NCT07153783Completed
Interventional AI-Human Collaboration for Liver Tumor Diagnosis
AI-human Collaborative Diagnosis of Liver Tumors Using CE-CT
Source: ClinicalTrials.gov · Last updated 18 Nov 2025
Brief summary (registry, in English)
Recent advances in artificial intelligence (AI), particularly deep learning technology, have transformed medical imaging analysis. AI systems have demonstrated diagnostic performance comparable to or exceeding that of expert radiologists in specific tasks. Liver-focused AI diagnostic systems have achieved promising results in multi-center validations; however, these retrospective studies have not yet addressed two critical gaps. First, large-scale prospective trials are required to establish real-world clinical effectiveness. Second, it remains unclear whether AI can be organically embedded into clinical diagnostic workflows to reshape diagnostic and therapeutic pathways, particularly by enhancing the detection and follow-up of hepatic malignancies and ultimately improving patient outcomes.
- Status (registry)
- Completed
- Study type
- Interventional
- Enrollment
- 10333 (actual)
- First submitted
- 26 Aug 2025
- Start date
- 1 Sept 2025
- Primary completion date
- 29 Oct 2025
- Lead sponsor
- Shengjing Hospital
- Diseases
- Liver and biliary tract cancer
- NCT number
- NCT07153783
What you commit to
- Study type: Interventional
- Participants enrolled: 10333
- From 1 Sept 2025 to the primary completion date, 29 Oct 2025
- 1 site in 1 country
- Visits and tests: ask the trial team, the registry does not list them
Built from the registry fields of ClinicalTrials.gov. It describes the study, not your situation.
Who cannot take part
Copied verbatim from ClinicalTrials.gov and grouped by topic. Only the trial team decides who can take part.
Prior treatment
- History of recent upper-abdominal surgery (within 30 days) or major hepatobiliary-pancreatic surgery affecting liver evaluation (e.g., liver transplantation or Whipple procedure); patients with prior simple cholecystectomy or single-lesion interventional procedures are not excluded
Other illness
- History of recent hepatic trauma (within 30 days)
Other
- Poor image quality or severe noise artifacts (e.g., metal or motion artifacts)
- Missing required imaging phases (required at least non-contrast, arterial, and venous phases) or inadequate scan range (e.g., lower-abdomen CT such as pelvic or rectal scans not covering the liver)
Who the study is looking for
- Age range 18 years and above
- Underwent dynamic contrast-enhanced abdominal CT examination with liver coverage
- Imaging must include at least three required phases: non-contrast, arterial phase, and venous phase; an delayed phase is optional
- Complete imaging data that meet AI system analysis requirements.
Age in the registry: 18 years to - · Sex: All · Accepts healthy volunteers
Sites (1)
Sites in registry order. Pick your city on the disease page to sort them by distance.
| Site | City | Country | Site status |
|---|---|---|---|
| Shengjing Hospital Of China Medical University Coordinator of this site? Confirm its status | Shenyang | China | Unknown status |
Related publications
- Large-scale AI-guided liver malignancy diagnosis: multicenter study and a single-arm trial.Nat Med · 2026 · PMID 42618635
This page is information, not medical advice. Discuss any trial with your doctor.