Parkinsonian Tremor Research Articles

AI-powered Neuroprosthetics for brain-computer interfaces (BCIs)

Imagine a world where individuals with lost or impaired sensory or motor function can regain independence and control through technology. This is the promise of neuroprosthetics, a rapidly evolving field that bridges the gap between the nervous system and external devices. Neuroprosthetics encompass a range of implanted or external devices designed to: Substitute for a malfunctioning part of the nervous system. Assist in the recovery or enhancement of lost or impaired function. Augment existing capabilities, creating new possibilities. These devices interact with the nervous system using various methods, including: Electrical stimulation: Directly stimulating nerves or brain tissue to evoke desired responses. Recording brain activity: Capturing electrical signals generated by the brain for further processing and interpretation. Common applications of neuroprosthetics include: Cochlear implants: Restoring hearing in individuals with severe hearing loss. Deep brain stimulation (DBS): Treating movement disorders like Parkinson's disease and essential tremor. Bionic limbs: Providing control of prosthetic arms and legs for individuals with limb loss. Brain-computer interfaces (BCIs): Enabling communication and control of external devices using brain signals alone. Neuroprosthetics offer a glimpse into the future of medicine and technology. With ongoing advancements, these devices have the potential to revolutionize how we treat neurological conditions, restore lost abilities, and even enhance human potential. However, significant challenges remain, including ensuring long-term safety, improving accuracy and reliability, and addressing ethical considerations. As research continues, neuroprosthetics holds immense potential to improve the lives of millions and redefine what it means to be human. The integration of artificial intelligence (AI) with neuroprosthetics has marked a significant milestone in the development of brain-computer interfaces (BCIs). This emerging synergy aims to enhance the quality of life for individuals with disabilities by restoring lost sensory, motor, and cognitive functions. This review article explores the advancements in AI-powered neuroprosthetics for BCIs, focusing on their design, functionality, and the ethical considerations that accompany their integration into medical practice.

P.051 Parkinson’s disease tremor can show entrainment and distractibility with tapping test

Background: Electrophysiological tests such as the tapping test are used to distinguish functional and organic tremors, in which patients with functional tremor commonly show entrainment and amplitude reduction (>50% decrease relative to baseline) of contralateral tremor during tapping. While these features are suggested to be specific to functional tremor, the tapping test in Parkinson’s disease (PD) tremor has not been tested. Methods: We evaluated 18 PD patients (2F, age 64.17±7.30 [mean±SD] years) with rest and postural tremors using surface electromyography and triaxial accelerometry. Patients were recorded while tapping at 1, 3 and 5 Hz with the contralateral arm at rest or outstretched. Tremor amplitude and frequency were calculated using power spectrum analysis from accelerometer recordings. Results: Reduction of rest tremor amplitude was observed in 3/18 patients during 1 and 3 Hz tapping. Reduction was seen in 3/16 and 1/16 patients with postural tremors at 1 and 3 Hz tapping, respectively. Frequency shifts (>1.5 Hz) were observed in 3/18 rest tremors and 6/16 postural tremors. Seven patients exhibited rest and/or postural tremor entrainment during 3 or 5 Hz tapping. Conclusions: Distractibility and entrainment can be found in PD tremor. The tapping test may not reliably distinguish between PD tremor and functional tremor.

Analysis of alpha-synuclein harvested from intracranial instruments used in deep brain stimulation surgery for Parkinson's disease.

Alpha-synuclein (αSyn) forms pathologic aggregates in Parkinson's disease (PD) and is implicated in mechanisms underlying neurodegeneration. While pathologic αSyn has been extensively studied, there is currently no method to evaluate αSyn within the brains of living patients. Patients with PD are often treated with deep brain stimulation (DBS) surgery in which surgical instruments are in direct contact with neuronal tissue; herein, we describe a method by which tissue is purified from DBS surgical instruments in PD and essential tremor (ET) patients and demonstrate that αSyn is robustly detected. 24 patients undergoing DBS surgery for PD (17 patients) or ET (7 patients) were enrolled; from patient samples, 81.2 ± 44.8 μg protein (n=15) is able to be purified, with immunoblot assays specific for αSyn reactive in all tested samples. Light microscopy revealed axons and capillaries as the primary components of purified tissue (n=3). Further analysis was conducted using western blot, demonstrating that truncated αSyn (1-125 αSyn) was significantly increased in PD (n=5) compared to ET (n=3), in which αSyn misfolding is not expected (0.64 ± 0.25 vs. 0.25 ± 0.12, P = 0.046), thus showing that pathologic αSyn can be reliably purified from living PD patients with this method.

Speech, voice, and language outcomes following deep brain stimulation: A systematic review.

Deep brain stimulation (DBS) reliably ameliorates cardinal motor symptoms in Parkinson's disease (PD) and essential tremor (ET). However, the effects of DBS on speech, voice and language have been inconsistent and have not been examined comprehensively in a single study. We conducted a systematic analysis of literature by reviewing studies that examined the effects of DBS on speech, voice and language in PD and ET. A total of 675 publications were retrieved from PubMed, Embase, CINHAL, Web of Science, Cochrane Library and Scopus databases. Based on our selection criteria, 90 papers were included in our analysis. The selected publications were categorized into four subcategories: Fluency, Word production, Articulation and phonology and Voice quality. The results suggested a long-term decline in verbal fluency, with more studies reporting deficits in phonemic fluency than semantic fluency following DBS. Additionally, high frequency stimulation, left-sided and bilateral DBS were associated with worse verbal fluency outcomes. Naming improved in the short-term following DBS-ON compared to DBS-OFF, with no long-term differences between the two conditions. Bilateral and low-frequency DBS demonstrated a relative improvement for phonation and articulation. Nonetheless, long-term DBS exacerbated phonation and articulation deficits. The effect of DBS on voice was highly variable, with both improvements and deterioration in different measures of voice. This was the first study that aimed to combine the outcome of speech, voice, and language following DBS in a single systematic review. The findings revealed a heterogeneous pattern of results for speech, voice, and language across DBS studies, and provided directions for future studies.

Association Analysis of Essential Tremor-Associated Genetic Variants in Sporadic Late-Onset Parkinson's Disease.

Parkinson's disease (PD) and Essential tremor (ET) are the two most common tremor diseases with recognized genetic pathogenesis. The overlapping clinical features suggest they may share genetic predispositions. Our previous study systematically investigated the association between rare coding variants in ET-associated genes and early-onset PD (EOPD), and found the suggestive association between teneurin transmembrane protein 4 (TENM4) and EOPD. In the current research, we explored the potential genetic interplay between ET-associated genetic loci/genes and sporadic late-onset PD (LOPD). We performed whole-genome sequencing in the 1962 sporadic LOPD cases and 1279 controls from mainland China. We first used logistic regression analysis to test the top 16 SNPs identified by the ET genome-wide association study for the association between ET and LOPD. Then we applied the optimized sequence kernel association testing to explore the rare variant burden of 33 ET-associated genes in this cohort. We did not observe a significant association between the included SNPs with LOPD. We also did not discover a significant burden of rare deleterious variants of ET-associated genes in association with LOPD risk. Our results do not support the role of ET-associated genetic loci and variants in LOPD. 1962 cases and 1279 controls were recruited to study the potential genetic interplay between ET-associated genetic loci/variants and sporadic LOPD.No significant association between the ET-associated SNPs and LOPD were observed.No significant burden of rare deleterious variants of ET-associated gene in LOPD risk were found.

Epidemiology and differential diagnosis of tremor

Tremor are involuntary, rhythmic, oscillatory movements of a body part. The diagnosis of tremor is based on clinical information obtained from the history and physical examination. The most common types are enhanced physiological tremor, essential tremor, and parkinsonian tremor. The first step in evaluating a patient with a tremor is to classify the tremor based on its activation state, topographic distribution, and frequency. We analyzed the medical records of 99 patients who applied with complaints of tremor to the Regional Clinical Hospital, which showed that the most common diagnoses in patients with tremor were Parkinson's disease (44.4 %) and essential tremor (15.1 %).

The Role of Treatment-Related Parameters and Brain Morphology in the Lesion Volume of Magnetic-Resonance-Guided Focused Ultrasound Thalamotomy in Patients with Tremor-Dominant Neurological Conditions.

To determine the best predictor of lesion volume induced by magnetic resonance (MR)-guided focused ultrasound (MRgFUS) thalamotomy in patients with tremor-dominant symptoms in Parkinson's disease (PD) and essential tremor (ET) patients. Thirty-six neurological patients with medication-refractory tremor (n°19 PD; n°17 ET) were treated using a commercial MRgFUS brain system (Exablate Neuro 4000, Insightec) integrated with a 1.5 T MRI unit (Sigma HDxt; GE Medical System). Linear regression analysis was used to determine how the demographic, clinical, radiological (Fazekas scale), volumetric (total GM/WM/CSF volume, cortical thickness), and MRgFUS-related parameters [Skull Density Ratio (SDR), n° of transducer elements, n° of sonications, skull area, maximal energy delivered (watt), maximal power delivered (joule), maximal sonication time delivered, maximal mean temperature reached (T°C_max), accumulated thermal dose (ATD)] impact on ventral intermediate (VIM)-thalamotomy-related 3D volumetric lesions of necrosis and edema. The VIM thalamotomy was clinically efficacious in improving the tremor symptoms of all the patients as measured at 1 week after treatment. Multiple regression analysis revealed that T°C_max and n° of transducer elements were the best predictors of the necrosis and edema volumes. Moreover, total WM volume also predicted the size of necrosis. Our study provides new insights into the clinical MRgFUS procedures that can be used to forecast brain lesion size and improve treatment outcomes.

Modeling the volume of tissue activated in deep brain stimulation and its clinical influence: a review.

Deep brain stimulation (DBS) is a neuromodulatory therapy that has been FDA approved for the treatment of various disorders, including but not limited to, movement disorders (e.g., Parkinson's disease and essential tremor), epilepsy, and obsessive-compulsive disorder. Computational methods for estimating the volume of tissue activated (VTA), coupled with brain imaging techniques, form the basis of models that are being generated from retrospective clinical studies for predicting DBS patient outcomes. For instance, VTA models are used to generate target-and network-based probabilistic stimulation maps that play a crucial role in predicting DBS treatment outcomes. This review defines the methods for calculation of tissue activation (or modulation) including ones that use heuristic and clinically derived estimates and more computationally involved ones that rely on finite-element methods and biophysical axon models. We define model parameters and provide a comparison of commercial, open-source, and academic simulation platforms available for integrated neuroimaging and neural activation prediction. In addition, we review clinical studies that use these modeling methods as a function of disease. By describing the tissue-activation modeling methods and highlighting their application in clinical studies, we provide the neural engineering and clinical neuromodulation communities with perspectives that may influence the adoption of modeling methods for future DBS studies.

Frameless, Virtual Cone Linac-based Stereotactic Radiosurgery for Essential & Parkinsonian Tremor: A Phase I/II Prospective Clinical Trial (S35.001)

Frameless, Virtual Cone Linac-based Stereotactic Radiosurgery for Essential & Parkinsonian Tremor: A Phase I/II Prospective Clinical Trial (S35.001)

Model-based closed-loop control of thalamic deep brain stimulation.

Introduction: Closed-loop control of deep brain stimulation (DBS) is beneficial for effective and automatic treatment of various neurological disorders like Parkinson's disease (PD) and essential tremor (ET). Manual (open-loop) DBS programming solely based on clinical observations relies on neurologists' expertise and patients' experience. Continuous stimulation in open-loop DBS may decrease battery life and cause side effects. On the contrary, a closed-loop DBS system uses a feedback biomarker/signal to track worsening (or improving) of patients' symptoms and offers several advantages compared to the open-loop DBS system. Existing closed-loop DBS control systems do not incorporate physiological mechanisms underlying DBS or symptoms, e.g., how DBS modulates dynamics of synaptic plasticity. Methods: In this work, we propose a computational framework for development of a model-based DBS controller where a neural model can describe the relationship between DBS and neural activity and a polynomial-based approximation can estimate the relationship between neural and behavioral activities. A controller is used in our model in a quasi-real-time manner to find DBS patterns that significantly reduce the worsening of symptoms. By using the proposed computational framework, these DBS patterns can be tested clinically by predicting the effect of DBS before delivering it to the patient. We applied this framework to the problem of finding optimal DBS frequencies for essential tremor given electromyography (EMG) recordings solely. Building on our recent network model of ventral intermediate nuclei (Vim), the main surgical target of the tremor, in response to DBS, we developed neural model simulation in which physiological mechanisms underlying Vim-DBS are linked to symptomatic changes in EMG signals. By using a proportional-integral-derivative (PID) controller, we showed that a closed-loop system can track EMG signals and adjust the stimulation frequency of Vim-DBS so that the power of EMG reaches a desired control target. Results and discussion: We demonstrated that the model-based DBS frequency aligns well with that used in clinical studies. Our model-based closed-loop system is adaptable to different control targets and can potentially be used for different diseases and personalized systems.

1136 Risk Factors for Postoperative Urinary Retention After Deep Brain Stimulation Surgery: The Role of the Subthalamic Nucleus

INTRODUCTION: Deep brain stimulation (DBS) is a widely used neurosurgical procedure for treating Parkinson's disease (PD) and essential tremor (ET). Lower urinary tract dysfunction is a common complication in PD, and this study examines the risk factors for postoperative urinary retention (POUR) after DBS surgery in PD and ET patients to improve patient outcomes. METHODS: This retrospective study analyzed data from patients who underwent DBS surgery for PD and ET at the University of Florida between 2010 and 2021. Data on patient characteristics and surgical details were collected and analyzed using univariate and mixed-linear models. RESULTS: 350 patients underwent 1086 DBS or IPG surgeries, with 153 of them having PD and 197 having ET. The rate of POUR was 79/477 (16.6%), 19/295 (5.2%), and 1/246 (0.4%) for Part 1, Part 2, and IPG replacement. Optimal mixed linear modeling revealed history of urinary retention (OR = 10.2, p = .002), Part 1 surgery (OR = 3.6 compared to Part 2, p < .0003), male sex (OR = 2.5, p = .011), having an electrode placed or connected for the first time (OR = 1.8, p = .046), surgical time (OR 1.5 for each 30 min increase, p < .0001), CCI (OR = 1.4 per comorbidity, p= .006), and preoperative opioid use (OR 1.4 for each additional 10 MME, p = .022) to be significant risk factors for POUR. Having an electrode in STN was found to be protective of POUR (OR = 0.4, p = .030). CONCLUSIONS: While most identified risk factors for POUR in DBS are non-modifiable, they remain important for preoperative planning. Reducing opioid use and minimizing surgical time may help mitigate POUR risk. Targeting the STN during DBS may lead to decreased POUR rates, indicating the potential benefits of STN-targeted DBS for PD and ET patients.

Differential influences of rest tremor on brain fiber architecture in essential tremor and Parkinson's disease

BackgroundRest tremor is a movement disorder commonly found in diseases like Parkinson's disease (PD) and essential tremor (ET). Rest tremor typically shows slower progression in PD, but more severe progression in ET. However, the underlying white matter organization of rest tremor behind PD and ET remains unclear. MethodsThis study included 57 ET patients (40 without rest tremor (ETWR), 17 with rest tremor (ETRT)), 68 PD patients (34 without rest tremor (PDWR), 34 with rest tremor (PDRT)), and 62 normal controls (NC). Fixel-based analysis was used to evaluate the structural changes of white matter in rest tremor in these different diseases. ResultsThe fiber-bundle cross-section (FC) of the right non-decussating dentato-rubro-thalamic tract and several fibers outside the dentato-rubro-thalamic pathway in ETWR were significantly higher than that in NC. The fiber density and cross-section of the left nigro-pallidal in PDWR is significantly lower than that in NC, while the FC of bilateral nigro-pallidal in PDRT is significantly lower than that in NC. ConclusionET patients with pure action tremor showed over-activation of fiber tracts. However, when superimposed with rest tremor, ET patients no longer exhibited over-activation of fiber tracts, but rather showed a trend of fiber tract damage. Except for the nigro-pallidal degeneration in all PD, PDRT will not experience further deterioration in fiber organization. These results provide important insights into the unique effects of rest tremor on brain fiber architecture in ET and PD.

Исследование и разработка методов автоматического поиска признаков болезни Паркинсона и эссенциального тремора на базе AUC-диаграмм

Methods and optimization algorithms for automatic search for AUC-diagram-based features of Parkinson's disease and essential tremor were studied and developed. AUC diagrams are a new method for statistical analysis of biomedical signals, based on visualizing the parameters of wave train electrical activity in the brain and muscles. The effectiveness of this method has been demonstrated in solving problems of early and differential diagnosis of Parkinson's disease and essential tremor. The disadvantage of this method is the need to construct and analyze a large number of graphic diagrams. In this regard, automation of the analysis of AUC diagrams is an urgent task. The mathematical problem of finding features based on the analysis of AUC diagrams is reduced to an optimization problem in a multidimensional feature space. A distinctive feature of the space constructed using AUC diagrams is the presence of relatively large compact areas containing local maxima and minima. This property of the feature space facilitates the search for solutions to the optimization problem, but at the same time requires the selection of optimization algorithms and fitness functions that increase the likelihood of detecting global extrema. In this work, methods for automatically searching for global extrema in the multidimensional space of features of wave train electrical activity are investigated and developed.

Differential patterns of functional connectivity in tremor dominant Parkinson's disease and essential tremor plus.

Tremor dominant Parkinson's disease (TDPD) and essential tremor plus (ETP) syndrome are commonly encountered tremor dominant neurological disorders. Although the basal ganglia thalamocortical (BGTC) and cerebello thalamocortical (CTC) networks are implicated in tremorogenesis, the extent of functional connectivity alterations across disorders is uncertain. This study aims to evaluate functional connectivity of the BGTC and CTC in TDPD and ETP. Resting state functional MRI was acquired for 25 patients with TDPD, ETP and 22 healthy controls (HC). Following pre-processing and denoising, seed-to-voxel based connectivity was carried out at FDR < 0.05 using ROIs belonging to the BGTC and CTC. Fahn-Tolosa-Marin tremor rating scale (FTMRS) was correlated with the average connectivity values at FDR < 0.05. Compared to HC, TDPD showed decreased connectivity between cerebellum and pre, post central gyrus. While, ETP showed decreased connectivity between pallidum and occipital cortex, precuneus, cuneus compared to HC. In comparison to ETP, TDPD showed increased connectivity between precentral gyrus, pallidum, SNc with the default mode network (DMN), and decreased connectivity between cerebellum with superior, middle frontal gyrus was observed. Tremor severity positively correlated with connectivity between SNc and DMN in TDPD, and negatively correlated with pallidal connectivity in ETP. Pattern of BGTC, CTC involvement is differential i.e., higher connectivity of the BGTC nodes in TDPD, and higher connectivity of cerebellar nodes in ETP. The interesting observation of pallidal involvement in ETP suggests the role of BGTC in the pathogenesis of ETP, and indicated similarities in concepts of tremor genesis in TDPD and ETP.

Persistence of Basal Ganglia Oscillatory Activity During Tremor Attenuation by Movement in Parkinson's Disease Patients.

One of the characteristics of parkinsonian tremor is that its amplitude decreases with movement. Current models suggest an interaction between basal ganglia (BG) and cerebello-thalamo-cortical circuits in parkinsonian tremor pathophysiology. We aimed to correlate central oscillation in the BG with electromyographic activity during re-emergent tremor in order to detect changes in BG oscillatory activity when tremor is attenuated by movement. We performed a prospective, observational study on consecutive parkinsonian patients who underwent deep brain stimulation surgery and presented re-emergent tremor. Coherence analysis between subthalamic nucleus/globus pallidus internus (STN/GPi) tremorous activity measured by microrecording (MER) and electromyogram (EMG) from flexor and extensor wrist muscles during rest, posture, and re-emergent tremor pause was performed during surgery. The statistical significance level of the MER-EMG coherence was determined using surrogate data analysis, and the directionality of information transfer between BG and muscle was performed using entropy transfer analysis. We analyzed 148 MERs with tremor-like activity from 6 patients which were evaluated against the simultaneous EMGs, resulting in 296 correlations. Of these, 26 presented a significant level of coherence at tremor frequency, throughout rest and posture, with a complete EMG stop in between. During the pause, all recordings showed sustained MER peaks at tremor frequency (±1.5 Hz). Information flows preferentially from BG to muscle during rest and posture, with a loss of directionality during the pause. Our results suggest that oscillatory activity in STN/GPi functionally linked to tremor sustains firing frequency during re-emergent tremor pause, thus suggesting no direct role of the BG circuit on tremor attenuation due to voluntary movements. © 2024 International Parkinson and Movement Disorder Society.

Coupled Activation of the Hyperdirect and Cerebellothalamic Pathways with Zona Incerta Deep Brain Stimulation.

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) or ventral intermediate nucleus (VIM) are established targets for the treatment of Parkinson's disease (PD) or essential tremor (ET), respectively. However, DBS of the zona incerta (ZI) can be effective for both disorders. VIM DBS is assumed to achieve its therapeutic effect via activation of the cerebellothalamic (CBT) pathway, whereas the activation of the hyperdirect (HD) pathway likely plays a role in the mechanisms of STN DBS. Interestingly, HD pathway axons also emit collaterals to the ZI and red nucleus (RN) and the CBT pathway courses nearby to the ZI. The aim was to examine the ability of ZI DBS to mutually activate the HD and CBT pathways in a detailed computational model of human DBS. We extended a previous model of the human HD pathway to incorporate axon collaterals to the ZI and RN. The anatomical framework of the model system also included representations of the CBT pathway and internal capsule (IC) fibers of passage. We then performed detailed biophysical simulations to quantify DBS activation of the HD, CBT, and IC pathways with electrodes located in either the STN or ZI. STN DBS and ZI DBS both robustly activated the HD pathway. However, STN DBS was limited by IC activation at higher stimulus amplitudes. Alternatively, ZI DBS avoided IC activation while simultaneously activating the HD and CBT pathways. From both neuroanatomical and biophysical perspectives, ZI DBS represents an advantageous target for coupled activation of the HD and CBT pathways. © 2024 International Parkinson and Movement Disorder Society.

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

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. 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. 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. 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.

Risk factors for postoperative urinary retention after deep brain stimulation surgery: the role of the subthalamic nucleus.

Deep brain stimulation (DBS) is a common procedure in neurosurgery used for the treatment of Parkinson's disease (PD) and essential tremor (ET) among other disorders. Lower urinary tract dysfunction is a common complication in PD, and this study aimed to evaluate the risk factors of postoperative urinary retention (POUR) after DBS surgery in patients with PD compared with patients with ET. Understanding the risk factors associated with this complication may help in the development of strategies to minimize its occurrence and improve patient outcomes. The study was a retrospective analysis of patients who underwent DBS surgery for PD and ET at the University of Florida between 2010 and 2021. The surgical technique used has been described in previous articles and included a two-stage procedure, with stage 1 involving burr hole placement, microelectrode recording, and electrode implantation and stage 2 involving the placement of an implantable pulse generator (IPG). Data were collected on patient characteristics and surgical details and analyzed using univariate and mixed-linear models. Post hoc propensity score matching was used to confirm the association between subthalamic nucleus (STN)-DBS and POUR. The study included 350 patients (153 with PD and 197 with ET) who underwent 1086 DBS surgeries (lead implantations, IPG placement, and IPG replacements). The POUR rates were 16.6% (79/477), 5.2% (19/363), and 0.4% (1/246) for stage 1, stage 2, and IPG replacement procedures, respectively. Optimal mixed-effects logistic modeling revealed history of urinary retention (OR 9.3, p = 0.004), male sex (OR 2.7, p = 0.011), having an electrode placed or connected for the first time (OR 2.2, p = 0.014), anesthesia time (OR 1.5 for each 30-minute increase, p < 0.0001), preoperative opioid use (OR 1.4 for each additional 10 morphine milligram equivalents, p = 0.032), and Charlson Comorbidity Index (OR 1.4 per comorbidity, p = 0.017) to be significant risk factors for POUR. Having an electrode in the STN was found to be protective of POUR (propensity score-matched analysis: OR 0.2, p = 0.010). Most risk factors found to increase the risk of POUR in DBS are not modifiable but are still important to consider in preoperative planning. Opioid use reduction and shorter anesthesia time may be modifiable risk factors to weigh against their alternative. Targeting the STN during DBS may result in decreased rates of POUR. This highlights the potential for STN-targeted DBS in reducing POUR risk in PD and ET patients.

Disparities in the treatment of movement disorders using deep brain stimulation.

Deep brain stimulation (DBS) is a well-established treatment for Parkinson's disease (PD) and essential tremor (ET). Although the prevalence of PD and ET can vary by sex and race, little is known about the accessibility of neurosurgical treatments for these conditions. In this nationwide study, the authors aimed to characterize trends in the use of DBS for the treatment of PD and ET and to identify disparities in the neurosurgical treatment of these diseases based on ethnic, racial, sex, insurance, income, hospital, and geographic factors. Using the dates January 1, 2012, to December 31, 2019, the authors queried the National Inpatient Sample database for all discharges with an ICD-9 or ICD-10 diagnosis of PD or ET. Among these discharges, the DBS rates were reported for each subgroup of race, ethnicity, and sex. To develop national estimates, all analyses were weighted. Among 2,517,639 discharges with PD, 29,820 (1.2%) received DBS, and among 652,935 discharges with ET, 11,885 (1.8%) received DBS. Amid the PD cases, Black patients (n = 405 [0.2%], OR 0.16, 95% CI 0.12-0.20) were less likely than White patients (n = 23,975 [1.2%]) to receive DBS treatment, as were Hispanic patients (n = 1965 [1.1%], OR 0.76, 95% CI 0.65-0.88), whereas Asian/Pacific Islander patients (n = 855 [1.5%]) did not statistically differ from White patients. Amid the ET cases, Black (n = 230 [0.8%], OR 0.39, 95% CI 0.27-0.56), Hispanic (n = 215 [1.0%], OR 0.39, 95% CI 0.28-0.55), and Asian/Pacific Islander (n = 55 [1.0%], OR 0.51, 95% CI 0.28-0.93) patients were less likely than White patients (n = 10,440 [1.9%]) to receive DBS. Females were less likely than males to receive DBS for PD (OR 0.69, p < 0.0001) or ET (OR 0.70, p < 0.0001). The authors describe significant racial and sex-based differences in the utilization of DBS for the treatment of PD and ET. Further research is required to ascertain the causes of these disparities, as well as any differences in access to specialty neurosurgical care and referral for neuromodulation approaches.

Pose-based tremor type and level analysis for Parkinson's disease from video.

Current methods for diagnosis of PD rely on clinical examination. The accuracy of diagnosis ranges between 73 and 84%, and is influenced by the experience of the clinical assessor. Hence, an automatic, effective and interpretable supporting system for PD symptom identification would support clinicians in making more robust PD diagnostic decisions. We propose to analyze Parkinson's tremor (PT) to support the analysis of PD, since PT is one of the most typical symptoms of PD with broad generalizability. To realize the idea, we present SPA-PTA, a deep learning-based PT classification and severity estimation system that takes consumer-grade videos of front-facing humans as input. The core of the system is a novel attention module with a lightweight pyramidal channel-squeezing-fusion architecture that effectively extracts relevant PT information and filters noise. It enhances modeling performance while improving system interpretability. We validate our system via individual-based leave-one-out cross-validation on two tasks: the PT classification task and the tremor severity rating estimation task. Our system presents a 91.3% accuracy and 80.0% F1-score in classifying PT with non-PT class, while providing a 76.4% accuracy and 76.7% F1-score in more complex multiclass tremor rating classification task. Our system offers a cost-effective PT classification and tremor severity estimation results as warning signs of PD for undiagnosed patients with PT symptoms. In addition, it provides a potential solution for supporting PD diagnosis in regions with limited clinical resources.