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Prospective Validation of a Digital Pathology-based Artificial Intelligence Diagnostic Model for Lymphovascular Invasion in Bladder Cancer

Prospective Validation of a Digital Pathology-based Artificial Intelligence Diagnostic Model for Lymphovascular Invasion in Bladder Cancer

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500095428
Enrollment
Unknown
Registered
2025-01-07
Start date
2025-01-13
Completion date
Unknown
Last updated
2025-01-13

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:Diagnosis reviewed by two or more senior pathologists, IHC staining can be added if necessary.
Index test:Diagnosis from AI diagnostic model.

Sponsors

Sun Yat-sen Memorial Hospital of Sun Yat-sen University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 90 Years

Inclusion criteria

Inclusion criteria: 1: Age >= 18. 2: Patients with bladder cancer, undergoing radical cystectomy. 3: Patients with complete clinical and pathological information and pathological sections available.

Exclusion criteria

Exclusion criteria: 1: Patients simultaneously merging with other tumor diseases. 2: Patients refuseing to participate in this diagnostic test.

Design outcomes

Primary

MeasureTime frame
Area under the ROC curve, AUC;—

Secondary

MeasureTime frame
Sensitivity;Specificity;—

Countries

China

Contacts

Public ContactLin Tianxin

Sun Yat-sen Memorial Hospital of Sun Yat-sen University

lintx@mail.sysu.edu.cn+86 20 3407 1255

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026