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Artificial Intelligence–Based Classification, Diagnosis, and Prognostic Analysis of Hepatic Lesions Using MR Imaging: A Multicenter Study

Artificial Intelligence–Based Classification, Diagnosis, and Prognostic Analysis of Hepatic Lesions Using MR Imaging

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600123350
Enrollment
Unknown
Registered
2026-04-24
Start date
2026-05-01
Completion date
Unknown
Last updated
2026-05-04

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Focal liver lesions

Interventions

Gold Standard:Malignant diseases such as intrahepatic cholangiocarcinoma have been confirmed by pathology
Hepatocellular carcinoma is confirmed by pathology or by at least two imaging examinations as stipulated in the primary liver cancer diagnosis and treatment guidelines
Benign lesions need to meet any of the following conditions: 1) Confirmed by a joint diagnosis of 3 radiologists, 2) Confirmed by at least 6 months of follow-up through two imaging examination methods
Index test:MRI + AI Diagnostic System for Focal Liver Lesions (including classification diagnosis, lesion annotation, report generation, and prognosis assessment)

Sponsors

The First Affiliated Hospital Of Guangxi Medical University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: 1. The patient is at least 18 years old; 2. The MRI sequence is complete (T1WI, T2WI, DWI/ADC, dynamic enhancement arterial phase/portal venous phase/delayed phase); 3. There is a clear label required for the diagnostic endpoint (HCC, ICC, cyst, hemangioma, metastasis, FNH, other rare tumors, abscess or normal, etc. of different categories); 4. The image quality meets the diagnostic requirements.

Exclusion criteria

Exclusion criteria: 1. No enhanced MRI scan was performed; 2. Has undergone surgery or other anti-tumor treatments; 3. The clinical diagnosis is unclear.

Design outcomes

Primary

MeasureTime frame
Area under the curve;Recall;Accuracy;Specificity;Sensitivity;

Countries

China

Contacts

Public ContactYidi Chen

The First Affiliated Hospital Of Guangxi Medical University

chenyidi1152@126.com+86 186 7169 8163

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: May 7, 2026