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Computational Models of High-Definition Electroconvulsive Therapy for Focal or Multitargeting Treatment.

Publication ,  Journal Article
Khadka, N; Deng, Z-D; Lisanby, SH; Bikson, M; Camprodon, JA
Published in: J ECT
August 26, 2024

Attempts to dissociate electroconvulsive therapy (ECT) therapeutic efficacy from cognitive side effects of ECT include modifying electrode placement, but traditional electrode placements employing 2 large electrodes are inherently nonfocal, limiting the ability to selectively engage targets associated with clinical benefit while avoiding nontargets associated with adverse side effects. Limited focality represents a technical limitation of conventional ECT, and there is growing evidence that the spatial distribution of the ECT electric fields induced in the brain drives efficacy and side effects. Computational models can be used to predict brain current flow patterns for existing and novel ECT montages. Using finite element method simulations (under quasi-static, nonadaptive assumptions, 800-mA total current), the electric fields generated in the superficial cortex and subcortical structures were predicted for the following traditional ECT montages (bilateral temporal, bifrontal, right unilateral) and experimental montages (focal electrically administered seizure therapy, lateralized high-definition [HD]-ECT, unilateral 4 × 1-ring HD-ECT, bilateral 4 × 1-ring HD-ECT, and a multipolar HD-ECT). Peak brain current density in regions of interest was quantified. Conventional montages (bilateral bifrontal, right unilateral) each produce distinct but diffuse and deep current flow. Focal electrically administered seizure therapy and lateralized HD-ECT produce unique, lateralized current flow, also impacting specific deep regions. A 4 × 1-ring HD-ECT restricts current flow to 1 (unilateral) or 2 (bilateral) cortical regions. Multipolar HD-ECT shows optimization to a specific target set. Future clinical trials are needed to determine whether enhanced control over current distribution is achieved with these experimental montages, and the resultant seizures, improve the risk/benefit ratio of ECT.

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Published In

J ECT

DOI

EISSN

1533-4112

Publication Date

August 26, 2024

Location

United States

Related Subject Headings

  • Psychiatry
  • 5203 Clinical and health psychology
  • 3209 Neurosciences
  • 3202 Clinical sciences
  • 1701 Psychology
  • 1109 Neurosciences
  • 1103 Clinical Sciences
 

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Khadka, N., Deng, Z.-D., Lisanby, S. H., Bikson, M., & Camprodon, J. A. (2024). Computational Models of High-Definition Electroconvulsive Therapy for Focal or Multitargeting Treatment. J ECT. https://doi.org/10.1097/YCT.0000000000001069
Khadka, Niranjan, Zhi-De Deng, Sarah H. Lisanby, Marom Bikson, and Joan A. Camprodon. “Computational Models of High-Definition Electroconvulsive Therapy for Focal or Multitargeting Treatment.J ECT, August 26, 2024. https://doi.org/10.1097/YCT.0000000000001069.
Khadka N, Deng Z-D, Lisanby SH, Bikson M, Camprodon JA. Computational Models of High-Definition Electroconvulsive Therapy for Focal or Multitargeting Treatment. J ECT. 2024 Aug 26;
Khadka, Niranjan, et al. “Computational Models of High-Definition Electroconvulsive Therapy for Focal or Multitargeting Treatment.J ECT, Aug. 2024. Pubmed, doi:10.1097/YCT.0000000000001069.
Khadka N, Deng Z-D, Lisanby SH, Bikson M, Camprodon JA. Computational Models of High-Definition Electroconvulsive Therapy for Focal or Multitargeting Treatment. J ECT. 2024 Aug 26;

Published In

J ECT

DOI

EISSN

1533-4112

Publication Date

August 26, 2024

Location

United States

Related Subject Headings

  • Psychiatry
  • 5203 Clinical and health psychology
  • 3209 Neurosciences
  • 3202 Clinical sciences
  • 1701 Psychology
  • 1109 Neurosciences
  • 1103 Clinical Sciences