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.

Distinct phenotypes of stimulation-induced dysarthria represent different cortical networks in STN-DBS.

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Increased functional connectivity in a population at risk of developing Parkinson's disease.

BACKGROUND: While the concept of prodromal Parkinson's disease (PD) is well established, reliable markers for the diagnosis of this disease stage are still lacking. We investigated the functional connectivity of the putamina in a resting-state functional MRI analysis in persons with at least two prodromal factors for PD, which is considered a high risk for PD (HRPD) group, in comparison to PD patients and controls. METHODS: We included 16 PD patients, 20 healthy controls and 20 HRPD subjects. Resting state echo planar images and anatomical T1-weighted images were acquired with a Siemens Prisma 3 T scanner. The computation of correlation maps of the left and the right putamen to the rest of the brain was done in a voxel-wise approach using the REST toolbox. Finally, group differences in the correlation maps were compared on voxel-level and summarized in cluster z-statistics. RESULTS: Compared to both PD patients and healthy controls, the HRPD group showed higher functional connectivity of both putamina to brain regions involved in execution of motion and coordination (cerebellum, vermis, pre- and postcentral gyrus, supplementary motor area) as well as the planning of movement (precuneus, cuneus, superior medial frontal lobe). CONCLUSIONS: Higher functional connectivity of the putamina of HRPD subjects to other brain regions involved in motor execution and planning may indicate a compensatory mechanism. Follow-up evaluation and independent longitudinal studies should test whether our results reflect a dynamic process associated with a prodromal PD state.