Literature DB >> 25029124

Evaluation of high-perimeter electrode designs for deep brain stimulation.

Bryan Howell1, Warren M Grill.   

Abstract

OBJECTIVE: Deep brain stimulation (DBS) is an effective treatment for movement disorders and a promising therapy for treating epilepsy and psychiatric disorders. Despite its clinical success, complications including infections and mis-programing following surgical replacement of the battery-powered implantable pulse generator adversely impact the safety profile of this therapy. We sought to decrease power consumption and extend battery life by modifying the electrode geometry to increase stimulation efficiency. The specific goal of this study was to determine whether electrode contact perimeter or area had a greater effect on increasing stimulation efficiency. APPROACH: Finite-element method (FEM) models of eight prototype electrode designs were used to calculate the electrode access resistance, and the FEM models were coupled with cable models of passing axons to quantify stimulation efficiency. We also measured in vitro the electrical properties of the prototype electrode designs and measured in vivo the stimulation efficiency following acute implantation in anesthetized cats. MAIN
RESULTS: Area had a greater effect than perimeter on altering the electrode access resistance; electrode (access or dynamic) resistance alone did not predict stimulation efficiency because efficiency was dependent on the shape of the potential distribution in the tissue; and, quantitative assessment of stimulation efficiency required consideration of the effects of the electrode-tissue interface impedance. SIGNIFICANCE: These results advance understanding of the features of electrode geometry that are important for designing the next generation of efficient DBS electrodes.

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Year:  2014        PMID: 25029124      PMCID: PMC4198383          DOI: 10.1088/1741-2560/11/4/046026

Source DB:  PubMed          Journal:  J Neural Eng        ISSN: 1741-2552            Impact factor:   5.379


  36 in total

Review 1.  Selection of stimulus parameters for deep brain stimulation.

Authors:  Alexis M Kuncel; Warren M Grill
Journal:  Clin Neurophysiol       Date:  2004-11       Impact factor: 3.708

2.  Patient-specific analysis of the volume of tissue activated during deep brain stimulation.

Authors:  Christopher R Butson; Scott E Cooper; Jaimie M Henderson; Cameron C McIntyre
Journal:  Neuroimage       Date:  2006-11-17       Impact factor: 6.556

3.  Deep brain stimulation for treatment-resistant depression.

Authors:  Helen S Mayberg; Andres M Lozano; Valerie Voon; Heather E McNeely; David Seminowicz; Clement Hamani; Jason M Schwalb; Sidney H Kennedy
Journal:  Neuron       Date:  2005-03-03       Impact factor: 17.173

Review 4.  Deep brain stimulation reduces symptoms of Parkinson disease.

Authors:  E B Montgomery
Journal:  Cleve Clin J Med       Date:  1999-01       Impact factor: 2.321

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.  Specific impedance of cerebral white matter.

Authors:  P W Nicholson
Journal:  Exp Neurol       Date:  1965-12       Impact factor: 5.330

7.  Management of referred deep brain stimulation failures: a retrospective analysis from 2 movement disorders centers.

Authors:  Michael S Okun; Michele Tagliati; Michael Pourfar; Hubert H Fernandez; Ramon L Rodriguez; Ron L Alterman; Kelly D Foote
Journal:  Arch Neurol       Date:  2005-06-13

8.  Three-dimensional somatotopic organization and probabilistic mapping of motor responses from the human internal capsule.

Authors:  Emma G Duerden; Kirk W Finnis; Terry M Peters; Abbas F Sadikot
Journal:  J Neurosurg       Date:  2011-03-04       Impact factor: 5.115

Review 9.  Deep brain stimulation for psychiatric disorders.

Authors:  Jens Kuhn; Theo O J Gründler; Doris Lenartz; Volker Sturm; Joachim Klosterkötter; Wolfgang Huff
Journal:  Dtsch Arztebl Int       Date:  2010-02-19       Impact factor: 5.594

10.  Patient perspectives on the efficacy and ergonomics of rechargeable spinal cord stimulators.

Authors:  Carson K Lam; Joshua M Rosenow
Journal:  Neuromodulation       Date:  2010-02-24
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  12 in total

1.  Design and in vivo evaluation of more efficient and selective deep brain stimulation electrodes.

Authors:  Bryan Howell; Brian Huynh; Warren M Grill
Journal:  J Neural Eng       Date:  2015-07-14       Impact factor: 5.379

2.  Selective Mapping of Deep Brain Stimulation Lead Currents Using Acoustoelectric Imaging.

Authors:  Chet Preston; Willard S Kasoff; Russell S Witte
Journal:  Ultrasound Med Biol       Date:  2018-08-14       Impact factor: 2.998

3.  Orientation selective deep brain stimulation.

Authors:  Lauri J Lehto; Julia P Slopsema; Matthew D Johnson; Artem Shatillo; Benjamin A Teplitzky; Lynn Utecht; Gregor Adriany; Silvia Mangia; Alejandra Sierra; Walter C Low; Olli Gröhn; Shalom Michaeli
Journal:  J Neural Eng       Date:  2017-01-09       Impact factor: 5.379

4.  Clinical deep brain stimulation strategies for orientation-selective pathway activation.

Authors:  Julia P Slopsema; Edgar Peña; Remi Patriat; Lauri J Lehto; Olli Gröhn; Silvia Mangia; Noam Harel; Shalom Michaeli; Matthew D Johnson
Journal:  J Neural Eng       Date:  2018-08-10       Impact factor: 5.379

Review 5.  Systems approaches to optimizing deep brain stimulation therapies in Parkinson's disease.

Authors:  Sabato Santaniello; John T Gale; Sridevi V Sarma
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2018-03-20

6.  Visualization of electrical field of electrode using voltage-controlled fluorescence release.

Authors:  Wenyan Jia; Jiamin Wu; Di Gao; Hao Wang; Mingui Sun
Journal:  Comput Biol Med       Date:  2016-05-16       Impact factor: 4.589

Review 7.  Model-based analysis and design of waveforms for efficient neural stimulation.

Authors:  Warren M Grill
Journal:  Prog Brain Res       Date:  2015-09-04       Impact factor: 2.453

8.  Electrochemical Evaluations of Fractal Microelectrodes for Energy Efficient Neurostimulation.

Authors:  Hyunsu Park; Pavel Takmakov; Hyowon Lee
Journal:  Sci Rep       Date:  2018-03-12       Impact factor: 4.379

9.  Model-Based Comparison of Deep Brain Stimulation Array Functionality with Varying Number of Radial Electrodes and Machine Learning Feature Sets.

Authors:  Benjamin A Teplitzky; Laura M Zitella; YiZi Xiao; Matthew D Johnson
Journal:  Front Comput Neurosci       Date:  2016-06-10       Impact factor: 2.380

10.  Model-Based Analysis of Electrode Placement and Pulse Amplitude for Hippocampal Stimulation.

Authors:  Clayton S Bingham; Kyle Loizos; Gene J Yu; Andrew Gilbert; Jean-Marie C Bouteiller; Dong Song; Gianluca Lazzi; Theodore W Berger
Journal:  IEEE Trans Biomed Eng       Date:  2018-01-25       Impact factor: 4.538

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