Retrospective analysis of hemispheric structural network change as a function of location and size of glioma

Abstract

Gliomas are neoplasms that arise from glial cell origin and represent the largest fraction of primary malignant brain tumours (77%). These highly infiltrative malignant cell clusters modify brain structure and function through expansion, invasion and intratumoral modification. Depending on the growth rate of the tumour, location and degree of expansion, functional reorganization may not lead to overt changes in behaviour despite significant cerebral adaptation. Studies in simulated lesion models and in patients with stroke reveal both local and distal functional disturbances, using measures of anatomical brain networks. Investigations over the last two decades have sought to use diffusion tensor imaging tractography data in the context of intracranial tumours to improve surgical planning, intraoperative functional localization, and post-operative interpretation of functional change. In this study, we used diffusion tensor imaging tractography to assess the impact of tumour location on the white matter structural network. To better understand how various lobe localized gliomas impact the topology underlying efficiency of information transfer between brain regions, we identified the major alterations in brain network connectivity patterns between the ipsilesional versus contralesional hemispheres in patients with gliomas localized to the frontal, parietal or temporal lobe. Results were indicative of altered network efficiency and the role of specific brain regions unique to different lobe localized gliomas. This work draws attention to connections and brain regions which have shared structural susceptibility in frontal, parietal and temporal lobe glioma cases. This study also provides a preliminary anatomical basis for understanding which affected white matter pathways may contribute to preoperative patient symptomology.

Keywords: DTI; glioma; graph network; structural connectivity.

Graphical Abstract

Figure 1

Nodal percent change in network measure from contralesional hemisphere. (A) Percent change in FA weighted BC from the contralesional hemisphere for each AAL2 identified node. (B) Compiled percent change dot plots of each network measure (CC, EC, LE) weighted by end-point tract count, FA, and MD for each AAL2 identified node. A list of all anatomical abbreviations is provided in Supplementary Table 1 (Rolls et al., 2020).

Figure 2

Euclidian distance from tumour (mm) versus average percent change in DTI-connectivity measure. (A) Correlation analysis between the average Euclidian distance of ipsilesional AAL2 node from centroid of tumour ROI (mm) against the average percent change in BC count, FA and MD from the corresponding contralesional AAL2 node. (B) Correlation analysis between the average Euclidian distance of ipsilesional AAL2 node from centroid of tumour ROI (mm) against the average percent change in CC count, FA, and MD from the corresponding contralesional AAL2 node. (C) Correlation analysis between the average Euclidian distance of ipsilesional AAL2 node from centroid of tumour ROI (mm) against the average percent change in EC count, FA, and MD from the corresponding contralesional AAL2 node. (D) Correlation analysis between the average Euclidian distance of ipsilesional AAL2 node from centroid of tumour ROI (mm) against the average percent change in LE count, FA and MD from the corresponding contralesional AAL2 node.

Figure 3

Distribution of mean percent change in top 10 percentile AAL2 brain regions affected by glioma lobe localization. (A) Density and dot plot visualization of the percent change in CC of the top 10 percentile AAL2 nodes affected by glioma lobe localization. H-test revealed the distribution of percent change in CC in these nodes was found to be significantly different in temporal lobe localized gliomas. (B) Density and dot plot visualization of the percent change in LE of the top 10 percentile AAL2 nodes affected by glioma lobe localization. H-test revealed no significantly different distributions between the three lobe localized glioma groups. (C) Density and dot plot visualization of the percent change in BC of the top 10 percentile AAL2 nodes affected by glioma lobe localization. H-test revealed the distribution of percent change in BC in these nodes was found to be significantly different in temporal lobe localized gliomas. (D) Density and dot plot visualization of the percent change in EC of the top 10 percentile AAL2 nodes affected by glioma lobe localization. H-test revealed the distribution of percent change in EC in these nodes was found to be significantly different in frontal and temporal lobe localized gliomas. A list of all anatomical abbreviations is provided in Supplementary Table 1 (Rolls et al., 2020).

Figure 4

Mean change in FA in significantly altered connections of frontal, parietal and temporal lobe localized glioma cases. An axial anatomical representation of mean change in FA of significantly affected connections (by change in end-point tract count) in frontal, parietal, and temporal lobe localized glioma cases. A list of all anatomical abbreviations is provided in Supplementary Table 1 (Rolls et al., 2020).