Skip to main navigation Skip to search Skip to main content

Application of Quantitative Assessment of Coronary Atherosclerosis by Coronary Computed Tomographic Angiography

  • Su Nam Lee
  • , Andrew Lin
  • , Damini Dey
  • , Daniel S. Berman
  • , Donghee Han
  • Monash University
  • Cedars-Sinai Medical Center

Research output: Contribution to journalReview articlepeer-review

17 Scopus citations

Abstract

Coronary computed tomography angiography (CCTA) has emerged as a pivotal tool for diagnosing and risk-stratifying patients with suspected coronary artery disease (CAD). Recent advancements in image analysis and artificial intelligence (AI) techniques have enabled the comprehensive quantitative analysis of coronary atherosclerosis. Fully quantitative assessments of coronary stenosis and lumen attenuation have improved the accuracy of assessing stenosis severity and predicting hemodynamically significant lesions. In addition to stenosis evaluation, quantitative plaque analysis plays a crucial role in predicting and monitoring CAD progression. Studies have demonstrated that the quantitative assessment of plaque subtypes based on CT attenuation provides a nuanced understanding of plaque characteristics and their association with cardiovascular events. Quantitative analysis of serial CCTA scans offers a unique perspective on the impact of medical therapies on plaque modification. However, challenges such as time-intensive analyses and variability in software platforms still need to be addressed for broader clinical implementation. The paradigm of CCTA has shifted towards comprehensive quantitative plaque analysis facilitated by technological advancements. As these methods continue to evolve, their integration into routine clinical practice has the potential to enhance risk assessment and guide individualized patient management. This article reviews the evolving landscape of quantitative plaque analysis in CCTA and explores its applications and limitations.

Original languageEnglish
Pages (from-to)518-539
Number of pages22
JournalKorean Journal of Radiology
Volume25
Issue number6
DOIs
StatePublished - Jun 2024

Bibliographical note

Publisher Copyright:
© 2024 The Korean Society of Radiology.

Keywords

  • Artificial intelligence
  • Coronary artery atherosclerosis
  • Coronary computed tomography angiography
  • Quantitative plaque analysis

Fingerprint

Dive into the research topics of 'Application of Quantitative Assessment of Coronary Atherosclerosis by Coronary Computed Tomographic Angiography'. Together they form a unique fingerprint.

Cite this