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AI joins radiologists in massive liver tumor diagnosis trial

NCT ID NCT07153783

Diagnosis Sponsor: Shengjing 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 Results may not be published yet.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This status has not been confirmed recently, so it may be out of date.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 Jun 27, 2026 · Last updated Jun 27, 2026

Summary

This large completed trial tested whether an AI system can help radiologists better diagnose liver tumors from CT scans. Over 10,000 adults with various liver conditions participated. The AI analyzed scans overnight, and a senior radiologist reviewed any differences between the AI and the initial report. The goal was to see if this teamwork improves diagnostic accuracy in real-world hospital settings.

What this could mean

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

Active substance
AI-human collaborative diagnostic system for contrast-enhanced CT scans
What this could lead to
If successful, this could show that AI helps radiologists diagnose liver tumors more accurately and efficiently in real-world settings.
What could go wrong
This is a completed trial, but results are not yet published. The AI may not perform as well in practice as in earlier studies, and it may not work for all types of liver lesions.

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.

Phase

Not a phased trial

Phase numbers describe drug development. The registry uses this when they do not apply, as it does for trials of devices, procedures or behaviour changes, and for observational studies.

Participants

10,333 people

The number who actually took part.

Started

Sep 2025

Finished

Nov 2025

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.

Ages

18 years and older

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: 1. Age range 18 years and above 2. Underwent dynamic contrast-enhanced abdominal CT examination with liver coverage 3. Imaging must include at least three required phases: non-contrast, arterial phase, and venous phase; an delayed phase is optional 4. Complete imaging data that meet AI system analysis requirements. Exclusion Criteria: 1. History of recent upper-abdominal surgery (within 30 days) or major hepatobiliary-pancreatic surgery affecting liver evaluation (e.g., liver transplantation or Whipple procedure); patients with prior simple cholecystectomy or single-lesion interventional procedures are not excluded 2. History of recent hepatic trauma (within 30 days) 3. Poor image quality or severe noise artifacts (e.g., metal or motion artifacts) 4. Missing required imaging phases (required at least non-contrast, arterial, and venous phases) or inadequate scan range (e.g., lower-abdomen CT such as pelvic or rectal scans not covering the liver)

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Conditions

The condition(s) this trial relates to.

cholangiocarcinoma Cirrhosis, Familial, with Pulmonary Hypertension Cysts focal nodular hyperplasia hepatocellular carcinoma intrahepatic cholangiocarcinoma liver hemangioma

As listed by the trial registrant

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

Cyst Focal nodular hyperplasia Hepatic hemangioma Hepatic metastasis Hepatocellular carcinoma (HCC) Intrahepatic cholangiocarcinoma (ICC)

Contacts and locations

Locations

  • Shengjing Hospital of China Medical University

    Shenyang, Liaoning, 110004, China

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