High-grade dysplastic nodules (HGDN) and small hepatocellular carcinoma (sHCC)
Conditions
Interventions
Sponsors
Southern Medical University Southern Hospital
Eligibility
Sex/Gender
All
Age
18 Years to No maximum
Inclusion criteria
Inclusion criteria: 1. Age >= 18 years; 2. Gender: Male or female, no restriction; 3. Patients diagnosed and treated at Nanfang Hospital, Southern Medical University between January 2014 and June 2024; 4. Underwent EOB-MRI examination; 5. No prior local liver treatments, such as partial hepatectomy, thermal ablation, transarterial chemoembolization (TACE), or other interventional therapies.
Exclusion criteria
Exclusion criteria: 1.Patients without a definitive final diagnosis; 2.Poor image quality; 3.Patients with incomplete clinical data
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| The performance of the model in LI-RADS classification, detection and classification of HCC/HGDN, and prediction of malignant progression (including accuracy, sensitivity, precision, and F1 score).; | — |
Secondary
| Measure | Time frame |
|---|---|
| The impact of the AI-assisted diagnostic system on the diagnostic performance of clinicians with varying levels of experience;The value of EOB-MRI images in classifying the benignity/malignancy of hepatic nodules and predicting the risk of malignant progression in high-grade dysplastic nodules (HGDN).;The value of clinical characteristics (e.g., age, gender, liver function indicators, etc.) in distinguishing the benignity/malignancy of hepatic nodules and predicting the risk of malignant progression in high-grade dysplastic nodules (HGDN).; | — |
Countries
China
Contacts
Public ContactYan Chenggong
Southern Medical University Southern Hospital
Outcome results
None listed