Theta frequency deep brain stimulation in the subthalamic nucleus improves working memory in Parkinson's disease.

Most research in Parkinson's disease focuses on improving motor symptoms. Yet, up to 80% of patients present with non-motor symptoms that often have a large impact on patients' quality of life. Impairment in working memory, a fundamental cognitive process, is common in Parkinson's disease. While deep brain stimulation (DBS) of the subthalamic nucleus (STN) improves motor symptoms in Parkinson's disease, its impact on cognitive functions is less well studied. Here, we examine the effect of DBS in the theta, beta, low and high gamma frequency on working memory in 20 Parkinson's disease patients with bilateral STN-DBS. A linear mixed effects model demonstrates that STN-DBS in the theta frequency improves working memory performance. This effect is frequency-specific and was absent for beta and gamma frequency stimulation. Further, this effect is specific to cognitive performance, as theta frequency DBS did not affect motor function. A non-parametric cluster-based permutation analysis of whole-brain normative structural connectivity shows that working memory enhancement by theta frequency stimulation is associated with higher connectivity between the stimulated subthalamic area and the right middle frontal gyrus. Again, this association is frequency- and task-specific. These findings highlight the potential of theta frequency STN-DBS as a targeted intervention to improve working memory in patients with Parkinson's disease.

Diffusion tensor imaging in pediatric patients with dystonia.

BACKGROUND: Childhood-onset dystonia is often progressive and severely impairs a child´s life. The pathophysiology is very heterogeneous and treatment responses vary in patients with dystonia. Factors influencing treatment effects remain to be elucidated. We hypothesize that differences in brain connectivity and fiber coherence contribute to the heterogeneity in treatment response among pediatric patients with inherited and acquired dystonia. METHODS: Twenty patients with childhood-onset dystonia were retrospectively recruited including twelve patients with inherited or idiopathic, and eight patients with acquired dystonia (mean age 10 years; 8 female/12 male). Fiber density between the internal part of the globus pallidus and selective target regions, as well as the diffusion measures of fractional anisotropy (FA) and mean diffusivity (MD) were analyzed and compared between different etiologies. RESULTS: Patients with acquired dystonia presented higher fiber density to the premotor cortex and putamen and lower FA values in the thalamus compared to patients with inherited/idiopathic dystonia. MD in the premotor cortex was higher in patients with acquired dystonia, while it was lower in the thalamus. CONCLUSION: Diffusion MRI reveals microstructural and network alterations in patients with dystonia of different etiologies.

One side effect: two networks? Lateral and posteromedial stimulation spreads induce dysarthria in subthalamic deep brain stimulation for Parkinson's disease.

BACKGROUND: Stimulation-induced dysarthria (SID) is a troublesome and potentially therapy-limiting side effect of deep brain stimulation of the subthalamic nucleus (STN-DBS) in patients with Parkinson's disease (PD). To date, the origin of SID, and especially whether there is an involvement of cerebellar pathways as well as the pyramidal tract, remains a matter of debate. Therefore, this study aims to shed light on structural networks associated with SID and to derive a data-driven model to predict SID in patients with PD and STN-DBS. METHODS: Randomised, double-blinded monopolar reviews determining SID thresholds were conducted in 25 patients with PD and STN-DBS. A fibre-based mapping approach, implementing the calculation of fibr-wise ORs for SID, was employed to identify the distributional pattern of SID in the STN's vicinity. The ability of the data-driven model to classify stimulation volumes as 'causing SID' or 'not causing SID' was validated by calculating receiver operating characteristics (ROC) in an independent out-of-sample cohort comprising 14 patients with PD and STN-DBS. RESULTS: Local fibre-based stimulation maps showed an involvement of fibres running lateral and posteromedial to the STN in the pathogenesis of SID, independent of the investigated hemisphere. ROC analysis in the independent out-of-sample cohort resulted in a good fit of the data-driven model for both hemispheres (area under the curve (AUC)left=0.88, AUCright=0.88). CONCLUSIONS: This study reveals an involvement of both, cerebello-thalamic fibres, as well as the pyramidal tract, in the pathogenesis of SID in STN-DBS. The results may impact future postoperative programming strategies to avoid SID in patients with PD and STN-DBS TRIAL REGISTRATION NUMBER: DRKS00023221; German Clinical Trials Register (DRKS) Number.

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.

Lead-DBS v3.0: Mapping deep brain stimulation effects to local anatomy and global networks.

Following its introduction in 2014 and with support of a broad international community, the open-source toolbox Lead-DBS has evolved into a comprehensive neuroimaging platform dedicated to localizing, reconstructing, and visualizing electrodes implanted in the human brain, in the context of deep brain stimulation (DBS) and epilepsy monitoring. Expanding clinical indications for DBS, increasing availability of related research tools, and a growing community of clinician-scientist researchers, however, have led to an ongoing need to maintain, update, and standardize the codebase of Lead-DBS. Major development efforts of the platform in recent years have now yielded an end-to-end solution for DBS-based neuroimaging analysis allowing comprehensive image preprocessing, lead localization, stimulation volume modeling, and statistical analysis within a single tool. The aim of the present manuscript is to introduce fundamental additions to the Lead-DBS pipeline including a deformation warpfield editor and novel algorithms for electrode localization. Furthermore, we introduce a total of three comprehensive tools to map DBS effects to local, tract- and brain network-levels. These updates are demonstrated using a single patient example (for subject-level analysis), as well as a retrospective cohort of 51 Parkinson's disease patients who underwent DBS of the subthalamic nucleus (for group-level analysis). Their applicability is further demonstrated by comparing the various methodological choices and the amount of explained variance in clinical outcomes across analysis streams. Finally, based on an increasing need to standardize folder and file naming specifications across research groups in neuroscience, we introduce the brain imaging data structure (BIDS) derivative standard for Lead-DBS. Thus, this multi-institutional collaborative effort represents an important stage in the evolution of a comprehensive, open-source pipeline for DBS imaging and connectomics.

Probabilistic Mapping Reveals Optimal Stimulation Site in Essential Tremor.

OBJECTIVE: The objective of this study was to obtain individual clinical and neuroimaging data of patients undergoing deep brain stimulation (DBS) for essential tremor (ET) from 5 different European centers to identify predictors of outcome and to identify an optimal stimulation site. METHODS: We analyzed retrospectively baseline covariates, pre- and postoperative clinical tremor scores (for 12 months) as well as individual imaging data from 119 patients to obtain individual electrode positions and stimulation volumes. Individual imaging and clinical data were used to calculate a probabilistic stimulation map in normalized space using voxel-wise statistical analysis. Finally, we used this map to train a classifier to predict tremor improvement. RESULTS: Probabilistic mapping of stimulation effects yielded a statistically significant cluster that was associated with a tremor improvement >50%. This cluster of optimal stimulation extended from the posterior subthalamic area to the ventralis intermedius nucleus and coincided with a normative structural connectivity-based cerebellothalamic tract (CTT). The combined features "distance between the stimulation volume and the significant cluster" and "CTT activation" were used as a predictor of tremor improvement. This correctly classified a >50% tremor improvement with a sensitivity of 89% and a specificity of 57%. INTERPRETATION: Our multicenter ET probabilistic stimulation map identified an area of optimal stimulation along the course of the CTT. The results of this study are mainly descriptive until confirmed in independent datasets, ideally through prospective testing. This target will be made openly available and may be used to guide surgical planning and for computer-assisted programming of DBS in the future. ANN NEUROL 2022;91:602-612.

Accelerometric Classification of Resting and Postural Tremor Amplitude.

Clinical rating scales for tremors have significant limitations due to low resolution, high rater dependency, and lack of applicability in outpatient settings. Reliable, quantitative approaches for assessing tremor severity are warranted, especially evaluating treatment effects, e.g., of deep brain stimulation (DBS). We aimed to investigate how different accelerometry metrics can objectively classify tremor amplitude of Essential Tremor (ET) and tremor in Parkinson's Disease (PD). We assessed 860 resting and postural tremor trials in 16 patients with ET and 25 patients with PD under different DBS settings. Clinical ratings were compared to different metrics, based on either spectral components in the tremorband or pure acceleration, derived from simultaneous triaxial accelerometry captured at the index finger and wrist. Nonlinear regression was applied to a training dataset to determine the relationship between accelerometry and clinical ratings, which was then evaluated in a holdout dataset. All of the investigated accelerometry metrics could predict clinical tremor ratings with a high concordance (>70%) and substantial interrater reliability (Cohen's weighted Kappa > 0.7) in out-of-sample data. Finger-worn accelerometry performed slightly better than wrist-worn accelerometry. We conclude that triaxial accelerometry reliably quantifies resting and postural tremor amplitude in ET and PD patients. A full release of our dataset and software allows for implementation, development, training, and validation of novel methods.

Brain Morphometry Associated With Response to Levodopa and Deep Brain Stimulation in Parkinson Disease.

OBJECTIVES: Whether treatment response in patients with Parkinson disease depends on brain atrophy is insufficiently understood. The goal of this study is to identify specific atrophy patterns associated with response to dopaminergic therapy and deep brain stimulation. MATERIALS AND METHODS: In this study, we analyzed the association of gray matter brain atrophy patterns, as identified by voxel-based morphometry, with acute response to levodopa (N = 118) and subthalamic nucleus deep brain stimulation (N = 39). Motor status was measured as a change in points on the Unified Parkinson's Disease Rating Scale III score. Baseline values were obtained before surgery, after cessation of dopaminergic medication for at least 12 hours; response to medication was assessed after administration of a standardized dose of levodopa. Response to deep brain stimulation was measured three months after surgery in the clinical condition after withdrawal of dopaminergic medication. RESULTS: Although frontoparietal brain gray matter loss was associated with subpar response to deep brain stimulation, there was no significant link between brain atrophy and response to levodopa. CONCLUSION: We conclude that response to deep brain stimulation relies on gray matter integrity; hence, gray matter loss may present a risk factor for poor response to deep brain stimulation and may be considered when making decision regarding clinical practice.

Network Fingerprint of Stimulation-Induced Speech Impairment in Essential Tremor.

OBJECTIVE: This study was undertaken to gain insights into structural networks associated with stimulation-induced dysarthria (SID) and to predict stimulation-induced worsening of intelligibility in essential tremor patients with bilateral thalamic deep brain stimulation (DBS). METHODS: Monopolar reviews were conducted in 14 essential tremor patients. Testing included determination of SID thresholds, intelligibility ratings, and a fast syllable repetition task. Volumes of tissue activated (VTAs) were calculated to identify discriminative fibers for stimulation-induced worsening of intelligibility in a structural connectome. The resulting fiber-based atlas structure was then validated in a leave-one-out design. RESULTS: Fibers determined as discriminative for stimulation-induced worsening of intelligibility were mainly connected to the ipsilateral precentral gyrus as well as to both cerebellar hemispheres and the ipsilateral brain stem. In the thalamic area, they ran laterally to the thalamus and posteromedially to the subthalamic nucleus, in close proximity, mainly anterolaterally, to fibers beneficial for tremor control as published by Al-Fatly et al in 2019. The overlap of the respective clinical stimulation setting's VTAs with these fibers explained 62.4% (p < 0.001) of the variance of stimulation-induced change in intelligibility in a leave-one-out analysis. INTERPRETATION: This study demonstrates that SID in essential tremor patients is associated with both motor cortex and cerebellar connectivity. Furthermore, the identified fiber-based atlas structure might contribute to future postoperative programming strategies to achieve optimal tremor control without speech impairment in essential tremor patients with thalamic DBS. ANN NEUROL 2021;89:315-326.

StimFit-A Data-Driven Algorithm for Automated Deep Brain Stimulation Programming.

BACKGROUND: Finding the optimal deep brain stimulation (DBS) parameters from a multitude of possible combinations by trial and error is time consuming and requires highly trained medical personnel. OBJECTIVE: We developed an automated algorithm to identify optimal stimulation settings in Parkinson's disease (PD) patients treated with subthalamic nucleus (STN) DBS based on imaging-derived metrics. METHODS: Electrode locations and monopolar review data of 612 stimulation settings acquired from 31 PD patients were used to train a predictive model for therapeutic and adverse stimulation effects. Model performance was then evaluated within the training cohort using cross-validation and on an independent cohort of 19 patients. We inverted the model by applying a brute-force approach to determine the optimal stimulation sites in the target region. Finally, an optimization algorithm was established to identify optimal stimulation parameters. Suggested stimulation parameters were compared to the ones applied in clinical practice. RESULTS: Predicted motor outcome correlated with observed outcome (R = 0.57, P < 10-10 ) across patients within the training cohort. In the test cohort, the model explained 28% of the variance in motor outcome differences between settings. The stimulation site for maximum motor improvement was located at the dorsolateral border of the STN. When compared to two empirical settings, model-based suggestions more closely matched the setting with superior motor improvement. CONCLUSION: We developed and validated a data-driven model that can suggest stimulation parameters leading to optimal motor improvement while minimizing the risk of stimulation-induced side effects. This approach might provide guidance for DBS programming in the future. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

The Contribution of Subthalamic Nucleus Deep Brain Stimulation to the Improvement in Motor Functions and Quality of Life.

BACKGROUND: Subthalamic nucleus deep brain stimulation (STN-DBS) effectively treats motor symptoms and quality of life (QoL) of advanced and fluctuating early Parkinson's disease. Little is known about the relation between electrode position and changes in symptom control and ultimately QoL. OBJECTIVES: The relation between the stimulated part of the STN and clinical outcomes, including the motor score of the Unified Parkinson's Disease Rating Scale (UPDRS) and the quality-of-life questionnaire, was assessed in a subcohort of the EARLYSTIM study. METHODS: Sixty-nine patients from the EARLYSTIM cohort who underwent DBS, with a comprehensive clinical characterization before and 24 months after surgery, were included. Intercorrelations of clinical outcome changes, correlation between the affected functional parts of the STN, and changes in clinical outcomes were investigated. We further calculated sweet spots for different clinical parameters. RESULTS: Improvements in the UPDRS III and Parkinson's Disease Questionnaire (PDQ-39) correlated positively with the extent of the overlap with the sensorimotor STN. The sweet spots for the UPDRS III (x = 11.6, y = -13.1, z = -6.3) and the PDQ-39 differed (x = 14.8, y = -12.4, z = -4.3) ~3.8 mm. CONCLUSIONS: The main influence of DBS on QoL is likely mediated through the sensory-motor basal ganglia loop. The PDQ sweet spot is located in a posteroventral spatial location in the STN territory. For aspects of QoL, however, there was also evidence of improvement through stimulation of the other STN subnuclei. More research is necessary to customize the DBS target to individual symptoms of each patient. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Quality of Life After Deep Brain Stimulation of Pediatric Patients with Dyskinetic Cerebral Palsy: A Prospective, Single-Arm, Multicenter Study with a Subsequent Randomized Double-Blind Crossover (STIM-CP).

BACKGROUND: Patients with dyskinetic cerebral palsy are often severely impaired with limited treatment options. The effects of deep brain stimulation (DBS) are less pronounced than those in inherited dystonia but can be associated with favorable quality of life outcomes even in patients without changes in dystonia severity. OBJECTIVE: The aim is to assess DBS effects in pediatric patients with pharmacorefractory dyskinetic cerebral palsy with focus on quality of life. METHODS: The method used is a prospective, single-arm, multicenter study. The primary endpoint is improvement in quality of life (CPCHILD [Caregiver Priorities & Child Health Index of Life with Disabilities]) from baseline to 12 months under therapeutic stimulation. The main key secondary outcomes are changes in Burke-Fahn-Marsden Dystonia Rating Scale, Dyskinesia Impairment Scale, Gross Motor Function Measure-66, Canadian Occupational Performance Measure (COPM), and Short-Form (SF)-36. After 12 months, patients were randomly assigned to a blinded crossover to receive active or sham stimulation for 24 hours each. Severity of dystonia and chorea were blindly rated. Safety was assessed throughout. The trial was registered at ClinicalTrials.gov, number NCT02097693. RESULTS: Sixteen patients (age: 13.4 ± 2.9 years) were recruited by seven clinical sites. Primary outcome at 12-month follow-up is as follows: mean CPCHILD increased by 4.2 ± 10.4 points (95% CI [confidence interval] -1.3 to 9.7; P = 0.125); among secondary outcomes: improvement in COPM performance measure of 1.1 ± 1.5 points (95% CI 0.2 to 1.9; P = 0.02) and in the SF-36 physical health component by 5.1 ± 6.2 points (95% CI 0.7 to 9.6; P = 0.028). Otherwise, there are no significant changes. CONCLUSION: Evidence to recommend DBS as routine treatment to improve quality of life in pediatric patients with dyskinetic cerebral palsy is not yet sufficient. Extended follow-up in larger cohorts will determine the impact of DBS further to guide treatment decisions in these often severely disabled patients. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Sweetspot Mapping in Deep Brain Stimulation: Strengths and Limitations of Current Approaches.

OBJECTIVES: Open questions remain regarding the optimal target, or sweetspot, for deep brain stimulation (DBS) in, for example, Parkinson's disease. Previous studies introduced different methods of mapping DBS effects to determine sweetspots. While having a direct impact on surgical targeting and postoperative programming in DBS, these methods so far have not been compared. MATERIALS AND METHODS: This study investigated five previously published DBS mapping approaches regarding their potential to correctly identify a predefined target. Methods were investigated in silico in eight different use-case scenarios, which incorporated different types of clinical data, noise, and differences in underlying neuroanatomy. Dice coefficients were calculated to determine the overlap between identified sweetspots and the predefined target. Additionally, out-of-sample predictive capabilities were assessed using the amount of explained variance R2. RESULTS: The five investigated methods resulted in highly variable sweetspots. Methods based on voxel-wise statistics against average outcomes showed the best performance overall. While predictive capabilities were high, even in the best of cases Dice coefficients remained limited to values around 0.5, highlighting the overall limitations of sweetspot identification. CONCLUSIONS: This study highlights the strengths and limitations of current approaches to DBS sweetspot mapping. Those limitations need to be taken into account when considering the clinical implications. All future approaches should be investigated in silico before being applied to clinical data.

Deep Brain Stimulation Reduces Conflict-Related Theta and Error-Related Negativity in Patients With Obsessive-Compulsive Disorder.

OBJECTIVES: Obsessive-compulsive disorder (OCD) is a psychiatric disorder with alterations of cortico-striato-thalamo-cortical loops and impaired performance monitoring. Electrophysiological markers such as conflict-related medial frontal theta (MFT) and error-related negativity (ERN) may be altered by clinically effective deep brain stimulation (DBS) of the anterior limb of the internal capsule and nucleus accumbens (ALIC/NAc). We hypothesized that ALIC/NAc DBS modulates electrophysiological performance monitoring markers. MATERIALS AND METHODS: Fifteen patients (six male) with otherwise treatment-refractory OCD receiving ALIC/NAc DBS performed a flanker task with EEG recordings at three sessions: presurgery and at follow-up with DBS on and off. We examined MFT, ERN, and task performance. Furthermore, we investigated interrelations with clinical efficacy and then explored the influence of the location of individual stimulation volumes on EEG modulations. RESULTS: MFT and ERN were significantly attenuated by DBS with differences most pronounced between presurgery and DBS-on states. Also, we observed reaction time slowing for erroneous responses during DBS-off. Larger presurgery ERN amplitudes were associated with decreased clinical efficacy. Exploratory anatomical analyses suggested that stimulation volumes encompassing the NAc were associated with MFT modulation, whereas ALIC stimulation was associated with modulation of the ERN and clinical efficacy. CONCLUSION: ALIC/NAc DBS diminished MFT and ERN, demonstrating modulation of the medial frontal performance monitoring system in OCD. Furthermore, our findings encourage further studies to explore the ERN as a potential predictor for clinical efficacy.

Temporal Stability of Lead Orientation in Directional Deep Brain Stimulation.

BACKGROUND: Directional deep brain stimulation (DBS) enlarges the therapeutic window by increasing side-effect thresholds and improving clinical benefits. To determine the optimal stimulation settings and interpret clinical observations, knowledge of the lead orientation in relation to the patient's anatomy is required. OBJECTIVE: To determine if directional leads remain in a fixed orientation after implantation or whether orientation changes over time. METHOD: Clinical records of 187 patients with directional DBS electrodes were screened for CT scans in addition to the routine postoperative CT. The orientation angle of each electrode at a specific point in time was reconstructed from CT artifacts using the DiODe algorithm implemented in Lead-DBS. The orientation angles over time were compared with the originally measured orientations from the routine postoperative CT. RESULTS: Multiple CT scans were identified in 18 patients and the constancy of the orientation angle was determined for 29 leads at 48 points in time. The median time difference between the observations and the routine postoperative CT scan was 82 (range 1-811) days. The mean difference of the orientation angles compared to the initial measurement was -1.1 ± 3.9° (range -7.6 to 8.7°). Linear regression showed no relevant drift of the absolute value of the orientation angle over time (0.8°/year, adjusted R2: 0.040, p = 0.093). CONCLUSION: The orientation of directional leads was stable and showed no clinically relevant changes either in the first weeks after implantation or over longer periods of time.

Potentials and Limitations of Directional Deep Brain Stimulation: A Simulation Approach.

BACKGROUND: Directional leads are increasingly used in deep brain stimulation. They allow shaping the electrical field in the axial plane. These new possibilities increase the complexity of programming. Thus, optimized programming approaches are needed to assist clinical testing and to obtain full clinical benefit. OBJECTIVES: This simulation study investigates to what extent the electrical field can be shaped by directional steering to compensate for lead malposition. METHOD: Binary volumes of tissue activated (VTA) were simulated, by using a finite element method approach, for different amplitude distributions on the three directional electrodes. VTAs were shifted from 0 to 2 mm at different shift angles with respect to the lead orientation, to determine the best compensation of a target volume. RESULTS: Malpositions of 1 mm can be compensated with the highest gain of overlap with directional leads. For larger shifts, an improvement of overlap of 10-30% is possible, depending on the stimulation amplitude and shift angle of the lead. Lead orientation and shift determine the amplitude distribution of the electrodes. CONCLUSION: To get full benefit from directional leads, both the shift angle as well as the shift to target volume are required to choose the correct amplitude distribution on the electrodes. Current directional leads have limitations when compensating malpositions >1 mm; however, they still outperform conventional leads in reducing overstimulation. Further, their main advantage probably lies in the reduction of side effects. Databases like the one from this simulation could serve for optimized lead programming algorithms in the future.

Probabilistic sweet spots predict motor outcome for deep brain stimulation in Parkinson disease.

OBJECTIVE: To investigate whether functional sweet spots of deep brain stimulation (DBS) in the subthalamic nucleus (STN) can predict motor improvement in Parkinson disease (PD) patients. METHODS: Stimulation effects of 449 DBS settings in 21 PD patients were clinically and quantitatively assessed through standardized monopolar reviews and mapped into standard space. A sweet spot for best motor outcome was determined using voxelwise and nonparametric permutation statistics. Two independent cohorts were used to investigate whether stimulation overlap with the sweet spot could predict acute motor outcome (10 patients, 163 settings) and long-term overall Unified Parkinson's Disease Rating Scale Part III (UPDRS-III) improvement (63 patients). RESULTS: Significant clusters for suppression of rigidity and akinesia, as well as for overall motor improvement, resided around the dorsolateral border of the STN. Overlap of the volume of tissue activated with the sweet spot for overall motor improvement explained R2 = 37% of the variance in acute motor improvement, more than triple what was explained by overlap with the STN (R2 = 9%) and its sensorimotor subpart (R2 = 10%). In the second independent cohort, sweet spot overlap explained R2 = 20% of the variance in long-term UPDRS-III improvement, which was equivalent to the variance explained by overlap with the STN (R2 = 21%) and sensorimotor STN (R2 = 19%). INTERPRETATION: This study is the first to predict clinical improvement of parkinsonian motor symptoms across cohorts based on local DBS effects only. The new approach revealed a distinct sweet spot for STN DBS in PD. Stimulation overlap with the sweet spot can predict short- and long-term motor outcome and may be used to guide DBS programming. ANN NEUROL 2019;86:527-538.

Deep Brain Stimulation for Freezing of Gait in Parkinson's Disease With Early Motor Complications.

BACKGROUND: Effects of DBS on freezing of gait and other axial signs in PD patients are unclear. OBJECTIVE: Secondary analysis to assess whether DBS affects these symptoms within a large randomized controlled trial comparing DBS of the STN combined with best medical treatment and best medical treatment alone in patients with early motor complications (EARLYSTIM-trial). METHODS: One hundred twenty-four patients were randomized in the stimulation group and 127 patients in the best medical treatment group. Presence of freezing of gait was assessed in the worst condition based on item-14 of the UPDRS-II at baseline and follow-up. The posture, instability, and gait-difficulty subscore of the UPDRS-III, and a gait test including quantification of freezing of gait and number of steps, were performed in both medication-off and medication-on conditions. RESULTS: Fifty-two percent in both groups had freezing of gait at baseline based on UPDRS-II. This proportion decreased in the stimulation group to 34%, but did not change in the best medical treatment group at 24 months (P = 0.018). The steps needed to complete the gait test decreased in the stimulation group and was superior to the best medical treatment group (P = 0.016). The axial signs improved in the stimulation group compared to the best medical treatment group (P < 0.01) in both medication-off and medication-on conditions. CONCLUSIONS: Within the first 2 years of DBS, freezing of gait and other axial signs improved in the medication-off condition compared to best medical treatment in these patients. © 2019 International Parkinson and Movement Disorder Society.

Non-motor outcomes depend on location of neurostimulation in Parkinson's disease.

Deep brain stimulation of the subthalamic nucleus is an effective and established therapy for patients with advanced Parkinson's disease improving quality of life, motor symptoms and non-motor symptoms. However, there is a considerable degree of interindividual variability for these outcomes, likely due to variability in electrode placement and stimulation settings. Here, we present probabilistic mapping data from a prospective, open-label, multicentre, international study to investigate the influence of the location of subthalamic nucleus deep brain stimulation on non-motor symptoms in patients with Parkinson's disease. A total of 91 Parkinson's disease patients undergoing bilateral deep brain stimulation of the subthalamic nucleus were included, and we investigated NMSScale, NMSQuestionnaire, Scales for Outcomes in Parkinson's disease-motor examination, -activities of daily living, and -motor complications, and Parkinson's disease Questionnaire-8 preoperatively and at 6-month follow-up after surgery. Leads were localized in standard space using the Lead-DBS toolbox and individual volumes of tissue activated were calculated based on clinical stimulation settings. Probabilistic stimulation maps and non-parametric permutation statistics were applied to identify voxels with significant above or below average improvement for each scale and analysed using the DISTAL atlas. All outcomes improved significantly at follow-up. Significant spatial distribution patterns of neurostimulation were observed for NMSScale total score and its mood/apathy and attention/memory domains. For both domains, voxels associated with below average improvement were mainly located dorsal to the subthalamic nucleus. In contrast, above average improvement for mood/apathy was observed in the ventral border region of the subthalamic nucleus and in its sensorimotor subregion and for attention/memory in the associative subregion. A trend was observed for NMSScale sleep domain showing voxels with above average improvement located ventral to the subthalamic nucleus. Our study provides evidence that the interindividual variability of mood/apathy, attention/memory, and sleep outcomes after subthalamic nucleus deep brain stimulation depends on the location of neurostimulation. This study highlights the importance of holistic assessments of motor and non-motor aspects of Parkinson's disease to tailor surgical targeting and stimulation parameter settings to patients' personal profiles.

Reliable Detection of Atrial Fibrillation with a Medical Wearable during Inpatient Conditions.

Atrial fibrillation (AF) is the most common arrhythmia and has a major impact on morbidity and mortality; however, detection of asymptomatic AF is challenging. This study sims to evaluate the sensitivity and specificity of non-invasive AF detection by a medical wearable. In this observational trial, patients with AF admitted to a hospital carried the wearable and an ECG Holter (control) in parallel over a period of 24 h, while not in a physically restricted condition. The wearable with a tight-fit upper armband employs a photoplethysmography technology to determine pulse rates and inter-beat intervals. Different algorithms (including a deep neural network) were applied to five-minute periods photoplethysmography datasets for the detection of AF. A total of 2306 h of parallel recording time could be obtained in 102 patients; 1781 h (77.2%) were automatically interpretable by an algorithm. Sensitivity to detect AF was 95.2% and specificity 92.5% (area under the receiver operating characteristics curve (AUC) 0.97). Usage of deep neural network improved the sensitivity of AF detection by 0.8% (96.0%) and specificity by 6.5% (99.0%) (AUC 0.98). Detection of AF by means of a wearable is feasible in hospitalized but physically active patients. Employing a deep neural network enables reliable and continuous monitoring of AF.