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• W4320898582 abstract "Abstract Background: The correct selection of stimulation parameters is pivotal to treatment success of Deep Brain Stimulation (DBS) therapy. However, this currently follows a time-consuming and demanding trial-and-error process. We recently developed and retrospectively validated a data-driven algorithm (StimFit) which can suggest optimal stimulation parameters based on electrode location in PD patients treated with subthalamic nucleus (STN) DBS. We now prospectively evalutated the treatment effects of stimulation settings suggested by StimFit in a double-blind, randomized, cross-over, non-inferiority trial. Methods: 35 PD patients who underwent STN-DBS surgery at Charité - Universitätsmedizin Berlin participated in this study. Motor performance was assessed after overnight dopaminergic withdrawal according to the MDS-UPDRS-III in OFF-stimulation state and under two stimulation conditions: 1) Patients' standard of care (SoC) setting, which was clinically derived according to our centers postoperative routine and 2) the settings suggested by our StimFit algorithm based on neuroimaging data. Treatment conditions were applied in a double-blind randomized manner. The primary endpoint of this study was the absolute mean difference between motor scores under StimFit and SoC stimulation, with a non-inferiority margin of five points. Findings: MDS-UPDRS-III scores improved by 48 % under SoC and 43 % under StimFit stimulation conditions from an OFF-stimulation baseline of 47·3 ± 17·1 points. The mean absolute difference of motor scores under both conditions was -1·6 ± 7·1 (95% CI: [-4·0, 0·9]) in favor of SoC, which was statistically non-significant (Superiority test: psup = 0·20). Non-inferiority of StimFit stimulation was established at a margin of -5 points (Non-inferiority test pnoninf = 0·0038). Interpretation: Predictive models embedded in mathematical optimization procedures can identify beneficial DBS parameters. This could drastically reduce programming time and ressources and pave the way for novel electrode designs. Long-term data including effects on quality of life and ON-medication assessments require further investigation. Research Category and Technology and Methods Translational Research: 1. Deep Brain Stimulation (DBS) Keywords: Parkinson’s disease, subthalamic nucleus, image-guided programming, clinical trial" @default.
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• W4320898582 date "2023-01-01" @default.
• W4320898582 modified "2023-10-16" @default.
• W4320898582 title "Automated deep brain stimulation programming based on electrode location – a randomized, cross-over trial using a data-driven algorithm" @default.
• W4320898582 doi "https://doi.org/10.1016/j.brs.2023.01.762" @default.
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