LEAF (Liver Tumor dEtection And classiFication AI)
Recruiting now · Not applicable
Conditions studied: Liver Malignancy
In brief
This study aims to assess the feasibility of leveraging non-contrast CT and artificial intelligence to detect liver cancer in consecutive real-world patients. To this end, we deploy LEAF in a prospective real-world clinical setting for real-time monitoring, with a particular focus on flagging cases with liver cancer that may be missed by routine clinical workflow.
Key facts
- Study ID
- NCT06859840
- Run by
- Zhejiang University
- People needed
- 2500
- Starts
- 2026-07-17
- Expected to finish
- 2026-11-10
- Last updated by the study team
- 2026-07-17
Who can join
Age: 18 and older, up to 90. Sex: any. Healthy volunteers: accepted.
You may qualify if…
- Age range 18 years and above;
- Underwent non-contrast chest or abdominal CT examination with liver coverage;
- Patients with an established diagnosis of cirrhosis;
- Patients with an established diagnosis of extrahepatic cancer.
You may not qualify if…
- Patients who have been diagnosed with malignant liver tumor;
- Patients who underwent liver transplantation;
- Low quality image, severe artifacts and noise.
Where it is running
- the First Affiliated Hospital, School of Medicine, Zhejiang University — Hangzhou, Zhejiang, China (enrolling)
Full record on ClinicalTrials.gov
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