GliomaGliomaAI-A23NCT07673666
GliomaAI-Astro23: MRI-Based Detection of IDH Mutant Astrocytoma (Grade 2 and 3)
An observational study of Glioma and Glioma (Diagnosis), run by Deep Learning Institute of Radiological Sciences at 1 site in India.
Trial summary
The goal of this observational study is to learn whether an artificial intelligence system called GliomaAI-Astro23 can help detect a specific molecular type of brain tumour called IDH mutant Astrocytoma (grade 2 and 3) using routine MRI scans. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Glioma, Glioma (Diagnosis), Astrocytoma
- What is being tested?
- GliomaAI-Astro23
- Type of treatment
- Medical device
- How many people
- 1,372 participants
- Where
- 1 siteIndia
- Study dates
- 14 Mar 2017to 16 Jul 2021
- Phase
- Observational
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Patients with glioma diagnosis included in the TCIA cohort.
Who may be able to join
- Adult (>=18 years of age)
- Having pre op MRI scan
- Having biopsy / surgery
- Having post biopsy/ surgery histology diagnosis and genetic analysis.
Who cannot join
- MRI scan significantly degraded by motion or other artefact
- Incomplete genetic analysis
- Prior treatment (e.g., radiotherapy or chemotherapy) before baseline MRI
Trial locations and contacts
1 site in 1 country.
About this study
Official title: GliomaAI-Astro23: Non-Invasive MRI-Based Detection of IDH Mutant Astrocytoma (Grade 2 and 3) Using Artificial Intelligence
The goal of this observational study is to learn whether an artificial intelligence system called GliomaAI-Astro23 can help detect a specific molecular type of brain tumour called IDH mutant Astrocytoma (grade 2 and 3) 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:
Read more
- How accurately can GliomaAI-Astro23 identify IDH mutant Astrocytoma (grade 2 and 3) 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.
- Conditions
- Glioma, Glioma (Diagnosis), Astrocytoma, Astrocytoma of Brain, Astrocytoma, Grade II, Astrocytoma, IDH-Mutant, Grade 2
- Being tested
- GliomaAI-Astro23
- Keywords
- Glioma, Brain Tumour, Glioma AI, MRI, Astrocytoma
- Medical subject headings
- Glioma, Disease, Astrocytoma, Lymphoma, Follicular, Brain Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
GliomaAI-Astro23Device
Software as Medical Device (SaMD) for predicting astrocytoma (grade 2 and 3)
What is being measured
The primary outcome is the main question the study is designed to answer.
Diagnostic performance of GliomaAI-Astro23 for identification of IDH mutant Astrocytoma (grade 2 and 3) from MRI, measured by accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and area under the ROC
The diagnostic performance of the GliomaAI-Astro23 artificial intelligence model will be assessed by comparing pre-operative MRI-based predictions of IDH mutant Astrocytoma (grade 2 and 3) status against post-operative (biopsy or surgery) molecular/genetic profiling results as the reference standard. Performance metrics including accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and AUC will be calculated.
Measured: Perioperative
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted29 Jun 2026
- Study start14 Mar 2017
- Primary completion9 Mar 2021
- Study completion16 Jul 2021
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for GliomaStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 1,372 participants (actual)
Sponsor and investigators
- Lead sponsor
- Deep Learning Institute of Radiological Sciences
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07673666
- Sponsor's protocol ID
- DLIRS-GLIOMAAI-ASTRO23
- Acronym
- GliomaAI-A23
- Status last verified
- Jun 2026
- First submitted
- 23 Jun 2026
- Last updated
- 29 Jun 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- Yes
- Individual data sharing
- Yes: Study protocol will be shared with researchers