Electrical conductivity of tissue at frequencies below 1 MHz

Gabriel, Camelia; Peyman, Azadeh; Grant, E H

doi:10.1088/0031-9155/54/16/002

Cited by 590 publications

(497 citation statements)

References 47 publications

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“…Dielectric tissue parameters were obtained from the IT'IS database, 10 which utilizes the work of Gabriel et al [11][12][13] This method yields unusually high permittivity values at the low frequencies used in TMS but these have been shown to be an insignificant factor in the calculation of induced electric field for TMS. 14,15 B. Calculation of magnetic and electric field Magnetic and electric fields were calculated using SEMCAD X, implementing a low frequency solver based on a quasi-static model.…”

Section: A Anatomical Mouse Modelmentioning

confidence: 99%

Transcranial magnetic stimulation of mouse brain using high-resolution anatomical models

Crowther

Hadimani

Kanthasamy

et al. 2014

Journal of Applied Physics

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Transcranial magnetic stimulation (TMS) offers the possibility of non-invasive treatment of braindisorders in humans. Studies on animals can allow rapid progress of the research including exploring a variety of different treatment conditions. Numerical calculations using animalmodels are needed to help design suitable TMS coils for use in animal experiments, in particular, to estimate the electric field induced in animal brains. In this paper, we have implemented a high-resolution anatomical MRI-derived mouse model consisting of 50 tissuetypes to accurately calculate induced electric field in the mouse brain. Magnetic field measurements have been performed on the surface of the coil and compared with the calculations in order to validate the calculated magnetic and induced electric fields in the brain.Results show how the induced electric field is distributed in a mouse brain and allow investigation of how this could be improved for TMS studies using mice. The findings have important implications in further preclinical development of TMS for treatment of human diseases. Transcranial magnetic stimulation (TMS) offers the possibility of non-invasive treatment of brain disorders in humans. Studies on animals can allow rapid progress of the research including exploring a variety of different treatment conditions. Numerical calculations using animal models are needed to help design suitable TMS coils for use in animal experiments, in particular, to estimate the electric field induced in animal brains. In this paper, we have implemented a high-resolution anatomical MRI-derived mouse model consisting of 50 tissue types to accurately calculate induced electric field in the mouse brain. Magnetic field measurements have been performed on the surface of the coil and compared with the calculations in order to validate the calculated magnetic and induced electric fields in the brain. Results show how the induced electric field is distributed in a mouse brain and allow investigation of how this could be improved for TMS studies using mice. The findings have important implications in further preclinical development of TMS for treatment of human diseases. V C 2014 AIP Publishing LLC.

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Section: A Anatomical Mouse Modelmentioning

confidence: 99%

Transcranial magnetic stimulation of mouse brain using high-resolution anatomical models

Crowther

Hadimani

Kanthasamy

et al. 2014

Journal of Applied Physics

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“…Additionally 24 % (16 screws) of thoracic and 15 % (21 screws) of lumbar screws caused cortical breach in either horizontal, vertical or both directions, but had stimulation thresholds above 10 mA (false negatives, Table 2). Split into three regions (10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30) and [30 mA, Fig. 2) the stimulation threshold range of 10-20 mA hosts both, the majority of correctly placed and the majority (67 %) of misplaced thoracic screws.…”

Section: Resultsmentioning

confidence: 99%

A CT-based study investigating the relationship between pedicle screw placement and stimulation threshold of compound muscle action potentials measured by intraoperative neurophysiological monitoring

et al. 2013

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Purpose Neurophysiological monitoring aims to improve the safety of pedicle screw placement, but few quantitative studies assess specificity and sensitivity. In this study, screw placement within the pedicle is measured (post-op CT scan, horizontal and vertical distance from the screw edge to the surface of the pedicle) and correlated with intraoperative neurophysiological stimulation thresholds. Methods A single surgeon placed 68 thoracic and 136 lumbar screws in 30 consecutive patients during instrumented fusion under EMG control. The female to male ratio was 1.6 and the average age was 61.3 years (SD 17.7). Radiological measurements, blinded to stimulation threshold, were done on reformatted CT reconstructions using OsiriX software. A standard deviation of the screw position of 2.8 mm was determined from pilot measurements, and a 1 mm of screw-pedicle edge distance was considered as a difference of interest (standardised difference of 0.35) leading to a power of the study of 75 % (significance level 0.05). Results Correct placement and stimulation thresholds above 10 mA were found in 71 % of screws. Twenty-two percent of screws caused cortical breach, 80 % of these had stimulation thresholds above 10 mA (sensitivity 20 %, specificity 90 %). True prediction of correct position of the screw was more frequent for lumbar than for thoracic screws. Conclusion A screw stimulation threshold of [10 mA does not indicate correct pedicle screw placement. A hypothesised gradual decrease of screw stimulation thresholds was not observed as screw placement approaches the nerve root. Aside from a robust threshold of 2 mA indicating direct contact with nervous tissue, a secondary threshold appears to depend on patients' pathology and surgical conditions.

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“…K. S. Cole and R. H. Cole provided empirical formula to calculate dispersion and absorption properties of a number of liquids and dielectrics across the wide frequency band, termed as N-term Cole-Cole model [23]. Later on, S. Gabriel and C. Gabriel modified the N-term Cole-Cole model to adapt for assignment of dielectric properties to over 30 body tissues [9][10][11][12][13]. It is termed as 4-term Cole-Cole model and is valid across the frequency range of 10 Hz to 20 GHz.…”

Section: Fig 1: Layout Of An Emit-based Head Imaging Systemmentioning

confidence: 99%

“…The dielectric properties are allocated as it is, to different layers of head tissues using Gabriel database [9][10][11][12][13]. We understand that the verification of microwave systems for head imaging is highly dependent on an anatomically accurate and structurally detailed human head model.…”

Section: Head Model Generationmentioning

confidence: 99%

“…Mostly, the realistic head models are developed using MRI images or CT data sets. The dielectric properties to different head tissues are assigned using averaged values or frequency-dispersive models [9][10][11][12][13]. To mimic the directional behavior of dielectric properties of brain tissues; diffusion tensor imaging (DTI) or diffusion spectrum imaging (DSI) based mapping is incorporated in the head models [14].…”

mentioning

confidence: 99%

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An Investigation Into Electromagnetic Based Impedance Tomography Using Realistic Human Head Model

Munawar

Mustansar

Nadeem

et al. 2016

Int J Pharm Pharm Sci

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College of Electrical and Mechanical Engineering, National University of Sciences and Technology, Islamabad, Pakistan Email: awaismunawar.phd06@rcms.nust.edu.pkThe objective of this research is to investigate the feasibility of Electromagnetic based Impedance Tomography (EMIT) for brain stroke detection, localization and classification. Electromagnetic based Impedance Tomography employing microwave imaging technique is an emerging brain stroke diagnostic modality. It relies on the significant contrast between dielectric properties of the normal and abnormal brain tissues. To study the interaction between micro-wave signals and head tissues, the simulations are performed using a geometrically simple 3-D ellipsoid head model with emulated stroke. Finite Element numerical technique is adopted to find the solution of Maxwell's equations to measure the transmitted and backscattered signals in forward problem. Contrast Source Inversion technique is proposed to solve the inverse scattering problem and reconstruct brain images based on calculated dielectric profiles. Detailed analysis is performed to determine the safety limits of transmitted signals to minimize ionizing effects while ensuring maximum penetration. The simulations verify the inhomogeneous and frequency-dispersive behavior of brain tissue's dielectric properties. The solution of the forward problem demonstrates the microwave signals scattering by the multilayer structure of the head model, duly validated by analytical results. The scattering phenomena can be fully capitalized by image reconstruction algorithm to obtain brain images and detect stroke presence. The initial results obtained in this research and prior work indicates that EMIT-based head imaging system has a potential for rapid stroke detection, classification, and continuous brain monitoring and offers a comparatively cost-effective solution.

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Electrical conductivity of tissue at frequencies below 1 MHz

Cited by 590 publications

References 47 publications

Transcranial magnetic stimulation of mouse brain using high-resolution anatomical models

Transcranial magnetic stimulation of mouse brain using high-resolution anatomical models

A CT-based study investigating the relationship between pedicle screw placement and stimulation threshold of compound muscle action potentials measured by intraoperative neurophysiological monitoring

An Investigation Into Electromagnetic Based Impedance Tomography Using Realistic Human Head Model

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