Adaptive Estimation of the Neural Activation Extent in Computational Volume Conductor Models of Deep Brain Stimulation

Abstract

Abstract-Objective: The aim of this study is to propose an adaptive scheme embedded into an open-source environment for the estimation of the neural activation extent during deep brain stimulation and to investigate the feasibility of approximating the neural activation extent by thresholds of the field solution. Methods: Open-source solutions for solving the field equation in volume conductor models of deep brain stimulation and computing the neural activation are embedded into a Python package to estimate the neural activation dependent on the dielectric tissue properties and axon parameters by employing a spatially adaptive scheme. Feasibility of the approximation of the neural activation extent by field thresholds is investigated to further reduce the computational expense. Results: The varying extents of neural activation for different patient-specific dielectric properties were estimated with the adaptive scheme. The results revealed the strong influence of the dielectric properties of the encapsulation layer in the acute and chronic phase after surgery. The computational time required to determine the neural activation extent in each studied model case was substantially reduced. Conclusion: The neural activation extent is altered by patientspecific parameters. Threshold values of the electric potential and electric field norm facilitate a computationally efficient method to estimate the neural activation extent. Significance: The presented adaptive scheme is able to robustly determine neural activation extents and field threshold estimates for varying dielectric tissue properties and axon diameters while reducing substantially the computational expense. , from which electrical stimulation of the sensorimotor zone is mostly associated with the relief of motor symptoms of PD [4]. Due to patient-specific parameters, such as brain structure anatomy, dielectric tissue properties, electrode location, and severity of symptoms, the adjustment and optimization of stimulation parameters during and after surgery can be rather time consuming and connected Manuscript submitted to IEEE TBME on April, 26 2017. Asterisk indicates corresponding author.* C. Schmidt is with the Institute of General Electrical Engineering, University of Rostock, 18059 Rostock, Germany (e-mail: cschmidt18057@gmail.com) U. van Rienen is with the Institute of General Electrical Engineering, University of Rostock, 18059 Rostock, Germany to additional costs. Computational models provide a possibility to estimate the stimulation impact by determining activated areas in the deep brain based on the given patient-specific parameters. The extent of neural activation, or the volume of tissue activated (VTA), is a common computational modeling approach to estimate the size of the activated tissue during DBS and has been applied in various computational studies in this area including homogeneous [5], rotationally symmetric [6], heterogeneous [7], [8], and anisotropic volume conductor models [9] of the human brain and deep brain target areas. In general, ...

Endovascular deep brain stimulation: Investigating the relationship between vascular structures and deep brain stimulation targets

“…2). However, owing to the non-linear thresholddistance relationship, which dictates the recruitment of neuronal tissue as a function of distance from a constant stimulation source [23,24], only six DBS targets were deemed close enough to a vessel for endovascular DBS to be potentially feasible: medial forebrain bundle (mfb), nucleus accumbens (NA), dentatorubrothalamic tract (drt), fornix (fx), pedunculopontine nucleus (PPN), and subcallosal cingulate cortex (SCC) (Fig. 3).…”

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

“…The activation arises from the membrane polarization driven by the extracellular electric field. In [7], authors have created Python libraries for axons with different fiber diameters and prepared routines for computations in the NEURON environment [12], in which the axon model is defined. These scripts were adopted for the use in OSS-DBS.…”

“…Various simulation tools for DBS have already been developed [7,[27][28][29], but to the best of our knowledge, either the computational model was comparatively simplified, or the design was conducted manually with a low feasibility of optimization, or commercial software was employed. Our work has a structural resemblance with [7], from which the workflow was partially adapted. In contrast to [7], the workflow is automated in the platform, significantly reducing the prototyping effort.…”

“…Our work has a structural resemblance with [7], from which the workflow was partially adapted. In contrast to [7], the workflow is automated in the platform, significantly reducing the prototyping effort. For the same reason, an adaptive mesh refinement algorithm was introduced.…”

“…The platform was primarily developed for use among experimental researchers, and thus requires only a relatively simple presetting of input parameters via a graphical user interface. This work originates from [7], where an open-source workflow for electric field calculation was described. However, in that paper the authors' primary aim was to evaluate neural activation extent and field thresholds.…”