MRI data was flipped according to the affected AN (i.e., right hemisphere represents ipsilateral to the tumor) with the MRIcron software ( Subsequent analysis steps were performed by the Brainsuite software package for SBM ( In brief, Brainsuite performs a sequence of image analysis steps including skull and scalp removal, nonuniformity correction, tissue classification, topology correction, and surface generation to produce triangular surface mesh models of the inner and outer boundaries of the cerebral cortex. Next, the surfaces for each subject were registered to a reference atlas surface using Brainsuite's surface/volume registration software (SVReg, The SVReg-results were proofed manually to ensure proper segmentation and surface/volume registration (see Fig. 5). This results in a spatial alignment of the white/gray matter (WM/GM) cortical surfaces across all subjects. The GM volume of each region-of-interest (ROI) was averaged and used for ROI-based analysis (Table (Table2).2). For, vertex-vice (i.e., whole-brain) analysis data was smoothed using a 2.5‐mm kernel compensating for registration inaccuracies.

(A) Exemplary MR image of a patient with a T3 vestibular schwannoma of the right side. Data processing included skull striping and brain extraction process followed by the automated brain atlas registration (B,C).

The GM volume of each ROI was normalized by division of the total cortical (GM + WM) volume82,83 in order to correct for global effects such as head size, age and gender84,85. Most commonly, an estimate of intracranial volume is including the cerebrospinal fluid (CSF + GM + WM)8689. In the present study, however, CSF volume, in contrast to GM and WM, was not normally distributed (p = 0.023, Kolgomorov-Smirnov-Test) and was consequently not included in the normalization process. This could be explained by the fact that vestibular schwannomas affect CSF circulation by obstruction or malreabsorption90,91. Finally, the presence of tinnitus did not affect CSF volume in the present study (p > 0.756, Kruskal–Wallis).

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