Imaging and urine biomarkers for renal tumor assessment.
- Conditions
- renal tumorC64Malignant neoplasm of kidney, except renal pelvis
- Registration Number
- DRKS00029264
- Lead Sponsor
- Department of Diagnostic and Interventional Radiology, University Medical Center Goettingen
- Brief Summary
Not available
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- Pending
- Sex
- All
- Target Recruitment
- 905
Inclusion Criteria
patients age > 18yo with radiologically or urological suspected renal tumor receiving CT imaging; or those undergoing systemic therapy for renal tumors
Exclusion Criteria
patients unable for comprehend the consent for study participation
Study & Design
- Study Type
- observational
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method 1) for non-metastatic RCC: development of a deep learning algorithm combining CT-imaging-data, clinical information, and urine biomarker expression to predict renal tumor histological subtype and malignancy.<br><br>2) for metastatic RCC (mRCC): development of a deep learning algorithm combining CT-imaging-data, clinical information, and urine biomarker expression to predict renal tumor histological subtype, molecular expression patterns and response to systemic therapy.
- Secondary Outcome Measures
Name Time Method inter- / intrareader reliability of radiologists; progression-free, cancer-free and overall survival