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Purpose: To provide comparative prognostic information of coronary atherosclerotic plaque volume and stenosis assessment in patients with suspected coronary artery disease (CAD)., Methods: We followed 372 patients with suspected or known CAD enrolled in the CORE320 study for 2 years after baseline 320-detector row cardiac CT scanning and invasive quantitative coronary angiography (QCA). CT images were analyzed for coronary calcium scanning (CACS), semi-automatically derived total percent atheroma volume (PAV), segment stenosis score (SSS), in addition to traditional stenosis assessment (≥ 50%) by CT and QCA for (1) 30-day revascularization and (2) major adverse cardiac events (MACE). Area under the receiver operating characteristic curve (AUC) was used to compare accuracy of risk prediction., Results: Sixty percent of patients had obstructive CAD by QCA with 23% undergoing 30-day revascularization and 9% experiencing MACE at 2 years. Most late events (20/32) were revascularization procedures. Prediction of 30-day revascularization was modest (AUC range 0.67-0.78) but improved after excluding patients with known CAD (AUC range 0.73-0.86, p < 0.05 for all). Similarly, prediction of MACE improved after excluding patients with known CAD (AUC range 0.58-0.73 vs. 0.63-0.77). CT metrics of atherosclerosis burden performed overall similarly but stenosis assessment was superior for predicting 30-day revascularization., Conclusions: Angiographic and coronary atherosclerotic plaque metrics perform only modestly well for predicting 30-day revascularization and 2-year MACE in high risk patients but improve after excluding patients with known CAD. Atherosclerotic plaque metrics did not yield incremental value over stenosis assessment for predicting events that predominantly consisted of revascularization procedures., Clinical Trial Registration: NCT00934037.

Background: Total atherosclerotic plaque burden assessment by CT angiography (CTA) is a promising tool for diagnosis and prognosis of coronary artery disease (CAD) but its validation is restricted to small clinical studies. We tested the feasibility of semi-automatically derived coronary atheroma burden assessment for identifying patients with hemodynamically significant CAD in a large cohort of patients with heterogenous characteristics., Methods: This study focused on the CTA component of the CORE320 study population. A semi-automated contour detection algorithm quantified total coronary atheroma volume defined as the difference between vessel and lumen volume. Percent atheroma volume (PAV = [total atheroma volume/total vessel volume] × 100) was the primary metric for assessment (n = 374). The area under the receiver operating characteristic curve (AUC) determined the diagnostic accuracy for identifying patients with hemodynamically significant CAD defined as ≥50% stenosis by quantitative coronary angiography and associated myocardial perfusion abnormality by SPECT., Results: Of 374 patients, 139 (37%) had hemodynamically significant CAD. The AUC for PAV was 0.78 (95% confidence interval [CI] 0.73-0.83) compared with 0.84 [0.79-0.88] by standard expert CTA interpretation (p = 0.02). Accuracy for both CTA (0.91 [0.87, 0.96]) and PAV (0.86 [0.81-0.91]) increased after excluding patients with history of CAD (p < 0.01 for both). Bland-Altman analysis revealed good agreement between two observers (bias of 280.2 mm(3) [161.8, 398.7])., Conclusions: A semi-automatically derived index of total coronary atheroma volume yields good accuracy for identifying patients with hemodynamically significant CAD, though marginally inferior to CTA expert reading. These results convey promise for rapid, reliable evaluation of clinically relevant CAD., (Copyright © 2016 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.)

Background: Appropriate clinical decisions concerning diagnosis and treatment of coronary artery disease rely on correct integration of data on coronary anatomy and myocardial perfusion. The purpose of this article is to introduce a new left ventricular segmentation model for improved alignment of coronary arterial segments and myocardial perfusion territories, designed for the CORE320 study., Methods and Results: CORE320 is a prospective, multicenter study with a primary objective to evaluate the diagnostic accuracy of 320-row detector computed tomography (CT) to detect coronary artery luminal stenosis and corresponding myocardial perfusion deficits in patients with suspected coronary artery disease compared with the gold standard of conventional coronary angiography and single-photon emission CT myocardial perfusion imaging. We describe a 19-coronary segment and 13-myocardial territory alignment model, its application in both standard and CT image data sets, and the adjudication process of the initial cohort of patients recruited for the CORE320 study. Adjudication committees reviewed the images of the first 101 gold standard and 107 CT data sets. On the basis of the presented model and rules, all cases for adjudication were correctly identified. During image review, 6 (5.9%) gold standard and 9 (8.4%) CT data sets needed further realignment not triggered by the algorithm., Conclusions: We present a vascular territory distribution model developed for the CORE320 multicenter study, which accounts for variability in coronary anatomy and potential myocardial perfusion territory overlap.