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Development of AI Model for Renal Tumor Diagnosis Using CT and Lab Tests

Completed
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
Inclusion Criteria
  • 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.
Exclusion Criteria
  • 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
NameTimeMethod
postoperative pathological reportFrom the time of surgery to the release of the postoperative pathological report (typically within 2 weeks post-surgery).
Secondary Outcome Measures
NameTimeMethod

Trial Locations

Locations (1)

Shanghai Jiaotong University School of Medicine, Renji Hospital

🇨🇳

Shanghai, Shanghai, China

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