Literature DB >> 33740780

Impact of brain shift on neural pathways in deep brain stimulation: a preliminary analysis via multi-physics finite element models.

Ma Luo1,2, Saramati Narasimhan2,3, Paul S Larson4, Alastair J Martin5, Peter E Konrad6, Michael I Miga1,2,3.   

Abstract

Objective.The effectiveness of deep brain stimulation (DBS) depends on electrode placement accuracy, which can be compromised by brain shift during surgery. While there have been efforts in assessing the impact of electrode misplacement due to brain shift using preop- and postop-imaging data, such analysis using preop- and intraop-imaging data via biophysical modeling has not been conducted. This work presents a preliminary study that applies a multi-physics analysis framework using finite element biomechanical and bioelectric models to examine the impact of realistic intraoperative shift on neural pathways determined by tractography.Approach.The study examined six patients who had undergone interventional magnetic resonance-guided DBS surgery. The modeling framework utilized a biomechanical approach to update preoperative MR to reflect shift-induced anatomical changes. Using this anatomically deformed image and its undeformed counterpart, bioelectric effects from shifting electrode leads could be simulated and neural activation differences were approximated. Specifically, for each configuration, volume of tissue activation was computed and subsequently used for tractography estimation. Total tract volume and overlapping volume with motor regions as well as connectivity profile were compared. In addition, volumetric overlap between different fiber bundles among configurations was computed and correlated to estimated shift.Main results.The study found deformation-induced differences in tract volume, motor region overlap, and connectivity behavior, suggesting the impact of shift. There is a strong correlation (R= -0.83) between shift from intended target and intended neural pathway recruitment, where at threshold of ∼2.94 mm, intended recruitment completely degrades. The determined threshold is consistent with and provides quantitative support to prior observations and literature that deviations of 2-3 mm are detrimental.Significance.The findings support and advance prior studies and understanding to illustrate the need to account for shift in DBS and the potentiality of computational modeling for estimating influence of shift on neural activation.
© 2021 IOP Publishing Ltd.

Entities:  

Keywords:  brain shift; computational modeling; deep brain stimulation; neurosurgery; tractography

Mesh:

Year:  2021        PMID: 33740780      PMCID: PMC9476060          DOI: 10.1088/1741-2552/abf066

Source DB:  PubMed          Journal:  J Neural Eng        ISSN: 1741-2552            Impact factor:   5.043


  52 in total

1.  Conductivity tensor mapping of the human brain using diffusion tensor MRI.

Authors:  D S Tuch; V J Wedeen; A M Dale; J S George; J W Belliveau
Journal:  Proc Natl Acad Sci U S A       Date:  2001-09-25       Impact factor: 11.205

Review 2.  Advances in functional and structural MR image analysis and implementation as FSL.

Authors:  Stephen M Smith; Mark Jenkinson; Mark W Woolrich; Christian F Beckmann; Timothy E J Behrens; Heidi Johansen-Berg; Peter R Bannister; Marilena De Luca; Ivana Drobnjak; David E Flitney; Rami K Niazy; James Saunders; John Vickers; Yongyue Zhang; Nicola De Stefano; J Michael Brady; Paul M Matthews
Journal:  Neuroimage       Date:  2004       Impact factor: 6.556

3.  An atlas-based method to compensate for brain shift: preliminary results.

Authors:  Prashanth Dumpuri; Reid C Thompson; Benoit M Dawant; A Cao; Michael I Miga
Journal:  Med Image Anal       Date:  2007-03-01       Impact factor: 8.545

Review 4.  Deep brain stimulation for movement disorders.

Authors:  Kelly L Collins; Emily M Lehmann; Parag G Patil
Journal:  Neurobiol Dis       Date:  2009-12-05       Impact factor: 5.996

5.  An unexpectedly high rate of revisions and removals in deep brain stimulation surgery: Analysis of multiple databases.

Authors:  John D Rolston; Dario J Englot; Philip A Starr; Paul S Larson
Journal:  Parkinsonism Relat Disord       Date:  2016-09-12       Impact factor: 4.891

6.  Retrospective study comparing model-based deformation correction to intraoperative magnetic resonance imaging for image-guided neurosurgery.

Authors:  Ma Luo; Sarah F Frisken; Jared A Weis; Logan W Clements; Prashin Unadkat; Reid C Thompson; Alexandra J Golby; Michael I Miga
Journal:  J Med Imaging (Bellingham)       Date:  2017-09-13

7.  Patient-specific models of deep brain stimulation: influence of field model complexity on neural activation predictions.

Authors:  Ashutosh Chaturvedi; Christopher R Butson; Scott F Lempka; Scott E Cooper; Cameron C McIntyre
Journal:  Brain Stimul       Date:  2010-04       Impact factor: 8.955

8.  Accounting for Deformation in Deep Brain Stimulation Surgery With Models: Comparison to Interventional Magnetic Resonance Imaging.

Authors:  Ma Luo; Paul S Larson; Alastair J Martin; Michael I Miga
Journal:  IEEE Trans Biomed Eng       Date:  2020-02-14       Impact factor: 4.756

9.  Electric Field Comparison between Microelectrode Recording and Deep Brain Stimulation Systems-A Simulation Study.

Authors:  Fabiola Alonso; Dorian Vogel; Johannes Johansson; Karin Wårdell; Simone Hemm
Journal:  Brain Sci       Date:  2018-02-06

10.  The minimal preprocessing pipelines for the Human Connectome Project.

Authors:  Matthew F Glasser; Stamatios N Sotiropoulos; J Anthony Wilson; Timothy S Coalson; Bruce Fischl; Jesper L Andersson; Junqian Xu; Saad Jbabdi; Matthew Webster; Jonathan R Polimeni; David C Van Essen; Mark Jenkinson
Journal:  Neuroimage       Date:  2013-05-11       Impact factor: 6.556

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  1 in total

1.  Automatic framework for patient-specific modelling of tumour resection-induced brain shift.

Authors:  Yue Yu; Saima Safdar; George Bourantas; Benjamin Zwick; Grand Joldes; Tina Kapur; Sarah Frisken; Ron Kikinis; Arya Nabavi; Alexandra Golby; Adam Wittek; Karol Miller
Journal:  Comput Biol Med       Date:  2022-01-30       Impact factor: 6.698

  1 in total

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