The goal of this U44 proposal is to develop and test CranialProgrammer, an image-guided programming toolfor 2D/3D mapping of disease-related neural signals over patient and device data for more efficient andeffective programming of directional deep brain stimulation (DBS) systems. DBS is an established treatmentfor advanced, refractory movement disorders used in over 150,000 patients. However, many patients receiveinadequate symptom control due to poorly placed DBS leads, current spread to unwanted structures, or non-optimized stimulation parameters; all of which are caused or exacerbated by the use of conventional 4-contact"omnidirectional" leads. Recent advances show directional leads, i.e. 8-contact leads with circumferentiallysegmented electrodes in a 1-3-3-1 configuration, can alleviate limitations by steering current towardpathological regions of interest (ROIs) and away from unwanted structures. This can increase DBS efficacyand widen therapeutic windows (TW) up to 111%. However, the greater numbers of contacts on directionalleads adds more possible monopolar and bipolar configurations, especially when combined with independentcurrent sources that distribute current unevenly across contacts. Although these advancements offerunprecedented therapeutic control, the time needed to explore all possible parameters is overwhelming.Tools are needed to narrow the neurologist's focus for identification of correct programming settings ondirectional DBS leads. Recent studies show features of basal ganglia local field potentials (LFPs) are stronglycorrelated to Parkinson's disease (PD) symptoms, indicating LFPs can be used to guide DBS toward thepathological ROI. Therefore, a new programming method using LFP-maps could harness directional leadbenefits by offsetting their added complexity. To this end, we propose CranialProgrammer, an intuitive, LFP-based DBS programming software module to facilitate contact selection on directional leads. It will interfacewith Nexeon's SynapseTM DBS System, which has unprecedented capabilities for directional stimulation anddirectional LFP sensing in DBS implants. CranialProgrammer will allow visualization of disease-related LFPscollected by the Synapse and mapped over multimodal patient data, including brain MRI, CT images of leadimplants, microelectrode recordings, and motor scores. It will provide clinicians with auto-generated, easily-navigable, data-rich patient images to select the best contact for directional DBS more efficiently andeffectively.In Phase I we will automate CranialProgrammer to perform data entry, analysis and spatial mapping of LFPson multi-modal datasets via the Nexeon External Research System (ERS) (Aim 1). We will perform verificationand validation testing (Aim 2), and get IRB approval for a clinical study (Aim 3). In Phase II we will validateefficacy of map-based selection compared to clinical selection on PD patients (N=10) with the chronicallyimplanted Synapse device. The Criteria for Success is â¥80% of patients exhibit either a clinically meaningfulincrease in therapeutic window (>16%) or efficacy (>2.3-pt in UPDRS-III) when programmed withCranialProgrammer.
Public Health Relevance Statement: PROJECT NARRATIVE
Deep brain stimulation (DBS) is an established treatment for advanced Parkinson's disease, but many patients
receive inadequate symptom control. Current steering with directional leads has shown great potential to improve
DBS efficacy by targeting diseased brain regions and avoiding off-target effects; however, current steering
widens the parameter space, adding significant complexity to post-operative DBS programming. We propose
the development of CranialProgrammer, an intuitive, image-guided tool for 2D/3D mapping of disease-related
neural signals over patient and device data for more efficient and effective programming of directional leads.
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