Postprocessing of MRIs Using FreeSurfer in Epilepsy Surgery Patients Provides an Excellent Imaging Marker of Hippocampal Sclerosis but Fails to Separate Subtypes

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Objective. Histopathological examinations will diminish as minimally invasive epilepsy surgery increasingly replaces open surgery. The objective of this study was to test if visual and computer-aided quantitative analyses of presurgical high-quality 3 Tesla MRIs complying with the International League Against Epilepsy (ILAE) Neuroimaging Task Force recommendations can inform on histopathological diagnosis. Methods. Ninety-two patients from Copenhagen and Oslo University Hospitals fulfilled patient-, imaging-, and histopathological inclusion criteria: 69 patients were diagnosed with hippocampal sclerosis (HS) ILAE type 1 or 2, and 23 patients had normal appearing hippocampi or other histopathology than HS (no-HS). MRIs from 52 healthy controls (HC) were included. Image processing was performed in FreeSurfer v.6.0 with the built-in cross-sectional hippocampal subfield segmentation tool and multimodal MRI input. Volume outputs were used to calculate volume asymmetry ratios (VARs) for whole hippocampus (WH) and subfields. Results. HS patients had significantly larger WH VARs compared to no-HS patients and HC, with a sensitivity=0.93 and specificity=1.0 for histopathological HS diagnosis. Visual MRI assessment yielded a sensitivity=0.90 and specificity=0.96 for histopathological HS diagnosis. CA1 and CA4 VARs and the number of seizure-free patients were not significantly different in HS ILAE type 1 compared to type 2 patients. Significance. FreeSurfer analyses of presurgical MRIs are excellent at separating patients histopathologically diagnosed with HS from patients with other pathology or normal appearing hippocampi. Using the FreeSurfer hippocampal subfield segmentation tool did not allow for separating HS ILAE subtypes.

OriginalsprogEngelsk
Artikelnummer2366355
BogserieActa Neurologica Scandinavica
Vol/bind2023
Antal sider10
ISSN0001-6314
DOI
StatusUdgivet - 2023

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© 2023 Ane G. Kloster et al.

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