Literature DB >> 32628719

OSS-DBS: Open-source simulation platform for deep brain stimulation with a comprehensive automated modeling.

Konstantin Butenko1, Christian Bahls1, Max Schröder2, Rüdiger Köhling3,4, Ursula van Rienen1,5.   

Abstract

In this study, we propose a new open-source simulation platform that comprises computer-aided design and computer-aided engineering tools for highly automated evaluation of electric field distribution and neural activation during Deep Brain Stimulation (DBS). It will be shown how a Volume Conductor Model (VCM) is constructed and examined using Python-controlled algorithms for generation, discretization and adaptive mesh refinement of the computational domain, as well as for incorporation of heterogeneous and anisotropic properties of the tissue and allocation of neuron models. The utilization of the platform is facilitated by a collection of predefined input setups and quick visualization routines. The accuracy of a VCM, created and optimized by the platform, was estimated by comparison with a commercial software. The results demonstrate no significant deviation between the models in the electric potential distribution. A qualitative estimation of different physics for the VCM shows an agreement with previous computational studies. The proposed computational platform is suitable for an accurate estimation of electric fields during DBS in scientific modeling studies. In future, we intend to acquire SDA and EMA approval. Successful incorporation of open-source software, controlled by in-house developed algorithms, provides a highly automated solution. The platform allows for optimization and uncertainty quantification (UQ) studies, while employment of the open-source software facilitates accessibility and reproducibility of simulations.

Entities:  

Year:  2020        PMID: 32628719     DOI: 10.1371/journal.pcbi.1008023

Source DB:  PubMed          Journal:  PLoS Comput Biol        ISSN: 1553-734X            Impact factor:   4.475


  5 in total

1.  Lead-OR: A multimodal platform for deep brain stimulation surgery.

Authors:  Simón Oxenford; Jan Roediger; Clemens Neudorfer; Luka Milosevic; Christopher Güttler; Philipp Spindler; Peter Vajkoczy; Wolf-Julian Neumann; Andrea Kühn; Andreas Horn
Journal:  Elife       Date:  2022-05-20       Impact factor: 8.713

Review 2.  Deep Brain Stimulation: Emerging Tools for Simulation, Data Analysis, and Visualization.

Authors:  Karin Wårdell; Teresa Nordin; Dorian Vogel; Peter Zsigmond; Carl-Fredrik Westin; Marwan Hariz; Simone Hemm
Journal:  Front Neurosci       Date:  2022-04-11       Impact factor: 5.152

3.  Numerical Study on Electrode Design for Rodent Deep Brain Stimulation With Implantations Cranial to Targeted Nuclei.

Authors:  Konstantin Butenko; Rüdiger Köhling; Ursula van Rienen
Journal:  Front Comput Neurosci       Date:  2021-02-02       Impact factor: 2.380

4.  Optimal deep brain stimulation sites and networks for cervical vs. generalized dystonia.

Authors:  Andreas Horn; Martin M Reich; Siobhan Ewert; Ningfei Li; Bassam Al-Fatly; Florian Lange; Jonas Roothans; Simon Oxenford; Isabel Horn; Steffen Paschen; Joachim Runge; Fritz Wodarg; Karsten Witt; Robert C Nickl; Matthias Wittstock; Gerd-Helge Schneider; Philipp Mahlknecht; Werner Poewe; Wilhelm Eisner; Ann-Kristin Helmers; Cordula Matthies; Joachim K Krauss; Günther Deuschl; Jens Volkmann; Andrea A Kühn
Journal:  Proc Natl Acad Sci U S A       Date:  2022-03-31       Impact factor: 12.779

5.  Using a Digital Twin of an Electrical Stimulation Device to Monitor and Control the Electrical Stimulation of Cells in vitro.

Authors:  Julius Zimmermann; Kai Budde; Nils Arbeiter; Francia Molina; Alexander Storch; Adelinde M Uhrmacher; Ursula van Rienen
Journal:  Front Bioeng Biotechnol       Date:  2021-12-08
  5 in total

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