Glioma
Conditions
Keywords
glioma, glioblastoma
Brief summary
This study is investigating how brain tumors might mutate over time, and whether new brain imaging tools like MRI and PET can predict these mutations.
Detailed description
This study is investigating how brain tumors might mutate over time, and whether new brain imaging tools like MRI and PET can predict these mutations. Subjects who are radiologically diagnosed with gliomas and are expected to undergo a tumor biopsy will be enrolled in the study. Subjects will complete two visits and will then undergo a follow-up period. At the baseline visit, subjects will under go a pregnancy test (if applicable), two PET-CT scans using different radioactive tracers, an MRI scan, and blood draws. At the biopsy visit, the subject will undergo an MRI scan as part of their standard of care and at least biopsy samples will be collected for research purposes using stereotactic core biopsy. The study team will take pictures of the locations of tumor samples as they are removed during surgery. The samples then get studied for genetic mutations, and the study team will look at the parts of the image the samples came from to see if they could have been predicted. Follow-up MRIs and potentially other radiology scans will be completed as part of subjects' regular care on a schedule determined by their healthcare provider at the facility ordered by their physician. The study team will follow subjects' care and collect the information from their regularly scheduled treatments and brain scans after their biopsy.
Interventions
DRUGFET F-18
PET scan with FET prior to biopsy
DRUGO-15 Radioisotope
PET scan with O-15 Water prior to biopsy
PROCEDURECT scan
CT scan prior to biopsy
PROCEDUREMRI with gadolinium-based contrast
MRI prior to biopsy
PROCEDUREBiopsy Collection
Biopsy collection during standard of care neurosurgery for glioma diagnosis/excision
Sponsors
Children's Hospital of Philadelphia
Indiana University
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
1. Subject is between 18 and 89 years of age. 2. Subject has radiologically-diagnosed or suspected WHO Grade II-IV glioma based on physician review or conformance with published WHO criteria as evaluated by the PI\*. 3. Subject is treatment-naïve with the exception of previous biopsy for the above condition. 4. Subject is planning to undergo surgical resection and biopsy of their brain tumor. 5. Subject has sufficient tissue so that the study team is able to acquire at least 2 biopsy samples during resection. 6. Subject is able to read and write in English. 7. Subject is able to lay supine for up to 80 minutes. 8. Subject is able to hold still during MRI procedures. 9. Subject or their LAR has signed the consent form for participation in the study.
Exclusion criteria
1. Subject has conditions that would preclude the completion of an MRI such as claustrophobia, pacemaker, metal objects in the body, and/or pregnancy. 2. Subject has serious unstable medical or mental illness. 3. Subject has insufficient tissue to acquire at least two biopsy samples during resection. 4. Subject has a medical contraindication to any element of the study procedures. 5. Subject or their LAR has not read and signed the informed consent form, or does not understand its contents. 6. Subject is pregnant.\*\* 7. Subject is at high risk for NSF (eGFR\<60 or serum creatine \>1.3) and cannot follow the weight-based dosing protocol for Gadavist.\*\*\*
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Classification sensitivity | Through study completion, an average of 1 year. | Statistical evaluation of the area under the ROC curve. 3.1.1 SMM classification sensitivity to \>80% 3.1.2 Reduce computation time by a factor of 10, and maintain accuracy (\>.95) |
| Multivariate analysis | 2032 | Statistically determine if MRI, and 15O-H2O and FET-PET (if available) independently predict multiscale properties and together improve classification accuracy and sensitivity for SMM compared to 5 baseline MR sequences |
| Survival | 2032 | Statistically determine if SMM classifications using MRI, and 15O-H2O and FET-PET (if available) can predict progression-free survival (PFS) and overall survival (OS), and individual voxel responses to chemotherapy and radiation therapy. |
Countries
United States
Contacts
Primary ContactJason Parker, PhD
Backup ContactJason Parker, PhD
Outcome results
None listed