Neurosurgical Neuronavigation Using Resting State MRI and Machine Learning

Part of paid clinical trials in St Louis, Missouri.

Sponsor
Washington University School of Medicine
Study ID
NCT05864976
Status
Recruiting
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Conditions

  • Glioblastoma Multiforme

Eligibility Criteria

Sex
ALL
Age
18 Years - N/A
Healthy Volunteers
Not accepted

Interventions

  • Support Vector Machine — DEVICE
    Machine learning algorithm

Study Details

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.

Key Dates

Start date
Dec 6, 2023
Status verified
Jun 2025
Primary completion
Jan 31, 2030
Completion
Jan 31, 2030

Study Design

Enrollment
100 participants (estimated)

Arms

  • Arm: 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.

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) ]

Central Contacts

Locations (1)

FacilityCityStateZIPSite coordinators
Washington University School of MedicineSt LouisMissouri63110
Dimitrios Mathios, M.D.
[email protected]
314-747-6146
Dimitrios Mathios, M.D. (PRINCIPAL_INVESTIGATOR)
Joshua Shimony, M.D. (SUB_INVESTIGATOR)
Milan Chheda, M.D. (SUB_INVESTIGATOR)
Abraham Synder, M.D., Ph.D. (SUB_INVESTIGATOR)
Patrick Luckett, Ph.D. (SUB_INVESTIGATOR)
Feng Gao, Ph.D. (SUB_INVESTIGATOR)
Eric Leuthardt, M.D. (SUB_INVESTIGATOR)

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