Glioblastoma MultiformeNCT05864976
Neurosurgical Neuronavigation Using Resting State MRI and Machine Learning
An observational study of Glioblastoma Multiforme, run by Washington University School of Medicine at 1 site in United States.
Trial summary
This study is investigating the use of a computer algorithm to analyze scans of the brain before surgery to predict how a person's tumor will respond to treatment. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Glioblastoma Multiforme
- What is being tested?
- Support Vector Machine
- Type of treatment
- Medical device
- How many people
- 100 participants
- Where
- 1 siteUnited States
- Study dates
- 6 Dec 2023to 31 Jan 2030
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
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: Participants being seen at Washington University School of Medicine.
Who may be able to join
- Must have a radiological diagnosis of a lesion in the brain with characteristics consistent with glioblastoma multiforme.
- Must be planning to undergo a pre-operative MRI.
- Must be at least 18 years old.
- Must be able to understand and willing to sign an IRB approved written informed consent document.
Who cannot join
- Contraindication to MRI.
- Inability to have clinical follow-up (e.g., patient is out of town and will do follow-up elsewhere).
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
United States1 site, 1 recruiting
- Recruiting
Washington University School of Medicine
St Louis, Missouri, 63110
Dimitrios Mathios, M.D., 314-747-6146, mathios@wustl.edu
Dimitrios Mathios, M.D.
About this study
Official title: Advancing Neurosurgical Neuronavigation Using Resting State MRI and Machine Learning - a Prospective Study
This study is investigating the use of a computer algorithm to analyze scans of the brain before surgery to predict how a person's tumor will respond to treatment.
- Conditions
- Glioblastoma Multiforme
- Being tested
- Support Vector Machine
- Medical subject headings
- Glioblastoma
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Support Vector MachineDevice
Machine learning algorithm
| Study group | Role | What they receive |
|---|---|---|
| Standard of care rsfMRI using the Support Vector Machine algorithm | * Once enrolled, clinical pre-surgical MRI will be done on Siemens 3T Prisma or Skyra scanners using a standard pre-surgical tumor protocol. Resting-state functional MRI (rsfMRI) will be acquired. The Support Vector Machine (SVM) algorithm will be used on this pre-surgical MRI.
* Patients will undergo post-operative MRI at approximately 8-12 weeks following surgical resection to evaluate extent of resection. Patients will then undergo subsequent MRI imaging every 2-3 months as part of routine clinical care to monitor for recurrence. The following MR sequences will be acquired: pre-and post-contrast T1-weighted, T2-weighted FLAIR, diffusion weighted imaging. MRI scans will be reviewed by a board-certified neuroradiologist to determine date of radiographic progression/recurrence. Imaging features at recurrence including location, multifocality, and presence of diffuse or distant recurrence will also be recorded. Receives: Device: Support Vector Machine |
What is being measured
The primary outcome is the main question the study is designed to answer.
Number of participants who are deemed as short-term survivor or a long-term survivor
-Patients will be deemed as a short-term survivor or a long-term survivor and this will be defined as overall survival as less than or greater than 14.5 months, respectively.
Measured: Through completion of follow-up (estimated to be 2 years)
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted18 May 2023
- Study start6 Dec 2023
- Primary completion31 Jan 2030 (estimated)
- Study completion31 Jan 2030 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Glioblastoma MultiformeStudies of the same condition, open and under way.
- More trials run by Washington University School of MedicineThe sponsor's other registered studies.
- 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
- Prospective
- Enrolment
- 100 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Washington University School of Medicine
- Sponsor type
- University, hospital or other
- Collaborators
- National Cancer Institute (NCI)
- Responsible party
- Sponsor
- Investigators
- Dimitrios Mathios, M.D., Principal investigator, Washington University School of Medicine
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05864976
- Sponsor's protocol ID
- 202305045
- Other IDs
- 2R01CA203861
- Status last verified
- Jun 2026
- First submitted
- 8 May 2023
- Last updated
- 30 Jun 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- Yes
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 30 Jun 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Advancing Neurosurgical Neuronavigation Using Resting State MRI and Machine Learning - a Prospective Study
- ClinicalTrials.gov ID
- NCT05864976
- Acronym / sponsor ID
- 202305045
- Conditions
- Glioblastoma Multiforme
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 100 participants (estimated)
- Lead sponsor
- Washington University School of MedicineUniversity, hospital or other
- Collaborators
- National Cancer Institute (NCI)
- Study start
- 6 Dec 2023 (actual)
- Primary completion
- 31 Jan 2030 (estimated)
- Study completion
- 31 Jan 2030 (estimated)
- First posted
- 18 May 2023 (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.
This study is investigating the use of a computer algorithm to analyze scans of the brain before surgery to predict how a person's tumor will respond to treatment.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Standard of care rsfMRI using the Support Vector Machine algorithm | – | Device: Support Vector Machine* Once enrolled, clinical pre-surgical MRI will be done on Siemens 3T Prisma or Skyra scanners using a standard pre-surgical tumor protocol. Resting-state functional MRI (rsfMRI) will be acquired. The Support Vector Machine (SVM) algorithm will be used on this pre-surgical MRI. * Patients will undergo post-operative MRI at approximately 8-12 weeks following surgical resection to evaluate extent of resection. Patients will then undergo subsequent MRI imaging every 2-3 months as part of routine clinical care to monitor for recurrence. The following MR sequences will be acquired: pre-and post-contrast T1-weighted, T2-weighted FLAIR, diffusion weighted imaging. MRI scans will be reviewed by a board-certified neuroradiologist to determine date of radiographic progression/recurrence. Imaging features at recurrence including location, multifocality, and presence of diffuse or distant recurrence will also be recorded. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Participants being seen at Washington University School of Medicine.
Key inclusion criteria (4 listed)
- Must have a radiological diagnosis of a lesion in the brain with characteristics consistent with glioblastoma multiforme.
- Must be planning to undergo a pre-operative MRI.
- Must be at least 18 years old.
- Must be able to understand and willing to sign an IRB approved written informed consent document.
Key exclusion criteria (2 listed)
- Contraindication to MRI.
- Inability to have clinical follow-up (e.g., patient is out of town and will do follow-up elsewhere).
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 |
|---|---|---|
| Support Vector MachineMachine learning algorithm | Device | Standard of care rsfMRI using the Support Vector Machine algorithm |
Primary outcome
Number of participants who are deemed as short-term survivor or a long-term survivor
Time frame: Through completion of follow-up (estimated to be 2 years)
-Patients will be deemed as a short-term survivor or a long-term survivor and this will be defined as overall survival as less than or greater than 14.5 months, respectively.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 30 Jun 2026.
- Alvin J. Siteman Cancer Center at Barnes-Jewish Hospital and Washington University School of MedicineLink provided by the sponsor.
- Individual participant dataSharing planned: No
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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.
Dimitrios Mathios, M.D. principal investigator
Washington University School of Medicine
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 Glioblastoma Multiforme, run by Washington University School of Medicine at 1 site in United States.
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 2 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: looking for participants now, as of the sponsor's last update on 30 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 United States. 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?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Dimitrios Mathios, M.D. (314-747-6146, mathios@wustl.edu), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Number of participants who are deemed as short-term survivor or a long-term survivor (time frame: Through completion of follow-up (estimated to be 2 years)). 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 30 Jun 2026.