Closed-Loop Adaptive Deep Brain Stimulation in Parkinson's Disease: Procedures to Achieve It and Future Perspectives

Revisiting the role of computational neuroimaging in the era of integrative neuroscience

Computational models have become integral to human neuroimaging research, providing both mechanistic insights and predictive tools for human cognition and behavior. However, concerns persist regarding the ecological validity of lab-based neuroimaging studies and whether their spatiotemporal resolution is not sufficient for capturing neural dynamics. This review aims to re-examine the utility of computational neuroimaging, particularly in light of the growing prominence of alternative neuroscientific methods and the growing emphasis on more naturalistic behaviors and paradigms. Specifically, we will explore how computational modeling can both enhance the analysis of high-dimensional imaging datasets and, conversely, how neuroimaging, in conjunction with other data modalities, can inform computational models through the lens of neurobiological plausibility. Collectively, this evidence suggests that neuroimaging remains critical for human neuroscience research, and when enhanced by computational models, imaging can serve an important role in bridging levels of analysis and understanding. We conclude by proposing key directions for future research, emphasizing the development of standardized paradigms and the integrative use of computational modeling across neuroimaging techniques.

Comparison of the Burdens and Attitudes Between Standard and Web-Based Remote Programming for Deep Brain Stimulation in Parkinson Disease: Survey Study

Background

Remote programming enables physicians to adjust implantable pulse generators over the internet for patients with Parkinson disease who have undergone deep brain stimulation (DBS) surgery. Despite these technological advances, the demand for and attitudes toward remote programming compared with standard programming among patients with Parkinson disease are still not well understood.

Objective

This study aims to investigate the preferences and perceptions associated with these 2 programming methods among patients with Parkinson disease through a web-based survey.

Methods

A web-based survey was administered to 463 patients with Parkinson disease who have undergone DBS surgery. The survey aimed to assess the burdens associated with postoperative programming and to compare patients' attitudes toward the 2 different programming methods.

Results

A total of 225 patients completed the survey, all of whom had undergone standard programming, while 132 patients had also experienced remote programming. Among those who received standard programming, 191 (85%) patients required the support of more than 1 caregiver, 129 (58%) patients experienced over 2 days of lost work time, 98 (42%) patients incurred expenses ranging from US $42 to US $146, and 14 (6%) patients spent over US $421. Of the 132 patients who had used remote programming, 81 (62%) patients indicated a preference for remote programming in the future. However, challenges with remote programming persisted, including difficulties in obtaining official prescriptions, a lack of medical insurance coverage, and limited medical resources.

Conclusions

Postoperative programming of DBS imposes significant burdens on patients and their caregivers during standard programming sessions-burdens that could be mitigated through remote programming. While patient satisfaction with remote programming is high, it is imperative for clinicians to develop personalized programming strategies tailored to the needs of different patients.

Deep brain stimulation for Tourette's syndrome

OBJECTIVES

This is a protocol for a Cochrane Review (intervention). The objectives are as follows: To assess the efficacy and harm of deep brain stimulation for motor symptoms, with psychiatric and behavioural comorbidities, either individually or in combination, in adults and adolescents with Tourette's syndrome compared to placebo, sham intervention, or the best available behavioural and pharmacological treatment.

Comparison of children and adults in deep brain stimulation for Tourette Syndrome: a large-scale multicenter study of 102 cases with long-term follow-up

BACKGROUND

Deep brain stimulation (DBS) is a promising therapy for refractory Gilles de la Tourette syndrome (GTS). However, its long-term efficacy, safety, and recommended surgical age remain controversial, requiring evidence to compare different age categories.

METHODS

This retrospective cohort study recruited 102 GTS patients who underwent DBS between October 2006 and April 2022 at two national centers. Patients were divided into two age categories: children (aged < 18 years; n = 34) and adults (aged ≥ 18 years; n = 68). The longitudinal outcomes as tic symptoms were assessed by the YGTSS, and the YBOCS, BDI, and GTS-QOL were evaluated for symptoms of obsessive-compulsive disorder (OCD), depression, and quality of life, respectively.

RESULTS

Overall, these included patients who finished a median 60-month follow-up, with no significant difference between children and adults (p = 0.44). Overall, the YGTSS total score showed significant postoperative improvements and further improved with time (improved 45.2%, 51.6%, 55.5%, 55.6%, 57.8%, 61.4% after 6, 12, 24, 36, 48, and ≥ 60 months of follow-up compared to baseline, respectively) in all included patients (all p < 0.05). A significantly higher improvement was revealed in children than adults at ≥ 60 months of follow-up in the YGTSS scores (70.1% vs 55.9%, p = 0.043), and the time to achieve 60% improvement was significantly shorter in the children group (median 6 months vs 12 months, p = 0.013). At the last follow-up, the mean improvements were 45.4%, 48.9%, and 55.9% and 40.3%, 45.4%, and 47.9% in YBOCS, BDI, and GTS-QOL scores for children and adults, respectively, which all significantly improved compared to baseline (all p < 0.05) but without significant differences between these two groups (all p > 0.05), and the children group received significantly higher improvement in GTS-QOL scores than adults (55.9% vs. 47.9%, p = 0.049).

CONCLUSIONS

DBS showed acceptable long-term efficacy and safety for both children and adults with GTS. Surgeries performed for patients younger than 18 years seemed to show acceptable long-term efficacy and safety and were not associated with increased risks of loss of benefit compared to patients older than 18 at the time of surgery. However, surgeries for children should also be performed cautiously to ensure their refractoriness and safety.

Trends and hotspots in non-motor symptoms of Parkinson's disease: a 10-year bibliometric analysis

Non-motor symptoms are prevalent among individuals with Parkinson's disease (PD) and seriously affect patient quality of life, even more so than motor symptoms. In the past decade, an increasing number of studies have investigated non-motor symptoms in PD. The present study aimed to comprehensively analyze the global literature, trends, and hotspots of research investigating non-motor symptoms in PD through bibliometric methods. Studies addressing non-motor symptoms in the Web of Science Core Collection (WoSCC), published between January 2013 and December 2022, were retrieved. Bibliometric methods, including the R package "Bibliometrix," VOS viewer, and CiteSpace software, were used to investigate and visualize parameters, including yearly publications, country/region, institution, and authors, to collate and quantify information. Analysis of keywords and co-cited references explored trends and hotspots. There was a significant increase in the number of publications addressing the non-motor symptoms of PD, with a total of 3,521 articles retrieved. The United States was ranked first in terms of publications (n = 763) and citations (n = 11,269), maintaining its leadership position among all countries. King's College London (United Kingdom) was the most active institution among all publications (n = 133) and K Ray Chaudhuri was the author with the most publications (n = 131). Parkinsonism & Related Disorders published the most articles, while Movement Disorders was the most cited journal. Reference explosions have shown that early diagnosis, biomarkers, novel magnetic resonance imaging techniques, and deep brain stimulation have become research "hotspots" in recent years. Keyword clustering revealed that alpha-synuclein is the largest cluster for PD. The keyword heatmap revealed that non-motor symptoms appeared most frequently (n = 1,104), followed by quality of life (n = 502), dementia (n = 403), and depression (n = 397). Results of the present study provide an objective, comprehensive, and systematic analysis of these publications, and identifies trends and "hot" developments in this field of research. This work will inform investigators worldwide to help them conduct further research and develop new therapies.

Computational Neurosurgery in Deep Brain Stimulation

Computational methods and technologies are critical for neurosurgery in general and in deep brain stimulation (DBS) in particular. They increasingly inform every aspect of clinical DBS therapy, from presurgical planning and hardware implantation to postoperative adjustment of stimulation parameters. Computational methods also occupy a prominent position within the DBS research sphere, where they facilitate efforts to better understand DBS' underlying mechanisms and optimize and individualize its delivery. This chapter provides a high-level overview of the various computational tools and methods that have been applied to DBS. First, we discuss the invaluable contribution of computational neuroimaging (primarily magnetic resonance imaging) to DBS, targeting and the role of postoperative methods of image analysis-specifically, electrode localization, volume of activated tissue modeling, and sweet-spot mapping-in precisely localizing DBS' targets in the brain and discerning optimal treatment loci. We then address the growing field of connectomics, which leverages specific magnetic resonance imaging (MRI) sequences and post-acquisition processing algorithms to explore how DBS operates at the level of brain-wide networks. Next, the search for electrophysiological and imaging-based biomarkers of optimal DBS therapy is explored. We lastly touch on the incipient field of spatial characterization analysis and discuss the ongoing development of adaptive, closed-loop DBS systems.

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 ( β =5.041, 3.324-6.758 and β =0.008, 0.004-0.012; all P <0.001) and more functional neurosurgery doctors ( β =3.596, 0.353-6.839; P =0.031 and β =0.010, 0.002-0.017; P =0.013) positively influenced surgical populations and coverages, while higher insurance levels ( β =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.

EEG-based biomarkers for optimizing deep brain stimulation contact configuration in Parkinson's disease

Objective

Subthalamic deep brain stimulation (STN-DBS) is a neurosurgical therapy to treat Parkinson's disease (PD). Optimal therapeutic outcomes are not achieved in all patients due to increased DBS technological complexity; programming time constraints; and delayed clinical response of some symptoms. To streamline the programming process, biomarkers could be used to accurately predict the most effective stimulation configuration. Therefore, we investigated if DBS-evoked potentials (EPs) combined with imaging to perform prediction analyses could predict the best contact configuration.

Methods

In 10 patients, EPs were recorded in response to stimulation at 10 Hz for 50 s on each DBS-contact. In two patients, we recorded from both hemispheres, resulting in recordings from a total of 12 hemispheres. A monopolar review was performed by stimulating on each contact and measuring the therapeutic window. CT and MRI data were collected. Prediction models were created to assess how well the EPs and imaging could predict the best contact configuration.

Results

EPs at 3 ms and at 10 ms were recorded. The prediction models showed that EPs can be combined with imaging data to predict the best contact configuration and hence, significantly outperformed random contact selection during a monopolar review.

Conclusion

EPs can predict the best contact configuration. Ultimately, these prediction tools could be implemented into daily practice to ease the DBS programming of PD patients.

Cerebellar and cerebral white matter changes in Parkinson's disease with resting tremor

PURPOSE

Cerebellum modulates the amplitude of resting tremor in Parkinson's disease (PD) via cerebello-thalamo-cortical (CTC) circuit. Tremor-related white matter alterations have been identified in PD patients by pathological studies, but in vivo evidence is limited; the influence of such cerebellar white matter alterations on tremor-related brain network, including CTC circuit, is also unclear. In this study, we investigated the cerebral and cerebellar white matter alterations in PD patients with resting tremor using diffusion tensor imaging (DTI).

METHODS

In this study, 30 PD patients with resting tremor (PDWR), 26 PD patients without resting tremor (PDNR), and 30 healthy controls (HCs) from the Parkinson's Progression Markers Initiative (PPMI) cohort were included. Tract-based spatial statistics (TBSS) and region of interest-based analyses were conducted to determine white matter difference. Correlation analysis between DTI measures and clinical characteristics was also performed.

RESULTS

In the whole brain, TBSS and region of interest-based analyses identified higher fractional anisotropy (FA) value, lower mean diffusivity (MD) value, and lower radial diffusivity (RD) in multiple fibers. In the cerebellum, TBSS analysis revealed significantly higher FA value, decreased RD value as well as MD value in multiple cerebellar tracts including the inferior cerebellar peduncle (ICP) and middle cerebellar peduncle (MCP) when comparing the PDWR with HC, and higher FA value in the MCP when compared with PDNR.

CONCLUSION

We identified better white matter integrity in the cerebrum and cerebellum in PDWR indicating a potential association between the cerebral and cerebellar white matter and resting tremor in PD.