Dong Ah Lee1, Ho-Joon Lee2, Hyung Chan Kim1, Kang Min Park3. 1. Department of Neurology, Haeundae Paik Hospital, Inje University College of Medicine, Haeundae-ro 875, Haeundae-gu, Busan, 48108, Korea. 2. Department of Radiology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Korea. 3. Department of Neurology, Haeundae Paik Hospital, Inje University College of Medicine, Haeundae-ro 875, Haeundae-gu, Busan, 48108, Korea. smilepkm@hanmail.net.
Abstract
PURPOSE: The aim of this study was to determine whether anti-seizure medication (ASM) response is associated with structural connectivity in diffusion tensor imaging (DTI) or functional co-variance network in arterial spin labeling (ASL) magnetic resonance imaging (MRI) in patients with focal epilepsy. METHODS: In this retrospective study conducted at a tertiary hospital, we enrolled 105 patients with focal epilepsy, of which 64 patients were good ASM responders, and 41 patients were poor ASM responders. All patients showed normal MRI findings on visual inspection and underwent DTI and ASL MRI from August 2018 to July 2020, with regular follow-up for at least 12 months after epilepsy diagnosis while taking ASMs. We calculated the structural connectivity based on DTI and functional co-variance network based on ASL MRI by using graph theory and analyzed their differences in relation to the ASM response. RESULTS: No differences were observed in structural connectivity between the good and poor ASM responders. However, significant differences were observed in functional co-variance network between the good and poor ASM responders. In comparison with good ASM responders, poor ASM responders showed a significantly greater characteristic path length (2.557 vs. 1.753, p = 0.034) and a lower local efficiency (2.311 vs. 3.927, p = 0.048). CONCLUSION: Significant differences were observed in functional co-variance network based on ASL MRI between the good and poor ASM responders. These findings suggest that functional co-variance network could serve as a new biomarker of ASM response in focal epilepsy.
PURPOSE: The aim of this study was to determine whether anti-seizure medication (ASM) response is associated with structural connectivity in diffusion tensor imaging (DTI) or functional co-variance network in arterial spin labeling (ASL) magnetic resonance imaging (MRI) in patients with focal epilepsy. METHODS: In this retrospective study conducted at a tertiary hospital, we enrolled 105 patients with focal epilepsy, of which 64 patients were good ASM responders, and 41 patients were poor ASM responders. All patients showed normal MRI findings on visual inspection and underwent DTI and ASL MRI from August 2018 to July 2020, with regular follow-up for at least 12 months after epilepsy diagnosis while taking ASMs. We calculated the structural connectivity based on DTI and functional co-variance network based on ASL MRI by using graph theory and analyzed their differences in relation to the ASM response. RESULTS: No differences were observed in structural connectivity between the good and poor ASM responders. However, significant differences were observed in functional co-variance network between the good and poor ASM responders. In comparison with good ASM responders, poor ASM responders showed a significantly greater characteristic path length (2.557 vs. 1.753, p = 0.034) and a lower local efficiency (2.311 vs. 3.927, p = 0.048). CONCLUSION: Significant differences were observed in functional co-variance network based on ASL MRI between the good and poor ASM responders. These findings suggest that functional co-variance network could serve as a new biomarker of ASM response in focal epilepsy.
Authors: Ze Wang; Geoffrey K Aguirre; Hengyi Rao; Jiongjiong Wang; María A Fernández-Seara; Anna R Childress; John A Detre Journal: Magn Reson Imaging Date: 2007-09-10 Impact factor: 2.546
Authors: Barbara A K Kreilkamp; Andrea McKavanagh; Batil Alonazi; Lorna Bryant; Kumar Das; Udo C Wieshmann; Anthony G Marson; Peter N Taylor; Simon S Keller Journal: Neuroimage Clin Date: 2021-01-19 Impact factor: 4.881