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Author Spotlight: Noninvasive Cerebral Blood Flow Determination in Human Functional Brain Region for Diagnosis of Neurological Disorders
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A novel radiological classification system for cerebral gliomas: The Brain-Grid
Francesco Latini1, Markus Fahlström2, Shala G Berntsson3
1Department of Neuroscience, Neurosurgery, Uppsala University, Uppsala, Sweden.
Plos One
|January 25, 2019
Summary
A novel Brain-Grid system enhances glioma classification by integrating MRI scans with white matter atlases. This tool offers precise insights into tumor extension and progression, improving understanding of glioma behavior.
Area of Science:
- Neuroimaging
- Neurosurgery
- Radiology
Background:
- Standard glioma classifications lack detailed anatomical context.
- Current systems do not fully capture tumor relationship with white matter architecture.
Purpose of the Study:
- Introduce the Brain-Grid system for standardized glioma classification.
- Integrate serial MRI scans with tractographic atlases for anatomical accuracy.
Main Methods:
- Analyzed MRI scans from 39 glioma patients using a standardized grid system.
- Reconstructed white matter pathways using deterministic tracking on a reference atlas.
- Utilized Brain-Grid for analysis in MNI and Talairach spaces.
Main Results:
- Identified 48 brain grid voxels (A, C, S coordinates) consistently infiltrated across patients.
- Most frequent involvement observed in sub-cortical insula/basal ganglia (A3-C2-S2) and fronto-insular region (A3-C2-S1).
- Associated white matter pathways included inferior fronto-occipital fasciculus, anterior thalamic radiation, uncinate fasciculus, and external capsule.
Conclusions:
- The Brain-Grid system provides an accurate tool for glioma classification and observation.
- Enables detailed analysis of tumor kinetics, including extension, speed, and progression direction.
- Facilitates improved comprehension of glioma behavior in clinical and research settings.
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