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A Prototype AI Algorithm Versus Liver Imaging Reporting and Data System (LI-RADS) Criteria in Diagnosing HCC on CT

NCT06626087 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 300

Last updated 2026-05-15

No results posted yet for this study

Summary

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.

Conditions

Interventions

DIAGNOSTIC_TEST

Prototype artificial intelligence algorithm

Developed by the University of Hong Kong

DIAGNOSTIC_TEST

LI-RADS

The Liver Imaging Reporting and Data System (LIRADS) was established to standardize the lexicon, interpretation and communication of radiological findings related to HCC

Sponsors & Collaborators

  • Education University of Hong Kong

    collaborator OTHER

  • The University of Hong Kong

    lead OTHER

Principal Investigators

  • Wai-Kay Seto, MD · The University of Hong Kong

Study Design

Allocation
RANDOMIZED
Purpose
DIAGNOSTIC
Masking
SINGLE
Model
PARALLEL

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2023-11-01
Primary Completion
2026-03-31
Completion
2026-03-31

Countries

  • Hong Kong

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06626087 on ClinicalTrials.gov