NCT06092450

Deep Learning Radiomics Model for Predicting Post-cystectomy Outcome in Muscle Invasive Bladder Cancer

Deep Learning Radiomics Model for Predicting Post-cystectomy Outcome From Preoperative CT in Muscle Invasive Bladder Cancer

• Status: Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 500 (estimated)
• Sponsor: First Affiliated Hospital of Chongqing Medical University · Academic / Other
• Sex: All
• Age: —
• Healthy volunteers: Not accepted

Summary

Muscle invasive bladder cancer (MIBC) has a poor prognosis even after radical cystectomy. Postoperative survival stratification based on radiomics and deep learning may be useful for treatment decisions to improve prognosis. This study was aimed to develop and validate a deep learning radiomics model based on preoperative enhanced CT to predict postoperative survival in MIBC.

Conditions

• Bladder Cancer

Interventions

Type	Name	Description
OTHER	develop and validate a deep learning radiomics model based on preoperative enhanced CT image	develop and validate a deep learning radiomics model based on preoperative enhanced CT to predict postoperative survival in MIBC

Timeline

• Start date: 2023-08-01
• Primary completion: 2025-06-01
• Completion: 2025-06-01
• First posted: 2023-10-23
• Last updated: 2025-05-31

Locations

1 site across 1 country: China