Literature DB >> 22452983

A DTI-based model for TMS using the independent impedance method with frequency-dependent tissue parameters.

N De Geeter1, G Crevecoeur, L Dupré, W Van Hecke, A Leemans.   

Abstract

Accurate simulations on detailed realistic head models are necessary to gain a better understanding of the response to transcranial magnetic stimulation (TMS). Hitherto, head models with simplified geometries and constant isotropic material properties are often used, whereas some biological tissues have anisotropic characteristics which vary naturally with frequency. Moreover, most computational methods do not take the tissue permittivity into account. Therefore, we calculate the electromagnetic behaviour due to TMS in a head model with realistic geometry and where realistic dispersive anisotropic tissue properties are incorporated, based on T1-weighted and diffusion-weighted magnetic resonance images. This paper studies the impact of tissue anisotropy, permittivity and frequency dependence, using the anisotropic independent impedance method. The results show that anisotropy yields differences up to 32% and 19% of the maximum induced currents and electric field, respectively. Neglecting the permittivity values leads to a decrease of about 72% and 24% of the maximum currents and field, respectively. Implementing the dispersive effects of biological tissues results in a difference of 6% of the maximum currents. The cerebral voxels show limited sensitivity of the induced electric field to changes in conductivity and permittivity, whereas the field varies approximately linearly with frequency. These findings illustrate the importance of including each of the above parameters in the model and confirm the need for accuracy in the applied patient-specific method, which can be used in computer-assisted TMS.

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Year:  2012        PMID: 22452983     DOI: 10.1088/0031-9155/57/8/2169

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  7 in total

Review 1.  The development and modelling of devices and paradigms for transcranial magnetic stimulation.

Authors:  Stefan M Goetz; Zhi-De Deng
Journal:  Int Rev Psychiatry       Date:  2017-04-26

2.  The effect of local anatomy on the electric field induced by TMS: evaluation at 14 different target sites.

Authors:  Arno M Janssen; Thom F Oostendorp; Dick F Stegeman
Journal:  Med Biol Eng Comput       Date:  2014-08-28       Impact factor: 2.602

3.  Indirect frontocingulate structural connectivity predicts clinical response to accelerated rTMS in major depressive disorder

Authors:  Deborah C.W. Klooster; Iris N. Vos; Karen Caeyenberghs; Alexander Leemans; Szabolcs David; René M.H. Besseling; Albert P. Aldenkamp; Chris Baeken
Journal:  J Psychiatry Neurosci       Date:  2020-07-01       Impact factor: 6.186

4.  Impact of brain tissue filtering on neurostimulation fields: a modeling study.

Authors:  Tim Wagner; Uri Eden; Jarrett Rushmore; Christopher J Russo; Laura Dipietro; Felipe Fregni; Stephen Simon; Stephen Rotman; Naomi B Pitskel; Ciro Ramos-Estebanez; Alvaro Pascual-Leone; Alan J Grodzinsky; Markus Zahn; Antoni Valero-Cabré
Journal:  Neuroimage       Date:  2013-07-10       Impact factor: 6.556

5.  Groupwise image registration based on a total correlation dissimilarity measure for quantitative MRI and dynamic imaging data.

Authors:  Jean-Marie Guyader; Wyke Huizinga; Dirk H J Poot; Matthijs van Kranenburg; André Uitterdijk; Wiro J Niessen; Stefan Klein
Journal:  Sci Rep       Date:  2018-08-30       Impact factor: 4.379

6.  The influence of sulcus width on simulated electric fields induced by transcranial magnetic stimulation.

Authors:  A M Janssen; S M Rampersad; F Lucka; B Lanfer; S Lew; U Aydin; C H Wolters; D F Stegeman; T F Oostendorp
Journal:  Phys Med Biol       Date:  2013-06-21       Impact factor: 3.609

7.  Noninvasive Electric Current Induction for Low-Frequency Tissue Conductivity Reconstruction: Is It Feasible With a TMS-MRI Setup?

Authors:  Stefano Mandija; Petar I Petrov; Sebastian F W Neggers; Peter R Luijten; Cornelis A T van den Berg
Journal:  Tomography       Date:  2016-09
  7 in total

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