screening mammo­grams were interpreted sequentially by radiologists, first on the basis of standard 2D mammography alone, and then by the same radiologist (on the same day) on the basis of integrated 2D and 3D mammography (figure). Thus, integrated 2D and 3D mammography screening refers to non-independent screen reading based on joint interpretation of 2D and 3D images, and does not refer to analytical combinations. Radiologists had to record whether or not to recall the participant at each screen-reading phase before progressing to the next phase of the sequence. For each screen, data were also collected for breast density (at the 2D screen-read), and the side and quadrant for any recalled abnormality (at each screen-read). All eight radiologists were breast radiologists with a mean of 8 years (range 3–13 years) experience in mammography screening, and had received basic training in integrated 2D and 3D mammography. Several of the radiologists had also used 2D and 3D mammography for patients recalled after positive conventional mammography screening as part of previous studies of tomosynthesis.8,13

Mammograms were interpreted in two independent screen-reads done in parallel, as practiced in most population breast-screening programs in Europe. A screen was considered positive and the woman recalled for further investigations if either screen-reader recorded a positive result at either 2D or integrated 2D and 3D screening (figure). When previous screening mammograms were available, these were shown to the radiologist at the time of screen-reading, as is standard practice. For assessment of breast density, we used Breast Imaging Reporting and Data System (BI-RADS)14 classification, with participants allocated to one of two groups (1–2 [low density] or 3–4 [high density]). Disagreement between readers about breast density was resolved by assessment by a third reader.

Our primary outcomes were the number of cancers detected, the number of cancers detected per 1000 screens, the number and percentage of false posi­tive recalls, and the incremental cancer detection rate attributable to integrated 2D and 3D mammography screening. We compared the number of cancers that were detected only at 2D mammography screen-reading and those that were detected only at 2D and 3D mammography screen-reading; we also did this analysis for false positive recalls. To explore the potential effect of integrated 2D and 3D screening on false-positive recalls, we also estimated how many false-positive recalls would have resulted from using a hypothetical conditional false-positive recall approach; – i.e. positive integrated 2D and 3D mammography as a condition of recall (screening recalled at 2D mammography only would not be recalled). Pre-planned secondary analyses were comparison of outcome measures by age group and breast density.

Outcomes were assessed by excision histology for participants who had surgery, or the complete assessment outcome (including investigative imaging with or without histology from core needle biopsy) for all recalled participants. Because our study focuses on the difference in detection by the two screening methods, some cancers might have been missed by both 2D and integrated 2D and 3D mammography; this possibility could be assessed at future follow-up to identify interval cancers. However, this outcome is not assessed in the present study and does not affect estimates of our primary outcomes – i.e. comparative true or false positive detection for 2D-only versus integrated 2D and 3D mammography.

 

Statistical analysis

The sample size was chosen to provide 80% power to detect a difference of 20% in cancer detection, assuming a detection probability of 80% for integrated 2D and 3D screening mammography and 60% for 2D only screening, with a two-sided significance threshold of 5%. Based on the method of Lachenbruch15 for estimating sample size for studies that use McNemar’s test for paired binary data, a minimum of 40 cancers were needed. Because most screens in the participating centres were incident (repeat) screening (75%–80%), we used an underlying breast-cancer prevalence of 0·5% to estimate that roughly 7500–8000 screens would be needed to identify 40 cancers in the study population.

We calculated the Wilson CI for the false-positive recall ratio for integrated 2D and 3D screening with conditional recall compared with 2D only screening.16 All of the other analyses were done with SAS/STAT (version 9.2), using exact methods to compute 95 CIs and p-values.

Role of the funding source

The sponsors of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. The corresponding author (NH) had full access to all the data in the study and had final responsibility for the decision to submit for publication.

Results

7292 participants with a median age of 58 years (IQR 54–63, range 48–71) were screened between Aug 12, 2011, and June 29, 2012. Roughly 5% of invited women declined integrated 2D and 3D screening and received standard 2D mammography. We present data for 7294 screens because two participants had bilateral cancer (detected with different screen-reading techniques for one participant). We detected 59 breast cancers in 57 participants (52 invasive cancers and seven ductal carcinoma in-situ). Of the invasive cancers, most were invasive ductal (n=37); others were invasive special types (n=7), invasive lobular (n=4), and mixed invasive types (n=4).

Table 1 shows the characteristics of the cancers. Mean tumour size (for the invasive cancers with known exact size) was 13.7 mm (SD 5.8) for cancers detected with both 2D alone and integrated 2D and 3D screening (n=29), and 13.5 mm (SD 6.7) for cancers detected only with integrated 2D and 3D screening (n=13).

 

Table 1

Of the 59 cancers, 39 were detected at both 2D and integrated 2D and 3D screening (table 2). 20 cancers were detected with only integrated 2D and 3D screening compared with none detected with only 2D screening (p<0.0001; table 2). 395 screens were false positive (5.5%, 95% CI 5.0–6.0); 181 occurred at both screen-readings, and 141 occurred at 2D screening only compared with 73 at integrated 2D and 3D screening (p<0.0001; table 2). These differences were still significant in sensitivity analyses that excluded the two participants with bilateral cancer (data not shown).


Table 2

5.3 cancers per 1000 screens (95% CI 3.8–7.3; table 3) were detected with 2D mammography only versus 8.1 cancers per 1000 screens (95% CI 6.2–10.4) with integrated 2D and 3D mammography (p<0.0001). The incremental cancer detection rate attributable to inte­grated 2D and 3D screening was 2.7 cancers per 1000 screens (95% CI 1.7–4.2), which is 33.9% (95% CI 22.1–47.4) of the cancers detected in the study popu­lation. In a sensitivity analysis that excluded the two participants with bilateral cancer the estimated incre­mental cancer detection rate attributable to integrated 2D and 3D screening was 2.6 cancers per 1000 screens (95% CI 1.4–3.8). The stratified results show that integrated 2D and 3D mammography was associated with an incrementally increased cancer detection rate in both age-groups and density categories (tables 3–5). A minority (16.7%) of breasts were of high density (category 3–4) reducing the power of statistical comparisons in this subgroup (table 5). The incremental cancer detection rate was much the same in low density versus high density groups (2.8 per 1000 vs 2.5 per 1000; p=0.84; table 3).


Table 3

Table 4-5

Overall recall—any recall resulting in true or false positive screens—was 6.2% (95% CI 5.7–6.8), and the false-positive rate for the 7235 screens of participants who did not have breast cancer was 5.5% (5.0–6.0). Table 6 shows the contribution to false-positive recalls from 2D mammography only, integrated 2D and 3D mammography only, and both, and the estimated number of false positives if positive integrated 2D and 3D mammography was a condition for recall (positive 2D only not recalled). Overall, more of the false-positive rate was driven by 2D mammography only than by integrated 2D and 3D, although almost half of the false-positive rate was a result of false positives recalled at both screen-reading phases (table 6). The findings were much the same when stratified by age and breast density (table 6). Had a conditional recall rule been applied, we estimate that the false-positive rate would have been 3.5% (95% CI 3.1–4.0%; table 6) and could have potentially prevented 68 of the 395 false positives (a reduction of 17.2%; 95% CI 13.6–21.3). The ratio between the number of false positives with integrated 2D and 3D screening with conditional recall (n=254) versus 2D only screening (n=322) was 0.79 (95% CI 0.71–0.87).

Discussion

Our study showed that integrated 2D and 3D mam­mography screening significantly increases detection of breast cancer compared with conventional mammog­raphy screening. There was consistent evidence of an incremental improvement in detection from integrated 2D and 3D mammography across age-group and breast density strata, although the analysis by breast density was limited by low number of women with breasts of high density.

One should note that we investigated comparative cancer detection, and not absolute screening sensitivity. By integrating 2D and 3D mammography using the study screen-reading protocol, 1% of false-positive recalls resulted from 2D and 3D screen-reading only (table 6). However, significantly more false positives resulted from 2D only mammography compared with integrated 2D and 3D mammography, both overall and in the stratified analyses. Application of a conditional recall rule would have resulted in a false-positive rate of 3.5% instead of the actual false-positive rate of 5.5%. The estimated false positive recall ratio of 0.79 for integrated 2D and 3D screening with conditional recall compared with 2D only screening suggests that integrated 2D and 3D screening could reduce false recalls by roughly a fifth. Had such a condition been adopted, none of the cancers detected in the study would have been missed because no cancers were detected by 2D mammography only, although this result might be because our design allowed an independent read for 2D only mammography whereas the integrated 2D and 3D read was an interpretation of a combination of 2D and 3D imaging. We do not recommend that such a conditional recall rule be used in breast-cancer screening until our findings are replicated in other mammography screening studies—STORM involved double-reading by experienced breast radiologists, and our results might not apply to other screening settings. Using a test set of 130 mammograms, Wallis and colleagues7 report that adding tomosynthesis to 2D mammography increased the accuracy of inexperienced readers (but not of experienced readers), therefore having experienced radiologists in STORM could have underestimated the effect of integrated 2D and 3D screen-reading.

No other population screening trials of integrated 2D and 3D mammography have reported final results (panel); however, an interim analysis of the Oslo trial17 a large population screening study has shown that integrated 2D and 3D mammography substantially increases detection of breast cancer. The Oslo study investigators screened women with both 2D and 3D mammography, but randomised reading strategies (with vs without 3D mammograms) and adjusted for the different screen-readers,17whereas we used sequential screen-reading to keep the same reader for each exam­ination. Our estimates for comparative cancer detection and for cancer detection rates are consistent with those of the interim analysis of the Oslo study.17 The applied recall methods differed between the Oslo study (which used an arbitration meeting to decide recall) and the STORM study (we recalled based on a decision by either screen-reader), yet both studies show that 3D mammog­raphy reduces false-positive recalls when added to standard mammography.

An editorial in The Lancet18 might indeed signal the closing of a chapter of debate about the benefits and harms of screening. We hope that our work might be the beginning of a new chapter for mammography screening: our findings should encourage new assessments of screening using 2D and 3D mammography and should factor several issues related to our study. First, we compared standard 2D mammography with integrated 2D and 3D mammography the 3D mammograms were not interpreted independently of the 2D mammograms therefore 3D mammography only (without the 2D images) might not provide the same results. Our experience with breast tomosynthesis and a review6 of 3D mammography underscore the importance of 2D images in integrated 2D and 3D screen-reading. The 2D images form the basis of the radiologist’s ability to integrate the information from 3D images with that from 2D images. Second, although most screening in STORM was incident screening, the substantial increase in cancer detection rate with integrated 2D and 3D mammography results from the enhanced sensitivity of integrated 2D and 3D screening and is probably also a result of a prevalence effect (ie, the effect of a first screening round with integrated 2D and 3D mammography). We did not assess the effect of repeat (incident) screening with integrated 2D and 3D mammography on cancer detection it might provide a smaller effect on cancer detection rates than what we report. Third, STORM was not designed to measure biological differences between the cancers detected at integrated 2D and 3D screening compared with those detected at both screen-reading phases. Descriptive analyses suggest that, generally, breast cancers detected only at integrated 2D and 3D screening had similar features (eg, histology, pathological tumour size, node status) as those detected at both screen-reading phases. Thus, some of the cancers detected only at 2D and 3D screening might represent early detection (and would be expected to receive screening benefit) whereas some might represent over-detection and a harm from screening, as for conventional screening mam mography.1,19 The absence of consensus about over-diagnosis in breast-cancer screening should not detract from the importance of our study findings to applied screening research and to screening practice; however, our trial was not done to assess the extent to which integrated 2D and 3D mam­mography might contribute to over-diagnosis.

The average dose of glandular radiation from the many low-dose projections taken during a single acquisition of 3D mammography is roughly the same as that from 2D mammography.6,20–22 Using integrated 2D and 3D en­tails both a 2D and 3D acquisition in one breast com­pression, which roughly doubles the radiation dose to the breast. Therefore, integrated 2D and 3D mammography for population screening might only be justifiable if improved outcomes were not defined solely in terms of improved detection. For example, it would be valuable to show that the increased detection with integrated 2D and 3D screening leads to reduced interval cancer rates at follow-up. A limitation of our study might be that data for interval cancers were not available; however, because of the paired design we used, future evaluation of interval cancer rates from our study will only apply to breast cancers that were not identified using 2D only or integrated 2D and 3D screening. We know of two patients from our study who have developed interval cancers (follow-up range 8–16 months). We did not get this information from cancer registries and follow-up was very short, so these data should be interpreted very cautiously, especially because interval cancers would be expected to occur in the second year of the standard 2 year interval between screening rounds. Studies of interval cancer rates after integrated 2D and 3D mammography would need to be randomised controlled trials and have a very large sample size. Additionally, the development of reconstructed 2D images from a 3D mammogram23 provides a timely solution to concerns about radiation by providing both the 2D and 3D images from tomosynthesis, eliminating the need for two acquisitions.

We have shown that integrated 2D and 3D mammog­raphy in population breast-cancer screening increases detection of breast cancer and can reduce false-positive recalls depending on the recall strategy. Our results do not warrant an immediate change to breast-screening practice, instead, they show the urgent need for random­ised controlled trials of integrated 2D and 3D versus 2D mammography, and for further translational research in breast tomosynthesis. We envisage that future screening trials investigating this issue will include measures of breast cancer detection, and will be designed to assess interval cancer rates as a surrogate endpoint for screening efficacy.

Contributors

SC had the idea for and designed the study, and collected and interpreted data. NH advised on study concepts and methods, analysed and interpreted data, searched the published work, and wrote and revised the report. DB and FC were lead radiologists, recruited participants, collected data, and commented on the draft report. MP, SB, PT, PB, PT, CF, and MV did the screen-reading, collected data, and reviewed the draft report. SM collected data and reviewed the draft report. PM planned the statistical analysis, analysed and interpreted data, and wrote and revised the report.

Conflicts of interest

SC, DB, FC, MP, SB, PT, PB, CF, MV, and SM received assistance from Hologic (Hologic USA; Technologic Italy) in the form of tomosynthesis technology and technical support for the duration of the study, and travel support to attend collaborators’ meetings. NH receives research support from a National Breast Cancer Foundation (NBCF Australia) Practitioner Fellowship, and has received travel support from Hologic to attend a collaborators’ meeting. PM receives research support through Australia’s National Health and Medical Research Council programme grant 633003 to the Screening & Test Evaluation Program.

 

References

1       Independent UK Panel on Breast Cancer Screening. The benefits and harms of breast cancer screening: an independent review. Lancet 2012; 380: 1778–86.

2       Glasziou P, Houssami N. The evidence base for breast cancer screening. Prev Med 2011; 53: 100–102.

3       Autier P, Esserman LJ, Flowers CI, Houssami N. Breast cancer screening: the questions answered. Nat Rev Clin Oncol 2012; 9: 599–605.

4       Baker JA, Lo JY. Breast tomosynthesis: state-of-the-art and review of the literature. Acad Radiol 2011; 18: 1298–310.

5       Helvie MA. Digital mammography imaging: breast tomosynthesis and advanced applications. Radiol Clin North Am 2010; 48: 917–29.

6      Houssami N, Skaane P. Overview of the evidence on digital breast tomosynthesis in breast cancer detection. Breast 2013; 22: 101–08.

7   Wallis MG, Moa E, Zanca F, Leifland K, Danielsson M. Two-view and single-view tomosynthesis versus full-field digital mammography: high-resolution X-ray imaging observer study. Radiology 2012; 262: 788–96.

8   Bernardi D, Ciatto S, Pellegrini M, et al. Prospective study of breast tomosynthesis as a triage to assessment in screening. Breast Cancer Res Treat 2012; 133: 267–71.

9   Michell MJ, Iqbal A, Wasan RK, et al. A comparison of the accuracy of film-screen mammography, full-field digital mammography, and digital breast tomosynthesis. Clin Radiol 2012; 67: 976–81.

10 Skaane P, Gullien R, Bjorndal H, et al. Digital breast tomosynthesis (DBT): initial experience in a clinical setting. Acta Radiol 2012; 53: 524–29.

11 Pellegrini M, Bernardi D, Di MS, et al. Analysis of proportional incidence and review of interval cancer cases observed within the mammography screening programme in Trento province, Italy. Radiol Med 2011; 116: 1217–25.

12 Caumo F, Vecchiato F, Pellegrini M, Vettorazzi M, Ciatto S, Montemezzi S. Analysis of interval cancers observed in an Italian mammography screening programme (2000–2006). Radiol Med 2009; 114: 907–14.

13 Bernardi D, Ciatto S, Pellegrini M, et al. Application of breast tomosynthesis in screening: incremental effect on mammography acquisition and reading time. Br J Radiol 2012; 85: e1174–78.

14 American College of Radiology. ACR BI-RADS: breast imaging reporting and data system, Breast Imaging Atlas. Reston: American College of Radiology, 2003.

15  Lachenbruch PA. On the sample size for studies based on McNemar’s test. Stat Med 1992; 11: 1521–25.

16  Bonett DG, Price RM. Confidence intervals for a ratio of binomial proportions based on paired data. Stat Med 2006; 25: 3039–47.

17  Skaane P, Bandos AI, Gullien R, et al. Comparison of digital mammography alone and digital mammography plus tomosynthesis in a population-based screening program. Radiology 2013; published online Jan 3. http://dx.doi.org/10.1148/ radiol.12121373.

18  The Lancet. The breast cancer screening debate: closing a chapter? Lancet 2012; 380: 1714.

19  Biesheuvel C, Barratt A, Howard K, Houssami N, Irwig L. Effects of study methods and biases on estimates of invasive breast cancer overdetection with mammography screening: a systematic review. Lancet Oncol 2007; 8: 1129–38.

20  Tagliafico A, Astengo D, Cavagnetto F, et al. One-to-one comparison between digital spot compression view and digital breast tomosynthesis. Eur Radiol 2012; 22: 539–44.

21  Tingberg A, Fornvik D, Mattsson S, Svahn T, Timberg P, Zackrisson S. Breast cancer screening with tomosynthesis—initial experiences. Radiat Prot Dosimetry 2011; 147: 180–83.

22  Feng SS, Sechopoulos I. Clinical digital breast tomosynthesis system: dosimetric characterization. Radiology 2012; 263: 35–42.

23  Gur D, Zuley ML, Anello MI, et al. Dose reduction in digital breast tomosynthesis (DBT) screening using synthetically reconstructed projection images: an observer performance study. Acad Radiol 2012; 19: 166–71.

A very good and down-to-earth comment on this article was made by Jules H Sumkin who disclosed that he is an unpaid member of SAB Hologic Inc and have a PI research agreement between University of Pittsburgh and Hologic Inc.

The results of the study by Stefano Ciatto and colleagues1 are consistent with recently published prospective,2,3 retrospective,4 and observational5 reports on the same topic. The study1 had limitations, including the fact that the same radiologist interpreted screens sequentially the same day without cross-balancing which examination was read first. Also, the false-negative findings for integrated 2D and 3D mammography, and therefore absolute benefit from the procedure, could not be adequately assessed because cases recalled by 2D mammography alone (141 cases) did not result in a single detection of an additional cancer while the recalls from the integrated 2D and 3D mammography alone (73 cases) resulted in the detection of 20 additional cancers. Nevertheless, the results are in strong agreement with other studies reporting of substantial performance improvements when the screening is done with integrated 2D and 3D mammography.

I disagree with the conclusion of the study with regards to the urgent need for randomised clinical trials of integrated 2D and 3D versus 2D mammography. First, to assess differences in mortality as a result of an imaging-based diagnostic method, a randomised trial will require several repeated screens by the same method in each study group, and the strong results from all studies to date will probably result in substantial crossover and self-selection biases over time. Second, because of the high survival rate (or low mortality rate) of breast cancer, the study will require long follow-up times of at least 10 years. In a rapidly changing environment in terms of improvements in screening technologies and therapeutic inter­ventions, the avoidance of biases is likely to be very difficult, if not impossible. The use of the number of interval cancers and possible shifts in stage at detection, while appropriately accounting for confounders, would be almost as daunting a task. Third, the imaging detection of cancer is only the first step in many management decisions and interventions that can affect outcome. The appropriate control of biases related to patient management is highly unlikely. The arguments above, in addition to the existing reports to date that show substantial improvements in cancer detection, particularly with the detection of invasive cancers, with a simultaneous reduction in recall rates, support the argument that a randomised trial is neither necessary nor warranted. The current technology might be obsolete by the time results of an appropriately done and analysed randomised trial is made public.

In order to better link the information given by “scientific” papers to the context of daily patients’ reality I suggest to spend some time reviewing few of the videos in the below links:

  1. The following group of videos is featured on a website by Siemens. Nevertheless, the presenting radiologists are leading practitioners who affects thousands of lives every year – What the experts say about tomosynthesis. – click on ECR 2013
  2. Breast Tomosynthesis in Practice – part of a commercial ad of the Washington Radiology Associates featured on the website of Diagnostic Imaging. As well, affects thousands of lives in the Washington area every year.

The pivotal questions yet to be answered are:

  1. What should be done in order to translate increase in sensitivity and early detection into decrease in mortality?

  2. What is the price of such increase in sensitivity in terms of quality of life and health-care costs and is it worth-while to pay?

An article that summarises positively the experience of introducing Tomosynthesis into routine screening practice was recently published on AJR:

Implementation of Breast Tomosynthesis in a Routine Screening Practice: An Observational Study

Stephen L. Rose1, Andra L. Tidwell1, Louis J. Bujnoch1, Anne C. Kushwaha1, Amy S. Nordmann1 and Russell Sexton, Jr.1

Affiliation: 1 All authors: TOPS Comprehensive Breast Center, 17030 Red Oak Dr, Houston, TX 77090.

Citation: American Journal of Roentgenology. 2013;200:1401-1408

 

ABSTRACT :

OBJECTIVE. Digital mammography combined with tomosynthesis is gaining clinical acceptance, but data are limited that show its impact in the clinical environment. We assessed the changes in performance measures, if any, after the introduction of tomosynthesis systems into our clinical practice.

MATERIALS AND METHODS. In this observational study, we used verified practice- and outcome-related databases to compute and compare recall rates, biopsy rates, cancer detection rates, and positive predictive values for six radiologists who interpreted screening mammography studies without (n = 13,856) and with (n = 9499) the use of tomosynthesis. Two-sided analyses (significance declared at p < 0.05) accounting for reader variability, age of participants, and whether the examination in question was a baseline were performed.

RESULTS. For the group as a whole, the introduction and routine use of tomosynthesis resulted in significant observed changes in recall rates from 8.7% to 5.5% (p < 0.001), nonsignificant changes in biopsy rates from 15.2 to 13.5 per 1000 screenings (p = 0.59), and cancer detection rates from 4.0 to 5.4 per 1000 screenings (p = 0.18). The invasive cancer detection rate increased from 2.8 to 4.3 per 1000 screening examinations (p = 0.07). The positive predictive value for recalls increased from 4.7% to 10.1% (p < 0.001).

CONCLUSION. The introduction of breast tomosynthesis into our practice was associated with a significant reduction in recall rates and a simultaneous increase in breast cancer detection rates.

Here are the facts in tables and pictures from this article

Table 1 AJR

Table 2-3 AJR

 

Table 4 AJR

 

p1 ajr

p2 ajr

Other articles related to the management of breast cancer were published on this Open Access Online Scientific Journal:

Automated Breast Ultrasound System (‘ABUS’) for full breast scanning: The beginning of structuring a solution for an acute need!

Introducing smart-imaging into radiologists’ daily practice.

Not applying evidence-based medicine drives up the costs of screening for breast-cancer in the USA.

New Imaging device bears a promise for better quality control of breast-cancer lumpectomies – considering the cost impact

Harnessing Personalized Medicine for Cancer Management, Prospects of Prevention and Cure: Opinions of Cancer Scientific Leaders @ http://pharmaceuticalintelligence.com

Predicting Tumor Response, Progression, and Time to Recurrence

“The Molecular pathology of Breast Cancer Progression”

Personalized medicine gearing up to tackle cancer

What could transform an underdog into a winner?

Mechanism involved in Breast Cancer Cell Growth: Function in Early Detection & Treatment

Nanotech Therapy for Breast Cancer

A Strategy to Handle the Most Aggressive Breast Cancer: Triple-negative Tumors

Breakthrough Technique Images Breast Tumors in 3-D With Great Clarity, Reduced Radiation

Closing the Mammography gap

Imaging: seeing or imagining? (Part 1)

Imaging: seeing or imagining? (Part 2)

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Not applying evidence-based medicine drives up the costs of screening for breast-cancer in the USA

Author: Dror Nir

 

Costs for breast screening are being driven higher by increased use of new imaging technologies such as digital mammography and MRI, workflows incorporating 2nd and 3rd remote-readings as quality control measure, use of computer-aided detection (CAD) applications and growth in aged population.

According to recent publication in JAMA, 40% of the annual spending is for screening women ages 75 and older. Under existing guidelines routine screening is not recommended for this age group since “There is insufficient evidence to assess the benefits and harms of screening mammography”

The study population comprised women of 66 to 100 years old. “Forty-two percent of the women in the study were younger than age 75, and almost 60% of this group had one or more screening mammograms. Women ages 75 to 85 represented 40% of the total; 42% of this group had mammograms. Women 85 years and older represented 18% of the total; only 15% of this group had mammograms. Women with multiple chronic health conditions were much less likely to have a mammogram (26.6%) than healthy women (47.4%).”

“Abstract

The Cost of Breast Cancer Screening in the Medicare Population.

Cary P. Gross, MD; Jessica B. Long, MPH; Joseph S. Ross, MD, MHS; Maysa M. Abu-Khalaf, MD; Rong Wang, PhD; Brigid K. Killelea, MD, MPH; Heather T. Gold, PhD; Anees B. Chagpar, MD, MA, MPH, MSc; Xiaomei Ma, PhD

JAMA Intern Med. 2013;():1-7. doi:10.1001/jamainternmed.2013.1397. Published online January 7, 2013

Background  Little is known about the cost to Medicare of breast cancer screening or whether regional-level screening expenditures are associated with cancer stage at diagnosis or treatment costs, particularly because newer breast cancer screening technologies, like digital mammography and computer-aided detection (CAD), have diffused into the care of older women.

Methods Using the linked Surveillance, Epidemiology, and End Results–Medicare database, we identified 137 274 women ages 66 to 100 years who had not had breast cancer and assessed the cost to fee-for-service Medicare of breast cancer screening and workup during 2006 to 2007. For women who developed cancer, we calculated initial treatment cost. We then assessed screening-related cost at the Hospital Referral Region (HRR) level and evaluated the association between regional expenditures and workup test utilization, cancer incidence, and treatment costs.

Results In the United States, the annual costs to fee-for-service Medicare for breast cancer screening-related procedures (comprising screening plus workup) and treatment expenditures were $1.08 billion and $1.36 billion, respectively. For women 75 years or older, annual screening-related expenditures exceeded $410 million. Age-standardized screening-related cost per beneficiary varied more than 2-fold across regions (from $42 to $107 per beneficiary); digital screening mammography and CAD accounted for 65% of the difference in screening-related cost between HRRs in the highest and lowest quartiles of cost. Women residing in HRRs with high screening costs were more likely to be diagnosed as having early-stage cancer (incidence rate ratio, 1.78 [95% CI, 1.40-2.26]). There was no significant difference in the cost of initial cancer treatment per beneficiary between the highest and lowest screening cost HRRs ($151 vs $115; P = .20).

Conclusions The cost to Medicare of breast cancer screening exceeds $1 billion annually in the fee-for-service program. Regional variation is substantial and driven by the use of newer and more expensive technologies; it is unclear whether higher screening expenditures are achieving better breast cancer outcomes.”

The study is mainly addressing the difference in costs between different regions of referrals. It would be interesting to explore the situation in the age group of 40 to 66 years old.

Written by:  Dr. Dror Nir, PhD.

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Closing the Mammography gap

Author and Curator: Dror Nir, PhD

There are 40 million women seeking mammography breast-screening every year in the USA, out of which 15 million are women with heterogeneously dense or extremely dense breasts. USA epidemiology statistics show that 6 out of 7 missed cancers at mammography occur in women with dense breasts. It is also known that the majority of women presenting with mammography-dense breasts are below 45 years old.

The Oct. 22 issue of the American Journal of Roentgenology ( AJR) publishes results of a study showing that ultrasound is superior to mammography in evaluating symptomatic women 30-39 years of age [1].

This study was conducted by researchers at the Seattle Cancer Alliance and University of Washington. Patients were recruited between January 2002 and August 2006.   954 women ranging from 30 to 39 years old who presented for diagnostic breast imaging evaluation were  examined, and it was found that sensitivity (probability for cancer detection) of ultrasound was 95.7 percent compared to 60.9 percent for mammography. A very important result of this study is the calculated Negative Predictive Value (the probability to have negative pathology if the imaging-test is negative) which was similar for both modalities: 99.9% for ultrasound and 99.2% for mammography.

Show case in images (All images courtesy of the American Roentgen Ray Society.):

35-year-old woman who presented with a palpable left breast lump. Whole-breast craniocaudal (above left) and mediolateral oblique (above right) and spot-magnification craniocaudal (below left) and mediolateral (below right) mammographic images show no abnormality at area of clinical concern, marked by BB.

Zoom-in on the region of interest

Targeted ultrasound image above reveals solid mass with irregular shape and indistinct and angular margins. BI-RADS 5 assessment was made. Histopathology from ultrasound-guided core needle biopsy showed invasive ductal carcinoma.

In regards to which imaging modality should be used when screening such a population, the conclusion of the investigators is very clear: “Ultrasound has high sensitivity (95.7%) and high NPV (99.9%) in this setting and should be the primary imaging modality of choice. The added value of adjunct mammography is low.”

When reading this article I noted a gap to overcome if we want to successfully replace mammography with ultrasound. The Positive Predictive Value (the probability of  detecting a cancer) calculated for ultrasound in these study settings was lower than that calculated for mammography: 13.2% for ultrasound and 18.4% for mammography. This is because mammography detected one additional malignancy in an asymptomatic area in a 32-year-old woman who was subsequently found to have a BRCA2 gene mutation. Mammography could do that because it scans the whole breast, whereas the investigators in this study used ultrasound just for scanning the suspicious lumps. A solution is offered in using the recently introduced ultrasound modalities, which are able to perform automatic full breast ultrasound scans [2], preferably enhanced by real-time tissue characterisation capability – a technology I’m working to develop.

References:

  1. Accuracy and Value of Breast Ultrasound for Primary Imaging Evaluation of Symptomatic Women 30-39 Years of Age,Constance D. Lehman1,2Christoph I. Lee1,2Vilert A. Loving1,2, Michael S. Portillo1,2Sue Peacock1,2 and Wendy B. DeMartini1,2, Oct. 22 issue of the American Journal of Roentgenology
1 Department of Radiology, University of Washington School of Medicine, Seattle WA.
2 Seattle Cancer Care Alliance, G2-600, 825 Eastlake Ave E, Seattle, WA 98109.

2. Using Automated Breast Sonography as Part of a Multimodality Approach to Dense Breast Screening, Vincenzo Giuliano, MD, RDMS, RVT1, Concetta Giuliano, DO1, Journal of Diagnostic Medical SonographyJuly/August 2012 28: 159-165,

1Novasoutheastern University, Winter Springs, FL, USA
 
 
Written by: Dror Nir, PhD.

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The unfortunate ending of the Tower of Babel construction project and its effect on modern imaging-based cancer patients’ management

The unfortunate ending of the Tower of Babel construction project and its effect on modern imaging-based cancer patients’ management

Curator: Dror Nir, PhD

 

The story of the city of Babel is recorded in the book of Genesis 11 1-9. At that time, everyone on earth spoke the same language.

Picture: Pieter Bruegel the Elder: The Tower of Babel_(Vienna)

It is probably safe to assume that medical practitioners at that time were reporting the status of their patients in a standard manner. Although not mentioned, one might imagine that, at that time, ultrasound or MRI scans were also reported in a standard and transferrable manner. The people of Babel noticed the potential in uniform communication and tried to build a tower so high that it would  reach the gods. Unfortunately, God did not like that, so he went down (in person) and confounded people’s speech, so that they could not understand each another. Genesis 11:7–8.

This must be the explanation for our inability to come to a consensus on reporting of patients’ imaging-outcome. Progress in development of efficient imaging protocols and in clinical management of patients is withheld due to high variability and subjectivity of clinicians’ approach to this issue.

Clearly, a justification could be found for not reaching a consensus on imaging protocols: since the way imaging is performed affects the outcome, (i.e. the image and its interpretation) it takes a long process of trial-and-error to come up with the best protocol.  But, one might wonder, wouldn’t the search for the ultimate protocol converge faster if all practitioners around the world, who are conducting hundreds of clinical studies related to imaging-based management of cancer patients, report their results in a standardized and comparable manner?

Is there a reason for not reaching a consensus on imaging reporting? And I’m not referring only to intra-modality consensus, e.g. standardizing all MRI reports. I’m referring also to inter-modality consensus to enable comparison and matching of reports generated from scans of the same organ by different modalities, e.g. MRI, CT and ultrasound.

As developer of new imaging-based technologies, my personal contribution to promoting standardized and objective reporting was the implementation of preset reporting as part of the prostate-HistoScanning product design. For use-cases, as demonstrated below, in which prostate cancer patients were also scanned by MRI a dedicated reporting scheme enabled matching of the HistoScanning scan results with the prostate’s MRI results.

The MRI reporting scheme used as a reference is one of the schemes offered in a report by Miss Louise Dickinson on the following European consensus meeting : Magnetic Resonance Imaging for the Detection, Localisation, and Characterisation of Prostate Cancer: Recommendations from a European Consensus Meeting, Louise Dickinson a,b,c,*, Hashim U. Ahmed a,b, Clare Allen d, Jelle O. Barentsz e, Brendan Careyf, Jurgen J. Futterer e, Stijn W. Heijmink e, Peter J. Hoskin g, Alex Kirkham d, Anwar R. Padhani h, Raj Persad i, Philippe Puech j, Shonit Punwani d, Aslam S. Sohaib k, Bertrand Tomball,Arnauld Villers m, Jan van der Meulen c,n, Mark Emberton a,b,c,

http://www.europeanurology.com/article/S0302-2838(10)01187-5

Image of MRI reporting scheme taken from the report by Miss Louise Dickinson

The corresponding HistoScanning report is following the same prostate segmentation and the same analysis plans:


Preset reporting enabling matching of HistoScanning and MRI reporting of the same case.

It is my wish that already in the near-future, the main radiology societies (RSNA, ESR, etc..) will join together to build the clinical Imaging’s “Tower of Babel” to effectively address the issue of standardizing reporting of imaging procedures. This time it will not be destroyed…:-)

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Knowing the tumor’s size and location, could we target treatment to THE ROI by applying imaging-guided intervention?

Knowing the tumor’s size and location, could we target treatment to THE ROI by applying imaging-guided intervention?

Author: Dror Nir, PhD

Advances in techniques for cancer lesions’ detection and localisation [1-6] opened the road to methods of localised (“focused”) cancer treatment [7-10].  An obvious challenge on the road is reassuring that the imaging-guided treatment device indeed treats the region of interest and preferably, only it.

A step in that direction was taken by a group of investigators from Sunnybrook Health Sciences Centre, University of Toronto, Ontario, Canada who evaluate the feasibility and safety of magnetic resonance (MR) imaging–controlled transurethral ultrasound therapy for prostate cancer in humans [7]. Their study’s objective was to prove that using real-time MRI guidance of HIFU treatment is possible and it guarantees that the location of ablated tissue indeed corresponds to the locations planned for treatment. Eight eligible patients were recruited.

 

The setup

 

Treatment protocol

 

The result

 

“There was excellent agreement between the zone targeted for treatment and the zone of thermal injury, with a targeting accuracy of ±2.6 mm. In addition, the temporal evolution of heating was very consistent across all patients, in part because of the ability of the system to adapt to changes in perfusion or absorption properties according to the temperature measurements along the target boundary.”

 

Technological problems to be resolved in the future:

“Future device designs could incorporate urinary drainage during the procedure, given the accumulation of urine in the bladder during treatment.”

“Sufficient temperature resolution could be achieved only by using 10-mm-thick sections. Our numeric studies suggest that 5-mm-thick sections are necessary for optimal three-dimensional conformal heating and are achievable by using endorectal imaging coils or by performing the treatment with a 3.0-T platform.”

Major limitation: “One of the limitations of the study was the inability to evaluate the efficacy of this treatment; however, because this represents, to our knowledge, the first use of this technology in human prostate, feasibility and safety were emphasized. In addition, the ability to target the entire prostate gland was not assessed, again for safety considerations. We have not attempted to evaluate the effectiveness of this treatment for eradicating cancer or achieving durable biochemical non-evidence of disease status.”

References

  1. SIMMONS (L.A.M.), AUTIER (P.), ZATURA (F.), BRAECKMAN (J.G.), PELTIER (A.), ROMICS (I.), STENZL (A.), TREURNICHT (K.), WALKER (T.), NIR (D.), MOORE (C.M.), EMBERTON (M.). Detection, localisation and characterisation of prostate cancer by Prostate HistoScanning.. British Journal of Urology International (BJUI). Issue 1 (July). Vol. 110, Page(s): 28-35
  2. WILKINSON (L.S.), COLEMAN (C.), SKIPPAGE (P.), GIVEN-WILSON (R.), THOMAS (V.). Breast HistoScanning: The development of a novel technique to improve tissue characterization during breast ultrasound. European Congress of Radiology (ECR), A.4030, C-0596, 03-07/03/2011.
  3. Hebert Alberto Vargas, MD, Tobias Franiel, MD,Yousef Mazaheri, PhD, Junting Zheng, MS, Chaya Moskowitz, PhD, Kazuma Udo, MD, James Eastham, MD and Hedvig Hricak, MD, PhD, Dr(hc) Diffusion-weighted Endorectal MR Imaging at 3 T for Prostate Cancer: Tumor Detection and Assessment of Aggressiveness. June 2011 Radiology, 259,775-784.
  4. Wendie A. Berg, Kathleen S. Madsen, Kathy Schilling, Marie Tartar, Etta D. Pisano, Linda Hovanessian Larsen, Deepa Narayanan, Al Ozonoff, Joel P. Miller, and Judith E. Kalinyak Breast Cancer: Comparative Effectiveness of Positron Emission Mammography and MR Imaging in Presurgical Planning for the Ipsilateral Breast Radiology January 2011 258:1 59-72.
  5. Anwar R. Padhani, Dow-Mu Koh, and David J. Collins Reviews and Commentary – State of the Art: Whole-Body Diffusion-weighted MR Imaging in Cancer: Current Status and Research Directions Radiology December 2011 261:3 700-718
  6. Eggener S, Salomon G, Scardino PT, De la Rosette J, Polascik TJ, Brewster S. Focal therapy for prostate cancer: possibilities and limitations. Eur Urol 2010;58(1):57–64).
  7. Rajiv Chopra, PhD, Alexandra Colquhoun, MD, Mathieu Burtnyk, PhD, William A. N’djin, PhD, Ilya Kobelevskiy, MSc, Aaron Boyes, BSc, Kashif Siddiqui, MD, Harry Foster, MD, Linda Sugar, MD, Masoom A. Haider, MD, Michael Bronskill, PhD and Laurence Klotz, MD. MR Imaging–controlled Transurethral Ultrasound Therapy for Conformal Treatment of Prostate Tissue: Initial Feasibility in Humans. October 2012 Radiology, 265,303-313.
  8. Black, Peter McL. M.D., Ph.D.; Alexander, Eben III M.D.; Martin, Claudia M.D.; Moriarty, Thomas M.D., Ph.D.; Nabavi, Arya M.D.; Wong, Terence Z. M.D., Ph.D.; Schwartz, Richard B. M.D., Ph.D.; Jolesz, Ferenc M.D.  Craniotomy for Tumor Treatment in an Intraoperative Magnetic Resonance Imaging Unit. Neurosurgery: September 1999 – Volume 45 – Issue 3 – p 423
  9. Medel, Ricky MD,  Monteith, Stephen J. MD, Elias, W. Jeffrey MD, Eames, Matthew PhD, Snell, John PhD, Sheehan, Jason P. MD, PhD, Wintermark, Max MD, MAS, Jolesz, Ferenc A. MD, Kassell, Neal F. MD. Neurosurgery: Magnetic Resonance–Guided Focused Ultrasound Surgery: Part 2: A Review of Current and Future Applications. October 2012 – Volume 71 – Issue 4 – p 755–763
  10. Bruno Quesson PhD, Jacco A. de Zwart PhD, Chrit T.W. Moonen PhD. Magnetic resonance temperature imaging for guidance of thermotherapy. Journal of Magnetic Resonance Imaging, Special Issue: Interventional MRI, Part 1, Volume 12, Issue 4, pages 525–533, October 2000

Writer: Dror Nir, PhD

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