• 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