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AI reads CT scans to spot kidney tumors without contrast dye

NCT ID NCT07304492

Diagnosis Sponsor: Fudan University Source: ClinicalTrials.gov ↗

What the study statuses mean

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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 Results may not be published yet.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This status has not been confirmed recently, so it may be out of date.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 Jun 25, 2026 · Last updated Jun 27, 2026 · Updated 2 times

Summary

This observational study will test an artificial intelligence model that can automatically detect and diagnose kidney tumors and cysts using non-contrast CT scans. Researchers aim to enroll 10,000 patients to build a system that distinguishes between cysts, benign growths, and malignant tumors. If successful, this could make kidney cancer screening safer and more accessible by avoiding the need for contrast dye.

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 model
What this could lead to
If successful, this AI could help doctors find and diagnose kidney tumors faster and safer using standard CT scans, without needing contrast dye.
What could go wrong
This is an early observational study, not a treatment trial. The AI may not be accurate enough for real-world use, and results may not apply to all patients or hospitals.

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 10,000 people

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

Expected to start

Jan 2026

An estimate. Start dates often move.

Expected to finish

Dec 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

Patients who underwent an abdominal CT examination.

Ages

18 to 80 years

Sex

Anyone

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. Patients who underwent an abdominal CT examination. 2. Patients with renal lesions were managed according to standard clinical pathways, which included follow-up, biopsy, or surgery. 3. Malignant lesions were pathologically confirmed; benign lesions were confirmed by either pathological diagnosis or imaging follow-up. 4. No prior treatment had been received for the renal disease. Exclusion Criteria: 1. Patients refuse to undergo recommended follow-up, biopsy, or surgery, which precluded definitive diagnosis of the renal lesion. 2. Absence of complete pathological confirmation for lesions suspected to be malignant. 3. Patients have received any form of prior treatment for the renal lesion. 4. Poor image quality that hampered diagnostic evaluation.

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Conditions

The condition(s) this trial relates to.

cystic kidney disease kidney cancer kidney neoplasm

As listed by the trial registrant

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

Renal cyst Renal neoplasms

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

  • Fudan university Shanghai Cancer Center

    Shanghai, Shanghai Municipality, 200032, China

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