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Advancing Neurosurgical Neuronavigation Using Resting State MRI and Machine Learning - a Prospective Study
NCT ID: NCT05864976Sponsor: Washington University School of MedicineLast updated: 2025-06-25
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.
Arms & interventions
- DeviceSupport Vector Machine
Machine learning algorithm
Outcome measures
Primary
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.
Time frame: Through completion of follow-up (estimated to be 2 years)
Eligibility criteria
Sex: AllAge: 18 Years and olderHealthy volunteers: No
Inclusion Criteria:
* 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.
Exclusion Criteria:
* Contraindication to MRI.
* Inability to have clinical follow-up (e.g., patient is out of town and will do follow-up elsewhere).
Study locations (1)
Washington University School of Medicine
St Louis, Missouri, 63110
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