GliomaGliomaAI-MGNCT07664254
GliomaAI-MG: MRI-Based Detection of Molecular Glioblastoma
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-MG can help detect a specific molecular type of brain tumour called molecular glioblastoma 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), Glioblastom WHO Grade 4
- What is being tested?
- GliomaAI-MG
- Type of treatment
- Medical device
- How many people
- 1,372 participants
- Where
- 1 siteIndia
- Study dates
- 14 Mar 2017to 16 Jul 2021
- Phase
- Observational
- Are there results?
- None posted in the registry
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-MG: Non-Invasive MRI-Based Detection of Molecular Glioblastoma Using Artificial Intelligence
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:
Read more
- 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.
- Conditions
- Glioma, Glioma (Diagnosis), Glioblastom WHO Grade 4
- Being tested
- GliomaAI-MG
- Keywords
- Glioma, Brain Tumour, Glioma AI, Molecular Glioblastoma, MRI
- Medical subject headings
- Glioma, Disease, Brain Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
GliomaAI-MGDevice
Software as Medical Device (SaMD) for predicting molecular glioblastoma
What is being measured
The primary outcome is the main question the study is designed to answer.
Diagnostic performance of GliomaAI-MG for identification of molecular glioblastoma from MRI, measured by accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve
The diagnostic performance of the GliomaAI-MG artificial intelligence model will be assessed by comparing pre-operative MRI-based predictions of molecular glioblastoma 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 posted24 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
- NCT07664254
- Sponsor's protocol ID
- DLIRS-GLIOMAAI-MG
- Acronym
- GliomaAI-MG
- Status last verified
- Jun 2026
- First submitted
- 13 Jun 2026
- Last updated
- 24 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
Study at a glance
From the registry record, last updated by the sponsor on 24 Jun 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- GliomaAI-MG: Non-Invasive MRI-Based Detection of Molecular Glioblastoma Using Artificial Intelligence
- ClinicalTrials.gov ID
- NCT07664254
- Acronym / sponsor ID
- GliomaAI-MG / DLIRS-GLIOMAAI-MG
- Conditions
- Glioma, Glioma (Diagnosis), Glioblastom WHO Grade 4
- Keywords
- Glioma, Brain Tumour, Glioma AI, Molecular Glioblastoma, MRI
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 1,372 participants (actual)
- Lead sponsor
- Deep Learning Institute of Radiological SciencesUniversity, hospital or other
- Study start
- 14 Mar 2017 (actual)
- Primary completion
- 9 Mar 2021 (actual)
- Study completion
- 16 Jul 2021 (actual)
- First posted
- 24 Jun 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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
- Observational model
- Cohort
- Time perspective
- Retrospective
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Patients with glioma diagnosis included in the TCIA cohort.
Key inclusion criteria (4 listed)
- Adult (>=18 years of age)
- Having pre op MRI scan
- Having biopsy / surgery
- Having post biopsy/ surgery histology diagnosis and genetic analysis.
Key exclusion criteria (3 listed)
- MRI scan significantly degraded by motion or other artefact
- Incomplete genetic analysis
- Prior treatment (e.g., radiotherapy or chemotherapy) before baseline MRI
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| GliomaAI-MGSoftware as Medical Device (SaMD) for predicting molecular glioblastoma | Device | – |
Primary outcome
Diagnostic performance of GliomaAI-MG for identification of molecular glioblastoma from MRI, measured by accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve
Time frame: Perioperative
The diagnostic performance of the GliomaAI-MG artificial intelligence model will be assessed by comparing pre-operative MRI-based predictions of molecular glioblastoma 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.
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 24 Jun 2026.
- Individual participant dataSharing planned: Yes. Study protocol will be shared with researchers
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Glioma and Glioma (Diagnosis), run by Deep Learning Institute of Radiological Sciences at 1 site in India.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 24 Jun 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in India. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Diagnostic performance of GliomaAI-MG for identification of molecular glioblastoma from MRI, measured by accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve (time frame: Perioperative). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 24 Jun 2026.