Surgical Treatment of Parkinson Disease

Ultrasound robotics for precision therapy

In recent years, the application of microrobots in precision therapy has gained significant attention. The small size and maneuverability of these micromachines enable them to potentially access regions that are difficult to reach using traditional methods; thus, reducing off-target toxicities and maximizing treatment effectiveness. Specifically, acoustic actuation has emerged as a promising method to exert control. By harnessing the power of acoustic energy, these small machines potentially navigate the body, assemble at the desired sites, and deliver therapies with enhanced precision and effectiveness. Amidst the enthusiasm surrounding these miniature agents, their translation to clinical environments has proven difficult. The primary objectives of this review are threefold: firstly, to offer an overview of the fundamental acoustic principles employed in the field of microrobots; secondly, to assess their current applications in medical therapies, encompassing tissue targeting, drug delivery or even cell infiltration; and lastly, to delve into the continuous efforts aimed at integrating acoustic microrobots into in vivo applications.

Magnetic resonance imaging image analysis of the therapeutic effect and neuroprotective effect of deep brain stimulation in Parkinson's disease based on a deep learning algorithm

In order to study the therapeutic neuroprotective effect of deep brain stimulation (DBS) in Parkinson's disease (PD), based on the deep learning algorithm, this study combines with magnetic resonance imaging (MRI) image analysis technology to study the clinical efficacy of DBS in the surgical treatment of PD and the neuroprotective and neurological recovery effects after surgery. Establish a deep learning algorithm model based on MRI image analysis technology, comparison of UPDRS motor status assessment and the improvement of daily life ability before and after DBS surgery, evaluate the accuracy rate and the detection speed of the model. The models constructed in this study have an accuracy rate of more than 90% in the PD detection test, and the detection speed of the algorithm model under the condition of big data is between 60 and 200 ms. DBS significantly improve a series of clinical symptoms in patients with PD. The deep learning algorithm model based on MRI image analysis technology in this paper has a certain effect. DBS operation can improve the symptoms of PD, and has the effect of neuroprotection and neurological recovery.

Multifunctional role of natural products for the treatment of Parkinson's disease: At a glance

Natural substances originating from plants have long been used to treat neurodegenerative disorders (NDs). Parkinson's disease (PD) is a ND. The deterioration and subsequent cognitive impairments of the midbrain nigral dopaminergic neurons distinguish by this characteristic. Various pathogenic mechanisms and critical components have been reported, despite the fact that the origin is unknown, such as protein aggregation, iron buildup, mitochondrial dysfunction, neuroinflammation and oxidative stress. Anti-Parkinson drugs like dopamine (DA) agonists, levodopa, carbidopa, monoamine oxidase type B inhibitors and anticholinergics are used to replace DA in the current treatment model. Surgery is advised in cases where drug therapy is ineffective. Unfortunately, the current conventional treatments for PD have a number of harmful side effects and are expensive. As a result, new therapeutic strategies that control the mechanisms that contribute to neuronal death and dysfunction must be addressed. Natural resources have long been a useful source of possible treatments. PD can be treated with a variety of natural therapies made from medicinal herbs, fruits, and vegetables. In addition to their well-known anti-oxidative and anti-inflammatory capabilities, these natural products also play inhibitory roles in iron buildup, protein misfolding, the maintenance of proteasomal breakdown, mitochondrial homeostasis, and other neuroprotective processes. The goal of this research is to systematically characterize the currently available medications for Parkinson's and their therapeutic effects, which target diverse pathways. Overall, this analysis looks at the kinds of natural things that could be used in the future to treat PD in new ways or as supplements to existing treatments. We looked at the medicinal plants that can be used to treat PD. The use of natural remedies, especially those derived from plants, to treat PD has been on the rise. This article examines the fundamental characteristics of medicinal plants and the bioactive substances found in them that may be utilized to treat PD.

Deep brain stimulation and stereotactic-assisted brain graft injection targeting fronto-striatal circuits for Huntington's disease: an update

INTRODUCTION

Huntington's Disease as progressive neurological disorders associated with motor, behavioral, and cognitive impairment poses a therapeutic challenge in case of limited responsiveness to established therapeutics. Pallidal deep brain stimulation and neurorestorative strategies (brain grafts) scoping to modulate fronto-striatal circuits have gained increased recognition for the treatment of refractory Huntington's disease (HD).

AREAS COVERED

A review (2000-2022) was performed in PubMed, Embase, and Cochrane Library covering clinical trials conceptualized to determine the efficacy and safety of invasive, stereotactic-guided deep-brain stimulation and intracranial brain-graft injection targeting the globus pallidus and adjunct structures (striatum).

EXPERT OPINION

Stereotactic brain-grafting strategies were performed in few HD patients with inconsistent findings and mild-to-moderate clinical responsiveness with a recently published large, randomized-controlled trial (NCT00190450) yielding negative results. We identified 19 in-human DBS trials (uncontrolled) targeting the globus pallidus internus/externus along with randomized-controlled trial pending report (NCT02535884). We did not detect any significant changes in the UHDRS total score after restorative injections, while in contrast, the use of deep-brain stimulation resulted in a significant reduction of chorea. GPi-DBS should be considered in cases where selective chorea is present. However, both invasive therapies remain experimental and are not ready for the implementation in clinical use.

Deep brain stimulation in patients on chronic antiplatelet or anticoagulation treatment

BACKGROUND

In the aging society, many patients with movement disorders, pain syndromes, or psychiatric disorders who are candidates for deep brain stimulation (DBS) surgery suffer also from cardiovascular co-morbidities that require chronic antiplatelet or anticoagulation treatment. Because of a presumed increased risk of intracranial hemorrhage during or after surgery and limited knowledge about perioperative management, chronic antiplatelet or anticoagulation treatment often has been considered a relative contraindication for DBS. Here, we evaluate whether or not there is an increased risk for intracranial hemorrhage or thromboembolic complications in patients on chronic treatment (paused for surgery or bridged with subcutaneous heparin) as compared to those without.

METHODS

Out of a series of 465 patients undergoing functional stereotactic neurosurgery, 34 patients were identified who were on chronic treatment before and after receiving DBS. In patients with antiplatelet treatment, medication was stopped in the perioperative period. In patients with vitamin K antagonists or novel oral anticoagulants (NOACs), heparin was used for bridging. All patients had postoperative stereotactic CT scans, and were followed up for 1 year after surgery.

RESULTS

In patients on chronic antiplatelet or anticoagulation treatment, intracranial hemorrhage occurred in 2/34 (5.9%) DBS surgeries, whereas the rate of intracranial hemorrhage was 15/431 (3.5%) in those without, which was statistically not significant. Implantable pulse generator pocket hematomas were seen in 2/34 (5.9%) surgeries in patients on chronic treatment and in 4/426 (0.9%) without. There were only 2 instances of thromboembolic complications which both occurred in patients without chronic treatment. There were no hemorrhagic complications during follow-up for 1 year.

CONCLUSIONS

DBS surgery in patients on chronic antiplatelet or anticoagulation treatment is feasible. Also, there was no increased risk of hemorrhage in the first year of follow-up after DBS surgery. Appropriate patient selection and standardized perioperative management are necessary to reduce the risk of intracranial hemorrhage and thromboembolic complications.

Increasing Serotonin to Reduce Parkinsonian Tremor

While current dopamine-based drugs seem to be effective for most Parkinson's disease (PD) motor dysfunctions, they produce variable responsiveness for resting tremor. This lack of consistency could be explained by considering recent evidence suggesting that PD resting tremor can be divided into different partially overlapping phenotypes based on the dopamine response. These phenotypes may be associated with different pathophysiological mechanisms produced by a cortical-subcortical network involving even non-dopaminergic areas traditionally not directly related to PD. In this study, we propose a bio-constrained computational model to study the neural mechanisms underlying a possible type of PD tremor: the one mainly involving the serotoninergic system. The simulations run with the model demonstrate that a physiological serotonin increase can partially recover dopamine levels at the early stages of the disease before the manifestation of overt tremor. This result suggests that monitoring serotonin concentration changes could be critical for early diagnosis. The simulations also show the effectiveness of a new pharmacological treatment for tremor that acts on serotonin to recover dopamine levels. This latter result has been validated by reproducing existing data collected with human patients.

An Embedded Multi-Core Real-Time Simulation Platform of Basal Ganglia for Deep Brain Stimulation

Closed-loop deep brain stimulation (DBS) paradigm is gaining tremendous favor due to its potential capability of further and more efficient improvements in neurological diseases. Preclinical validation of closed-loop controller is quite necessary in order to minimize injury risks of clinical trials to patients, which can greatly benefit from real-time computational models and thus potentially reduce research and development costs and time. Here we developed an embedded multi-core real-time simulation platform (EMC-RTP) for a biological-faithful computational network model of basal ganglia (BG). The single neuron model is implemented in a highly real-time manner using a reasonable simplification. A modular mapping architecture with hierarchical routing organization was constructed to mimic the pathological neural activities of BG observed in parkinsonian conditions. A closed-loop simulation testbed for DBS validation was then set up using a host computer as the DBS controller. The availability of EMC-RTP and the testbed system was validated by comparing the performance of open-loop and proportional-integral (PI) controllers. Our experimental results showed that the proposed EMC-RTP reproduces abnormal beta bursts of BG in parkinsonian conditions while meets requirements of both real-time and computational accuracy as well. Closed-loop DBS experiments using the EMC-RTP suggested that the platform could perform reasonable output under different kinds of DBS strategies, indicating the usability of the platform.

Surgical Management of Parkinson's Disease in the Elderly

Background

Deep Brain Stimulation (DBS) is an increasingly popular therapy for Parkinson's Disease (PD). Despite the experience gained over time with DBS of either the subthalamus or the globus pallidus pars interna, there is still no consensus regarding the age limit for DBS indication.

Objectives

This narrative review of the literature discusses the issues of age and DBS, emphasizing the critical need for good quality evidence to support the surgical management of elderly patients with PD.

Methods

We searched PubMed using the terms Parkinson's Disease; Parkinson's Disease therapy; deep brain stimulation; antiparkinsonian agents therapeutic use; age factors; aged; aged, 80 and over; middle aged; treatment outcome; and risk assessments.

Results

We identified several limitations of the available evidence, such as under-representation of older patients in DBS studies, small sample sizes in studies with older participants, heterogeneity of outcomes, and conflicting results.

Conclusions

Despite preliminary suggestions that age might affect the outcomes of DBS, the evidence to support the hypothesis of age as an independent predictor of DBS outcomes is limited and results are controversial. Ultimately, finding an age-independent biomarker predicting DBS outcome is the final goal to expand this powerful treatment to all patients age in an effective and safe manner.

Creation of a gene expression classifier for predicting Parkinson's disease rate of progression

Parkinson's disease (PD) etiology is heterogeneous, genetic, and multi-factorial, resulting in a varied disease from a mild slow progression to a more severe rapid progression. Prognostic information on the nature of the patient's disease at diagnosis aids the physician in counseling patients on treatment options and life planning. In a cohort of PD patients from the PPMI study, the relative gene expression levels of SKP1A, UBE2K, ALDH1A1, PSMC4, HSPA8 and LAMB2 were measured in baseline blood samples by real-time quantitative PCR. At baseline PD patients were up to 2 years from diagnosis, H&Y scale ≤ 2 and PD treatment naïve. PD-Prediction algorithm comprised of ALDH1A1, LAMB2, UBE2K, SKP1A and age was created by logistic regression for predicting progression to ≤ 70% Modified Schwab and England Activities of Daily Living (S&E-ADL). In relation to patients negative for PD-Prediction (n = 180), patients positive (n = 30) for Cutoff-1 (at 82% specificity, 80.0% sensitivity) had positive hazard ratio (HR+) of 10.6 (95% CI, 2.2-50.1), and positive (n = 23) for Cutoff-2 (at 93% specificity, 47% sensitivity) had HR+ of 17.1 (95% CI, 3.2-89.9) to progress to ≤ 70% S&E-ADL within 3 years (P value < 0.0001). Likewise, patients positive for PD-Prediction Cutoff-1 (n = 49) had HR+ 4.3 (95% CI, 1.6-11.6) for faster time to H&Y 3 in relation to patients negative (n = 170) for PD-Prediction (P value = 0.0002). Our findings show an algorithm that seems to predict fast PD progression and may potentially be used as a tool to assist the physician in choosing an optimal treatment plan, improving the patient's quality of life and overall health outcome.