Volume Of Tissue Activated Research Articles

Probabilistic mapping of the antidystonic effect of pallidal neurostimulation: a multicentre imaging study.

Deep brain stimulation of the internal globus pallidus is a highly effective and established therapy for primary generalized and cervical dystonia, but therapeutic success is compromised by a non-responder rate of up to 25%, even in carefully-selected groups. Variability in electrode placement and inappropriate stimulation settings may account for a large proportion of this outcome variability. Here, we present probabilistic mapping data on a large cohort of patients collected from several European centres to resolve the optimal stimulation volume within the pallidal region. A total of 105 dystonia patients with pallidal deep brain stimulation were enrolled and 87 datasets (43 with cervical dystonia and 44 with generalized dystonia) were included into the subsequent 'normative brain' analysis. The average improvement of dystonia motor score was 50.5 ± 30.9% in cervical and 58.2 ± 48.8% in generalized dystonia, while 19.5% of patients did not respond to treatment (<25% benefit). We defined probabilistic maps of anti-dystonic effects by aggregating individual electrode locations and volumes of tissue activated (VTA) in normative atlas space and ranking voxel-wise for outcome distribution. We found a significant relation between motor outcome and the stimulation volume, but not the electrode location per se. The highest probability of stimulation induced motor benefit was found in a small volume covering the ventroposterior globus pallidus internus and adjacent subpallidal white matter. We then used the aggregated VTA-based outcome maps to rate patient individual VTAs and trained a linear regression model to predict individual outcomes. The prediction model showed robustness between the predicted and observed clinical improvement, with an r2 of 0.294 (P < 0.0001). The predictions deviated on average by 16.9 ± 11.6 % from observed dystonia improvements. For example, if a patient improved by 65%, the model would predict an improvement between 49% and 81%. Results were validated in an independent cohort of 10 dystonia patients, where prediction and observed benefit had a correlation of r2 = 0.52 (P = 0.02) and a mean prediction error of 10.3% (±8.9). These results emphasize the potential of probabilistic outcome brain mapping in refining the optimal therapeutic volume for pallidal neurostimulation and advancing computer-assisted planning and programming of deep brain stimulation.

Electrode Reconstruction Assists Postoperative Contact Selection in Deep Brain Stimulation

Postoperative contact selection of deep brain stimulation (DBS), testing one contact at a time, is a clinically time-consuming procedure being challenged by incoming applications of more complex DBS leads. The objective of this study is to guide clinicians to select the optimal contact by neuroanatomic information derived from electrode reconstruction. We reviewed 33 patients with Parkinson disease who underwent bilateral subthalamic nucleus (STN) DBS with preoperative magnetic resonance imaging and postoperative computed tomography scan. All electrodes were reconstructed in standardized Montreal Neurological Institute and Hospital space, and the volume of tissue activated (VTA) was estimated for each contact. According to the DISTAL atlas, we calculated 6 neuroanatomic parameters: the distances of each contact to the STN and the motor part of the STN (M-STN), the volumes of the overlapping areas of the VTA and STN/M-STN, and the number and ratio of fiber tracts through both the VTA and motor areas (primary motor cortex and supplementary motor area). All 6 parameters showed significant group differences between clinical optimal and nonoptimal contacts by permutation test. Moreover, the possibility of being the optimal contact was estimated for all contacts under the combination of these 6 parameters using a generalized linear model, which resulted in accuracy of 72.7% for prediction of contact selection. Electrode reconstruction could assist in selecting the clinical optimal contact and improving its efficiency.

Unilateral Thalamic Deep Brain Stimulation for Voice Tremor

Background: Voice tremor (VT) is the involuntary and rhythmical phonatory instability of the voice. Recent findings suggest that unilateral deep brain stimulation of the ventral intermediate nucleus (Vim-DBS) can sometimes be effective for VT. In this exploratory analysis, we investigated the effect of Vim-DBS on VT and tested the hypothesis that unilateral thalamic stimulation is effective for patients with VT. Methods: Seven patients with VT and previously implanted bilateral Vim-DBS were enrolled in the study. Each patient was randomized and recorded performing sustained phonation during the following conditions: left thalamic stimulation, right thalamic stimulation, bilateral thalamic stimulation (Bil-ON), and no stimulation (Bil-OFF). Perceptual VT ratings and an acoustic analysis to find the rate of variation of the fundamental frequency measured by the standard deviation of the pitch (f0SD) were performed in a blinded manner. For the purposes of this study, a “dominant” side was defined as one with more than twice as much reduction in VT following Vim-DBS compared to the contralateral side. The Wilcoxon signed-rank test was performed to compare the effect of the dominant side stimulation in the reduction of VT scores and f0SD. The volume of activated tissue (VAT) of the dominant stimulation side was modelled against the degree of improvement in VT to correlate the significant stimulation cluster with thalamic anatomy. Finally, tractography analysis was performed to analyze the connectivity of the significant stimulation cluster. Results: Unilateral stimulation was beneficial in all 7 patients. Five patients clearly had a “dominant” side with either benefit only seen following stimulation of one side or more than twice as much benefit from one side compared to the other. Two patients had similar benefit with unilateral stimulation from either side. The Wilcoxon paired test showed significant differences between unilateral dominant and unilateral nondominant stimulation for VT scores (p = 0.04), between unilateral dominant and Bil-OFF (p = 0.04), and between Bil-ON and unilateral nondominant stimulation (p = 0.04). No significant differences were found between Bil-ON and unilateral dominant condition (p = 0.27), or between Bil-OFF and unilateral nondominant (p = 0.23). The dominant VAT showed that the significant voxels associated with the best VT control were located in the most ventral and medial part of the Vim nucleus and the ventralis caudalis anterior internus nucleus. The connectivity analysis showed significant connectivity with the cortical areas of the speech circuit. Conclusions: Unilateral dominant-side thalamic stimulation and bilateral thalamic stimulation were equally effective in reducing VT. Nondominant unilateral stimulation alone did not significantly improve VT.

On the (Non-)equivalency of monopolar and bipolar settings for deep brain stimulation fMRI studies of Parkinson's disease patients.

The majority of Parkinson's disease patients with deep brain stimulation (DBS) use a monopolar configuration, which presents challenges for EEG and MRI studies. The literature reports algorithms to convert monopolar to bipolar settings. To assess brain responses of Parkinson's disease patients implanted with DBS during fMRI studies using their clinical and presumed equivalent settings using a published conversion recipe. Prospective. Thirteen DBS patients. 1.5T and 3T, fMRI using gradient echo-planar imaging. Patients underwent 30/30sec ON/OFF DBS fMRI scans using monopolar and bipolar settings. To convert to a bipolar setting, the negative contact used for the monopolar configuration remained constant and the adjacent dorsal contact was rendered positive, while increasing the voltage by 30%. fMRI activation/deactivation maps and motor Unified Parkinson's Disease Rating Scale (UPDRS-III) scores were compared for patients in both configurations. T-tests were used to compare UPDRS scores and volumes of tissue activated (VTA) diameters in monopolar and bipolar configurations. The patterns of fMRI activation in the monopolar and bipolar configurations were generally different. The thalamus, pallidum, and visual cortices exhibited higher activation using the patient's clinical settings than the presumed equivalent settings. VTA diameters were lower (7 mm vs. 6.3 mm, P = 0.047) and UPDRS scores were generally higher in the bipolar (33.2 ± 16) than in the monopolar configuration (28.3 ± 17.4), without reaching statistical significance (P > 0.05). Monopolar and bipolar configurations result in different patterns of brain activation while using a previously published monopolar-bipolar conversion algorithm. Clinical benefits may be achieved with varying patterns of brain responses. Blind conversion from one to the other should be avoided for purposes of understanding the mechanisms of DBS. 1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018.

Differences in functional connectivity profiles as a predictor of response to anterior thalamic nucleus deep brain stimulation for epilepsy: a hypothesis for the mechanism of action and a potential biomarker for outcomes.

OBJECTIVE Deep brain stimulation (DBS) of the anterior nucleus of the thalamus (ANT) is a promising therapy for refractory epilepsy. Unfortunately, the variability in outcomes from ANT DBS is not fully understood. In this pilot study, the authors assess potential differences in functional connectivity related to the volume of tissue activated (VTA) in ANT DBS responders and nonresponders as a means for better understanding the mechanism of action and potentially improving DBS targeting. METHODS This retrospective analysis consisted of 6 patients who underwent ANT DBS for refractory epilepsy. Patients were classified as responders (n = 3) if their seizure frequency decreased by at least 50%. The DBS electrodes were localized postoperatively and VTAs were computationally generated based on DBS programming settings. VTAs were used as seed points for resting-state functional MRI connectivity analysis performed using a control dataset. Differences in cortical connectivity to the VTA were assessed between the responder and nonresponder groups. RESULTS The ANT DBS responders showed greater positive connectivity with the default mode network compared to nonresponders, including the posterior cingulate cortex, medial prefrontal cortex, inferior parietal lobule, and precuneus. Interestingly, there was also a consistent anticorrelation with the hippocampus seen in responders that was not present in nonresponders. CONCLUSIONS Based on their pilot study, the authors observed that successful ANT DBS in patients with epilepsy produces increased connectivity in the default mode network, which the authors hypothesize increases the threshold for seizure propagation. Additionally, an inhibitory effect on the hippocampus mediated through increased hippocampal γ-aminobutyric acid (GABA) concentration may contribute to seizure suppression. Future studies are planned to confirm these findings.

Quantifying axonal responses in patient-specific models of subthalamic deep brain stimulation

Medical imaging has played a major role in defining the general anatomical targets for deep brain stimulation (DBS) therapies. However, specifics on the underlying brain circuitry that is directly modulated by DBS electric fields remain relatively undefined. Detailed biophysical modeling of DBS provides an approach to quantify the theoretical responses to stimulation at the cellular level, and has established a key role for axonal activation in the therapeutic mechanisms of DBS. Estimates of DBS-induced axonal activation can then be coupled with advances in defining the structural connectome of the human brain to provide insight into the modulated brain circuitry and possible correlations with clinical outcomes. These pathway-activation models (PAMs) represent powerful tools for DBS research, but the theoretical predictions are highly dependent upon the underlying assumptions of the particular modeling strategy used to create the PAM. In general, three types of PAMs are used to estimate activation: 1) field-cable (FC) models, 2) driving force (DF) models, and 3) volume of tissue activated (VTA) models. FC models represent the “gold standard” for analysis but at the cost of extreme technical demands and computational resources. Consequently, DF and VTA PAMs, derived from simplified FC models, are typically used in clinical research studies, but the relative accuracy of these implementations is unknown. Therefore, we performed a head-to-head comparison of the different PAMs, specifically evaluating DBS of three different axonal pathways in the subthalamic region. The DF PAM was markedly more accurate than the VTA PAMs, but none of these simplified models were able to match the results of the patient-specific FC PAM across all pathways and combinations of stimulus parameters. These results highlight the limitations of using simplified predictors to estimate axonal stimulation and emphasize the need for novel algorithms that are both biophysically realistic and computationally simple.

Thalamic Directional Deep Brain Stimulation for tremor: Spend less, get more

BackgroundDirectional Deep Brain Stimulation (D-DBS) allows axially asymmetric electrical field shaping, away from structures causing side-effects. However, concerns regarding the impact on device lifespan and complexity of the monopolar survey have contributed to sparing use of these features. ObjectiveTo investigate whether chronically implanted D-DBS systems can improve the therapeutic window, without a negative impact on device lifespan, in thalamic deep brain stimulation (DBS). MethodsWe evaluated stable outcomes of initial programming sessions (4–6 weeks post-implantation) retrospectively in 8 patients with drug-resistant disabling tremor syndromes. We assessed the impact of directional stimulation on the Therapeutic Window (TW), Therapeutic Current Strength (TCS), tremor scores, disability scores and total electrical energy delivered. Finally, we performed Volume of Tissue Activation (VTA) modelling, based on a range of parameters. ResultsWe report significant gains in TW (91%) and reductions in TCS (31%) with stimulation in the best direction compared to best omnidirectional stimulation alternative. Tremor and ADL scores improvements remained unchanged at six months. There was no increase in averaged IPG power consumption (there is a 6% reduction over the omnidirectional-only alternative). Illustrative VTA modelling shows that D-DBS achieves 85% of the total activation volume at just 69% of the stimulation amplitude of non-directional configuration.Conclusions: D-DBS can improve the therapeutic window over non-directional DBS, leading to significant reduction in disability that may be sustained without additional reprogramming visits. When averaged across the cohort, power output and predicted device lifespan was not impacted by the use of directional stimulation in this study.

Structural connectivity-based segmentation of the thalamus and prediction of tremor improvement following thalamic deep brain stimulation of the ventral intermediate nucleus.

ObjectivesTraditional targeting methods for thalamic deep brain stimulation (DBS) performed to address tremor have predominantly relied on indirect atlas-based methods that focus on the ventral intermediate nucleus despite known variability in thalamic functional anatomy. Improvements in preoperative targeting may help maximize outcomes and reduce thalamic DBS–related complications. In this study, we evaluated the ability of thalamic parcellation with structural connectivity–based segmentation (SCBS) to predict tremor improvement following thalamic DBS.MethodsIn this retrospective analysis of 40 patients with essential tremor, hard segmentation of the thalamus was performed by using probabilistic tractography to assess structural connectivity to 7 cortical targets. The volume of tissue activated (VTA) was modeled in each patient on the basis of the DBS settings. The volume of overlap between the VTA and the 7 thalamic segments was determined and correlated with changes in preoperative and postoperative Fahn-Tolosa-Marin Tremor Rating Scale (TRS) scores by using multivariable linear regression models.ResultsA significant association was observed between greater VTA in the supplementary motor area (SMA) and premotor cortex (PMC) thalamic segment and greater improvement in TRS score when considering both the raw change (P = .001) and percentage change (P = .011). In contrast, no association was observed between change in TRS score and VTA in the primary motor cortex thalamic segment (P ≥ .19).ConclusionsOur data suggest that greater VTA in the thalamic SMA/PMC segment during thalamic DBS was associated with significant improvement in TRS score in patients with tremor. These findings support the potential role of thalamic SCBS as an independent predictor of tremor improvement in patients who receive thalamic DBS.

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.

Dysarthria in pallidal Deep Brain Stimulation in dystonia depends on the posterior location of active electrode contacts: a pilot study

BackgroundPallidal Deep Brain Stimulation (GPi-DBS) is an efficient treatment for primary dystonia. We investigated stimulation-induced dysarthria, which is the most frequent side-effect of GPi-DBS. MethodsSpeech was recorded while reading a standard text, and performing rapid syllable repetitions ON and OFF DBS in ten dystonia patients (6 men; 3 cervical, 4 segmental, 3 generalized, unselected for DBS-related speech impairments). Speech and articulation rate, pauses, and syllable repetition rates were extracted via acoustic analysis. Locations of active stimulation contacts and volumes of tissue activated (VTA) were calculated. ResultsThe number of pauses increased significantly ON vs. OFF stimulation (Wilcoxon test, p < 0.05). More posteriorly localized active contacts were associated with slower syllable repetition (Pearson correlation, p < 0.05). VTA size did not correlate with any measure of dysarthria. ConclusionUsing quantitative acoustic signal analysis, this study demonstrates that GPi-DBS alters motor aspects of speech. Both inadvertent stimulation of parts of the internal capsule, or interference with GPi function and outflow are possible causes. Understanding causes of GPi-DBS-induced speech changes can improve DBS programming.

Optimal deep brain stimulation site and target connectivity for chronic cluster headache.

Objective:To investigate the mechanism of action of deep brain stimulation for refractory chronic cluster headache and the optimal target within the ventral tegmental area.Methods:Seven patients with refractory chronic cluster headache underwent high spatial and angular resolution diffusion MRI preoperatively. MRI-guided and MRI-verified electrode implantation was performed unilaterally in 5 patients and bilaterally in 2. Volumes of tissue activation were generated around active lead contacts with a finite-element model. Twelve months after surgery, voxel-based morphometry was used to identify voxels associated with higher reduction in headache load. Probabilistic tractography was used to identify the brain connectivity of the activation volumes in responders, defined as patients with a reduction of ≥30% in headache load.Results:There was no surgical morbidity. Average follow-up was 34 ± 14 months. Patients showed reductions of 76 ± 33% in headache load, 46 ± 41% in attack severity, 58 ± 41% in headache frequency, and 51 ± 46% in attack duration at the last follow-up. Six patients responded to treatment. Greatest reduction in headache load was associated with activation in an area cantered at 6 mm lateral, 2 mm posterior, and 1 mm inferior to the midcommissural point of the third ventricle. Average responders' activation volume lay on the trigeminohypothalamic tract, connecting the trigeminal system and other brainstem nuclei associated with nociception and pain modulation with the hypothalamus, and the prefrontal and mesial temporal areas.Conclusions:We identify the optimal stimulation site and structural connectivity of the deep brain stimulation target for cluster headache, explicating possible mechanisms of action and disease pathophysiology.

Accelerating the computation of the volume of tissue activated during deep brain stimulation using Gaussian processes

The volume of tissue activated (VTA) is a well-established approach to model the direct effect of deep brain stimulation (DBS) on neural tissue. Previous studies have pointed to its potential clinical applications. However, the elevated computational runtime required to estimate the VTA with standard techniques used in biological neural modeling limits its suitability for practical use. The goal of this study was to develop a novel methodology to reduce the computation time of VTA estimation. To that end, we built a Gaussian process emulator. It combines multicompartment axon models coupled to the stimulating electric field with a Gaussian process classifier (GPC), following the premise that computing the VTA from a field of axons is in essence a binary classification problem. We achieved a considerable reduction in the average time required to estimate the VTA, under both ideal isotropic and realistic anisotropic brain tissue conductive conditions, limiting the loss of accuracy and overcoming other drawbacks entailed by alternative methods.

Deep Brain Stimulation for Tremor: Is There a Common Structure?

Background: Subthalamic nucleus (STN) stimulation has been recognized to control resting tremor in Parkinson disease. Similarly, thalamic stimulation (ventral intermediate nucleus; VIM) has shown tremor control in Parkinson disease, essential, and intention tremors. Recently, stimulation of the posterior subthalamic area (PSA) has been associated with excellent tremor control. Thus, the optimal site of stimulation may be located in the surrounding white matter. Aims: The objective of this work was to investigate the area of stimulation by determining the contact location correlated with the best tremor control in STN/VIM patients. Methods: The mean stimulation site and related volume of tissue activated (VTA) of 25 tremor patients (STN or VIM) were projected on the Morel atlas and compared to stimulation sites from other tremor studies. Results: All patients showed a VTA that covered ≥50% of the area superior and medial to the STN or inferior to the VIM. Our stimulation areas suggest involvement of the more lateral and superior part of the dentato-rubro-thalamic tract (DRTT), whereas targets described in other studies seem to involve the DRTT in its more medial and inferior part when it crosses the PSA. Conclusions: According to anatomical and diffusion tensor imaging data, the DRTT might be the common structure stimulated at different portions within the PSA/caudal zona incerta.

Intraoperative clinical testing overestimates the therapeutic window of the permanent DBS electrode in the subthalamic nucleus

Intraoperative test stimulation is established to optimize target localization in STN DBS, but requires a time-consuming awake surgery in off-medication state. The aim of this study was to compare the thresholds of stimulation-induced effects of test stimulation and the permanent electrode. Fifty-nine PD patients receiving bilateral STN DBS were clinically examined with stepwise increasing monopolar stimulation during surgery and DBS programming at matched stimulation depths. Thresholds of therapeutic and side effects were obtained from standardized examination protocols. Postoperative stimulation via the permanent electrode caused side effects at a significantly lower threshold than predicted during intraoperative test stimulation (P<0.001); whereas sufficient therapeutic effects were achieved at significantly higher thresholds (P<0.001). Intraoperative testing may lead to an overestimation of the therapeutic window. The two different electrodes lead to distinct spreading of the electric field in the STN and surrounding tissues that causes different volume of tissue activated (VTA). Clinicians involved in DBS surgery and programming should be aware of the differences in both stimulation settings, concerning electrodes geometry, stimulation modes as well as the impact of time. Therapeutic and side effects of permanent stimulation are not predictable by intraoperative test stimulation. Test stimulation may be an orientating test for very low thresholds of side effects instead.

EP 54. Modeling the effects of current steering with directional leads

Background Deep brain stimulation (DBS) systems differ in designs and stimulation abilities. New developments in DBS are focusing on enabling directional stimulation capabilities that may possibly activate targets with greater specificity. We sought to use computational modeling to demonstrate that combining directional leads with Multiple Independent Current Control (MICC) may offer additional control over the shape of the Volume of Tissue Activated (VTA) using proposed lead designs from three different manufacturers. We also explore the effect of single and multiple source current control on directional stimulation with these leads. Methods Finite element models (COMSOL) were created for each lead and used to calculate the potentials in space (isotropic, homogenous, 0.1 S/m encapsulation layer, 500 μm thickness; 0.2 S/m bulk) due to unit currents on each electrode. These potentials were then used to evaluate neural activation using axon cable models (NEURON; MRG axon ( McIntyre et al., 2002 ). Results Modeled threshold fields iso-surfaced at relevant stimulation levels demonstrates the ability of MICC to enable selection and shaping of field profiles that are not possible when using single source systems. Conclusions Modeling results suggest additional clinical benefit may be achieved when coupling directional leads with MICC designs. These additional fields may result in clinical benefits for some patients, and further study will be needed to evaluate their effects.

Estimation of the neuromodulation parameters from the planned volume of tissue activated in deep brain stimulation

Deep brain stimulation (DBS) is a therapy with promissory results for the treatment of movement disorders. It delivers electric stimulation via an electrode to a specific target brain region. The spatial extent of neural response to this stimulation is known as volume of tissue activated (VTA). Changes in stimulation parameters that control VTA, such as amplitude, pulse width and electrode configuration can affect the effectiveness of the DBS therapy. In this study, we develop a novel methodology for estimating suitable DBS neuromodulation parameters, from planned VTA, that attempts to maximize the therapeutic effects, and to minimize the adverse effects of DBS. For estimating the continuous outputs (amplitude and pulse width), we use multi-output support vector regression, taking the geometry of the VTA as input space. For estimating the electrode polarity configuration, we perform several classification problems, also using support vector machines from the same input space. Our methodology attains promising results for both the regression setting, and for predicting electrode active contacts and their polarity. Combining biological neural modeling techniques together with machine learning, we introduce a novel area of research where parameters of neuromodulation in DBS can be tuned by manually specifying a desired geometric volume.

Efficient Computation of the Neural Activation During Deep Brain Stimulation for Dispersive Electrical Properties of Brain Tissue

Deep brain stimulation (DBS) is a widely employed neurosurgical method to treat symptoms of neurodegenerative disorders. Computational modeling of DBS can help to gain insight into the mechanisms of its action. Among these models, the estimation of the volume of tissue activated (VTA) comprises a method to predict the extent of beneficial stimulation and unwanted side effects. This method requires the computation of the time-dependent extracellular potential in the proximity of the stimulation electrode, which is, in general, computationally expensive due to the dispersive electrical properties of brain tissue. We present an adaptive scheme based on two interpolation methods, which approximates the transfer function of the extracellular potential distribution in the frequency domain. The results suggest that the proposed method is able to substantially reduce the computational expense for the computation of the extracellular field distribution and VTA compared with the standard approach.

Computing stimulation voltage in a bipolar electrode configuration to avoid side effects during deep brain stimulation

Deep brain stimulation (DBS) in the subthalamic nucleus (STN) has been applied for advanced Parkinson’s disease (PD). In clinical practices, monopolar configuration is often utilized based on clinical efficiency. Meanwhile, the volume of tissue activated (VTA) by DBS is estimated for controlling and/or limiting the stimulated region. However, side effects like dyskinesia and tremor were accompanied during stimulation. Most studies had found that bipolar stimulation is an alternative approach for side effects avoidance. The goal of this paper is to develop a quantified relationship of stimulation voltage from monopolar to bipolar configuration to improve neural stimulation. In this paper, an electromagnetic finite element model is first built for a patient-specific physiological brain model, which is established by magnetic resonance imaging (MRI) data. The model is then used for finite element analysis (FEA) to estimate VTA with varied electrode voltage in monopolar and bipolar configurations. With the goals to avoid side effects and achieve symptoms suppression, the stimulation voltage of bipolar configuration is successfully computerized based on the electromagnetic FEA simulations. Experiments are conducted successfully to validate simulation results.

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 5V), pulse widths (30 to 120μs), and axon diameters (2.0 to 7.5μm). 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.

Defining a therapeutic target for pallidal deep brain stimulation for dystonia.

To create a data-driven computational model that identifies brain regions most frequently influenced by successful deep brain stimulation (DBS) of the globus pallidus (GP) for advanced, medication-resistant, generalized dystonia. We studied a retrospective cohort of 21 DYT1 primary dystonia patients treated for at least 1 year with bilateral pallidal DBS. We first created individual volume of tissue activation (VTA) models utilizing neuroimaging and postoperative stimulation and clinical data. These models were then combined into a standardized probabilistic dystonia stimulation atlas (DSA). Finally, we constructed a candidate target volume from electrodes demonstrating at least 75% improvement in contralateral symptoms, utilizing voxels stimulated by least 75% of these electrodes. Pallidal DBS resulted in a median contralateral hemibody improvement of 90% (mean = 83%, standard deviation [SD] = 20) after 1 year of treatment. Individual VTA models of the 42 active electrodes included in the study demonstrated a mean stimulation volume of 501mm ([SD] = 284). The resulting DSA showed that areas most frequently stimulated were located squarely in the middle of the posterior GP, with a common target volume measuring 153mm(3) . Our results provide a map of the region of influence of therapeutic DBS for dystonia and represent a potential target to refine current methods of surgical planning and stimulation parameters selection. Based on their role in alleviating symptoms, these regions may also provide anatomical and physiological information relevant to disease models of dystonia. Further experimental and clinical studies will be needed to validate their importance.