P.078 fMRI-based deep brain stimulation programming: a blinded, crossover clinical trial

Abstract

Background: Success of deep brain stimulation (DBS) in Parkinson’s disease (PD) relies on time-consuming trial-and-error testing of stimulation settings. Here, we prospectively compared an fMRI-based stimulation optimization algorithm with >1 year of standard-of-care (SoC) programming in a double-blind, crossover, non-inferiority trial. Methods: Twenty-seven PD-DBS patients were prospectively enrolled for fMRI using a 30-sec DBS-ON/OFF cycling paradigm. Optimal settings were identified using our published classification algorithm. Subjects then underwent >1 year of SoC programming. Clinical improvement was assessed, after an overnight medication washout period, under SoC and fMRI-determined stimulation conditions. A predefined non-inferiority margin was -5 points on the Unified Parkinson’s Disease Rating Scale (UPDRSIII). Results: UPDRSIII improved from 45.3 (SD=14.6) at baseline to 24.9 (SD=10.9) and 24.1 (SD=10.9) during SoC and fMRI-determined stimulation, respectively. The mean difference in scores was 0.8 (SD=8.5; 95% CI -4.5 to 6.2). The non-inferiority margin was not contained within the 95% confidence interval, establishing non-inferiority (p=0.013). Conclusions: This is the first prospective evaluation of an algorithm able to suggest stimulation parameters solely from the fMRI response to stimulation. It suggests equivalent outcomes may be achieved in 3 hours of fMRI scanning immediately after surgery compared to SoC requiring 6 or more in-person clinic visits throughout >1 year.