Deep Brain Stimulation Programming Based on Local Field Potentials Detection in Parkinson Disease: A Single Center Experience

WSSFN 2025 Interim Meeting. Abstract 0128.

Autores/as

  • Adriana Lucia Lopez Rios Hospital San Vicente Fundación Rionegro. Colombia.
  • William Duncan Hutchison Toronto Western Hospital, Universtiy Health Network. Canada.
  • Carlos Anibal Restrepo Bravo Universidad CES. Facultad De Medicina. Colombia.
  • Daniel Henao Lopez University of Toronto. Canada.
  • Manuela Pelaez Soto Hospital San Vicente Fundación Rionegro. Colombia.
  • Luis Fernando Botero Posada Hospital San Vicente Fundación Rionegro. Colombia.
  • Carlos Ignacio Velez Arango Hospital San Vicente Fundación Rionegro. Colombia.
  • Juan Sebastian Saavedra Moreno Hospital San Vicente Fundación Rionegro. Colombia.

DOI:

https://doi.org/10.47924/neurotarget2025567

Resumen

Introduction: Subthalamic nucleus DBS (STN-DBS) is an established effective therapy for refractory symptoms in Parkinson’s disease (PD). Perceptive devices that detect local field potentials (LFPs) in the vicinity of the stimulating electrodes allow identification and use of physiological biomarkers that help determining the best contact to stimulate,1 and allow chronic detection of signals for follow-up and further therapy adjustments. The investigator’s interest is to describe our center’s experience, Hospital San Vicente Fundacion Rionegro in the use of LFP-detecting devices in the programming of patients implanted with perceptive devices for STN-DBS in PD,2 the signals found in the first session and their stability over time, stimulation parameters used chronically and outcomes in terms of levodopa-equivalent daily dose (LEDDs) reduction post-operatively in the last visit.
Method: Cross-sectional descriptive study involving patients with PD and STN-DBS. All patients implanted from March 2024 through June 2025 were included, LFPs were measured in the off-medication state. Variables measured included demographic, clinical (diagnosis, age at onset, disease duration, LEDDs, MDS-UPDRS-III scale) and physiological (frequency of interest FOI for sensing at first post-operative programming session, band and stimulation parameters). Data was collected on an Excel database, analyzed in JASP software 0.19.3v. Numeric variables are presented as mean (SD) and qualitative variables in absolute and relative frequencies.
Results: 25 patients (50 electrodes) were included in the analysis. Mean age at implant was 63.7 (8.1) y, mean duration of disease was 10.8 (5.1) y. All patients were implanted bilaterally at the STN. 15 (60%) patients had right-sided predominant symptoms whereas 10 (40%) had left-sided predominance. Mean FOIs were 15.8 (7.7) Hz for right-STN electrodes and 17.5 (4.4) for left-STN electrodes. All electrodes in left hemispheres showed beta band activity on the off state whereas only 2 electrodes on right hemispheres showed different FOIs (7.8 Hz on a patient with left-predominant tremor and 36 Hz on a patient with left-sided biphasic dyskinesia). No significant LFP activity was found on two patients (8%). First programming was on average on day 19 (13) post-implant. Last follow-up was done 151(120) days post-operatively. Mean LEEDs reduction was 557 (369.6) mg.
Discussion: From our knowledge, this is the first report on real world data of LFP-based programming in Latin America, with up to 1.3 years of follow-up. Our data align with previous works, with most patients exhibiting high beta-band activity in the STN related to the off state.3 Theta activity in the contralateral STN to refractory arm tremor was found in one patient and low gamma correlated with biphasic dyskinesia in other. Parameters remained stable and no change in contact stimulated was required. High-power beta oscillations helped in selection of contact for chronic stimulation in most patients.4
Conclusions: LFP-based programming is a useful and efficient tool for chronic programming of STN-DBS in patients with PD. FOIs are usually within the low beta range but should be determined individually based on clinical features.

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Citas

Strelow JN, Dembek TA, Baldermann JC, Andrade P, Fink GR, Visser-Vandewalle V, et al. Low beta-band suppression as a tool for DBS contact selection for akinetic-rigid symptoms in Parkinson’s disease. Parkinsonism Relat Disord. 2023;112. Available from: https://pubmed.ncbi.nlm.nih.gov/37331065/

Asadi A, Madadi Asl M, Vahabie AH, Valizadeh A. The Origin of Abnormal Beta Oscillations in the Parkinsonian Corticobasal Ganglia Circuits. Parkinsons Dis. 2022;2022:7524066. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC8896962/

Shah A, Nguyen TAK, Peterman K, Khawaldeh S, Debove I, Shah SA, et al. Combining Multimodal Biomarkers to Guide Deep Brain Stimulation Programming in Parkinson Disease. Neuromodulation. 2023;26(2):320–32. Available from: https://pubmed.ncbi.nlm.nih.gov/35219571/

Leung CHS, Simpson HD, Thyagarajan D. The Place of Local Field Potentials in Deep Brain Stimulation Programming for Parkinson’s Disease: A Review. Brain Sciences. 2025;(15):116 Available from: https://www.mdpi.com/2076-3425/15/2/116/htm

Muller M, Scafa S, Hanafi I, Varescon C, Palmisano C, van der Gaag S, Zutt R, van der Gaag NA, Hoffmann CFE, Bloch J, Jiménez MC, Bally JF, Capetian P, Isaias IU, Moraud EM, Contarino MF (2024). Online prediction of optimal deep brain stimulation contacts from local field potentials in chronically-implanted patients with Parkinson’s disease. medRxiv. 2024. [doi:10.1101/2024.11.26.24317968]

Little S, Brown P. What brain signals are suitable for feedback control of deep brain stimulation in Parkinson’s disease? Annals of the New York Academy of Sciences. 2022; 1265(1): 9-24. [doi:10.1111/j.1749-6632.2022.08456.x]

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Publicado

2025-11-18

Cómo citar

1.
Lopez Rios AL, Duncan Hutchison W, Restrepo Bravo CA, Henao Lopez D, Pelaez Soto M, Botero Posada LF, et al. Deep Brain Stimulation Programming Based on Local Field Potentials Detection in Parkinson Disease: A Single Center Experience: WSSFN 2025 Interim Meeting. Abstract 0128. NeuroTarget [Internet]. 18 de noviembre de 2025 [citado 27 de noviembre de 2025];19(2):105-6. Disponible en: https://neurotarget.com/index.php/nt/article/view/567

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