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Updated: Jul 20, 2026
Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Published on: July 28, 2013
Gliomas: histopathologic evaluation of changes in directionality and magnitude of water diffusion at diffusion-tensor
Andreas Stadlbauer1, Oliver Ganslandt, Rolf Buslei
1Department of Neurosurgery, Neurocenter, Departments of Neuropathology and Neurology, University of Erlangen-Nuremberg, Erlangen, Germany.
Purpose:
To retrospectively correlate changes in fractional anisotropy (FA) and mean diffusivity in gliomas at diffusion-tensor magnetic resonance (MR) imaging with the degree of tumor cell infiltration determined histologically.
Materials And Methods:
The institutional review board required neither ethics committee approval nor patient informed consent for this study. Twenty patients (eight women, 12 men; age range, 18-53 years) with glioma (seven World Health Organization grade II and 13 grade III tumors) underwent diffusion-tensor MR imaging at 1.5 T. Diffusion-tensor data were obtained with an echo-planar imaging sequence with six diffusion directions (b = 1000 sec/mm(2)), isotropic 1.9-mm voxels, and five averages. FA and mean diffusivity values were calculated from diffusion-tensor data. Coregistration with a three-dimensional MR imaging data set (used for stereotactic brain biopsies) enabled correlation of FA and mean diffusivity values with the histopathologic findings total cell number (CN), tumor CN, and percentage tumor infiltration (TI) by using linear, exponential, and logarithmic models. Student t and Mann-Whitney U tests were performed.
Results:
Histopathologic findings of 77 MR image-guided stereotactic biopsies in all 20 patients were correlated with FA and mean diffusivity values at the biopsy locus. For FA and mean diffusivity, a logarithmic model showed strongest correlation with tumor CN and total CN; a linear model showed strongest correlation with percentage TI. For FA there were negative logarithmic (R = -0.802, P < .001) and linear (R = -0.796, P < .001) correlations with tumor CN and percentage TI, respectively. For mean diffusivity there were positive logarithmic (R = 0.557, P < .001) and linear correlations (R = 0.521, P < .001) with tumor CN and percentage TI, respectively. Differences between correlations for FA and mean diffusivity versus tumor CN (P < .001) and percentage TI (P < .001) were significant.
Conclusion:
FA is better than mean diffusivity for assessment and delineation of different degrees of pathologic changes (ie, TI) in glioma.
