Clinical trial · Observational
Neurosurgical Neuronavigation Using Resting State MRI and Machine Learning
Advancing Neurosurgical Neuronavigation Using Resting State MRI and Machine Learning - a Prospective Study
NCT05864976CI-TRIAL-00116354recruitingClinicalTrials.gov clinicaltrialsProvenance
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
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
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Glioblastoma Multiforme | Glioblastoma | CURATED_BROADER | 0.80 |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| Support Vector Machine | Device | — | UNRESOLVED |
Design
Arms and outcomes
Arms (1)
- label
- Standard of care rsfMRI using the Support Vector Machine algorithm
- description
- * 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.
- interventionNames
- Device: Support Vector Machine
Primary outcomes (1)
- measure
- Number of participants who are deemed as short-term survivor or a long-term survivor
- timeFrame
- Through completion of follow-up (estimated to be 2 years)
- description
- -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.
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
Show eligibility criteria text
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).
References
Publications (0)
Data not yet available
No reference posted for this study.