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AI spots hidden liver disease in routine scans

NCT ID NCT07613827

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 This study
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 Results may not be published yet.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This status has not been confirmed recently, so it may be out of date.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 26, 2026 · Last updated Jun 27, 2026 · Updated 1 time

Summary

This study tests whether an AI system can help doctors identify patients with fatty liver disease who need specialist care. About 8,000 adults getting routine CT scans will have their images analyzed by AI to flag those at risk. The goal is to see if AI can improve detection and referral compared to standard care.

What this could mean

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

Active substance
AI-guided screening system
What this could lead to
If successful, this could make early detection of serious fatty liver disease faster and more accurate using CT scans already done for other reasons.
What could go wrong
This is an early-stage study testing a new workflow, not a treatment. The AI may not improve detection in real-world settings and could lead to unnecessary referrals.

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

About 7,969 people

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

Started

Feb 2026

Expected to finish

Feb 2027

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.

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: * Adults aged ≥18 years undergoing routine non-contrast or contrast-enhanced chest or abdominal CT examination. * CT images with adequate hepatic coverage and sufficient image quality for MAOSS analysis. * Willing to undergo the recall evaluation and either: having a FIB-4 result within the past 1 month, or willing to complete blood testing (ALT, AST, platelet count) required for FIB-4 calculation and undergo FibroScan or MRE assessment. * Willing to participate in the study and able to provide written informed consent at the time of recall. Exclusion Criteria: * Known malignant liver tumors (e.g., HCC, cholangiocarcinoma) or a history of liver transplantation or major hepatic resection. * Known cirrhosis based on noninvasive fibrosis assessment tests, liver biopsy or complications of decompensated disease, or with a documented history of cirrhosis identified by clinical notes will be excluded. * Biliary obstruction, acute cholangitis, or other conditions that may interfere with interpretation of liver biochemistry or fibrosis risk assessment. * CT images with severe artifacts or incomplete liver coverage preventing reliable MAOSS analysis. * Severe acute systemic illness (e.g., sepsis, shock, acute heart failure), or pregnancy or breastfeeding. * Unwilling or unable to complete recall procedures, including required blood tests, FibroScan, or MRE when indicated, or unable to comply with study follow-up. * Severe comorbidity with an expected survival of less than 1 year (e.g., terminal malignancy).

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Conditions

The condition(s) this trial relates to.

alcoholic fatty liver disease cirrhosis of liver fatty liver disease fibrotic liver disease metabolic dysfunction and alcohol associated liver disease

As listed by the trial registrant

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

Liver fibrosis Liver fibrosis progression in chronic liver disease Liver steatosis Steatotic liver disease Steatotic liver disease of mixed origin (metald)

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

    The full official record for this study. This one lists no contact details, but it is the first place any would appear.

    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

  • Shengjing Hospital of China Medical University

    Shenyang, Liaoning, 110004, China

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