Deep Brain Stimulation Programming for Movement Disorders: Current Concepts and Evidence-Based Strategies

3D-visualization of segmented contacts of directional deep brain stimulation electrodes via registration and fusion of CT and FDCT

OBJECTIVES

3D-visualization of the segmented contacts of directional deep brain stimulation (DBS) electrodes is desirable since knowledge about the position of every segmented contact could shorten the timespan for electrode programming. CT cannot yield images fitting that purpose whereas highly resolved flat detector computed tomography (FDCT) can accurately image the inner structure of the electrode. This study aims to demonstrate the applicability of image fusion of highly resolved FDCT and CT to produce highly resolved images that preserve anatomical context for subsequent fusion to preoperative MRI for eventually displaying segmented contactswithin anatomical context in future studies.

MATERIAL AND METHODS

Retrospectively collected datasets from 15 patients who underwent bilateral directional DBS electrode implantation were used. Subsequently, after image analysis, a semi-automated 3D-registration of CT and highly resolved FDCT followed by image fusion was performed. The registration accuracy was assessed by computing the target registration error.

RESULTS

Our work demonstrated the feasibility of highly resolved FDCT to visualize segmented electrode contacts in 3D. Semiautomatic image registration to CT was successfully implemented in all cases. Qualitative evaluation by two experts revealed good alignment regarding intracranial osseous structures. Additionally, the average for the mean of the target registration error over all patients, based on the assessments of two raters, was computed to be 4.16 mm.

CONCLUSION

Our work demonstrated the applicability of image fusion of highly resolved FDCT to CT for a potential workflow regarding subsequent fusion to MRI in the future to put the electrodes in an anatomical context.

A longitudinal electrophysiological and behavior dataset for PD rat in response to deep brain stimulation

Here we presented an electrophysiological dataset collected from layer V of the primary motor cortex (M1) and the corresponding behavior dataset from normal and hemi-parkinson rats over 5 consecutive weeks. The electrophysiological dataset was constituted by the raw wideband signal, neuronal spikes, and local field potential (LFP) signal. The open-field test was done and recorded to evaluate the behavior variation of rats among the entire experimental cycle. We conducted technical validation of this dataset through sorting the spike data to form action potential waveforms and analyzing the spectral power of LFP data, then based on these findings a closed-loop DBS protocol was developed by the oscillation activity response of M1 LFP signal. Additionally, this protocol was applied to the hemi-parkinson rat for five consecutive days while simultaneously recording the electrophysiological data. This dataset is currently the only publicly available dataset that includes longitudinal closed-loop DBS recordings, which can be utilized to investigate variations of neuronal activity within the M1 following long-term closed-loop DBS, and explore additional reliable biomarkers.

Deep brain stimulation of the subthalamic nucleus for Parkinson's disease: A network imaging marker of the treatment response

Subthalamic nucleus deep brain stimulation (STN-DBS) alleviates motor symptoms of Parkinson's disease (PD), thereby improving quality of life. However, quantitative brain markers to evaluate DBS responses and select suitable patients for surgery are lacking. Here, we used metabolic brain imaging to identify a reproducible STN-DBS network for which individual expression levels increased with stimulation in proportion to motor benefit. Of note, measurements of network expression from metabolic and BOLD imaging obtained preoperatively predicted motor outcomes determined after DBS surgery. Based on these findings, we computed network expression in 175 PD patients, with time from diagnosis ranging from 0 to 21 years, and used the resulting data to predict the outcome of a potential STN-DBS procedure. While minimal benefit was predicted for patients with early disease, the proportion of potential responders increased after 4 years. Clinically meaningful improvement with stimulation was predicted in 18.9 - 27.3% of patients depending on disease duration.

Continuous iontronic chemotherapy reduces brain tumor growth in embryonic avian in vivo models

Local and long-lasting administration of potent chemotherapeutics is a promising therapeutic intervention to increase the efficiency of chemotherapy of hard-to-treat tumors such as the most lethal brain tumors, glioblastomas (GBM). However, despite high toxicity for GBM cells, potent chemotherapeutics such as gemcitabine (Gem) cannot be widely implemented as they do not efficiently cross the blood brain barrier (BBB). As an alternative method for continuous administration of Gem, we here operate freestanding iontronic pumps - "GemIPs" - equipped with a custom-synthesized ion exchange membrane (IEM) to treat a GBM tumor in an avian embryonic in vivo system. We compare GemIP treatment effects with a topical metronomic treatment and observe that a remarkable growth inhibition was only achieved with steady dosing via GemIPs. Daily topical drug administration (at the maximum dosage that was not lethal for the embryonic host organism) did not decrease tumor sizes, while both treatment regimes caused S-phase cell cycle arrest and apoptosis. We hypothesize that the pharmacodynamic effects generate different intratumoral drug concentration profiles for each technique, which causes this difference in outcome. We created a digital model of the experiment, which proposes a fast decay in the local drug concentration for the topical daily treatment, but a long-lasting high local concentration of Gem close to the tumor area with GemIPs. Continuous chemotherapy with iontronic devices opens new possibilities in cancer treatment: the long-lasting and highly local dosing of clinically available, potent chemotherapeutics to greatly enhance treatment efficiency without systemic side-effects. SIGNIFICANCE STATEMENT: Iontronic pumps (GemIPs) provide continuous and localized administration of the chemotherapeutic gemcitabine (Gem) for treating glioblastoma in vivo. By generating high and constant drug concentrations near the vascularized growing tumor, GemIPs offer an efficient and less harmful alternative to systemic administration. Continuous GemIP dosing resulted in remarkable growth inhibition, superior to daily topical Gem application at higher doses. Our digital modelling shows the advantages of iontronic chemotherapy in overcoming limitations of burst release and transient concentration profiles, and providing precise control over dosing profiles and local distribution. This technology holds promise for future implants, could revolutionize treatment strategies, and offers a new platform for studying the influence of timing and dosing dependencies of already-established drugs in the fight against hard-to-treat tumors.

Electrocardiographic approach strategies in patients with Parkinson disease treated with deep brain stimulation

Deep brain stimulation (DBS) is an interdisciplinary and reversible therapy that uses high-frequency electrical stimulation to correct aberrant neural pathways in motor and cognitive neurological disorders. However, the high frequency of the waves used in DBS can interfere with electrical recording devices (e.g., electrocardiogram, electroencephalogram, cardiac monitor), creating artifacts that hinder their interpretation. The compatibility of DBS with these devices varies and depends on factors such as the underlying disease and the configuration of the neurostimulator. In emergencies where obtaining an electrocardiogram is crucial, the need for more consensus on reducing electrical artifacts in patients with DBS becomes a significant challenge. Various strategies have been proposed to attenuate the artifact generated by DBS, such as changing the DBS configuration from monopolar to bipolar, temporarily deactivating DBS during electrocardiographic recording, applying frequency filters both lower and higher than those used by DBS, and using non-standard leads. However, the inexperience of medical personnel, variability in DBS models, or the lack of a controller at the time of approach limit the application of these strategies. Current evidence on their reproducibility and efficacy is limited. Due to the growing elderly population and the rising utilization of DBS, it is imperative to create electrocardiographic methods that are easily accessible and reproducible for general physicians and emergency services.

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 guiding effect of local field potential during deep brain stimulation surgery for programming in Parkinson's disease patients

BACKGROUND

Parkinson's disease (PD) patients undergoing deep brain stimulation (DBS) surgery require subsequent programming, which is complex and cumbersome. The local field potential (LFP) in the deep brain is associated with motor symptom improvement. The current study aimed to identify LFP biomarkers correlated with improved motor symptoms in PD patients after DBS and verify their guiding role in postoperative programming.

METHODS

Initially, the study included 36 PD patients undergoing DBS surgery. Temporary external electrical stimulation was performed during electrode implantation, and LFP signals around the electrode contacts were collected before and after stimulation. The stimulating contact at 6 months of programming was regarded as the optimal and effective stimulating contact. The LFP signal of this contact during surgery was analyzed to identify potential LFP biomarkers. Next, we randomly assigned another 30 PD patients who had undergone DBS to physician empirical programming and LFP biomarker-guided programming groups and compared the outcomes.

RESULTS

In the first part of the study, LFP signals of electrode contacts changed after electrical stimulation. Electrical stimulation reduced gamma energy and the beta/alpha oscillation ratio. The different programming method groups were compared, indicating the superiority of beta/alpha oscillations ratio-guided programming over physician experience programming for patients' improvement rate (IR) of UPDRS-III. There were no significant differences in the IR of UPDRS-III, post-LED, IR-PDQ39, number of programmings, and the contact change rate between the gamma oscillations-guided programming and empirical programming groups.

CONCLUSION

Overall, the findings reveal that gamma oscillations and the beta/alpha oscillations ratio are potential biomarkers for programming in PD patients after DBS. Instead of relying solely on spike action potential signals from single neurons, LFP biomarkers can provide the appropriate depth for electrode placement.

GPi-DBS-induced brain metabolic activation in cervical dystonia

BACKGROUND

Deep brain stimulation (DBS) of the globus pallidus interna (GPi) is a highly efficacious treatment for cervical dystonia, but its mechanism of action is not fully understood. Here, we investigate the brain metabolic effects of GPi-DBS in cervical dystonia.

METHODS

Eleven patients with GPi-DBS underwent brain 18F-fluorodeoxyglucose positron emission tomography imaging during stimulation on and off. Changes in regional brain glucose metabolism were investigated at the active contact location and across the whole brain. Changes in motor symptom severity were quantified using the Toronto Western Spasmodic Torticollis Rating Scale (TWSTRS), executive function using trail making test (TMT) and parkinsonism using Unified Parkinson's Disease Rating Scale (UPDRS).

RESULTS

The mean (SD) best therapeutic response to DBS during the treatment was 81 (22)%. The TWSTRS score was 3.2 (3.9) points lower DBS on compared with off (p=0.02). At the stimulation site, stimulation was associated with increased metabolism, which correlated with DBS stimulation amplitude (r=0.70, p=0.03) but not with changes in motor symptom severity (p>0.9). In the whole brain analysis, stimulation increased metabolism in the GPi, subthalamic nucleus, putamen, primary sensorimotor cortex (PFDR<0.05). Acute improvement in TWSTRS correlated with metabolic activation in the sensorimotor cortex and overall treatment response in the supplementary motor area. Worsening of TMT-B score was associated with activation of the anterior cingulate cortex and parkinsonism with activation in the putamen.

CONCLUSIONS

GPi-DBS increases metabolic activity at the stimulation site and sensorimotor network. The clinical benefit and adverse effects are mediated by modulation of specific networks.

Nonlinear effects at the electrode-tissue interface of deep brain stimulation electrodes

Objective.The electrode-tissue interface provides the critical path for charge transfer in neurostimulation therapies and exhibits well-established nonlinear properties at high applied currents or voltages. These nonlinear properties may influence the efficacy and safety of applied stimulation but are typically neglected in computational models. In this study, nonlinear behavior of the electrode-tissue interface impedance was incorporated in a computational model of deep brain stimulation (DBS) to simulate the impact on neural activation and safety considerations.Approach.Nonlinear electrode-tissue interface properties were incorporated in a finite element model of DBS electrodesin vitroandin vivo,in the rat subthalamic nucleus, using an iterative approach. The transition point from linear to nonlinear behavior was determined for voltage and current-controlled stimulation. Predicted levels of neural activation during DBS were examined and the region of linear operation of the electrode was compared with the Shannon safety limit.Main results.A clear transition of the electrode-tissue interface impedance to nonlinear behavior was observed for both current and voltage-controlled stimulation. The transition occurred at lower values of activation overpotential for simulatedin vivothanin vitroconditions (91 mV and 165 mV respectively for current-controlled stimulation; 110 mV and 275 mV for voltage-controlled stimulation), corresponding to an applied current of 30μA and 45μA, or voltage of 330 mV at 1 kHz. The onset of nonlinearity occurred at lower values of the overpotential as frequency was increased. Incorporation of nonlinear properties resulted in activation of a higher proportion of neurons under voltage-controlled stimulation. Under current-controlled stimulation, the predicted transition to nonlinear behavior and Faradaic charge transfer at stimulation amplitudes of 30μA, corresponds to a charge density of 2.29μC cm-2and charge of 1.8 nC, well-below the Shannon safety limit.Significance.The results indicate that DBS electrodes may operate within the nonlinear region at clinically relevant stimulation amplitudes. This affects the extent of neural activation under voltage-controlled stimulation and the transition to Faradaic charge transfer for both voltage- and current-controlled stimulation with important implications for targeting of neural populations and the design of safe stimulation protocols.

Improved Side-Effect Stimulation Thresholds and Postoperative Transient Confusion With Asleep, Image-Guided Deep Brain Stimulation

BACKGROUND AND OBJECTIVES

Asleep, image-guided deep brain stimulation (DBS) is a modern alternative to awake, microelectrode recording (MER) guidance. Studies demonstrate comparable efficacy and complications between techniques, although some report lower stimulation thresholds for side effects with image guidance. In addition, few studies directly compare the risk of postoperative transient confusion (pTC) across techniques. The purpose of this study was to compare clinical efficacy, stimulation thresholds for side effects, and rates of pTC with MER-guided DBS vs intraoperative 3D-fluoroscopy (i3D-F) guidance in Parkinson's disease and essential tremor.

METHODS

Consecutive patients from 2006 to 2021 were identified from the departmental database and grouped as having either MER-guided DBS or i3D-F-guided DBS insertion. Directional leads were used once commercially available. Changes in Unified Parkinson's Disease Rating Scale (UPDRS)-III scores, levodopa equivalent daily dose, Fahn-Tolosa-Marin scores, and stimulation thresholds were assessed, as were rates of complications including pTC.

RESULTS

MER guidance was used to implant 487 electrodes (18 globus pallidus interna, GPi; 171 subthalamic nucleus; 76 ventrointermediate thalamus, VIM) in 265 patients. i3D-F guidance was used in 167 electrodes (19 GPi; 25 subthalamic nucleus; 41 VIM) in 85 patients. There were no significant differences in Unified Parkinson's Disease Rating III Scale, levodopa equivalent daily dose, or Fahn-Tolosa-Marin between groups. Stimulation thresholds for side effects were higher with i3D-F guidance in the subthalamic nucleus (MER, 2.80 mA ± 0.98; i3D-F, 3.46 mA ± 0.92; P = .002) and VIM (MER, 2.81 mA ± 1.00; i3D-F, 3.19 mA ± 1.03; P = .0018). Less pTC with i3D-F guidance (MER, 7.5%; i3D-F, 1.2%; P = .034) was also found.

CONCLUSION

Although clinical efficacy between MER-guided and i3D-F-guided DBS was comparable, thresholds for stimulation side effects were higher with i3D-F guidance and the rate of pTC was lower. This suggests that image-guided DBS may affect long-term side effects and pose a decreased risk of pTC.

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.

Short-term stimulations of the entopeduncular nucleus induce cerebellar changes of c-Fos expression in an animal model of paroxysmal dystonia

Deep brain stimulation (DBS) of the globus pallidus internus (entopeduncular nucleus, EPN, in rodents) is important for the treatment of drug-refractory dystonia. The pathophysiology of this movement disorder and the mechanisms of DBS are largely unknown. Insights into the mechanisms of DBS in animal models of dystonia can be helpful for optimization of DBS and add-on therapeutics. We recently found that short-term EPN-DBS with 130 Hz (50 µA, 60 µs) for 3 h improved dystonia in dtsz hamsters and reduced spontaneous excitatory cortico-striatal activity in brain slices of this model, indicating fast effects on synaptic plasticity. Therefore, in the present study, we examined if these effects are related to changes of c-Fos, a marker of neuronal activity, in brains derived from dtsz hamsters after these short-term DBS or sham stimulations. After DBS vs. sham, c-Fos intensity was increased around the electrode, but the number of c-Fos+ cells was not altered within the whole EPN and projection areas (habenula, thalamus). DBS did not induce changes in striatal and cortical c-Fos+ cells as GABAergic (GAD67+ and parvalbumin-reactive) neurons in motor cortex and striatum. Unexpectedly, c-Fos+ cells were decreased in deep cerebellar nuclei (DCN) after DBS, suggesting that cerebellar changes may be involved in antidystonic effects already during short-term DBS. However, the present results do not exclude functional changes within the basal ganglia-thalamo-cortical network, which will be further investigated by long-term EPN stimulations. The present study indicates that the cerebellum deserves attention in ongoing examinations on the mechanisms of DBS in dystonia.

Deep brain stimulation with short versus conventional pulse width in Parkinson's disease and essential tremor: A systematic review and meta-analysis

BACKGROUND

To maximize clinical benefit and minimize stimulation-induced side effects, optimising deep brain stimulation (DBS) parameters is paramount. Recent literature suggests a potential benefit of short pulse width DBS (spDBS; ≤40 μs) over conventional pulse width DBS (cDBS; ≥60 μs) in movement disorders.

OBJECTIVE

To compare therapeutic window (TW), therapeutic and side effects and energy consumption of spDBS and cDBS in movement disorders.

METHODS

We systematically searched Medline, Embase, Cochrane Library and Web of Science. Appropriate paired analyses were performed.

RESULTS

Nine Parkinson's disease (PD) (143 patients), 4 essential tremor (ET) (26 patients) and no dystonia studies were included in the meta-analysis. TW defined as therapeutic amplitude range was larger with spDBS vs. cDBS in PD (standardized mean difference (SMD) = -1.04, p < 0.001) and ET (SMD = -0.71, p < 0.001), but the TW in terms of charge per pulse (CPP) did not differ. In PD, no differences were found in therapeutic and side effects (MDS-UPDRS-III, speech and gait, dyskinesia, non-motor symptoms and quality of life). In ET, Fahn-Tolosa-Marin Tremor Rating Scale was lower with spDBS vs. cDBS (SMD = 0.36, p < 0.001). A qualitative analysis suggested fewer stimulation-induced side effects with spDBS. CPP was lower with spDBS vs. cDBS in PD (SMD = 0.79, p < 0.001) and ET (MD = 46.46 nC, p < 0.001), but real-world data on battery longevity are lacking.

CONCLUSION

Although spDBS enlarges the TW as a wider amplitude range in both PD and ET, it does not alter TW defined by CPP. The therapeutic efficacy of spDBS is not different from cDBS in PD, but spDBS apparently induces more tremor reduction in ET.

Parkinsonian rest tremor can be distinguished from voluntary hand movements based on subthalamic and cortical activity

OBJECTIVE

To distinguish Parkinsonian rest tremor and different voluntary hand movements by analyzing brain activity.

METHODS

We re-analyzed magnetoencephalography and local field potential recordings from the subthalamic nucleus of six patients with Parkinson's disease. Data were obtained after withdrawal from dopaminergic medication (Med Off) and after administration of levodopa (Med On). Using gradient-boosted tree learning, we classified epochs as tremor, fist-clenching, forearm extension or tremor-free rest.

RESULTS

Subthalamic activity alone was insufficient for distinguishing the four different motor states (balanced accuracy mean: 38%, std: 7%). The combination of cortical and subthalamic features, in contrast, allowed for a much more accurate classification (balanced accuracy mean: 75%, std: 17%). Adding a single cortical area improved balanced accuracy by 17% on average, as compared to classification based on subthalamic activity alone. In most patients, the most informative cortical areas were sensorimotor cortical regions. Decoding performance was similar in Med On and Med Off.

CONCLUSIONS

Electrophysiological recordings allow for distinguishing several motor states, provided that cortical signals are monitored in addition to subthalamic activity.

SIGNIFICANCE

By combining cortical recordings, subcortical recordings and machine learning, adaptive deep brain stimulation systems might be able to detect tremor specifically and to respond adequately to several motor states.

Combining ultrasound and microelectrode recordings for postoperative localization of subthalamic electrodes in Parkinson's disease

OBJECTIVE

To assess transcranial sonography (TCS) as stand-alone tool and in combination with microelectrode recordings (MER) as a method for the postoperative localization of deep brain stimulation (DBS) electrodes in the subthalamic nucleus (STN).

METHODS

Individual dorsal and ventral boundaries of STN (n = 12) were determined on intraoperative MER. Postoperatively, a standardized TCS protocol was applied to measure medio-lateral, anterior-posterior and rostro-caudal electrode position using visualized reference structures (midline, substantia nigra). TCS and combined TCS-MER data were validated using fusion-imaging and clinical outcome data.

RESULTS

Test-retest reliability of standard TCS measures of electrode position was excellent. Computed tomography and TCS measures of distance between distal electrode contact and midline agreed well (Pearson correlation; r = 0.86; p < 0.001). Comparing our "gold standard" of rostro-caudal electrode localization relative to STN boundaries, i.e. combining MRI-based stereotaxy and MER data, with the combination of TCS and MER data, the measures differed by 0.32 ± 0.87 (range, -1.35 to 1.25) mm. Combined TCS-MER data identified the clinically preferred electrode contacts for STN-DBS with high accuracy (Coheńs kappa, 0.86).

CONCLUSIONS

Combined TCS-MER data allow for exact localization of STN-DBS electrodes.

SIGNIFICANCE

Our method provides a new option for monitoring of STN-DBS electrode location and guidance of DBS programming in Parkinson's disease.

Intraoperative Local Field Potential Beta Power and Three-Dimensional Neuroimaging Mapping Predict Long-Term Clinical Response to Deep Brain Stimulation in Parkinson Disease: A Retrospective Study

BACKGROUND

Directional deep brain stimulation (DBS) leads allow a fine-tuning control of the stimulation field, however, this new technology could increase the DBS programming time because of the higher number of the possible combinations used in directional DBS than in standard nondirectional electrodes. Neuroimaging leads localization techniques and local field potentials (LFPs) recorded from DBS electrodes implanted in basal ganglia are among the most studied biomarkers for DBS programing.

OBJECTIVE

This study aimed to evaluate whether intraoperative LFPs beta power and neuroimaging reconstructions correlate with contact selection in clinical programming of DBS in patients with Parkinson disease (PD).

MATERIALS AND METHODS

In this retrospective study, routine intraoperative LFPs recorded from all contacts in the subthalamic nucleus (STN) of 14 patients with PD were analyzed to calculate the beta band power for each contact. Neuroimaging reconstruction obtained through Brainlab Elements Planning software detected contacts localized within the STN. Clinical DBS programming contact scheme data were collected after one year from the implant. Statistical analysis evaluated the diagnostic performance of LFPs beta band power and neuroimaging data for identification of the contacts selected with clinical programming. We evaluated whether the most effective contacts identified based on the clinical response after one year from implant were also those with the highest level of beta activity and localized within the STN in neuroimaging reconstruction.

RESULTS

LFPs beta power showed a sensitivity of 67%, a negative predictive value (NPV) of 84%, a diagnostic odds ratio (DOR) of 2.7 in predicting the most effective contacts as evaluated through the clinical response. Neuroimaging reconstructions showed a sensitivity of 62%, a NPV of 77%, a DOR of 1.20 for contact effectivity prediction. The combined use of the two methods showed a sensitivity of 87%, a NPV of 87%, a DOR of 2.7 for predicting the clinically more effective contacts.

CONCLUSIONS

The combined use of LFPs beta power and neuroimaging localization and segmentations predict which are the most effective contacts as selected on the basis of clinical programming after one year from implant of DBS. The use of predictors in contact selection could guide clinical programming and reduce time needed for it.

Bradykinesia and rigidity modulated by functional connectivity between the primary motor cortex and globus pallidus in Parkinson's disease

The mechanisms underlying motor fluctuations in patients with Parkinson's disease (PD) are currently unclear. Regional brain stimulation reported the changing of motor symptoms, but the correlation with functional connectivity (FC) in the brain network is not fully understood. Hence, our study aimed to explore the relationship between motor symptom severity and FC using resting-state functional magnetic resonance imaging (rsfMRI) in the "on" and "off" states of PD. In 26 patients with sporadic PD, FC was assessed using rsfMRI, and clinical severity was analyzed using the motor part of the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS Part III) in the on and off states. Correlations between FC values and MDS-UPDRS Part III scores were assessed using Pearson's correlation coefficient. The correlation between FC and motor symptoms differed in the on and off states. FC between the ipsilateral precentral gyrus (PreCG) and globus pallidus (GP) correlated with the total MDS-UPDRS Part III scores and those for bradykinesia/rigidity in the off state. Lateralization analysis indicated that FC between the PreCG and GP correlated with the contralateral total MDS-UPDRS Part III scores and those for bradykinesia/rigidity in the off state. Aberrant FC in cortico-striatal circuits correlated with the severity of motor symptoms in PD. Cortico-striatal hyperconnectivity, particularly in motor pathways involving PreCG and GP, is related to motor impairments in PD. These findings may facilitate our understanding of the mechanisms underlying motor symptoms in PD and aid in developing treatment strategies such as brain stimulation for motor impairment.

Unraveling the complexities of programming neural adaptive deep brain stimulation in Parkinson's disease

Over the past three decades, deep brain stimulation (DBS) for Parkinson's disease (PD) has been applied in a continuous open loop fashion, unresponsive to changes in a given patient's state or symptoms over the course of a day. Advances in recent neurostimulator technology enable the possibility for closed loop adaptive DBS (aDBS) for PD as a treatment option in the near future in which stimulation adjusts in a demand-based manner. Although aDBS offers great clinical potential for treatment of motor symptoms, it also brings with it the need for better understanding how to implement it in order to maximize its benefits. In this perspective, we outline considerations for programing several key parameters for aDBS based on our experience across several aDBS-capable research neurostimulators. At its core, aDBS hinges on successful identification of relevant biomarkers that can be measured reliably in real-time working in cohesion with a control policy that governs stimulation adaption. However, auxiliary parameters such as the window in which stimulation is allowed to adapt, as well as the rate it changes, can be just as impactful on performance and vary depending on the control policy and patient. A standardize protocol for programming aDBS will be crucial to ensuring its effective application in clinical practice.

Applicability of clinical genetic testing for deep brain stimulation treatment in monogenic Parkinson's disease and monogenic dystonia: a multidisciplinary team perspective

In this perspective article, we highlight the possible applicability of genetic testing in Parkinson's disease and dystonia patients treated with deep brain stimulation (DBS). DBS, a neuromodulatory technique employing electrical stimulation, has historically targeted motor symptoms in advanced PD and dystonia, yet its precise mechanisms remain elusive. Genetic insights have emerged as potential determinants of DBS efficacy. Known PD genes such as GBA, SNCA, LRRK2, and PRKN are most studied, even though further studies are required to make firm conclusions. Variable outcomes depending on genotype is present in genetic dystonia, as DYT-TOR1A, NBIA/DYTPANK2, DYT-SCGE and X-linked dystonia-parkinsonism have demonstrated promising outcomes following GPi-DBS, while varying outcomes have been documented in DYT-THAP1. We present two clinical vignettes that illustrate the applicability of genetics in clinical practice, with one PD patient with compound GBA mutations and one GNAL dystonia patient. Integrating genetic testing into clinical practice is pivotal, particularly with advancements in next-generation sequencing. However, there is a clear need for further research, especially in rarer monogenic forms. Our perspective is that applying genetics in PD and dystonia is possible today, and despite challenges, it has the potential to refine patient selection and enhance treatment outcomes.

Machine learning for adaptive deep brain stimulation in Parkinson's disease: closing the loop

Parkinson's disease (PD) is the second most common neurodegenerative disease bearing a severe social and economic impact. So far, there is no known disease modifying therapy and the current available treatments are symptom oriented. Deep Brain Stimulation (DBS) is established as an effective treatment for PD, however current systems lag behind today's technological potential. Adaptive DBS, where stimulation parameters depend on the patient's physiological state, emerges as an important step towards "smart" DBS, a strategy that enables adaptive stimulation and personalized therapy. This new strategy is facilitated by currently available neurotechnologies allowing the simultaneous monitoring of multiple signals, providing relevant physiological information. Advanced computational models and analytical methods are an important tool to explore the richness of the available data and identify signal properties to close the loop in DBS. To tackle this challenge, machine learning (ML) methods applied to DBS have gained popularity due to their ability to make good predictions in the presence of multiple variables and subtle patterns. ML based approaches are being explored at different fronts such as the identification of electrophysiological biomarkers and the development of personalized control systems, leading to effective symptom relief. In this review, we explore how ML can help overcome the challenges in the development of closed-loop DBS, particularly its role in the search for effective electrophysiology biomarkers. Promising results demonstrate ML potential for supporting a new generation of adaptive DBS, with better management of stimulation delivery, resulting in more efficient and patient-tailored treatments.

One-year outcomes of deep brain stimulation in refractory Tourette syndrome

AIM

Deep brain stimulation (DBS) is one option for treating refractory Tourette syndrome (TS); however, it remains unclear which preoperative factors are predictive of DBS outcomes. This study investigated the efficacy of DBS targeting the anteromedial globus pallidus internus and evaluated predisposing factors affecting the outcomes of DBS in a single center in Korea.

METHOD

Twenty patients who had undergone DBS for refractory TS were reviewed retrospectively. Tic symptoms were followed up at 3-month intervals for up to 1 year after surgery. The Yale Global Tic Severity Scale was used to evaluate preoperative/postoperative tic symptoms. Scores from the Yale-Brown Obsessive Compulsive Scale, Beck Depression Inventory-II, and Beck Anxiety Inventory were also evaluated.

RESULTS

Patients with refractory TS achieved improvement in tic symptoms within 1 year after DBS. Initial responders who achieved a 35% reduction in Yale Global Tic Severity Scale total score within the first 3 months after DBS showed larger treatment effects during 1-year follow-up. Although no clinical or demographic factors were predictive of initial responses, patients with serious self-injurious behaviors tended to show delayed responses.

CONCLUSION

This is the first study to our knowledge to report the DBS outcomes of 20 patients with TS in a single center in Asia. Our study supports the efficacy of DBS targeting anteromedial globus pallidus internus in refractory TS with no evident serious adverse events. Initial responses after DBS seem to be a predictor of long-term outcomes after surgery.

Impact of deep brain stimulation (DBS) on olfaction in Parkinson's disease: Clinical features and functional hypotheses

Deep brain stimulation (DBS) is a surgical therapy typically applied in Parkinson's disease (PD). The efficacity of DBS on the control of motor symptoms in PD is well grounded while the efficacity on non-motor symptoms is more controversial, especially on olfactory disorders (ODs). The present review shows that DBS does not improve hyposmia but can affect positively identification/discrimination scores in PD. The functional hypotheses suggest complex mechanisms in terms of cerebral connectivity and neurogenesis process which could act indirectly on the olfactory bulb and olfactory pathways related to specific cognitive olfactory tasks. The functional hypotheses also suggest complex mechanisms of cholinergic neurotransmitter interactions involved in these pathways. Finally, the impact of DBS on general cognitive functions in PD could also be beneficial to identification/discrimination tasks in PD.

Effects of deep brain stimulation of the subthalamic nucleus on patients with Parkinson's disease: a machine-learning voice analysis

Introduction

Deep brain stimulation of the subthalamic nucleus (STN-DBS) can exert relevant effects on the voice of patients with Parkinson's disease (PD). In this study, we used artificial intelligence to objectively analyze the voices of PD patients with STN-DBS.

Materials and methods

In a cross-sectional study, we enrolled 108 controls and 101 patients with PD. The cohort of PD was divided into two groups: the first group included 50 patients with STN-DBS, and the second group included 51 patients receiving the best medical treatment. The voices were clinically evaluated using the Unified Parkinson's Disease Rating Scale part-III subitem for voice (UPDRS-III-v). We recorded and then analyzed voices using specific machine-learning algorithms. The likelihood ratio (LR) was also calculated as an objective measure for clinical-instrumental correlations.

Results

Clinically, voice impairment was greater in STN-DBS patients than in those who received oral treatment. Using machine learning, we objectively and accurately distinguished between the voices of STN-DBS patients and those under oral treatments. We also found significant clinical-instrumental correlations since the greater the LRs, the higher the UPDRS-III-v scores.

Discussion

STN-DBS deteriorates speech in patients with PD, as objectively demonstrated by machine-learning voice analysis.

Case report: Unilateral GPi DBS in secondary myoclonus-dystonia syndrome after acute disseminated encephalomyelitis

Introduction

Deep brain stimulation (DBS) is an established and effective therapy for movement disorders. Here, we present a case of secondary myoclonus-dystonia syndrome following acute disseminated encephalomyelitis (ADEM) in childhood, which was alleviated by DBS. Using a patient-specific connectome analysis, we sought to characterise the fibres and circuits affected by stimulation.

Case report

We report a case of a 20-year-old man with progressive dystonia, myoclonic jerks, and impaired concentration following childhood ADEM. Motor assessments utilising the Unified Myoclonus Rating Scale (UMRS) and the Burke-Fahn-Marsden Dystonia Rating Scale (BFMDRS) revealed a greater improvement in dystonia compared to myoclonus following adjustments of DBS parameters. These adjustments were based on visualisation of electrode position and volume of tissue activated (VTA) 3 years after surgery. A patient-specific connectome analysis using the VTA as a region of interest revealed fibre tracts connecting to the cerebello-thalamo-cortical network and the superior frontal gyrus in addition to basal ganglia circuits as particularly effective.

Conclusion

Globus pallidus internus (GPi) DBS shows promise as a treatment for secondary myoclonus-dystonia syndromes. Personalised structural considerations, tailored to individual symptoms and clinical characteristics, can provide significant benefits. Patient-specific connectome analysis, specifically, offers insights into the structures involved and may enable a favourable treatment response.

Subthalamic Deep Brain Stimulation in Parkinson's Disease: A Boon or Bane - A Single Centre Retrospective Observational Study from India

Background  Subthalamic deep brain stimulation (STN-DBS) for refractory Parkinson's disease (PD) is more of a modality of treatment that is empirical, for which a physiological explanation is being sought. This study was done to determine the outcome and complications of patients undergoing STN-DBS for PD. Methods  This retrospective observational cohort study was conducted in an advanced neuromedicine facility in eastern India for 9 years (August 2013-August 2022), which included all patients undergoing STN-DBS. Results  A total of 53 patients were operated on during the study period. The mean age group of the study population was 60.5 (standard deviation [SD]: 8.2) years with a male (33 [62.3%]) predominance. The most common presenting complaints included rigidity and hypokinesia (27), severe dyskinesia (21), and tremors (17). During the postoperative period, rigidity and hypokinesia (21), severe dyskinesia (16), and tremors (12) improved significantly in a subset of the patients. The majority (45 [84.9%]) of these cases received bilateral monopolar simulation, whereas three patients (5.7%) had bilateral bipolar stimulation. Unilateral bipolar stimulation was used in five (9.4%) patients. In the immediate postoperative period, they were initiated on limb, speech, and swallowing therapy as indicated. Surgery-related complications were seen in five (9.4%) cases. At 6 months of follow-up, a significant improvement in the Unified PD rating scale component (mainly motor examination and complication of PD therapy) was noted in the majority (36 [67.9%]) of patients. One patient developed neuroleptic malignant syndrome and succumbed to his illness on the fourth postoperative day. Conclusion  Given these findings, STN-DBS appears to be a good, safe, and effective treatment for a subset of medically refractory PD with an overall improvement in two-thirds of the study cohort and less than 10% risk of complications.

Sub-harmonic entrainment of cortical gamma oscillations to deep brain stimulation in Parkinson's disease: Model based predictions and validation in three human subjects

OBJECTIVES

The exact mechanisms of deep brain stimulation (DBS) are still an active area of investigation, in spite of its clinical successes. This is due in part to the lack of understanding of the effects of stimulation on neuronal rhythms. Entrainment of brain oscillations has been hypothesised as a potential mechanism of neuromodulation. A better understanding of entrainment might further inform existing methods of continuous DBS, and help refine algorithms for adaptive methods. The purpose of this study is to develop and test a theoretical framework to predict entrainment of cortical rhythms to DBS across a wide range of stimulation parameters.

MATERIALS AND METHODS

We fit a model of interacting neural populations to selected features characterising PD patients' off-stimulation finely-tuned gamma rhythm recorded through electrocorticography. Using the fitted models, we predict basal ganglia DBS parameters that would result in 1:2 entrainment, a special case of sub-harmonic entrainment observed in patients and predicted by theory.

RESULTS

We show that the neural circuit models fitted to patient data exhibit 1:2 entrainment when stimulation is provided across a range of stimulation parameters. Furthermore, we verify key features of the region of 1:2 entrainment in the stimulation frequency/amplitude space with follow-up recordings from the same patients, such as the loss of 1:2 entrainment above certain stimulation amplitudes.

CONCLUSION

Our results reveal that continuous, constant frequency DBS in patients may lead to nonlinear patterns of neuronal entrainment across stimulation parameters, and that these responses can be predicted by modelling. Should entrainment prove to be an important mechanism of therapeutic stimulation, our modelling framework may reduce the parameter space that clinicians must consider when programming devices for optimal benefit.

Preliminary Experience with a Four-Lead Implantable Pulse Generator for Deep Brain Stimulation

BACKGROUND

Implantable pulse generators (IPGs) store energy and deliver electrical impulses for deep brain stimulation (DBS) to treat neurological and psychiatric disorders. IPGs have evolved over time to meet the demands of expanding clinical indications and more nuanced therapeutic approaches.

OBJECTIVES

The aim of this study was to examine the workflow of the first 4-lead IPG for DBS in patients with complex disease.

METHOD

The engineering capabilities, clinical use cases, and surgical technique are described in a cohort of 12 patients with epilepsy, essential tremor, Parkinson's disease, mixed tremor, and Tourette's syndrome with comorbid obsessive-compulsive disorder between July 2021 and July 2022.

RESULTS

This system is a rechargeable 32-channel, 4-port system with independent current control that can be connected to 8 contact linear or directionally segmented leads. The system is ideal for patients with mixed disease or those with multiple severe symptoms amenable to >2 lead implantations. A multidisciplinary team including neurologists, radiologists, and neurosurgeons is necessary to safely plan the procedure. There were no serious intraoperative or postoperative adverse events. One patient required revision surgery for bowstringing.

CONCLUSIONS

This new 4-lead IPG represents an important new tool for DBS surgery with the ability to expand lead implantation paradigms for patients with complex disease.

Biomarker-guided neuromodulation aids memory in traumatic brain injury

Traumatic brain injury (TBI) is a leading cause of cognitive disability in adults, often characterized by marked deficits in episodic memory and executive function. Prior studies have found that direct electrical stimulation of the temporal cortex yielded improved memory in epilepsy patients, but it is not clear if these results generalize to patients with a specific history of TBI. Here we asked whether applying closed-loop, direct electrical stimulation to lateral temporal cortex could reliably improve memory in a TBI cohort. Among a larger group of patients undergoing neurosurgical evaluation for refractory epilepsy, we recruited a subset of patients with a history of moderate-to-severe TBI. By analyzing neural data from indwelling electrodes as patients studied and recalled lists of words, we trained personalized machine-learning classifiers to predict momentary fluctuations in mnemonic function in each patient. We subsequently used these classifiers to trigger high-frequency stimulation of the lateral temporal cortex (LTC) at moments when memory was predicted to fail. This strategy yielded a 19% boost in recall performance on stimulated as compared with non-stimulated lists (P = 0.012). These results provide a proof-of-concept for using closed-loop stimulation of the brain in treatment of TBI-related memory impairment.

Evaluation of the PaCER Algorithm for Postoperative Subthalamic Nucleus Deep Brain Stimulation Electrode Localization. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023;2023:1-4. [PMID: 38083396 DOI: 10.1109/embc40787.2023.10340555] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Deep Brain Stimulation (DBS) is an established therapy for many movement disorders. DBS entails electrical stimulation of precise brain structures using permanently implanted electrodes. Following implantation, locating the electrodes relative to the target brain structure assists patient outcome optimization. Here we evaluated an open-source automatic algorithm (PaCER) to localize individual electrodes on Computed Tomography imaging (co-registered to Magnetic Resonance Imaging). In a dataset of 111 participants, we found a modified version of the algorithm matched manual-markups with median error less than 0.191 mm (interquartile range 0.698 mm). Given the error is less than the voxel resolution (1 mm3) of the images, we conclude that the automatic algorithm is suitable for DBS electrode localizations.Clinical Relevance- Automated DBS electrode localization identifies the closest electrode to the target brain structure; allowing the neurologist to direct electrical stimulation to maximize patient outcomes. Further, if none of the electrodes are deemed suitable, localization will guide re-implantation.

Deep brain stimulation programming for intractable obsessive-compulsive disorder using a long pulse width

Introduction

Around 25% of patients with obsessive-compulsive disorder (OCD) do not respond to medication or psychotherapy, producing significant impairment and treatment challenges. Deep Brain Stimulation (DBS) has been shown in multiple blinded trials to be a safe and durable emerging option for treatment-refractory OCD. Intraoperative device interrogation offers a theoretical anchor for starting outpatient DBS programming; however, no definitive post-operative programming algorithm for psychiatrists exists currently.

Case

Here we present a 58-year-old female with childhood-onset, severe, intractable OCD with multiple failed trials of psychotherapy, medication, and electroconvulsive therapy. After interdisciplinary evaluation, she underwent bilateral electrode implantation targeting the anterior limb of the internal capsule, nucleus accumbens (ALIC/NAc). Intraoperative interrogation afforded sparse information about a preferred lead contact or current density target. Subsequent outpatient interrogation consisted of systematic and independent mapping using monopolar cathodic stimulation with constant current. Modulating bipolar and triple monopolar configurations, amplitude, and pulse width all failed to induce observable effects. Given negligible interrogation feedback, we created an electrical field through the ALIC bilaterally, using the three most ventral contacts to create triple monopoles, with a long pulse width and moderate amperage.

Conclusion

Three months post-programming, the patient reported significant improvement in OCD symptoms, particularly checking behaviors, with response sustained over the next several months. As with our case, the majority of DBS lead contacts do not induce affective or physiological markers in patients, complicating programming optimization. Here, we discuss an approach to titrating various stimulation parameters and purported mechanisms of physiological markers in DBS for OCD.

Low beta-band suppression as a tool for DBS contact selection for akinetic-rigid symptoms in Parkinson's disease

BACKGROUND

Suppression of pathologically altered activity in the beta-band has previously been suggested as a biomarker for feedback-based neurostimulation in subthalamic deep brain stimulation (STN-DBS) for Parkinson's Disease (PD).

OBJECTIVE

To assess the utility of beta-band suppression as a tool for contact selection in STN-DBS for PD.

METHODS

A sample of seven PD patients (13 hemispheres) with newly implanted directional DBS leads of the STN were recorded during a standardized monopolar contact review (MPR). Recordings were received from contact pairs adjacent to the stimulation contact. The degree of beta-band suppression for each investigated contact was then correlated to the respective clinical results. Additionally, we have implemented a cumulative ROC analysis, to test the predictive value of beta-band suppression on the clinical efficacy of the respective contacts.

RESULTS

Stimulation ramping led to frequency-specific changes in the beta-band, while lower frequencies remained unaffected. Most importantly, our results showed that the degree of low beta-band suppression from baseline activity (stimulation off) served as a predictor for clinical efficacy of the respective stimulation contact. In contrast suppression of high beta-band activity yielded no predictive power.

CONCLUSION

The degree of low beta-band suppression can serve as a time-saving, objective tool for contact selection in STN-DBS.

Comparison of Monopolar Review to Fixed Parameter Fractionation in Deep Brain Stimulation

Background

Technological advancements in deep brain stimulation (DBS) require methodological changes in programming. Fractionalization poses significant practical challenges for the most common approach for assessing DBS efficacy, monopolar review (MR).

Objectives

Two DBS programming methods: MR and fixed parameter vertical and horizontal fractionalization (FPF) were compared.

Methods

A two-phase process of vertical and horizontal FPF was performed. MR was conducted thereafter. After a short wash-out period, both optimal configurations determined by MR and FPF were tested in a double-blind randomized manner.

Results

Seven PD patients were enrolled, providing 11 hemispheres to compare the two conditions. In all subjects, the blinded examiner selected a directional or fractionalization configuration. There was no significant difference in clinical benefits between MR and FPF. FPF was the preferred method for initial programming as selected by subject and clinician.

Conclusions

FPF programming is a viable and efficient methodology that may be incorporated into clinical practice.

Potential Biomarkers for Parkinson Disease from Functional Enrichment and Bioinformatic Analysis of Global Gene Expression Patterns of Blood and Substantia Nigra Tissues

The Parkinson disease (PD) is the second most common neurodegenerative disorder affecting the central nervous system and motor functions. The biological complexity of PD is yet to reveal potential targets for intervention or to slow the disease severity. Therefore, this study aimed to compare the fidelity of blood to substantia nigra (SN) tissue gene expression from PD patients to provide a systematic approach to predict role of the key genes of PD pathobiology. Differentially expressed genes (DEGs) from multiple microarray data sets of PD blood and SN tissue from GEO database are identified. Using the theoretical network approach and variety of bioinformatic tools, we prioritized the key genes from DEGs. A total of 540 and 1024 DEGs were identified in blood and SN tissue samples, respectively. Functional pathways closely related to PD such as ERK1 and ERK2 cascades, mitogen-activated protein kinase (MAPK) signaling, Wnt, nuclear factor-κB (NF-κB), and PI3K-Akt signaling were observed by enrichment analysis. Expression patterns of 13 DEGs were similar in both blood and SN tissues. Comprehensive network topological analysis and gene regulatory networks identified additional 10 DEGs functionally connected with molecular mechanisms of PD through the mammalian target of rapamycin (mTOR), autophagy, and AMP-activated protein kinase (AMPK) signaling pathways. Potential drug molecules were identified by chemical-protein network and drug prediction analysis. These potential candidates can be further validated in vitro/in vivo to be used as biomarkers and/or novel drug targets for the PD pathology and/or to arrest or delay the neurodegeneration over the years, respectively.

Open Mind Neuromodulation Interface for the CorTec Brain Interchange (OMNI-BIC): an investigational distributed research platform for next-generation clinical neuromodulation research

The rise of adaptive stimulation approaches has shown great therapeutic promise in the growing field of neuromodulation. The discovery and growth of these novel adaptive stimulation paradigms has been largely concentrated around several implantable devices with research application programming interfaces (APIs) that allow for custom applications to be created for clinical neuromodulation studies. However, the sunsetting of devices and ongoing development of new platforms is leading to an increased fragmentation in the research environment- resulting in the reinvention of system features and the inability to leverage previous development efforts for future studies. The Open Mind Neuromodulation Interface (OMNI) is a previously proposed solution to address the weaknesses of the DLL-driven API approach of past neuromodulation research by utilizing an alternative gRPC-enabled microservice framework. Here, we introduce OMNI-BIC, an implementation of the OMNI framework to the CorTec Brain Interchange system. This paper describes the design and implementation of the OMNI-BIC software tools and demonstrates the framework's capabilities for implementing customized neuromodulation therapies for clinical investigations. Through the development and deployment of the OMNI-BIC system, we hope to improve future clinical studies with the Brain Interchange system and aid in continuing the growth and momentum of the exciting field of adaptive neuromodulation.

DBS-evoked cortical responses index optimal contact orientations and motor outcomes in Parkinson's disease

Although subthalamic deep brain stimulation (DBS) is a highly-effective treatment for alleviating motor dysfunction in patients with Parkinson's disease (PD), clinicians currently lack reliable neurophysiological correlates of clinical outcomes for optimizing DBS parameter settings, which may contribute to treatment inefficacies. One parameter that could aid DBS efficacy is the orientation of current administered, albeit the precise mechanisms underlying optimal contact orientations and associated clinical benefits are not well understood. Herein, 24 PD patients received monopolar stimulation of the left STN during magnetoencephalography and standardized movement protocols to interrogate the directional specificity of STN-DBS current administration on accelerometer metrics of fine hand movements. Our findings demonstrate that optimal contact orientations elicit larger DBS-evoked cortical responses in the ipsilateral sensorimotor cortex, and importantly, are differentially predictive of smoother movement profiles in a contact-dependent manner. Moreover, we summarize traditional evaluations of clinical efficacy (e.g., therapeutic windows, side effects) for a comprehensive review of optimal/non-optimal STN-DBS contact settings. Together, these data suggest that DBS-evoked cortical responses and quantitative movement outcomes may provide clinical insight for characterizing the optimal DBS parameters necessary for alleviating motor symptoms in patients with PD in the future.

A wearable platform for closed-loop stimulation and recording of single-neuron and local field potential activity in freely moving humans

Advances in technologies that can record and stimulate deep brain activity in humans have led to impactful discoveries within the field of neuroscience and contributed to the development of novel therapies for neurological and psychiatric disorders. Further progress, however, has been hindered by device limitations in that recording of single-neuron activity during freely moving behaviors in humans has not been possible. Additionally, implantable neurostimulation devices, currently approved for human use, have limited stimulation programmability and restricted full-duplex bidirectional capability. In this study, we developed a wearable bidirectional closed-loop neuromodulation system (Neuro-stack) and used it to record single-neuron and local field potential activity during stationary and ambulatory behavior in humans. Together with a highly flexible and customizable stimulation capability, the Neuro-stack provides an opportunity to investigate the neurophysiological basis of disease, develop improved responsive neuromodulation therapies, explore brain function during naturalistic behaviors in humans and, consequently, bridge decades of neuroscientific findings across species.

Association of subthalamic beta frequency sub-bands to symptom severity in patients with Parkinson's disease: A systematic review

OBJECTIVE

Local field potentials (LFP), specifically beta (13-30Hz) frequency measures, have been found to be associated with motor dysfunction in people with Parkinson's disease (PwPD). A consensus on beta subband (low- and high-beta) relationships to clinical state or therapy response has yet to be determined. The objective of this review is to synthesize literature reporting the association of low- and high-beta characteristics to clinical ratings of motor symptoms in PwPD.

METHODS

A systematic search of existing literature was completed using EMBASE. Articles which collected subthalamic nucleus (STN) LFPs using macroelectrodes in PwPD, analyzed low- (13-20 Hz) and high-beta (21-35 Hz) bands, collected UPDRS-III, and reported correlational strength or predictive capacity of LFPs to UPDRS-III scores.

RESULTS

The initial search yielded 234 articles, with 11 articles achieving inclusion. Beta measures included power spectral density, peak characteristics, and burst characteristics. High-beta was a significant predictor of UPDRS-III responses to therapy in 5 (100%) articles. Low-beta was significantly associated with UPDRS-III total score in 3 (60%) articles. Low- and high-beta associations to UPDRS-III subscores were mixed.

CONCLUSION

This systematic review reinforces previous reports that beta band oscillatory measures demonstrate a consistent relationship to Parkinsonian motor symptoms and ability to predict motor response to therapy. Specifically, high-beta, demonstrated a consistent ability to predict UPDRS-III responses to common PD therapies, while low-beta measures were associated with general Parkinsonian symptom severity. Continued research is needed to determine which beta subband demonstrates the greatest association to motor symptom subtypes and potentially offers clinical utility toward LFP-guided DBS programming and adaptive DBS.

Artificial neural network-based rapid predictor of biological nerve fiber activation for DBS applications

Objective.Computational models are powerful tools that can enable the optimization of deep brain stimulation (DBS). To enhance the clinical practicality of these models, their computational expense and required technical expertise must be minimized. An important aspect of DBS models is the prediction of neural activation in response to electrical stimulation. Existing rapid predictors of activation simplify implementation and reduce prediction runtime, but at the expense of accuracy. We sought to address this issue by leveraging the speed and generalization abilities of artificial neural networks (ANNs) to create a novel predictor of neural fiber activation in response to DBS.Approach.We developed six variations of an ANN-based predictor to predict the response of individual, myelinated axons to extracellular electrical stimulation. ANNs were trained using datasets generated from a finite-element model of an implanted DBS system together with multi-compartment cable models of axons. We evaluated the ANN-based predictors using three white matter pathways derived from group-averaged connectome data within a patient-specific tissue conductivity field, comparing both predicted stimulus activation thresholds and pathway recruitment across a clinically relevant range of stimulus amplitudes and pulse widths.Main results.The top-performing ANN could predict the thresholds of axons with a mean absolute error (MAE) of 0.037 V, and pathway recruitment with an MAE of 0.079%, across all parameters. The ANNs reduced the time required to predict the thresholds of 288 axons by four to five orders of magnitude when compared to multi-compartment cable models.Significance.We demonstrated that ANNs can be fast, accurate, and robust predictors of neural activation in response to DBS.

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

Background

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

Objective

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

Methods

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

Results

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

Conclusion

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

Clinical trial registration

ClinicalTrials.gov, identifier NCT04658641.

Clinician vs. imaging-based subthalamic nucleus deep brain stimulation programming

INTRODUCTION

We sought to explore whether electrode visualization tools (EVT) can accurately predict the selection of optimal Deep Brain Stimulation (DBS) electrode contacts.

METHODS

Twelve patients with Parkinson's disease (PD) undergoing STN-DBS at The Ohio State University were enrolled in a prospective analysis to evaluate the accuracy of EVT-based vs. standard DBS programming. EVTs were generated by the Surgical Information Sciences (SIS) system to develop a 3D model showing the implanted lead location relative to the STN. Then, imaging-based data were compared to the results of a standard monopolar review to evaluate concordance with clinical data and time spent selecting useable, non-useable, and borderline electrode contacts.

RESULTS

A total of 18 DBS leads (n = 68 electrode contacts) were analyzed. The concordance between EVT and standard clinical programming expressed as the kappa coefficient was 0.65 (82.35% raw agreement) for non-useable, 0.52 for useable (64.71% raw agreement), and 0.52 for borderline (58.82% raw agreement). The average time spent determining whether an electrode contact was useable, non-useable, or borderline was 1.46 ± 0.76 min with EVT vs. 61.25 ± 17.47 with standard monopolar review. Eight different categories of side effects were identified, with facial pulling and speech difficulties being observed with the most frequency. The type of side effect observed was accurately predicted using EVT 90% of the time.

CONCLUSIONS

This study demonstrates that next-generation EVT-based programming can be implemented into STN-DBS programming workflows with a considerable saving of time and effort spent in testing combinations of stimulation settings, particularly for the identification of non-useable electrode contacts.

Case report: Left gaze and facial nerve palsies after ventral intermediate thalamic nucleus deep brain stimulation implantation

Deep brain stimulation (DBS) to the ventral intermediate nucleus (VIM) of the thalamus has become a common procedure for some refractory, medication-resistant movement disorders like essential tremors. The most common adverse effects from this surgery include dysarthria and gait disturbances. This case report details a left gaze and ipsilateral facial nerve palsy following overshot cannula insertion into the pons during a VIM DBS procedure. Initial patient presentation after surgery revealed significant impairment of horizontal gaze to the left. This improved during follow-up visits and after the recession of the bilateral medial recti. When considering complications of the VIM DBS procedure, surgeons should be aware of the risks of cannula overshot given the anatomic proximity between the thalamus and brainstem. Furthermore, patients should be aware of this risk when making their surgical decision. All patients who undergo VIM DBS should be assessed for cranial nerve deficits after placement.

Local Field Potential-Guided Contact Selection Using Chronically Implanted Sensing Devices for Deep Brain Stimulation in Parkinson's Disease

Intra- and perioperatively recorded local field potential (LFP) activity of the nucleus subthalamicus (STN) has been suggested to guide contact selection in patients undergoing deep brain stimulation (DBS) for Parkinson's disease (PD). Despite the invention of sensing capacities in chronically implanted devices, a comprehensible algorithm that enables contact selection using such recordings is still lacking. We evaluated a fully automated algorithm that uses the weighted average of bipolar recordings to determine effective monopolar contacts based on elevated activity in the beta band. LFPs from 14 hemispheres in seven PD patients with newly implanted directional DBS leads of the STN were recorded. First, the algorithm determined the stimulation level with the highest beta activity. Based on the prior determined level, the directional contact with the highest beta activity was chosen in the second step. The mean clinical efficacy of the contacts chosen using the algorithm did not statistically differ from the mean clinical efficacy of standard contact selection as performed in clinical routine. All recording sites were projected into MNI standard space to investigate the feasibility of the algorithm with respect to the anatomical boundaries of the STN. We conclude that the proposed algorithm is a first step towards LFP-based contact selection in STN-DBS for PD using chronically implanted devices.

Remote programming for subthalamic deep brain stimulation in Parkinson's disease

Introduction

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is effective for the treatment of Parkinson's disease (PD). Moreover, remote programming is widely used in Mainland China. This necessitates evaluating the ability of remote programming to achieve the ideal postoperative effect. Therefore, we aimed to retrospectively evaluate the effects of different programming modes on the effectiveness of STN-DBS 12 months postoperatively in patients with PD.

Methods

Clinical data were collected retrospectively, before and 12 months after surgery, in 83 patients with PD. Based on the programming modes voluntarily selected by the patients during 12 months postoperatively, they were divided into three groups, namely remote programming alone, hospital programming alone, and hospital + remote programming. We compared the programming data and the effects of different programming methods on STN-DBS-related improvements 12 months postoperatively among these groups. Furthermore, we analyzed STN-DBS-related improvements at 12 months postoperatively in 76 patients.

Results

The effectiveness of STN-DBS was not influenced by the three programming modes. The postoperative Movement Disorder Society Unified Parkinson's Disease Rating Scale scores did not reveal statistically significant differences between the remote alone and hospital alone programming groups, except for motor examination. The postoperative decline in the levodopa equivalent daily dose was most apparent in the hospital programming alone group. The programming frequency of the hospital + remote programming group was considerably higher than that of the remaining groups. Seventy-six patients with PD displayed good STN-DBS surgical efficacy.

Conclusion

Programming modes do not influence the short-term efficacy of STN-DBS, and remote programming can yield a satisfactory surgical effect.

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.

Artifact characterization and mitigation techniques during concurrent sensing and stimulation using bidirectional deep brain stimulation platforms

Bidirectional deep brain stimulation (DBS) platforms have enabled a surge in hours of recordings in naturalistic environments, allowing further insight into neurological and psychiatric disease states. However, high amplitude, high frequency stimulation generates artifacts that contaminate neural signals and hinder our ability to interpret the data. This is especially true in psychiatric disorders, for which high amplitude stimulation is commonly applied to deep brain structures where the native neural activity is miniscule in comparison. Here, we characterized artifact sources in recordings from a bidirectional DBS platform, the Medtronic Summit RC + S, with the goal of optimizing recording configurations to improve signal to noise ratio (SNR). Data were collected from three subjects in a clinical trial of DBS for obsessive-compulsive disorder. Stimulation was provided bilaterally to the ventral capsule/ventral striatum (VC/VS) using two independent implantable neurostimulators. We first manipulated DBS amplitude within safe limits (2–5.3 mA) to characterize the impact of stimulation artifacts on neural recordings. We found that high amplitude stimulation produces slew overflow, defined as exceeding the rate of change that the analog to digital converter can accurately measure. Overflow led to expanded spectral distortion of the stimulation artifact, with a six fold increase in the bandwidth of the 150.6 Hz stimulation artifact from 147–153 to 140–180 Hz. By increasing sense blank values during high amplitude stimulation, we reduced overflow by as much as 30% and improved artifact distortion, reducing the bandwidth from 140–180 Hz artifact to 147–153 Hz. We also identified artifacts that shifted in frequency through modulation of telemetry parameters. We found that telemetry ratio changes led to predictable shifts in the center-frequencies of the associated artifacts, allowing us to proactively shift the artifacts outside of our frequency range of interest. Overall, the artifact characterization methods and results described here enable increased data interpretability and unconstrained biomarker exploration using data collected from bidirectional DBS devices.

Long-term efficacy with deep brain stimulation of the globus pallidus internus in cervical dystonia: a retrospective monocentric study

BACKGROUND

Cervical dystonia (CD) is characterized by involuntary contractions of the cervical muscles. Data on long-term effectiveness of deep brain stimulation (DBS) are rare. The aim of this study was to evaluate the longitudinal ten years treatment efficacy of DBS in the globus pallidus internus (GPI).

METHODS

A retrospective single-center data analysis was performed on patients with idiopathic CD, who were treated with GPI DBS for at least 10 years. TWSTR severity score and individual sub-items were compared between pre and post DBS surgery (n = 15) over time.

RESULTS

There was a significant and persistent positive effect regarding the severity of TWSTRS between the conditions immediately before and 1, 5, and 10 years after establishment of GPI DBS (mean difference: 6.6-7 ± 1.6). Patients with increasing CD complexity showed a poorer response to established treatment forms, such as injection of botulinum toxin and were thus DBS candidates. Especially a predominant torticollis was significantly improved by DBS.

CONCLUSION

GPI DBS is an effective procedure especially in severely affected patients with a positive 10-year outcome. It should be considered in more complex CD-forms or predominant torticollis.

Deep Brain Stimulation for Pediatric Dystonia: A Review of the Literature and Suggested Programming Algorithm

Deep brain stimulation (DBS) is an established intervention for use in pediatric movement disorders, especially dystonia. Although multiple publications have provided guidelines for deep brain stimulation patient selection and programming in adults, there are no evidence-based or consensus statements published for pediatrics. The result is lack of standardized care and underutilization of this effective treatment. To this end, we assembled a focus group of 13 pediatric movement disorder specialists and 1 neurosurgeon experienced in pediatric deep brain stimulation to review recent literature and current practices and propose a standardized approach to candidate selection, implantation target site selection, and programming algorithms. For pediatric dystonia, we provide algorithms for (1) programming for initial session and follow-up sessions, and (2) troubleshooting side effects encountered during programming. We discuss common side effects, how they present, and recommendations for management. This topical review serves as a resource for movement disorders specialists interested in using deep brain stimulation for pediatric dystonia.