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AI reads CT scans to spot rare kidney cancer before surgery

NCT ID NCT07181954

Knowledge-focused Sponsor: First Affiliated Hospital of Fujian Medical University 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 Results may not be published yet.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This status has not been confirmed recently, so it may be out of date.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 Jun 26, 2026 · Last updated Jun 26, 2026

Summary

This completed study tested whether a computer model could predict a rare type of kidney cancer (MIT family translocation kidney cancer) from standard CT scans. Researchers analyzed data from 746 patients with kidney cancer, using AI to find patterns in the scans that might indicate this specific cancer type. The goal was to improve diagnosis before surgery, allowing for more personalized treatment.

What this could mean

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

What this could lead to
If successful, this could lead to a new, non-invasive way to identify a rare kidney cancer before surgery, helping doctors choose the best treatment.
What could go wrong
This is a retrospective study, meaning it looks back at existing data. The model needs to be tested in real-time, prospective studies to confirm it works in practice.

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

746 people

The number who actually took part.

Started

Jan 2016

Finished

Dec 2023

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

Retrospective data collection was conducted from January 2009 to December 2023 at the First Affiliated Hospital of Fujian Medical University, the Provincial Hospital Affiliated to Fuzhou University, the Second Affiliated Hospital of Fujian Medical University, the First Affiliated Hospital of Chongqing Medical University, and the First Affiliated Hospital of Xiamen University.

Ages

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

Sex

Anyone

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: 1. Pathological diagnosis of RCC; 2. Have complete clinical, pathological and follow-up data; 3. Renal CT plain scan and enhanced images can be obtained from the image storage and transmission system (PACS) Exclusion Criteria: 1. Patients who are not suitable for treatment: patients with severe comorbidities or unable to receive any form of treatment; 2. Combined with other malignant tumors: have been treated with other malignant tumors (or have other untreated active malignancies at the same time); 3. Patients with poor CT image quality/absence; 4. Patients with missing clinical/pathological/follow-up data

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Conditions

The condition(s) this trial relates to.

renal cell carcinoma

As listed by the trial registrant

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

Renal cell carcinoma (RCC)

More trials for these conditions

Other studies related to the condition(s) this trial covers.