Contrast-enhanced CT-based Deep Learning Model for Preoperative Prediction of Disease-free Survival (DFS) in Localized Clear Cell Renal Cell Carcinoma (ccRCC)

Mingzhao Xiao

Status: Enrolling

Conditions: Recurrent Renal Cell Cancer; Clear Cell Renal Cell Carcinoma; Prognostic Cancer Model

Study type: Observational

Funder types: Other

Identifiers

NCT06088134

DL-ccRCC

Details and patient eligibility

About

This study aims to preoperatively predict DFS of patients with localised ccRCC using a deep learning prognostic model based on enhanced contrast CT images, validate it's predictive ability in multicentre data and compare it's predictive ability with traditional models.

Enrollment: 800 estimated patients

Sex: All

Volunteers: No Healthy Volunteers

Inclusion criteria

• underwent partial/radical nephrectomies
• histologically diagnosed as ccRCC
• with complete clinical data and preoperative CT image data

Exclusion criteria

• with incomplete clinic-pathological data
• lack of preoperative contrast-enhanced CT images or the image quality was unsuitable for analysis
• who received pre-surgery neoadjuvant or adjuvant therapies
• with multiple renal tumors or/and had synchronous metastasis

Trial design

800 participants in 2 patient groups

Non-recurrence group

Recurrence group