JACC Case Rep. 2026 Sep 16;31(37):109115. doi: 10.1016/j.jaccas.2026.109115. Epub 2026 Sep 8.
ABSTRACT
BACKGROUND: In hospitalized patients undergoing coronary computed tomography angiography (CCTA), variability in stenosis interpretation may contribute to missed obstructive coronary artery disease (CAD) or unnecessary invasive coronary angiography.
PROJECT SUMMARY: We retrospectively evaluated inpatient CCTA interpretation workflows at a tertiary academic center between 2023 and 2025. Among 177 hospitalized patients undergoing CCTA, 139 had both artificial intelligence (AI)-assisted and physician interpretations available for comparison. Twenty patients underwent same-admission invasive coronary angiography, with 19 included in final invasive angiographic analysis. AI-assisted interpretation demonstrated higher agreement with invasive coronary angiography than physician interpretation within the exploratory invasive angiography subgroup (78.6% vs 55.0%). Discordance patterns were primarily driven by false-negative physician interpretations and AI-assisted stenosis overestimation. Significant CAD was identified in 73.7% of the invasive angiography subgroup, with 52.6% ultimately undergoing revascularization.
TAKE-HOME MESSAGE: Hybrid AI-physician interpretation workflows may support more consistent inpatient CAD evaluation while preserving physician-guided clinical decision making.
PMID:42752016 | DOI:10.1016/j.jaccas.2026.109115