Literature DB >> 27393801

Heat transfer due to electroconvulsive therapy: Influence of anisotropic thermal and electrical skull conductivity.

Marilia Menezes de Oliveira1, Peng Wen2, Tony Ahfock2.   

Abstract

BACKGROUND AND OBJECTIVES: This paper focuses on electroconvulsive therapy (ECT) and head models to investigate temperature profiles arising when anisotropic thermal and electrical conductivities are considered in the skull layer. The aim was to numerically investigate the threshold for which this therapy operates safely to the brain, from the thermal point of view.
METHODS: A six-layer spherical head model consisting of scalp, fat, skull, cerebro-spinal fluid, grey matter and white matter was developed. Later on, a realistic human head model was also implemented. These models were built up using the packages from COMSOL Inc. and Simpleware Ltd. In these models, three of the most common electrode montages used in ECT were applied. Anisotropic conductivities were derived using volume constraint and included in both spherical and realistic head models. The bio-heat transferring problem governed by Laplace equation was solved numerically.
RESULTS: The results show that both the tensor eigenvalues of electrical conductivity and the electrode montage affect the maximum temperature, but thermal anisotropy does not have a significant influence. Temperature increases occur mainly in the scalp and fat, and no harm is caused to the brain by the current applied during ECT.
CONCLUSIONS: The work assures the thermal safety of ECT and also provides a numerical method to investigate other non-invasive therapies.
Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Anisotropy; ECT; Finite element method; Head model; Temperature

Mesh:

Year:  2016        PMID: 27393801     DOI: 10.1016/j.cmpb.2016.05.022

Source DB:  PubMed          Journal:  Comput Methods Programs Biomed        ISSN: 0169-2607            Impact factor:   5.428


  1 in total

1.  Towards an Accurate MRI Acute Ischemic Stroke Lesion Segmentation Based on Bioheat Equation and U-Net Model.

Authors:  Abdelmajid Bousselham; Omar Bouattane; Mohamed Youssfi; Abdelhadi Raihani
Journal:  Int J Biomed Imaging       Date:  2022-07-16
  1 in total

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