Cargando…
Towards biomarker-based optimization of deep brain stimulation in Parkinson’s disease patients
BACKGROUND: Subthalamic deep brain stimulation (DBS) is an established therapy to treat Parkinson’s disease (PD). To maximize therapeutic outcome, optimal DBS settings must be carefully selected for each patient. Unfortunately, this is not always achieved because of: (1) increased technological comp...
Autores principales: | , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9875598/ https://www.ncbi.nlm.nih.gov/pubmed/36711127 http://dx.doi.org/10.3389/fnins.2022.1091781 |
_version_ | 1784877993467838464 |
---|---|
author | Peeters, Jana Boogers, Alexandra Van Bogaert, Tine Dembek, Till Anselm Gransier, Robin Wouters, Jan Vandenberghe, Wim De Vloo, Philippe Nuttin, Bart Mc Laughlin, Myles |
author_facet | Peeters, Jana Boogers, Alexandra Van Bogaert, Tine Dembek, Till Anselm Gransier, Robin Wouters, Jan Vandenberghe, Wim De Vloo, Philippe Nuttin, Bart Mc Laughlin, Myles |
author_sort | Peeters, Jana |
collection | PubMed |
description | BACKGROUND: Subthalamic deep brain stimulation (DBS) is an established therapy to treat Parkinson’s disease (PD). To maximize therapeutic outcome, optimal DBS settings must be carefully selected for each patient. Unfortunately, this is not always achieved because of: (1) increased technological complexity of DBS devices, (2) time restraints, or lack of expertise, and (3) delayed therapeutic response of some symptoms. Biomarkers to accurately predict the most effective stimulation settings for each patient could streamline this process and improve DBS outcomes. OBJECTIVE: To investigate the use of evoked potentials (EPs) to predict clinical outcomes in PD patients with DBS. METHODS: In ten patients (12 hemispheres), a monopolar review was performed by systematically stimulating on each DBS contact and measuring the therapeutic window. Standard imaging data were collected. EEG-based EPs were then recorded in response to stimulation at 10 Hz for 50 s on each DBS-contact. Linear mixed models were used to assess how well both EPs and image-derived information predicted the clinical data. RESULTS: Evoked potential peaks at 3 ms (P3) and at 10 ms (P10) were observed in nine and eleven hemispheres, respectively. Clinical data were well predicted using either P3 or P10. A separate model showed that the image-derived information also predicted clinical data with similar accuracy. Combining both EPs and image-derived information in one model yielded the highest predictive value. CONCLUSION: Evoked potentials can accurately predict clinical DBS responses. Combining EPs with imaging data further improves this prediction. Future refinement of this approach may streamline DBS programming, thereby improving therapeutic outcomes. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov, identifier NCT04658641. |
format | Online Article Text |
id | pubmed-9875598 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-98755982023-01-26 Towards biomarker-based optimization of deep brain stimulation in Parkinson’s disease patients Peeters, Jana Boogers, Alexandra Van Bogaert, Tine Dembek, Till Anselm Gransier, Robin Wouters, Jan Vandenberghe, Wim De Vloo, Philippe Nuttin, Bart Mc Laughlin, Myles Front Neurosci Neuroscience BACKGROUND: Subthalamic deep brain stimulation (DBS) is an established therapy to treat Parkinson’s disease (PD). To maximize therapeutic outcome, optimal DBS settings must be carefully selected for each patient. Unfortunately, this is not always achieved because of: (1) increased technological complexity of DBS devices, (2) time restraints, or lack of expertise, and (3) delayed therapeutic response of some symptoms. Biomarkers to accurately predict the most effective stimulation settings for each patient could streamline this process and improve DBS outcomes. OBJECTIVE: To investigate the use of evoked potentials (EPs) to predict clinical outcomes in PD patients with DBS. METHODS: In ten patients (12 hemispheres), a monopolar review was performed by systematically stimulating on each DBS contact and measuring the therapeutic window. Standard imaging data were collected. EEG-based EPs were then recorded in response to stimulation at 10 Hz for 50 s on each DBS-contact. Linear mixed models were used to assess how well both EPs and image-derived information predicted the clinical data. RESULTS: Evoked potential peaks at 3 ms (P3) and at 10 ms (P10) were observed in nine and eleven hemispheres, respectively. Clinical data were well predicted using either P3 or P10. A separate model showed that the image-derived information also predicted clinical data with similar accuracy. Combining both EPs and image-derived information in one model yielded the highest predictive value. CONCLUSION: Evoked potentials can accurately predict clinical DBS responses. Combining EPs with imaging data further improves this prediction. Future refinement of this approach may streamline DBS programming, thereby improving therapeutic outcomes. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov, identifier NCT04658641. Frontiers Media S.A. 2023-01-11 /pmc/articles/PMC9875598/ /pubmed/36711127 http://dx.doi.org/10.3389/fnins.2022.1091781 Text en Copyright © 2023 Peeters, Boogers, Van Bogaert, Dembek, Gransier, Wouters, Vandenberghe, De Vloo, Nuttin and Mc Laughlin. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Peeters, Jana Boogers, Alexandra Van Bogaert, Tine Dembek, Till Anselm Gransier, Robin Wouters, Jan Vandenberghe, Wim De Vloo, Philippe Nuttin, Bart Mc Laughlin, Myles Towards biomarker-based optimization of deep brain stimulation in Parkinson’s disease patients |
title | Towards biomarker-based optimization of deep brain stimulation in Parkinson’s disease patients |
title_full | Towards biomarker-based optimization of deep brain stimulation in Parkinson’s disease patients |
title_fullStr | Towards biomarker-based optimization of deep brain stimulation in Parkinson’s disease patients |
title_full_unstemmed | Towards biomarker-based optimization of deep brain stimulation in Parkinson’s disease patients |
title_short | Towards biomarker-based optimization of deep brain stimulation in Parkinson’s disease patients |
title_sort | towards biomarker-based optimization of deep brain stimulation in parkinson’s disease patients |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9875598/ https://www.ncbi.nlm.nih.gov/pubmed/36711127 http://dx.doi.org/10.3389/fnins.2022.1091781 |
work_keys_str_mv | AT peetersjana towardsbiomarkerbasedoptimizationofdeepbrainstimulationinparkinsonsdiseasepatients AT boogersalexandra towardsbiomarkerbasedoptimizationofdeepbrainstimulationinparkinsonsdiseasepatients AT vanbogaerttine towardsbiomarkerbasedoptimizationofdeepbrainstimulationinparkinsonsdiseasepatients AT dembektillanselm towardsbiomarkerbasedoptimizationofdeepbrainstimulationinparkinsonsdiseasepatients AT gransierrobin towardsbiomarkerbasedoptimizationofdeepbrainstimulationinparkinsonsdiseasepatients AT woutersjan towardsbiomarkerbasedoptimizationofdeepbrainstimulationinparkinsonsdiseasepatients AT vandenberghewim towardsbiomarkerbasedoptimizationofdeepbrainstimulationinparkinsonsdiseasepatients AT devloophilippe towardsbiomarkerbasedoptimizationofdeepbrainstimulationinparkinsonsdiseasepatients AT nuttinbart towardsbiomarkerbasedoptimizationofdeepbrainstimulationinparkinsonsdiseasepatients AT mclaughlinmyles towardsbiomarkerbasedoptimizationofdeepbrainstimulationinparkinsonsdiseasepatients |