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
This study aims to prospective validate this AI algorithm in comparison with the current standard of radiological reporting in a randomized manner in the at-risk population undergoing triphasic contrast CT. This research project is totally independent and separated from the actual clinical reporting of the CT scan by the duty radiologist. The primary study outcome is to compare the diagnostic performance of the prototype AI algorithm versus LI-RADS criteria in determining HCC on CT in the at-risk population.
• 1\. Age \>=18 years.
• 2\. Defined as the at-risk population requiring regular liver ultrasonography surveillance.
∙ These include:
⁃ Cirrhotic patients of any disease etiology,
⁃ 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.