Abstract

Deep brain stimulation (DBS) has been proven to be an effective treatment modality for various late-stage neurological and psychiatric disorders. However, knowledge on the electrical field distribution in the brain tissue is still scarce. Most recent attempts to understand electric field spread were primarily focused on the effect of different electrodes on rather simple tissue models. The influence of microanatomic, biophysical tissue properties in particular has not been investigated in depth. Ethical concerns restrict thorough research on field distribution in human in vivo brain tissue. By means of a simplified model, we investigated the electric field distribution in a broader area of the subthalamic nucleus (STN). Pivotal biophysical parameters including conductivity, permittivity and permeability of brain tissue were incorporated in the model. A brain tissue model was created with the finite element method (FEM). Stimulation was mimicked with parameters used for monopolar stimulation of patients suffering from Parkinson’s disease. Our results were visualized with omnidirectional and segmented electrodes. The stimulated electric field was visualized with superimpositions on a stereotactic atlas (Morel). Owing to the effects of regional tissue properties near the stimulating electrode, marked field distortions occur. Such effects include, for example, isolating effects of heavily myelinated neighboring structures, e.g., the internal capsule. In particular, this may be illustrated through the analysis of a larger coronal area. While omnidirectional stimulation has been associated with vast current leakage, higher targeting precision was obtained with segmented electrodes. Finally, targeting was improved when the influence of microanatomic structures on the electric spread was considered. Our results confirm that lead design is not the sole influence on current spread. An omnidirectional lead configuration does not automatically result in an omnidirectional spread of current. In turn, segmented electrodes do not automatically imply an improved steering of current. Our findings may provide an explanation for side-effects secondary to current leakage. Furthermore, a possible explanation for divergent results in the comparison of the intraoperative awake patient and the postoperative setting is given. Due to the major influence of biophysical tissue properties on electric field shape, the local microanatomy should be considered for precise surgical targeting and optimal hardware implantation.

Highlights

  • Deep brain stimulation is an effective treatment modality for various neurological disorders (Lozano and Lipsman, 2013)

  • The model of the electric field distribution was superimposed on an axial slice from the stereotactic atlas of Morel (2007)

  • Paresthesia, disconjugate gaze and diplopia, conjugated deviation of gaze, light sensations, cognitive and emotional alterations and tonic muscle contractions can occur due to inadvertent co-stimulation (Montgomery, 2010)

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Summary

Introduction

Deep brain stimulation is an effective treatment modality for various neurological disorders (Lozano and Lipsman, 2013). Due to deficient knowledge on specific stimulationeffects, a good clinical outcome can only be obtained through a time-consuming adjustment of postoperative parameters (Ineichen et al, 2014) This adjustment is largely based on phenotypic observation of the patient. While a straightforward calculation of the electric field expansion is possible when based on stimulus intensity and frequency, a much greater challenge is presented by the incorporation of the biophysical properties of anisotropic anatomical tissue (e.g., McIntyre et al., Abbreviations: al, ansa lenticularis; ac, anterior commissure; bic, brachium of the inferior colliculus; Cd, caudate nucleus; CT, computer tomography; DBS, deep brain stimulation; DTI, diffusion tensor imaging; fct, fasciculus cerebellothalamicus; FEM, finite element method; fx, fornix; GPi and GPe, respectively, globus pallidus internus and externus; Hyp, hypothalamus; ic, internal capsule; MRI, magnetic resonance imaging; mtt, mammillothalamic tract; MGN and LGN, respectively, medial and lateral geniculate nucleus; ml, medial lemniscus; Acb, nucleus accumbens; PDEs, partial differential equations; PAG, periaqueductal (or central) gray; pc, posterior commissure; Pul, pulvinar; Put, putamen; R, reticular thalamic nucleus; RN, red nucleus; STh or STN, subthalamic nucleus

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