Clinical trial · Observational
Development and Prospective Validation of a Digital Pathology-based Artificial Intelligence Diagnostic Model for Pan-cancer Lymphatic Metastasis
- 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)
The goal of this diagnostic test is to develop an artificial intelligence (AI)-based pan-cancer universal diagnostic model for detecting pathological lymph node metastasis (LNM), and prospectively evaluate its apllication value in the real-world clinical practice. 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 cancer LNM in in the real world.
Conditions
Conditions (2)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Cancer | Malignant Neoplasm | ALIAS | 0.90 |
| Lymphatic Metastasis | — | UNRESOLVED | — |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| Artificial intelligence (AI)-based diagnostic model | Diagnostic Test | — | UNRESOLVED |
Design
Arms and outcomes
Arms (1)
- label
- Patients with cancer undergoing LND
- description
- Patients undergo radical tumor resection and lymph node dissection (LND)
- interventionNames
- Diagnostic Test: Artificial intelligence (AI)-based diagnostic model
Primary outcomes (1)
- measure
- sensitivity
- timeFrame
- For each enrolled patient, the diagnosis results of AI model will be obtained in servel days after lymph node dissection, and the sensitivity of the AI model will be evaluated through study completion, an average of 3 year.
- description
- the number of correctly diagnosed positive slides (with lymphatic metastasis), to be divided by the number of positive slides in total
Secondary outcomes (1)
- measure
- specificity
- timeFrame
- For each enrolled patient, the diagnosis results of AI model will be obtained in servel days after lymph node dissection, and the sensitivity of the AI model will be evaluated through study completion, an average of 3 year.
Eligibility
Eligibility (as posted)
- Sex
- All
Show eligibility criteria text
Inclusion Criteria: * Patients with cancer, undergoing radical tumor resection and lymph node dissection. * Patients with complete clinical and pathological information. Exclusion Criteria: * The patient refused to participate in this diagnostic test.
References
Publications (0)
Data not yet available