Estimation of ANT-DBS Electrodes on Target Positioning Based on a New PerceptTM PC LFP Signal Analysis.
Sensors (Basel)
; 22(17)2022 Sep 01.
Article
em En
| MEDLINE
| ID: mdl-36081060
ABSTRACT
Deep brain stimulation of the Anterior Nucleus of the Thalamus (ANT-DBS) is an effective therapy in epilepsy. Poorer surgical outcomes are related to deviations of the lead from the ANT-target. The target identification relies on the visualization of anatomical structures by medical imaging, which presents some disadvantages. This study aims to research whether ANT-LFPs recorded with the PerceptTM PC neurostimulator can be an asset in the identification of the DBS-target. For this purpose, 17 features were extracted from LFPs recorded from a single patient, who stayed at an Epilepsy Monitoring Unit for a 5-day period. Features were then integrated into two machine learning (ML)-based methodologies, according to different LFP bipolar montages Pass1 (nonadjacent channels) and Pass2 (adjacent channels). We obtained an accuracy of 76.6% for the Pass1-classifier and 83.33% for the Pass2-classifier in distinguishing locations completely inserted in the target and completely outside. Then, both classifiers were used to predict the target percentage of all combinations, and we found that contacts 3 (left hemisphere) and 2 and 3 (right hemisphere) presented higher signatures of the ANT-target, which agreed with the medical images. This result opens a new window of opportunity for the use of LFPs in the guidance of DBS target identification.
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Base de dados:
MEDLINE
Assunto principal:
Núcleos Anteriores do Tálamo
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Estimulação Encefálica Profunda
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Epilepsia
Idioma:
En
Ano de publicação:
2022
Tipo de documento:
Article