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Atherosclerosis Quantification and Cardiovascular Risk
TAKE-HOME MESSAGE
- In this exploratory analysis of the ISCHEMIA trial, total coronary plaque volume quantified by CCTA was strongly associated with increased risks of cardiovascular death and myocardial infarction. A clinical risk model that incorporated total plaque volume quantification and characterization alongside baseline risk factors improved event-risk prediction; however, the overall discrimination of the model remained modest.
- These findings highlight overall plaque burden as a significant risk factor for cardiovascular events, with implications for risk-stratification and treatment strategies.
abstract
This abstract is available on the publisher's site.
Access this abstract nowBACKGROUND AND AIMS
The aim of this study was to determine the prognostic value of coronary computed tomography angiography (CCTA)-derived atherosclerotic plaque analysis in ISCHEMIA.
METHODS
Atherosclerosis imaging quantitative computed tomography (AI-QCT) was performed on all available baseline CCTAs to quantify plaque volume, composition, and distribution. Multivariable Cox regression was used to examine the association between baseline risk factors (age, sex, smoking, diabetes, hypertension, ejection fraction, prior coronary disease, estimated glomerular filtration rate, and statin use), number of diseased vessels, atherosclerotic plaque characteristics determined by AI-QCT, and a composite primary outcome of cardiovascular death or myocardial infarction over a median follow-up of 3.3 (interquartile range 2.2-4.4) years. The predictive value of plaque quantification over risk factors was compared in an area under the curve (AUC) analysis.
RESULTS
Analysable CCTA data were available from 3711 participants (mean age 64 years, 21% female, 79% multivessel coronary artery disease). Amongst the AI-QCT variables, total plaque volume was most strongly associated with the primary outcome (adjusted hazard ratio 1.56, 95% confidence interval 1.25-1.97 per interquartile range increase [559 mm3]; P = .001). The addition of AI-QCT plaque quantification and characterization to baseline risk factors improved the model's predictive value for the primary outcome at 6 months (AUC 0.688 vs. 0.637; P = .006), at 2 years (AUC 0.660 vs. 0.617; P = .003), and at 4 years of follow-up (AUC 0.654 vs. 0.608; P = .002). The findings were similar for the other reported outcomes.
CONCLUSIONS
In ISCHEMIA, total plaque volume was associated with cardiovascular death or myocardial infarction. In this highly diseased, high-risk population, enhanced assessment of atherosclerotic burden using AI-QCT-derived measures of plaque volume and composition modestly improved event prediction.
Additional Info
Disclosure statements are available on the authors' profiles:
Atherosclerosis quantification and cardiovascular risk: the ISCHEMIA trial
Eur Heart J 2024 Aug 05;[EPub Ahead of Print], NS Nurmohamed, JK Min, R Anthopolos, HR Reynolds, JP Earls, T Crabtree, GBJ Mancini, J Leipsic, MJ Budoff, CJ Hague, SM O'Brien, GW Stone, JS Berger, R Donnino, MS Sidhu, JD Newman, WE Boden, BR Chaitman, PH Stone, S Bangalore, JA Spertus, DB Mark, LJ Shaw, JS Hochman, DJ MaronFrom MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.
Technology using artificial intelligence (AI) to analyze coronary artery anatomy as well as atherosclerotic plaque volume and characteristics on CCTA exists. The ISCHEMIA trial investigators evaluated the incremental value of AI-enabled plaque analysis when added to conventional clinical risk factors. The AI algorithm quantified the number of diseased vessels; the volume of calcified, noncalcified, and low-density necrotic core components; total plaque volume; and measures of vascular remodeling, and it identified high-risk plaque phenotypes. The primary outcome was a composite of cardiovascular death and myocardial infarction during a median follow-up period of 3.3 years.
Approximately 70% of participants randomized in the ISCHEMIA trial had CCTA results at baseline that could be analyzed. After adjusting for covariates, including other plaque characteristics, total plaque volume was the only plaque variable that had a positive association with the composite outcome of cardiovascular death and myocardial infarction (aHR, 1.56; 95% CI, 1.25–1.97 per interquartile range increase [559 mm3]; P = .001). The addition of plaque quantification and characterization to baseline risk factors improved the model’s predictive value for the primary outcome at 6 months (AUC, 0.688 vs 0.637; P = .006), 2 years (AUC, 0.660 vs 0.617; P = .003), and 4 years of follow-up (AUC, 0.654 vs 0.608; P = .002).
The take-home message is that quantifying total plaque volume modestly improved the prediction of cardiovascular death and myocardial infarction when added to readily available clinical risk factors. Most prior CCTA studies involving cohorts with less severe coronary artery disease reported stronger associations between quantitative plaque characteristics and cardiovascular events. The value of changes in plaque characteristics on serial imaging examinations as a predictor of cardiovascular events is being evaluated in other studies.