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Prospective Validation of Pathology-based Artificial Intelligence Diagnostic Model for Lymph Node Metastasis in Prostate Cancer

NCT06253065 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 225

Last updated 2026-02-11

No results posted yet for this study

Summary

The goal of this diagnostic test is to prospectively test the performance of pre-developed artificial intelligence (AI) diagnostic model for detecting pathological lymph node metastasis (LNM) of prostate cancer. Investigators had developed this AI model based on deep learning algorithms in preliminary research, and it performed well in retrospective tests.

Investigators will compare the diagnostic performance (sensitivity, specificity, etc.) of the AI model and routine pathological report issued by pathologists, to see if the AI model can improve the clinical workflow of pathological evaluation of LNM in prostate cancer in the real world.

Conditions

  • Prostatic Neoplasms
  • Lymphatic Metastasis

Interventions

DIAGNOSTIC_TEST

Artificial intelligence (AI)-based diagnostic model (developed)

Collect pathological slides of resected lymph nodes of the enrolled patients. Digitise these slides into whole-slide images (WSIs). Analyze the WSIs using the AI model to generate diagnostic results (with or without lymphatic metastasis). No intervention to patients would be performed in this diagnostic test study.

Sponsors & Collaborators

  • Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

    lead OTHER

Principal Investigators

  • Tianxin Lin, Ph.D · Department of Urology of Sun Yat-sen Memorial Hospital of Sun Yat-sen University

Eligibility

Sex
MALE
Healthy Volunteers
No

Timeline & Regulatory

Start
2024-01-12
Primary Completion
2025-12-31
Completion
2025-12-31

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06253065 on ClinicalTrials.gov