Connectomic Guided DBS for Parkinson's Disease

Overview

The objective of this research is to use advanced connectomic imaging models to identify disease-relevant axonal pathway targets for better tremor control in Parkinson's disease patients while avoiding undesirable side effects, with the goal of increasing precision and facilitating the choice of optimal DBS parameters for certain disease phenotypes. The investigators hypothesize that patient centered subthalamic nucleus deep brain stimulation of cerebellothalamic axonal pathways and pallidothalamic tract activation can provide better tremor control while avoiding worsening dyskinesias in patients with Parkinson's disease with significant tremor.

Patients with Parkinson's disease (PD) can suffer from significant disability due to tremors, rigidity, bradykinesia, or motor fluctuations, in addition to non-motor symptoms of the disease. Deep brain stimulation (DBS) is the main surgical approach approved by the US Food and Drug Administration (FDA) for the treatment of medication-refractory PD. Despite recent advances, the selection of DBS parameters is based on trial-and-error experimentation by specialists over the course of months. Better understanding of the optimal network targets for symptomatic control would allow for therapy improvement and simplify the DBS programming process, increase efficiency, and possibly increase access to care. Most studies of structural connectivity in PD have focused on the analysis of the subthalamic nucleus (STN). Previous studies analyzing structural connectivity of STN DBS have shown that specific motor symptoms benefit from the activation of different networks. Several tracts such as the cerebellothalamic tract (CBT), pallidothalamic (PT) and corticospinal tract (CST) course through the STN and might be relevant for DBS targeting. For patients with essential tremor, stimulation of the CBT might provide better tremor control, but studies in PD are lacking. The investigators will use connectomic models to better understand the mechanistic qualities of axonal pathways in the STN in Parkinson's disease and address the need for phenotype driven stimulation in PD. Estimating targeted axonal pathways by using connectomic models may guide personalized decision-making and targeting of DBS. It has the potential to improve clinical outcomes and reduce the number of visits needed for DBS optimization. The study involves the extraction of data collected during routine clinical care, and data collected during the intervention study. Data collected during routine clinical care includes: * Demographic characteristics: age, gender, ethnicity, race. * Clinical characteristics: disease duration, Movement Disorders Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS III) prior to DBS implementation, levodopa equivalent daily dose of medications. * Imaging data: DBS lead location, stimulation model activation pathway, recruitment curves, percent of each pathway activated with clinical DBS settings