Multimodal Prediction of Postoperative Prognosis After Partial Nephrectomy for Endophytic Renal Cell Carcinoma

Condition(s) studied

Investigational drug(s) / intervention(s)

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.

Study 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.

Eligibility

Primary outcome measure(s)

• Modified Pentafecta Achievement After Partial Nephrectomy — From the date of partial nephrectomy to the last available postoperative follow-up, up to 12 months after surgery.
  Modified pentafecta achievement will be defined as the simultaneous fulfillment of predefined postoperative outcome criteria, including negative surgical margin, absence of major postoperative complications, preservation of renal function, absence of significant perioperative adverse events, and absence of early tumor recurrence or other prespecified unfavorable outcomes. Patients who do not meet all criteria will be classified as modified pentafecta failure.

Trial sites (1)

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