A Prototype Artificial Intelligence Algorithm Versus Liver Imaging Reporting and Data System (LI-RADS) Criteria in Diagnosing Hepatocellular Carcinoma on Computed Tomography: a Randomized Trial
Sponsor: The University of Hong Kong
Trial Details
| Condition | Hepatocellular Carcinoma |
| Intervention | Prototype artificial intelligence algorithm; LI-RADS |
| Phase | NA |
| Status | Completed |
| Participants | 300 |
| Est. Completion | 31 Mar 2026 |
| Last Updated | 15 May 2026 |
Primary Outcome
Diagnostic accuracy for HCC
Eligibility Criteria
Inclusion Criteria
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.
Trial Sites
Countries
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