Neurosurgical Neuronavigation Using Resting State MRI and Machine Learning
ConditionGlioblastoma Multiforme
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18+
SponsorWashington University School of Medicine
About this trial
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.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
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.
Disqualifiers
Contraindication to MRI.
Inability to have clinical follow-up (e.g., patient is out of town and will do follow-up elsewhere).
Trial population
Participants being seen at Washington University School of Medicine.
Trial design
Design model
Cohort
Time perspective
Prospective
Treatments tested in this trial
Support Vector Machine
DeviceMachine learning algorithm
Treatment groups
100 Participants
are divided into 1 treatment groupGroup A: Standard of care rsfMRI using the Support Vector Machine algorithm1 intervention
Trial outcomes
Primary outcomes
1
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)Sponsors and contacts
Click on the lead sponsor to view all of their trials.
Washington University School of Medicine
Lead sponsor
National Cancer Institute (NCI)
Collaborator
Source ClinicalTrials.gov