Clinical trial · Observational
Whole-slide Image and CT Radiomics Based Deep Learning System for Prognostication Prediction in Bladder Cancer
NCT06389019CI-TRIAL-00090246recruitingClinicalTrials.gov clinicaltrialsProvenance
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
Bladder cancer (BLCA), with its diverse histopathological features and varying patient outcomes, poses significant challenges in diagnosis and prognosis. Postoperative survival stratification based on radiomics feature and whole slide image feature may be useful for treatment decisions to improve prognosis. In this research, we aim to develop a deep learning-based prognostic-stratification system for automatic prediction of overall and cancer-specific survival in patients with BLCA.
Conditions
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Bladder Cancer | Malignant Bladder Neoplasm | CURATED_EXACT | 0.92 |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| Deep learning system for prognostication prediction in bladder cancer | Other | — | UNRESOLVED |
Design
Arms and outcomes
Arms (1)
- label
- BLCA
- description
- patients with bladder cancer who had surgery like radical cystectomy or transurethral resection of bladder tumour (TURBT).
- interventionNames
- Other: Deep learning system for prognostication prediction in bladder cancer
Primary outcomes (1)
- measure
- Overall survival
- timeFrame
- up to 10 years
- description
- the time from the date of surgery to death from any cause or the date of last contact (censored observation) at the date of data cut-off.
Secondary outcomes (1)
- measure
- Recurrence free survival
- timeFrame
- up to 10 years
- description
- the time from the date of surgery to the date of first documented disease recurrence. Patients without recurrence at the time of analysis will be censored
Eligibility
Eligibility (as posted)
- Sex
- All
Show eligibility criteria text
Inclusion Criteria: * patients with bladder cancer who had surgery like radical cystectomy or transurethral resection of bladder tumour (TURBT) * contrast-CT scan less than two weeks before surgery * complete CT image data and clinical data * complete whole slide image data Exclusion Criteria: * patients with a postoperative diagnosis of non-urothelial carcinoma * poor quality of CT images * incomplete clinical and follow-up data
References
Publications (0)
Data not yet available
No reference posted for this study.