Cardiac Computed Tomography Radiomics for the Non-Invasive Assessment of Coronary Inflammation

Kevin Cheng, Andrew Lin, Jeremy Yuvaraj, Stephen J. Nicholls, Dennis T.L. Wong

Research output: Contribution to journalReview ArticleResearchpeer-review

Abstract

Radiomics, via the extraction of quantitative information from conventional radiologic images, can identify imperceptible imaging biomarkers that can advance the characterization of coronary plaques and the surrounding adipose tissue. Such an approach can unravel the underlying pathophysiology of atherosclerosis which has the potential to aid diagnostic, prognostic and, therapeutic decision making. Several studies have demonstrated that radiomic analysis can characterize coronary atherosclerotic plaques with a level of accuracy comparable, if not superior, to current conventional qualitative and quantitative image analysis. While there are many milestones still to be reached before radiomics can be integrated into current clinical practice, such techniques hold great promise for improving the imaging phenotyping of coronary artery disease.

Original languageEnglish
Article number879
Number of pages17
JournalCells
Volume10
Issue number4
DOIs
Publication statusPublished - Apr 2021

Keywords

  • acute coronary syndrome
  • atherosclerosis
  • coronary computed tomography angiography
  • machine learning
  • peri-coronary adipose tissue
  • plaque
  • radiomics

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