Artificial Intelligence for the Intra-procedural Assessment of Uterine Artery Embolization

Uterine artery embolization is a minimally invasive treatment for symptomatic uterine fibroids, but intra-procedural assessment of embolization adequacy currently relies on subjective angiographic criteria. This study evaluates a proprietary angiographic analysis software (AQ-VERO) that extracts quantitative time-to-density perfusion metrics in real time. The study aims to (1) validate the accuracy and reproducibility of AQ-VERO during uterine artery mebolization, and (2) develop an AI-based decision support system using AQ-VERO-derived metrics to improve objective intra-procedural assessment of treatment endpoints.