Supporting clinical decision making during deep brain stimulation surgery by means of a stochastic dynamical model.
Identifieur interne : 001A76 ( Main/Merge ); précédent : 001A75; suivant : 001A77Supporting clinical decision making during deep brain stimulation surgery by means of a stochastic dynamical model.
Auteurs : Sofia D. Karamintziou [Grèce] ; George L. Tsirogiannis ; Pantelis G. Stathis ; George A. Tagaris ; Efstathios J. Boviatsis ; Damianos E. Sakas ; Konstantina S. NikitaSource :
- Journal of neural engineering [ 1741-2552 ] ; 2014.
Descripteurs français
- KwdFr :
- Adulte d'âge moyen, Femelle, Humains, Implantation de prothèse (), Maladie de Parkinson (), Maladie de Parkinson (physiopathologie), Modèles neurologiques, Modèles statistiques, Mâle, Noyau subthalamique (), Noyau subthalamique (physiopathologie), Processus stochastiques, Résultat thérapeutique, Simulation numérique, Stimulation cérébrale profonde (), Stimulation cérébrale profonde (instrumentation), Sujet âgé, Surveillance peropératoire (), Systèmes d'aide à la décision clinique, Électrodes implantées.
- MESH :
- physiopathologie : Maladie de Parkinson, Noyau subthalamique.
- instrumentation : Adulte d'âge moyen, Femelle, Humains, Implantation de prothèse, Maladie de Parkinson, Modèles neurologiques, Modèles statistiques, Mâle, Noyau subthalamique, Processus stochastiques, Résultat thérapeutique, Simulation numérique, Stimulation cérébrale profonde, Sujet âgé, Surveillance peropératoire, Systèmes d'aide à la décision clinique, Électrodes implantées.
English descriptors
- KwdEn :
- Aged, Computer Simulation, Decision Support Systems, Clinical, Deep Brain Stimulation (instrumentation), Deep Brain Stimulation (methods), Electrodes, Implanted, Female, Humans, Male, Middle Aged, Models, Neurological, Models, Statistical, Monitoring, Intraoperative (methods), Parkinson Disease (physiopathology), Parkinson Disease (therapy), Prosthesis Implantation (methods), Stochastic Processes, Subthalamic Nucleus (physiopathology), Subthalamic Nucleus (surgery), Treatment Outcome.
- MESH :
- instrumentation : Deep Brain Stimulation.
- methods : Deep Brain Stimulation, Monitoring, Intraoperative, Prosthesis Implantation.
- physiopathology : Parkinson Disease, Subthalamic Nucleus.
- surgery : Subthalamic Nucleus.
- therapy : Parkinson Disease.
- Aged, Computer Simulation, Decision Support Systems, Clinical, Electrodes, Implanted, Female, Humans, Male, Middle Aged, Models, Neurological, Models, Statistical, Stochastic Processes, Treatment Outcome.
Abstract
During deep brain stimulation (DBS) surgery for the treatment of advanced Parkinson's disease (PD), microelectrode recording (MER) in conjunction with functional stimulation techniques are commonly applied for accurate electrode implantation. However, the development of automatic methods for clinical decision making has to date been characterized by the absence of a robust single-biomarker approach. Moreover, it has only been restricted to the framework of MER without encompassing intraoperative macrostimulation. Here, we propose an integrated series of novel single-biomarker approaches applicable to the entire electrophysiological procedure by means of a stochastic dynamical model.
DOI: 10.1088/1741-2560/11/5/056019
PubMed: 25241917
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pubmed:25241917Le document en format XML
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<term>Decision Support Systems, Clinical</term>
<term>Deep Brain Stimulation (instrumentation)</term>
<term>Deep Brain Stimulation (methods)</term>
<term>Electrodes, Implanted</term>
<term>Female</term>
<term>Humans</term>
<term>Male</term>
<term>Middle Aged</term>
<term>Models, Neurological</term>
<term>Models, Statistical</term>
<term>Monitoring, Intraoperative (methods)</term>
<term>Parkinson Disease (physiopathology)</term>
<term>Parkinson Disease (therapy)</term>
<term>Prosthesis Implantation (methods)</term>
<term>Stochastic Processes</term>
<term>Subthalamic Nucleus (physiopathology)</term>
<term>Subthalamic Nucleus (surgery)</term>
<term>Treatment Outcome</term>
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<term>Femelle</term>
<term>Humains</term>
<term>Implantation de prothèse ()</term>
<term>Maladie de Parkinson ()</term>
<term>Maladie de Parkinson (physiopathologie)</term>
<term>Modèles neurologiques</term>
<term>Modèles statistiques</term>
<term>Mâle</term>
<term>Noyau subthalamique ()</term>
<term>Noyau subthalamique (physiopathologie)</term>
<term>Processus stochastiques</term>
<term>Résultat thérapeutique</term>
<term>Simulation numérique</term>
<term>Stimulation cérébrale profonde ()</term>
<term>Stimulation cérébrale profonde (instrumentation)</term>
<term>Sujet âgé</term>
<term>Surveillance peropératoire ()</term>
<term>Systèmes d'aide à la décision clinique</term>
<term>Électrodes implantées</term>
</keywords>
<keywords scheme="MESH" qualifier="instrumentation" xml:lang="en"><term>Deep Brain Stimulation</term>
</keywords>
<keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Deep Brain Stimulation</term>
<term>Monitoring, Intraoperative</term>
<term>Prosthesis Implantation</term>
</keywords>
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<term>Noyau subthalamique</term>
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<term>Subthalamic Nucleus</term>
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<term>Models, Statistical</term>
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<term>Humains</term>
<term>Implantation de prothèse</term>
<term>Maladie de Parkinson</term>
<term>Modèles neurologiques</term>
<term>Modèles statistiques</term>
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<term>Surveillance peropératoire</term>
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<front><div type="abstract" xml:lang="en">During deep brain stimulation (DBS) surgery for the treatment of advanced Parkinson's disease (PD), microelectrode recording (MER) in conjunction with functional stimulation techniques are commonly applied for accurate electrode implantation. However, the development of automatic methods for clinical decision making has to date been characterized by the absence of a robust single-biomarker approach. Moreover, it has only been restricted to the framework of MER without encompassing intraoperative macrostimulation. Here, we propose an integrated series of novel single-biomarker approaches applicable to the entire electrophysiological procedure by means of a stochastic dynamical model.</div>
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