CUED Publications database

FastField: An open-source toolbox for efficient approximation of deep brain stimulation electric fields.

Baniasadi, M and Proverbio, D and Gonçalves, J and Hertel, F and Husch, A (2020) FastField: An open-source toolbox for efficient approximation of deep brain stimulation electric fields. Neuroimage, 223. 117330-.

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Abstract

Deep brain stimulation (DBS) is a surgical therapy to alleviate symptoms of certain brain disorders by electrically modulating neural tissues. Computational models predicting electric fields and volumes of tissue activated are key for efficient parameter tuning and network analysis. Currently, we lack efficient and flexible software implementations supporting complex electrode geometries and stimulation settings. Available tools are either too slow (e.g. finite element method-FEM), or too simple, with limited applicability to basic use-cases. This paper introduces FastField, an efficient open-source toolbox for DBS electric field and VTA approximations. It computes scalable electric field approximations based on the principle of superposition, and VTA activation models from pulse width and axon diameter. In benchmarks and case studies, FastField is solved in about 0.2 s, ~ 1000 times faster than using FEM. Moreover, it is almost as accurate as using FEM: average Dice overlap of 92%, which is around typical noise levels found in clinical data. Hence, FastField has the potential to foster efficient optimization studies and to support clinical applications.

Item Type: Article
Uncontrolled Keywords: Deep brain stimulation Electric field Neuromodulation Simulation Toolbox volume of tissue activated Axons Brain Deep Brain Stimulation Electrodes, Implanted Electromagnetic Phenomena Electrophysiological Phenomena Humans Models, Neurological Software
Subjects: UNSPECIFIED
Divisions: Div F > Control
Depositing User: Unnamed user with email sms67@cam.ac.uk
Date Deposited: 01 Sep 2021 20:36
Last Modified: 09 Sep 2021 02:04
DOI: 10.1016/j.neuroimage.2020.117330