: Deep Brain Stimulation (DBS) programming in Parkinson's disease relies on clinical evaluation, yet beta-band activity in local field potentials (LFPs) may offer objective guidance. We evaluated LFP-guided contact selection against clinical programming (CP) at initial monopolar review and long-term follow-up. Bipolar LFPs were recorded in patients with sensing-enabled DBS systems, where central levels were clinically chosen. Three methods based on beta peak amplitude were tested: Broad-Bipolar (non-adjacent rings), Narrow-Bipolar (contiguous rings), and Segment-Bipolar (horizontal segments). Performance was assessed using correlation, agreement, and selection similarity with CP and compared to random selection. Narrow-Bipolar showed the strongest correlation and agreement with CP at both timepoints, outperforming other methods and random selection. It showed the greatest selection stability over time and the highest prediction. Its performance was comparable to imaging-guided programming and did not differ between STN and GPi. These results support Narrow-Bipolar as a valid, easy-to-perform beta-based method for guiding DBS programming.

Local field potentials survey to guide DBS programming in Parkinson’s disease: a clinical-neurophysiological longitudinal study

D'Onofrio, Valentina;Weis, Luca;Rigon, Leonardo;Landi, Andrea;Porcaro, Camillo;Antonini, Angelo;Guerra, Andrea
2025

Abstract

: Deep Brain Stimulation (DBS) programming in Parkinson's disease relies on clinical evaluation, yet beta-band activity in local field potentials (LFPs) may offer objective guidance. We evaluated LFP-guided contact selection against clinical programming (CP) at initial monopolar review and long-term follow-up. Bipolar LFPs were recorded in patients with sensing-enabled DBS systems, where central levels were clinically chosen. Three methods based on beta peak amplitude were tested: Broad-Bipolar (non-adjacent rings), Narrow-Bipolar (contiguous rings), and Segment-Bipolar (horizontal segments). Performance was assessed using correlation, agreement, and selection similarity with CP and compared to random selection. Narrow-Bipolar showed the strongest correlation and agreement with CP at both timepoints, outperforming other methods and random selection. It showed the greatest selection stability over time and the highest prediction. Its performance was comparable to imaging-guided programming and did not differ between STN and GPi. These results support Narrow-Bipolar as a valid, easy-to-perform beta-based method for guiding DBS programming.
2025
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3571972
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