Objective: To assess clinical outcomes of an acute automated image-guided programming (aIGP) algorithm in PD patients implanted with a deep brain stimulation (DBS) system.

Background: The effectiveness of DBS in Parkinson’s disease is highly dependent on multiple factors, including patient selection, optimal lead placement, and precise programming of stimulation parameters. Traditionally, DBS programming has been performed in a trial-and-error manner, requiring multiple patient visits to optimize therapeutic effects while minimizing side effects. Recent advancements in imaging and modeling offers the potential to improve DBS programming using image-guided algorithms, which may enhance efficiency, reduce patient burden, and improve clinical outcomes by systematically identifying optimal settings based on patient-specific anatomy and lead location.  This report presents preliminary clinical results demonstrating the use of an aIGP algorithm in patients with idiopathic PD.

Method: This is an ongoing, prospective, blinded, acute cross-over study involving 13 patients (10 male; 11 STN, 2 GPi) chronically implanted with a bilateral DBS system (minimum of 6-month post-DBS activation and on a stable standard-of-care [SoC] DBS program for at least 4 weeks). Patients present to clinic in a meds-off state and undergo programming with either SoC or aIGP before crossing to receive alternative therapy. Blinded MDS-UPDRS III assessments in meds-off/stim-on state is performed with both programs after which patients are restarted on medications and undergo an MDS-UPDRS III assessment in meds-on/stim-on state with aIGP adjusted for medications.

Results: Compared to meds-off/stim-off state, in the meds-off/initial aIGP suggested DBS-on state, motor symptoms significantly improved by an average of 37% (p=0.004).  Similarly, in the meds-on/clinician-optimized aIGP DBS-on state, motor symptoms improved significantly by an average of 51% (p=0.00001). These improvements were not statistically different as compared to the optimized SoC DBS program in both meds-OFF (p=0.81) and meds-ON (p=0.4) states.

Conclusion: Here we present preliminary results that show an automated image-guided DBS program provides beneficial motor improvement equivalent to optimized SoC DBS programming. Chronic evaluation of these automated programs are underway to evaluate long-term efficacy.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/automated-image-guided-programming-algorithm-supports-clinicians-during-dbs-programming-for-parkinsons-disease-patients/