Objectives: Deep brain stimulation (DBS) programming is based on clinical response testing. Our clinical pilot trial assessed the feasibility of image-guided programing using software depicting the lead location in a patient-specific anatomical model.Methods: Parkinson's disease patients with subthalamic nucleus-DBS were randomly assigned to standard clinical-based programming (CBP) or anatomical-based (imaging-guided) programming (ABP) in an 8-week crossover trial. Programming characteristics and clinical outcomes were evaluated.Results: In 10 patients, both programs led to similar motor symptom control (MDS-UPDRS III) after 4 weeks (medicationOFF/stimulationON; CPB: 18.27 ± 9.23; ABP: 18.37 ± 6.66). Stimulation settings were not significantly different, apart from higher frequency in the baseline program than CBP (p = 0.01) or ABP (p = 0.003). Time spent in a program was not significantly different (CBP: 86.1 ± 29.82%, ABP: 88.6 ± 29.0%). Programing time was significantly shorter (p = 0.039) with ABP (19.78 ± 5.86 min) than CBP (45.22 ± 18.32).Conclusion: Image-guided DBS programming in PD patients drastically reduces programming time without compromising symptom control and patient satisfaction in this small feasibility trial.

Subthalamic nucleus deep brain stimulation (STN-DBS) is an effective treatment for advanced Parkinson's disease (PD). Clinical outcomes after DBS can be limited by poor programming, which remains a clinically driven, lengthy and iterative process. Electrophysiological recordings in PD patients undergoing STN-DBS have shown an association between STN spectral power in the beta frequency band (beta power) and the severity of clinical symptoms. New commercially-available DBS devices now enable the recording of STN beta oscillations in chronically-implanted PD patients, thereby allowing investigation into the use of beta power as a biomarker for DBS programming. To determine the potential advantages of beta-guided DBS programming over clinically and image-guided programming in terms of clinical efficacy and programming time. We conducted a randomized, blinded, three-arm, crossover clinical trial in eight Parkinson's patients with STN-DBS who were evaluated three months after DBS surgery. We compared clinical efficacy and time required for each DBS programming paradigm, as well as DBS parameters and total energy delivered between the three strategies (beta-, clinically- and image-guided). All three programming methods showed similar clinical efficacy, but the time needed for programming was significantly shorter for beta- and image-guided programming compared to clinically-guided programming (p < 0.001). Beta-guided programming may be a useful and more efficient approach to DBS programming in Parkinson's patients with STN-DBS. It takes significantly less time to program than traditional clinically-based programming, while providing similar symptom control. In addition, it is readily available within the clinical DBS programmer, making it a valuable tool for improving current clinical practice.

Deep brain stimulation (DBS) of the thalamic ventral intermediate nucleus is one of the main advanced neurosurgical treatments for drug-resistant tremor. However, not every patient may be eligible for this procedure. Nowadays, various other functional neurosurgical procedures are available. In particular cases, radiofrequency thalamotomy, focused ultrasound and radiosurgery are proven alternatives to DBS. Besides, other DBS targets, such as the posterior subthalamic area (PSA) or the dentato-rubro-thalamic tract (DRT), may be appraised as well. In this review, the clinical characteristics and pathophysiology of tremor syndromes, as well as long-term outcomes of DBS in different targets, will be summarized. The effectiveness and safety of lesioning procedures will be discussed, and an evidence-based clinical treatment approach for patients with drug-resistant tremor will be presented. Lastly, the future directions in the treatment of severe tremor syndromes will be elaborated.

Deep brain stimulation of the subthalamic nucleus is an effective treatment of Parkinson's disease, yet it is often associated with a general deterioration of speech intelligibility. Clustering the phenotypes of dysarthria has been proposed as a strategy to tackle these stimulation-induced speech problems. In this study, we examine a cohort of 24 patients to test the real-life application of the proposed clustering and attempt to attribute the clusters to specific brain networks with two different approaches of connectivity analysis. Both our data-driven and hypothesis-driven approaches revealed strong connections of variants of stimulation-induced dysarthria to brain regions that are known actors of motor speech control. We showed a strong connection between the spastic dysarthria type and the precentral gyrus and supplementary motor area, prompting a possible disruption of corticobulbar fibers. The connection between the strained voice dysarthria and more frontal areas hints toward a deeper disruption of the motor programming of speech production. These results provide insights into the mechanism of stimulation-induced dysarthria in deep brain stimulation of the subthalamic nucleus and may guide reprogramming attempts for individual Parkinson's patients based on pathophysiological understanding of the affected networks.

We developed VisionMD, an AI computer vision platform, analyzing over 1200 clinical videos of Parkinson’s patients’ hand movements across 13 years. This large-scale, markerless analysis identified three kinematic domains (speed, consistency, timing/scale) reliably improved by levodopa. Our method offers objective, quantitative motor assessment, reducing subjectivity and enhancing reproducibility compared to traditional scales.

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