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Multi-scale Image Analysis and Prediction of Visual Field De | 94643

Internationale Zeitschrift für Verbundforschung im Bereich Innere Medizin und öffentliche Gesundheit

ISSN - 1840-4529

Abstrakt

Multi-scale Image Analysis and Prediction of Visual Field Defects after Selective Amygdalohippocampectomy

Shagufta Hasan

Patients with therapy-refractory temporal lobe epilepsy benefit from selective amygdalohippocampectomy, however it can induce Visual Field Defects (VFD). We used whole-brain studies from voxel to network level to describe tissue-specific pre- and postoperative imaging correlates of VFD severity. Pre- and postoperative MRI (T1-MPRAGE and Diffusion Tensor Imaging) as well as kinetic perimetry according to the Goldmann standard were performed on 28 individuals with temporal lobe epilepsy. Using voxel-based morphometry and tract-based spatial statistics, we looked for whole-brain Grey Matter (GM) and White Matter (WM) correlations with VFD. We also performed local and global network studies, as well as reconstructing individual structural connectomes. The postsurgical GM volume decreased with increasing VFD severity in two clusters in the bihemispheric middle temporal gyri (FWE-corrected p 0.05). With increasing severity of VFD in the ipsilesional optic radiation, the fractional anisotropy of a single WM cluster decreased (FWE-corrected p 0.05). Furthermore, patients with VFD had a larger number of postoperative local connectivity alterations than those without. We identified no preoperative associations of VFD severity in the GM, WM, or network measures. Nonetheless, an artificial neural network meta-classifier could predict the occurrence of VFD based on presurgical connectomes above the chance level in an exploratory study.