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Randomized Controlled Trial
. 2024 Sep 29;45(36):3735-3747.
doi: 10.1093/eurheartj/ehae471.

Atherosclerosis quantification and cardiovascular risk: the ISCHEMIA trial

Nick S Nurmohamed  1   2   3 , James K Min  4 , Rebecca Anthopolos  5 , Harmony R Reynolds  5 , James P Earls  4   6 , Tami Crabtree  4 , G B John Mancini  7 , Jonathon Leipsic  7 , Matthew J Budoff  8 , Cameron J Hague  7 , Sean M O'Brien  9 , Gregg W Stone  10 , Jeffrey S Berger  5 , Robert Donnino  5 , Mandeep S Sidhu  11 , Jonathan D Newman  5 , William E Boden  12 , Bernard R Chaitman  13 , Peter H Stone  14 , Sripal Bangalore  5 , John A Spertus  15 , Daniel B Mark  9 , Leslee J Shaw  16 , Judith S Hochman  5 , David J Maron  17
Affiliations
Randomized Controlled Trial

Atherosclerosis quantification and cardiovascular risk: the ISCHEMIA trial

Nick S Nurmohamed et al. Eur Heart J. .

Abstract

Background 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.

Keywords: Artificial intelligence; Atherosclerosis; CCTA; Coronary artery disease; Ischaemia; Plaque.

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Figures

Structured Graphical Abstract
Structured Graphical Abstract
Study design and main outcomes of the current study. AI-QCT, atherosclerosis imaging quantitative computed tomography; AUC, area under the curve; CAD, coronary artery disease; CCTA, coronary computed tomography angiography; CV, cardiovascular; FU, follow-up; MI, myocardial infarction; NRI, net reclassification improvement.
Figure 1
Figure 1
Distribution of plaque volumes in ISCHEMIA. Shown are histograms of the different plaque components in the ISCHEMIA trial population (n = 3711). Plaque volumes (x-axis) were transformed using a square root transformation
Figure 2
Figure 2
Relation between total plaque volume and cardiovascular death or myocardial infarction and the secondary composite outcome. Upper panel: shown is the cumulative incidence of cardiovascular death or myocardial infarction (A) and the secondary composite outcome of cardiovascular death, myocardial infarction, or hospitalization for unstable angina, heart failure, or resuscitated cardiac arrest (B). Patients were categorized according to total plaque volume stages [Stage 1 (≤250 mm3); Stage 2 (>250–750 mm3); Stage 3 (>750 mm3)]. P-values are from the Fine–Gray test to account for the competing risk of non-cardiovascular death. Lower panel: 4-year event probability of cardiovascular death or myocardial infarction (C) and the secondary composite outcome of cardiovascular death, myocardial infarction, or hospitalization for unstable angina, heart failure, or resuscitated cardiac arrest (D), according to total plaque volume. The vertical bars along the horizontal axis show the distribution of total plaque volume amongst the study participants. Shading refers to the 95% confidence interval
Figure 3
Figure 3
Prognostic value of different models for cardiovascular death or myocardial infarction. Discriminatory value for the primary outcome of cardiovascular death and myocardial infarction. Receiver operating characteristic curves of a model with clinical characteristics (Model 1), a model with clinical and atherosclerosis imaging quantitative computed tomography stenosis parameters (Model 2) and a model with clinical, atherosclerosis imaging quantitative computed tomography stenosis, and atherosclerosis imaging quantitative computed tomography atherosclerotic variables (Model 3). Areas under the curve were calculated at 6 months (A), 2 years (B), and 4 years (C) of follow-up. The 95% confidence interval is shown between brackets
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