1. Voxel-based lesion mapping of meningioma: a comprehensive lesion location mapping of 260 lesions.
- Author
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Hirayama R, Kinoshita M, Arita H, Kagawa N, Kishima H, Hashimoto N, Fujimoto Y, and Yoshimine T
- Subjects
- Adult, Aged, Aged, 80 and over, Cranial Sinuses diagnostic imaging, Female, Humans, Imaging, Three-Dimensional methods, Magnetic Resonance Imaging methods, Male, Meninges diagnostic imaging, Middle Aged, Retrospective Studies, Skull Base Neoplasms diagnostic imaging, Skull Neoplasms diagnostic imaging, Young Adult, Brain Mapping methods, Brain Neoplasms diagnostic imaging, Meningioma diagnostic imaging
- Abstract
OBJECTIVE In the present study the authors aimed to determine preferred locations of meningiomas by avoiding descriptive analysis and instead using voxel-based lesion mapping and 3D image-rendering techniques. METHODS Magnetic resonance images obtained in 248 treatment-naïve meningioma patients with 260 lesions were retrospectively and consecutively collected. All images were registered to a 1-mm isotropic, high-resolution, T1-weighted brain atlas provided by the Montreal Neurological Institute (the MNI152), and a lesion frequency map was created, followed by 3D volume rendering to visualize the preferred locations of meningiomas in 3D. RESULTS The 3D lesion frequency map clearly showed that skull base structures such as parasellar, sphenoid wing, and petroclival regions were commonly affected by the tumor. The middle one-third of the superior sagittal sinus was most commonly affected in parasagittal tumors. Substantial lesion accumulation was observed around the leptomeninges covering the central sulcus and the sylvian fissure, with very few lesions observed at the frontal, parietal, and occipital convexities. CONCLUSIONS Using an objective visualization method, meningiomas were shown to be located around the middle third of the superior sagittal sinus, the perisylvian convexity, and the skull base. These observations, which are in line with previous descriptive analyses, justify further use of voxel-based lesion mapping techniques to help understand the biological nature of this disease.
- Published
- 2018
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