T2 Star MRI and Blood Tests for Malignant Gliomas
This study is looking at whether a special type of MRI called T2 star (T2*) magnetic resonance imaging and blood tests can help predict how malignant gliomas (a type of brain tumor) might change or grow over time. Researchers want to see if these tests can help identify if the tumor is coming back after treatment. You would undergo T2* MRI, standard MRI, and give blood samples. To join, you need to be over 21, have a new diagnosis of a specific type of malignant glioma (WHO grade IV), have a KPS score over 60 (a measure of your ability to perform daily activities), and be able to give informed consent for standard treatments and study procedures. The main goal is to see how T2* MRI relates to a specific marker in your blood up to three months after radiation therapy. The current status of this study is unclear.
- Study design
- This is an interventional study with a planned enrollment of 15 participants. It is not specified if it is randomized or blinded.
- What's involved
- You would undergo T2* MRI, standard MRI, and provide blood samples. The primary endpoint is measured up to 3 months post-radiation therapy.
- Compensation
- Not stated in the trial record.
- Follow-up
- The primary endpoint is measured up to 3 months post-radiation therapy.
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T2 Star Magnetic Resonance Imaging and Biomarker Blood Testing to Predict the Change and Progress of Malignant Gliomas
At a glance
Conditions
Where it's being run
1 sites across 1 statesStudy leadership
- John Buatti, MD · PRINCIPAL_INVESTIGATOR · University of Iowa
Who to contact
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Do you actually qualify for this trial?
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Inclusion
Exclusion
What this trial measures
- Relationship between T2 (observed)-weighted imaging (T2*) magnetic resonance imaging relation time and dimeric transferrin receptor expressionUp to 3 months post-radiation therapy
Will be characterized with mixed effects regression modeling. Correlation between the two biomarkers will be estimated with the multivariate linear mixed effects regression approach of Hamlett, Ryan, and Wolfinger. Cluster bootstrapping will be employed to calculate a 95% confidence interval for their correlation and a p-value for testing its significance at the 5% level.