Ignite Creation Date:
2025-12-24 @ 4:49 PM
Ignite Modification Date:
2025-12-26 @ 4:26 AM
Study NCT ID:
NCT06092450
Status:
RECRUITING
Last Update Posted:
2025-05-31
First Post:
2023-10-12
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Deep Learning Radiomics Model for Predicting Post-cystectomy Outcome in Muscle Invasive Bladder Cancer
Sponsor:
First Affiliated Hospital of Chongqing Medical University
Organization:
Study Overview
Official Title:
Deep Learning Radiomics Model for Predicting Post-cystectomy Outcome From Preoperative CT in Muscle Invasive Bladder Cancer
Status:
RECRUITING
Status Verified Date:
2025-05
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief 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.
Detailed Description:
None
Study Oversight
Has Oversight DMC:
False
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
False
Is an FDA AA801 Violation?:
Secondary ID Infos
| Secondary ID | Type | Domain | Link | View |
|---|---|---|---|---|
| 2022-K508 | OTHER | The First Affiliated Hospital of Chongqing Medical University | View |