東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

3-dimensional modeling of transcrani...

The University of Texas Health Science Center at San Antonio., Biomedical Engineering.

Linked to FindBook

Google Book

Amazon

博客來

3-dimensional modeling of transcranial magnetic stimulation: Design and application.

Record Type:	Electronic resources : Monograph/item
Title/Author:	3-dimensional modeling of transcranial magnetic stimulation: Design and application./
Author:	Salinas, Felipe Santiago.
Description:	195 p.
Notes:	Adviser: Jack L. Lancaster.
Contained By:	Dissertation Abstracts International69-07B.
Subject:	Biophysics, Medical. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3320139
ISBN:	9780549713586

3-dimensional modeling of transcranial magnetic stimulation: Design and application.
Salinas, Felipe Santiago.

3-dimensional modeling of transcranial magnetic stimulation: Design and application. - 195 p.

Adviser: Jack L. Lancaster.

Thesis (Ph.D.)--The University of Texas Health Science Center at San Antonio, 2008.

Over the past three decades, transcranial magnetic stimulation (TMS) has emerged as an effective tool for many research, diagnostic and therapeutic applications in humans. TMS delivers highly localized brain stimulations via non-invasive externally applied magnetic fields. This non-invasive, painless technique provides researchers and clinicians a unique tool capable of stimulating both the central and peripheral nervous systems. However, a complete analysis of the macroscopic electric fields produced by TMS has not yet been performed. In this dissertation, we present a thorough examination of the total electric field induced by TMS in air and a realistic head model with clinically relevant coil poses. In the first chapter, a detailed account of TMS coil wiring geometry was shown to provide significant improvements in the accuracy of primary E-field calculations. Three-dimensional models which accounted for the TMS coil's wire width, height, shape and number of turns clearly improved the fit of calculated-to-measured E-fields near the coil body. Detailed primary E-field models were accurate up to the surface of the coil body (within 0.5% of measured values) whereas simple models were often inadequate (up to 32% different from measured). In the second chapter, we addressed the importance of the secondary E-field created by surface charge accumulation during TMS using the boundary element method (BEM). 3-D models were developed using simple head geometries in order to test the model and compare it with measured values. The effects of tissue geometry, size and conductivity were also investigated. Finally, a realistic head model was used to assess the effect of multiple surfaces on the total E-field. We found that secondary E-fields have the greatest impact at areas in close proximity to each tissue layer. Throughout the head, the secondary E-field magnitudes were predominantly between 25% and 45% of the primary E-fields magnitude. The direction of the secondary E-field was primarily in opposition to the primary E-field, however there are some locations (i.e. going from high to low conductivity) where the secondary E-field adds to the primary E-field. Thus the total E-field vector may change in magnitude and direction. These findings show that realistic head geometries should be used when modeling the total E-field. In the third chapter, we addressed the importance of the secondary electric field (E-field) in a realistic head model using the boundary element method at clinically relevant coil positions and orientations (ex. primary motor cortex) during transcranial magnetic stimulation (TMS). The effective E-fields produced at each clinical orientation were then correlated with electromyographic (EMG) recordings using the total E-field with the cortical column cosine model. Some TMS coil orientations led to total E-fields as much as 40% lower than the primary E-fields at sites located on the TMS coil's main axis of stimulation. Effective E-field values at the cortical level, were highly correlated (r = 0.9644, P < 0.01) with EMG responses indicating that both local biological characteristics (such as tissue geometry and electrical conductivity) and the total E-field induced by the TMS coil may provide a means for predicting the optimum coil position/orientation to consistently produce neuronal activations.

ISBN: 9780549713586Subjects--Topical Terms:

1017681
Biophysics, Medical.

3-dimensional modeling of transcranial magnetic stimulation: Design and application.
LDR:04619nmm 2200361 a 45 001 867498
005 20100804
008 100804s2008 ||||||||||||||||| ||eng d
020 $a 9780549713586
035 $a (UMI)AAI3320139
035 $a AAI3320139
040 $a UMI $c UMI
100 1 $a Salinas, Felipe Santiago. $3 1036235
245 1 0 $a 3-dimensional modeling of transcranial magnetic stimulation: Design and application.
300 $a 195 p.
500 $a Adviser: Jack L. Lancaster.
500 $a Source: Dissertation Abstracts International, Volume: 69-07, Section: B, page: 4294.
502 $a Thesis (Ph.D.)--The University of Texas Health Science Center at San Antonio, 2008.
520 $a Over the past three decades, transcranial magnetic stimulation (TMS) has emerged as an effective tool for many research, diagnostic and therapeutic applications in humans. TMS delivers highly localized brain stimulations via non-invasive externally applied magnetic fields. This non-invasive, painless technique provides researchers and clinicians a unique tool capable of stimulating both the central and peripheral nervous systems. However, a complete analysis of the macroscopic electric fields produced by TMS has not yet been performed. In this dissertation, we present a thorough examination of the total electric field induced by TMS in air and a realistic head model with clinically relevant coil poses. In the first chapter, a detailed account of TMS coil wiring geometry was shown to provide significant improvements in the accuracy of primary E-field calculations. Three-dimensional models which accounted for the TMS coil's wire width, height, shape and number of turns clearly improved the fit of calculated-to-measured E-fields near the coil body. Detailed primary E-field models were accurate up to the surface of the coil body (within 0.5% of measured values) whereas simple models were often inadequate (up to 32% different from measured). In the second chapter, we addressed the importance of the secondary E-field created by surface charge accumulation during TMS using the boundary element method (BEM). 3-D models were developed using simple head geometries in order to test the model and compare it with measured values. The effects of tissue geometry, size and conductivity were also investigated. Finally, a realistic head model was used to assess the effect of multiple surfaces on the total E-field. We found that secondary E-fields have the greatest impact at areas in close proximity to each tissue layer. Throughout the head, the secondary E-field magnitudes were predominantly between 25% and 45% of the primary E-fields magnitude. The direction of the secondary E-field was primarily in opposition to the primary E-field, however there are some locations (i.e. going from high to low conductivity) where the secondary E-field adds to the primary E-field. Thus the total E-field vector may change in magnitude and direction. These findings show that realistic head geometries should be used when modeling the total E-field. In the third chapter, we addressed the importance of the secondary electric field (E-field) in a realistic head model using the boundary element method at clinically relevant coil positions and orientations (ex. primary motor cortex) during transcranial magnetic stimulation (TMS). The effective E-fields produced at each clinical orientation were then correlated with electromyographic (EMG) recordings using the total E-field with the cortical column cosine model. Some TMS coil orientations led to total E-fields as much as 40% lower than the primary E-fields at sites located on the TMS coil's main axis of stimulation. Effective E-field values at the cortical level, were highly correlated (r = 0.9644, P < 0.01) with EMG responses indicating that both local biological characteristics (such as tissue geometry and electrical conductivity) and the total E-field induced by the TMS coil may provide a means for predicting the optimum coil position/orientation to consistently produce neuronal activations.
590 $a School code: 0853.
650 4 $a Biophysics, Medical. $3 1017681
650 4 $a Engineering, Biomedical. $3 1017684
650 4 $a Physics, Electricity and Magnetism. $3 1019535
690 $a 0541
690 $a 0607
690 $a 0760
710 2 $a The University of Texas Health Science Center at San Antonio. $b Biomedical Engineering. $3 1036234
773 0 $t Dissertation Abstracts International $g 69-07B.
790 $a 0853
790 1 0 $a Fox, Peter T. $e committee member
790 1 0 $a George, John $e committee member
790 1 0 $a Lancaster, Jack L., $e advisor
790 1 0 $a Narayana, Shalini $e committee member
790 1 0 $a Roberson, Dawnlee $e committee member
790 1 0 $a Sardar, Dhiraj K. $e committee member
790 1 0 $a Senseman, David $e committee member
791 $a Ph.D.
792 $a 2008
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3320139