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Development of an AI-Based Prediction Model for CT Image Diagnosis of Muscle Invasion and Lymph Node Metastasis in Bladder Cancer

Development of an AI-Based Prediction Model for CT Image Diagnosis of Muscle Invasion and Lymph Node Metastasis in Bladder Cancer

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600128358
Enrollment
Unknown
Registered
2026-07-17
Start date
2025-12-31
Completion date
Unknown
Last updated
2026-07-20

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Bladder cancer

Interventions

Gold Standard:The stage of urothelial carcinoma (NMIBC/MIBC) and lymph node metastasis confirmed by postoperative pathology after "transurethral plasma resection of bladder tumor" or "radical cystecto
Index test:Ai-assisted CT diagnostic model

Sponsors

Sichuan Cancer Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 85 Years

Inclusion criteria

Inclusion criteria: 1.Availability of imaging examinations (e.g., CT, multiparametric MRI, or PET-CT) within one month prior to surgery. 2.Having undergone "TURBT" or "Radical Cystectomy + Pelvic Lymph Node Dissection" at our institution. 3.Postoperative pathological confirmation of urothelial carcinoma with definitive pathological staging.

Exclusion criteria

Exclusion criteria: 1.Previous neoadjuvant chemotherapy or radiotherapy prior to surgery. 2.Coexistence of other malignant tumors.

Design outcomes

Primary

MeasureTime frame
Depth of bladder tumor invasion (muscle-invasive or not);Lymph node metastasis status;

Secondary

MeasureTime frame
Model performance metrics (AUC, sensitivity, specificity, etc.);

Countries

China

Contacts

Public ContactLiao Hong

Sichuan Cancer Hospital

liaohong131@163.com+86 28 85420037

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Jul 23, 2026