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Towards linking diffusion MRI based macro- and microstructure measures with cortico-cortical transmission in brain tumor patients.
Filipiak, Patryk; Almairac, Fabien; Papadopoulo, Théodore; Fontaine, Denys; Mondot, Lydiane; Chanalet, Stéphane; Deriche, Rachid; Clerc, Maureen; Wassermann, Demian.
Afiliación
  • Filipiak P; INRIA, Université Côte d'Azur, France. Electronic address: patryk.filipiak@inria.fr.
  • Almairac F; Service de Neurochirurgie, CHU de Nice, Université Côte d'Azur, France.
  • Papadopoulo T; INRIA, Université Côte d'Azur, France.
  • Fontaine D; Service de Neurochirurgie, CHU de Nice, Université Côte d'Azur, France.
  • Mondot L; Service de Radiologie, CHU de Nice, Université Côte d'Azur, France.
  • Chanalet S; Service de Radiologie, CHU de Nice, Université Côte d'Azur, France.
  • Deriche R; INRIA, Université Côte d'Azur, France.
  • Clerc M; INRIA, Université Côte d'Azur, France.
  • Wassermann D; INRIA, Université Côte d'Azur, France; INRIA, CEA, Université Paris-Saclay, France.
Neuroimage ; 226: 117567, 2021 02 01.
Article en En | MEDLINE | ID: mdl-33221443
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.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Neoplasias Encefálicas / Corteza Cerebral / Imagen de Difusión por Resonancia Magnética / Potenciales Evocados / Sustancia Blanca / Electrocorticografía Tipo de estudio: Prognostic_studies Límite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Neuroimage Asunto de la revista: DIAGNOSTICO POR IMAGEM Año: 2021 Tipo del documento: Article

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Neoplasias Encefálicas / Corteza Cerebral / Imagen de Difusión por Resonancia Magnética / Potenciales Evocados / Sustancia Blanca / Electrocorticografía Tipo de estudio: Prognostic_studies Límite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Neuroimage Asunto de la revista: DIAGNOSTICO POR IMAGEM Año: 2021 Tipo del documento: Article