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Towards Linking Diffusion MRI based Macro-and Microstructure Measures with Cortico-Cortical Transmission in Brain Tumor Patients

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  • معلومة اضافية
    • Contributors:
      Computational Imaging of the Central Nervous System (ATHENA); Inria Sophia Antipolis - Méditerranée (CRISAM); Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria); Institut National de Recherche en Informatique et en Automatique (Inria); Centre Hospitalier Universitaire de Nice (CHU Nice); Commissariat à l'énergie atomique et aux énergies alternatives (CEA); Inria Saclay - Ile de France; ANR-16-NEUC-0002,NeuroRef,Building Normative Atlases of Diffusion MRI to Identify Subject-Specific Neuroimaging Abnormalities in Brain Trauma and Post-Traumatic Stress(2016)
    • بيانات النشر:
      HAL CCSD
      Elsevier
    • الموضوع:
      2021
    • Collection:
      HAL-CEA (Commissariat à l'énergie atomique et aux énergies alternatives)
    • نبذة مختصرة :
      International audience ; We aimed to link macro-and microstructure measures of brain white matter obtained from diffusion MRI with effective connectivity measures based on a propagation of cortico-cortical evoked potentials induced with intrasurgical direct electrical stimulation. For this, we compared streamline lengths and log-transformed ratios of streamlines computed from presurgical diffusion-weighted images, and the delays and amplitudes of N1 peaks recorded intrasurgically with electrocorticography electrodes in a pilot study of 9 brain tumor patients. Our results showed positive correlation between these two modalities in the vicinity of the stimulation sites (Pearson coefficient 0.54±0.13 for N1 delays, and 0.47±0.23 for N1 amplitudes), which could correspond to the neural propagation via U-fibers. In addition, we reached high sensitivities (0.78±0.07) and very high specificities (0.93±0.03) in a binary variant of our comparison. Finally, we used the structural connectivity measures to predict the effective connectivity using a multiple linear regression model, and showed a significant role of brain microstructure-related indices in this relation.
    • Relation:
      hal-03015641; https://inria.hal.science/hal-03015641; https://inria.hal.science/hal-03015641/document; https://inria.hal.science/hal-03015641/file/main.pdf
    • الرقم المعرف:
      10.1016/j.neuroimage.2020.117567
    • الدخول الالكتروني :
      https://inria.hal.science/hal-03015641
      https://inria.hal.science/hal-03015641/document
      https://inria.hal.science/hal-03015641/file/main.pdf
      https://doi.org/10.1016/j.neuroimage.2020.117567
    • Rights:
      info:eu-repo/semantics/OpenAccess
    • الرقم المعرف:
      edsbas.4DA8ABC8