Abstract
PurposeStandard radiological/topographical classifications of gliomas often do not reflect the real extension of the tumor within the lobar-cortical anatomy. Furthermore, these systems do not provide information on the relationship between tumor growth and the subcortical white matter architecture. We propose the use of an anatomically standardized grid system (the Brain-Grid) to merge serial morphological magnetic resonance imaging (MRI) scans with a representative tractographic atlas. Two illustrative cases are presented to show the potential advantages of this classification system.MethodsMRI scans of 39 patients (WHO grade II and III gliomas) were analyzed with a standardized grid created by intersecting longitudinal lines on the axial, sagittal, and coronal planes. The anatomical landmarks were chosen from an average brain, spatially normalized to the Montreal Neurological Institute (MNI) space and the Talairach space. Major white matter pathways were reconstructed with a deterministic tracking algorithm on a reference atlas and analyzed using the Brain-Grid system.ResultsIn all, 48 brain grid voxels (areas defined by 3 coordinates, axial (A), coronal (C), sagittal (S) and numbers from 1 to 4) were delineated in each MRI sequence and on the tractographic atlas. The number of grid voxels infiltrated was consistent, also in the MNI space. The sub-cortical insula/basal ganglia (A3-C2-S2) and the fronto-insular region (A3-C2-S1) were most frequently involved. The inferior fronto-occipital fasciculus, anterior thalamic radiation, uncinate fasciculus, and external capsule were the most frequently associated pathways in both hemispheres.ConclusionsThe Brain-Grid based classification system provides an accurate observational tool in all patients with suspected gliomas, based on the comparison of grid voxels on a morphological MRI and segmented white matter atlas. Important biological information on tumor kinetics including extension, speed, and preferential direction of progression can be observed and even predicted with this system. This novel classification can easily be applied to both prospective and retrospective cohorts of patients and increase our comprehension of glioma behavior.
Highlights
Gliomas comprise approximately 30% of all primary CNS tumors and 80% of malignant brain tumors [1, 2]
When proliferation is the predominant phenomenon, the effects of tumor infiltration do not affect tumor shape, which is grossly bulky, whereas diffusively infiltrating tumors with low proliferation will lead to a complex shape with digitations along the deep white matter fibers [5,8,10,12,13,14]
To illustrate the advantages of the Brain-Grid classification system, we presented the temporal course of 2 patients who were conservatively managed following radiological diagnosis
Summary
Gliomas comprise approximately 30% of all primary CNS tumors and 80% of malignant brain tumors [1, 2]. Low-grade gliomas are WHO grade II tumors and are characterized by slow growth but extensive infiltration. Dissemination of astrocytic tumors seems to be confined to the white matter near the cortex or deep gray nuclei, which, under certain circumstances, act as barriers to the invasion of some gliomas [6,15,16]. This phenomenon is less prominent in oligodendrogliomas, which will frequently invade the cortex and are less likely to respect anatomic boundaries [17]. Tumor grade does not seem to be strictly related to the degree of local invasion, and low-grade astrocytomas (WHO II) may show extensive infiltration of adjacent subcortical regions [18]
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