The association of artificial intelligence-enabled coronary plaque analysis with future non-ST elevation myocardial infarction.
Authors
Affiliations (3)
Affiliations (3)
- Division of Cardiac Imaging, DeMatteis Cardiovascular Institute, St Francis Hospital & Heart Center, Roslyn, New York.
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California.
- Department of Nephrology and Hypertension, Renaissance School of Medicine at Stony Brook University, Stony Brook, New York, USA.
Abstract
There is emerging evidence that plaque features may play a critical role in future acute coronary syndrome. In this study, we analyzed plaque features using an artificial intelligence-enabled algorithm in a clinical cohort who developed non-ST-elevation myocardial infarction (NSTEMI) following coronary CT angiogram (CCTA). We performed a case-control study selected from 13β 751 consecutive cases in a single center referred for outpatient CCTA. After a follow-up of 4.3β Β±β 4β years, 48 patients without preexisting coronary disease developed NSTEMI. Controls (Nβ =β 187) were matched to the cases on age, gender, BMI, and kilovoltage for CTA acquisition. Quantitative plaque analysis was performed using artificial intelligence-enabled Autoplaque software (Autoplaque version 3.0; Cedars-Sinai Medical Center, Los Angeles, California, USA). Multivariable Cox proportional hazards models were performed to identify the predictors of NSTEMI. The mean age was 64β Β±β 11β years. Both case and control groups had mild stenosis at baseline (26 vs 17%, Pβ =β 0.01). The total calcified plaque and fibrous plaque volume were not different (Pβ =β 0.10 and Pβ =β 0.13, respectively). Necrotic core plaque volume and fibrous fatty plaque volume were higher in the NSTEMI group (28β Β±β 29 vs 9β Β±β 13β mm3, 169β Β±β 157 vs 84β Β±β 105β mm3, respectively, both Pβ <β 0.01). In multivariable Cox regression, necrotic core volume portended the greatest risk of NSTEMI, a seven-fold higher than that of total plaque volume. Using artificial intelligence-enabled plaque analysis, noncalcified plaque volume, especially necrotic core and fibrous fatty plaque volume are important precursors for future NSTEMI events.