Prospective Real-World Study of Pathology AI for Glioma Molecular Prediction
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- This is an observational study: the protocol does not assign a study treatment.
- Who it may be relevant to
- Registry conditions: Glioma. Basic parameters: 18 years — 100 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- China
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official title
A Prospective Real-World Study of Pathology Artificial Intelligence for Predicting Molecular Alterations in Gliomas
Overview
The goal of this clinical study is to learn if an artificial intelligence (AI) model can accurately predict important molecular changes in gliomas, a type of brain tumor, using digital pathology images. The main questions this study aims to answer are: How accurate is the AI model in predicting key molecular alterations compared with standard molecular testing? Can the AI model shorten the time needed for diagnosis and reduce the need for expensive molecular tests? Researchers will collect whole slide images from multiple hospitals and use the AI model to predict molecular results. The predictions will be compared with the actual test results from standard laboratory methods. Participants will: Allow the use of their pathology images and molecular test results for research. Have no additional treatments or procedures beyond standard medical care. This study will help determine whether AI-assisted tools can provide faster and lower-cost molecular diagnosis for glioma, improving patient care and supporting equal access to precision medicine.
Primary outcome measures
- Accuracy of AI model in predicting key molecular alterations in glioma [Time frame: Within 1 week after whole slide images (WSIs) are obtained]
Eligibility criteria
Inclusion criteria
- Participant (or legally authorized representative) has voluntarily signed the informed consent form.
- Age ≥ 18 years at the time of enrollment.
- Histologically suspected diffuse glioma based on biopsy or surgical resection.
- Availability of complete clinical information and usable digital pathology slides with hematoxylin and eosin (H\&E) staining.
- Postoperative molecular pathology results available for comparison.
Exclusion criteria
- Poor-quality pathology samples (e.g., insufficient tissue, large folding or contamination of slides, or substandard digital scanning quality).
- Determined by the investigator to be unsuitable for participation in the study for any reason.
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Observational model
- Cohort
Study locations
China · 1 center
- Nanfang Hospital, Southern Medical University — Guangzhou
Identifiers
NCT: NCT07263711 · NFEC-2025-508