Reduced Programming Time and Strong Symptom Control Even in Chronic Course Through Imaging-Based DBS Programming

Are we ready for automated deep brain stimulation programming?

Deep brain stimulation (DBS) requires individualized programming of stimulation parameters, a time-consuming process performed manually by clinicians with specialized training. This process limits DBS accessibility, delays treatment, and constrains the potential for next-generation technology to improve patient outcomes. This review describes technological advancements that could automate DBS programming, focusing on Parkinson's disease biomarkers that can provide objective outcome measurement and algorithms that can quickly and automatically identify optimal DBS settings. We first define key performance criteria for an automated programming system, including effectiveness, efficiency, and ease of use, and then describe and evaluate each component with respect to these criteria. We conclude that the state of current research provides a strong foundation for developing automated DBS programming. The primary remaining obstacle lies in identifying and deploying the best combination of available techniques that will overcome the high entry barrier needed for wide-scale clinical deployment and adoption.

Subjective patient rating as a novel feedback signal for DBS programming in Parkinson's disease

BACKGROUND

Deep brain stimulation of the subthalamic nucleus (STN-DBS) effectively alleviates motor fluctuations in Parkinson's disease (PD). Optimal electrode placement and effective programming significantly influence outcomes. From a patient's perspective, DBS should relieve motor symptoms while avoiding side effects. However, there is a lack of programming routines that consider patients' subjective feedback for parameter adjustment.

OBJECTIVE

This study assessed the usefulness of patients' subjective ratings as feedback for DBS programming.

METHODS

We analyzed 260 DBS settings from 11 STN-DBS patients, pairing each volume of tissue activated (VTA) with a subjective rating measured by a visual analogue scale (VAS). We performed sweet spot mapping and connectivity analyses, utilizing voxel-wise and nonparametric permutation statistics to identify neuroanatomical regions and connectivity profiles associated with the highest VAS ratings. To validate our findings, we cross-validated the results in an independent test dataset of 6 patients (189 settings) to determine if the sweet spot and connectivity profile could predict the subjective patient perception.

RESULTS

VTAs with the highest VAS scores were localized to the dorsolateral STN, consistent with published sweet spots derived from clinical data. Connectivity with the supplementary motor area (SMA) and primary motor cortex (M1) was associated with a more positive subjective perception. Connectivity profiles derived from one dataset successfully predicted outcomes in an independent dataset, as validated through leave-one-cohort-out cross-validation.

CONCLUSIONS

Mapping patients' subjective perceptions using VAS yields conclusive anatomical results that align with objective clinical and imaging measures. VAS-guided programming could provide an additional feedback mechanism for both acute and chronic DBS parameter adjustments.

Clinically Implemented Sensing-Based Initial Programming of Deep Brain Stimulation for Parkinson's Disease: A Retrospective Study

OBJECTIVES

Initial deep brain stimulation (DBS) programming using a monopolar review is time-consuming, subjective, and burdensome. Incorporating neurophysiology has the potential to expedite, objectify, and automatize initial DBS programming. We aimed to assess the feasibility and performance of clinically implemented sensing-based initial DBS programming for Parkinson's disease (PD).

MATERIALS AND METHODS

We conducted a single-center retrospective study in 15 patients with PD (25 hemispheres) implanted with a sensing-enabled neurostimulator in whom initial subthalamic nucleus/globus pallidus pars interna DBS programming was guided by beta power in real-time local field potential recordings, instead of a monopolar review.

RESULTS

The initial sensing-based programming visit lasted on average 42.2 minutes (SD 18) per hemisphere. During the DBS optimization phase, a conventional monopolar clinical review was not required in any patients. The initial stimulation contact level remained the same at the final follow-up visit in all hemispheres except three. The final amplitude was on average 0.8 mA (SD 0.9) higher than initially set after the original sensing-based programming visit. One year after surgery, off-medication International Parkinson and Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) III total score, tremor subscore, MDS-UPDRS IV, and levodopa-equivalent dose improved by 47.0% (p < 0.001), 77.7% (p = 0.001), 51.1% (p = 0.006), and 44.8% (p = 0.011) compared with preoperatively using this approach.

CONCLUSIONS

This study shows that sensing-based initial DBS programming for PD is feasible and rapid, and selected clinically effective contacts in most patients, including those with tremor. Technologic innovations and practical developments could improve sensing-based programming.

Concordance between imaging and clinical based STN-DBS programming improves motor outcomes of directional stimulation in Parkinson's disease

BackgroundAdvances in STN-DBS technology, among which directional stimulation, improved Parkinson's disease (PD) treatment efficacy, while increasing the clinical programming complexity. Lead localization software may aid the stimulation contact selection process.ObjectiveWe aimed to assess the concordance between imaging-suggested (IGP) and conventional-programming (CP) selected stimulation contacts one year after surgery and its impact on motor outcomes.MethodsSixty-four PD patients with bilateral STN-DBS were enrolled. Lead localization was reconstructed with BrainlabTM software. For each electrode, the vertical contact level and, when applicable, the directionality predicted by the lead reconstruction software to be the most effective were established and compared to the stimulation parameters clinically activated one-year post-surgery. IGP/CP concordance ratio was calculated for both stimulation level and directional contacts. Post-operative modifications of PD motor symptoms severity were compared among groups of concordant and discordant IGP/CP programming.ResultsOne-year post-surgery, IGP/CP concordance was 80% for active stimulation vertical contact level and 51% for directionality. No significant difference in motor outcomes was found between IGP/CP concordant and discordant patients for contact level activation, whereas patients with concordant IGP/CP active directional stimulation (c-Direction) showed superior motor outcomes at one-year follow-up than those discordant (d-Direction) (UPDRS-III stimulation-induced improvement: c-Direction = -25.66 ± 13.74 vs. d-Direction = -12.54 ± 11.86; p = 0.011).ConclusionsVisual reconstruction software correctly predicted the most clinically effective stimulation contact levels in most patients. Imaging therefore facilitates classic STN-DBS clinical programming while assuring similar outcomes. Moreover, better motor outcomes were reached by patients with concordant IGP/CP directional parameters, suggesting that visualization can represent an added value in particular for directional stimulation programming.

Proceedings of the 12th annual deep brain stimulation think tank: cutting edge technology meets novel applications

The Deep Brain Stimulation (DBS) Think Tank XII was held on August 21st to 23rd. This year we showcased groundbreaking advancements in neuromodulation technology, focusing heavily on the novel uses of existing technology as well as next-generation technology. Our keynote speaker shared the vision of using neuro artificial intelligence to predict depression using brain electrophysiology. Innovative applications are currently being explored in stroke, disorders of consciousness, and sleep, while established treatments for movement disorders like Parkinson's disease are being refined with adaptive stimulation. Neuromodulation is solidifying its role in treating psychiatric disorders such as depression and obsessive-compulsive disorder, particularly for patients with treatment-resistant symptoms. We estimate that 300,000 leads have been implanted to date for neurologic and neuropsychiatric indications. Magnetoencephalography has provided insights into the post-DBS physiological changes. The field is also critically examining the ethical implications of implants, considering the long-term impacts on clinicians, patients, and manufacturers.

Motor evoked potentials as a side effect biomarker for deep brain stimulation programming

Objectives

To determine if motor evoked potentials (mEP) - stimulation-induced muscle activation measured using electromyography - can serve as a biomarker of corticobulbar (CBT) and corticospinal (CST) tract activation for deep brain stimulation (DBS) programming.

Methods

In 12 patients with Parkinson's disease and subthalamic or pallidal DBS, contact mapping determined clinical motor side effect thresholds. For equivalent stimulation parameters, EMG was recorded from cranial and arm muscles to determine the presence, peak amplitudes and latencies of mEP. Clinical and mEP thresholds were compared and accuracy metrics calculated to assess similarity between mEP and reported side effects.

Results

The mEP amplitudes increased with stimulation intensity. Latencies were shorter for cranial muscles, which were more likely to generate an mEP. Clinical and mEP thresholds were significantly correlated (R 2 = 0.31; p=0.0006), although most mEP thresholds were lower than clinical side effect thresholds. The mEP accuracy in predicting side effects was 0.72, with a sensitivity of 0.68 and a specificity of 0.73.

Conclusions

EMG-recorded mEP correlated well with clinical side effects, and mEP often indicated subclinical CBT and CST activations.

Significance

This study characterizes motor potentials evoked by DBS and demonstrates their utility as an objective biomarker for motor side effect threshold detection during DBS programming.

Highlights

Deep brain stimulation can activate corticospinal/bulbar tract and evoke motor potentials in muscles measurable by surface EMGMotor evoked potential thresholds correlate significantly with clinical side effect thresholds but occur at lower stimulation intensitiesMotor evoked potentials may be a useful side effect biomarker for deep brain stimulation programming.

The Place of Local Field Potentials in Deep Brain Stimulation Programming for Parkinson's Disease: A Review

Background/Objections: The pharmacological management of Parkinson's Disease (PD) is often supplemented by deep brain stimulation (DBS) to tackle problems of advanced disease such as motor fluctuation, dyskinesias or medication-resistant tremor. DBS uses high-frequency stimulation with spatially distributed electrodes to produce electrical fields that influence neuronal networks. The programming of such stimulation is complex and time-consuming. Recent technological advancements have enabled DBS systems to record local field potentials (LFPs). In conjunction with biomarker discovery, such as beta oscillations, this shows promise in streamlining the DBS programming process. This review aims to synthesize the current literature investigating LFP characteristics in PD in order to understand the place of LFPs in assisting with DBS programming.

METHODS

A comprehensive literature search was conducted using databases including OVID MEDLINE, Scopus, and Cochrane Library, resulting in 738 identified articles; 122 studies remained after screening and 87 studies were selected for detailed analysis.

RESULTS

Analyzing LFPs clearly has the potential to assist or streamline DBS programming in clinical practice, but there are knowledge gaps and challenges to overcome, especially in the utilization of intraoperative LFPs.

CONCLUSIONS

More research is required to compare different algorithms that utilize LFPs in DBS programming to identify a simple, practical and time-saving algorithm incorporating reliable LFP biomarkers that will enhance the DBS programming experience for both patients and clinicians.

Directional deep brain stimulation electrodes in Parkinson's disease: meta-analysis and systematic review of the literature

BACKGROUND

Since their introduction in 2015, directional leads have practically replaced conventional leads for deep brain stimulation (DBS) in Parkinson's disease (PD). Yet, the benefits of directional DBS (dDBS) over omnidirectional DBS (oDBS) remain unclear. This meta-analysis and systematic review compares the literature on dDBS and oDBS for PD.

METHODS

Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed. Database searches included Pubmed, Cochrane (CENTRAL) and EmBase, using relevant keywords such as 'directional', 'segmented', 'brain stimulation' and 'neuromodulation'. The screening was based on the title and abstract.

RESULTS

23 papers reporting on 1273 participants (1542 leads) were included. The therapeutic window was 0.70 mA wider when using dDBS (95% CI 0.13 to 1.26 mA, p=0.02), with a lower therapeutic current (0.41 mA, 95% CI 0.27 to 0.54 mA, p=0.01) and a higher side-effect threshold (0.56 mA, 95% CI 0.38 to 0.73 mA, p<0.01). However, there was no relevant difference in mean Unified Parkinson's Disease Rating Scale III change after dDBS (45.8%, 95% CI 30.7% to 60.9%) compared with oDBS (39.0%, 95% CI 36.9% to 41.2%, p=0.39), in the medication-OFF state. Median follow-up time for dDBS and oDBS studies was 6 months and 3 months, respectively (range 3-12 for both). The use of directionality often improves dyskinesia, dysarthria, dysesthesia and pyramidal side effects. Directionality was used in 55% of directional leads at 3-6 months, remaining stable over time (56% at a mean of 14.1 months).

CONCLUSIONS

These findings suggest that stimulation parameters favour dDBS. However, these do not appear to have a significant impact on motor scores, and the availability of long-term data is limited. dDBS is widely accepted, but clinical data justifying its increased complexity and cost are currently sparse.

PROSPERO REGISTRATION NUMBER

CRD42023438056.

Prospective Connectomic-Based Deep Brain Stimulation Programming for Parkinson's Disease

BACKGROUND

Efficacy of deep brain stimulation (DBS) relies on accurate lead placement as well as optimization of the stimulation parameters. Although clinical software tools are now available, programming still largely relies on a monopolar review, a tedious process for both patients and programmers.

OBJECTIVE

This study investigates the safety and feasibility of prospective automated connectomic DBS programming (automated connectomic programming [ACP]), focusing on the recruitment of specific white matter pathways.

METHODS

After DBS implantation, a detailed connectomic DBS model in patient-specific space was developed for each study participant. A driving-force model was used to quantify pathway recruitment across 2400 different DBS settings. Optimization algorithms maximized recruitment of therapeutic pathways while minimizing recruitment of side-effect pathways. Thirteen subjects were enrolled in two study phases that compared DBS settings derived from ACP to standard clinical DBS settings.

RESULTS

Nine patients underwent reprogramming with ACP (5 globus pallidus interna [GPi], 4 subthalamic nucleus [STN]). Four patients underwent initial programming with ACP (3 GPi, 1 STN). All patients tolerated ACP without persistent side effects. In the reprogramming cohort, 3 patients preferred their ACP program, and 1 patient felt it was comparable to their clinical program. Unified Parkinson's Disease Rating Scale, Part III, scores for the initial ACP cohort (3 GPi, 1 STN) improved by an average of 43.5% (40.4-52.6 ± 5.6%).

CONCLUSIONS

ACP appeared clinically safe and feasible. It provided reasonable motor improvement, which can be further optimized with subsequent clinical adjustment. Additional investigation is required to refine the optimization algorithm and to quantify the clinical benefit of ACP in a larger cohort. © 2024 International Parkinson and Movement Disorder Society.

Advanced therapies in Parkinson's disease: an individualized approach to their indication

Device aided therapies (DAT) comprising the intrajejunal administration of levodopa/carbidopa intestinal gel (LCIG) and levodopa/carbidopa/entacapone intestinal gel (LECIG), the continuous subcutaneous application of foslevodopa/foscarbidopa or apomorphine infusion (CSAI) and deep brain stimulation (DBS) are used to treat Parkinson's disease with insufficient symptom alleviation under intensified pharmacotherapy. These DAT significantly differ in their efficacy profiles, indication, invasiveness, contraindications, and potential side effects. Usually, the evaluation of all these procedures is conducted simultaneously at the same point in time. However, as disease progression and symptom burden is extremely heterogeneous, clinical experience shows that patients reach the individual milestones for a certain therapy at different points in their disease course. Therefore, advocating for an individualized therapy evaluation for each DAT, requiring an ongoing evaluation. This necessitates that, during each consultation, the current symptomatology should be analyzed, and the potential suitability for a DAT be assessed. This work represents a critical interdisciplinary appraisal of these therapies in terms of their individual profiles and compares these DAT regarding contraindications, periprocedural considerations as well as their efficacy regarding motor- and non-motor deficits, supporting a personalized approach.

Automatic Detection of Directional Lead Orientation in Deep Brain Stimulation using Photon-Counting Detector Computed Tomography: A Phantom Study

INTRODUCTION

Photon-counting detector computed tomography (PCD-CT) represents the next generation of CT technology, offering enhanced capabilities for detecting the orientation of directional leads in deep brain stimulation (DBS). This study aims to refine PCD-CT-based lead orientation determination using an automated method applicable to devices from various manufacturers, addressing current methodological limitations and improving neurosurgical precision.

METHODS

An automated method was developed to ascertain the orientation of directional DBS leads using PCD-CT data and grayscale model fitting for devices from Boston Scientific, Medtronic, and Abbott. A phantom study was conducted to evaluate the precision and accuracy of this method, comparing it with the stripe artifact method across different lead alignments relative to the CT gantry axis.

RESULTS

Except for the Medtronic Sensight™ lead, where detection was occasionally unfeasible if aligned normal to the z-axis of the CT gantry, a clinically very unlikely alignment, the lead orientation could be automatically determined regardless of its position. The accuracy and precision of this automated method was comparable to those of the stripe artifact method.

CONCLUSION

PCD-CT enables the automatic determination of lead orientation from leading manufacturers with an accuracy comparable to the stripe artifact method, and it offers the added benefit of being independent of the clinically occurring orientation of the head and, consequently, the lead relative to the CT gantry axis.

Comparison of beta peak detection algorithms for data-driven deep brain stimulation programming strategies in Parkinson's disease

Oscillatory activity within the beta frequency range (13-30 Hz) serves as a Parkinson's disease biomarker for tailoring deep brain stimulation (DBS) treatments. Currently, identifying clinically relevant beta signals, specifically frequencies of peak amplitudes within the beta spectral band, is a subjective process. To inform potential strategies for objective clinical decision making, we assessed algorithms for identifying beta peaks and devised a standardized approach for both research and clinical applications. Employing a novel monopolar referencing strategy, we utilized a brain sensing device to measure beta peak power across distinct contacts along each DBS electrode implanted in the subthalamic nucleus. We then evaluated the accuracy of ten beta peak detection algorithms against a benchmark established by expert consensus. The most accurate algorithms, all sharing similar underlying algebraic dynamic peak amplitude thresholding approaches, matched the expert consensus in performance and reliably predicted the clinical stimulation parameters during follow-up visits. These findings highlight the potential of algorithmic solutions to overcome the subjective bias in beta peak identification, presenting viable options for standardizing this process. Such advancements could lead to significant improvements in the efficiency and accuracy of patient-specific DBS therapy parameterization.

Biophysical Principles and Computational Modeling of Deep Brain Stimulation

BACKGROUND

Deep brain stimulation (DBS) has revolutionized the treatment of neurological disorders, yet the mechanisms of DBS are still under investigation. Computational models are important in silico tools for elucidating these underlying principles and potentially for personalizing DBS therapy to individual patients. The basic principles underlying neurostimulation computational models, however, are not well known in the clinical neuromodulation community.

OBJECTIVE

In this study, we present a tutorial on the derivation of computational models of DBS and outline the biophysical contributions of electrodes, stimulation parameters, and tissue substrates to the effects of DBS.

RESULTS

Given that many aspects of DBS are difficult to characterize experimentally, computational models have played an important role in understanding how material, size, shape, and contact segmentation influence device biocompatibility, energy efficiency, the spatial spread of the electric field, and the specificity of neural activation. Neural activation is dictated by stimulation parameters including frequency, current vs voltage control, amplitude, pulse width, polarity configurations, and waveform. These parameters also affect the potential for tissue damage, energy efficiency, the spatial spread of the electric field, and the specificity of neural activation. Activation of the neural substrate also is influenced by the encapsulation layer surrounding the electrode, the conductivity of the surrounding tissue, and the size and orientation of white matter fibers. These properties modulate the effects of the electric field and determine the ultimate therapeutic response.

CONCLUSION

This article describes biophysical principles that are useful for understanding the mechanisms of neurostimulation.

The history of deep brain stimulation

Deep brain stimulation (DBS) surgery is an established and effective treatment for several movement disorders (tremor, Parkinson's disease, and dystonia), and is under investigation in numerous other neurological and psychiatric disorders. However, the origins and development of this neurofunctional technique are not always well understood and recognized. In this mini-review, we review the history of DBS, highlighting important milestones and the most remarkable protagonists (neurosurgeons, neurologists, and neurophysiologists) who pioneered and fostered this therapy throughout the 20th and early 21st century. Alongside DBS historical markers, we also briefly discuss newer developments in the field, and the future challenges which accompany such progress.

Seeing Is Believing: Photon Counting Computed Tomography Clearly Images Directional Deep Brain Stimulation Lead Segments and Markers After Implantation

BACKGROUND AND OBJECTIVES

Directional deep brain stimulation (DBS) electrodes are increasingly used, but conventional computed tomography (CT) is unable to directly image segmented contacts owing to physics-based resolution constraints. Postoperative electrode segment orientation assessment is necessary because of the possibility of significant deviation during or immediately after insertion. Photon-counting detector (PCD) CT is a relatively novel technology that enables high resolution imaging while addressing several limitations intrinsic to CT. We show how PCD CT can enable clear in vivo imaging of DBS electrodes, including segmented contacts and markers for all major lead manufacturers.

MATERIALS AND METHODS

We describe postoperative imaging and reconstruction protocols we have developed to enable optimal lead visualization. PCD CT images were obtained of directional leads from the three major manufacturers and fused with preoperative 3T magnetic resonance imaging (MRI). Radiation dosimetry also was evaluated and compared with conventional imaging controls. Orientation estimates from directly imaged leads were compared with validated software-based reconstructions (derived from standard CT imaging artifact analysis) to quantify congruence in alignment and directional orientation.

RESULTS

High-fidelity images were obtained for 15 patients, clearly indicating the segmented contacts and directional markers both on CT alone and when fused to MRI. Our routine imaging protocol is described. Ionizing radiation doses were significantly lower than with conventional CT. For most leads, the directly imaged lead orientations and depths corresponded closely to those predicted by CT artifact-based reconstructions. However, unlike direct imaging, the software reconstructions were susceptible to 180° error in orientation assessment.

CONCLUSIONS

High-resolution photon-counting CT can very clearly image segmented DBS electrode contacts and directional markers and unambiguously determine lead orientation, with lower radiation than in conventional imaging. This obviates the need for further imaging and may facilitate anatomically tailored directional programming.

Directional electrodes in deep brain stimulation: Results of a survey by the European Association of Neurosurgical Societies (EANS)

Introduction

Directional Leads (dLeads) represent a new technical tool in Deep Brain Stimulation (DBS), and a rapidly growing population of patients receive dLeads.

Research question

The European Association of Neurosurgical Societies(EANS) functional neurosurgery Task Force on dLeads conducted a survey of DBS specialists in Europe to evaluate their use, applications, advantages, and disadvantages.

Material and methods

EANS functional neurosurgery and European Society for Stereotactic and Functional Neurosurgery (ESSFN) members were asked to complete an online survey with 50 multiple-choice and open questions on their use of dLeads in clinical practice.

Results

Forty-nine respondents from 16 countries participated in the survey (n = 38 neurosurgeons, n = 8 neurologists, n = 3 DBS nurses). Five had not used dLeads. All users reported that dLeads provided an advantage (n = 23 minor, n = 21 major). Most surgeons (n = 35) stated that trajectory planning does not differ when implanting dLeads or conventional leads. Most respondents selected dLeads for the ability to optimize stimulation parameters (n = 41). However, the majority (n = 24), regarded time-consuming programming as the main disadvantage of this technology. Innovations that were highly valued by most participants included full 3T MRI compatibility, remote programming, and closed loop technology.

Discussion and conclusion

Directional leads are widely used by European DBS specialists. Despite challenges with programming time, users report that dLeads have had a positive impact and maintain an optimistic view of future technological advances.

Image-guided programming deep brain stimulation improves clinical outcomes in patients with Parkinson's disease

Deep brain stimulation (DBS) is an effective treatment for patients with Parkinson's disease (PD). However, some patients may not respond optimally to clinical programming adjustments. Advances in DBS technology have led to more complex and time-consuming programming. Image-guided programming (IGP) could optimize and improve programming leading to better clinical outcomes in patients for whom DBS programming is not ideal due to sub-optimal response. We conducted a prospective single-center study including 31 PD patients with subthalamic nucleus (STN) DBS and suboptimal responses refractory to clinical programming. Programming settings were adjusted according to the volumetric reconstruction of the stimulation field using commercial postoperative imaging software. Clinical outcomes were assessed at baseline and at 3-month follow-up after IGP, using motor and quality of life (QoL) scales. Additionally, between these two assessment points, follow-up visits for fine-tuning amplitude intensity and medication were conducted at weeks 2, 4, 6, and 9. After IGP, twenty-six patients (83.9%) experienced motor and QoL improvements, with 25.8% feeling much better and 38.7% feeling moderately better according to the patient global impression scale. Five patients (16.1%) had no clinical or QoL changes after IGP. The MDS-UPDRS III motor scale showed a 21.9% improvement and the DBS-IS global score improved by 41.5%. IGP optimizes STN-DBS therapy for PD patients who are experiencing suboptimal clinical outcomes. These findings support using IGP as a standard tool in clinical practice, which could save programming time and improve patients' QoL.

General Algorithm Applicability in Determining DBS Lead Orientation: Adapting 2D and 3D X-Ray Techniques for SenSightTM Leads

INTRODUCTION

With recent advancements in deep brain stimulation (DBS), directional leads featuring segmented contacts have been introduced, allowing for targeted stimulation of specific brain regions. Given that manufacturers employ diverse markers for lead orientation, our investigation focuses on the adaptability of the 2017 techniques proposed by the Cologne research group for lead orientation determination.

METHODS

We tailored the two separate 2D and 3D X-ray-based techniques published in 2017 and originally developed for C-shaped markers, to the dual-marker of the Medtronic SenSight™ lead. In a retrospective patient study, we evaluated their feasibility and consistency by comparing the degree of agreement between the two methods.

RESULTS

The Bland-Altman plot showed favorable concordance without any noticeable systematic errors. The mean difference was 0.79°, with limits of agreement spanning from 21.4° to -19.8°. The algorithms demonstrated high reliability, evidenced by an intraclass correlation coefficient of 0.99 (p < 0.001).

CONCLUSION

The 2D and 3D algorithms, initially formulated for discerning the circular orientation of a C-shaped marker, were adapted to the marker of the Medtronic SenSight™ lead. Statistical analyses revealed a significant level of agreement between the two methods. Our findings highlight the adaptability of these algorithms to different markers, achievable through both low-dose intraoperative 2D X-ray imaging and standard CT imaging.

Computational Neurosurgery in Deep Brain Stimulation

Computational methods and technologies are critical for neurosurgery in general and in deep brain stimulation (DBS) in particular. They increasingly inform every aspect of clinical DBS therapy, from presurgical planning and hardware implantation to postoperative adjustment of stimulation parameters. Computational methods also occupy a prominent position within the DBS research sphere, where they facilitate efforts to better understand DBS' underlying mechanisms and optimize and individualize its delivery. This chapter provides a high-level overview of the various computational tools and methods that have been applied to DBS. First, we discuss the invaluable contribution of computational neuroimaging (primarily magnetic resonance imaging) to DBS, targeting and the role of postoperative methods of image analysis-specifically, electrode localization, volume of activated tissue modeling, and sweet-spot mapping-in precisely localizing DBS' targets in the brain and discerning optimal treatment loci. We then address the growing field of connectomics, which leverages specific magnetic resonance imaging (MRI) sequences and post-acquisition processing algorithms to explore how DBS operates at the level of brain-wide networks. Next, the search for electrophysiological and imaging-based biomarkers of optimal DBS therapy is explored. We lastly touch on the incipient field of spatial characterization analysis and discuss the ongoing development of adaptive, closed-loop DBS systems.

The Use of Image Guided Programming to Improve Deep Brain Stimulation Workflows with Directional Leads in Parkinson's Disease

BACKGROUND

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is a preferred treatment for parkinsonian patients with severe motor fluctuations. Proper targeting of the STN sensorimotor segment appears to be a crucial factor for success of the procedure. The recent introduction of directional leads theoretically increases stimulation specificity in this challenging area but also requires more precise stimulation parameters.

OBJECTIVE

We investigated whether commercially available software for image guided programming (IGP) could maximize the benefits of DBS by informing the clinical standard care (CSC) and improving programming workflows.

METHODS

We prospectively analyzed 32 consecutive parkinsonian patients implanted with bilateral directional leads in the STN. Double blind stimulation parameters determined by CSC and IGP were assessed and compared at three months post-surgery. IGP was used to adjust stimulation parameters if further clinical refinement was required. Overall clinical efficacy was evaluated one-year post-surgery.

RESULTS

We observed 78% concordance between the two electrode levels selected by the blinded IGP prediction and CSC assessments. In 64% of cases requiring refinement, IGP improved clinical efficacy or reduced mild side effects, predominantly by facilitating the use of directional stimulation (93% of refinements).

CONCLUSIONS

The use of image guided programming saves time and assists clinical refinement, which may be beneficial to the clinical standard care for STN-DBS and further improve the outcomes of DBS for PD patients.

A Retrospective Comparison of Multiple Approaches to Anatomically Informed Contact Selection in Subthalamic Deep Brain Stimulation for Parkinson's Disease

Background

Conventional deep brain stimulation (DBS) programming via trial-and-error warrants improvement to ensure swift achievement of optimal outcomes. The definition of a sweet spot for subthalamic DBS in Parkinson's disease (PD-STN-DBS) may offer such advancement.

Objective

This investigation examines the association of long-term motor outcomes with contact selection during monopolar review and different strategies for anatomically informed contact selection in a retrospective real-life cohort of PD-STN-DBS.

Methods

We compared contact selection based on a monopolar review (MPR) to multiple anatomically informed contact selection strategies in a cohort of 28 PD patients with STN-DBS. We employed a commercial software package for contact selection based on visual assessment of individual anatomy following two predefined strategies and two algorithmic approaches with automatic targeting of either the sensorimotor STN or our previously published sweet spot. Similarity indices between chronic stimulation and contact selection strategies were correlated to motor outcomes at 12 months follow-up.

Results

Lateralized motor outcomes of chronic DBS were correlated to the similarity between chronic stimulation and visual contact selection targeting the dorsal part of the posterior STN (rho = 0.36, p = 0.007). Similar relationships could not be established for MPR or any of the other investigated strategies.

Conclusions

Our data demonstrates that a visual contact selection following a predefined strategy can be linked to beneficial long-term motor outcomes in PD-STN-DBS. Since similar correlations could not be observed for the other approaches to anatomically informed contact selection, we conclude that clear definitions and prospective validation of any approach to imaging-based DBS-programming is warranted.

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.

Variations in Determining Actual Orientations of Segmented Deep Brain Stimulation Leads Using the DiODe Algorithm: A Retrospective Study Across Different Lead Designs and Medical Institutions

INTRODUCTION

Directional deep brain stimulation (DBS) leads have become widely used in the past decade. Understanding the asymmetric stimulation provided by directional leads requires precise knowledge of the exact orientation of the lead in respect to its anatomical target. Recently, the DiODe algorithm was developed to automatically determine the orientation angle of leads from the artifact on postoperative computed tomography (CT) images. However, manual DiODe results are user-dependent. This study analyzed the extent of lead rotation as well as the user agreement of DiODe calculations across the two most common DBS systems, namely, Boston Scientific's Vercise and Abbott's Infinity, and two independent medical institutions.

METHODS

Data from 104 patients who underwent an anterior-facing unilateral/bilateral directional DBS implantation at either Northwestern Memorial Hospital (NMH) or Albany Medical Center (AMC) were retrospectively analyzed. Actual orientations of the implanted leads were independently calculated by three individual users using the DiODe algorithm in Lead-DBS and patients' postoperative CT images. The deviation from the intended orientation and user agreement were assessed.

RESULTS

All leads significantly deviated from the intended 0° orientation (p < 0.001), regardless of DBS lead design (p < 0.05) or institution (p < 0.05). However, the Boston Scientific leads showed an implantation bias toward the left at both institutions (p = 0.014 at NMH, p = 0.029 at AMC). A difference of 10° between at least two users occurred in 28% (NMH) and 39% (AMC) of all Boston Scientific and 76% (NMH) and 53% (AMC) of all Abbott leads.

CONCLUSION

Our results show that there is a significant lead rotation from the intended surgical orientation across both DBS systems and both medical institutions; however, a bias toward a single direction was only seen in the Boston Scientific leads. Additionally, these results raise questions into the user error that occurs when manually refining the orientation angles calculated with DiODe.

Machine versus physician-based programming of deep brain stimulation in isolated dystonia: A feasibility study

BACKGROUND

Deep brain stimulation of the internal globus pallidus effectively alleviates dystonia motor symptoms. However, delayed symptom control and a lack of therapeutic biomarkers and a single pallidal sweetspot region complicates optimal programming. Postoperative management is complex, typically requiring multiple, lengthy follow-ups with an experienced physician - an important barrier to widespread adoption in medication-refractory dystonia patients.

OBJECTIVE

Here we prospectively tested the best machine-predicted programming settings in a dystonia cohort treated with GPi-DBS against the settings derived from clinical long-term care in a specialised DBS centre.

METHODS

Previously, we reconstructed an anatomical map of motor improvement probability across the pallidal region using individual stimulation volumes and clinical outcomes in dystonia patients. We used this to develop an algorithm that tests in silico thousands of putative stimulation settings in de novo patients after reconstructing an individual, image-based anatomical model of electrode positions, and suggests stimulation parameters with the highest likelihood of optimal symptom control. To test real-life application, our prospective study compared results in 10 patients against programming settings derived from long-term care.

RESULTS

In this cohort, dystonia symptom reduction was observed at 74.9 ± 15.3% with C-SURF programming as compared to 66.3 ± 16.3% with clinical programming (p < 0.012). The average total electrical energy delivered (TEED) was similar for both the clinical and C-SURF programming (262.0 μJ/s vs. 306.1 μJ/s respectively).

CONCLUSION

Our findings highlight the clinical potential of machine-based programming in dystonia, which could markedly reduce the programming burden in postoperative management.

Prediction of Movement Ratings and Deep Brain Stimulation Parameters in Idiopathic Parkinson's Disease

BACKGROUND

Deep brain stimulation (DBS) parameter fine-tuning after lead implantation is laborious work because of the almost uncountable possible combinations. Patients and practitioners often gain the perception that assistive devices could be beneficial for adjusting settings effectively.

OBJECTIVE

We aimed at a proof-of-principle study to assess the benefits of noninvasive movement recordings as a means to predict best DBS settings.

MATERIALS AND METHODS

For this study, 32 patients with idiopathic Parkinson's disease, under chronic subthalamic nucleus stimulation with directional leads, were recorded. During monopolar review, each available contact was activated with currents between 0.5 and 5 mA, and diadochokinesia, rigidity, and tapping ability were rated clinically. Moreover, participants' movements were measured during four simple hand movement tasks while wearing a commercially available armband carrying an inertial measurement unit (IMU). We trained random forest models to learn the relations between clinical ratings, electrode settings, and movement features obtained from the IMU.

RESULTS

Firstly, we could show that clinical mobility ratings can be predicted from IMU features with correlations of up to r = 0.68 between true and predicted values. Secondly, these features also enabled a prediction of DBS parameters, which showed correlations of up to approximately r = 0.8 with clinically optimal DBS settings and were associated with congruent volumes of tissue activated.

CONCLUSION

Movement recordings from customer-grade mobile IMU carrying devices are promising candidates, not only for remote symptom assessment but also for closed-loop DBS parameter adjustment, and could thus extend the list of available aids for effective programming beyond imaging techniques.

Automated deep brain stimulation programming based on electrode location: a randomised, crossover trial using a data-driven algorithm

BACKGROUND

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is highly effective in controlling motor symptoms in patients with Parkinson's disease. However, correct selection of stimulation parameters is pivotal to treatment success and currently follows a time-consuming and demanding trial-and-error process. We aimed to assess treatment effects of stimulation parameters suggested by a recently published algorithm (StimFit) based on neuroimaging data.

METHODS

This double-blind, randomised, crossover, non-inferiority trial was carried out at Charité - Universitätsmedizin, Berlin, Germany, and enrolled patients with Parkinson's disease treated with directional octopolar electrodes targeted at the STN. All patients had undergone DBS programming according to our centre's standard of care (SoC) treatment before study recruitment. Based on perioperative imaging data, DBS electrodes were reconstructed and StimFit was applied to suggest optimal stimulation settings. Patients underwent motor assessments using the Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS-III) during OFF-medication and in OFF-stimulation and ON-stimulation states under both conditions, StimFit and SoC parameter settings. Patients were randomly assigned (1:1) to receive either StimFit-programmed DBS first and SoC-programmed DBS second, or SoC-programmed DBS first and StimFit-programmed DBS second. The allocation schedule was generated using a computerised random number generator. Both the rater and patients were masked to the sequence of SoC and StimFit stimulation conditions. All patients who participated in the study were included in the analysis. The primary endpoint of this study was the absolute mean difference between MDS-UPDRS-III scores under StimFit and SoC stimulation, with a non-inferiority margin of 5 points. The study was registered at the German Register for Clinical Trials (DRKS00023115), and is complete.

FINDINGS

Between July 10, 2020, and Oct 28, 2021, 35 patients were enrolled in the study; 18 received StimFit followed by SoC stimulation, and 17 received SoC followed by StimFit stimulation. Mean MDS-UPDRS-III scores improved from 47·3 (SD 17·1) at OFF-stimulation baseline to 24·7 (SD 12·4) and 26·3 (SD 12·4) under SoC and StimFit stimulation, respectively. Mean difference between motor scores was -1·6 (SD 7·1; 95% CI -4·0 to 0·9; superiority test p_superiority=0·20; n=35), establishing non-inferiority of StimFit stimulation at a margin of -5 points (non-inferiority test p_{non-inferiority}=0·0038). In six patients (17%), initial programming of StimFit settings resulted in acute side-effects and amplitudes were reduced until side-effects disappeared.

INTERPRETATION

Automated data-driven algorithms can predict stimulation parameters that lead to motor symptom control comparable to SoC treatment. This approach could significantly decrease the time necessary to obtain optimal treatment parameters.

FUNDING

Deutsche Forschungsgemeinschaft through NeuroCure Clinical Research Center and TRR 295.

Proceedings of the 10th annual deep brain stimulation think tank: Advances in cutting edge technologies, artificial intelligence, neuromodulation, neuroethics, interventional psychiatry, and women in neuromodulation

The deep brain stimulation (DBS) Think Tank X was held on August 17-19, 2022 in Orlando FL. The session organizers and moderators were all women with the theme women in neuromodulation. Dr. Helen Mayberg from Mt. Sinai, NY was the keynote speaker. She discussed milestones and her experiences in developing depression DBS. The DBS Think Tank was founded in 2012 and provides an open platform where clinicians, engineers and researchers (from industry and academia) can freely discuss current and emerging DBS technologies as well as the logistical and ethical issues facing the field. The consensus among the DBS Think Tank X speakers was that DBS has continued to expand in scope however several indications have reached the "trough of disillusionment." DBS for depression was considered as "re-emerging" and approaching a slope of enlightenment. DBS for depression will soon re-enter clinical trials. The group estimated that globally more than 244,000 DBS devices have been implanted for neurological and neuropsychiatric disorders. This year's meeting was focused on advances in the following areas: neuromodulation in Europe, Asia, and Australia; cutting-edge technologies, closed loop DBS, DBS tele-health, neuroethics, lesion therapy, interventional psychiatry, and adaptive DBS.

Programming of subthalamic nucleus deep brain stimulation for Parkinson's disease with sweet spot-guided parameter suggestions

Deep Brain Stimulation (DBS) is an effective treatment for advanced Parkinson's disease. However, identifying stimulation parameters, such as contact and current amplitudes, is time-consuming based on trial and error. Directional leads add more stimulation options and render this process more challenging with a higher workload for neurologists and more discomfort for patients. In this study, a sweet spot-guided algorithm was developed that automatically suggested stimulation parameters. These suggestions were retrospectively compared to clinical monopolar reviews. A cohort of 24 Parkinson's disease patients underwent bilateral DBS implantation in the subthalamic nucleus at our center. First, the DBS' leads were reconstructed with the open-source toolbox Lead-DBS. Second, a sweet spot for rigidity reduction was set as the desired stimulation target for programming. This sweet spot and estimations of the volume of tissue activated were used to suggest (i) the best lead level, (ii) the best contact, and (iii) the effect thresholds for full therapeutic effect for each contact. To assess these sweet spot-guided suggestions, the clinical monopolar reviews were considered as ground truth. In addition, the sweet spot-guided suggestions for best lead level and best contact were compared against reconstruction-guided suggestions, which considered the lead location with respect to the subthalamic nucleus. Finally, a graphical user interface was developed as an add-on to Lead-DBS and is publicly available. With the interface, suggestions for all contacts of a lead can be generated in a few seconds. The accuracy for suggesting the best out of four lead levels was 56%. These sweet spot-guided suggestions were not significantly better than reconstruction-guided suggestions (p = 0.3). The accuracy for suggesting the best out of eight contacts was 41%. These sweet spot-guided suggestions were significantly better than reconstruction-guided suggestions (p < 0.001). The sweet spot-guided suggestions of each contact's effect threshold had a mean error of 1.2 mA. On an individual lead level, the suggestions can vary more with mean errors ranging from 0.3 to 4.8 mA. Further analysis is warranted to improve the sweet spot-guided suggestions and to account for more symptoms and stimulation-induced side effects.

Multiple input algorithm-guided Deep Brain stimulation-programming for Parkinson's disease patients

Technological advances of Deep Brain Stimulation (DBS) within the subthalamic nucleus (STN) for Parkinson's disease (PD) provide increased programming options with higher programming burden. Reducing the effort of DBS optimization requires novel programming strategies. The objective of this study was to evaluate the feasibility of a semi-automatic algorithm-guided-programming (AgP) approach to obtain beneficial stimulation settings for PD patients with directional DBS systems. The AgP evaluates iteratively the weighted combination of sensor and clinician assessed responses of multiple PD symptoms to suggested DBS settings until it converges to a final solution. Acute clinical effectiveness of AgP DBS settings and DBS settings that were found following a standard of care (SoC) procedure were compared in a randomized, crossover and double-blind fashion in 10 PD subjects from a single center. Compared to therapy absence, AgP and SoC DBS settings significantly improved (p = 0.002) total Unified Parkinson's Disease Rating Scale III scores (median 69.8 interquartile range (IQR) 64.6|71.9% and 66.2 IQR 58.1|68.2%, respectively). Despite their similar clinical results, AgP and SoC DBS settings differed substantially. Per subject, AgP tested 37.0 IQR 34.0|37 settings before convergence, resulting in 1.7 IQR 1.6|2.0 h, which is comparable to previous reports. Although AgP long-term clinical results still need to be investigated, this approach constitutes an alternative for DBS programming and represents an important step for future closed-loop DBS optimization systems.

Utility of Postoperative Imaging Software for Deep Brain Stimulation Targeting in Patients with Movement Disorders

OBJECTIVE

The objective of this study was to evaluate the accuracy of the SureTune3 postoperative imaging software in determining the location of a deep brain stimulation (DBS) electrode based on clinical outcomes and the adverse effects (AEs) observed.

METHODS

Twenty-six consecutive patients with Parkinson disease (n = 17), essential tremor (n = 8), and dystonia (n = 1) who underwent bilateral DBS surgery (52 electrodes) were included in this study. Presurgical assessments were performed in all patients prior to surgery and at 3 and 6 months after surgery, using quality-of-life and clinical scales in each case. The SureTune3 software was used to evaluate the anatomical positioning of the DBS electrodes.

RESULTS

Following DBS surgery, motor and quality-of-life improvement was observed in all patients. Different AEs were detected in 12 patients, in 10 of whom (83.3%) SureTune3 related the symptoms to the positioning of an electrode. A clinical association was observed with SureTune3 for 48 of 52 (92.3%) electrodes, whereas no association was found between the AEs or clinical outcomes and the SureTune3 reconstructions for 4 of 52 electrodes (7.7%) from 4 different patients. In 2 patients, the contact chosen was modified based on the SureTune3 data, and in 2 cases, the software helped determine that second electrode replacement surgery was necessary.

CONCLUSIONS

The anatomical position of electrodes analyzed with SureTune3 software was strongly correlated with both the AEs and clinical outcomes. Thus, SureTune3 may be useful in clinical practice, and it could help improve stimulation parameters and influence decisions to undertake electrode replacement surgery.

MaDoPO: Magnetic Detection of Positions and Orientations of Segmented Deep-Brain Stimulation Electrodes: A Radiation-Free Method Based on Magnetoencephalography

Background: Current approaches to detect the positions and orientations of directional deep-brain stimulation (DBS) electrodes rely on radiative imaging data. In this study, we aim to present an improved version of a radiation-free method for magnetic detection of the position and the orientation (MaDoPO) of directional electrodes based on a series of magnetoencephalography (MEG) measurements and a possible future solution for optimized results using emerging on-scalp MEG systems. Methods: A directional DBS system was positioned into a realistic head–torso phantom and placed in the MEG scanner. A total of 24 measurements of 180 s each were performed with different predefined electrode configurations. Finite element modeling and model fitting were used to determine the position and orientation of the electrode in the phantom. Related measurements were fitted simultaneously, constraining solutions to the a priori known geometry of the electrode. Results were compared with the results of the high-quality CT imaging of the phantom. Results: The accuracy in electrode localization and orientation detection depended on the number of combined measurements. The localization error was minimized to 2.02 mm by considering six measurements with different non-directional bipolar electrode configurations. Another six measurements with directional bipolar stimulations minimized the orientation error to 4°. These values are mainly limited due to the spatial resolution of the MEG. Moreover, accuracies were investigated as a function of measurement time, number of sensors, and measurement direction of the sensors in order to define an optimized MEG device for this application. Conclusion: Although MEG introduces inaccuracies in the detection of the position and orientation of the electrode, these can be accepted when evaluating the benefits of a radiation-free method. Inaccuracies can be further reduced by the use of on-scalp MEG sensor arrays, which may find their way into clinics in the foreseeable future.