AI-assisted imaging for diagnosing and managing focal liver lesions
Official title: A Prospective, Randomized Controlled Trial of Artificial Intelligence-Assisted Imaging for the Diagnosis and Clinical Management of Focal Liver Lesions
Run by Sun Yat-sen University · NCT07926672 · Data updated 2026-11-12
Researchers are testing whether AI-powered imaging can help doctors better diagnose focal liver lesions in adults undergoing CT scans.
Quick facts
| Study type | Interventional |
|---|---|
| Ages | 18 Years to 75 Years |
| Sex | All |
| Enrollment | 10000 (estimated) |
| Sponsor | Sun Yat-sen University Academic / other |
| Locations | 2 sites (Guangzhou, Guangdong and 1 other locations) |
| Status | Recruiting |
| Started | December 15, 2026 |
| Main results expected | April 15, 2027 |
| Study ends | May 31, 2027 |
| Registry record updated | November 9, 2026 |
| Trial ID | NCT07926672 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Adults aged 18-75 who are undergoing clinically indicated liver CT examinations.
✕Probably not a fit
Patients whose imaging data are not compatible with predefined technical requirements or have nondiagnostic scans due to artifacts may not benefit.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This trial compares AI-assisted imaging interpretation with conventional physician evaluation to determine if AI can improve diagnostic accuracy for focal liver lesions. Participants are adults 18 to 75 undergoing clinically indicated liver CT exams. The study analyzes imaging data to see if AI can aid in selecting appropriate treatment strategies, recognizing that distinguishing lesion types can be challenging due to overlapping imaging features. The design focuses on real-world imaging scenarios and aims to support clinical decision-making with AI-driven insights.
Why it matters
Potential benefit: If successful, AI-assisted imaging could improve diagnostic accuracy and help guide treatment decisions for patients with focal liver lesions.
How similar studies have gone: Previous work in AI-assisted medical imaging has shown promise in improving accuracy for complex liver lesion evaluation, but results vary by setting.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * Patients aged 18-75 years. * Patients undergoing clinically indicated liver computed tomography (CT) examinations. Exclusion Criteria: -Liver CT examinations that do not meet the predefined technical requirements or are nondiagnostic because of severe imaging artifacts.
Where it's running
-
The First Affiliated Hospital, Sun Yat-sen University
Guangzhou, Guangdong, China Recruiting -
Sun Yat-sen University Cancer Center
Guangzhou, Guangdong, China Recruiting
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.