Priyanka Satish, Aashna Vajramani, Swapnil Gupta, Tsung‐Wei Ma, Tanushree Prasad, Suvasini Lakshmanan, Matthew Budoff, Dinesh Kalra, Muhammad Shahzeb Khan, Jonathon Leipsic, Amro Alsaid, Anandita Kulkarni
South Asians (SA) face disproportionately high rates of premature coronary artery disease (CAD), often underestimated by traditional risk calculators. We aim to characterize CT angiography (CTA)-derived plaque composition, plaque burden, and association with risk factors among SA in the DILWALE registry. Clinically indicated coronary CTAs from 341 patients in the Baylor Scott and White DILWALE registry were analyzed using Artificial intelligence enabled quantitative coronary plaque analysis (AIQCPA) to characterize age- and sex-specific plaque burden. Of 341 patients, 63% (n=215) exhibited any plaque by AIQCPA. Non-calcified plaque (NCP) was the predominant plaque subtype across all age groups, but calcified plaque volumes increased with age. The median PAV was 3.5% (IQR 0-18.5%). Age, male sex, and statin use were significant predictors of the presence of any plaque, while age and male sex predicted the presence of low attenuation plaque ≥ 10 mm 3 . This study represents one of the largest CTA based cohorts evaluating plaque characteristics in SA in the United States. Our findings highlight the value of AIQCPA CTA in revealing subclinical plaque, particularly non-calcified plaque in SA. Future studies should identify optimal imaging strategies for SA along with outcome-based validation of plaque characteristics.