Objective: Investigate the correlation between power in local field potential (LFP) beta band sensed from the subthalamic nucleus (STN) and the volume of neural activation (VNA) during monopolar stimulation in patients with Parkinson’s disease

Background: Deep brain stimulation (DBS) is a safe and effective therapy for managing the motor symptoms of Parkinson’s disease (PD). Novel neural stimulator technology now allows the simultaneous delivery of therapeutic stimulation and recording of neural data. In PD, LFP beta power is an established real-time biomarker. This pilot study investigates the relationship between LFP beta and the VNA associated with optimal DBS programming settings.

Method: Ten PD patients (n = 20 hemispheres) with bilateral STN-DBS implanted with 1-3-3-1 segmented leads and a sensing capable neural stimulator were enrolled. The therapeutic electrode was selected by identifying the electrode with the highest beta peak from sensing data collected at the programming visit [1]. Amplitude titration was performed to determine the response window based on beta power suppression using 0.2 mA steps while sensing data was simultaneously collected. Post-hoc analysis was performed to calculate the VNA for each step to assess the correlation between the real-time sensing data and post-hoc imaging analysis. LFP beta power was normalized to allow for aggregate data analysis.

Results: Across subjects and hemispheres, we observed 1) reduced rigidity correlated with increased VNA-STN overlap, 2) decreased normalized beta peak power correlated with increased VNA-STN overlap, 3) no relationship between normalized beta peak power and VNA overlap within the zona incerta, and 4) adverse effects were associated with greater VNA outside the STN.

Conclusion: VNA overlap of the STN strongly correlated with reduced rigidity and reduced beta peak power. Stimulation beyond the STN was not effective in reducing beta peak power and was associated with adverse effects. This demonstrated that LFP sensing data may provide sufficient guidance for objective programming of electrodes. If this relationship generalizes across a larger cohort, programming time may be reduced and allow for optimization of other DBS programming parameters.

References: [1] “Pilot Study to Investigate the Use of In-Clinic Sensing to Identify Optimal Stimulation Parameters for Deep Brain Stimulation Therapy in Parkinson’s Disease.” Neuromodulation: Technology at the Neural Interface (2023).

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MDS Abstracts - https://www.mdsabstracts.org/abstract/correlation-of-neural-sensing-with-the-volume-of-neural-activation-within-the-desired-patient-specific-anatomical-target-in-deep-brain-stimulation-for-parkinsons-disease/