Adrenal tumor
Conditions
Interventions
Gold Standard:Pathological diagnosis result
Index test:Machine Learning Model Based on CT Radiomics Features
Sponsors
Fujian Medical University Union Hospital
Eligibility
Sex/Gender
All
Age
18 Years to 65 Years
Inclusion criteria
Inclusion criteria: 1. Patients undergoing unilateral adrenal mass resection; 2. Preoperative routine CT imaging revealed a unilateral adrenal mass with a diameter greater than 1 cm; 3. Patients have complete medical history data; 4. Had not received any treatment related to the adrenal tumor prior to the CT scan; 5. Each CT scan included images of the arterial phase, venous phase, and non-contrast phase, and triple-phase CT images were used in all cases; 6. Patients aged between 18 and 65 years inclusive.
Exclusion criteria
Exclusion criteria: 1. Cases with incomplete clinical data; 2. CT examination revealed multiple adrenal masses or a single mass with a diameter of less than 1 cm; 3. Poor image quality or imaging artifacts.
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Diagnostic performance of the radiomics model for adrenal tumor functional status prediction; | — |
Secondary
| Measure | Time frame |
|---|---|
| Sensitivity;Specificity;Accuracy;Identification of key radiomic features associated with tumor functional status; | — |
Countries
China
Contacts
Public ContactLi Mengqiang
Department of Urology, Fujian Medical University Union Hospital
Outcome results
None listed