GliomaAI-MG: Non-Invasive MRI-Based Detection of Molecular Glioblastoma Using Artificial Intelligence
Trial Snapshot
- Phase
- Not Applicable
- Status
- Completed
- Sponsor
- Enrollment
- 1,372
- Locations
- 1
Study Overview
Brief Summary
The goal of this observational study is to learn whether an artificial intelligence system called GliomaAI-MG can help detect a specific molecular type of brain tumour called molecular glioblastoma using routine MRI scans. The study uses previously collected and fully anonymised MRI data from 1,372 patients from 13 institutions in the Cancer Imaging Archive (TCIA).
The main questions it aims to answer are:
- How accurately can GliomaAI-MG identify molecular glioblastoma from MRI scans?
- How well does the system perform across data from different hospitals and patient groups?
Researchers will use existing MRI scans and clinical information to train and test the AI system. No new scans, treatments, or hospital visits are required for participants, and all data used is fully anonymised and obtained from an existing research database.
Participants will not be asked to do anything, as this study only uses previously collected imaging data.
Study Design
- Study Type
- Observational
- Observational Model
- Cohort
- Time Perspective
- Retrospective
Eligibility Criteria
- Ages
- 18 Years to — (Adult, Older Adult)
- Sex
- All
- Accepts Healthy Volunteers
- No
Inclusion Criteria
- •Adult (>=18 years of age)
- •Having pre op MRI scan
- •Having biopsy / surgery
- •Having post biopsy/ surgery histology diagnosis and genetic analysis.
Exclusion Criteria
- •MRI scan significantly degraded by motion or other artefact
- •Incomplete genetic analysis
- •Prior treatment (e.g., radiotherapy or chemotherapy) before baseline MRI