Quantification of Coronary Atherosclerosis in the Assessment of Coronary Artery Disease. (July 2018) - Lee, Sang-Eun; Sung, Ji Min; Rizvi, Asim; Lin, Fay Y.; Kumar, Amit; Hadamitzky, Martin; Kim, Yong-Jin; Conte, Edoardo; Andreini, Daniele; Pontone, Gianluca; Budoff, Matthew J.; Gottlieb, Ilan; et al.
Abstract : Background: Diagnosis of coronary artery disease and management strategies have relied solely on the presence of diameter stenosis ≥50%. We assessed whether direct quantification of plaque burden (PB) and plaque characteristics assessed by coronary computed tomography angiography could provide additional value in terms of predicting rapid plaque progression. Methods and Results: From a 13-center, 7-country prospective observational registry, 1345 patients (60.4±9.4 years old; 57.1% male) who underwent repeated coronary computed tomography angiography >2 years apart were enrolled. For conventional angiographic analysis, the presence of stenosis ≥50%, number of vessel involved, segment involvement score, and the presence of high-risk plaque feature were determined. For quantitative analyses, PB and annual change in PB (△PB/y) in the entire coronary tree were assessed. Clinical outcomes (cardiac death, nonfatal myocardial infarction, and coronary revascularization) were recorded. Rapid progressors, defined as a patient with ≥median value of △PB/y (0.33%/y), were older, more frequently male, and had more clinical risk factors than nonrapid progressors (all P <0.05). After risk adjustment, addition of baseline PB improved prediction of rapid progression to each angiographic assessment of coronary artery disease, and the presence of high-risk plaque further improved the predictive performance (all P <0.001). For prediction of adverse outcomes, adding both baseline PB and △PB/y showed best predictive performance (C statistics, 0.763; P <0.001). Conclusions: Direct quantification of atherosclerotic PB in addition to conventional angiographic assessment of coronary artery disease might be beneficial for improving risk stratification of coronary artery disease. Clinical Trial Registration: URL:https://www.clinicaltrials.gov . Unique identifier: NCT02803411. Abstract : Supplemental Digital Content is available in the text.