• World Neurosurg · Sep 2018

    Case Reports

    Predicting Current Thresholds for Pyramidal Tract Activation Using Volume of Activated Tissue Modeling in Patients Undergoing Deep Brain Stimulation Surgery.

    • Katia Bunaux, Mélissa Tir, Jean-Marc Constans, Jean-Michel Macron, Pierre Krystkowiak, and Michel Lefranc.
    • Department of Neurosurgery, Amiens Picardie University Hospital, Amiens, France. Electronic address: Bunaux.Katia@chu-amiens.fr.
    • World Neurosurg. 2018 Sep 1; 117: e692-e697.

    BackgroundThe volume of activated tissue (VTA) model attempts to represent in 3 dimensions the diffusion of the current provided by the deep brain stimulation lead on brain structures. The objective of the present study was to assess the correlations among the VTA, activation of the corticospinal tract, and the intraoperative side effect (ISE) threshold.MethodsThis double-blind, single-center study was performed between September 2016 and July 2017. We identified 2 groups for statistical analysis: the entire study population and a subset of patients with additional diffusion tensor imaging (DTI) data for determining the location of the pyramidal tract. We determined the intensity threshold at which the VTA reached the border of the target nucleus (referred to as the VTAn) and the intensity threshold when the VTA reached the pyramidal tract (VTAndti). In each group of patients, we studied the correlations between the ISE threshold and the VTAn or VTAndti threshold.ResultsFifteen patients were included in the study. In both groups, there was a significant correlation between the VTA intensity threshold and the ISE threshold (P = 0.018; r = 0.31 for VTAn in the entire study population). The correlation was stronger in the subset of patients with valid tractography data (P = 0.002; r = 0.5 for VTAndti).ConclusionsThe present study is the first to show a relationship between the intensity threshold as determined by the use of the VTA and the ISE threshold. The correlation between the clinical features and the VTA appears to be stronger in the model based on a combination of high-resolution anatomic data and interpretable DTI data.Copyright © 2018 Elsevier Inc. All rights reserved.

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