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Multimodal Prediction of Postoperative Prognosis After Partial Nephrectomy for Endophytic Renal Cell Carcinoma
Sponsor: Tianjin Medical University Second Hospital
Summary
This retrospective observational cohort study aims to develop and externally validate an imaging-clinical multimodal fusion model for predicting postoperative prognosis in patients with endophytic renal cell carcinoma undergoing partial nephrectomy. Preoperative computed tomography imaging features, three-dimensional reconstruction-derived tumor characteristics, radiomics features, and clinical variables will be integrated using machine learning and deep learning approaches. The primary objective is to evaluate whether the multimodal model improves prediction of postoperative prognostic outcomes compared with single-modality models based on clinical or imaging features alone.
Official title: Development and External Validation of an Imaging-Clinical Multimodal Fusion Model for Predicting Postoperative Prognosis After Partial Nephrectomy in Patients With Endophytic Renal Cell Carcinoma
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
OBSERVATIONAL
Enrollment
406
Start Date
2026-01-01
Completion Date
2026-12-01
Last Updated
2026-07-13
Healthy Volunteers
No
Conditions
Interventions
Imaging-clinical multimodal prognostic modeling
Preoperative CT imaging features, radiomics features, three-dimensional reconstruction-derived features, and clinical variables will be retrospectively analyzed to develop and validate a multimodal model for predicting postoperative prognosis after partial nephrectomy. No intervention will be assigned to participants.
Locations (1)
Tianjin Medical University Second Hospital
Tianjin, Tianjin Municipality, China