Literature DB >> 23269746

Influence of uncertainties in the material properties of brain tissue on the probabilistic volume of tissue activated.

Christian Schmidt1, Peadar Grant, Madeleine Lowery, Ursula van Rienen.   

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.

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Year:  2012        PMID: 23269746     DOI: 10.1109/TBME.2012.2235835

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  18 in total

1.  Assessing the Electromagnetic Fields Generated By a Radiofrequency MRI Body Coil at 64 MHz: Defeaturing Versus Accuracy.

Authors:  Elena Lucano; Micaela Liberti; Gonzalo G Mendoza; Tom Lloyd; Maria Ida Iacono; Francesca Apollonio; Steve Wedan; Wolfgang Kainz; Leonardo M Angelone
Journal:  IEEE Trans Biomed Eng       Date:  2015-12-17       Impact factor: 4.538

2.  Impact of uncertain head tissue conductivity in the optimization of transcranial direct current stimulation for an auditory target.

Authors:  Christian Schmidt; Sven Wagner; Martin Burger; Ursula van Rienen; Carsten H Wolters
Journal:  J Neural Eng       Date:  2015-07-14       Impact factor: 5.379

3.  A retrospective evaluation of automated optimization of deep brain stimulation parameters.

Authors:  Johannes Vorwerk; Andrea A Brock; Daria N Anderson; John D Rolston; Christopher R Butson
Journal:  J Neural Eng       Date:  2019-11-06       Impact factor: 5.379

4.  High-definition transcranial direct current stimulation induces both acute and persistent changes in broadband cortical synchronization: a simultaneous tDCS-EEG study.

Authors:  Abhrajeet Roy; Bryan Baxter; Bin He
Journal:  IEEE Trans Biomed Eng       Date:  2014-07       Impact factor: 4.538

5.  Influences of interpolation error, electrode geometry, and the electrode-tissue interface on models of electric fields produced by deep brain stimulation.

Authors:  Bryan Howell; Sagar Naik; Warren M Grill
Journal:  IEEE Trans Biomed Eng       Date:  2014-02       Impact factor: 4.538

6.  A statistical framework for quantification and visualisation of positional uncertainty in deep brain stimulation electrodes.

Authors:  Tushar M Athawale; Kara A Johnson; Christopher R Butson; Chris R Johnson
Journal:  Comput Methods Biomech Biomed Eng Imaging Vis       Date:  2018-10-09

Review 7.  Neuroimaging Technological Advancements for Targeting in Functional Neurosurgery.

Authors:  Alexandre Boutet; Robert Gramer; Christopher J Steele; Gavin J B Elias; Jürgen Germann; Ricardo Maciel; Walter Kucharczyk; Ludvic Zrinzo; Andres M Lozano; Alfonso Fasano
Journal:  Curr Neurol Neurosci Rep       Date:  2019-05-30       Impact factor: 5.081

8.  Analyzing the tradeoff between electrical complexity and accuracy in patient-specific computational models of deep brain stimulation.

Authors:  Bryan Howell; Cameron C McIntyre
Journal:  J Neural Eng       Date:  2016-05-11       Impact factor: 5.379

9.  Lead-DBS v2: Towards a comprehensive pipeline for deep brain stimulation imaging.

Authors:  Andreas Horn; Ningfei Li; Till A Dembek; Ari Kappel; Chadwick Boulay; Siobhan Ewert; Anna Tietze; Andreas Husch; Thushara Perera; Wolf-Julian Neumann; Marco Reisert; Hang Si; Robert Oostenveld; Christopher Rorden; Fang-Cheng Yeh; Qianqian Fang; Todd M Herrington; Johannes Vorwerk; Andrea A Kühn
Journal:  Neuroimage       Date:  2018-09-01       Impact factor: 6.556

10.  Deep brain stimulation in Parkinson's disease: motor effects relative to the MRI-defined STN.

Authors:  Juergen Ralf Schlaier; Christine Hanson; Annette Janzen; Claudia Fellner; Andreas Hochreiter; Martin Proescholdt; Alexander Brawanski; Max Lange
Journal:  Neurosurg Rev       Date:  2014-02-28       Impact factor: 3.042

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