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AI takes on knee scans: a smarter way to spot joint problems?

NCT ID NCT07784686

Knowledge-focused Sponsor: Tang-Du Hospital 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
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 This study
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 Results may not be published yet.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This status has not been confirmed recently, so it may be out of date.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 25, 2026 · Last updated Aug 26, 2026 · Updated 1 time

Summary

This study is testing whether artificial intelligence can accurately analyze knee MRI images. Researchers will review thousands of existing knee scans to see if AI can identify and measure knee structures and abnormalities as well as trained experts. The goal is to make knee imaging evaluation more objective and consistent, potentially improving how knee conditions are diagnosed and monitored.

What this could mean

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

Active substance
Artificial intelligence-based image analysis of knee MRI scans
What this could lead to
If successful, this could lead to more objective and consistent AI tools for reading knee MRIs, potentially aiding diagnosis and treatment planning.
What could go wrong
This is an observational study using existing scans, so it cannot prove AI improves patient outcomes. The AI's performance may not generalize to other hospitals or MRI machines.

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

9,500 people

The number who actually took part.

Started

Jul 2026

Finished

Aug 2026

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

The study population consisted of patients who underwent knee MRI examinations at participating medical centers during the predefined study period. Eligible participants were retrospectively identified from existing imaging and clinical databases according to the predefined inclusion and exclusion criteria.

Ages

Children (under 18), adults (18 to 64) and older adults (65 and over)

Sex

Anyone

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: * Complete knee MRI data, including sagittal and coronal images. Adequate image quality without significant motion artifacts, metal artifacts, or magnetic susceptibility artifacts, with clear visualization of key anatomical structures of the knee. Complete demographic and clinical information available for study grouping and analysis. Exclusion Criteria: * Incomplete MRI data or poor image quality. History of knee surgery or implantation. Incomplete clinical information.

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As listed by the trial registrant

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

Knee joint

Contacts and locations

Locations

  • Tangdu Hospital, Fourth Military Medical University

    Xi'an, Shaanxi, 710038, China

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