Evaluation of a programming algorithm for deep brain stimulation in dystonia used in a double-blind, sham-controlled multicenter study

GPi-DBS-induced brain metabolic activation in cervical dystonia

BACKGROUND

Deep brain stimulation (DBS) of the globus pallidus interna (GPi) is a highly efficacious treatment for cervical dystonia, but its mechanism of action is not fully understood. Here, we investigate the brain metabolic effects of GPi-DBS in cervical dystonia.

METHODS

Eleven patients with GPi-DBS underwent brain 18F-fluorodeoxyglucose positron emission tomography imaging during stimulation on and off. Changes in regional brain glucose metabolism were investigated at the active contact location and across the whole brain. Changes in motor symptom severity were quantified using the Toronto Western Spasmodic Torticollis Rating Scale (TWSTRS), executive function using trail making test (TMT) and parkinsonism using Unified Parkinson's Disease Rating Scale (UPDRS).

RESULTS

The mean (SD) best therapeutic response to DBS during the treatment was 81 (22)%. The TWSTRS score was 3.2 (3.9) points lower DBS on compared with off (p=0.02). At the stimulation site, stimulation was associated with increased metabolism, which correlated with DBS stimulation amplitude (r=0.70, p=0.03) but not with changes in motor symptom severity (p>0.9). In the whole brain analysis, stimulation increased metabolism in the GPi, subthalamic nucleus, putamen, primary sensorimotor cortex (PFDR<0.05). Acute improvement in TWSTRS correlated with metabolic activation in the sensorimotor cortex and overall treatment response in the supplementary motor area. Worsening of TMT-B score was associated with activation of the anterior cingulate cortex and parkinsonism with activation in the putamen.

CONCLUSIONS

GPi-DBS increases metabolic activity at the stimulation site and sensorimotor network. The clinical benefit and adverse effects are mediated by modulation of specific networks.

Machine versus physician-based programming of deep brain stimulation in isolated dystonia: A feasibility study

BACKGROUND

Deep brain stimulation of the internal globus pallidus effectively alleviates dystonia motor symptoms. However, delayed symptom control and a lack of therapeutic biomarkers and a single pallidal sweetspot region complicates optimal programming. Postoperative management is complex, typically requiring multiple, lengthy follow-ups with an experienced physician - an important barrier to widespread adoption in medication-refractory dystonia patients.

OBJECTIVE

Here we prospectively tested the best machine-predicted programming settings in a dystonia cohort treated with GPi-DBS against the settings derived from clinical long-term care in a specialised DBS centre.

METHODS

Previously, we reconstructed an anatomical map of motor improvement probability across the pallidal region using individual stimulation volumes and clinical outcomes in dystonia patients. We used this to develop an algorithm that tests in silico thousands of putative stimulation settings in de novo patients after reconstructing an individual, image-based anatomical model of electrode positions, and suggests stimulation parameters with the highest likelihood of optimal symptom control. To test real-life application, our prospective study compared results in 10 patients against programming settings derived from long-term care.

RESULTS

In this cohort, dystonia symptom reduction was observed at 74.9 ± 15.3% with C-SURF programming as compared to 66.3 ± 16.3% with clinical programming (p < 0.012). The average total electrical energy delivered (TEED) was similar for both the clinical and C-SURF programming (262.0 μJ/s vs. 306.1 μJ/s respectively).

CONCLUSION

Our findings highlight the clinical potential of machine-based programming in dystonia, which could markedly reduce the programming burden in postoperative management.

Deep Brain Stimulation for Pediatric Dystonia: A Review of the Literature and Suggested Programming Algorithm

Deep brain stimulation (DBS) is an established intervention for use in pediatric movement disorders, especially dystonia. Although multiple publications have provided guidelines for deep brain stimulation patient selection and programming in adults, there are no evidence-based or consensus statements published for pediatrics. The result is lack of standardized care and underutilization of this effective treatment. To this end, we assembled a focus group of 13 pediatric movement disorder specialists and 1 neurosurgeon experienced in pediatric deep brain stimulation to review recent literature and current practices and propose a standardized approach to candidate selection, implantation target site selection, and programming algorithms. For pediatric dystonia, we provide algorithms for (1) programming for initial session and follow-up sessions, and (2) troubleshooting side effects encountered during programming. We discuss common side effects, how they present, and recommendations for management. This topical review serves as a resource for movement disorders specialists interested in using deep brain stimulation for pediatric dystonia.

DIPS (Dystonia Image-based Programming of Stimulation: a prospective, randomized, double-blind crossover trial)

Introduction

Deep brain stimulation of the internal globus pallidus is an effective treatment for dystonia. However, there is a large variability in clinical outcome with up to 25% non-responders even in highly selected primary dystonia patients. In a large cohort of patients we recently demonstrated that the variable clinical outcomes of pallidal DBS for dystonia may result to a large degree by the exact location and stimulation volume within the pallidal region. Here we test a novel approach of programing based on these insights: we first defined probabilistic maps of anti-dystonic effects by aggregating individual electrode locations and volumes of tissue activated of > 80 patients collected in a multicentre effort. We subsequently modified the algorithms to be able to test all possible stimulation settings of de novo patients in silico based on the expected clinical outcome and thus potentially predict the best possible stimulation parameters for the individual patients.

Methods

Within the framework of a BMBF-funded study, this concept of a computer-based prediction of optimal stimulation parameters for patients with dystonia will be tested in a randomized, controlled crossover study. The main parameter for clinical efficacy and primary endpoint is based on the blinded physician rating of dystonia severity reflected by Clinical Dystonia Rating Scales for both interventions (best clinical settings and model predicted settings) after 4 weeks of continuous stimulation. The primary endpoint is defined as “successful treatment with model predicted settings” (yes or no). The value is “yes” if the motor symptoms with model predicted settings are equal or better (tolerance 5% of absolute difference in percentages) to clinical settings. Secondary endpoints will include measures of quality of life, calculated energy consumption of the neurostimulation system and physician time for programming.

Perspective

We envision, that computer-guided deep brain stimulation programming in silico might provide optimal stimulation settings for patients with dystonia without the burden of months of programming sessions. The study protocol is designed to evaluate which programming method is more effective in controlling motor symptom severity and improving quality of life in dystonia (best clinical settings and model predicted settings).

Trial registration Registered with ClinicalTrials.gov on Oct 27, 2021 (NCT05097001).

A practical guide to troubleshooting pallidal deep brain stimulation issues in patients with dystonia

High frequency deep brain stimulation (DBS) of the internal portion of the globus pallidus has, in the last two decades, become a mainstream therapy for the management of medically-refractory dystonia syndromes. Such increasing uptake places an onus on movement disorder physicians to become familiar with this treatment modality, in particular optimal patient selection for the procedure and how to troubleshoot problems relating to sub-optimal efficacy and therapy-related side effects. Deep brain stimulation for dystonic conditions presents some unique challenges. For example, the frequent lack of immediate change in clinical status following stimulation alterations means that programming often relies on personal experience and local practice rather than real-time indicators of efficacy. Further, dystonia is a highly heterogeneous disorder, making the development of unifying guidelines and programming algorithms for DBS in this population difficult. Consequently, physicians may feel less confident in managing DBS for dystonia as compared to other indications e.g. Parkinson's disease. In this review, we integrate our years of personal experience of the programming of DBS systems for dystonia with a critical appraisal of the literature to produce a practical guide for troubleshooting common issues encountered in patients with dystonia treated with DBS, in the hope of improving the care for these patients.