Modeling of Electric Fields in Individual Imaging Atlas for Capsular Threshold Prediction of Deep Brain Stimulation in Parkinson's Disease: A Pilot Study

The Therapeutic Potential of Non-Invasive and Invasive Cerebellar Stimulation Techniques in Hereditary Ataxias

The degenerative ataxias comprise a heterogeneous group of inherited and acquired disorders that are characterized by a progressive cerebellar syndrome, frequently in combination with one or more extracerebellar signs. Specific disease-modifying interventions are currently not available for many of these rare conditions, which underscores the necessity of finding effective symptomatic therapies. During the past five to ten years, an increasing number of randomized controlled trials have been conducted examining the potential of different non-invasive brain stimulation techniques to induce symptomatic improvement. In addition, a few smaller studies have explored deep brain stimulation (DBS) of the dentate nucleus as an invasive means to directly modulate cerebellar output, thereby aiming to alleviate ataxia severity. In this paper, we comprehensively review the clinical and neurophysiological effects of transcranial direct current stimulation (tDCS), repetitive transcranial magnetic stimulation (rTMS), and dentate nucleus DBS in patients with hereditary ataxias, as well as the presumed underlying mechanisms at the cellular and network level and perspectives for future research.

Stability and Effect of Parkinsonian State on Deep Brain Stimulation Cortical Evoked Potentials

OBJECTIVES

To characterize and compare the stability of cortical potentials evoked by deep brain stimulation (DBS) of the subthalamic nucleus (STN) across the naïve, parkinsonian, and pharmacologically treated parkinsonian states. To advance cortical potentials as possible biomarkers for DBS programming.

MATERIALS AND METHODS

Serial electrocorticographic (ECoG) recordings were made more than nine months from a single non-human primate instrumented with bilateral ECoG grids spanning anterior parietal to prefrontal cortex. Cortical evoked potentials (CEPs) were generated through time-lock averaging of the ECoG recordings to DBS pulses delivered unilaterally in the STN region using a chronically implanted, six-contact, scaled DBS lead. Recordings were made across the naïve followed by mild and moderate parkinsonian conditions achieved by staged injections of the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) neurotoxin. In addition to characterizing the spatial distribution and stability of the response within each state, changes in the amplitude and latency of CEP components as well as in the frequency content were examined in relation to parkinsonian severity and dopamine replacement.

RESULTS

In the naïve state, the STN DBS CEP presented as a multiphase response maximal over M1 cortex, with components attributable to physiological activity distinguishable from stimulus artifact as early as 0.45-0.75 msec poststimulation. When delivered using therapeutically effective parameters in the parkinsonian state, the CEP was highly stable across multiple recording sessions within each behavioral state. Across states, significant differences were present with respect to both the latency and amplitude of individual response components, with greater differences present for longer-latency components (all p < 0.05). Power spectral density analysis revealed a high-beta peak within the evoked response, with significant changes in power between disease states across multiple frequency bands.

CONCLUSIONS

Our findings underscore the spatiotemporal specificity and relative stability of the DBS-CEP associated with different disease states and with therapeutic benefit. DBS-CEP may be a viable biomarker for therapeutic programming.

Image-based biophysical modeling predicts cortical potentials evoked with subthalamic deep brain stimulation

BACKGROUND

Subthalamic deep brain stimulation (DBS) is an effective surgical treatment for Parkinson's disease and continues to advance technologically with an enormous parameter space. As such, in-silico DBS modeling systems have become common tools for research and development, but their underlying methods have yet to be standardized and validated.

OBJECTIVE

Evaluate the accuracy of patient-specific estimates of neural pathway activations in the subthalamic region against intracranial, cortical evoked potential (EP) recordings.

METHODS

Pathway activations were modeled in eleven patients using the latest advances in connectomic modeling of subthalamic DBS, focusing on the hyperdirect pathway (HDP) and corticospinal/bulbar tract (CSBT) for their relevance in human research studies. Correlations between pathway activations and respective EP amplitudes were quantified.

RESULTS

Good model performance required accurate lead localization and image fusions, as well as appropriate selection of fiber diameter in the biophysical model. While optimal model parameters varied across patients, good performance could be achieved using a global set of parameters that explained 60% and 73% of electrophysiologic activations of CSBT and HDP, respectively. Moreover, restricted models fit to only EP amplitudes of eight standard (monopolar and bipolar) electrode configurations were able to extrapolate variation in EP amplitudes across other directional electrode configurations and stimulation parameters, with no significant reduction in model performance across the cohort.

CONCLUSIONS

Our findings demonstrate that connectomic models of DBS with sufficient anatomical and electrical details can predict recruitment dynamics of white matter. These results will help to define connectomic modeling standards for preoperative surgical targeting and postoperative patient programming applications.

Selecting the Most Effective DBS Contact in Essential Tremor Patients Based on Individual Tractography

Postoperative choice of the most effective deep brain stimulation (DBS) contact in patients with essential tremor (ET) so far relies on lengthy clinical testing. Previous studies showed that the postoperative effectiveness of DBS contacts depends on the distance to the dentatorubrothalamic tract (DRTT). Here, we investigated whether the most effective DBS contact could be determined from calculating stimulation overlap with the individual DRTT. Seven ET patients with bilateral thalamic deep brain stimulation were included retrospectively. Tremor control was assessed for each contact during test stimulation with 2mA. Individual DRTTs were identified from diffusion tensor imaging and contacts were ranked by their stimulation overlap with the respective DRTT in relation to their clinical effectiveness. A linear mixed-effects model was calculated to determine the influence of the DRTT overlap on tremor control. In 92.9% of investigated DBS leads, the contact with the best clinical effect was the contact with the highest or second-highest DRTT-overlap. At the group level, the DRTT-overlap explained 26.7% of the variance in the clinical outcomes (p < 0.001). Our data suggest that the overlap with the DRTT based on individual tractography may serve as a marker to determine the most effective DBS contact in ET patients and reduce burdensome clinical testing in the future.

In silico Accuracy and Energy Efficiency of Two Steering Paradigms in Directional Deep Brain Stimulation

Background: In Deep Brain Stimulation (DBS), stimulation field steering is used to achieve stimulation spatial specificity, which is critical to obtain clinical benefits and avoid side effects. Multiple Independent Current Control (MICC) and Interleaving/Multi Stim Set (Interleaving/MSS) are two stimulation field steering paradigms in commercially available DBS systems. This work investigates the stimulation field steering accuracy and energy efficiency of these two paradigms in directional DBS.

Methods: Volumes of Tissue Activated (VTAs) were generated in silico using pulse widths of 60 μs and five pulse amplitude fractionalizations intended to steer the VTAs radially in 12° steps. For each fractionalization, VTAs were generated with nine pre-defined target radii. Stimulation field steering accuracy was assessed based on the VTAs rotation angle. Energy efficiency was inferred from current draw from battery values, which were calculated based on the pulse amplitudes needed to generate and steer the VTAs, as well as electrode impedance measurements of clinically implanted directional leads.

Results: For radial steering, MICC needed a single VTA. In contrast, Interleaving/MSS required the generation of two VTAs, whose union and intersection created an Interleaving/MSS VTA and an Intersection VTA, respectively. MICC VTAs were 6.8 (−3.2–11.8)% larger than Interleaving/MSS VTAs. The Intersection VTAs accounted for 26.2 (16.0–32.8)% of Interleaving/MSS VTAs and were exposed to a higher stimulation frequency. For all VTA radius-fractionalization combinations, steering accuracy was 7.0 (4.5–10.5)° for MICC and 24.0 (9.0–25.3)° for Interleaving/MSS. Pulse amplitudes were 16.1 (9.2–28.6)% lower for MICC than for Interleaving/MSS, leading to a 45.9 (18.8–72.6)% lower current draw from battery for MICC.

Conclusions: The results of this work show that in silico, MICC achieves a significantly better stimulation field steering accuracy and has a significantly higher energy efficiency than Interleaving/MSS. Although direct evidence still needs to be generated to translate the results of this work to clinical practice, clinical outcomes may profit from the better stimulation field steering accuracy of MICC and longevity of DBS systems may profit from its higher energy efficiency.