Artificial Intelligence for the Intra-procedural Assessment of Uterine Artery Embolization (AI-EMBO)

Validation and Implementation With Artificial Intelligence of Software 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.

Study Overview

• Status: Not yet recruiting
• Conditions: Uterine Fibroids (UF)

Detailed Description

Background and Rationale.

Uterine fibroids affect up to 70-80% of women of reproductive age. Uterine artery embolization achieves technical success rates above 95% and symptom improvement in approximately 75-90% of patients; however, it is associated with a 20-30% cumulative risk of clinical failure or need for reintervention at 5 years. Current intra-procedural assessment of embolization adequacy is based on qualitative angiographic criteria (e.g., "5-10 heartbeats stasis," "pruned tree appearance"), which are subjective and operator-dependent. Emerging evidence suggests that achieving near-complete, rather than complete, flow stasis may reduce post-procedural pain, underscoring the need for quantitative and standardized assessment tools.

AQ-VERO is an internally developed software platform that performs quantitative time-to-density (TTD) analysis of angiographic images to objectively quantify uterine and fibroid perfusion in real time.

Objectives.

Primary Objective: To validate the accuracy and intra-/interobserver reproducibility of AQ-VERO TTD metrics in quantifying perfusion changes during uterine artery embolization.

Secondary Objectives: (a) To develop and internally validate an AI-based decision support model that uses AQ-VERO-derived metrics to identify predefined embolization endpoints; (b) To explore the correlation between intra-procedural TTD metrics and post-procedural clinical outcomes, including symptom improvement, early pain scores, and need for reintervention.

Study Design. This is an ambispective (includes retrospective and prospective follow-up), multicenter observational study including women undergoing uterine artery embolization for symptomatic uterine fibroids. Standardized angiograms will be acquired and analyzed with AQ-VERO to extract TTD perfusion parameters (e.g., time-to-peak, area under the curve, wash-in/wash-out characteristics). Operators will document conventional qualitative angiographic endpoints. Clinical and imaging follow-up will be collected according to institutional protocols.

Primary Objective:

• To evaluate whether the AI predictive model developed using AQ-VERO© metrics can predict the clinical outcome, defined as complete or significant resolution of fibroid-related symptoms.

Secondary Objectives:

• To correlate distinct TTD curve morphologies and AQ-VERO metrics with post-procedural pain.
• To detect the presence of collateral or accessory arterial supply that may compromise embolization efficacy.

Significance. This study is expected to establish a quantitative and AI-augmented framework for intra-procedural embolization assessment during uterine artery embolization, potentially reducing variability and improving long-term clinical outcomes.

• Study Type: Observational
• Enrollment (Estimated): 250

Contacts and Locations

• Study Contact: Name: Emanuele Barabino, MD; Phone Number: 00393331002778; Email: emanuele.barabino@hsanmartino.it

Study Locations

• Italy
  • Genova
    • Genova, Genova, Italy, 16100
      • IRCCS Ospedale Policlinico San Martino

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

The study population consists of adult female patients aged 18 to 55 years with symptomatic uterine fibroids who underwent or are undergoing uterine artery embolization as their primary treatment. All participants must have angiographic imaging suitable for quantitative analysis and a minimum of 6 months of available clinical follow-up.

Description

Inclusion Criteria:

• Female patients ≥18 years
• Symptomatic uterine fibroids (e.g., bleeding, bulk symptoms, pain)
• Underwent UAE as definitive therapy
• Availability of baseline clinical/imaging data (for retrospective arm) or ability to provide informed consent (for prospective arm)

Exclusion Criteria:

• Lack of clinical follow-up
• Poor quality or incomplete angiographic images.

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort
250 patients with a diagnosis of uterine fibroids who underwent uterine artery embolization; Women diagnosed with symptomatic uterine fibroids who underwent image-guided uterine artery embolization as treatment. No additional surgical or medical interventions were performed during the procedure.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
The primary outcome measure is the AUPRC of the predictive models.	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.	From treatment to the end of the required follow-up (6 months).

Collaborators and Investigators

• Sponsor: Emanuele Barabino
• Investigators: Study Chair: Giuseppe Cittadini, MD, IRCCS Ospedale Policlinico San Martino

Publications and helpful links

General Publications

• Spies JB, Coyne K, Guaou Guaou N, Boyle D, Skyrnarz-Murphy K, Gonzalves SM. The UFS-QOL, a new disease-specific symptom and health-related quality of life questionnaire for leiomyomata. Obstet Gynecol. 2002 Feb;99(2):290-300. doi: 10.1016/s0029-7844(01)01702-1.
• Pron G, Bennett J, Common A, Wall J, Asch M, Sniderman K; Ontario Uterine Fibroid Embolization Collaboration Group. The Ontario Uterine Fibroid Embolization Trial. Part 2. Uterine fibroid reduction and symptom relief after uterine artery embolization for fibroids. Fertil Steril. 2003 Jan;79(1):120-7. doi: 10.1016/s0015-0282(02)04538-7.
• Manyonda I, Belli AM, Lumsden MA, Moss J, McKinnon W, Middleton LJ, Cheed V, Wu O, Sirkeci F, Daniels JP, McPherson K; FEMME Collaborative Group. Uterine-Artery Embolization or Myomectomy for Uterine Fibroids. N Engl J Med. 2020 Jul 30;383(5):440-451. doi: 10.1056/NEJMoa1914735.

Study record dates

Study Major Dates

• Study Start (Estimated): December 1, 2025
• Primary Completion (Estimated): December 1, 2026
• Study Completion (Estimated): May 31, 2027

Study Registration Dates

• First Submitted: November 13, 2025
• First Submitted That Met QC Criteria: November 13, 2025
• First Posted (Estimated): November 17, 2025

Study Record Updates

• Last Update Posted (Actual): November 19, 2025
• Last Update Submitted That Met QC Criteria: November 15, 2025
• Last Verified: November 1, 2025

More Information

Terms related to this study

• Keywords: artificial intelligence; embolization; uterine artery embolization; uterine fibroids; quantitative imaging
• Additional Relevant MeSH Terms: Neoplasms; Neoplasms by Histologic Type; Neoplasms, Connective and Soft Tissue; Neoplasms, Muscle Tissue; Leiomyoma
• Other Study ID Numbers: AI-EMBO 2.0

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO
• IPD Plan Description: Individual participant data (IPD) will not be shared.

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No