Clinical trial · Observational
Histopathology Images Based Survival Prediction of Glioma Patients Using Artificial Intelligence
Histopathology Images Based Survival Prediction of Patients With Primary Glioma Using Deep Learning or Machine Learning
- 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)
This registry aims to collect clinical, molecular and histopathology imaging including detailed survival data, clinical parameters, molecular pathology (1p/19q codeletion, MGMT methylation, IDH and TERTp mutations, etc) and images of HE slices in primary gliomas. By leveraging artificial intelligence, this registry will seek to construct and refine hstopathology imaging based algorithms that able to predict patients' survivals in the frame of molecular pathology or subgroups of gliomas.
Conditions
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Glioma | Glioma | ONTOLOGY_EXACT | 0.98 |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| Histopathology images based survival prediction for glioma patients | Diagnostic Test | — | UNRESOLVED |
Design
Arms and outcomes
Arms (0)
[]Primary outcomes (1)
- measure
- AUC of survival prediction performance
- timeFrame
- up to 10 years
- description
- AUC of survival prediction performance=sensitivity+specificity-1
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 1 Year
- Maximum age
- 90 Years
Show eligibility criteria text
Inclusion Criteria: * Patients must have radiologically and histologically confirmed diagnosis of primary glioma * Life expectancy of greater than 3 months * Must receive tumor resection * Signed informed consent Exclusion Criteria: * No gliomas * No sufficient amount of tumor tissues for detection of molecular pathology * Patients who are pregnant or breast feeding * Patients who are suffered from severe systematic malfuctions
References
Publications (0)
Data not yet available