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Association of AI-Enabled Quantitative Coronary Plaque Volumes With Clinical Outcomes
TAKE-HOME MESSAGE
- This study investigated the interactions among luminal stenosis, FFRCT images, high-risk plaque features, and patient outcomes, including major adverse cardiac events (MACE) and late revascularization. Retrospective analysis of data from 4430 patients enrolled in the ADVANCE Registry revealed that a total plaque volume >564 mm3, after adjustment for various factors, was associated with an increased risk of MACE/late revascularization. A total percent atheroma volume >24.4% was linked to increased risks of MACE/late revascularization and cardiovascular death/myocardial infarction. Calcified, noncalcified, and low-attenuation plaque volumes were also associated with adverse outcomes.
- These findings suggest that total plaque volume provides incremental predictive value over luminal stenosis and FFRCT for the prediction of 1-year adverse clinical events.
abstract
This abstract is available on the publisher's site.
Access this abstract nowBACKGROUND
Luminal stenosis, computed tomography-derived fractional-flow reserve (FFRCT), and high-risk plaque features on coronary computed tomography angiography are all known to be associated with adverse clinical outcomes. The interactions between these variables, patient outcomes, and quantitative plaque volumes have not been previously described.
METHODS
Patients with coronary computed tomography angiography (n=4430) and one-year outcome data from the international ADVANCE (Assessing Diagnostic Value of Noninvasive FFRCT in Coronary Care) registry underwent artificial intelligence-enabled quantitative coronary plaque analysis. Optimal cutoffs for coronary total plaque volume and each plaque subtype were derived using receiver-operator characteristic curve analysis. The resulting plaque volumes were adjusted for age, sex, hypertension, smoking status, type 2 diabetes, hyperlipidemia, luminal stenosis, distal FFRCT, and translesional delta-FFRCT. Median plaque volumes and optimal cutoffs for these adjusted variables were compared with major adverse cardiac events, late revascularization, a composite of the two, and cardiovascular death and myocardial infarction.
RESULTS
At one year, 55 patients (1.2%) had experienced major adverse cardiac events, and 123 (2.8%) had undergone late revascularization (>90 days). Following adjustment for age, sex, risk factors, stenosis, and FFRCT, total plaque volume above the receiver-operator characteristic curve-derived optimal cutoff (total plaque volume >564 mm3) was associated with the major adverse cardiac event/late revascularization composite (adjusted hazard ratio, 1.515 [95% CI, 1.093-2.099]; P=0.0126), and both components. Total percent atheroma volume greater than the optimal cutoff was associated with both major adverse cardiac event/late revascularization (total percent atheroma volume >24.4%; hazard ratio, 2.046 [95% CI, 1.474-2.839]; P<0.0001) and cardiovascular death/myocardial infarction (total percent atheroma volume >37.17%, hazard ratio, 4.53 [95% CI, 1.943-10.576]; P=0.0005). Calcified, noncalcified, and low-attenuation percentage atheroma volumes above the optimal cutoff were associated with all adverse outcomes, although this relationship was not maintained for cardiovascular death/myocardial infarction in analyses stratified by median plaque volumes.
CONCLUSIONS
Analysis of the ADVANCE registry using artificial intelligence-enabled quantitative plaque analysis shows that total plaque volume is associated with one-year adverse clinical events, with incremental predictive value over luminal stenosis or abnormal physiology by FFRCT.
Additional Info
Disclosure statements are available on the authors' profiles:
Interaction of AI-Enabled Quantitative Coronary Plaque Volumes on Coronary CT Angiography, FFRCT, and Clinical Outcomes: A Retrospective Analysis of the ADVANCE Registry
Circ Cardiovasc Imaging 2024 Mar 01;17(3)e016143, J Dundas, J Leipsic, T Fairbairn, N Ng, V Sussman, I Guez, R Rosenblatt, LM Hurwitz Koweek, PS Douglas, M Rabbat, G Pontone, K Chinnaiyan, B de Bruyne, JJ Bax, T Amano, K Nieman, C Rogers, H Kitabata, NPR Sand, T Kawasaki, S Mullen, W Huey, H Matsuo, MR Patel, BL Norgaard, A Ahmadi, G TzimasFrom MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.
Slowly but steadily, automated analysis of cardiac imaging is maturing. One cannot open a journal without seeing a paper on “AI-/machine learning–enabled analysis of…” some imaging modality, whether it be echocardiography, cardiac MRI, nuclear imaging, or CCTA.
In the current paper, the investigators used the robust ADVANCE Registry database to interrogate plaque volume and atheroma composition. ADVANCE was a registry involving more than 4000 patients undergoing CCTA, pooled from many international centers, who had adjudicated 1-year outcomes. They examined whether “AI-enabled” plaque volume and atheroma measures provided incremental risk-stratification value above other characteristics such as luminal stenosis, CT-derived fractional flow reserve, and high-risk plaque features.
The investigators found that both of the plaque features (total volume and percent atheroma volume) are associated with the 1-year outcomes of major adverse events and late revascularization, even after accounting for other factors such as the degree of stenosis and fractional flow reserve. An advance is that the calculation of the plaque volume characteristics was automated with an AI-derived and -driven algorithm.
The message here is that the risk of progression of coronary artery disease from a chronic to an acute syndrome is driven by a complex interplay of plaque characteristics and plaque effects. The evolution of image analysis is making the identification of the many elements driving the risk progression more available. Whether more precision in estimating risk can be tied to an intensification of some therapy to lower the risk remains an open question that must be tested in prospective trials.