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  3. Coronary artery stenosis, plaque burden, and severity of myocardial ischemia.
 

Coronary artery stenosis, plaque burden, and severity of myocardial ischemia.

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BORIS DOI
10.48620/93336
Publisher DOI
10.1093/ehjimp/qyaf139
PubMed ID
41393274
Description
Aims
The relationship between the extent and composition of coronary atherosclerosis and the severity of myocardial ischaemia remains incompletely understood. We assessed whether artificial intelligence-guided coronary computed tomography angiography-derived plaque burden and composition correlate with ischaemia severity.Methods And Results
We included 837 symptomatic patients undergoing coronary computed tomography angiography and subsequent 15O-water positron emission tomography myocardial perfusion imaging. Artificial intelligence-guided coronary computed tomography angiography was used to quantify plaque features-diameter stenosis, percent atheroma volume (PAV), percent non-calcified plaque volume (NCPV), and percent calcified plaque volume (CPV)-per patient and per major coronary artery (LAD, LCx, RCA). Ischaemia severity was classified into four categories based on regional hyperaemic myocardial blood flow. Increasing severity of ischaemia was associated with higher diameter stenosis and plaque burden (PAV, NCPV, CPV) on patient level and in all major coronary territories (overall P < 0.001). The LAD consistently demonstrated higher atherosclerotic burden as compared to the LCx and RCA. Ordinal logistic regression confirmed that diameter stenosis (OR 1.02-1.03, P < 0.001) and NCPV (OR 1.04-1.05, P = 0.011-0.031) were significant predictors of ischaemia severity in all coronary arteries, while CPV was predictive only in the LAD and RCA (OR 1.03-1.04, P = 0.002-0.015).Conclusion
Artificial intelligence-guided coronary computed tomography angiography-derived measures of plaque burden and stenosis are associated with the severity of myocardial ischaemia, although overlapping distributions across ischaemia severity indicate that anatomical imaging alone may be insufficient for accurate phenotyping of flow-limiting CAD. These findings encourage for the integration of functional imaging with quantitative plaque analysis for a more comprehensive evaluation of coronary artery disease.
Date of Publication
2025-10
Publication Type
Article
Subject(s)
600 Technology > 610 Medicine & health
Keyword(s)
artificial intelligence
•
coronary computed tomography angiography
•
coronary plaque
•
ischaemia
•
positron emission tomography
Language(s)
en
Contributor(s)
Kero, Tanja
Knuuti, Juhani
Bär, Sarah
Clinic of Cardiology
Bax, Jeroen J
Saraste, Antti
Maaniitty, Teemu
Additional Credits
Clinic of Cardiology
Series
European Heart Journal - Imaging Methods and Practice
Publisher
Oxford University Press
ISSN
2755-9637
Access(Rights)
open.access
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