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

NCT06092450 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 500

Last updated 2025-05-31

No results posted yet for this study

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

Interventions

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

Sponsors & Collaborators

  • First Affiliated Hospital of Chongqing Medical University

    lead OTHER

Eligibility

Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2023-08-01
Primary Completion
2025-06-01
Completion
2025-06-01

Countries

  • China

Study Locations

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Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06092450 on ClinicalTrials.gov