NCT04843176 Artificial Intelligence vs. LIRADS in Diagnosing HCC on CT
| NCT ID | NCT04843176 |
| Status | Recruiting |
| Phase | — |
| Sponsor | The University of Hong Kong |
| Condition | HCC |
| Study Type | INTERVENTIONAL |
| Enrollment | 250 participants |
| Start Date | 2021-03-19 |
| Primary Completion | 2025-12-31 |
Eligibility & Interventions
Eligibility Fast-Check
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What to Expect as a Participant
You will actively receive the study intervention — which may be a drug, biologic, device, or procedure.
This trial targets 250 participants in total. It began in 2021-03-19 with a primary completion date of 2025-12-31.
⚠ This information is for research awareness only. Always consult your physician before joining any clinical trial. Participation is voluntary and you may withdraw at any time.
Brief Summary
Liver cancer is the sixth most commonly diagnosed cancer and the fourth leading cause of cancer death worldwide. It is the 3rd most common cause of cancer death in Hong Kong. The five-year survival rates of liver cancer differ greatly with disease staging, ranging from 91.5% in early-stage to 11% in late-stage. The early and accurate diagnosis of liver cancer is paramount in improving cancer survival. Liver cancer is diagnosed radiologically via cross sectional imaging, e.g. computed tomography (CT), without the routine use of liver biopsy. However, with current internationally-recommended radiological reporting methods, up to 49% of liver lesions may be inconclusive, resulting in repeated scans and a delay in diagnosis and treatment. An artificial intelligence (AI) algorithm that that can accurately diagnosed liver cancer has been developed. Based on an interim analysis, the algorithm achieved a high diagnostic accuracy. The AI algorithm is now ready for implementation. 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 the diagnostic accuracy of liver cancer, which will be unbiasedly based on a composite clinical reference standard.
Eligibility 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.
Contact & Investigator
Frequently Asked Questions
Who can join the NCT04843176 clinical trial?
This trial is open to participants of all sexes, aged 18 Years or older, studying HCC. Full inclusion and exclusion criteria are listed in the Eligibility Criteria section. Always confirm your eligibility with the research team before applying.
Is NCT04843176 currently recruiting?
Yes, NCT04843176 is actively recruiting participants. Contact the research team at wkseto@hku.hk for enrollment information.
Where is the NCT04843176 trial being conducted?
This trial is being conducted at Hong Kong, Hong Kong.
Who is sponsoring the NCT04843176 clinical trial?
NCT04843176 is sponsored by The University of Hong Kong. The trial plans to enroll 250 participants.