TY - JOUR
T1 - Electric field strength induced by electroconvulsive therapy is associated with clinical outcome
AU - Fridgeirsson, Egill Axfjord
AU - Deng, Zhi-De
AU - Denys, Damiaan
AU - van Waarde, Jeroen A.
AU - van Wingen, Guido A.
N1 - Funding Information: We thank the department of radiology, Rijnstate Hospital, Arnhem, for their ongoing help in scanning our very ill patients. We thank O. Buno Heslinga, ECT nurse, for his never lasting help in gathering the data. Z.D. is supported by the National Institute of Mental Health Intramural Research Program (ZIAMH002955) and by Brain & Behavioral Research Foundation NARSAD Young Investigator Award 26161. Publisher Copyright: © 2021 The Author(s)
PY - 2021/1/1
Y1 - 2021/1/1
N2 - The clinical effect of electroconvulsive therapy (ECT) is mediated by eliciting a generalized seizure, which is achieved by applying electrical current to the head via scalp electrodes. The anatomy of the head influences the distribution of current flow in each brain region. Here, we investigated whether individual differences in simulated local electrical field strength are associated with ECT efficacy. We modeled the electric field of 67 depressed patients receiving ECT. Patient's T1 magnetic resonance images were segmented, conductivities were assigned to each tissue and the finite element method was used to solve for the electric field induced by the electrodes. We investigated the correlation between modelled electric field and ECT outcome using voxel-wise general linear models. The difference between bilateral (BL) and right unilateral (RUL) electrode placement was striking. Even within electrode configuration, there was substantial variability between patients. For the modeled BL placement, stronger electric field strengths appeared in the left hemisphere and part of the right temporal lobe. Importantly, a stronger electric field in the temporal lobes was associated with less optimal ECT response in patients treated with BL-ECT. No significant differences in electric field distributions were found between responders and non-responders to RUL-ECT. These results suggest that overstimulation of the temporal lobes during BL stimulation has negative consequences on treatment outcome. If replicated, individualized pre-ECT computer-modelled electric field distributions may inform the development of patient-specific ECT protocols.
AB - The clinical effect of electroconvulsive therapy (ECT) is mediated by eliciting a generalized seizure, which is achieved by applying electrical current to the head via scalp electrodes. The anatomy of the head influences the distribution of current flow in each brain region. Here, we investigated whether individual differences in simulated local electrical field strength are associated with ECT efficacy. We modeled the electric field of 67 depressed patients receiving ECT. Patient's T1 magnetic resonance images were segmented, conductivities were assigned to each tissue and the finite element method was used to solve for the electric field induced by the electrodes. We investigated the correlation between modelled electric field and ECT outcome using voxel-wise general linear models. The difference between bilateral (BL) and right unilateral (RUL) electrode placement was striking. Even within electrode configuration, there was substantial variability between patients. For the modeled BL placement, stronger electric field strengths appeared in the left hemisphere and part of the right temporal lobe. Importantly, a stronger electric field in the temporal lobes was associated with less optimal ECT response in patients treated with BL-ECT. No significant differences in electric field distributions were found between responders and non-responders to RUL-ECT. These results suggest that overstimulation of the temporal lobes during BL stimulation has negative consequences on treatment outcome. If replicated, individualized pre-ECT computer-modelled electric field distributions may inform the development of patient-specific ECT protocols.
KW - Electroconvulsive therapy
KW - Finite element modelling
KW - Major depressive disorder
UR - http://www.scopus.com/inward/record.url?scp=85100655851&partnerID=8YFLogxK
U2 - https://doi.org/10.1016/j.nicl.2021.102581
DO - https://doi.org/10.1016/j.nicl.2021.102581
M3 - Article
C2 - 33588322
SN - 2213-1582
VL - 30
JO - NeuroImage: Clinical
JF - NeuroImage: Clinical
M1 - 102581
ER -