Characterizing Disease Progression in Parkinson's Disease from Videos of the Finger Tapping Test.

INTRODUCTION: Parkinson's disease (PD) is characterized by motor symptoms whose progression is typically assessed using clinical scales, namely the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS). Despite its reliability, the scale is bounded by a 5-point scale that limits its ability to track subtle changes in disease progression and is prone to subjective interpretations. We aimed to develop an automated system to objectively quantify motor symptoms in PD using Machine Learning (ML) algorithms to analyze videos and capture nuanced features of disease progression. METHODS: We analyzed videos of the Finger Tapping test, a component of the MDS-UPDRS, from 24 healthy controls and 66 PD patients using ML algorithms for hand pose estimation. We computed multiple movement features related to bradykinesia from videos and employed a novel tiered classification approach to predict disease severity that employed different features according to severity. We compared our video-based disease severity prediction approach against other approaches recently introduced in the literature. RESULTS: Traditional kinematics features such as amplitude and velocity changed linearly with disease severity, while other non-traditional features displayed non-linear trends. The proposed disease severity prediction approach demonstrated superior accuracy in detecting PD and distinguishing between different levels of disease severity when compared to existing approaches.

Immunophenotyping Tracks Motor Progression in Parkinson's Disease Associated with a TH Mutation.

Background: Parkinson's disease (PD) is the second most common neurodegenerative disorder, with genetic factors accounting for about 15% of cases. There is a significant challenge in tracking disease progression and treatment response, crucial for developing new therapies. Traditional methods like imaging, clinical monitoring, and biomarker analysis have not conclusively tracked disease progression or treatment response in PD. Our previous research indicated that PD patients with increased dopamine transporter (DAT) and tyrosine hydroxylase (TH) in peripheral blood mononuclear cells (PBMCs) might show disease progression and respond to levodopa treatment. Objective: This study evaluates whether DAT- and TH-expressing PBMCs can monitor motor progression in a PD patient with a heterozygous TH mutation. Methods: We conducted a longitudinal follow-up of a 46-year-old female PD patient with a TH mutation, assessing her clinical features over 18 months through DaT scans and PBMC immunophenotyping. This was compared with idiopathic PD patients (130 subjects) and healthy controls (80 age/sex-matched individuals). Results: We found an increase in DAT+ immune cells concurrent with worsening motor scores (UPDRS-III). Following levodopa therapy, unlike idiopathic PD patients, TH+ immune cell levels in this patient remained high even as her motor scores improved. Conclusions: Longitudinal immunophenotyping in this PD patient suggests DAT+ and TH+ PBMCs as potential biomarkers for tracking PD progression and treatment efficacy, supporting further exploration of this approach in PD research.

Neuron-level explainable AI for Alzheimer's Disease assessment from fundus images.

Alzheimer's Disease (AD) is a progressive neurodegenerative disease and the leading cause of dementia. Early diagnosis is critical for patients to benefit from potential intervention and treatment. The retina has emerged as a plausible diagnostic site for AD detection owing to its anatomical connection with the brain. However, existing AI models for this purpose have yet to provide a rational explanation behind their decisions and have not been able to infer the stage of the disease's progression. Along this direction, we propose a novel model-agnostic explainable-AI framework, called Granu la ̲ r Neuron-le v ̲ el Expl a ̲ iner (LAVA), an interpretation prototype that probes into intermediate layers of the Convolutional Neural Network (CNN) models to directly assess the continuum of AD from the retinal imaging without the need for longitudinal or clinical evaluations. This innovative approach aims to validate retinal vasculature as a biomarker and diagnostic modality for evaluating Alzheimer's Disease. Leveraged UK Biobank cognitive tests and vascular morphological features demonstrate significant promise and effectiveness of LAVA in identifying AD stages across the progression continuum.

Deep learning predicts prevalent and incident Parkinson's disease from UK Biobank fundus imaging.

Parkinson's disease is the world's fastest-growing neurological disorder. Research to elucidate the mechanisms of Parkinson's disease and automate diagnostics would greatly improve the treatment of patients with Parkinson's disease. Current diagnostic methods are expensive and have limited availability. Considering the insidious and preclinical onset and progression of the disease, a desirable screening should be diagnostically accurate even before the onset of symptoms to allow medical interventions. We highlight retinal fundus imaging, often termed a window to the brain, as a diagnostic screening modality for Parkinson's disease. We conducted a systematic evaluation of conventional machine learning and deep learning techniques to classify Parkinson's disease from UK Biobank fundus imaging. Our results suggest Parkinson's disease individuals can be differentiated from age and gender-matched healthy subjects with 68% accuracy. This accuracy is maintained when predicting either prevalent or incident Parkinson's disease. Explainability and trustworthiness are enhanced by visual attribution maps of localized biomarkers and quantified metrics of model robustness to data perturbations.

Impacts of Deep Brain Stimulation of the Globus Pallidus Internus on Swallowing: A Retrospective, Cross-Sectional Study.

Deep brain stimulation (DBS) is a common treatment for motor symptoms of Parkinson disease (PD), a condition associated with increased risk of dysphagia. The effect of DBS on swallowing function has not been comprehensively evaluated using gold-standard imaging techniques, particularly for globus pallidus internus (GPi) DBS. The objective of this retrospective, cross-sectional study was to identify differences in swallowing safety and timing kinematics among PD subjects with and without GPi DBS. We investigated the effects of unilateral and bilateral GPi DBS as well as the relationship between swallowing safety and DBS stimulation parameters, using retrospective analysis of videofluoroscopy recordings (71 recordings from 36 subjects) from electronic medical records. Outcomes were analyzed by surgical status (pre-surgical, unilateral DBS, bilateral DBS). The primary outcome was percent of thin-liquid bolus trials rated as unsafe, with Penetration-Aspiration Scale scores of 3 or higher. Secondary analyses included swallowing timing measures, relationships between swallowing safety and DBS stimulation parameters, and Dynamic Imaging Grade of Swallowing Toxicity ratings. Most subjects swallowed all boluses safely (19/29 in the pre-surgical, 16/26 in the unilateral DBS, and 10/16 in the bilateral DBS conditions). Swallowing safety impairment did not differ among stimulation groups. There was no main effect of stimulation condition on timing metrics, though main effects were found for sex and bolus type. Stimulation parameters were not correlated with swallowing safety. Swallowing efficiency and overall impairment did not differ among conditions. These results provide evidence that GPi DBS does not affect pharyngeal swallowing function. Further, prospective, investigations are needed.

Meta-analysis of Association between Newer Glucose-Lowering Drugs and Risk of Parkinson's Disease.

Background: The association between newer classes of glucose-lowering drugs (GLDs) and the risk of Parkinson's disease (PD) remains unclear. Objective: The aim was to examine the effect of newer GLDs on the risk of PD through a meta-analysis of randomized outcome trials. Methods: The methods included randomized placebo-controlled outcome trials that reported PD events associated with three newer classes of GLDs (ie, dipeptidyl peptidase-4 inhibitors, glucagon-like peptide-1 receptor agonists, and sodium-glucose co-transporter-2 inhibitors) in participants with or without type 2 diabetes. The pooled odds ratio (OR) and 95% confidence interval (CI) were estimated using Peto's method. Results: The study included 24 trials involving 33 PD cases among 185,305 participants during a median follow-up of 2.2 years. Newer GLDs were significantly associated with a lower PD risk (OR: 0.50; 95% CI: 0.25-0.98) than placebo. Conclusion: Newer GLDs may possibly be associated with a decreased risk of PD; however, larger datasets are required to confirm or refute this notion.

Does in-vehicle automation help individuals with Parkinson's disease? A preliminary analysis.

Introduction: PD is a progressive neurodegenerative disorder that affects, according to the ICF, body systems (cognitive, visual, and motor), and functions (e.g., decreased executive functions, decreased visual acuity, impaired contrast sensitivity, decreased coordination)-all which impact driving performance, an instrumental activity of daily living in the domain of "Activity" and "Participation" according to the ICF. Although there is strong evidence of impaired driving performance in PD, few studies have explored the real-world benefits of in-vehicle automation technologies, such as in-vehicle information systems (IVIS) and advanced driver assistance systems (ADAS), for drivers with PD. These technologies hold potential to alleviate driving impairments, reduce errors, and improve overall performance, allowing individuals with PD to maintain their mobility and independence more safely and for longer periods. This preliminary study aimed to fill the gap in the literature by examining the impact of IVIS and ADAS on driving safety, as indicated by the number of driving errors made by people with PD in an on-road study. Methods: Forty-five adults with diagnosed PD drove a 2019 Toyota Camry equipped with IVIS and ADAS features (Toyota Safety Sense 2.0) on a route containing highway and suburban roads. Participants drove half of the route with the IVIS and ADAS systems activated and the other half with the systems deactivated. Results: The results suggest that systems that assume control of the driving task, such as adaptive cruise control, were most effective in reducing driving errors. Furthermore, individual differences in cognitive abilities, particularly memory, were significantly correlated with the total number of driving errors when the systems were deactivated, but no significant correlations were present when the systems were activated. Physical capability factors, such as rigidity and bradykinesia, were not significantly correlated with driving error. Discussion: Taken together, these results show that in-vehicle driver automation systems can benefit drivers with PD and diminish the impact of individual differences in driver cognitive ability.

Weight and survival after deep brain stimulation for Parkinson's disease.

BACKGROUND: Weight loss in Parkinson's disease (PD) is common and associated with increased mortality. The clinical significance of weight changes following deep brain stimulation (DBS) of the subthalamic nucleus (STN) and globus pallidus internus (GPi) is unclear. OBJECTIVES: To address (1) whether PD patients exhibit progressive weight loss, (2) whether staged DBS surgery is associated with weight changes, and (3) whether survival after DBS correlates with post-DBS weight. METHODS: This is a single-center, longitudinal, retrospective cohort study of 1625 PD patients. We examined trends in weight over time and the relationship between weight and years survival after DBS using regression and mixed model analyses. RESULTS: There was a decline in body weight predating motor symptom onset (n = 756, 0.70 ± 0.03% decrease per year, p < 0.001). Weight decline accelerated in the decade preceding death (n = 456, 2.18 ± 0.31% decrease per year, p < 0.001). DBS patients showed a weight increase of 2.0 ± 0.33% at 1 year following the first DBS lead implant (n = 455) and 2.68 ± 1.1% at 3 years if a contralateral DBS lead was placed (n = 249). The bilateral STN DBS group gained the most weight after surgery during 6 years of follow up (vs bilateral GPi, 3.03 ± 0.45% vs 1.89 ± 0.31%, p < 0.01). An analysis of the DBS cohort with date of death available (n = 72) revealed that post-DBS weight (0-12 months after the first or 0-36 months after the second surgery) was positively associated with survival (R2 = 0.14, p < 0.001). DISCUSSION: Though PD is associated with significant weight loss, DBS patients gained weight following surgery. Higher post-operative weight was associated with increased survival. These results should be replicated in other cohorts.

The Interface between Inflammatory Bowel Disease, Neuroinflammation, and Neurological Disorders.

Inflammatory Bowel Disease (IBD) is a complex, chronic inflammatory condition affecting the gastrointestinal tract. IBD has been associated with a variety of neurologic manifestations including peripheral nerve involvement, increased risk of thrombotic, demyelinating and events. Furthermore, an evolving association between IBD and neurodegenerative disorders has been recognized, and early data suggests an increased risk of these disorders in patients diagnosed with IBD. The relationship between intestinal inflammatory disease and neuroinflammation is complex, but the bidirectional interaction between the brain-gut-microbiome axis is likely to play an important role in the pathogenesis of these disorders. Identification of common mechanisms and pathways will be key to developing potential therapies. In this review, we discuss the evolving interface between IBD and neurological conditions, with a focus on clinical, mechanistic, and potentially therapeutic implications.

Utilization, surgical populations, centers, coverages, regional balance, and their influential factors of deep brain stimulation for Parkinson's disease: a large-scale multicenter cross-sectional study from 1997 to 2021.

BACKGROUND: Deep brain stimulation (DBS) is an emerging and effective therapy for Parkinson's disease (PD). However, little is known about its utilization, surgical populations, centers, coverages, regional balance, and influential factors. MATERIALS AND METHODS: This large-scale multicenter cross-sectional study was conducted using a national census involving 74 Chinese centers. National DBS populations and centers for PD were investigated in 1997-2021, and regional sociodemographic features, surgical populations, related resources, and insurance policies in 2020 were explored. RESULTS: Since the first DBS surgery in 1997, a total of 38 122 PD patients from 349 centers underwent DBS by 2021, which covered 1.118% (1.108-1.129) of patients and 0.954% (0.933-0.976) of centers. Significant upward trends in the annual surgical population and coverages were observed with rapid climbing rates, while the annual surgical centers and their coverage showed two growth peaks in 2002-2006 and 2010-2018, correlating with clinical approvals and new technologies. A total of 103 070 (51 165-154 975) PD patients [2.088% (1.351-2.825) coverage] and 603 (72-1134) centers [1.356% (1.126-1.586) coverage] are predicted to conduct DBS by 2030. The new remotely programmed DBS technology was recoded as the first application in 2015 and rapidly increased to 2771 (47.39%, 46.11-48.67) patients with 10 507 remote programming sessions annually in 2021. Provinces in the eastern and central regions had better economic status, more surgical patients, higher insurance affordability, and more related resources than those in the western and northeastern regions. Higher gross domestic product per capita ( ß =5.041, 3.324-6.758 and ß =0.008, 0.004-0.012; all P <0.001) and more functional neurosurgery doctors ( ß =3.596, 0.353-6.839; P =0.031 and ß =0.010, 0.002-0.017; P =0.013) positively influenced surgical populations and coverages, while higher insurance levels ( ß =128.888, 64.702-193.075; P <0.001) positively influenced surgical coverages. CONCLUSION: Although surgical populations, centers, and coverages of DBS for PD have rapidly improved and are predicted to show future increases, this is still insufficient to cover potential eligible patients. Regionally imbalanced health coverage should be given attention to promote coordinated development.

Therapies for Parkinson's disease and the gut microbiome: evidence for bidirectional connection.

The gut brain axis (GBA), a bidirectional communication pathway has often been linked to health and disease, and gut microbiota (GM), a key component of this pathway shown to be altered in Parkinson's disease (PD), are suggested to contribute to the pathogenesis of PD. There are few studies that report the impact of oral medication therapy on GM, however, there are even fewer studies that discuss the impact of other treatments such as device assisted therapies (DAT) including deep brain stimulation (DBS), levodopa-carbidopa intestinal gel infusion (LCIG) and photobiomodulation (PBM) and how these might impact GM. Here, we review the literature and summarize findings of the potential contributions of GM to the heterogenous clinical response to pharmaceutical therapies among individuals with PD. We also discuss the potential interactions between the GM and DATs such as DBS and LCIG and present evidence for alterations in GM in response to DATs. Given the complexity and highly individual nature of the GM of patients with PD and the potential influence that other external factors such as diet, lifestyle, medications, stage of the disease and other comorbidities, further investigations into the response of GM to therapies are worthy of future study in prospective, controlled trials as well as medication naïve individuals. Such detailed studies will help us further comprehend the relationship between GM in PD patients, and will help investigate the potential of targeting GM associated changes as a treatment avenue for PD.

Applications of Transcranial Magnetic Stimulation for Understanding and Treating Dystonia.

Transcranial magnetic stimulation (TMS)-based studies have led to an advanced understanding of the pathophysiology of dystonia. This narrative review summarizes the TMS data contributed to the literature so far. Many studies have shown that increased motor cortex excitability, excessive sensorimotor plasticity, and abnormal sensorimotor integration are the core pathophysiological substrates for dystonia. However, an increasing body of evidence supports a more widespread network dysfunction involving many other brain regions. Repetitive TMS pulses (rTMS) in dystonia have therapeutic potential as they can induce local and network-wide effects through modulation of excitability and plasticity. The bulk of rTMS studies has targeted the premotor cortex with some promising results in focal hand dystonia. Some studies have targeted the cerebellum for cervical dystonia and the anterior cingulate cortex for blepharospasm. We believe that therapeutic potential could be leveraged better when rTMS is implemented in conjunction with standard-of-care pharmacological treatments. However, due to several limitations in the studies conducted to date, including small samples, heterogeneous populations, variability in the target sites, and inconsistencies in the study design and control arm, it is hard to draw a definite conclusion. Further studies are warranted to determine optimal targets and protocols yielding the most beneficial outcomes that will translate into meaningful clinical changes.

Brain Recording Analysis and Visualization Online (BRAVO): An open-source visualization tool for deep brain stimulation data.

BACKGROUND: Deep brain stimulation (DBS) devices with neural recording capabilities are commercially available and may potentially improve clinical care and advance research. However, tools, to visualize neural recording data have been limited. These tools in general, require custom-made software for processing and analysis. The development of new tools will be critical for clinicians and researchers to fully leverage the latest device capabilities. OBJECTIVE: There is an urgent need for a user-friendly tool for in-depth visualization and analysis of brain signals and of DBS data. METHODS AND RESULTS: The Brain Recording Analysis and Visualization Online (BRAVO) platform was developed to easily import, visualize, and analyze brain signals. This Python-based web interface has been designed and implemented on a Linux server. The tool processes the session files from DBS programming generated by a clinical 'programming' tablet. The platform is capable of parsing and organizing neural recordings for longitudinal analysis. We present the platform and cases exemplifying its application and use. CONCLUSION: The BRAVO platform is an accessible easy-to-use, open-source web interface for clinicians and researchers to apply for analysis of longitudinal neural recording data. The tool can be used for both clinical and research applications.

Interactive mobile application for Parkinson's disease deep brain stimulation (MAP DBS): An open-label, multicenter, randomized, controlled clinical trial.

INTRODUCTION: Deep brain stimulation (DBS) is an effective treatment for Parkinson's disease (PD), but its efficacy is tied to DBS programming, which is often time consuming and burdensome for patients, caregivers, and clinicians. Our aim is to test whether the Mobile Application for PD DBS (MAP DBS), a clinical decision support system, can improve programming. METHODS: We conducted an open-label, 1:1 randomized, controlled, multicenter clinical trial comparing six months of SOC standard of care (SOC) to six months of MAP DBS-aided programming. We enrolled patients between 30 and 80 years old who received DBS to treat idiopathic PD at six expert centers across the United States. The primary outcome was time spent DBS programming and secondary outcomes measured changes in motor symptoms, caregiver strain and medication requirements. RESULTS: We found a significant reduction in initial visit time (SOC: 43.8 ± 28.9 min n = 37, MAP DBS: 27.4 ± 13.0 min n = 35, p = 0.001). We did not find a significant difference in total programming time between the groups over the 6-month study duration. MAP DBS-aided patients experienced a significantly larger reduction in UPDRS III on-medication scores (-7.0 ± 7.9) compared to SOC (-2.7 ± 6.9, p = 0.01) at six months. CONCLUSION: MAP DBS was well tolerated and improves key aspects of DBS programming time and clinical efficacy.

COVID-19 and Integrated Multidisciplinary Care Model in Parkinson's Disease: Literature Review & Future Perspectives.

Clinical diversity and multi-systemic manifestations of Parkinson's disease (PD) necessitate the involvement of several healthcare professionals from different disciplines for optimal care. Clinical guidelines recommend that all persons with PD should have access to a broad range of medical and allied health professionals to implement an efficient and effective multidisciplinary care model. This is well supported by growing evidence showing the benefits of multidisciplinary interventions on improving quality of life and disease progression in PD. However, a "multidisciplinary" approach requires gathering healthcare professionals from different disciplines into an integrative platform for collaborative teamwork. With the Coronavirus Disease 2019 (COVID-19) pandemic, implementation of such a multidisciplinary care model has become increasingly challenging due to social distancing mandates, isolation and quarantine, clinics cancellation, among others. To address this problem, multidisciplinary teams are developing innovate virtual platforms to maintain care of people with PD. In the present review, we cover aspects on how SARS-CoV-2 has affected people with PD, their caregivers, and care team members. We also review current evidence on the importance of maintaining patient-centered care in the era of social distancing, and how can we utilize telehealth and innovative virtual platforms for multidisciplinary care in PD.

Safety of deep brain stimulation in pregnancy: A comprehensive review.

Introduction: Deep brain stimulation (DBS) is increasingly used to treat the symptoms of various neurologic and psychiatric conditions. People can undergo the procedure during reproductive years but the safety of DBS in pregnancy remains relatively unknown given the paucity of published cases. We thus conducted a review of the literature to determine the state of current knowledge about DBS in pregnancy and to determine how eligibility criteria are approached in clinical trials with respect to pregnancy and the potential for pregnancy. Methods: A literature review was conducted in EMBASE to identify articles involving DBS and pregnancy. Two reviewers independently analyzed the articles to confirm inclusion. Data extracted for analysis included conditions treated, complications at all stages of pregnancy, neonatal/pediatric outcomes, and DBS target. A second search was then conducted using www.clinicaltrials.gov. The same two reviewers then assessed whether each trial excluded pregnant individuals, lactating individuals, or persons of childbearing age planning to conceive. Also assessed was whether contraception had to be deemed adequate prior to enrollment. Results: The literature search returned 681 articles. Following independent analysis and agreement of two reviewers, 8 pregnancy related DBS articles were included for analysis. These articles described 27 subjects, 29 pregnancies (2 with subsequent pregnancies), and 31 infants (2 twin pregnancies). There was 1 preterm birth at 35 weeks, and 3 patients who experienced discomfort from the DBS battery (i.e., impulse generator) placement site. All 27 patients had a DBS device implanted before they became pregnant, which remained in use throughout their pregnancy. There was exclusion of pregnant individuals from 68% of 135 interventional trials involving DBS. Approximately 44% of these trials excluded persons of childbearing age not on "adequate contraception" or wishing to conceive in the coming years. Finally, 22% excluded breastfeeding persons. Conclusion: The data from 29 pregnancies receiving DBS treatment during pregnancy was not associated with unexpected pregnancy or post-partum complication patterns. Many clinical trials have excluded pregnant individuals. Documentation of outcomes in larger numbers of pregnancies will help clarify the safety profile and will help guide study designs that will safely include pregnant patients.