AI-enhanced CCTA boosts ACS culprit lesion detection similarly in women and men

AI-enhanced quantitative coronary plaque and hemodynamic assessment (AI-QCPHA) improved culprit lesion discrimination in ACS over conventional CCTA, with AUC rising from 0.78 to 0.84 in women (p=0.002) and 0.75 to 0.82 in men (p<0.001). Delta FFRCT was the top predictor.

• Sub-study of the EMERALD II trial included 351 patients (90 women, 261 men) with 2,451 lesions who underwent CCTA 1 month to 3 years before an ACS event.
• AI-QCPHA identified the same best predictive features in both sexes; conventional high-risk plaque criteria performed differently by sex.
• Obstructive stenosis (CAD-RADS ≥3) showed similar diagnostic performance across sexes with conventional CCTA.

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