CT Angiographic and Plaque Predictors of Functionally Significant Coronary Disease and Outcome Using Machine Learning

Seokhun Yang, Bon Kwon Koo, Masahiro Hoshino, Joo Myung Lee, Tadashi Murai, Jiesuck Park, Jinlong Zhang, Doyeon Hwang, Eun Seok Shin, Joon Hyung Doh, Chang Wook Nam, Jianan Wang, Shaoliang Chen, Nobuhiro Tanaka, Hitoshi Matsuo, Takashi Akasaka, Gilwoo Choi, Kersten Petersen, Hyuk Jae Chang, Tsunekazu KakutaJagat Narula

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Objectives: The goal of this study was to investigate the association of stenosis and plaque features with myocardial ischemia and their prognostic implications. Background: Various anatomic, functional, and morphological attributes of coronary artery disease (CAD) have been independently explored to define ischemia and prognosis. Methods: A total of 1,013 vessels with fractional flow reserve (FFR) measurement and available coronary computed tomography angiography were analyzed. Stenosis and plaque features of the target lesion and vessel were evaluated by an independent core laboratory. Relevant features associated with low FFR (≤0.80) were identified by using machine learning, and their predictability of 5-year risk of vessel-oriented composite outcome, including cardiac death, target vessel myocardial infarction, or target vessel revascularization, were evaluated. Results: The mean percent diameter stenosis and invasive FFR were 48.5 ± 17.4% and 0.81 ± 0.14, respectively. Machine learning interrogation identified 6 clusters for low FFR, and the most relevant feature from each cluster was minimum lumen area, percent atheroma volume, fibrofatty and necrotic core volume, plaque volume, proximal left anterior descending coronary artery lesion, and remodeling index (in order of importance). These 6 features showed predictability for low FFR (area under the receiver-operating characteristic curve: 0.797). The risk of 5-year vessel-oriented composite outcome increased with every increment of the number of 6 relevant features, and it had incremental prognostic value over percent diameter stenosis and FFR (area under the receiver-operating characteristic curve: 0.706 vs. 0.611; p = 0.031). Conclusions: Six functionally relevant features, including minimum lumen area, percent atheroma volume, fibrofatty and necrotic core volume, plaque volume, proximal left anterior descending coronary artery lesion, and remodeling index, help define the presence of myocardial ischemia and provide better prognostication in patients with CAD. (CCTA-FFR Registry for Risk Prediction; NCT04037163)

Original languageEnglish
Pages (from-to)629-641
Number of pages13
JournalJACC: Cardiovascular Imaging
Volume14
Issue number3
DOIs
Publication statusPublished - 2021 Mar

Bibliographical note

Publisher Copyright:
© 2021 American College of Cardiology Foundation

All Science Journal Classification (ASJC) codes

  • Radiology Nuclear Medicine and imaging
  • Cardiology and Cardiovascular Medicine

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