AUTHOR=Chu Yongqiang , Wu Jun , Wang Du , Huang Junli , Li Wei , Zhang Sheng , Ren Hongwei 

TITLE=Altered voxel-mirrored homotopic connectivity in right temporal lobe epilepsy as measured using resting-state fMRI and support vector machine analyses

JOURNAL=Frontiers in Psychiatry

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/psychiatry/articles/10.3389/fpsyt.2022.958294

DOI=10.3389/fpsyt.2022.958294

ISSN=1664-0640

ABSTRACT=Background: Prior reports have revealed abnormalities in voxel-mirrored homotopic connectivity (VMHC) when analyzing neuroimaging data from patients with various psychiatric conditions, including temporal lobe epilepsy (TLE). Whether these VHMC changes can be leveraged to aid in the diagnosis of right TLE (rTLE), however, remains to be established. This study was thus developed to examine abnormal VMHC findings associated with rTLE in order to determine whether these changes can be used to guide rTLE diagnosis. 
Methods: Resting-state functional magnetic resonance imaging (rs-fMRI) analyses of 59 rTLE patients and 60 normal control individuals, after which the resultant imaging data were analyzed using VMHC and support vector machine (SVM) approaches.
Results: Relative to normal controls, rTLE patients were found to exhibit decreased VMHC values in the bilateral superior and middle temporal pole (STP, MTP), the bilateral middle and inferior temporal gyrus (MTG, ITG), and the bilateral orbital portion of the inferior frontal gyrus (OrbIFG). These patients further exhibited increases in VMHC values in the bilateral precentral gyrus (PreCG), postcentral gyrus (PoCG), and supplemental motor area (SMA). These findings highlight the value of the right middle temporal gyrus (rMTG) when differentiating between rTLE and control individuals, with a corresponding SVM analysis yielding respective accuracy, sensitivity, and specificity values of 70.59% (84/119), 78.33% (47/60), and 69.49% (41/59). 
Conclusion: In summary, rTLE patients exhibit various forms of abnormal functional connectivity, and SVM analyses support the potential value of abnormal VMHC values as a neuroimaging biomarker that can aid in the diagnosis of this condition.