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AI reads ultrasound images to spot ovarian cancer risk

NCT ID NCT07793201

Diagnosis Sponsor: Fondazione Policlinico Universitario Agostino Gemelli IRCCS Source: ClinicalTrials.gov ↗

What the study statuses mean

This study's is highlighted.

Recruitment status, easiest to join first

Recruiting now
This trial is taking on new participants right now.
Not yet recruiting This study
Registered, but not yet taking participants.
By invitation only
Not open to general applications. Only people the study team invites can take part.
Paused
Paused for now. It may or may not start again.
Ongoing
Running, but no longer taking on new participants.
Completed
The trial has finished. Results may not be published yet.
Stopped early
Stopped early, before it reached the end. That can be for many reasons, including safety.
Cancelled
Cancelled before anyone took part.

Expanded access (not trials)

Expanded access
Not a trial. This treatment can be requested outside a study, case by case, for people who qualify.
Expanded access (paused)
Not a trial. The treatment can normally be requested outside a study, but is unavailable right now.
Expanded access (ended)
Not a trial. The treatment could once be requested outside a study, but no longer can.
Approved
The treatment has been approved, so it is available normally rather than through this programme.

When the status isn't known

Details not published
The full record has not been published yet, so there is little to show here.
Status unknown
This status has not been confirmed recently, so it may be out of date.

First seen Aug 28, 2026 · Last updated Aug 28, 2026

Summary

This study tests whether machine learning can analyze ultrasound images to distinguish benign from malignant adnexal masses, growths near the ovaries that are common but hard to classify. Researchers will develop and validate AI models using images from 12,000 patients across multiple centers. The goal is to see if AI can match or improve on doctors' assessments, potentially reducing unnecessary surgeries and ensuring cancer patients get referred to specialists sooner. The study also checks whether AI can tell apart borderline tumors, primary invasive cancers, and metastases, and whether it could change how patients are managed.

What this could mean

Our plain-language read of the trial. This is informational only, not medical advice or a prediction.

Active substance
Machine learning algorithms analyzing ultrasound images
What this could lead to
If it works, this could give doctors a reliable AI tool to tell benign from malignant adnexal masses on ultrasound, reducing unnecessary surgeries and speeding referrals for cancer care.
What could go wrong
This is an observational study, not a treatment trial, so it will not change care directly. The AI models may not perform well enough in real-world settings, and the retrospective analysis may not reflect actual clinical impact.

This is an AI summary of the original study and may miss details. Read our disclaimer.

Study facts

What this study's own registry entry says, in plain language.

Participants

About 12,000 people

The number the study aims to enrol. It can still change while the study runs.

Expected to start

Sep 2026

An estimate. Start dates often move.

Expected to finish

Sep 2029

An estimate. End dates often move.

Lead sponsor

Other sponsor

The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.

Who can take part

This study's own entry requirements. Only the study team can say for certain whether you qualify.

Who is studied

Patients with adnexal masses

Ages

18 years and older

Sex

Female participants only

Healthy volunteers

Not accepted

This study is not open to healthy volunteers. The entry requirements below say who it is open to.

Show the full entry requirements

Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.

Inclusion Criteria: * Patients with an adnexal mass identified at ultrasound examination who either undergo surgery within 6 months of the ultrasound or have at least 1 year of follow-up. This includes: the retrospective cohort recruited from IOTA centers, and the prospective cohort recruited from nonIOTA centers. * Age ≥ 18 years old * Availability of at least one grayscale digital ultrasound image clearly depicting the adnexal mass. * Signed written informed consent Exclusion Criteria: * Patients without available digital ultrasound images. * Patients without an outcome (final histology or follow up at one year). * Absence of written informed consent

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Conditions

The condition(s) this trial relates to.

ovarian cancer

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

Adnexal masses

How to take part

Only the study team decides who joins. These are the ways to reach them.

  1. The places running it

    1 site. The list below names each one and where it is.

  2. The official record

    ClinicalTrials.gov lists the study team's own contact details, including names and phone numbers. We don't republish those.

    Open the record ↗

  3. A doctor treating you

    A doctor who knows your case can contact a study site on your behalf, and can tell you whether this study is worth pursuing at all.

Contacts and locations

Locations

  • Fondazione Policlinico Universitario Agostino Gemelli IRCCS

    Roma, 00168, Italy