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

Probabilistic stimulation mapping from intra-operative thalamic deep brain stimulation data in essential tremor

Deep brain stimulation (DBS) is a therapy for Parkinson's disease (PD) and essential tremor (ET). The mechanism of action of DBS is still incompletely understood. Retrospective group analysis of intra-operative data recorded from ET patients implanted in the ventral intermediate nucleus of the thalamus (Vim) is rare. Intra-operative stimulation tests generate rich data and their use in group analysis has not yet been explored.Objective.To implement, evaluate, and apply a group analysis workflow to generate probabilistic stimulation maps (PSMs) using intra-operative stimulation data from ET patients implanted in Vim.Approach.A group-specific anatomical template was constructed based on the magnetic resonance imaging scans of 6 ET patients and 13 PD patients. Intra-operative test data (total:n= 1821) from the 6 ET patients was analyzed: patient-specific electric field simulations together with tremor assessments obtained by a wrist-based acceleration sensor were transferred to this template. Occurrence and weighted mean maps were generated. Voxels associated with symptomatic response were identified through a linear mixed model approach to form a PSM. Improvements predicted by the PSM were compared to those clinically assessed. Finally, the PSM clusters were compared to those obtained in a multicenter study using data from chronic stimulation effects in ET.Main results.Regions responsible for improvement identified on the PSM were in the posterior sub-thalamic area (PSA) and at the border between the Vim and ventro-oral nucleus of the thalamus (VO). The comparison with literature revealed a center-to-center distance of less than 5 mm and an overlap score (Dice) of 0.4 between the significant clusters. Our workflow and intra-operative test data from 6 ET-Vim patients identified effective stimulation areas in PSA and around Vim and VO, affirming existing medical literature.Significance.This study supports the potential of probabilistic analysis of intra-operative stimulation test data to reveal DBS's action mechanisms and to assist surgical planning.

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.

Deep Brain Stimulation Lead Localization Variability Comparing Intraoperative MRI Versus Postoperative Computed Tomography

BACKGROUND AND OBJECTIVES

Commercially available lead localization software for deep brain stimulation (DBS) often relies on postoperative computed tomography (CT) scans to define electrode positions. When cases are performed with intraoperative MRI, another imaging set exists with which to perform these localizations. To compare DBS localization error between postoperative CT scans and intraoperative MRI.

METHODS

A retrospective cohort of patients who underwent MRI-guided placement of DBS electrodes using the ClearPoint platform was identified. Using Brainlab Elements, postoperative CT scans were coregistered to intraoperative magnetic resonance images visualizing the ClearPoint guidance sheaths and ceramic stylets. DBS electrodes were identified in CT scans using Brainlab's lead localization tool. Trajectory and vector errors were quantified between scans for each lead in each patient.

RESULTS

Eighty patients with a total of 157 implanted DBS electrodes were included. We observed mean trajectory and vector errors of 0.78 ± 0.44 mm (range 0.1-2.0 mm) and 1.57 ± 0.79 mm (range 0.2-4.2 mm), respectively, between postoperative CT and intraoperative MRI. There were 7 patients with CT scans collected at multiple time points. Trajectory error increased by 0.15 ± 0.42 mm ( P = .31), and vector error increased by 0.22 ± 0.53 mm ( P = .13) in the later scans. Across all scans, there was no significant association between trajectory ( P = .053) or vector ( P = .98) error and the date of CT acquisition. DBS electrodes targeting the subthalamic nucleus had significantly greater trajectory errors ( P = .02) than those targeting the globus pallidus pars internus nucleus.

CONCLUSION

Commercially available software produced largely concordant lead localizations when comparing intraoperative MRIs with postoperative CT scans, with trajectory errors on average <1 mm. CT scans tend to be more comparable with intraoperative MRI in the immediate postoperative period, with increased time intervals associated with a greater magnitude of error between modalities.

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.

How Sample Size Impacts Probabilistic Stimulation Maps in Deep Brain Stimulation

Probabilistic stimulation maps of deep brain stimulation (DBS) effect based on voxel-wise statistics (p-maps) have increased in literature over the last decade. These p-maps require correction for Type-1 errors due to multiple testing based on the same data. Some analyses do not reach overall significance, and this study aims to evaluate the impact of sample size on p-map computation. A dataset of 61 essential tremor patients treated with DBS was used for the investigation. Each patient contributed with four stimulation settings, one for each contact. From the dataset, 5 to 61 patients were randomly sampled with replacement for computation of p-maps and extraction of high- and low-improvement volumes. For each sample size, the process was iterated 20 times with new samples generating in total 1140 maps. The overall p-value corrected for multiple comparisons, significance volumes, and dice coefficients (DC) of the volumes within each sample size were evaluated. With less than 30 patients (120 simulations) in the sample, the variation in overall significance was larger and the median significance volumes increased with sample size. Above 120 simulations, the trends stabilize but present some variations in cluster location, with a highest median DC of 0.73 for n = 57. The variation in location was mainly related to the region between the high- and low-improvement clusters. In conclusion, p-maps created with small sample sizes should be evaluated with caution, and above 120 simulations in single-center studies are probably required for stable results.

Toward a cerebello-thalamo-cortical computational model of spinocerebellar ataxia

Computational neural network modelling is an emerging approach for optimization of drug treatment of neurological disorders and fine-tuning of rehabilitation strategies. In the current study, we constructed a cerebello-thalamo-cortical computational neural network model to simulate a mouse model of cerebellar ataxia (pcd^5J mice) by manipulating cerebellar bursts through reduction of GABAergic inhibitory input. Cerebellar output neurons were projected to the thalamus and bidirectionally connected with the cortical network. Our results showed that reduction of inhibitory input in the cerebellum orchestrated the cortical local field potential (LFP) dynamics to generate specific motor outputs of oscillations of the theta, alpha, and beta bands in the computational model as well as in mouse motor cortical neurons. The therapeutic potential of deep brain stimulation (DBS) was tested in the computational model by increasing the sensory input to restore cortical output. Ataxia mice showed normalization of the motor cortex LFP after cerebellum DBS. We provide a novel approach to computational modelling to investigate the effect of DBS by mimicking cerebellar ataxia involving degeneration of Purkinje cells. Simulated neural activity coincides with findings from neural recordings of ataxia mice. Our computational model could thus represent cerebellar pathologies and provide insight into how to improve disease symptoms by restoring neuronal electrophysiological properties using DBS.

Probabilistic maps for deep brain stimulation - Impact of methodological differences

BACKGROUND

Group analysis of patients with deep brain stimulation (DBS) has the potential to help understand and optimize the treatment of patients with movement disorders. Probabilistic stimulation maps (PSM) are commonly used to analyze the correlation between tissue stimulation and symptomatic effect but are applied with different methodological variations.

OBJECTIVE

To compute a group-specific MRI template and PSMs for investigating the impact of PSM model parameters.

METHODS

Improvement and occurrence of dizziness in 68 essential tremor patients implanted in caudal zona incerta were analyzed. The input data includes the best parameters for each electrode contact (screening), and the clinically used settings. Patient-specific electric field simulations (n = 488) were computed for all DBS settings. The electric fields were transformed to a group-specific MRI template for analysis and visualization. The different comparisons were based on PSMs representing occurrence (N-map), mean improvement (M-map), weighted mean improvement (wM-map), and voxel-wise t-statistics (p-map). These maps were used to investigate the impact from input data (clinical/screening settings), clustering methods, sampling resolution, and weighting function.

RESULTS

Screening or clinical settings showed the largest impacts on the PSMs. The average differences of wM-maps were 12.4 and 18.2% points for the left and right sides respectively. Extracting clusters based on wM-map or p-map showed notable variation in volumes, while positioning was similar. The impact on the PSMs was small from weighting functions, except for a clear shift in the positioning of the wM-map clusters.

CONCLUSION

The distribution of the input data and the clustering method are most important to consider when creating PSMs for studying the relationship between anatomy and DBS outcome.

DBSim and ELMA - Freeware for Simulations of Deep Brain Stimulation

Finite Element Method (FEM) simulations of the electric field is a useful tool to estimate the activated tissue around Deep Brain Stimulation (DBS) electrodes. Based on our previous research, a two-part software package named DBSim and ELMA is presented. ELMA is used to classify brain tissue into grey matter, white matter, blood, and cerebrospinal fluid and assign electric conductivities accordingly. This data is then used in DBSim to generate patient-specific simulations of the electric field around currently implemented leads Medtronic 3387 and 3389, and Abbott 6180 and 6181. The software is available for free download at https://liu.se/en/article/ne-downloads Clinical Relevance- This is a tool meant for research and educational purposes for e.g. studies on optimal target areas for DBS.

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.

Distribution of electric field in patients with obsessive compulsive disorder treated with deep brain stimulation of the bed nucleus of stria terminalis

Background

Deep brain stimulation (DBS) is being investigated as a treatment for therapy-refractory obsessive compulsive disorder (OCD). Many different brain targets are being trialled. Several of these targets such as the ventral striatum (including the nucleus accumbens (NAc)), the ventral capsule, the inferior thalamic peduncle, and the bed nucleus of stria terminalis (BNST)) belong to the same network, are anatomically very close to one another, or even overlap. Data is still missing on how various stimulation parameters in a given target will affect surrounding anatomical areas and impact the clinical outcome of DBS.

Methods

In a pilot study of eleven participants with DBS of the BNST, we investigate through patient-specific simulation of electric field, which anatomical areas are affected by the electric field, and if this can be related to the clinical results. Our study combined individual patient’s stimulation parameters at 12- and 24-month follow-up with image data from the preoperative MRI and postoperative CT. These data were used to calculate the distribution of electric field and create individual anatomical models of the field of stimulation.

Results

The individual electric stimulation fields by stimulation in the BNST were similar at both the 12- and 24-month follow-up, involving mainly anterior limb of the internal capsule (ALIC), genu of the internal capsule (IC), BNST, fornix, anteromedial globus pallidus externa (GPe), and the anterior commissure. A statistical significant correlation (p < 0.05) between clinical effect measured by the Yale-Brown Obsessive Compulsive Scale and stimulation was found at the 12-month follow-up in the ventral ALIC and anteromedial GPe.

Conclusions

Many of the targets under investigation for OCD are in anatomical proximity. As seen in our study, off-target effects are overlapping. Therefore, DBS in the region of ALIC, NAc, and BNST may perhaps be considered to be stimulation of the same target.

A Randomized Trial Directly Comparing Ventral Capsule and Anteromedial Subthalamic Nucleus Stimulation in Obsessive-Compulsive Disorder: Clinical and Imaging Evidence for Dissociable Effects

(Appeared originally in Biological Psychiatry 2019; 85:726-734) Reprinted under Creative Commons CC-BY license.

Frequency-specific network activity predicts bradykinesia severity in Parkinson's disease

OBJECTIVE

Bradykinesia has been associated with beta and gamma band interactions in the basal ganglia-thalamo-cortical circuit in Parkinson's disease. In this present cross-sectional study, we aimed to search for neural networks with electroencephalography whose frequency-specific actions may predict bradykinesia.

METHODS

Twenty Parkinsonian patients treated with bilateral subthalamic stimulation were first prescreened while we selected four levels of contralateral stimulation (0: OFF, 1-3: decreasing symptoms to ON state) individually, based on kinematics. In the screening period, we performed 64-channel electroencephalography measurements simultaneously with electromyography and motion detection during a resting state, finger tapping, hand grasping tasks, and pronation-supination of the arm, with the four levels of contralateral stimulation. We analyzed spectral power at the low (13-20 Hz) and high (21-30 Hz) beta frequency bands and low (31-60 Hz) and high (61-100 Hz) gamma frequency bands using the dynamic imaging of coherent sources. Structural equation modelling estimated causal relationships between the slope of changes in network beta and gamma activities and the slope of changes in bradykinesia measures.

RESULTS

Activity in different subnetworks, including predominantly the primary motor and premotor cortex, the subthalamic nucleus predicted the slopes in amplitude and speed while switching between stimulation levels. These subnetwork dynamics on their preferred frequencies predicted distinct types and parameters of the movement only on the contralateral side.

DISCUSSION

Concurrent subnetworks affected in bradykinesia and their activity changes in the different frequency bands are specific to the type and parameters of the movement; and the primary motor and premotor cortex are common nodes.

Boundary element fast multipole method for modeling electrical brain stimulation with voltage and current electrodes

Objective. To formulate, validate, and apply an alternative to the finite element method (FEM) high-resolution modeling technique for electrical brain stimulation-the boundary element fast multipole method (BEM-FMM). To include practical electrode models for both surface and embedded electrodes.Approach. Integral equations of the boundary element method in terms of surface charge density are combined with a general-purpose fast multipole method and are expanded for voltage, shunt, current, and floating electrodes. The solution of coupled and properly weighted/preconditioned integral equations is accompanied by enforcing global conservation laws: charge conservation law and Kirchhoff's current law.Main results.A sub-percent accuracy is reported as compared to the analytical solutions and simple validation geometries. Comparison to FEM considering realistic head models resulted in relative differences of the electric field magnitude in the range of 3%-6% or less. Quantities that contain higher order spatial derivatives, such as the activating function, are determined with a higher accuracy and a faster speed as compared to the FEM. The method can be easily combined with existing head modeling pipelines such as headreco or mri2mesh.Significance.The BEM-FMM does not rely on a volumetric mesh and is therefore particularly suitable for modeling some mesoscale problems with submillimeter (and possibly finer) resolution with high accuracy at moderate computational cost. Utilizing Helmholtz reciprocity principle makes it possible to expand the method to a solution of EEG forward problems with a very large number of cortical dipoles.

Deep Brain Stimulation of Caudal Zona Incerta for Parkinson's Disease: One-Year Follow-Up and Electric Field Simulations

OBJECTIVE

To evaluate the effects of bilateral caudal zona incerta (cZi) deep brain stimulation (DBS) for Parkinson's disease (PD) one year after surgery and to create anatomical improvement maps based on patient-specific simulation of the electric field.

MATERIALS AND METHODS

We report the one-year results of bilateral cZi-DBS in 15 patients with PD. Patients were evaluated on/off medication and stimulation using the Unified Parkinson's Disease Rating Scale (UPDRS). Main outcomes were changes in motor symptoms (UPDRS-III) and quality of life according to Parkinson's Disease Questionnaire-39 (PDQ-39). Secondary outcomes included efficacy profile according to sub-items of UPDRS-III, and simulation of the electric field distribution around the DBS lead using the finite element method. Simulations from all patients were transformed to one common magnetic resonance imaging template space for creation of improvement maps and anatomical evaluation.

RESULTS

Median UPDRS-III score off medication improved from 40 at baseline to 21 on stimulation at one-year follow-up (48%, p < 0.0005). PDQ-39 summary index did not change but the subdomains activities of daily living (ADL) and stigma improved (25%, p < 0.03 and 75%, p < 0.01), whereas communication worsened (p < 0.03). For UPDRS-III sub-items, stimulation alone reduced median tremor score by 9 points, akinesia by 3, and rigidity by 2 points at one-year follow-up in comparison to baseline (90%, 25%, and 29% respectively, p < 0.01). Visual analysis of the anatomical improvement maps based on simulated electrical fields showed no evident relation with the degree of symptom improvement and neither did statistical analysis show any significant correlation.

CONCLUSIONS

Bilateral cZi-DBS alleviates motor symptoms, especially tremor, and improves ADL and stigma in PD patients one year after surgery. Improvement maps may be a useful tool for visualizing the spread of the electric field. However, there was no clear-cut relation between anatomical location of the electric field and the degree of symptom relief.

Comparison between patient-specific deep brain stimulation simulations and commercial system SureTune3

Objective. Software to visualize estimated volume of tissue activated (VTA) in deep brain stimulation assuming a homogeneous tissue surrounding such as SureTune3 has recently become available for clinical use. The objective of this study is to compare SureTune3 with homogeneous and heterogeneous patient-specific finite element method (FEM) simulations of the VTA to elucidate how well they coincide in their estimates.Approach. FEM simulations of the VTA were performed in COMSOL Multiphysics and compared with VTA from SureTune3 with variation of voltage and current amplitude, pulse width, axon diameter, number of active contacts, and surrounding homogeneous grey or white matter. Patient-specific simulations with heterogeneous tissue were also performed.Main results. The VTAs corresponded well for voltage control in homogeneous tissue, though with the smallest VTAs being slightly larger in SureTune3 and the largest VTAs being slightly larger in the FEM simulations. In current control, FEM estimated larger VTAs in white matter and smaller VTAs in grey matter compared to SureTune3 as grey matter has higher electric conductivity than white matter and requires less voltage to reach the same current. The VTAs also corresponded well in the patient-specific cases except for one case with a cyst of highly conductive cerebrospinal fluid (CSF) near the active contacts.Significance. The VTA estimates without taking the surrounding tissue into account in SureTune3 are in good agreement with patient-specific FEM simulations when using voltage control in the absence of CSF-filled cyst. In current control or when CSF is present near the active contacts, the tissue characteristics are important for the VTA and needs consideration.Clinical. trial ethical approval: Local ethics committee at Linköping University (2012/434-31).

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.

Cross-frequency coupling between gamma oscillations and deep brain stimulation frequency in Parkinson's disease

The disruption of pathologically enhanced beta oscillations is considered one of the key mechanisms mediating the clinical effects of deep brain stimulation on motor symptoms in Parkinson's disease. However, a specific modulation of other distinct physiological or pathological oscillatory activities could also play an important role in symptom control and motor function recovery during deep brain stimulation. Finely tuned gamma oscillations have been suggested to be prokinetic in nature, facilitating the preferential processing of physiological neural activity. In this study, we postulate that clinically effective high-frequency stimulation of the subthalamic nucleus imposes cross-frequency interactions with gamma oscillations in a cortico-subcortical network of interconnected regions and normalizes the balance between beta and gamma oscillations. To this end we acquired resting state high-density (256 channels) EEG from 31 patients with Parkinson's disease who underwent deep brain stimulation to compare spectral power and power-to-power cross-frequency coupling using a beamformer algorithm for coherent sources. To show that modulations exclusively relate to stimulation frequencies that alleviate motor symptoms, two clinically ineffective frequencies were tested as control conditions. We observed a robust reduction of beta and increase of gamma power, attested in the regions of a cortical (motor cortex, supplementary motor area, premotor cortex) and subcortical network (subthalamic nucleus and cerebellum). Additionally, we found a clear cross-frequency coupling of narrowband gamma frequencies to the stimulation frequency in all of these nodes, which negatively correlated with motor impairment. No such dynamics were revealed within the control posterior parietal cortex region. Furthermore, deep brain stimulation at clinically ineffective frequencies did not alter the source power spectra or cross-frequency coupling in any region. These findings demonstrate that clinically effective deep brain stimulation of the subthalamic nucleus differentially modifies different oscillatory activities in a widespread network of cortical and subcortical regions. Particularly the cross-frequency interactions between finely tuned gamma oscillations and the stimulation frequency may suggest an entrainment mechanism that could promote dynamic neural processing underlying motor symptom alleviation.

Atlas-independent, N-of-1 tissue activation modeling to map optimal regions of subthalamic deep brain stimulation for Parkinson disease

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Neuroanatomical variations among patients are obscured in atlas-based VTA modeling.

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N-of-1 neuroanatomical and VTA modeling enables patient-level precision.

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Mean optimal stimulation is dorsomedial to the STN, near its posterior half.

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Individual VTAs deviate from optimal stimulation sites to varying degrees.

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Optimal stimulation sites for rigidity, bradykinesia, and tremor partially overlap.

Background

Motor outcomes after subthalamic deep brain stimulation (STN DBS) for Parkinson disease (PD) vary considerably among patients and strongly depend on stimulation location. The objective of this retrospective study was to map the regions of optimal STN DBS for PD using an atlas-independent, fully individualized (N-of-1) tissue activation modeling approach and to assess the relationship between patient-level therapeutic volumes of tissue activation (VTAs) and motor improvement.

Methods

The stimulation-induced electric field for 40 PD patients treated with bilateral STN DBS was modeled using finite element analysis. Neurostimulation models were generated for each patient, incorporating their individual STN anatomy, DBS lead position and orientation, anisotropic tissue conductivity, and clinical stimulation settings. A voxel-based analysis of the VTAs was then used to map the optimal location of stimulation. The amount of stimulation in specific regions relative to the STN was measured and compared between STNs with more and less optimal stimulation, as determined by their motor improvement scores and VTA. The relationship between VTA location and motor outcome was then assessed using correlation analysis. Patient variability in terms of STN anatomy, active contact position, and VTA location were also evaluated. Results from the N-of-1 model were compared to those from a simplified VTA model.

Results

Tissue activation modeling mapped the optimal location of stimulation to regions medial, posterior, and dorsal to the STN centroid. These regions extended beyond the STN boundary towards the caudal zona incerta (cZI). The location of the VTA and active contact position differed significantly between STNs with more and less optimal stimulation in the dorsal-ventral and anterior-posterior directions. Therapeutic stimulation spread noticeably more in the dorsal and posterior directions, providing additional evidence for cZI as an important DBS target. There were significant linear relationships between the amount of dorsal and posterior stimulation, as measured by the VTA, and motor improvement. These relationships were more robust than those between active contact position and motor improvement. There was high variability in STN anatomy, active contact position, and VTA location among patients. Spherical VTA modeling was unable to reproduce these results and tended to overestimate the size of the VTA.

Conclusion

Accurate characterization of the spread of stimulation is needed to optimize STN DBS for PD. High variability in neuroanatomy, stimulation location, and motor improvement among patients highlights the need for individualized modeling techniques. The atlas-independent, N-of-1 tissue activation modeling approach presented in this study can be used to develop and evaluate stimulation strategies to improve clinical outcomes on an individual basis.

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

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.

Deep brain stimulation induced normalization of the human functional connectome in Parkinson's disease

Neuroimaging has seen a paradigm shift away from a formal description of local activity patterns towards studying distributed brain networks. The recently defined framework of the 'human connectome' enables global analysis of parts of the brain and their interconnections. Deep brain stimulation (DBS) is an invasive therapy for patients with severe movement disorders aiming to retune abnormal brain network activity by local high frequency stimulation of the basal ganglia. Beyond clinical utility, DBS represents a powerful research platform to study functional connectomics and the modulation of distributed brain networks in the human brain. We acquired resting-state functional MRI in 20 patients with Parkinson's disease with subthalamic DBS switched on and off. An age-matched control cohort of 15 subjects was acquired from an open data repository. DBS lead placement in the subthalamic nucleus was localized using a state-of-the art pipeline that involved brain shift correction, multispectral image registration and use of a precise subcortical atlas. Based on a realistic 3D model of the electrode and surrounding anatomy, the amount of local impact of DBS was estimated using a finite element method approach. On a global level, average connectivity increases and decreases throughout the brain were estimated by contrasting on and off DBS scans on a voxel-wise graph comprising eight thousand nodes. Local impact of DBS on the motor subthalamic nucleus explained half the variance in global connectivity increases within the motor network (R = 0.711, P < 0.001). Moreover, local impact of DBS on the motor subthalamic nucleus could explain the degree to how much voxel-wise average brain connectivity normalized towards healthy controls (R = 0.713, P < 0.001). Finally, a network-based statistics analysis revealed that DBS attenuated specific couplings known to be pathological in Parkinson's disease. Namely, coupling between motor thalamus and motor cortex was increased while striatal coupling with cerebellum, external pallidum and subthalamic nucleus was decreased by DBS. Our results show that resting state functional MRI may be acquired in DBS on and off conditions on clinical MRI hardware and that data are useful to gain additional insight into how DBS modulates the functional connectome of the human brain. We demonstrate that effective DBS increases overall connectivity in the motor network, normalizes the network profile towards healthy controls and specifically strengthens thalamo-cortical connectivity while reducing striatal control over basal ganglia and cerebellar structures.

Modulation of Nigrofugal and Pallidofugal Pathways in Deep Brain Stimulation for Parkinson Disease

BACKGROUND

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is a well-established surgical therapy for patients with Parkinson disease (PD).

OBJECTIVE

To define the role of adjacent white matter stimulation in the effectiveness of STN-DBS.

METHODS

We retrospectively evaluated 43 patients with PD who received bilateral STN-DBS. The volumes of activated tissue were analyzed to obtain significant stimulation clusters predictive of 4 clinical outcomes: improvements in bradykinesia, rigidity, tremor, and reduction of dopaminergic medication. Tractography of the nigrofugal and pallidofugal pathways was performed. The significant clusters were used to calculate the involvement of the nigrofugal and pallidofugal pathways and the STN.

RESULTS

The clusters predictive of rigidity and tremor improvement were dorsal to the STN with most of the clusters outside of the STN. These clusters preferentially involved the pallidofugal pathways. The cluster predictive of bradykinesia improvement was located in the central part of the STN with an extension outside of the STN. The cluster predictive of dopaminergic medication reduction was located ventrolateral and caudal to the STN. These clusters preferentially involved the nigrofugal pathways.

CONCLUSION

Improvements in rigidity and tremor mainly involved the pallidofugal pathways dorsal to the STN. Improvement in bradykinesia mainly involved the central part of the STN and the nigrofugal pathways ventrolateral to the STN. Maximal reduction in dopaminergic medication following STN-DBS was associated with an exclusive involvement of the nigrofugal pathways.

Stimulation maps: visualization of results of quantitative intraoperative testing for deep brain stimulation surgery

Deep brain stimulation (DBS) is an established therapy for movement disorders such as essential tremor (ET). Positioning of the DBS lead in the patient's brain is crucial for effective treatment. Extensive evaluations of improvement and adverse effects of stimulation at different positions for various current amplitudes are performed intraoperatively. However, to choose the optimal position of the lead, the information has to be "mentally" visualized and analyzed. This paper introduces a new technique called "stimulation maps," which summarizes and visualizes the high amount of relevant data with the aim to assist in identifying the optimal DBS lead position. It combines three methods: outlines of the relevant anatomical structures, quantitative symptom evaluation, and patient-specific electric field simulations. Through this combination, each voxel in the stimulation region is assigned one value of symptom improvement, resulting in the division of stimulation region into areas with different improvement levels. This technique was applied retrospectively to five ET patients in the University Hospital in Clermont-Ferrand, France. Apart from identifying the optimal implant position, the resultant nine maps show that the highest improvement region is frequently in the posterior subthalamic area. The results demonstrate the utility of the stimulation maps in identifying the optimal implant position. Graphical abstract.

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.

Patient-Specific Simulations of Deep Brain Stimulation Electric Field with Aid of In-house Software ELMA

Deep brain stimulation (DBS) is an established technique for reduction of symptoms in movement disorders. Finite element method (FEM) simulations of the electric field magnitude (EF) are useful for estimating the affected tissue around the DBS lead and this can help optimize the therapy. This paper describes how patient-specific FEM models can be set up with the aid of the Matlab-based in-house software tool ELMA. Electrode placement is determined from two coordinates in postoperative medical imaging and electric conductivity is assigned from preoperative magnetic resonance imaging (MRI) and patient-specific DBS data. Simulations are performed using the equation for steady currents in Comsol Multiphysics (CM). The simulated EF is superimposed on the preoperative MRI for evaluation of affected structures. The method is demonstrated with patient-specific simulations in the zona incerta and a globus pallidus example containing cysts with higher conductive which causes considerable distortion of the EF. The improved software modules and precise lead positioning simplifies and reduces the time for DBS EF modelling and simulation.

A Randomized Trial Directly Comparing Ventral Capsule and Anteromedial Subthalamic Nucleus Stimulation in Obsessive-Compulsive Disorder: Clinical and Imaging Evidence for Dissociable Effects

BACKGROUND

Deep brain stimulation (DBS) is an emerging treatment for severe obsessive-compulsive disorder (OCD). We compared the efficacy of ventral capsule/ventral striatal (VC/VS) and anteromedial subthalamic nucleus (amSTN) DBS in the same patients and tested for mechanistic differences on mood and cognitive flexibility and associated neural circuitry. The possible synergistic benefit of DBS at both sites and cognitive behavioral therapy was explored.

METHODS

Six patients with treatment-refractory OCD (5 men; Yale-Brown Obsessive Compulsive Scale score >32) entered double-blind counterbalanced phases of 12-week amSTN or VC/VS DBS, followed by 12-week open phases when amSTN and VC/VS were stimulated together, in which optimal stimulation parameters were achieved and adjunctive inpatient cognitive behavioral therapy was delivered. OCD and mood were assessed with standardized scales and cognitive flexibility with the Cambridge Neuropsychological Test Automated Battery Intra-Extra Dimensional Set-Shift task. Diffusion-weighted and intraoperative magnetic resonance imaging scans were performed for tractography from optimally activated electrode contacts.

RESULTS

DBS at each site significantly and equivalently reduced OCD symptoms with little additional gain following combined stimulation. amSTN but not VC/VS DBS significantly improved cognitive flexibility, whereas VC/VS DBS had a greater effect on mood. The VC/VS effective site was within the VC. VC DBS connected primarily to the medial orbitofrontal cortex, and amSTN DBS to the lateral orbitofrontal cortex, dorsal anterior cingulate cortex, and dorsolateral prefrontal cortex. No further improvement followed cognitive behavioral therapy, reflecting a floor effect of DBS on OCD.

CONCLUSIONS

Both the VC/VS and amSTN are effective targets for severe treatment-refractory OCD. Differential improvements in mood and cognitive flexibility and their associated connectivity suggest that DBS at these sites modulates distinct brain networks.

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.

Lead-DBS v2: Towards a comprehensive pipeline for deep brain stimulation imaging

Deep brain stimulation (DBS) is a highly efficacious treatment option for movement disorders and a growing number of other indications are investigated in clinical trials. To ensure optimal treatment outcome, exact electrode placement is required. Moreover, to analyze the relationship between electrode location and clinical results, a precise reconstruction of electrode placement is required, posing specific challenges to the field of neuroimaging. Since 2014 the open source toolbox Lead-DBS is available, which aims at facilitating this process. The tool has since become a popular platform for DBS imaging. With support of a broad community of researchers worldwide, methods have been continuously updated and complemented by new tools for tasks such as multispectral nonlinear registration, structural/functional connectivity analyses, brain shift correction, reconstruction of microelectrode recordings and orientation detection of segmented DBS leads. The rapid development and emergence of these methods in DBS data analysis require us to revisit and revise the pipelines introduced in the original methods publication. Here we demonstrate the updated DBS and connectome pipelines of Lead-DBS using a single patient example with state-of-the-art high-field imaging as well as a retrospective cohort of patients scanned in a typical clinical setting at 1.5T. Imaging data of the 3T example patient is co-registered using five algorithms and nonlinearly warped into template space using ten approaches for comparative purposes. After reconstruction of DBS electrodes (which is possible using three methods and a specific refinement tool), the volume of tissue activated is calculated for two DBS settings using four distinct models and various parameters. Finally, four whole-brain tractography algorithms are applied to the patient's preoperative diffusion MRI data and structural as well as functional connectivity between the stimulation volume and other brain areas are estimated using a total of eight approaches and datasets. In addition, we demonstrate impact of selected preprocessing strategies on the retrospective sample of 51 PD patients. We compare the amount of variance in clinical improvement that can be explained by the computer model depending on the preprocessing method of choice. This work represents a multi-institutional collaborative effort to develop a comprehensive, open source pipeline for DBS imaging and connectomics, which has already empowered several studies, and may facilitate a variety of future studies in the field.

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.

Connectivity derived thalamic segmentation in deep brain stimulation for tremor

The ventral intermediate nucleus (VIM) of the thalamus is an established surgical target for stereotactic ablation and deep brain stimulation (DBS) in the treatment of tremor in Parkinson's disease (PD) and essential tremor (ET). It is centrally placed on a cerebello-thalamo-cortical network connecting the primary motor cortex, to the dentate nucleus of the contralateral cerebellum through the dentato-rubro-thalamic tract (DRT). The VIM is not readily visible on conventional MR imaging, so identifying the surgical target traditionally involved indirect targeting that relies on atlas-defined coordinates. Unfortunately, this approach does not fully account for individual variability and requires surgery to be performed with the patient awake to allow for intraoperative targeting confirmation. The aim of this study is to identify the VIM and the DRT using probabilistic tractography in patients that will undergo thalamic DBS for tremor. Four male patients with tremor dominant PD and five patients (three female) with ET underwent high angular resolution diffusion imaging (HARDI) (128 diffusion directions, 1.5 mm isotropic voxels and b value = 1500) preoperatively. Patients received VIM-DBS using an MR image guided and MR image verified approach with indirect targeting. Postoperatively, using parallel Graphical Processing Unit (GPU) processing, thalamic areas with the highest diffusion connectivity to the primary motor area (M1), supplementary motor area (SMA), primary sensory area (S1) and contralateral dentate nucleus were identified. Additionally, volume of tissue activation (VTA) corresponding to active DBS contacts were modelled. Response to treatment was defined as 40% reduction in the total Fahn-Tolosa-Martin Tremor Rating Score (FTMTRS) with DBS-ON, one year from surgery. Three out of nine patients had a suboptimal, long-term response to treatment. The segmented thalamic areas corresponded well to anatomically known counterparts in the ventrolateral (VL) and ventroposterior (VP) thalamus. The dentate-thalamic area, lay within the M1-thalamic area in a ventral and lateral location. Streamlines corresponding to the DRT connected M1 to the contralateral dentate nucleus via the dentate-thalamic area, clearly crossing the midline in the mesencephalon. Good response was seen when the active contact VTA was in the thalamic area with highest connectivity to the contralateral dentate nucleus. Non-responders had active contact VTAs outside the dentate-thalamic area. We conclude that probabilistic tractography techniques can be used to segment the VL and VP thalamus based on cortical and cerebellar connectivity. The thalamic area, best representing the VIM, is connected to the contralateral dentate cerebellar nucleus. Connectivity based segmentation of the VIM can be achieved in individual patients in a clinically feasible timescale, using HARDI and high performance computing with parallel GPU processing. This same technique can map out the DRT tract with clear mesencephalic crossing.

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.

Subthalamic deep brain stimulation sweet spots and hyperdirect cortical connectivity in Parkinson's disease

OBJECTIVES

Firstly, to identify subthalamic region stimulation clusters that predict maximum improvement in rigidity, bradykinesia and tremor, or emergence of side-effects; and secondly, to map-out the cortical fingerprint, mediated by the hyperdirect pathways which predict maximum efficacy.

METHODS

High angular resolution diffusion imaging in twenty patients with advanced Parkinson's disease was acquired prior to bilateral subthalamic nucleus deep brain stimulation. All contacts were screened one-year from surgery for efficacy and side-effects at different amplitudes. Voxel-based statistical analysis of volumes of tissue activated models was used to identify significant treatment clusters. Probabilistic tractography was employed to identify cortical connectivity patterns associated with treatment efficacy.

RESULTS

All patients responded well to treatment (46% mean improvement off medication UPDRS-III [p < 0.0001]) without significant adverse events. Cluster corresponding to maximum improvement in tremor was in the posterior, superior and lateral portion of the nucleus. Clusters corresponding to improvement in bradykinesia and rigidity were nearer the superior border in a further medial and posterior location. The rigidity cluster extended beyond the superior border to the area of the zona incerta and Forel-H₂ field. When the clusters where averaged, the coordinates of the area with maximum overall efficacy was X = -10(-9.5), Y = -13(-1) and Z = -7(-3) in MNI(AC-PC) space. Cortical connectivity to primary motor area was predictive of higher improvement in tremor; whilst that to supplementary motor area was predictive of improvement in bradykinesia and rigidity; and connectivity to prefrontal cortex was predictive of improvement in rigidity.

INTERPRETATION

These findings support the presence of overlapping stimulation sites within the subthalamic nucleus and its superior border, with different cortical connectivity patterns, associated with maximum improvement in tremor, rigidity and bradykinesia.

Patient-Specific Electric Field Simulations and Acceleration Measurements for Objective Analysis of Intraoperative Stimulation Tests in the Thalamus

Despite an increasing use of deep brain stimulation (DBS) the fundamental mechanisms of action remain largely unknown. Simulation of electric entities has previously been proposed for chronic DBS combined with subjective symptom evaluations, but not for intraoperative stimulation tests. The present paper introduces a method for an objective exploitation of intraoperative stimulation test data to identify the optimal implant position of the chronic DBS lead by relating the electric field (EF) simulations to the patient-specific anatomy and the clinical effects quantified by accelerometry. To illustrate the feasibility of this approach, it was applied to five patients with essential tremor bilaterally implanted in the ventral intermediate nucleus (VIM). The VIM and its neighborhood structures were preoperatively outlined in 3D on white matter attenuated inversion recovery MR images. Quantitative intraoperative clinical assessments were performed using accelerometry. EF simulations (n = 272) for intraoperative stimulation test data performed along two trajectories per side were set-up using the finite element method for 143 stimulation test positions. The resulting EF isosurface of 0.2 V/mm was superimposed to the outlined anatomical structures. The percentage of volume of each structure’s overlap was calculated and related to the corresponding clinical improvement. The proposed concept has been successfully applied to the five patients. For higher clinical improvements, not only the VIM but as well other neighboring structures were covered by the EF isosurfaces. The percentage of the volumes of the VIM, of the nucleus intermediate lateral of the thalamus and the prelemniscal radiations within the prerubral field of Forel increased for clinical improvements higher than 50% compared to improvements lower than 50%. The presented new concept allows a detailed and objective analysis of a high amount of intraoperative data to identify the optimal stimulation target. First results indicate agreement with published data hypothesizing that the stimulation of other structures than the VIM might be responsible for good clinical effects in essential tremor. (Clinical trial reference number: Ref: 2011-A00774-37/AU905)

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.

Investigation of the mechanisms of action behind Electromotive Drug Administration (EMDA)

OBJECTIVE

Bladder cancer is a cause of considerable morbidity worldwide. Electromotive Drug Administration is a method that combines intravesical chemotherapy with local electric field application. Electroporation has been suggested among other mechanisms as having a possible role in the therapy, so the goal of the present study was to investigate the electric fields present in the bladder wall during the treatment to determine which mechanisms might be involved.

MATERIAL AND METHODS

Electromotive Drug Administration involves applying intravesical mitomycin C with direct current of 20 mA delivered through a catheter electrode for 30 min. For numerical electric field computation we built a 3-D nonhomogeneous patient specific model based on CT images and used finite element method simulations to determine the electric fields in the whole body.

RESULTS

Results indicate that highest electric field in the bladder wall was 37.7 V/m. The mean electric field magnitude in the bladder wall was 3.03 V/m. The mean magnitude of the current density in the bladder wall was 0.61 A/m(2).

CONCLUSIONS

The present study shows that electroporation is not the mechanism of action in EMDA. A more likely explanation of the mechanism of action is iontophoretic forces increasing the mitomycin C concentration in the bladder wall.

Innovations in deep brain stimulation methodology

Deep brain stimulation is a powerful clinical method for movement disorders that no longer respond satisfactorily to pharmacological management, but its progress has been hampered by stagnation in technological procedure solutions and device development. Recently, the combined research efforts of bioengineers, neuroscientists, and clinicians have helped to better understand the mechanisms of deep brain stimulation, and solutions for the translational roadblock are emerging. Here, we define the needs for methodological advances in deep brain stimulation from a neurophysiological perspective and describe technological solutions that are currently evaluated for near-term clinical application. © 2016 International Parkinson and Movement Disorder Society.

Target coverage and selectivity in field steering brain stimulation

Deep Brain Stimulation (DBS) is an established treatment in Parkinson's Disease. The target area is defined based on the state and brain anatomy of the patient. The stimulation delivered via state-of-the-art DBS leads that are currently in clinical use is difficult to individualize to the patient particularities. Furthermore, the electric field generated by such a lead has a limited selectivity, resulting in stimulation of areas adjacent to the target and thus causing undesirable side effects. The goal of this study is, using actual clinical data, to compare in silico the stimulation performance of a symmetrical generic lead to a more versatile and adaptable one allowing, in particular, for asymmetric stimulation. The fraction of the volume of activated tissue in the target area and the fraction of the stimulation field that spreads beyond it are computed for a clinical data set of patients in order to quantify the lead performance. The obtained results suggest that using more versatile DBS leads might reduce the stimulation area beyond the target and thus lessen side effects for the same achieved therapeutical effect.

Web-based tool for visualization of electric field distribution in deep-seated body structures and planning of electroporation-based treatments

BACKGROUND

Treatments based on electroporation are a new and promising approach to treating tumors, especially non-resectable ones. The success of the treatment is, however, heavily dependent on coverage of the entire tumor volume with a sufficiently high electric field. Ensuring complete coverage in the case of deep-seated tumors is not trivial and can in best way be ensured by patient-specific treatment planning. The basis of the treatment planning process consists of two complex tasks: medical image segmentation, and numerical modeling and optimization.

METHODS

In addition to previously developed segmentation algorithms for several tissues (human liver, hepatic vessels, bone tissue and canine brain) and the algorithms for numerical modeling and optimization of treatment parameters, we developed a web-based tool to facilitate the translation of the algorithms and their application in the clinic. The developed web-based tool automatically builds a 3D model of the target tissue from the medical images uploaded by the user and then uses this 3D model to optimize treatment parameters. The tool enables the user to validate the results of the automatic segmentation and make corrections if necessary before delivering the final treatment plan.

RESULTS

Evaluation of the tool was performed by five independent experts from four different institutions. During the evaluation, we gathered data concerning user experience and measured performance times for different components of the tool. Both user reports and performance times show significant reduction in treatment-planning complexity and time-consumption from 1-2 days to a few hours.

CONCLUSIONS

The presented web-based tool is intended to facilitate the treatment planning process and reduce the time needed for it. It is crucial for facilitating expansion of electroporation-based treatments in the clinic and ensuring reliable treatment for the patients. The additional value of the tool is the possibility of easy upgrade and integration of modules with new functionalities as they are developed.

Careful treatment planning enables safe ablation of liver tumors adjacent to major blood vessels by percutaneous irreversible electroporation (IRE)

Background

Irreversible electroporation (IRE) is a tissue ablation method, which relies on the phenomenon of electroporation. When cells are exposed to a sufficiently electric field, the plasma membrane is disrupted and cells undergo an apoptotic or necrotic cell death. Although heating effects are known IRE is considered as non-thermal ablation technique and is currently applied to treat tumors in locations where thermal ablation techniques are contraindicated.

Materials and methods.

The manufacturer of the only commercially available pulse generator for IRE recommends a voltage-to-distance ratio of 1500 to 1700 V/cm for treating tumors in the liver. However, major blood vessels can influence the electric field distribution. We present a method for treatment planning of IRE which takes the influence of blood vessels on the electric field into account; this is illustrated on a treatment of 48-year-old patient with a metastasis near the remaining hepatic vein after a right side hemi-hepatectomy.

Results

Output of the numerical treatment planning method shows that a 19.9 cm3 irreversible electroporation lesion was generated and the whole tumor was covered with at least 900 V/cm. This compares well with the volume of the hypodense lesion seen in contrast enhanced CT images taken after the IRE treatment. A significant temperature raise occurs near the electrodes. However, the hepatic vein remains open after the treatment without evidence of tumor recurrence after 6 months.

Conclusions

Treatment planning using accurate computer models was recognized as important for electrochemotherapy and irreversible electroporation. An important finding of this study was, that the surface of the electrodes heat up significantly. Therefore the clinical user should generally avoid placing the electrodes less than 4 mm away from risk structures when following recommendations of the manufacturer.

Subject-specific computational modeling of DBS in the PPTg area

Deep brain stimulation (DBS) in the pedunculopontine tegmental nucleus (PPTg) has been proposed to alleviate medically intractable gait difficulties associated with Parkinson's disease. Clinical trials have shown somewhat variable outcomes, stemming in part from surgical targeting variability, modulating fiber pathways implicated in side effects, and a general lack of mechanistic understanding of DBS in this brain region. Subject-specific computational models of DBS are a promising tool to investigate the underlying therapy and side effects. In this study, a parkinsonian rhesus macaque was implanted unilaterally with an 8-contact DBS lead in the PPTg region. Fiber tracts adjacent to PPTg, including the oculomotor nerve, central tegmental tract, and superior cerebellar peduncle, were reconstructed from a combination of pre-implant 7T MRI, post-implant CT, and post-mortem histology. These structures were populated with axon models and coupled with a finite element model simulating the voltage distribution in the surrounding neural tissue during stimulation. This study introduces two empirical approaches to evaluate model parameters. First, incremental monopolar cathodic stimulation (20 Hz, 90 μs pulse width) was evaluated for each electrode, during which a right eyelid flutter was observed at the proximal four contacts (−1.0 to −1.4 mA). These current amplitudes followed closely with model predicted activation of the oculomotor nerve when assuming an anisotropic conduction medium. Second, PET imaging was collected OFF-DBS and twice during DBS (two different contacts), which supported the model predicted activation of the central tegmental tract and superior cerebellar peduncle. Together, subject-specific models provide a framework to more precisely predict pathways modulated by DBS.

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.

Word-level intelligibility after caudal zona incerta stimulation for Parkinson's disease

OBJECTIVES

To investigate the effect of caudal zona incerta-deep brain stimulation (cZi-DBS) on word-level speech intelligibility in patients with Parkinson's disease, under both an optimal listening condition and a simulated more naturalistic listening condition.

MATERIALS AND METHODS

Spoken single words were extracted from read samples collected from 10 bilaterally implanted patients with PD pre- and post-cZi-DBS. Intelligibility was assessed through a transcription task performed by 32 naive listeners under two listening conditions: (i) with low-amplitude conversational speech added as background and (ii) with no added background noise. The listeners' responses were scored in terms of agreement with the intended words.

RESULTS

Post-operatively, the total intelligibility score was significantly lower when cZi stimulation was switched on compared with off, for both listening conditions (with and without added background noise). Intelligibility was also significantly lower on stimulation compared with preoperative recordings, but only when assessed in the listening condition without background noise. The listening condition with added background noise resulted in significantly lower intelligibility scores compared with the no added noise condition for all stimulation conditions.

CONCLUSIONS

The results of this study indicate that cZi-DBS in patients with PD can be detrimental to word-level speech intelligibility.