Resting-state functional MRI (rs-fMRI) allows mapping temporally coherent brain networks, and intra-and inter-network alterations have been described in different diseases. This prospective study investigated hemispheric resting-state functional connectivity (RSFC) differences in the default-mode network (DMN) and frontoparietal network (FPN) between patients with left-and right-hemispheric gliomas (LH PAT, RH PAT), addressing asymmetry effects the tumor might have on networkspecific intrinsic functional connectivity under consideration of the prognostically relevant isocitrate-dehydrogenase (IDH) mutation status. Twenty-seven patients (16 LH PAT, 12 IDH-wildtype) and 27 healthy controls underwent anatomical and rs-fMRI as well as neuropsychological assessment. Independent component analyses were performed to identify the DMN and FPN. Hemispheric DMN-and FPN-RSFC were computed, compared across groups, and correlated with cognitive performance. Patient groups did not differ in tumor volume, grade or location. RH PAT showed higher contra-tumoral DMN-RSFC than controls and LH PAT. With regard to the FPN, contra-tumoral RSFC was increased in both patient groups as compared to controls. Higher contra-tumoral RSFC was associated with worse cognitive performance in patients, which, however, seemed to apply mainly to IDH-wildtype patients. The benefit of RSFC alterations for cognitive performance varied depending on the affected hemisphere, cognitive demand, and seemed to be altered by IDH-mutation status.

Immunohistochemical data based on isocitrate–dehydrogenase (IDH) mutation status have redefined glioma as a whole-brain disease, while occult tumor cell invasion along white matter fibers is inapparent in conventional magnetic resonance imaging (MRI). The functional and prognostic impact of focal glioma may however relate to the extent of white matter involvement. We used diffusion tensor imaging (DTI) to investigate microstructural characteristics of whole-brain normal-appearing white matter (NAWM) in relation to cognitive functions as potential surrogates for occult white matter involvement in glioma. Twenty patients (12 IDH-mutated) and 20 individually matched controls were preoperatively examined using DTI combined with a standardized neuropsychological examination. Tumor lesions including perifocal edema were masked, and fractional anisotropy (FA) as well as mean, radial, and axial diffusivity (MD, RD, and AD, respectively) of the remaining whole-brain NAWM were determined by using Tract-Based Spatial Statistics and histogram analyses. The relationship between extratumoral white matter integrity and cognitive performance was examined using partial correlation analyses controlling for age, education, and lesion volumes. In patients, mean FA and AD were decreased as compared to controls, which agrees with the notion of microstructural impairment of NAWM in glioma patients. Patients performed worse in all cognitive domains tested, and higher anisotropy and lower MD and RD values of NAWM were associated with better cognitive performance. In additional analyses, IDH-mutated and IDH-wildtype patients were compared. Patients with IDH-mutation showed higher FA, but lower MD, AD, and RD values as compared to IDH-wildtype patients, suggesting a better preserved microstructural integrity of NAWM, which may relate to a less infiltrative nature of IDH-mutated gliomas. Diffusion-based phenotyping and monitoring microstructural integrity of extratumoral whole-brain NAWM may aid in estimating occult white matter involvement and should be considered as a complementary biomarker in glioma.

With diffuse infiltrative glioma being increasingly recognized as a systemic brain disorder, the macroscopically apparent tumor lesion is suggested to impact on cerebral functional and structural integrity beyond the apparent lesion site. We investigated resting-state functional connectivity (FC) and diffusion-MRI-based structural connectivity (SC) (comprising edge-weight (EW) and fractional anisotropy (FA)) in isodehydrogenase mutated (IDHmut) and wildtype (IDHwt) patients and healthy controls. SC and FC were determined for whole-brain and the Default-Mode Network (DMN), mean intra- and interhemispheric SC and FC were compared across groups, and partial correlations were analyzed intra- and intermodally. With interhemispheric EW being reduced in both patient groups, IDHwt patients showed FA decreases in the ipsi- and contralesional hemisphere, whereas IDHmut patients revealed FA increases in the contralesional hemisphere. Healthy controls showed strong intramodal connectivity, each within the structural and functional connectome. Patients however showed a loss in structural and reductions in functional connectomic coherence, which appeared to be more pronounced in IDHwt glioma patients. Findings suggest a relative dissociation of structural and functional connectomic coherence in glioma patients at the time of diagnosis, with more structural connectomic aberrations being encountered in IDHwt glioma patients. Connectomic profiling may aid in phenotyping and monitoring prognostically differing tumor types.

Diffusion-weighted MRI makes it possible to quantify subvoxel brain microstructure and to reconstruct white matter fiber trajectories with which structural connectomes can be created. However, at the border between cerebrospinal fluid and white matter, or in the presence of edema, the obtained MRI signal originates from both the cerebrospinal fluid as well as from the white matter partial volume. Diffusion tractography can be strongly influenced by these free water partial volume effects. Thus, including a free water model can improve diffusion tractography in glioma patients. Here, we analyze how including a free water model influences structural connectivity estimates in healthy subjects as well as in brain tumor patients. During a clinical study, we acquired diffusion MRI data of 35 glioma patients and 28 age-and sex-matched controls, on which we applied an open-source deep learning based free water model. We performed deterministic as well as probabilistic tractography before and after free water modeling, and utilized the tractograms to create structural connectomes. Finally, we performed a quantitative analysis of the connectivity matrices. In our experiments, the number of tracked diffusion streamlines increased by 13% for high grade glioma patients, 9.25% for low grade glioma, and 7.65% for healthy controls. Intra-subject similarity of hemispheres increased significantly for the patient as well as for the control group, with larger effects observed in the patient group. Furthermore, inter-subject differences in connectivity between brain tumor patients and healthy subjects were reduced when including free water modeling. Our results indicate that free water modeling increases the similarity of connectivity matrices in brain tumor patients, while the observed effects are less pronounced in healthy subjects. As the similarity between brain tumor patients and healthy controls also increased, connectivity changes in brain tumor patients may have been overestimated in studies that did not perform free water modeling.

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