Modulation of subthalamic beta oscillations by movement, dopamine, and deep brain stimulation in Parkinson's disease.

Subthalamic beta band activity (13-35 Hz) is known as a real-time correlate of motor symptom severity in Parkinson's disease (PD) and is currently explored as a feedback signal for closed-loop deep brain stimulation (DBS). Here, we investigate the interaction of movement, dopaminergic medication, and deep brain stimulation on subthalamic beta activity in PD patients implanted with sensing-enabled, implantable pulse generators. We recorded subthalamic activity from seven PD patients at rest and during repetitive movements in four conditions: after withdrawal of dopaminergic medication and DBS, with medication only, with DBS only, and with simultaneous medication and DBS. Medication and DBS showed additive effects in improving motor performance. Distinct effects of each therapy were seen in subthalamic recordings, with medication primarily suppressing low beta activity (13-20 Hz) and DBS being associated with a broad decrease in beta band activity (13-35 Hz). Movement suppressed beta band activity compared to rest. This suppression was most prominent when combining medication with DBS and correlated with motor improvement within patients. We conclude that DBS and medication have distinct effects on subthalamic beta activity during both rest and movement, which might explain their additive clinical effects as well as their difference in side-effect profiles. Importantly, subthalamic beta activity significantly correlated with motor symptoms across all conditions, highlighting its validity as a feedback signal for closed-loop DBS.

Kinematic Effects of Combined Subthalamic and Dorsolateral Nigral Deep Brain Stimulation in Parkinson's Disease.

Background: Additional stimulation of the substantia nigra (SNr) has been proposed to target axial symptoms and gait impairment in patients with Parkinson's disease (PD). Objective: This study aimed to characterize effects of combined deep brain stimulation (DBS) of the subthalamic nucleus (STN) and SNr on gait performance in PD and to map stimulation sites within the SNr. Methods: In a double-blinded crossover design, 10 patients with PD and gait impairment underwent clinical examination and kinematic assessment with STN DBS, combined STN+SNr DBS and OFF DBS 30 minutes after reprogramming. To confirm stimulation within the SNr, electrodes, active contacts, and stimulation volumes were modeled in a common space and overlap with atlases of SNr was computed. Results: Overlap of stimulation volumes with dorsolateral SNr was confirmed for all patients. UPDRS III, scoring of freezing during turning and transitioning, stride length, stride velocity, and range of motion of shank, knee, arm, and trunk as well as peak velocities during turning and transitions and turn duration were improved with STN DBS compared to OFF. On cohort level, no further improvement was observed with combined STN+SNr DBS but additive improvement of spatiotemporal gait parameters was observed in individual subjects. Conclusions: Combined high frequency DBS of the STN and dorsolateral SNr did not consistently result in additional short-term kinematic or clinical benefit compared to STN DBS. Stimulation intervals, frequency, and patient selection for target symptoms as well as target region within the SNr need further refinement in future trials.

Single threshold adaptive deep brain stimulation in Parkinson's disease depends on parameter selection, movement state and controllability of subthalamic beta activity.

BACKGROUND: Deep brain stimulation (DBS) is an invasive treatment option for patients with Parkinson's disease. Recently, adaptive DBS (aDBS) systems have been developed, which adjust stimulation timing and amplitude in real-time. However, it is unknown how changes in parameters, movement states and the controllability of subthalamic beta activity affect aDBS performance. OBJECTIVE: To characterize how parameter choice, movement state and controllability interactively affect the electrophysiological and behavioral response to single threshold aDBS. METHODS: We recorded subthalamic local field potentials in 12 patients with Parkinson's disease receiving single threshold aDBS in the acute post-operative state. We investigated changes in two aDBS parameters: the onset time and the smoothing of real-time beta power. Electrophysiological patterns and motor performance were assessed while patients were at rest and during a simple motor task. We further studied the impact of controllability on aDBS performance by comparing patients with and without beta power modulation during continuous stimulation. RESULTS: Our findings reveal that changes in the onset time control the extent of beta power suppression achievable with single threshold adaptive stimulation during rest. Behavioral data indicate that only specific parameter combinations yield a beneficial effect of single threshold aDBS. During movement, action induced beta power suppression reduces the responsivity of the closed loop algorithm. We further demonstrate that controllability of beta power is a prerequisite for effective parameter dependent modulation of subthalamic beta activity. CONCLUSION: Our results highlight the interaction between single threshold aDBS parameter selection, movement state and controllability in driving subthalamic beta activity and motor performance. By this means, we identify directions for the further development of closed-loop DBS algorithms.

Automated quantification of vacuole fusion and lipophagy in Saccharomyces cerevisiae from fluorescence and cryo-soft X-ray microscopy data using deep learning.

During starvation in the yeast Saccharomyces cerevisiae vacuolar vesicles fuse and lipid droplets (LDs) can become internalized into the vacuole in an autophagic process named lipophagy. There is a lack of tools to quantitatively assess starvation-induced vacuole fusion and lipophagy in intact cells with high resolution and throughput. Here, we combine soft X-ray tomography (SXT) with fluorescence microscopy and use a deep-learning computational approach to visualize and quantify these processes in yeast. We focus on yeast homologs of mammalian NPC1 (NPC intracellular cholesterol transporter 1; Ncr1 in yeast) and NPC2 proteins, whose dysfunction leads to Niemann Pick type C (NPC) disease in humans. We developed a convolutional neural network (CNN) model which classifies fully fused versus partially fused vacuoles based on fluorescence images of stained cells. This CNN, named Deep Yeast Fusion Network (DYFNet), revealed that cells lacking Ncr1 (ncr1∆ cells) or Npc2 (npc2∆ cells) have a reduced capacity for vacuole fusion. Using a second CNN model, we implemented a pipeline named LipoSeg to perform automated instance segmentation of LDs and vacuoles from high-resolution reconstructions of X-ray tomograms. From that, we obtained 3D renderings of LDs inside and outside of the vacuole in a fully automated manner and additionally measured droplet volume, number, and distribution. We find that ncr1∆ and npc2∆ cells could ingest LDs into vacuoles normally but showed compromised degradation of LDs and accumulation of lipid vesicles inside vacuoles. Our new method is versatile and allows for analysis of vacuole fusion, droplet size and lipophagy in intact cells.Abbreviations: BODIPY493/503: 4,4-difluoro-1,3,5,7,8-pentamethyl-4-bora-3a,4a-diaza-s-Indacene; BPS: bathophenanthrolinedisulfonic acid disodium salt hydrate; CNN: convolutional neural network; DHE; dehydroergosterol; npc2∆, yeast deficient in Npc2; DSC, Dice similarity coefficient; EM, electron microscopy; EVs, extracellular vesicles; FIB-SEM, focused ion beam milling-scanning electron microscopy; FM 4-64, N-(3-triethylammoniumpropyl)-4-(6-[4-{diethylamino} phenyl] hexatrienyl)-pyridinium dibromide; LDs, lipid droplets; Ncr1, yeast homolog of human NPC1 protein; ncr1∆, yeast deficient in Ncr1; NPC, Niemann Pick type C; NPC2, Niemann Pick type C homolog; OD600, optical density at 600 nm; ReLU, rectifier linear unit; PPV, positive predictive value; NPV, negative predictive value; MCC, Matthews correlation coefficient; SXT, soft X-ray tomography; UV, ultraviolet; YPD, yeast extract peptone dextrose.

Kinetic modelling of sterol transport between plasma membrane and endo-lysosomes based on quantitative fluorescence and X-ray imaging data.

Niemann Pick type C1 and C2 (NPC1 and NPC2) are two sterol-binding proteins which, together, orchestrate cholesterol transport through late endosomes and lysosomes (LE/LYSs). NPC2 can facilitate sterol exchange between model membranes severalfold, but how this is connected to its function in cells is poorly understood. Using fluorescent analogs of cholesterol and quantitative fluorescence microscopy, we have recently measured the transport kinetics of sterol between plasma membrane (PM), recycling endosomes (REs) and LE/LYSs in control and NPC2 deficient fibroblasts. Here, we use kinetic modeling of this data to determine rate constants for sterol transport between intracellular compartments. Our model predicts that sterol is trapped in intraluminal vesicles (ILVs) of LE/LYSs in the absence of NPC2, causing delayed sterol export from LE/LYSs in NPC2 deficient fibroblasts. Using soft X-ray tomography, we confirm, that LE/LYSs of NPC2 deficient cells but not of control cells contain enlarged, carbon-rich intraluminal vesicular structures, supporting our model prediction of lipid accumulation in ILVs. By including sterol export via exocytosis of ILVs as exosomes and by release of vesicles-ectosomes-from the PM, we can reconcile measured sterol efflux kinetics and show that both pathways can be reciprocally regulated by the intraluminal sterol transfer activity of NPC2 inside LE/LYSs. Our results thereby connect the in vitro function of NPC2 as sterol transfer protein between membranes with its in vivo function.

Local Field Potentials Predict Motor Performance in Deep Brain Stimulation for Parkinson's Disease.

BACKGROUND: Deep brain stimulation (DBS) is an effective treatment option for patients with Parkinson's disease (PD). However, clinical programming remains challenging with segmented electrodes. OBJECTIVE: Using novel sensing-enabled neurostimulators, we investigated local field potentials (LFPs) and their modulation by DBS to assess whether electrophysiological biomarkers may facilitate clinical programming in chronically implanted patients. METHODS: Sixteen patients (31 hemispheres) with PD implanted with segmented electrodes in the subthalamic nucleus and a sensing-enabled neurostimulator were included in this study. Recordings were conducted 3 months after DBS surgery following overnight withdrawal of dopaminergic medication. LFPs were acquired while stimulation was turned OFF and during a monopolar review of both directional and ring contacts. Directional beta power and stimulation-induced beta power suppression were computed. Motor performance, as assessed by a pronation-supination task, clinical programming and electrode placement were correlated to directional beta power and stimulation-induced beta power suppression. RESULTS: Better motor performance was associated with stronger beta power suppression at higher stimulation amplitudes. Across directional contacts, differences in directional beta power and the extent of stimulation-induced beta power suppression predicted motor performance. However, within individual hemispheres, beta power suppression was superior to directional beta power in selecting the contact with the best motor performance. Contacts clinically activated for chronic stimulation were associated with stronger beta power suppression than non-activated contacts. CONCLUSIONS: Our results suggest that stimulation-induced ß power suppression is superior to directional ß power in selecting the clinically most effective contact. In sum, electrophysiological biomarkers may guide programming of directional DBS systems in PD patients. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Invasive neurophysiology and whole brain connectomics for neural decoding in patients with brain implants.

Brain computer interfaces (BCI) provide unprecedented spatiotemporal precision that will enable significant expansion in how numerous brain disorders are treated. Decoding dynamic patient states from brain signals with machine learning is required to leverage this precision, but a standardized framework for identifying and advancing novel clinical BCI approaches does not exist. Here, we developed a platform that integrates brain signal decoding with connectomics and demonstrate its utility across 123 hours of invasively recorded brain data from 73 neurosurgical patients treated for movement disorders, depression and epilepsy. First, we introduce connectomics-informed movement decoders that generalize across cohorts with Parkinson's disease and epilepsy from the US, Europe and China. Next, we reveal network targets for emotion decoding in left prefrontal and cingulate circuits in DBS patients with major depression. Finally, we showcase opportunities to improve seizure detection in responsive neurostimulation for epilepsy. Our platform provides rapid, high-accuracy decoding for precision medicine approaches that can dynamically adapt neuromodulation therapies in response to the individual needs of patients.

3D surface reconstruction of cellular cryo-soft X-ray microscopy tomograms using semisupervised deep learning.

Cryo-soft X-ray tomography (cryo-SXT) is a powerful method to investigate the ultrastructure of cells, offering resolution in the tens of nanometer range and strong contrast for membranous structures without requiring labeling or chemical fixation. The short acquisition time and the relatively large field of view leads to fast acquisition of large amounts of tomographic image data. Segmentation of these data into accessible features is a necessary step in gaining biologically relevant information from cryo-soft X-ray tomograms. However, manual image segmentation still requires several orders of magnitude more time than data acquisition. To address this challenge, we have here developed an end-to-end automated 3D segmentation pipeline based on semisupervised deep learning. Our approach is suitable for high-throughput analysis of large amounts of tomographic data, while being robust when faced with limited manual annotations and variations in the tomographic conditions. We validate our approach by extracting three-dimensional information on cellular ultrastructure and by quantifying nanoscopic morphological parameters of filopodia in mammalian cells.

Long-Term Follow-Up of Pediatric Patients with Dyskinetic Cerebral Palsy and Deep Brain Stimulation.

BACKGROUND: Deep brain stimulation (DBS) has been increasingly used in the management of dyskinetic cerebral palsy (DCP). Data on long-term effects and the safety profile are rare. OBJECTIVES: We assessed the efficacy and safety of pallidal DBS in pediatric patients with DCP. METHODS: The STIM-CP trial was a prospective, single-arm, multicenter study in which patients from the parental trial agreed to be followed-up for up to 36 months. Assessments included motor and non-motor domains. RESULTS: Of the 16 patients included initially, 14 (mean inclusion age 14 years) were assessed. There was a significant change in the (blinded) ratings of the total Dyskinesia Impairment Scale at 36 months. Twelve serious adverse events (possibly) related to treatment were documented. CONCLUSION: DBS significantly improved dyskinesia, but other outcome parameters did not change significantly. Investigations of larger homogeneous cohorts are needed to further ascertain the impact of DBS and guide treatment decisions in DCP. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Exploring Stakeholder Requirements to Enable Research and Development of Artificial Intelligence Algorithms in a Hospital-Based Generic Infrastructure: Results of a Multistep Mixed Methods Study.

BACKGROUND: Legal, controlled, and regulated access to high-quality data from academic hospitals currently poses a barrier to the development and testing of new artificial intelligence (AI) algorithms. To overcome this barrier, the German Federal Ministry of Health supports the "pAItient" (Protected Artificial Intelligence Innovation Environment for Patient Oriented Digital Health Solutions for developing, testing and evidence-based evaluation of clinical value) project, with the goal to establish an AI Innovation Environment at the Heidelberg University Hospital, Germany. It is designed as a proof-of-concept extension to the preexisting Medical Data Integration Center. OBJECTIVE: The first part of the pAItient project aims to explore stakeholders' requirements for developing AI in partnership with an academic hospital and granting AI experts access to anonymized personal health data. METHODS: We designed a multistep mixed methods approach. First, researchers and employees from stakeholder organizations were invited to participate in semistructured interviews. In the following step, questionnaires were developed based on the participants' answers and distributed among the stakeholders' organizations. In addition, patients and physicians were interviewed. RESULTS: The identified requirements covered a wide range and were conflicting sometimes. Relevant patient requirements included adequate provision of necessary information for data use, clear medical objective of the research and development activities, trustworthiness of the organization collecting the patient data, and data should not be reidentifiable. Requirements of AI researchers and developers encompassed contact with clinical users, an acceptable user interface (UI) for shared data platforms, stable connection to the planned infrastructure, relevant use cases, and assistance in dealing with data privacy regulations. In a next step, a requirements model was developed, which depicts the identified requirements in different layers. This developed model will be used to communicate stakeholder requirements within the pAItient project consortium. CONCLUSIONS: The study led to the identification of necessary requirements for the development, testing, and validation of AI applications within a hospital-based generic infrastructure. A requirements model was developed, which will inform the next steps in the development of an AI innovation environment at our institution. Results from our study replicate previous findings from other contexts and will add to the emerging discussion on the use of routine medical data for the development of AI applications. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/42208.

Improvement in compliance of ships' ballast water discharges during commissioning tests.

The number of ships installing ballast water management systems (BWMS) has risen steeply since the Ballast Water Management Convention entered into force. Since June 2022, biological testing is required during commissioning to verify compliance with the Convention. Data from 676 tests (from 2019 to 2022) show substantial improvement over time: the failure rate decreased from ~20 % to ~6 %. Notably, nearly all failures occurred in the largest size class of organisms (≥50 µm). Interestingly, proxy measurements suggest that high concentrations of living organisms in uptake water did not cause the failures. Also, failures determined using "indicative" analysis (here, adenosine triphosphate, ATP) were typically not confirmed by "detailed" analysis (microscopy), suggesting that ATP limits are over-precautionary. Finally, discharges containing high levels of Total Residual Oxidants (TRO) decreased over time. These data highlight the need for ongoing testing-focusing at least on organisms ≥50 µm-to minimize environmental risks from organisms transported in ships' ballast water.

Pallidal Beta Activity Is Linked to Stimulation-Induced Slowness in Dystonia.

BACKGROUND: Pallidal deep brain stimulation (DBS) effectively alleviates symptoms in dystonia patients, but may induce movement slowness as a side-effect. In Parkinson's disease, hypokinetic symptoms have been associated with increased beta oscillations (13-30 Hz). We hypothesize that this pattern is symptom-specific, thus accompanying DBS-induced slowness in dystonia. METHODS: In 6 dystonia patients, pallidal rest recordings with a sensing-enabled DBS device were performed and tapping speed was assessed using marker-less pose estimation over 5 time points following cessation of DBS. RESULTS: After cessation of pallidal stimulation, movement speed increased over time (P < 0.01). A linear mixed-effects model revealed that pallidal beta activity explained 77% of the variance in movement speed across patients (P = 0.01). CONCLUSIONS: The association between beta oscillations and slowness across disease entities provides further evidence for symptom-specific oscillatory patterns in the motor circuit. Our findings might help DBS therapy improvements, as DBS-devices able to adapt to beta oscillations are already commercially available. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Gender-specific outcomes of deep brain stimulation for Parkinson's disease - results from a single movement disorder center.

INTRODUCTION AND GOAL: The investigation of gender differences in treatment response is crucial for effective personalized therapies. With only 30%, women are underrepresented in trials for deep brain stimulation (DBS) in Parkinson's disease (PD). It is therefore important to evaluate gender-specific outcomes of DBS in PD in order to improve therapeutic counseling. METHODS: We analyzed clinical outcome parameters of 203 patients with PD that underwent DBS surgery targeting the subthalamic nucleus (STN) at our movement disorder center. A total of 27.6% of patients were female and 72.4% male. Motor and non-motor scores were compared before and 1 year after DBS surgery (1y FU) using Wilcoxon signed-rank tests and gender specific outcomes were analyzed with chi-square tests. RESULTS: At 1y FU, we found significant improvement in UPDRS II, UPDRS III (35.78 ± 36.14% MedOFF vs. StimON-MedOFF), UPDRS IV, depression (BDI-II), and health-related disability as (ADL) that showed no gender-specific differences. No significant change was revealed for UPDRS I, QUIP, and DemTect for the entire cohort. However, when analyzing both groups separately, only women improved in general cognition (plus 1.26 ± 3.03 DemTect points, p = 0.014*), whereas only men ameliorated in depression (minus 1.97 ± 6.92 BDI-II points, p = 0.002**) and impulsivity (minus 2.80 ± 7.27 QUIP points, p = 0.004**). Chi-square tests, however, revealed no significant differences between genders. CONCLUSION AND OUTLOOK: STN-DBS is a highly effective treatment for motor and non-motor symptoms of PD for both women and men but our study hints towards gender-specific outcomes in non-motor-domains like cognition, depressive symptoms, and impulsivity. To explore this in more detail, larger cohorts need to be investigated in multicenter trials.

Subthalamic beta bursts correlate with dopamine-dependent motor symptoms in 106 Parkinson's patients.

Pathologically increased beta power has been described as a biomarker for Parkinson's disease (PD) and related to prolonged bursts of subthalamic beta synchronization. Here, we investigate the association between subthalamic beta dynamics and motor impairment in a cohort of 106 Parkinson's patients in the ON- and OFF-medication state, using two different methods of beta burst determination. We report a frequency-specific correlation of low beta power and burst duration with motor impairment OFF dopaminergic medication. Furthermore, reduction of power and burst duration correlated significantly with symptom alleviation through dopaminergic medication. Importantly, qualitatively similar results were yielded with two different methods of beta burst definition. Our findings validate the robustness of previous results on pathological changes in subcortical oscillations both in the frequency- as well as in the time-domain in the largest cohort of PD patients to date with important implications for next-generation adaptive deep brain stimulation control algorithms.

Christmas-Related Reduction in Beta Activity in Parkinson's Disease.

BACKGROUND: Subthalamic nucleus (STN) beta (13 - 35 Hz) activity is a biomarker reflecting motor state in Parkinson's disease (PD). Adaptive deep brain stimulation (DBS) aims to use beta activity for therapeutic adjustments, but many aspects of beta activity in real-life situations are unknown. OBJECTIVE: The aim was to investigate Christmas-related influences on beta activity in PD. METHODS: Differences in Christmas Day to nonfestive daily averages in chronic biomarker recordings in 4 PD patients with a sensing-enabled STN DBS implant were retrospectively analyzed. Sweet-spot and whole-brain network connectomic analyses were performed. RESULTS: Beta activity was significantly reduced on Christmas Eve in all patients (4.00-9.00 p.m.: -12.30 ± 10.78%, P = 0.015). A sweet spot in the dorsolateral STN connected recording sites to motor, premotor, and supplementary motor cortices. CONCLUSIONS: We demonstrate that festive events can reduce beta biomarker activity. We conclude that circadian and holiday-related changes should be considered when tailoring adaptive DBS algorithms to patient demands. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Thoracolumbar Instrumentation Surgery in Patients with Parkinson's Disease: A Case-Control Study.

BACKGROUND: With increasing prevalence of Parkinson's disease (PD), instrumentation surgery of the thoracolumbar spine of PD patients grows in importance. Poor operative results with high rates of revision surgery have been reported. The goal of this study was to compare the biomechanical complications of thoracolumbar instrumentation surgery of patients with and without PD. METHODS: In a retrospective case-control study, we compared 16 PD patients with a matched cohort of 104 control patients regarding the following postinstrumentation complications: (1) adjacent joint disease, (2) material failure, and (3) material loosening. Also, we compared the spinal bone density, which is the main prognostic criteria for failed instrumentation surgery, between the groups. RESULTS: We found the rate of material revision to be significantly higher in PD patients (43.8 vs. 13.5%, p = 0.008, odds ratio (OR) = 5.0). Furthermore, the indications for revision surgery differed between the groups, with more hardware failures in the PD group and more adjacent segment degeneration in the control group. PD patients profited from modern operation techniques (percutaneous instrumentation and CT-navigated screw implantation). Hospitalization was significantly longer for PD patients (20.2 ± 15.1 vs. 14.1 ± 8.9 days, p = 0.03). CONCLUSION: PD patients exhibit challenging biomechanical demands on instrumenting the spine. Besides osteoporosis, especially sagittal imbalance, gait disturbance, and altered muscle tone may be contributive. PD patients may particularly profit from navigated and less invasive surgical techniques.

Surgical Site Infections Associated With Implanted Pulse Generators for Deep Brain Stimulation: Meta-Analysis and Systematic Review.

OBJECTIVES: The aim of this study was to identify and systematically analyze relevant literature on surgical site infections (SSIs) associated with implantable pulse generator (IPG) procedures for deep brain stimulation (DBS). MATERIALS AND METHODS: In compliance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, we conducted a systematic review and meta-analyses of 58 studies that reported SSI rates of 11,289 patients and 15,956 IPG procedures. A meta-analysis of proportions was performed to estimate the pooled proportion of SSIs across DBS procedures in general and to estimate the proportion of SSIs that occur at the IPG pocket. Moreover, a meta-analysis of odds ratio (OR) was conducted on those studies that reported their results of applying topical vancomycin powder during closure of the IPG wound. Results are presented as rates and OR with 95% CIs. RESULTS: The pooled proportion of SSIs was 4.9% (95% CI, 4.1%-6.1%) among all DBS procedures. The dominant SSI localization was the IPG pocket in 61.2% (95% CI, 53.4%-68.5%). A trend toward a beneficial effect of vancomycin powder over standard wound closure was found with an OR of 0.46 (95% CI, 0.21-1.02). Most studies (79.1%) that reported their treatment strategy in case of SSI had a strict protocol of removal of the IPG, followed by antimicrobial treatment and reimplantation of the IPG once the SSI had been eradicated. CONCLUSIONS: The IPG pocket was identified as the main site of SSI after DBS procedures. Most studies recommend complete IPG removal, antimicrobial treatment, and reimplantation of an IPG once the SSI has been eradicated. Future studies are needed to clarify the role of alternative approaches (eg, topical vancomycin powder) in the prevention of SSI associated with IPG.

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

BACKGROUND: Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is highly effective in controlling motor symptoms in patients with Parkinson's disease. However, correct selection of stimulation parameters is pivotal to treatment success and currently follows a time-consuming and demanding trial-and-error process. We aimed to assess treatment effects of stimulation parameters suggested by a recently published algorithm (StimFit) based on neuroimaging data. METHODS: This double-blind, randomised, crossover, non-inferiority trial was carried out at Charité - Universitätsmedizin, Berlin, Germany, and enrolled patients with Parkinson's disease treated with directional octopolar electrodes targeted at the STN. All patients had undergone DBS programming according to our centre's standard of care (SoC) treatment before study recruitment. Based on perioperative imaging data, DBS electrodes were reconstructed and StimFit was applied to suggest optimal stimulation settings. Patients underwent motor assessments using the Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS-III) during OFF-medication and in OFF-stimulation and ON-stimulation states under both conditions, StimFit and SoC parameter settings. Patients were randomly assigned (1:1) to receive either StimFit-programmed DBS first and SoC-programmed DBS second, or SoC-programmed DBS first and StimFit-programmed DBS second. The allocation schedule was generated using a computerised random number generator. Both the rater and patients were masked to the sequence of SoC and StimFit stimulation conditions. All patients who participated in the study were included in the analysis. The primary endpoint of this study was the absolute mean difference between MDS-UPDRS-III scores under StimFit and SoC stimulation, with a non-inferiority margin of 5 points. The study was registered at the German Register for Clinical Trials (DRKS00023115), and is complete. FINDINGS: Between July 10, 2020, and Oct 28, 2021, 35 patients were enrolled in the study; 18 received StimFit followed by SoC stimulation, and 17 received SoC followed by StimFit stimulation. Mean MDS-UPDRS-III scores improved from 47·3 (SD 17·1) at OFF-stimulation baseline to 24·7 (SD 12·4) and 26·3 (SD 12·4) under SoC and StimFit stimulation, respectively. Mean difference between motor scores was -1·6 (SD 7·1; 95% CI -4·0 to 0·9; superiority test psuperiority=0·20; n=35), establishing non-inferiority of StimFit stimulation at a margin of -5 points (non-inferiority test pnon-inferiority=0·0038). In six patients (17%), initial programming of StimFit settings resulted in acute side-effects and amplitudes were reduced until side-effects disappeared. INTERPRETATION: Automated data-driven algorithms can predict stimulation parameters that lead to motor symptom control comparable to SoC treatment. This approach could significantly decrease the time necessary to obtain optimal treatment parameters. FUNDING: Deutsche Forschungsgemeinschaft through NeuroCure Clinical Research Center and TRR 295.