Development of AI Model for Renal Tumor Diagnosis Using CT and Lab Tests
- Conditions
- Renal Tumors
- Registration Number
- NCT06761742
- Lead Sponsor
- RenJi Hospital
- Brief Summary
This multi-center retrospective study aims to develop a multimodal artificial intelligence diagnostic model using preoperative contrast-enhanced CT images and routine laboratory parameters from patients with renal tumors. The model is designed to assist clinicians in accurately predicting the pathological subtypes of renal tumors preoperatively, enabling detailed diagnoses and advancing precision medicine.
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- COMPLETED
- Sex
- All
- Target Recruitment
- 1922
- Underwent renal tumor resection with a complete postoperative pathological report, and the pathological diagnosis is one of the following types: clear cell renal cell carcinoma, papillary renal cell carcinoma, chromophobe renal cell carcinoma, renal angiomyolipoma, or renal oncocytoma.
- Complete and available four-phase contrast-enhanced CT scans prior to surgery.
- Complete and available routine laboratory test results prior to surgery.
- Incomplete CT data or poor image quality that affects diagnostic analysis.
- A time interval of more than three months between imaging or laboratory testing and pathological diagnosis.
- Patients diagnosed with fat-rich renal angiomyolipoma (AML).
- Pathological diagnosis indicating the coexistence of two or more pathological types of renal tumors.
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method postoperative pathological report From the time of surgery to the release of the postoperative pathological report (typically within 2 weeks post-surgery).
- Secondary Outcome Measures
Name Time Method
Related Research Topics
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Trial Locations
- Locations (1)
Shanghai Jiaotong University School of Medicine, Renji Hospital
🇨🇳Shanghai, Shanghai, China