Deep brain stimulation in movement disorders: stereotactic coregistration of two-dimensional electrical field modeling and magnetic resonance imaging

Modeling the volume of tissue activated in deep brain stimulation and its clinical influence: a review

Deep brain stimulation (DBS) is a neuromodulatory therapy that has been FDA approved for the treatment of various disorders, including but not limited to, movement disorders (e.g., Parkinson's disease and essential tremor), epilepsy, and obsessive-compulsive disorder. Computational methods for estimating the volume of tissue activated (VTA), coupled with brain imaging techniques, form the basis of models that are being generated from retrospective clinical studies for predicting DBS patient outcomes. For instance, VTA models are used to generate target-and network-based probabilistic stimulation maps that play a crucial role in predicting DBS treatment outcomes. This review defines the methods for calculation of tissue activation (or modulation) including ones that use heuristic and clinically derived estimates and more computationally involved ones that rely on finite-element methods and biophysical axon models. We define model parameters and provide a comparison of commercial, open-source, and academic simulation platforms available for integrated neuroimaging and neural activation prediction. In addition, we review clinical studies that use these modeling methods as a function of disease. By describing the tissue-activation modeling methods and highlighting their application in clinical studies, we provide the neural engineering and clinical neuromodulation communities with perspectives that may influence the adoption of modeling methods for future DBS studies.

Characterization and closed-loop control of infrared thalamocortical stimulation produces spatially constrained single-unit responses

Deep brain stimulation (DBS) is a powerful tool for the treatment of circuitopathy-related neurological and psychiatric diseases and disorders such as Parkinson's disease and obsessive-compulsive disorder, as well as a critical research tool for perturbing neural circuits and exploring neuroprostheses. Electrically mediated DBS, however, is limited by the spread of stimulus currents into tissue unrelated to disease course and treatment, potentially causing undesirable patient side effects. In this work, we utilize infrared neural stimulation (INS), an optical neuromodulation technique that uses near to midinfrared light to drive graded excitatory and inhibitory responses in nerves and neurons, to facilitate an optical and spatially constrained DBS paradigm. INS has been shown to provide spatially constrained responses in cortical neurons and, unlike other optical techniques, does not require genetic modification of the neural target. We show that INS produces graded, biophysically relevant single-unit responses with robust information transfer in rat thalamocortical circuits. Importantly, we show that cortical spread of activation from thalamic INS produces more spatially constrained response profiles than conventional electrical stimulation. Owing to observed spatial precision of INS, we used deep reinforcement learning (RL) for closed-loop control of thalamocortical circuits, creating real-time representations of stimulus-response dynamics while driving cortical neurons to precise firing patterns. Our data suggest that INS can serve as a targeted and dynamic stimulation paradigm for both open and closed-loop DBS.

Spatially specific, closed-loop infrared thalamocortical deep brain stimulation

Deep brain stimulation (DBS) is a powerful tool for the treatment of circuitopathy-related neurological and psychiatric diseases and disorders such as Parkinson's disease and obsessive-compulsive disorder, as well as a critical research tool for perturbing neural circuits and exploring neuroprostheses. Electrically-mediated DBS, however, is limited by the spread of stimulus currents into tissue unrelated to disease course and treatment, potentially causing undesirable patient side effects. In this work, we utilize infrared neural stimulation (INS), an optical neuromodulation technique that uses near to mid-infrared light to drive graded excitatory and inhibitory responses in nerves and neurons, to facilitate an optical and spatially constrained DBS paradigm. INS has been shown to provide spatially constrained responses in cortical neurons and, unlike other optical techniques, does not require genetic modification of the neural target. We show that INS produces graded, biophysically relevant single-unit responses with robust information transfer in thalamocortical circuits. Importantly, we show that cortical spread of activation from thalamic INS produces more spatially constrained response profiles than conventional electrical stimulation. Owing to observed spatial precision of INS, we used deep reinforcement learning for closed-loop control of thalamocortical circuits, creating real-time representations of stimulus-response dynamics while driving cortical neurons to precise firing patterns. Our data suggest that INS can serve as a targeted and dynamic stimulation paradigm for both open and closed-loop DBS.

EEG-based biomarkers for optimizing deep brain stimulation contact configuration in Parkinson's disease

Objective

Subthalamic deep brain stimulation (STN-DBS) is a neurosurgical therapy to treat Parkinson's disease (PD). Optimal therapeutic outcomes are not achieved in all patients due to increased DBS technological complexity; programming time constraints; and delayed clinical response of some symptoms. To streamline the programming process, biomarkers could be used to accurately predict the most effective stimulation configuration. Therefore, we investigated if DBS-evoked potentials (EPs) combined with imaging to perform prediction analyses could predict the best contact configuration.

Methods

In 10 patients, EPs were recorded in response to stimulation at 10 Hz for 50 s on each DBS-contact. In two patients, we recorded from both hemispheres, resulting in recordings from a total of 12 hemispheres. A monopolar review was performed by stimulating on each contact and measuring the therapeutic window. CT and MRI data were collected. Prediction models were created to assess how well the EPs and imaging could predict the best contact configuration.

Results

EPs at 3 ms and at 10 ms were recorded. The prediction models showed that EPs can be combined with imaging data to predict the best contact configuration and hence, significantly outperformed random contact selection during a monopolar review.

Conclusion

EPs can predict the best contact configuration. Ultimately, these prediction tools could be implemented into daily practice to ease the DBS programming of PD patients.

Towards biomarker-based optimization of deep brain stimulation in Parkinson's disease patients

Background

Subthalamic deep brain stimulation (DBS) is an established therapy to treat Parkinson's disease (PD). To maximize therapeutic outcome, optimal DBS settings must be carefully selected for each patient. Unfortunately, this is not always achieved because of: (1) increased technological complexity of DBS devices, (2) time restraints, or lack of expertise, and (3) delayed therapeutic response of some symptoms. Biomarkers to accurately predict the most effective stimulation settings for each patient could streamline this process and improve DBS outcomes.

Objective

To investigate the use of evoked potentials (EPs) to predict clinical outcomes in PD patients with DBS.

Methods

In ten patients (12 hemispheres), a monopolar review was performed by systematically stimulating on each DBS contact and measuring the therapeutic window. Standard imaging data were collected. EEG-based EPs were then recorded in response to stimulation at 10 Hz for 50 s on each DBS-contact. Linear mixed models were used to assess how well both EPs and image-derived information predicted the clinical data.

Results

Evoked potential peaks at 3 ms (P3) and at 10 ms (P10) were observed in nine and eleven hemispheres, respectively. Clinical data were well predicted using either P3 or P10. A separate model showed that the image-derived information also predicted clinical data with similar accuracy. Combining both EPs and image-derived information in one model yielded the highest predictive value.

Conclusion

Evoked potentials can accurately predict clinical DBS responses. Combining EPs with imaging data further improves this prediction. Future refinement of this approach may streamline DBS programming, thereby improving therapeutic outcomes.

Clinical trial registration

ClinicalTrials.gov, identifier NCT04658641.

Neurocapillary-Modulation

OBJECTIVES

We consider two consequences of brain capillary ultrastructure in neuromodulation. First, blood-brain barrier (BBB) polarization as a consequence of current crossing between interstitial space and the blood. Second, interstitial current flow distortion around capillaries impacting neuronal stimulation.

MATERIALS AND METHODS

We developed computational models of BBB ultrastructure morphologies to first assess electric field amplification at the BBB (principle 1) and neuron polarization amplification by the presence of capillaries (principle 2). We adapt neuron cable theory to develop an analytical solution for maximum BBB polarization sensitivity.

RESULTS

Electrical current crosses between the brain parenchyma (interstitial space) and capillaries, producing BBB electric fields (EBBB) that are >400x of the average parenchyma electric field (ĒBRAIN), which in turn modulates transport across the BBB. Specifically, for a BBB space constant (λBBB) and wall thickness (dth-BBB), the analytical solution for maximal BBB electric field (EABBB) is given as: (ĒBRAIN × λBBB)/dth-BBB. Electrical current in the brain parenchyma is distorted around brain capillaries, amplifying neuronal polarization. Specifically, capillary ultrastructure produces ∼50% modulation of the ĒBRAIN over the ∼40 μm inter-capillary distance. The divergence of EBRAIN (Activating function) is thus ∼100 kV/m2 per unit ĒBRAIN.

CONCLUSIONS

BBB stimulation by principle 1 suggests novel therapeutic strategies such as boosting metabolic capacity or interstitial fluid clearance. Whereas the spatial profile of EBRAIN is traditionally assumed to depend only on macroscopic anatomy, principle 2 suggests a central role for local capillary ultrastructure-which impact forms of neuromodulation including deep brain stimulation (DBS), spinal cord stimulation (SCS), transcranial magnetic stimulation (TMS), electroconvulsive therapy (ECT), and transcranial electrical stimulation (tES)/transcranial direct current stimulation (tDCS).

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

Deep brain stimulation (DBS) is a well-established neurosurgical procedure for movement disorders that is also being explored for treatment-resistant psychiatric conditions. This review highlights important consideration for DBS simulation and data analysis. The literature on DBS has expanded considerably in recent years, and this article aims to identify important trends in the field. During DBS planning, surgery, and follow up sessions, several large data sets are created for each patient, and it becomes clear that any group analysis of such data is a big data analysis problem and has to be handled with care. The aim of this review is to provide an update and overview from a neuroengineering perspective of the current DBS techniques, technical aids, and emerging tools with the focus on patient-specific electric field (EF) simulations, group analysis, and visualization in the DBS domain. Examples are given from the state-of-the-art literature including our own research. This work reviews different analysis methods for EF simulations, tractography, deep brain anatomical templates, and group analysis. Our analysis highlights that group analysis in DBS is a complex multi-level problem and selected parameters will highly influence the result. DBS analysis can only provide clinically relevant information if the EF simulations, tractography results, and derived brain atlases are based on as much patient-specific data as possible. A trend in DBS research is creation of more advanced and intuitive visualization of the complex analysis results suitable for the clinical environment.

Comparison of methodologies for modeling directional deep brain stimulation electrodes

Deep brain stimulation (DBS) is an established clinical therapy, and directional DBS electrode designs are now commonly used in clinical practice. Directional DBS leads have the ability to increase the therapeutic window of stimulation, but they also increase the complexity of clinical programming. Therefore, computational models of DBS have become available in clinical software tools that are designed to assist in the identification of therapeutic settings. However, the details of how the DBS model is implemented can influence the predictions of the software. The goal of this study was to compare different methods for representing directional DBS electrodes within finite element volume conductor (VC) models. We evaluated 15 different DBS VC model variants and quantified how their differences influenced estimates on the spatial extent of axonal activation from DBS. Each DBS VC model included the same representation of the brain and head, but the details of the current source and electrode contact were different for each model variant. The more complex VC models explicitly represented the DBS electrode contacts, while the more simple VC models used boundary condition approximations. The more complex VC models required 2-3 times longer to mesh, build, and solve for the DBS voltage distribution than the more simple VC models. Differences in individual axonal activation thresholds across the VC model variants were substantial (-24% to +47%). However, when comparing total activation of an axon population, or estimates of an activation volume, the differences between model variants decreased (-7% to +8%). Nonetheless, the technical details of how the electrode contact and current source are represented in the DBS VC model can directly affect estimates of the voltage distribution and electric field in the brain tissue.

Influence of Virchow-Robin spaces on the electric field distribution in subthalamic nucleus deep brain stimulation

Patient MRI from DBS implantations in the subthalamic nucleus (STN) were reviewed and it was found that around 10% had Virchow-Robin spaces (VRS). Patient-specific models were developed to evaluate changes in the electric field (EF) around DBS leads. The patients (n = 7) were implanted bilaterally either with the standard voltage-controlled lead 3389 or with the directional current-controlled lead 6180. The EF distribution was evaluated by comparing simulations using patient-specific models with homogeneous models without VRS. The EF, depicted with an isocontour of 0.2 V/mm, showed a deformation in the presence of the VRS around the DBS lead. For patient-specific models, the radial extension of the EF isocontours was enlarged regardless of the operating mode or the DBS lead used. The location of the VRS in relation to the active contact and the stimulation amplitude, determined the changes in the shape and extension of the EF. It is concluded that it is important to take the patients' brain anatomy into account as the high conductivity in VRS will alter the electric field if close to the DBS lead. This can be a cause of unexpected side effects.

Impact of deep brain stimulation of the subthalamic nucleus on natural language in patients with Parkinson's disease

Background

In addition to the typical motor symptoms, a majority of patients suffering from Parkinson’s disease experience language impairments. Deep Brain Stimulation of the subthalamic nucleus robustly reduces motor dysfunction, but its impact on language skills remains ambiguous.

Method

To elucidate the impact of subthalamic deep brain stimulation on natural language production, we systematically analyzed language samples from fourteen individuals (three female / eleven male, average age 66.43 ± 7.53 years) with Parkinson’s disease in the active (ON) versus inactive (OFF) stimulation condition. Significant ON-OFF differences were considered as stimulation effects. To localize their neuroanatomical origin within the subthalamic nucleus, they were correlated with the volume of tissue activated by therapeutic stimulation.

Results

Word and clause production speed increased significantly under active stimulation. These enhancements correlated with the volume of tissue activated within the associative part of the subthalamic nucleus, but not with that within the dorsolateral motor part, which again correlated with motor improvement. Language error rates were lower in the ON vs. OFF condition, but did not correlate with electrode localization. No significant changes in further semantic or syntactic language features were detected in the current study.

Conclusion

The findings point towards a facilitation of executive language functions occurring rather independently from motor improvement. Given the presumed origin of this stimulation effect within the associative part of the subthalamic nucleus, this could be due to co-stimulation of the prefrontal-subthalamic circuit.

White matter tracing combined with electric field simulation - A patient-specific approach for deep brain stimulation

OBJECTIVE

Deep brain stimulation (DBS) in zona incerta (Zi) is used for symptom alleviation in essential tremor (ET). Zi is positioned along the dentato-rubro-thalamic tract (DRT). Electric field simulations with the finite element method (FEM) can be used for estimation of a volume where the stimulation affects the tissue by applying a fixed isolevel (VDBS). This work aims to develop a workflow for combined patient-specific electric field simulation and white matter tracing of the DRT, and to investigate the influence on the VDBS from different brain tissue models, lead design and stimulation modes. The novelty of this work lies in the combination of all these components.

METHOD

Patients with ET were implanted in Zi (lead 3389, n = 3, voltage mode; directional lead 6172, n = 1, current mode). Probabilistic reconstruction from diffusion MRI (dMRI) of the DRT (n = 8) was computed with FSL Toolbox. Brain tissue models were created for each patient (two homogenous, one heterogenous isotropic, one heterogenous anisotropic) and the respective VDBS (n = 48) calculated from the Comsol Multiphysics FEM simulations. The DRT and VDBS were visualized with 3DSlicer and superimposed on the preoperative T2 MRI, and the common volumes calculated. Dice Coefficient (DC) and level of anisotropy were used to evaluate and compare the brain models.

RESULT

Combined patient-specific tractography and electric field simulation was designed and evaluated, and all patients showed benefit from DBS. All VDBS overlapped the reconstructed DRT. Current stimulation showed prominent difference between the tissue models, where the homogenous grey matter deviated most (67 < DC < 69). Result from heterogenous isotropic and anisotropic models were similar (DC > 0.95), however the anisotropic model consistently generated larger volumes related to a greater extension of the electric field along the DBS lead. Independent of tissue model, the steering effect of the directional lead was evident and consistent.

CONCLUSION

A workflow for patient-specific electric field simulations in combination with reconstruction of DRT was successfully implemented. Accurate tissue classification is essential for electric field simulations, especially when using the current control stimulation. With an accurate targeting and tractography reconstruction, directional leads have the potential to tailor the electric field into the desired region.

A Study on the Feasibility of the Deep Brain Stimulation (DBS) Electrode Localization Based on Scalp Electric Potential Recordings

Deep Brain Stimulation (DBS) is an effective therapy for patients disabling motor symptoms from Parkinson's disease, essential tremor, and other motor disorders. Precise, individualized placement of DBS electrodes is a key contributor to clinical outcomes following surgery. Electroencephalography (EEG) is widely used to identify the sources of intracerebral signals from the potential on the scalp. EEG is portable, non-invasive, low-cost, and it could be easily integrated into the intraoperative or ambulatory environment for localization of either the DBS electrode or evoked potentials triggered by stimulation itself. In this work, we studied with numerical simulations the principle of extracting the DBS electrical pulse from the patient's EEG - which normally constitutes an artifact - and localizing the source of the artifact (i.e., the DBS electrodes) using EEG localization methods. A high-resolution electromagnetic head model was used to simulate the EEG potential at the scalp generated by the DBS pulse artifact. The potential distribution on the scalp was then sampled at the 256 electrode locations of a high-density EEG Net. The electric potential was modeled by a dipole source created by a given pair of active DBS electrodes. The dynamic Statistical Parametric Maps (dSPM) algorithm was used to solve the EEG inverse problem, and it allowed localization of the position of the stimulus dipole in three DBS electrode bipolar configurations with a maximum error of 1.5 cm. To assess the accuracy of the computational model, the results of the simulation were compared with the electric artifact amplitudes over 16 EEG electrodes measured in five patients. EEG artifacts measured in patients confirmed that simulated data are commensurate to patients' data (0 ± 6.6 μV). While we acknowledge that further work is necessary to achieve a higher accuracy needed for surgical navigation, the results presented in this study are proposed as the first step toward a validated computational framework that could be used for non-invasive localization not only of the DBS system but also brain rhythms triggered by stimulation at both proximal and distal sites in the human central nervous system.

Understanding the Effects and Adverse Reactions of Deep Brain Stimulation: Is It Time for a Paradigm Shift Toward a Focus on Heterogenous Biophysical Tissue Properties Instead of Electrode Design Only?

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.

Deep brain stimulation targets for treating depression

Deep brain stimulation (DBS) is a new therapeutic approach for treatment-resistant depression (TRD). There is a preliminary evidence of the efficacy and safety of DBS for TRD in the subgenual anterior cingulate cortex, the ventral capsule/ventral striatum, the nucleus accumbens, the lateral habenula, the inferior thalamic peduncle, the medial forebrain bundle, and the bed nucleus of the stria terminalis. Optimal stimulation targets, however, have not yet been determined. Here we provide updated knowledge substantiating the suitability of each of the current and potential future DBS targets for treating depression. In this review, we discuss the future outlook for DBS treatment of depression in light of the fact that antidepressant effects of DBS can be achieved using different targets.

Bipolar dual-lead spinal cord stimulation between two electrodes on the ventral and dorsal sides of the spinal cord: consideration of putative mechanisms

We have applied bipolar dual-lead spinal cord stimulation (SCS) between two cylinder-type electrodes placed on the ventral and dorsal sides of the spinal cord (dual-VD-SCS). A 36-year-old man suffered from burning pain from his right elbow down to his hand after brachial plexus avulsion. The areas with paresthesia induced by conventional SCS did not include the painful hand area. However, dual-VD-SCS completely induced paresthesia in the painful hand area. We speculate that dual-VD-SCS can be applied to stimulate deeper sites of the dorsal column and dorsal horn than conventional SCS and is useful for pain reduction.

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

The success of deep brain stimulation (DBS) relies primarily on the localization of the implanted electrode. Its final position can be chosen based on the results of intraoperative microelectrode recording (MER) and stimulation tests. The optimal position often differs from the final one selected for chronic stimulation with the DBS electrode. The aim of the study was to investigate, using finite element method (FEM) modeling and simulations, whether lead design, electrical setup, and operating modes induce differences in electric field (EF) distribution and in consequence, the clinical outcome. Finite element models of a MER system and a chronic DBS lead were developed. Simulations of the EF were performed for homogenous and patient-specific brain models to evaluate the influence of grounding (guide tube vs. stimulator case), parallel MER leads, and non-active DBS contacts. Results showed that the EF is deformed depending on the distance between the guide tube and stimulating contact. Several parallel MER leads and the presence of the non-active DBS contacts influence the EF distribution. The DBS EF volume can cover the intraoperatively produced EF, but can also extend to other anatomical areas. In conclusion, EF deformations between stimulation tests and DBS should be taken into consideration as they can alter the clinical outcome.

The epigenetic component of the brain response to electromagnetic stimulation in Parkinson's Disease patients: A literature overview

Modulations of epigenetic machinery, namely DNA methylation pattern, histone modification, and non-coding RNAs expression, have been recently included among the key determinants contributing to Parkinson's Disease (PD) aetiopathogenesis and response to therapy. Along this line of reasoning, a set of experimental findings are highlighting the epigenetic-based response to electromagnetic (EM) therapies used to alleviate PD symptomatology, mainly Deep Brain Stimulation (DBS) and Transcranial Magnetic Stimulation (TMS). Notwithstanding the proven efficacy of EM therapies, the precise molecular mechanisms underlying the brain response to these types of stimulations are still far from being elucidated. In this review we provide an overview of the epigenetic changes triggered by DBS and TMS in both PD patients and neurons from different experimental animal models. Furthermore, we also propose a critical overview of the exposure modalities currently applied, in order to evaluate the technical robustness and dosimetric control of the stimulation, which are key issues to be carefully assessed when new molecular findings emerge from experimental studies. Bioelectromagnetics. 39:3-14, 2018. © 2017 Wiley Periodicals, Inc.

Refining the Deep Brain Stimulation Target within the Limbic Globus Pallidus Internus for Tourette Syndrome

BACKGROUND

Deep brain stimulation (DBS) in patients with severe, refractory Tourette syndrome (TS) has demonstrated promising but variable results thus far. The thalamus and anteromedial globus pallidus internus (amGPi) have been the most commonly stimulated sites within the cortico-striato thalamic circuit, but an optimal target is yet to be elucidated.

OBJECTIVES

This study of 15 patients with long-term amGPi DBS for severe TS investigated whether a specific anatomical site within the amGPi correlated with optimal clinical outcome for the measures of tics, obsessive compulsive behaviour (OCB), and mood.

METHODS

Validated clinical assessments were used to measure tics, OCB, quality of life, anxiety, and depression before DBS and at the latest follow-up (17-82 months). Electric field simulations were created for each patient using information on electrode location and individual stimulation parameters. A subsequent regression analysis correlated these patient-specific simulations to percentage changes in outcome measures in order to identify any significant voxels related to clinical improvement.

RESULTS

A region within the ventral limbic GPi, specifically on the medial medullary lamina in the pallidum at the level of the AC-PC, was significantly associated with improved tics but not mood or OCB outcome.

CONCLUSIONS

This study adds further support to the application of DBS in a tic-related network, though factors such as patient sample size and clinical heterogeneity remain as limitations and replication is required.

Investigation into Deep Brain Stimulation Lead Designs: A Patient-Specific Simulation Study

New deep brain stimulation (DBS) electrode designs offer operation in voltage and current mode and capability to steer the electric field (EF). The aim of the study was to compare the EF distributions of four DBS leads at equivalent amplitudes (3 V and 3.4 mA). Finite element method (FEM) simulations (n = 38) around cylindrical contacts (leads 3389, 6148) or equivalent contact configurations (leads 6180, SureStim1) were performed using homogeneous and patient-specific (heterogeneous) brain tissue models. Steering effects of 6180 and SureStim1 were compared with symmetric stimulation fields. To make relative comparisons between simulations, an EF isolevel of 0.2 V/mm was chosen based on neuron model simulations (n = 832) applied before EF visualization and comparisons. The simulations show that the EF distribution is largely influenced by the heterogeneity of the tissue, and the operating mode. Equivalent contact configurations result in similar EF distributions. In steering configurations, larger EF volumes were achieved in current mode using equivalent amplitudes. The methodology was demonstrated in a patient-specific simulation around the zona incerta and a "virtual" ventral intermediate nucleus target. In conclusion, lead design differences are enhanced when using patient-specific tissue models and current stimulation mode.

Technical aspects of neurostimulation: Focus on equipment, electric field modeling, and stimulation protocols

Neuromodulation is a field of science, medicine, and bioengineering that encompasses implantable and non-implantable technologies for the purpose of improving quality of life and functioning of humans. Brain neuromodulation involves different neurostimulation techniques: transcranial magnetic stimulation (TMS), transcranial direct current stimulation (tDCS), vagus nerve stimulation (VNS), and deep brain stimulation (DBS), which are being used both to study their effects on cognitive brain functions and to treat neuropsychiatric disorders. The mechanisms of action of neurostimulation remain incompletely understood. Insight into the technical basis of neurostimulation might be a first step towards a more profound understanding of these mechanisms, which might lead to improved clinical outcome and therapeutic potential. This review provides an overview of the technical basis of neurostimulation focusing on the equipment, the present understanding of induced electric fields, and the stimulation protocols. The review is written from a technical perspective aimed at supporting the use of neurostimulation in clinical practice.

Deep brain stimulation for chronic pain

Deep brain stimulation (DBS) is a neurosurgical intervention popularised in movement disorders such as Parkinson's disease, and also reported to improve symptoms of epilepsy, Tourette's syndrome, obsessive compulsive disorders and cluster headache. Since the 1950s, DBS has been used as a treatment to relieve intractable pain of several aetiologies including post stroke pain, phantom limb pain, facial pain and brachial plexus avulsion. Several patient series have shown benefits in stimulating various brain areas, including the sensory thalamus (ventral posterior lateral and medial), the periaqueductal and periventricular grey, or, more recently, the anterior cingulate cortex. However, this technique remains "off label" in the USA as it does not have Federal Drug Administration approval. Consequently, only a small number of surgeons report DBS for pain using current technology and techniques and few regions approve it. Randomised, blinded and controlled clinical trials that may use novel trial methodologies are desirable to evaluate the efficacy of DBS in patients who are refractory to other therapies. New imaging techniques, including tractography, may help optimise electrode placement and clinical outcome.

Relationship between neural activation and electric field distribution during deep brain stimulation

Models and simulations are commonly used to study deep brain stimulation (DBS). Simulated stimulation fields are often defined and visualized by electric field isolevels or volumes of tissue activated (VTA). The aim of the present study was to evaluate the relationship between stimulation field strength as defined by the electric potential V, the electric field E, and the divergence of the electric field ∇(2) V, and neural activation. Axon cable models were developed and coupled to finite-element DBS models in three-dimensional (3-D). Field thresholds ( VT , ET, and ∇(2) VT ) were derived at the location of activation for various stimulation amplitudes (1 to 5 V), pulse widths (30 to 120 μs), and axon diameters (2.0 to 7.5 μm). Results showed that thresholds for VT and ∇(2) VT were highly dependent on the stimulation amplitude while ET were approximately independent of the amplitude for large axons. The activation field strength thresholds presented in this study may be used in future studies to approximate the VTA during model-based investigations of DBS without the need of computational axon models.

Variation in deep brain stimulation electrode impedance over years following electrode implantation

BACKGROUND

Deep brain stimulation (DBS) electrode impedance is a major determinant of current delivery to target tissues, but long-term variation in impedance has received little attention.

OBJECTIVES

To assess the relationship between electrode impedance and time in a large DBS patient population and characterize the relationship between contact activity and impedance.

METHODS

We collected retrospective impedance and programming data from 128 electrodes in 84 patients with Parkinson's disease, essential tremor or dystonia. Effects of time, contact activity, stimulation voltage and other parameters on impedance were assessed. We also examined impedance changes following contact activation and deactivation.

RESULTS

Impedance decreased by 73 Ω/year (p < 0.001), with 72% of contacts following a downward trend. Impedance was on average 163 Ω lower in active contacts (p < 0.001). Contact activation and inactivation were associated with a more (p < 0.001) and less (p = 0.016) rapid decline in impedance, respectively. Higher stimulation voltages were associated with lower impedance values (p < 0.001). Contact number and electrode model were also significant predictors of impedance.

CONCLUSIONS

Impedance decreases gradually in a stimulation-dependent manner. These trends have implications for long-term programming, the development of a closed-loop DBS device and current understanding of the electrode-tissue interface.

Closing the loop of deep brain stimulation

High-frequency deep brain stimulation is used to treat a wide range of brain disorders, like Parkinson's disease. The stimulated networks usually share common electrophysiological signatures, including hyperactivity and/or dysrhythmia. From a clinical perspective, HFS is expected to alleviate clinical signs without generating adverse effects. Here, we consider whether the classical open-loop HFS fulfills these criteria and outline current experimental or theoretical research on the different types of closed-loop DBS that could provide better clinical outcomes. In the first part of the review, the two routes followed by HFS-evoked axonal spikes are explored. In one direction, orthodromic spikes functionally de-afferent the stimulated nucleus from its downstream target networks. In the opposite direction, antidromic spikes prevent this nucleus from being influenced by its afferent networks. As a result, the pathological synchronized activity no longer propagates from the cortical networks to the stimulated nucleus. The overall result can be described as a reversible functional de-afferentation of the stimulated nucleus from its upstream and downstream nuclei. In the second part of the review, the latest advances in closed-loop DBS are considered. Some of the proposed approaches are based on mathematical models, which emphasize different aspects of the parkinsonian basal ganglia: excessive synchronization, abnormal firing-rate rhythms, and a deficient thalamo-cortical relay. The stimulation strategies are classified depending on the control-theory techniques on which they are based: adaptive and on-demand stimulation schemes, delayed and multi-site approaches, stimulations based on proportional and/or derivative control actions, optimal control strategies. Some of these strategies have been validated experimentally, but there is still a large reservoir of theoretical work that may point to ways of improving practical treatment.

Simulations and visualizations for interpretation of brain microdialysis data during deep brain stimulation

Microdialysis of the basal ganglia was used in parallel to deep brain stimulation (DBS) for patients with Parkinson's disease. The aim of this study was to patient-specifically simulate and visualize the maximum tissue volume of influence (TVI(max)) for each microdialysis catheter and the electric field generated around each DBS electrode. The finite element method (FEM) was used for the simulations. The method allowed mapping of the anatomical origin of the microdialysis data and the electric stimulation for each patient. It was seen that the sampling and stimulation targets differed among the patients, and the results will therefore be used in the future interpretation of the biochemical data.

MRI-based multiscale model for electromagnetic analysis in the human head with implanted DBS

Deep brain stimulation (DBS) is an established procedure for the treatment of movement and affective disorders. Patients with DBS may benefit from magnetic resonance imaging (MRI) to evaluate injuries or comorbidities. However, the MRI radio-frequency (RF) energy may cause excessive tissue heating particularly near the electrode. This paper studies how the accuracy of numerical modeling of the RF field inside a DBS patient varies with spatial resolution and corresponding anatomical detail of the volume surrounding the electrodes. A multiscale model (MS) was created by an atlas-based segmentation using a 1 mm³ head model (mRes) refined in the basal ganglia by a 200 μm² ex-vivo dataset. Four DBS electrodes targeting the left globus pallidus internus were modeled. Electromagnetic simulations at 128 MHz showed that the peak of the electric field of the MS doubled (18.7 kV/m versus 9.33 kV/m) and shifted 6.4 mm compared to the mRes model. Additionally, the MS had a sixfold increase over the mRes model in peak-specific absorption rate (SAR of 43.9 kW/kg versus 7 kW/kg). The results suggest that submillimetric resolution and improved anatomical detail in the model may increase the accuracy of computed electric field and local SAR around the tip of the implant.

Computational modeling of deep brain stimulation

Deep brain stimulation (DBS) is an effective clinical treatment for several medically refractory neurological disorders. However, even after decades of clinical success, explicit understanding of the response of neurons to applied electric fields remains limited, and scientific definition of the therapeutic mechanisms of DBS remains elusive. In addition, it is presently unclear which electrode designs and stimulation paradigms are optimal for maximal therapeutic benefit and minimal side-effects with DBS. Detailed computer modeling of DBS has emerged recently as a powerful technique to enhance our understanding of the effects of DBS and to create a virtual testing ground for new stimulation strategies. This chapter summarizes the fundamentals of neurostimulation modeling, presents some scientific contributions of computer models to the field of DBS, and demonstrates the application of DBS modeling tools to augment the clinical utility of DBS.

Staged implantation of multiple electrodes in the internal globus pallidus in the treatment of primary generalized dystonia

Object

Deep brain stimulation (DBS) is used for treating various types of dystonia. Multiple electrodes could be proposed to improve the therapeutic outcome enabling the targeting of specific neuronal populations not reached by the electrical field generated by the initially implanted electrode. The authors address the question of the feasibility and safety of staged multiple lead implantations in the sensorimotor internal globus pallidus (GPi) in primary generalized dystonia (PGD). Criteria for patient selection, surgical technique, target selection, electrical settings management, and clinical outcome are presented.

Methods

Sixteen patients (8 harbored the DYT1 gene mutation) presented with PGD and were enrolled in this study. Patients underwent clinical assessment using the Burke-Fahn-Marsden Dystonia Rating Scale preoperatively and during follow-up with DBS. Prior to the addition of electrodes, the authors confirmed, by turning off stimulation, that the patient was still benefiting from DBS and that DBS settings adjustment did not provide further improvement. The second target was defined according to the position of the first electrode, to the residual volume within the sensorimotor GPi, and according to residual symptoms. The second surgery followed the same protocol as the first and the new electrode were inserted using the same bur hole as the first electrode.

Results

The addition of a new pair of electrodes was followed by significant improvement in the whole population (p = 0.005), as well as in the DYT1-negative subgroup (p = 0.012) but not in the DYT1 subgroup (p = not significant). Nevertheless, some patients did not exhibit significant additional benefit. Seven hardware-related complications occurred during the entire follow-up, 3 prior to it, and 4 after the addition of the second pair of electrodes.

Conclusions

The addition of a second pair of electrodes in the GPi in patients with PGD with suboptimal or decaying benefit following the first surgery seems to be a safe procedure and is not followed by an increase in surgery-related complications. This staged procedure may provide further clinical improvement in patients with PGD in whom DBS effect is initially incomplete or when disease progression occurs over time. The position of the additional electrode within the GPi is determined by the available volume within the posteroventral GPi and by the distribution of the dystonic symptoms that need to be controlled.

Explaining clinical effects of deep brain stimulation through simplified target-specific modeling of the volume of activated tissue

BACKGROUND AND PURPOSE

Although progress has been made in understanding the optimal anatomic structures as target areas for DBS, little effort has been put into modeling and predicting electromagnetic field properties of activated DBS electrodes and understanding their interactions with the adjacent tissue. Currently, DBS is performed with the patient awake to assess the effectiveness and the side effect spectrum of stimulation. This study was designed to create a robust and rather simple numeric and visual tool that provides sufficient and practical relevant information to visualize the patient's individual VAT.

MATERIALS AND METHODS

Multivariate polynomial fitting of previously obtained data from a finite-element model, based on a similar DBS system, was used. The model estimates VAT as a first-approximation sphere around the active DBS contact, using stimulation voltages and individual tissue-electrode impedances. Validation uses data from 2 patients with PD by MR imaging, DTI, fiber tractography, and postoperative CT data.

RESULTS

Our model can predict VAT for impedances between 500 and 2000 Ω with stimulation voltages up to 10 V. It is based on assumptions for monopolar DBS. Evaluation of 2 DBS cases showed a convincing correspondence between predicted VAT and neurologic (side) effects (internal capsule activation).

CONCLUSIONS

Stimulation effects during DBS can be readily explained with this simple VAT model. Its implementation in daily clinical routine might help in understanding the types of tissues activated during DBS. This technique might have the potential to facilitate DBS implantations with the patient under general anesthesia while yielding acceptable clinical effectiveness.

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

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) has become the surgical therapy of choice for medically intractable Parkinson's disease. However, quantitative understanding of the interaction between the electric field generated by DBS and the underlying neural tissue is limited. Recently, computational models of varying levels of complexity have been used to study the neural response to DBS. The goal of this study was to evaluate the quantitative impact of incrementally incorporating increasing levels of complexity into computer models of STN DBS. Our analysis focused on the direct activation of experimentally measureable fiber pathways within the internal capsule (IC). Our model system was customized to an STN DBS patient and stimulation thresholds for activation of IC axons were calculated with electric field models that ranged from an electrostatic, homogenous, isotropic model to one that explicitly incorporated the voltage-drop and capacitance of the electrode-electrolyte interface, tissue encapsulation of the electrode, and diffusion-tensor based 3D tissue anisotropy and inhomogeneity. The model predictions were compared to experimental IC activation defined from electromyographic (EMG) recordings from eight different muscle groups in the contralateral arm and leg of the STN DBS patient. Coupled evaluation of the model and experimental data showed that the most realistic predictions of axonal thresholds were achieved with the most detailed model. Furthermore, the more simplistic neurostimulation models substantially overestimated the spatial extent of neural activation.

Factors predicting improvement in primary generalized dystonia treated by pallidal deep brain stimulation

Despite the beneficial effects of Globus Pallidus internus (GPi) deep brain stimulation (DBS) in patients with primary generalized dystonia (PGD), the degree of improvement varies from one patient to another. The objective of this study was to examine the effects of clinical, anatomical (volume of the GPi), and electrical variables on the postoperative Burke-Fahn-Marsden Dystonia rating scale (BFMDRS) motor score to identify which factors may be predictive of the degree of improvement. We reviewed retrospectively the clinical records of 40 steady-state patients with PGD who had been treated by bilateral GPi lead implantation. The follow-up period was 2 to 8 years. The correlation between the electrical parameters (voltage, impedance, and current) and the clinical outcome was studied. An analysis of covariance was performed to identify factors predictive of the magnitude of improvement. The most influential factors according to the model are as follows: the preoperative BFMDRS score (P < 0.0001); age at surgery (P < 0.0001); the right GPi volume (P = 0.002); the left stimulated GPi volume (P = 0.005). No significant correlation was found between the electrical parameters used and the mean motor scores in steady state.

Deep brain stimulation activation volumes and their association with neurophysiological mapping and therapeutic outcomes

OBJECTIVE

Despite the clinical success of deep brain stimulation (DBS) for the treatment of Parkinson's disease (PD), little is known about the electrical spread of the stimulation. The primary goal of this study was to integrate neuroimaging, neurophysiology and neurostimulation data sets from 10 patients with PD, unilaterally implanted with subthalamic nucleus (STN) DBS electrodes, to identify the theoretical volume of tissue activated (VTA) by clinically defined therapeutic stimulation parameters.

METHODS

Each patient specific model was created with a series of five steps: (1) definition of the neurosurgical stereotactic coordinate system within the context of preoperative imaging data; (2) entry of intraoperative microelectrode recording locations from neurophysiologically defined thalamic, subthalamic and substantia nigra neurons into the context of the imaging data; (3) fitting a three dimensional brain atlas to the neuroanatomy and neurophysiology of the patient; (4) positioning the DBS electrode in the documented stereotactic location, verified by postoperative imaging data; and (5) calculation of the VTA using a diffusion tensor based finite element neurostimulation model.

RESULTS

The patient specific models show that therapeutic benefit was achieved with direct stimulation of a wide range of anatomical structures in the subthalamic region. Interestingly, of the five patients exhibiting a greater than 40% improvement in their Unified PD Rating Scale (UPDRS), all but one had the majority of their VTA outside the atlas defined borders of the STN. Furthermore, of the five patients with less than 40% UPDRS improvement, all but one had the majority of their VTA inside the STN.

CONCLUSIONS

Our results are consistent with previous studies suggesting that therapeutic benefit is associated with electrode contacts near the dorsal border of the STN, and provide quantitative estimates of the electrical spread of the stimulation in a clinically relevant context.

Deep brain stimulation of the nucleus accumbens reduces ethanol consumption in rats

Recent studies have shown that deep brain stimulation (DBS) of the nucleus accumbens (NAcc) has an inhibitory effect on drug-seeking behaviors including reinstatement responding for cocaine. The objective of the present study was to expand on these findings by assessing the effects of DBS on behaviors related to alcohol consumption. The specific aim of this study was to determine whether DBS delivered to either the shell or core of the NAcc would reduce ETOH intake in rats using a two-bottle choice limited access procedure. Long Evans rats were induced to drink a 10% ethanol solution using a saccharin fading procedure. Bipolar electrodes were implanted bilaterally into either the core or shell of the NAcc. During testing animals received DBS 5 min prior to and during a 30-minute test session in which both ETOH and water bottles were accessible. Current was delivered at amplitudes ranging from 0 to 150 microA. ETOH consumption was significantly reduced from baseline levels at the 150 microA current for both shell and core electrode placements. A significant current effect was not found for water consumption for either site. These results provide evidence that DBS delivered either to the nucleus accumbens core or shell subregions can significantly reduce ethanol intake in the rat.

Experimental and theoretical characterization of the voltage distribution generated by deep brain stimulation

Deep brain stimulation (DBS) is an established therapy for the treatment of Parkinson's disease and shows great promise for numerous other disorders. While the fundamental purpose of DBS is to modulate neural activity with electric fields, little is known about the actual voltage distribution generated in the brain by DBS electrodes and as a result it is difficult to accurately predict which brain areas are directly affected by the stimulation. The goal of this study was to characterize the spatial and temporal characteristics of the voltage distribution generated by DBS electrodes. We experimentally recorded voltages around active DBS electrodes in either a saline bath or implanted in the brain of a non-human primate. Recordings were made during voltage-controlled and current-controlled stimulation. The experimental findings were compared to volume conductor electric field models of DBS parameterized to match the different experiments. Three factors directly affected the experimental and theoretical voltage measurements: 1) DBS electrode impedance, primarily dictated by a voltage drop at the electrode-electrolyte interface and the conductivity of the tissue medium, 2) capacitive modulation of the stimulus waveform, and 3) inhomogeneity and anisotropy of the tissue medium. While the voltage distribution does not directly predict the neural response to DBS, the results of this study do provide foundational building blocks for understanding the electrical parameters of DBS and characterizing its effects on the nervous system.

Method for patient-specific finite element modeling and simulation of deep brain stimulation

Deep brain stimulation (DBS) is an established treatment for Parkinson's disease. Success of DBS is highly dependent on electrode location and electrical parameter settings. The aim of this study was to develop a general method for setting up patient-specific 3D computer models of DBS, based on magnetic resonance images, and to demonstrate the use of such models for assessing the position of the electrode contacts and the distribution of the electric field in relation to individual patient anatomy. A software tool was developed for creating finite element DBS-models. The electric field generated by DBS was simulated in one patient and the result was visualized with isolevels and glyphs. The result was evaluated and it corresponded well with reported effects and side effects of stimulation. It was demonstrated that patient-specific finite element models and simulations of DBS can be useful for increasing the understanding of the clinical outcome of DBS.

Quantifying the effects of the electrode-brain interface on the crossing electric currents in deep brain recording and stimulation

A depth electrode-brain interface (EBI) is formed once electrodes are implanted into the human brain. We investigated the impact of the EBI on the crossing electric currents during both deep brain recording (DBR) and deep brain stimulation (DBS) over the acute, chronic and transitional stages post-implantation, in order to investigate and quantify the effect which changes at the EBI have on both DBR and DBS. We combined two complementary methods: (1) physiological recording of local field potentials via the implanted electrode in patients; and (2) computational simulations of an EBI model. Our depth recordings revealed that the physiological modulation of the EBI in the acute stage via brain pulsation selectively affected the crossing neural signals in a frequency-dependent manner, as the amplitude of the electrode potential was inversely correlated with that of the tremor-related oscillation, but not the beta oscillation. Computational simulations of DBS during the transitional period showed that the shielding effect of partial giant cell growth on the injected current could shape the field in an unpredictable manner. These results quantitatively demonstrated that physiological modulation of the EBI significantly affected the crossing currents in both DBR and DBS. Studying the microenvironment of the EBI may be a key step in investigating the mechanisms of DBR and DBS, as well as brain-computer interactions in general.

Computational analysis of deep brain stimulation

Chronic, high-frequency electrical stimulation of subcortical brain structures (deep brain stimulation [DBS]) is an effective clinical treatment for several medically refractory neurological disorders. However, the clinical successes of DBS are tempered by the limited understanding of the response of neurons to applied electric fields and scientific definition of the therapeutic mechanisms of DBS remains elusive. In addition, it is presently unclear which electrode designs and stimulation parameters are optimal for maximum therapeutic benefit and minimal side effects. Detailed computer modeling of DBS has recently emerged as a powerful technique to enhance our understanding of the effects of DBS and to create a virtual testing ground for new stimulation paradigms. This review summarizes the fundamentals of neurostimulation modeling and provides an overview of some of the scientific contributions of computer models to the field of DBS. We then provide a prospective view on the application of DBS-modeling tools to augment the clinical utility of DBS and to design the next generation of DBS technology.