Classification and Prediction of Clinical Improvement in Deep Brain Stimulation From Intraoperative Microelectrode Recordings.
Identifieur interne : 001704 ( Ncbi/Checkpoint ); précédent : 001703; suivant : 001705Classification and Prediction of Clinical Improvement in Deep Brain Stimulation From Intraoperative Microelectrode Recordings.
Auteurs : Kyriaki Kostoglou ; Konstantinos P. Michmizos ; Pantelis Stathis ; Damianos Sakas ; Konstantina S. Nikita ; Georgios D. MitsisSource :
- IEEE transactions on bio-medical engineering [ 1558-2531 ] ; 2017.
Descripteurs français
- KwdFr :
- Cartographie cérébrale (), Cartographie cérébrale (instrumentation), Diagnostic assisté par ordinateur (), Diagnostic assisté par ordinateur (instrumentation), Humains, Maladie de Parkinson (), Maladie de Parkinson (diagnostic), Microélectrodes, Noyau subthalamique, Pronostic, Résultat thérapeutique, Stimulation cérébrale profonde (), Stimulation cérébrale profonde (instrumentation), Surveillance neurophysiologique peropératoire (), Surveillance neurophysiologique peropératoire (instrumentation), Thérapie assistée par ordinateur (), Thérapie assistée par ordinateur (instrumentation), Électrocorticographie (), Électrocorticographie (instrumentation).
- MESH :
- diagnostic : Maladie de Parkinson.
- instrumentation : Cartographie cérébrale, Diagnostic assisté par ordinateur, Humains, Maladie de Parkinson, Microélectrodes, Noyau subthalamique, Pronostic, Résultat thérapeutique, Stimulation cérébrale profonde, Surveillance neurophysiologique peropératoire, Thérapie assistée par ordinateur, Électrocorticographie.
English descriptors
- KwdEn :
- Brain Mapping (instrumentation), Brain Mapping (methods), Deep Brain Stimulation (instrumentation), Deep Brain Stimulation (methods), Diagnosis, Computer-Assisted (instrumentation), Diagnosis, Computer-Assisted (methods), Electrocorticography (instrumentation), Electrocorticography (methods), Humans, Intraoperative Neurophysiological Monitoring (instrumentation), Intraoperative Neurophysiological Monitoring (methods), Microelectrodes, Outcome Assessment, Health Care (methods), Parkinson Disease (diagnosis), Parkinson Disease (therapy), Prognosis, Subthalamic Nucleus, Therapy, Computer-Assisted (instrumentation), Therapy, Computer-Assisted (methods), Treatment Outcome.
- MESH :
- diagnosis : Parkinson Disease.
- instrumentation : Brain Mapping, Deep Brain Stimulation, Diagnosis, Computer-Assisted, Electrocorticography, Intraoperative Neurophysiological Monitoring, Therapy, Computer-Assisted.
- methods : Brain Mapping, Deep Brain Stimulation, Diagnosis, Computer-Assisted, Electrocorticography, Intraoperative Neurophysiological Monitoring, Outcome Assessment, Health Care, Therapy, Computer-Assisted.
- therapy : Parkinson Disease.
- Humans, Microelectrodes, Prognosis, Subthalamic Nucleus, Treatment Outcome.
Abstract
We present a random forest (RF) classification and regression technique to predict, intraoperatively, the unified Parkinson's disease rating scale (UPDRS) improvement after deep brain stimulation (DBS). We hypothesized that a data-informed combination of features extracted from intraoperative microelectrode recordings (MERs) can predict the motor improvement of Parkinson's disease patients undergoing DBS surgery. We modified the employed RFs to account for unbalanced datasets and multiple observations per patient, and showed, for the first time, that only five neurophysiologically interpretable MER signal features are sufficient for predicting UPDRS improvement. This finding suggests that subthalamic nucleus (STN) electrophysiological signal characteristics are strongly correlated to the extent of motor behavior improvement observed in STN-DBS.
DOI: 10.1109/TBME.2016.2591827
PubMed: 27429431
Affiliations:
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pubmed:27429431Le document en format XML
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