DocumentCode :
1765116
Title :
Influence of Uncertainties in the Material Properties of Brain Tissue on the Probabilistic Volume of Tissue Activated
Author :
Schmidt, Christoph ; Grant, P. ; Lowery, M. ; van Rienen, Ursula
Author_Institution :
Inst. of Gen. Electr. Eng., Univ. of Rostock, Rostock, Germany
Volume :
60
Issue :
5
fYear :
2013
fDate :
41395
Firstpage :
1378
Lastpage :
1387
Abstract :
The aim of this study was to examine the influence of uncertainty of the material properties of brain tissue on the probabilistic voltage response and the probabilistic volume of tissue activated (VTA) in a volume conductor model of deep brain stimulation. To quantify the uncertainties of the desired quantities without changing the deterministic model, a nonintrusive projection method was used by approximating these quantities by a polynomial expansion on a multidimensional basis known as polynomial chaos. The coefficients of this expansion were computed with a multidimensional quadrature on sparse Smolyak grids. The deterministic model combines a finite element model based on a digital brain atlas and a multicompartmental model of mammalian nerve fibers. The material properties of brain tissue were modeled as uniform random parameters using data from several experimental studies. Different magnitudes of uncertainty in the material properties were computed to allow predictions on the resulting uncertainties in the desired quantities. The results showed a major contribution of the uncertainties in the electrical conductivity values of brain tissue on the voltage response as well as on the predicted VTA, while the influence of the uncertainties in the relative permittivity was negligible.
Keywords :
bioelectric potentials; biological tissues; brain models; chaos; finite element analysis; integration; materials properties; neurophysiology; polynomials; probability; brain tissue electrical conductivity values; brain tissue material property uncertainty influence; brain tissue relative permittivity; deep brain stimulation; deterministic model; digital brain atlas; finite element model; mammalian nerve fiber multicompartmental model; multidimensional quadrature; nonintrusive projection method; polynomial chaos; polynomial expansion; polynomial multidimensional basis; probabilistic VTA; probabilistic voltage response; sparse Smolyak grids; volume conductor model; volume of tissue activated; Computational modeling; Conductivity; Electrodes; Permittivity; Satellite broadcasting; Uncertainty; Voltage control; Deep brain stimulation (DBS); finite element methods (FEMs); neural response; sensitivity analysis; Brain; Deep Brain Stimulation; Electric Conductivity; Finite Element Analysis; Humans; Magnetic Resonance Imaging; Models, Neurological; Models, Statistical; Sensitivity and Specificity; Signal Processing, Computer-Assisted;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/TBME.2012.2235835
Filename :
6392218
Link To Document :
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