Modeling of Electric Fields in Individual Imaging Atlas for Capsular Threshold Prediction of Deep Brain Stimulation in Parkinson's Disease: A Pilot Study

Détails

ID Serval
serval:BIB_467BDC00FF39
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Modeling of Electric Fields in Individual Imaging Atlas for Capsular Threshold Prediction of Deep Brain Stimulation in Parkinson's Disease: A Pilot Study
Périodique
Front Neurol
Auteur(s)
Bereau M., Kibleur A., Bouthour W., Tomkova Chaoui E., Maling N., Nguyen T. A. K., Momjian S., Vargas Gomez M. I., Zacharia A., Bally J. F., Fleury V., Tatu L., Burkhard P. R., Krack P.
ISSN
1664-2295 (Print)
ISSN-L
1664-2295
Statut éditorial
Publié
Date de publication
2020
Volume
11
Pages
532
Langue
anglais
Notes
Bereau, Matthieu
Kibleur, Astrid
Bouthour, Walid
Tomkova Chaoui, Emilie
Maling, Nicholas
Nguyen, T A Khoa
Momjian, Shahan
Vargas Gomez, Maria Isabel
Zacharia, Andre
Bally, Julien F
Fleury, Vanessa
Tatu, Laurent
Burkhard, Pierre R
Krack, Paul
eng
Switzerland
Front Neurol. 2020 Jul 2;11:532. doi: 10.3389/fneur.2020.00532. eCollection 2020.
Résumé
Background: Modeling of deep brain stimulation electric fields and anatomy-based software might improve post-operative management of patients with Parkinson's disease (PD) who have benefitted from subthalamic nucleus deep brain stimulation (STN-DBS). Objective: We compared clinical and software-guided determination of the thresholds for current diffusion to the pyramidal tract, the most frequent limiting side effect in post-operative management of STN-DBS PD patients. Methods: We assessed monopolar reviews in 16 consecutive STN-DBS PD patients and retrospectively compared clinical capsular thresholds, which had been assessed according to standard clinical practice, to those predicted by volume of tissue activated (VTA) model software. All the modeling steps were performed blinded from patients' clinical evaluations. Results: At the group level, we found a significant correlation (p = 0.0001) when performing statistical analysis on the z-scored capsular thresholds, but with a low regression coefficient (r = 0.2445). When considering intra-patient analysis, we found significant correlations (p < 0.05) between capsular threshold as modeled with the software and capsular threshold as determined clinically in five patients (31.2%). Conclusions: In this pilot study, the VTA model software was of limited assistance in identifying capsular thresholds for the whole cohort due to a large inter-patient variability. Clinical testing remains the gold standard in selecting stimulation parameters for STN-DBS in PD.
Mots-clé
Parkinson's disease, capsular prediction, deep brain stimulation, subthalamic nucleus, volume of tissue activated
Pubmed
Création de la notice
21/05/2021 10:09
Dernière modification de la notice
22/05/2021 6:34
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