An International Survey of Deep Brain Stimulation Utilization in Asia and Oceania: The DBS Think Tank East.

Introduction: To evaluate the current utilization and challenges in fully implementing the use of deep brain stimulation (DBS) treatment in Asia and Oceania. Methods: We conducted a medical literature search to identify DBS research performed by investigators with a primary affiliation in Asian and Oceania countries between March 1, 2013, and March 1, 2019, followed by an international survey-based study. Additionally, we obtained added information regarding the DBS challenges and opportunities from the technology/industry perspective within China and Japan. We also described the current situation of DBS in India. Results: Most publications (390/494; 78.95%) in the English language originated from East Asia. In West Asia, Turkey, Israel, and Iran accounted for most DBS publications. We found no publications from the remaining 35 Asian countries. Lack of community referrals to tertiary centers was identified as the most common limitation for the widespread use of DBS in Asia (68.97%). In China, despite an increasing number of centers performing DBS surgeries, most of them accomplished less than 10 cases per year. In contrast, the number of DBS cases in Japan has been decreasing. Centers offering DBS surgeries as well as corresponding fellowship training in India are limited. Conclusion: Appropriate referrals, access, infrastructure, and the presence of full multidisciplinary DBS teams are common limitations of DBS in Asia. Most centers in China, Japan, and India performed less than 10 cases per year and a future study is expected to address the impact on quality in centers performing such few cases

Anatomical categorization of isolated non-focal dystonia: novel and existing patterns using a data-driven approach

According to expert consensus, dystonia can be classified as focal, segmental, multifocal, and generalized, based on the affected body distribution. To provide an empirical and data-driven approach to categorizing these distributions, we used a data-driven clustering approach to compare frequency and co-occurrence rates of non-focal dystonia in pre-defined body regions using the Dystonia Coalition (DC) dataset. We analyzed 1,618 participants with isolated non-focal dystonia from the DC database. The analytic approach included construction of frequency tables, variable-wise analysis using hierarchical clustering and independent component analysis (ICA), and case-wise consensus hierarchical clustering to describe associations and clusters for dystonia affecting any combination of eighteen pre-defined body regions. Variable-wise hierarchical clustering demonstrated closest relationships between bilateral upper legs (distance = 0.40), upper and lower face (distance = 0.45), bilateral hands (distance = 0.53), and bilateral feet (distance = 0.53). ICA demonstrated clear grouping for the a) bilateral hands, b) neck, and c) upper and lower face. Case-wise consensus hierarchical clustering at k = 9 identified 3 major clusters. Major clusters consisted primarily of a) cervical dystonia with nearby regions, b) bilateral hand dystonia, and c) cranial dystonia. Our data-driven approach in a large dataset of isolated non-focal dystonia reinforces common segmental patterns in cranial and cervical regions. We observed unexpectedly strong associations between bilateral upper or lower limbs, which suggests that symmetric multifocal patterns may represent a previously underrecognized dystonia subtype

Tremor in cervical dystonia

Background: Cervical dystonia (CD) is the most common form of focal dystonia encountered in the clinic. Approximately one-third of CD patients have co-existing tremor in the head and hands. Assessment of tremor as regular or irregular in context of its oscillation trajectory, frequency, and amplitude is a major clinical challenge and can confound the diagnosis of CD. The misdiagnosis may lead to therapeutic failures, poor quality of life, and poor utilization of medical and financial resources.Methods: We analyzed the largest cohort of CD patients (n = 3117) available to date, collected from 37 movement disorder centers in North America, Europe, and Asia. We used machine learning to determine what clinical features from clinician reports predicted the presence of tremor as well as its regular or irregular appearance.Results: Out of 3,117 CD patients, 1,367 had neck tremor. The neck tremor was interpreted as irregular in 1,022, regular in 345, and mixed (both irregular and regular) in 442. A feature importance analysis determined that greater severity of CD, longer disease duration, and older age, in descending order, predicted the presence of neck tremor. The probability of neck tremor was reduced if the dystonia affected other body parts in addition to the neck. We also found a significantly heightened risk for developing neck tremor in women. An additional feature importance analysis indicated that increased severity of dystonia affecting other body parts, severity of CD, and prolonged disease duration was associated with a lower likelihood of regular neck tremor while increased age predicted a higher likelihood.Conclusion: Machine learning recognized the most relevant clinical features that can predict concurrent neck tremor and its irregularity in a large multi-center dystonia cohort. These results may facilitate a more accurate description of neck tremor and improved care path in CD

Proceedings of the Eighth Annual Deep Brain Stimulation Think Tank: Advances in Optogenetics, Ethical Issues Affecting DBS Research, Neuromodulatory Approaches for Depression, Adaptive Neurostimulation, and Emerging DBS Technologies

We estimate that 208,000 deep brain stimulation (DBS) devices have been implanted to address neurological and neuropsychiatric disorders worldwide. DBS Think Tank presenters pooled data and determined that DBS expanded in its scope and has been applied to multiple brain disorders in an effort to modulate neural circuitry. The DBS Think Tank was founded in 2012 providing a space where clinicians, engineers, researchers from industry and academia discuss current and emerging DBS technologies and logistical and ethical issues facing the field. The emphasis is on cutting edge research and collaboration aimed to advance the DBS field. The Eighth Annual DBS Think Tank was held virtually on September 1 and 2, 2020 (Zoom Video Communications) due to restrictions related to the COVID-19 pandemic. The meeting focused on advances in: (1) optogenetics as a tool for comprehending neurobiology of diseases and on optogenetically-inspired DBS, (2) cutting edge of emerging DBS technologies, (3) ethical issues affecting DBS research and access to care, (4) neuromodulatory approaches for depression, (5) advancing novel hardware, software and imaging methodologies, (6) use of neurophysiological signals in adaptive neurostimulation, and (7) use of more advanced technologies to improve DBS clinical outcomes. There were 178 attendees who participated in a DBS Think Tank survey, which revealed the expansion of DBS into several indications such as obesity, post-traumatic stress disorder, addiction and Alzheimer’s disease. This proceedings summarizes the advances discussed at the Eighth Annual DBS Think Tank

Cognitive Impact of Deep Brain Stimulation on Parkinson’s Disease Patients

Subthalamic nucleus (STN) or globus pallidus interna (GPi) deep brain stimulation (DBS) is considered a robust therapeutic tool in the treatment of Parkinson’s disease (PD) patients, although it has been reported to potentially cause cognitive decline in some cases. We here provide an in-depth and critical review of the current literature regarding cognition after DBS in PD, summarizing the available data on the impact of STN and GPi DBS as monotherapies and also comparative data across these two therapies on 7 cognitive domains. We provide evidence that, in appropriately screened PD patients, worsening of one or more cognitive functions is rare and subtle after DBS, without negative impact on quality of life, and that there is very little data supporting that STN DBS has a worse cognitive outcome than GPi DBS