Reporter: Aviva Lev-Ari, PhD, RN
Can Coronary Artery Anomalies Be Detected on CT Calcium Scoring Studies?
Academic Radiology, 04/11/2013 Review Article
Maddux PT et al. – The purpose of this study is to determine whether coronary artery anomalies can be detected on noncontrast computed tomography (CT) coronary artery calcium scoring (CCS) studies. Benign and malignant coronary artery anomalies can be detected with relatively high accuracy on noncontrast–enhanced CCS studies. CCS studies should be reviewed for signs of coronary artery anomalies in order to identify malignant variants with possible impact on patient management.
Methods
- A total of 126 patients (mean age 62 years; 35 women) underwent noncontrast CCS and contrast enhanced coronary CT angiography (cCTA).
- Thirty–three patients were diagnosed with a coronary anomaly on cCTA, whereas coronary anomalies were excluded in 93.
- Two observers (reader 1 [R1] and reader 2 [R2]), blinded to patient information independently evaluated each CCS study for: 1) visibility of coronary artery origins, 2) detection of coronary anomalies, and 3) benign or malignant (ie, interarterial) course.
- Using cCTA as the reference standard, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of CCS studies for detecting coronary anomalies were calculated.
Results
- Of the 33 coronary anomalies, 16 were benign and 17 malignant.
- Based on noncontrast CCS studies, R1 and R2 correctly identified the left main origin in 123/126 (97.6%) and 121/126 (96%) patients; the left anterior descending origin in 125/126 (99.2%) and 122/126 (96.8%); the circumflex origin in 120/126 (95.2%) and 105/126 (83.3%); and the right coronary artery origin in 117/126 (92.9%) and 103/126 (81.7%), respectively.
- R1 and R2 identified 34 and 27 coronary anomalies and classified 19 and 15 as malignant, respectively.
- Interobserver reproducibility for detection of coronary anomalies was good (k = 0.76).
- Interobserver agreement for detection of malignant variants was even stronger (k = 0.80).
- On average, coronary artery anomalies were diagnosed with 85.2% sensitivity, 96.4% specificity, 90.5% PPV, and 94.1% NPV on noncontrast CCS studies.
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Advanced CT reconstruction improves cardiac plaque assessment
By Eric Barnes, AuntMinnie.com staff writer
April 12, 2013 — Automated plaque assessment in coronary CT angiography (CCTA) is a promising new way to evaluate a patient’s plaque burden quickly and noninvasively — but it won’t be quick or accurate without the use of advanced iterative reconstruction, according to researchers from Massachusetts General Hospital in Boston.
“We know the plaque volume and characteristics … are at least as important as the presence of calcium,” said Dr. Stefan Puchner in an interview with AuntMinnie.com. “If we could make plaque assessment more accurate, we could implement all this stuff in our daily practice.”
The process isn’t accurate today. Automated plaque quantification requires significant time for radiologists to fix the incorrectly drawn vessel wall boundaries, making it impractical for routine use. Manually drawing the boundaries would actually take about a day’s work for each patient, so automation is the only way forward, Puchner said. The group wanted to determine if an advanced reconstruction algorithm might produce fewer errors and make semiautomated plaque estimation practical.
In a study that reconstructed ex vivo coronary vessel segments using three different reconstruction methods, the study team found that, indeed, accuracy in plaque quantification depended on the reconstruction algorithm, as well as vessel size and the extent of calcifications. Using advanced reconstruction, fewer corrections were needed to the vessel wall segmentation, Puchner reported at the 2013 European Congress of Radiology (ECR) in Vienna. Specifically, they compared the use of automated vessel assessment using model-based iterative reconstruction (MBIR, GE Healthcare) compared with an earlier IR algorithm, advanced statistical iterative reconstruction (ASIR, GE), or conventional filtered back projection (FBP) reconstruction.

For subjects, the group examined three ex vivo human hearts imaged with CCTA and reconstructed with FBP, ASIR, and MBIR. An automated plaque quantification tool (Vitrea Cardiac Solutions, Vital) was applied to each of the three reconstruction algorithms to fit the outer and inner vessel wall boundaries in nine “triplets” constituting 27 vessels. Only the first 40 mm of the contrast-filled vessels was used for analysis.
Each coronary cross section for which the software assigned incorrect boundaries was tallied and corrected in a blinded manner. The group then compared the number of vessel wall corrections between the different reconstruction algorithms using a Chi-square test.

“Our analysis included the percentage of corrections between the three algorithms, and a per-vessel comparison of the percentage of corrections between the three algorithms,” Puchner said in his presentation.
In all, the study comprised 2,295 cross sections in 0.5-mm increments from nine coronary vessels, combined into 765 coregistered triplets evaluated with the three algorithms. Overall, 31% of the cross sections needed boundary corrections, he said. Outer vessel wall boundary corrections were needed in 400 cross sections, and inner vessel boundaries were needed in 381 cross sections.

The percentage of corrected cross sections was lower for MBIR (24.1%) versus ASIR (32.4%, p = 0.0003) and FBP (36.6%, p < 0.0001) — but the differences were only marginal between ASIR and FBP, he said.
“We found that MBIR works much better than the conventional algorithms … significantly reducing the number of corrections needed compared to FBP and ASIR, whereas the difference between the two other algorithms was not significant,” Puchner said.
The use of MBIR significantly reduced the need for vessel wall boundary corrections compared with other reconstruction algorithms, particularly at the site of calcifications.
Automated segmentation is certainly faster than manual processing, Puchner said. Just on the three cases used in the study and in the analysis of the proximal 40 mm of each vessel, use of the software saved about three hours compared with what manual segmentation would have required. There is significant processing time required to create MBIR reconstructions, he acknowledged, but in those cases, it’s the technologists, not the physicians, who are spending the additional time, he said.
“The next step will be to look at it in an in vivo environment, to see this application in a beating heart,” Puchner told AuntMinnie.com. And to test other applications and other iterative reconstruction schemes, of course.
“I’m pretty sure that the other newer algorithms will have similar effects, because overall some studies have shown that the use of newer algorithms reduces blooming effects and other stuff that makes it difficult for the software to delineate it correctly,” he said. With manual segmentation, radiologists tend to overcorrect for older reconstruction algorithms and undercorrect for newer techniques, “but if the software does it, the software is much more dependent on image quality, and it makes a difference if it was reconstructed with the newer algorithms or the older algorithms.”
Automated plaque measurements will also have to be compared with assessments in other modalities such as intravascular ultrasound, and even to histology using the donor hearts, he said.
MBIR finds same nodules as ASIR, at fraction of dose, December 13, 2012
MBIR tops ASIR for ultralow-dose CT enterography, November 6, 2012
Study pinpoints optimal ASIR blend for stomach cancer, November 6, 2012
MBIR takes on ASIR in low-dose chest CT, November 6, 2012
Iterative reconstruction cuts CT dose for urinary stone disease, August 20, 2012
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Coronary CT Angiography in the ED
Acute Chest Pain/ER Admission: Three Emerging Alternatives to Angiography and PCI – Corus CAD, hs cTn, CCTA, Curator: Aviva Lev-Ari, PhD, RN, 3/10/2013
- Exercise treadmill stress test,
- Myocardial perfusion scan,
- Stress echocardiography, and/or
- Coronary CT angiography (CCTA).
Myocardial perfusion scans and stress echos have a sensitivity of 85–90% and specificity of 75–80%. In contrast, CCTA’s have been shown to have a sensitivity of 93-97% and specificity of 80-90%.
- Non-inferiority study
- 5 Pennsylvania EDs
- 1,370 patients, Age > 30 years
- Inclusion criteria: TIMI score of 0–2, EKG without ischemic changes, and negative first set of Cardiac Biomarkers
- Randomized 2 patients to CCTA arm (908 patients) for every 1 patient to Standard Stress arm (462 patients)
Primary Outcome:
- MI or Death from CAD at 30 days
Secondary Outcomes:
- Rate of discharge from ED
- Length of stay (LOS) in ED
- Rate of detection of CAD
- Resource utilization
What they found:
- 640/908 pts (70.5%) who underwent CCTA had coronary stenosis of <50% and none had MI or death due to CAD at 30 days
- Discharge from ED 49.6% with CCTA vs 22.7% with standard stress arm
- ED LOS 18 hr in CCTA arm vs 24.8 hr in standard stress arm
Conclusion: CCTA allows early discharge of low to intermediate risk patients presenting to the ED with possible ACS.
- Randomized controlled trial
- 9 EDs in the US
- 1,000 patients with acute chest pain with ages 40–74 years
- CCTA (501 patients) versus Standard Evaluation (499 patients)
Primary Outcome:
- Hospital length of stay
Secondary Outcomes:
- Cardiovascular events at 28 days
- Rate of discharge from ED
- Time to diagnosis
- Cost
- Utilization of resources
What they found:
- Hospital LOS decreased by 7.6 hr in CCTA group
- Rate of discharge from ED 47% in CCTA arm vs 12% in Standard Evaluation Arm
- No difference in cardiovascular events at 28 days
- Cost was similar between two groups $4,289 CCTA vs $4,060 in Standard arm
Conclusion: CCTA decreases length of stay without an increase in rate of cardiovascular events.
- CCTA with 0 lesions is NEGATIVE: These patients can certainly be discharged home with primary care follow up with a nearly 100% NPV for ACS/AMI.
- CCTA with <50% lesion is NOT NEGATIVE: This patient has CAD. It may not be clinically significant, but we can see plaques. 2/3 of AMIs occur from plaques that have <50% stenosis. Certainly we can start risk factor modification with beta blockers, ASA, and statins, but there are no studies looking at how this group of patients will do long term.
- CCTAs are anatomic studies and not functional studies. Identified lesions will lead to more diagnostic tests, which is one of the big arguments against CCTA. CCTA identifies CAD more often than standard stress modalities, which leads to more heart catheterizations and PCIs.
- As the number of CT slice increases, radiation dose decreases:
- A 64 slice CT = 10 – 15 mSv of radiation
- A 128 slice CT = 5 – 10 mSv of radiation
- A 256 slice CT = 1 – 5 mSv of radiation
- In contrast, a single-view CXR = 0.02 mSV of radiation
- There is currently an ongoing National Heart, Lung, and Blood Institute-funded trial called the PROMISE (Prospective Multi-center Imaging Study for Evaluation of Chest Pain) Study with 10,000 patients. Patients with symptoms suggestive of CAD will be randomized to a CCTA vs usual care with a functional test. What’s interesting about this study is it is being performed in the offices of primary care physicians and cardiologists rather than EDs. The study authors hypothesize that medically optimizing patients identified, as having non-obstructive CAD will yield improved long-term outcomes.
- Jancin B. Comparing Technologies for Imaging Chest Pain in the ED. ACEP News 2013 Mar; 32(3): 1 – 11.
- Goldstein JA. A Randomized Controlled Trial of Multi-Slice Coronary Computed Tomography for Evaluation of Acute Chest Pain. JACC 2007;49: 863 – 71. PMID: 17320744
- Goldstein JA. The CT-STAT (Coronary Computed Tomographic Angiography for Systematic Triage of Acute Chest Pain Patients to Treatment) Trial. JACC 2011 Sept; 58: 1414 – 22. PMID: 21939822
- Hulten E. Outcomes After Coronary Computed Tomography Angiography in the Emergency Department: A Systematic Review and Meta-Analysis of Randomized, Controlled Trials. JACC 2013 Feb; 61: 880 – 92. PMID: 23395069
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