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

Condition(s) studied

Study summary

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.

Eligibility

Primary outcome measure(s)

• The primary outcome measure is the AUPRC of the predictive models. — From treatment to the end of the required follow-up (6 months).
  The Area Under the Precision-Recall Curve (AUPRC) will be calculated to evaluate the performance of the AI-based decision support model in identifying clinically relevant embolization endpoints. AUPRC is a threshold-independent metric that summarizes the tradeoff between precision (positive predictive value) and recall (sensitivity) across all decision thresholds. It is particularly suitable for imbalanced datasets, where positive outcome events may be less frequent. Higher AUPRC values indicate better discriminative performance of the model.

Trial sites (1)