Gliomas can impair the white matter (WM) network, potentially resulting in dysfunction. We analysed the gliomas" effects on structural connectivity in relation to aphasia. We used the patients" connectomes to identify network impairments related to aphasia and network topology using network theory.
We studied 47 patients with left-perisylvian gliomas (WHO grade II (6), III (15), IV (26), 32; females; mean age=53, SD=14; age-range=28-78) for aphasia assessment using the Aachen aphasia test (AAT). AAT subtests included a token test, naming, repetition, and speech comprehension. 15 patients presented with aphasia. We constructed whole brain tractograms with constrained spherical deconvolution (CSD), performed anatomically constrained tractography and CSD-informed filtering of tractograms using MRtrix3. The resulting connectomes were based on the Desikan-Killiany-Tourville atlas and FreeSurfer. We calculated graph-based measures, such as assortativity, local & global efficiency, and node measures like node strength, betweenness centrality, and clustering coefficients, comparing these between hemispheres and correlating with AAT results.
We found significant differences between the two hemispheres in assortativity (p=3.8e-5) and global efficiency (p=3.6e-3). Strong correlations emerged between global efficiency and token test (rs(46)=.52, p=1.2e-3). Node measures correlated significantly with AAT subtests, especially in the left hemisphere. The left precentral gyrus showed the strongest negative correlation between node strength and naming (rs(46)=-.51, p=1.5e-4), and betweenness centrality and token test (rs(46)=-.41, p=1.3e-2). The left superior frontal gyrus correlated most strongly with token test and betweenness centrality (rs(46)=.47, p=4.5e-3) and the left superior parietal gyrus correlated with token test and node strength (rs(46)=-.54, p=7.4e-4). Further, the left paracentral region correlated most strongly with naming and betweenness centrality (rs(46)=-.55, p=4.09e-4), speech comprehension and betweenness centrality (rs(46)=-.46, p=5.3e-3), and token test and betweenness centrality (rs(46)=-.67, p=1.1e-5).
Network theory enables the mapping of impaired WM structure caused by tumors. Our analyses shed light on how a tumor affects a brain"s structural network and impairs the networks" integrity, leading to functional defects. Here, we identified significant sub-networks in relation to the gliomas" impact on the language network.