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Can AI spot ovarian cancer on CT scans before It's too late?

NCT ID NCT06851429

Diagnosis Sponsor: Chang Gung Memorial Hospital Source: ClinicalTrials.gov ↗

What the study statuses mean

This study's is highlighted.

Recruitment status, easiest to join first

Recruiting now This study
This trial is taking on new participants right now.
Not yet recruiting
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 Results may not be published yet.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This status has not been confirmed recently, so it may be out of date.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 12, 2026 · Last updated Aug 13, 2026 · Updated 1 time

Summary

This study is testing whether an artificial intelligence (AI) tool called CAT-OV can accurately identify ovarian cancer on CT scans. Ovarian cancer is often found late, when it's harder to treat, and current screening methods aren't reliable enough. The AI is being trained and tested on thousands of CT scans from women in Taiwan and the United States to see if it can flag signs of cancer that might be missed. If it works, this could lead to a new way to catch the disease earlier.

What this could mean

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

Active substance
A deep learning-based computer-aided diagnosis tool (CAT-OV) that analyzes CT images to identify ovarian cancer.
What this could lead to
If successful, this AI tool could help doctors spot ovarian cancer earlier on routine CT scans, potentially improving survival rates.
What could go wrong
The tool is still in development and needs further validation. It may not work equally well across all populations or imaging settings, and false positives or negatives remain possible.

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 12,578 people

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

Started

Sep 2022

Expected to finish

Aug 2028

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

Women who have undergone a CT scan.

Ages

20 years and older

Sex

Female participants only

Healthy volunteers

Accepted

You do not need to have the condition being studied to take part.

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: 1. Age ≥ 20 years old. 2. Female 3. undergone a CT scan 4. undergone a CT scan within 180 days prior to ovarian surgery for histopathological evaluation. Exclusion Criteria: 1. Age \< 20 years old. 2. Non-female 3. Non-CT imaging 4. Incorrect image orientation 5. Number of slices \< 10 6. Slice thickness \>10 mm or \< 1 mm 7. Unsuccessful DICM-to-NIfTI 8. Pelvic subvolume extraction failed 9. Non-contrast CT scans 10. Metallic artifacts 11. Inconclusive cases

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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.

Ovarian cancer

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

  • Chang Gung Memorial Hospital

    COMPLETED

    Taoyuan City, Guishan District, 333, Taiwan

  • Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital

    RECRUITING

    Taoyuan, Guishan, 333, Taiwan

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