Focal liver lesions
Conditions
Interventions
Index test:Radiomics models and deep learning models
Sponsors
The Affiliated Hospital of Guizhou Medical University
Eligibility
Sex/Gender
All
Age
18 Years to 80 Years
Inclusion criteria
Inclusion criteria: (1) Age: Adults aged 18 years or older. (2) Patients who have undergone both contrast-enhanced CT and non-contrast CT scans and were found to have focal liver lesions (FLLs). The pathological types of FLLs have been confirmed through pathology, such as hepatocellular carcinoma, cholangiocarcinoma, liver metastases, hepatic adenoma, focal nodular hyperplasia, etc.; or the FLLs have typical imaging features that can be directly diagnosed based on the enhanced images, such as hepatic hemangiomas, hepatic cysts, etc. (3) All patients have complete imaging data, and the enhanced CT images are standard triphasic scans, including the arterial phase, portal venous phase, and delayed phase.
Exclusion criteria
Exclusion criteria: (1) Incomplete imaging data. (2) Patients with renal insufficiency and contrast agent allergy are excluded from the study.
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Image Quality Assessment;Diagnostic Accuracy Metrics;Metrics for Generative Model Performance;Specificity;Sensitivity; | — |
Secondary
| Measure | Time frame |
|---|---|
| Performance Evaluation of Radiomics and Deep Learning Models;Model Development and Validation;Observe the outcome; | — |
Countries
China
Contacts
Public ContactPinggui Lei
The Affiliated Hospital of Guizhou Medical University
Outcome results
None listed