Objective: Explore the utility of chronic brain sensing in identifying patient-specific trends that could be useful to tailor deep brain stimulation (DBS) in Parkinson’s disease (PD).

Background: DBS is an established, effective therapy for alleviating motor symptoms in PD patients. Current FDA-approved devices can simultaneously deliver therapy and sense neural activity. Local field potential (LFP) recordings, specifically in the beta frequency range (13-30 Hz), have been shown to inform programming settings [1, 2] and provide a viable control signal to adapt stimulation amplitude based on patient needs [3]. However, the full utility of chronic LFP signals has additional potential that has not yet been fully explored. Here, we explore case studies of patients implanted with sense-enabled neural stimulators and equipped with wearable devices to highlight patient-specific trends that could inform therapy management.

Method: A cohort of PD patients implanted with DBS in the subthalamic nucleus or globus pallidus interna with concurrent LFP sensing and wearable data were analyzed. LFP sensing data was collected using standard-of-care capabilities. Three trends in the chronic sensing information were evaluated and compared to wearable metrics where possible. First, we looked at how chronic LFP sensing between the implant and first programming can be used to detect potential microlesion effects to inform when a patient has returned to “baseline.” Second, we investigated the prevalence of 24-hour trends, such as circadian rhythm, to identify characteristics of periodicity. Finally, we show how fluctuations in LFP beta power seen during therapy optimization correlate with wearable metrics in longitudinal data.

Results: We observed and quantified the occurrence of likely post-surgical LFP microlesion effects and the establishment of 24-hour patterns in a subset of patients. The analysis revealed a correlation between the brain sense signal and wearable metrics in a subset of patients with chronic sensing information.

Conclusion: The retrospective analysis used in the study provides valuable data-driven insight that could inform therapy decisions or prompt discussions with patients. The correlation between the brain sense data and wearable metrics in a subset of patients indicates that LFP signals can provide objective metrics for monitoring patient states and tailoring therapy decisions.

References: [1] Lange, F., Steigerwald, F., Brandt, G. A., Odorfer, T. M., Reich, M. M., Volkmann, J., . . . Capetian, P. D. (2021). Reduced programming time and strong symptom control even in chronic course through imaging-based DBS programming. Frontiers in Neurology.

[2] Lewis, S., Radcliffe, E., Ojemann, S., Kramer, D. R., Hirt, L., Case, M., . . . Thompson, J. A. (2023). 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.

[3] Oehrn, C. R., Cernera, S., Hammer, L. H., Shcherbakova, M., Yao, J., Hahn, A., . . . Starr, P. A. (2023). Personalized chronic adaptive deep brain stimulation outperforms conventional stimulation in Parkinson’s disease. medRxiv.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/case-studies-of-real-world-brain-sensing-showing-patient-specific-trends-to-inform-therapy-management-in-parkinsons-disease/