NCT06993779Active, not recruiting
Whole-slide Image and CT Radiomics Based Deep Learning System for Prognostication Prediction in Upper Tract Urothelial Carcinoma
Source: ClinicalTrials.gov · Last updated 29 May 2025
Brief summary (registry, in English)
Upper Tract Urothelial Carcinoma (UTUC), characterized by its anatomical complexity and often aggressive clinical behavior, presents substantial difficulties in accurate diagnosis and reliable prognostication. The stratification of postoperative survival utilizing radiomics features derived from imaging and characteristics from whole slide images could prove instrumental in guiding therapeutic decisions to enhance patient outcomes. In this research, our objective is to construct a deep learning-based prognostic-stratification system designed for the automated prediction of overall and cancer-specific survival in individuals diagnosed with UTUC.
- Status (registry)
- Active, not recruiting
- Study type
- Observational
- Enrollment
- 1000 (estimated)
- First submitted
- 20 May 2025
- Start date
- Jan 2025
- Primary completion date
- Jun 2025
- Lead sponsor
- Mingzhao Xiao
- Diseases
- Bladder cancer
- NCT number
- NCT06993779
What you commit to
- Study type: Observational
- Planned participants: 1000
- From Jan 2025 to the primary completion date, Jun 2025
- 1 site in 1 country
- Visits and tests: ask the trial team, the registry does not list them
Built from the registry fields of ClinicalTrials.gov. It describes the study, not your situation.
Who cannot take part
Copied verbatim from ClinicalTrials.gov and grouped by topic. Only the trial team decides who can take part.
Other
- Patients with a postoperative diagnosis of non-urothelial carcinoma.
- Poor quality of CT images and/or whole slide image data.
- Incomplete clinical and follow-up data.
Who the study is looking for
- Patients with Upper Tract Urothelial Carcinoma (UTUC) who had radical nephroureterectomy (RNU).
- Contrast-enhanced CT scan (e.g., CT urography) less than two weeks before surgery.
- Complete CT image data and clinical data.
- Complete whole slide image data.
Sex: All · Does not accept healthy volunteers
Sites (1)
Sites in registry order. Pick your city on the disease page to sort them by distance.
| Site | City | Country | Site status |
|---|---|---|---|
| Department of Urology, The First Affiliated Hospital of Chongqing Medical University, chongqing, chongqing 400016 Recruiting Coordinator of this site? Confirm its status | Chongqing | China | Unknown status |
This page is information, not medical advice. Discuss any trial with your doctor.