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New development in measuring mechanical properties of tissue

Posted in Health Economics and Outcomes Research, Imaging-based Cancer Patient Management, Medical Devices R&D and Inventions, Medical Devices R&D Investment, Medical Imaging Technology, Image Processing/Computing, MRI, CT, Nuclear Medicine, Ultra Sound, Personalized and Precision Medicine & Genomic Research, Population Health Management, Genetics & Pharmaceutical, Regulated Clinical Trials: Design, Methods, Components and IRB related issues, Technology Transfer: Biotech and Pharmaceutical, tagged Cancer - General, Clinical trial, elastography, health, Magnetic resonance imaging, magnetic resonance imaging mri, OCT, research, science, tissue, tissue differentiation on February 22, 2013| Leave a Comment »

New development in measuring mechanical properties of tissue

Author – Writer: Dror Nir, PhD

• 

Measuring the effects induced onto imaging by the mechanical properties of tissue is a common approach to differentiate tissue abnormalities. In previous posts I discussed the applicability of imaging applications that visualize variations in tissue stiffness; e.g. ultrasound-elastography and MRI-elastography as aid in the diagnosis workflow of cancer. Today, I would like to report on a recent publication made in SPIE Newsroom describing an optical-imaging system to measure tissue stiffness at high resolution. I think that such emerging technologies should be followed up as they bear promise to bridge deficiencies of the traditional modalities currently in use.

Reporting on: Optical elastography probes mechanical properties of tissue at high resolution

By: David Sampson, Kelsey Kennedy, Robert McLaughlin and Brendan Kennedy

Information published at: SPIE Newsroom – Biomedical Optics & Medical Imaging

Probing the micro-mechanical properties of tissue using optical imaging might offer new surgical tools that enable improved differentiation of tissue pathologies, such as cancer or atherosclerosis.

11 January 2013, SPIE Newsroom. DOI: 10.1117/2.1201212.004605

Elastography is an emerging branch of medical imaging that uses mechanical contrast to better characterize tissue pathology than can be achieved with structural imaging alone. It achieves this by imaging a tissue’s response to mechanical loading. Although commercial products based on ultrasonography and magnetic resonance imaging (MRI) have been available for several years, these new modalities offer superior tissue differentiation deep in the human body. However, elastography is limited by its low resolution compared with the length scales relevant to many diseases. Increasing the resolution with optical techniques might offer new opportunities for elastography in medical imaging and surgical guidance.

An elastography system requires a means of loading the tissue to cause deformation and an imaging system with sufficient sensitivity and range to capture this deformation. Implicit in these requirements is access to the tissue of interest. Optical elastography has previously been largely based on schemes that suit small tissue samples rather than intact tissue in living humans. Additionally, such schemes have not had the sensitivity or range to produce high-fidelity images of mechanical properties. We have addressed both these issues in our recent work, developing the means to access tissues in vivo and improve the sensitivity and range of optical elastography using phase-sensitive optical coherence tomography as the underlying modality. The use of optical coherence tomography to perform elastography has come to be referred to as optical coherence elastography.¹

To make optical coherence elastography on human subjects feasible, we designed an annular piezoelectric loading transducer (see Figure 1), through which we could simultaneously image, enabling the first in vivo dynamic optical coherence elastography on human subjects.² We were subsequently able to extend this to three dimensions (see Figure 2), in collaboration with Stephen Boppart’s group at the University of Illinois at Urbana-Champaign.³ This extension took advantage of the high speed of spectral-domain optical coherence tomography, and the maturity of phase-sensitive detection techniques originally developed for Doppler flowmetry and microangiography.

 

Figure 1. Schematic (left) and photograph (right) of the annular load transducer and imaging optics for in vivo optical coherence elastography.

 

Figure 2. 2D images of in vivo human skin selected from 3D stacks. (a) Optical coherence tomography image and (b) the same image overlaid by the 2D dynamic elastogram recorded at 125Hz load frequency, highlighting the greater strain in the epidermis. Reprinted in modified form with permission.³

For general access to tissues in the body, optical coherence elastography faces two basic limitations. The free-space probe requires miniaturization for versatile access to tissue in confined or convoluted geometries. We addressed this in studies of the elastic properties of human airways using catheter-based anatomical optical coherence tomography.⁴

 

Figure 3. (a) Schematic diagram of needle optical coherence elastography. The phase difference Δφ=φ₁– φ₂ determines the displacement, d, when scaled by the wavelength, λ, and refractive index, n. (b) Needle and pig trachea. (c) Local displacement versus distance, with tissue boundaries indicated by red stars. (d) Representative histology. Reprinted in modified form with permission.⁶

More fundamentally, optical coherence tomography can only penetrate, at best, 1–2mm into most tissues, limiting it to superficial applications. To address this issue, we combined optical coherence elastography with needle probes, an active research area in our group (see Figure 3).⁵ We conveniently use the needle probe itself to deform the tissue during insertion.⁶ The deformation ahead of the needle tip depends on the mechanical properties of the tissue encountered, as well as on the nearby tissue environment, particularly on any interfaces ahead of it. We measure the local sub-micrometer displacement of the tissue between two positions of the moving needle probe. We plot this displacement versus distance ahead of the probe: see Figure 3(c). The slope of the displacement at location z is a measure of the local strain. A change in slope signifies a change in tissue stiffness; the steeper the slope, the softer the tissue (other things being equal). Figure 3 highlights this effect in a layered sample of pig trachea. The positions of the changes in slope correlate well with the tissue interfaces shown in the accompanying histology: see Figure 3(d).

The other key area of improvement we have focused on is lowering the optical coherence elastography noise floor by increasing the detection sensitivity, which is vital to make clinical imaging practical. We firstly showed that Gaussian-smoothed, weighted-least squares strain estimation improved the sensitivity of estimates by up to 12dB over conventional finite-difference methods.⁷ Next, we showed that performance could be further improved at low optical coherence tomo- graphy signal-to-noise ratios (and, therefore, at greater depths in tissue) by employing a 2D Fourier transform technique.⁸Combined with other system refinements, these improvements have enabled us to reach a displacement sensitivity of 300pm for typical optical coherence tomography signal-to-noise ratios in tissue, with room for improvement.

The Young’s modulus of soft tissue varies from kPa to tens of MPa, whereas the scattering coefficient of such tissues—which is largely responsible for determining the contrast of optical coherence tomography—is typically in the range 2–20mm⁻¹. This apparent native advantage in mechanical over optical contrast (see the example in Figure 4), combined with the maturation of optical coherence elastography methods, bodes well for the future. In our group, we are pursuing tumor-margin identification using elastography; others have begun to consider corneal elastography,^{9, 10} and still others are examining shear wave schemes with the aim of probing Young’s modulus much deeper in tissues.^11,12

 

Figure 4. Optical coherence tomography (a) and optical coherence elastography (b) images of the same phantom with two inclusions visible, showing enhanced mechanical over scattering contrast.

Optical elastography currently sits at a similar stage of development as ultrasound elastography did in 1999. Based on a similar trajectory, this field will rapidly expand over the next decade. Our recent results point to the first convincing applications of optical elastography being just around the corner.

We acknowledge funding for this work from Perpetual Trustees, the Raine Medical Research Foundation, the Cancer Council of Western Australia, the Australian Research Council, the National Health and Medical Research Council (Australia), and the National Breast Cancer Foundation (Australia).

---

David Sampson

Optical+Biomedical Engineering Laboratory
School of Electrical, Electronic and Computer Engineering

and
Centre for Microscopy, Characterisation and Analysis
The University of Western Australia

 

Perth, Australia

Kelsey Kennedy, Robert McLaughlin, Brendan Kennedy

Optical+Biomedical Engineering Laboratory
School of Electrical, Electronic and Computer Engineering
The University of Western Australia

Perth, Australia

---

References:

1. J. Schmitt, OCT elastography: imaging microscopic deformation and strain of tissue, Opt. Express 3(6), p. 199-211, 1998.doi:10.1364/OE.3.000199

2. B. F. Kennedy, T. R. Hillman, R. A. McLaughlin, B. C. Quirk, D. D. Sampson, In vivo dynamic optical coherence elastography using a ring actuator, Opt. Express 17(24), p. 21762-21772, 2009.doi:10.1364/OE.17.021762

3. B. F. Kennedy, X. Liang, S. G. Adie, D. K. Gerstmann, B. C. Quirk, S. A. Boppart, D. D. Sampson, In vivo three-dimensional optical coherence elastography, Opt. Express 19(7), p. 6623-6634, 2011.doi:10.1364/OE.19.006623

4. J. P. Williamson, R. A. McLaughlin, W. J. Noffsingerl, A. L. James, V. A. Baker, A. Curatolo, J. J. Armstrong, Elastic properties of the central airways in obstructive lung diseases measured using anatomical optical coherence tomography, Am. J. Resp. Crit. Care 183(5), p. 612-619, 2011.doi:10.1164/rccm.201002-0178OC

5. R. A. McLaughlin, B. C. Quirk, A. Curatolo, R. W. Kirk, L. Scolaro, D. Lorenser, P. D. Robbins, B. A. Wood, C. M. Saunders, D. D. Sampson, Imaging of breast cancer with optical coherence tomography needle probes: Feasibility and initial results, IEEE J. Sel. Topics Quantum Electron. 18(3), p. 1184-1191, 2012. doi:10.1109/JSTQE.2011.2166757

6. K. M. Kennedy, B. F. Kennedy, R. A. McLaughlin, D. D. Sampson, Needle optical coherence elastography for tissue boundary detection, Opt. Lett. 37(12), p. 2310-2312, 2012. doi:10.1364/OL.37.002310

7. B. F. Kennedy, S. H. Koh, R. A. McLaughlin, K. M. Kennedy, P. R. T. Munro, D. D. Sampson, Strain estimation in phase-sensitive optical coherence elastography, Biomed. Opt. Express 3(8), p. 1865-1879, 2012.doi:10.1364/BOE.3.001865

8. B. F. Kennedy, M. Wojtkowski, M. Szkulmowski, K. M. Kennedy, K. Karnowski, D. D. Sampson, Improved measurement of vibration amplitude in dynamic optical coherence elastography, Biomed. Opt. Express 3(12), p. 3138-3152, 2012. doi:10.1364/BOE.3.003138

9. R. K. Manapuram, S. R. Aglyamov, F. M. Monediado, M. Mashiatulla, J. Li, S. Y. Emelianov, K. V. Larin, In vivo estimation of elastic wave parameters using phase-stabilized swept source optical coherence elastography, J. Biomed. Opt. 17(10), p. 100501, 2012.doi:10.1117/1.JBO.17.10.100501

10. W. Qi, R. Chen, L. Chou, G. Liu, J. Zhang, Q. Zhou, Z. Chen, Phase-resolved acoustic radiation force optical coherence elastography, J. Biomed. Opt. 17(11), p. 110505, 2012. doi:10.1117/1.JBO.17.11.110505

11. C. Li, G. Guan, S. Li, Z. Huang, R. K. Wang, Evaluating elastic properties of heterogeneous soft tissue by surface acoustic waves detected by phase-sensitive optical coherence tomography, J. Biomed. Opt. 17(5), p. 057002, 2012. doi:10.1117/1.JBO.17.5.057002

12. M. Razani, A. Mariampillai, C. Sun, T. W. H. Luk, V. X. D. Yang, M. C. Kolios, Feasibility of optical coherence elastography measurements of shear wave propagation in homogeneous tissue equivalent phantoms,Biomed. Opt. Express 3(5), p. 972-980, 2012. doi:10.1364/BOE.3.00097

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Imaging: seeing or imagining? (Part 1)

Posted in Bio Instrumentation in Experimental Life Sciences Research, CANCER BIOLOGY & Innovations in Cancer Therapy, Health Economics and Outcomes Research, Health Law & Patient Safety, Imaging-based Cancer Patient Management, Medical Devices R&D Investment, tagged blinded biopsies, breast biopsy, breast cancer, breast screening, Cancer - General, Cancer screening, contrast enhanced ultrasound imaging, diagnostic sonography, elastography, Food and Drug Administration, health, histoscanning, medical ultrasonography, medicine, prostate hisoscanning, systematic prostate biopsies, ultrasound histoscan, ultrasound image, ultrasound imaging on September 10, 2012| 11 Comments »

Imaging: seeing or imagining? (Part 1)

Author and Curator: Dror Nir, PhD

• 

That is the question…

We are all used to clichés such as “seeing is believing”, “seeing is knowing”, “don’t be blind” and so on. Out of our seven (natural and supernatural) senses we tend to use and trust our eyes the most. Especially, when it comes to learning, accumulation of experience and acceptance of information as correct. On the other hand, we are taught from childhood to be aware of illusions and not to judge according to looks but rather according to matter. The problem is, does one recognise the substance inside an image? To answer this, a wide-ranging discipline of image interpretation was developed alongside with imaging technology. In order not to fatigue the innocent reader, I’ll review the state of the art of imaging in medicine in subsequent posts, each dedicated to a specific modality. This post is dedicated to…

Current main trends in ultrasound imaging in cancer patients’ management;

The most used imaging modality in medicine is ultrasound. This is due to the fact that it is noninvasive, practically harmless, relatively inexpensive and fairly accessible; i.e. everyone can operate it, even a layman! No formal training or certification is required!

Interesting enough, ultrasound is labeled by the regulatory agencies, FDA and CE, as a diagnostic medical device! This is real demonstration of the aforementioned tendency to believe our eyes, even if these eyes do not see well or the brain behind them is lacking the experience required for ultrasound image interpretation.

Since “ultrasound imaging in medicine” is the subject of many text books and articles I found it  appropriate, for the sake of this post, simply  to refer the reader to Wikipedia’s page (http://en.wikipedia.org/wiki/Medical_ultrasonography) on ultrasound in medicine: “Diagnostic Sonography (ultrasonography) is an ultrasound-based diagnostic imaging technique used for visualizing subcutaneous body structures including tendons, muscles, joints, vessels and internal organs for possible pathology or lesions. Obstetric sonography is commonly used during pregnancy and is widely recognized by the public. In physics, the term “ultrasound” applies to all sound waves with a frequency above the audible range of normal human hearing, about 20 kHz. The frequencies used in diagnostic ultrasound are typically between 2 and 18 MHz.”

When it comes to cancer patients’ management, ultrasound provides real-time imaging of body organs at a relatively cost effective workflow. However, it suffers from lack of sensitivity and specificity, especially if the investigator is still fairly inex­perienced. Therefore, no diagnosis is confirmed without biopsy of the suspected lesion discovered during the ultrasound scan. As mentioned in my previous post; identification of suspicious lesions in the prostate during TRUS is so inconclusive that in order to reach diagnosis biopsies are taken randomly.

Did we hit the target?

To improve prostate cancer detection, various biopsy strategies to increase the diagnostic yield of prostate biopsy have been devised: sampling of visually abnormal areas; more lateral placement of biopsies; anterior biop­sies; and obtaining an increased number of cores, with up to 45 biopsy cores [1-5].

In recent years, new features such as 3D and contrast-enhanced sonography, elastography and HistoScanning were added to the basic video image in order to improve the quality of ultrasound based investiga­tion of cancer patients.

3-D Sonography.

3-D ultrasound allows si­multaneous biplanar imaging of the organ with com­puter reconstructions providing a coronal plane as well as a rendered 3-D image. This promises to improve the detection and pre-clinical grading of cancer lesions. Still, the interpretation is very much “image quality” and “user experience” dependent.

3D imaging of breast using ABUS by Siemens; using the coronal view to better investigate a lesion.

  

 

3D imaging of breast using Voluson 730 by GE; three planes are presented for review by the radiologist.

 

 

 Contrast-Enhanced Sonography.

Using intravenous micro-bubble agents in combination with color and pow­er Doppler imaging contributes to increase in the signal obtained in areas of increased vascularity. The underlying assumption is that vascularization in the tumor’s area will be more pronounced than in normal tissue. Hot off the press: The UK National Institute for Health and Clinical Excellence (NICE) has published guidance that supports the use of contrast-enhanced ultrasound with Bracco’s SonoVue ultrasound contrast agent for the diagnosis of liver cancer [6].  The main use of contrast-enhanced ultrasound is directing biopsies to the “most suspicious” areas; i.e. those who presents higher vascularity. Never­theless, in reported clinical studies [7] targeted biopsies’ sensitivity on contrast-enhanced ultrasound was only 68%.

 

Elastography.

Elastography is an imaging technique that evaluates the elasticity of the tissue. The underlying assumption is that tumors present greater stiffness than normal tissue and therefore will be characterized by limited compressibility. The first person to introduce this concept was  Professor Jonathan Ophir, University of Huston, Texas [http://www.uth.tmc.edu/schools/med/rad/elasto/]:
Estimation of differences in lesions’ stiffness relies  on computing the level of correlation between consecutive imaging frames while the tissue that is being imaged is subjected to changing compression, usually applied by the sonographer who manipulates the ultrasound probe. Since malignant and benign lesions exhibit similar elasticity, elastography is not suitable for lesion characterisation. Therefore, as in the previous example, elastography’s main use is identifying suspicious areas in which to take biopsies [8, 9].  Furthermore, users’ experiences related to elastography reveal a lot of controversy.  For example, according to Prof. Bruno Fornage of MD. Anderson [http://www.auntminnie.com/index.aspx?sec=sup&sub=wom&pag=dis&ItemID=99028]; “current commercially available scanners are confounded by a lack of intraobserver reliability, so that it’s not unusual to produce an opposite result on repeat testing a few seconds later”. “There are very few evidence-based non-industry sponsored studies reporting substantial superiority [of elastography] over standard grayscale ultrasound,” he said. “In fact, a sensitivity of 82% in the diagnosis of breast cancer has been reported for elastography, versus 94% for conventional grayscale ultrasound. More disturbing is that even if the technology of elastography worked flawlessly, the huge overlap in breast pathology between very firm solid benign lesions and less firm malignancies gives this technology no practical place in the differential diagnosis of solid breast masses.”

 

HistoScanning.

HistoScanning™ is a novel ultrasound-based software technology that utilizes advanced tissue characterization algorithms to address the clinical requirements for tissue characterization. It visualizes the position and extent of tissue suspected of being malignant in the target organ. In this respect its design is unique and superior to other ultrasound based-technologies [10, 11]. HistoScanning’s first clinically available application (since 2009) is in the management of prostate cancer patients.

 

 

HistoScanning indicating suspicious lesions superimposed on 3-D ultrasound of the prostate. The three imaging plans and 3D reconstruction of the segmented prostate are presented.

 

 

 To conclude; if we are looking to improve the current state of the art in ultrasound-based cancer patients’ management we should strive to introduce systems which will enable the medical practitioners to rule in or rule out suspicious lesions at imaging before they biopsy them. Using ultrasound just as a tool for directing biopsies as done today is not enough. Indeed, this requires capability of ultrasound-based tissue characterisation in addition to detection of ultrasound-based abnormality (i.e. circumstantial evidence for cancer). To-date, the only available system that bears the promise to provide such improvement is HistoScanning. Obviously, the level of confidence in the Negative Predictive Value of HistoScanning and future systems alike must be built to become high enough to provide the medical practitioner the reassurance and comfort that he is not missing any significant cancer by not taking a biopsy. Such confidence can only be built by subjecting these systems (i.e. HistoScanning and alike) to properly designed clinical studies and, not less important, by reporting the experience of early adopters who will test them in a controlled routine use.

 

References

1. Flanigan RC, Catalona WJ, Richie JP, Ah-mann FR, Hudson MA, Scardino PT, de-Kernion JB, Ratliff TL, Kavoussi LR, Dalkin BL: Accuracy of digital rectal examination and transrectal ultrasonography in localiz­ing prostate cancer: results of a multicenter clinical trial of 6,630 men. J Urol 1994; 152: 1506–1509.
2. Eichler K, Hempel S, Wilby J, Myers L, Bach­mann LM, Kleijnen J: Diagnostic value of systematic biopsy methods in the investiga­tion of prostate cancer: a systematic review. J Urol 2006; 175: 1605–1612.
3. Delongchamps NB, de la Roza G, Jones R, Jumbelic M, Haas GP: Saturation biopsies on autopsied prostates for detecting and charac­terizing prostate cancer. BJU Int 2009; 10: 49–54.
4. Rifkin MD, Dähnert W, Kurtz AB: State of the art: endorectal sonography of prostate gland. AJR Am J Roentgenol 1990; 154: 691– 700.
5. Chrouser KL, Lieber MM: Extended and sat­uration needle biopsy. Curr Urol Rep 2004; 5: 226–230.
6. http://www.auntminnieeurope.com/index.aspx?sec=nws&sub=rad&pag=dis&ItemID=607068&wf=284
7. Yi A, Kim JK, Park SH, Kim KW, Kim HS, Kim JH, Eun HW, Cho KS: Contrast-en­hanced sonography for prostate cancer de­tection in patients with indeterminate clini­cal findings. Am J Roentgenol 2006; 186: 1431–1435.
8. König K, Scheipers U, Pesavento A, Lorenz A, Ermert H, Senge T: Initial experiences with real-time elastography guided biopsies of the prostate. J Urol 2005; 174: 115–117.
9. 32 Pallwein L, Mitterberger M, Struve P, Hor-ninger W, Aigner F, Bartsch G, Gradl J, Schurich M, Pedross F, Frauscher F: Com­parison of sonoelastography guided biopsy with systematic biopsy: impact on prostate cancer detection. Eur Radiol 2007; 17: 2278– 2285.
10. SALOMON (G.), SPETHMANN (J.), BECKMANN (A.), AUTIER (P.), MOORE (C.), DURNER (L.), SANDMANN (M.), HASE (A.), SCHLOMM (T.), MICHL (U.), HEINZER (H.), GRAFEN (M.), STEUBER (T.).Accuracy of HistoScanning for the prediction of a negative surgical margin in patients undergoing radical prostatectomy. Published online in British Journal of Urology International (BJUI). 09/08/2012.
11. SIMMONS (L.A.M.), AUTIER (P.), ZATURA (F.), BRAECKMAN (J.G.), PELTIER (A.), ROMICS (I.), STENZL (A.), TREURNICHT (K.), WALKER (T.), NM (D.), MOORE (C.M.), EMBERTON (M.).  Detection, localisation and characterisation of prostate cancer by Prostate Hist°Scanning; Published in British Journal of Urology International (BJUI). Issue 1 (July). Vol 110, P 28-35.

 

 Written by Dror Nir

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The Incentive for “Imaging based cancer patient’ management”

Posted in Bio Instrumentation in Experimental Life Sciences Research, Biomarkers & Medical Diagnostics, CANCER BIOLOGY & Innovations in Cancer Therapy, Cell Biology, Signaling & Cell Circuits, FDA Regulatory Affairs, Health Economics and Outcomes Research, HealthCare IT, Imaging-based Cancer Patient Management, International Global Work in Pharmaceutical, Medical Devices R&D Investment, Personalized and Precision Medicine & Genomic Research, Pharmaceutical R&D Investment, Population Health Management, Genetics & Pharmaceutical, Scientist: Career considerations, Statistical Methods for Research Evaluation, Technology Transfer: Biotech and Pharmaceutical, tagged breast cancer, breast cancer mortality, breast cancer screening, breast thermography, Cancer - General, Cancer screening, cancer tumours, Cardiac surgery, Chemotherapy, Clinical trial, Conditions and Diseases, costs of treatment, Diagnosis, early diagnosis, elastography, evidence based medicine, health, health economics, histoscanning, imaging based cancer detection, imaging ultrasound, innovations in cancer detection, Magnetic resonance imaging, mammography, medicine, National Institutes of Health, New England Journal of Medicine, new methods for cancer detection, Proceedings of the National Academy of Sciences of the United States of America, Prostate cancer, Prostate cancer screening, research, science, smart imaging, tissue characterisation, ultrasound based cancer detection, United States on August 27, 2012| 15 Comments »

The Incentive for “Imaging based cancer patient’ management”

Author and Curator: Dror Nir, PhD

• 

Image taken from http://www.breastthermography.com/breast_thermography_mf.htm

It is generally agreed by radiologists and oncologists that in order to provide a comprehensive work-flow that complies with the principles of personalized medicine, future cancer patients’ management will heavily rely on “smart imaging” applications. These could be accompanied by highly sensitive and specific bio-markers, which are expected to be delivered by pharmaceutical companies in the upcoming decade. In the context of this post, smart imaging refers to imaging systems that are enhanced with tissue characterization and computerized image interpretation applications. It is expected that such systems will enable gathering of comprehensive clinical information on cancer tumors, such as location, size and rate of growth.

What is the main incentive for promoting cancer patients’ management based on smart imaging? 

It promises to enable personalized cancer patient management by providing the medical practitioner with a non-invasive and non-destructive tool to detect, stage and follow up cancer tumors in a standardized and reproducible manner. Furthermore, applying smart imaging that provides valuable disease-related information throughout the management pathway of cancer patient will eventually result in reducing the growing burden of health-care costs related to cancer patients’ treatment.

Let’s briefly review the segments that are common to all cancer patients’ pathway: screening, treatment and costs.

 

Screening for cancer: It is well known that one of the important factors in cancer treatment success is the specific disease staging. Often this is dependent on when the patient is diagnosed as a cancer patient. In order to detect cancer as early as possible, i.e. before any symptoms appear, leaders in cancer patients’ management came up with the idea of screening. To date, two screening programs are the most spoken of: the “officially approved and budgeted” breast cancer screening; and the unofficial, but still extremely costly, prostate cancer screening. After 20 years of practice, both are causing serious controversies:

In trend analysis of WHO mortality data base [1], the authors, Autier P, Boniol M, Gavin A and Vatten LJ, argue that breast cancer mortality in neighboring European countries with different levels of screening but similar access to treatment is the same: “The contrast between the time differences in implementation of mammography screening and the similarity in reductions in mortality between the country pairs suggest that screening did not play a direct part in the reductions in breast cancer mortality”.

In prostate cancer mortality at 11 years of follow-up [2],  the authors,Schröder FH et. al. argue regarding prostate cancer patients’ overdiagnosis and overtreatment: “To prevent one death from prostate cancer at 11 years of follow-up, 1055 men would need to be invited for screening and 37 cancers would need to be detected”.

The lobbying campaign (see picture below)  that AdmeTech (http://www.admetech.org/) is conducting in order to raise the USA administration’s awareness and get funding to improve prostate cancer treatment is a tribute to patients’ and practitioners’ frustration.

 

 

 

Treatment: Current state of the art in oncology is characterized by a shift in  the decision-making process from an evidence-based guidelines approach toward personalized medicine. Information gathered from large clinical trials with regard to individual biological cancer characteristics leads to a more comprehensive understanding of cancer.

Quoting from the National cancer institute (http://www.cancer.gov/) website: “Advances accrued over the past decade of cancer research have fundamentally changed the conversations that Americans can have about cancer. Although many still think of a single disease affecting different parts of the body, research tells us through new tools and technologies, massive computing power, and new insights from other fields that cancer is, in fact, a collection of many diseases whose ultimate number, causes, and treatment represent a challenging biomedical puzzle. Yet cancer’s complexity also provides a range of opportunities to confront its many incarnations”.

Personalized medicine, whether it uses cytostatics, hormones, growth inhibitors, monoclonal antibodies, and loco-regional medical devices, proves more efficient, less toxic, less expensive, and creates new opportunities for cancer patients and health care providers, including the medical industry.

To date, at least 50 types of systemic oncological treatments can be offered with much more quality and efficiency through patient selection and treatment outcome prediction.

Figure taken from presentation given by Prof. Jaak Janssens at the INTERVENTIONAL ONCOLOGY SOCIETY meeting held in Brussels in October 2011

For oncologists, recent technological developments in medical imaging-guided tissue acquisition technology (biopsy) create opportunities to provide representative fresh biological materials in a large enough quantity for all kinds of diagnostic tests.

 

Health-care economics: We are living in an era where life expectancy is increasing while national treasuries are over their limits in supporting health care costs. In the USA, of the nation’s 10 most expensive medical conditions, cancer has the highest cost per person. The total cost of treating cancer in the U.S. rose from about $95.5 billion in 2000 to $124.6 billion in 2010, the National Cancer Institute (www.camcer.gov) estimates. The true sum is probably higher as this estimate is based on average costs from 2001-2006, before many expensive treatments came out; quoting from www.usatoday.com : “new drugs often cost $100,000 or more a year. Patients are being put on them sooner in the course of their illness and for a longer time, sometimes for the rest of their lives.”

With such high costs at stake, solutions to reduce the overall cost of cancer patients’ management should be considered. My experience is that introducing smart imaging applications into routine use could contribute to significant savings in the overall cost of cancer patients’ management, by enabling personalized treatment choice and timely monitoring of tumors’ response to treatment.

 

 References

1. 1.      BMJ. 2011 Jul 28;343:d4411. doi: 10.1136/bmj.d4411
2. 2.      (N Engl J Med. 2012 Mar 15;366(11):981-90):

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