Differentiation of fibroblastic meningiomas from other benign subtypes using diffusion tensor imaging |
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Authors: | Tropine Andrei Dellani Paulo D Glaser Martin Bohl Juergen Plöner Till Vucurevic Goran Perneczky Axel Stoeter Peter |
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Affiliation: | Institute of Neuroradiology, University Clinic, Mainz, Germany. tropine@neuroradio.klinik.uni-mainz.de |
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Abstract: | PURPOSE: To differentiate fibroblastic meningiomas, usually considered to be of a hard consistency, from other benign subtypes using diffusion tensor imaging (DTI). MATERIALS AND METHODS: From DTI data sets of 30 patients with benign meningiomas, we calculated diffusion tensors and mean diffusivity (MD) and fractional anisotropy (FA) maps as well as barycentric maps representing the geometrical shape of the tensors. The findings were compared to postoperative histology. The study was approved by the local ethics committee, and informed consent was given by the patients. RESULTS: According to one-way analysis of variance (ANOVA), FA was the best parameter to differentiate between the subtypes (F=32.2; p<0.0001). Regarding tensor shape, endothelial meningiomas were represented by spherical tensors (80%) corresponding to isotropic diffusion, whereas the fibroblastic meningiomas showed a high percentage (43%) of nonspherical tensors, indicating planar or longitudinal diffusion. The difference was highly significant (F=28.4; p<0.0001) and may be due to the fascicular arrangement of long spindle-shaped tumor cells and the high content of intra- and interfascicular fibers as shown in the histology. In addition, a capsule-like rim of the in-plane diffusion surrounded most meningiomas irrespective of their histological type. CONCLUSION: If these results correlate to the intraoperative findings of meningioma consistency, DTI-based measurement of FA and analysis of the shape of the diffusion tensor is a promising method to differentiate between fibroblastic and other subtypes of benign meningiomas in order to get information about their "hard" or "soft" consistency prior to removal. |
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Keywords: | meningioma subtypes diffusion tensor imaging fractional anisotropy tensor shape barycentric maps |
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