Application of Quantitative Assessment of Coronary Atherosclerosis by Coronary Computed Tomographic Angiography.
Artificial intelligence
Coronary artery atherosclerosis
Coronary computed tomography angiography
Quantitative plaque analysis
Journal
Korean journal of radiology
ISSN: 2005-8330
Titre abrégé: Korean J Radiol
Pays: Korea (South)
ID NLM: 100956096
Informations de publication
Date de publication:
Jun 2024
Jun 2024
Historique:
received:
06
12
2023
revised:
29
02
2024
accepted:
23
03
2024
medline:
29
5
2024
pubmed:
29
5
2024
entrez:
29
5
2024
Statut:
ppublish
Résumé
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.
Identifiants
pubmed: 38807334
pii: 25.518
doi: 10.3348/kjr.2023.1311
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
518-539Subventions
Organisme : Dr. Miriam and Sheldon G. Adelson Medical Research Foundation
Pays : United States of America
Organisme : NHLBI NIH HHS
ID : 1R01HL148787-01A1
Pays : United States
Organisme : NHLBI NIH HHS
ID : 1R01HL151266
Pays : United States
Organisme : Winnick Family Foundation
Pays : United States of America
Informations de copyright
Copyright © 2024 The Korean Society of Radiology.
Déclaration de conflit d'intérêts
The authors have no potential conflicts of interest to disclose.