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AI takes on radiologists: can a computer beat the standard for liver cancer diagnosis?

NCT ID NCT06626087

Diagnosis Sponsor: The University of Hong Kong 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 Results may not be published yet.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This status has not been confirmed recently, so it may be out of date.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 study tested a new artificial intelligence (AI) algorithm against the standard LI-RADS criteria for diagnosing liver cancer (hepatocellular carcinoma) on CT scans. Researchers enrolled 300 people at risk for liver cancer who had a new liver nodule found on ultrasound. The goal was to see if the AI could match or improve diagnostic accuracy compared to the current standard method.

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 algorithm
What this could lead to
If successful, this AI could help doctors diagnose liver cancer more accurately and quickly from CT scans.
What could go wrong
This is a completed study with 300 participants, but the AI is still a prototype and may not outperform current methods in real-world settings.

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

300 people

The number who actually took part.

Started

Nov 2023

Finished

Mar 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.

Ages

18 years and older

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\. Age \>=18 years. * 2\. Defined as the at-risk population requiring regular liver ultrasonography surveillance. These include: 1. Cirrhotic patients of any disease etiology, 2. Chronic hepatitis B patients of age ≥40 years for men, age ≥50 years for women or with a family history of HCC. * 3\. At least one new-onset focal liver nodule detected on liver ultrasonography. Exclusion Criteria: * 1\. Liver nodules of \<1 cm. Currently such nodules are not reported using LI-RADS criteria but are recommended for a repeat scan in 3-6 months. In patients with multiple liver nodules, the largest nodule will be assessed. * 2\. Patients with contraindications for contrast CT imaging, including a history of contrast anaphylaxis and impaired renal function (glomerular filtration rate \<30 ml/min). * 3\. Patients with prior transarterial chemoembolization or other interventional procedures with intrahepatic injection of lipiodol. Lipiodol is extremely hyperdense on computed tomography and will preclude objective interpretation. Such patients were also excluded in the development of our prototype AI algorithm.

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Conditions

The condition(s) this trial relates to.

hepatocellular carcinoma Liver Neoplasms

As listed by the trial registrant

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

Hepatocellular carcinoma

Contacts and locations

Locations

  • Department of Medicine and Department of Surgery, The University of Hong Kong, Queen Mary Hospital

    Hong Kong, Hong Kong

  • Department of Medicine, The University of Hong Kong, Queen Mary Hospital

    Hong Kong, Hong Kong

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