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Statistical Analysis of White Matter Integrity for the Clinical Study of Typical Specific Language Impairment in Children

  • Emmanuel Vallée
  • Olivier Commowick
  • Camille Maumet
  • Aymeric Stamm
  • Elisabeth Le Rumeur
  • Catherine Allaire
  • Jean-Christophe Ferré
  • Clément de Guibert
  • Christian Barillot
Conference paper
Part of the Mathematics and Visualization book series (MATHVISUAL)

Abstract

Children affected by Specific Language Impairment (SLI) fail to develop a normal language capability. To date, the etiology of SLI remains largely unknown. It induces difficulties with oral language which cannot be directly attributed to intellectual deficit or other developmental delay. Whereas previous studies on SLI focused on the psychological and genetic aspects of the pathology, few imaging studies investigated defaults in neuroanatomy or brain function. We propose to investigate the integrity of white matter in SLI thanks to diffusion Magnetic Resonance Imaging . An exploratory analysis was performed without a prior on the impaired regions. A region of interest statistical analysis was performed based, first, on regions defined from Catani’s atlas and, then, on tractography-based regions. Both the mean fractional anisotropy and mean apparent diffusion coefficient were compared across groups. To the best of our knowledge, this is the first study focusing on white matter integrity in specific language impairment. Twenty-two children with SLI and 19 typically developing children were involved in this study. Overall, the tractography-based approach to group comparison was more sensitive than the classical ROI-based approach. Group differences between controls and SLI patients included decreases in FA in both the perisylvian and ventral pathways of language, comforting findings from previous functional studies.

Keywords

Apparent Diffusion Coefficient Fractional Anisotropy Specific Language Impairment Oral Language White Matter Integrity 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Emmanuel Vallée
    • 1
  • Olivier Commowick
    • 1
  • Camille Maumet
    • 1
  • Aymeric Stamm
    • 1
  • Elisabeth Le Rumeur
    • 2
  • Catherine Allaire
    • 3
  • Jean-Christophe Ferré
    • 1
    • 2
  • Clément de Guibert
    • 4
    • 5
  • Christian Barillot
    • 1
  1. 1.Inria, INSERM, VisAGeS U746 Unit/ProjectRennesFrance
  2. 2.Department of NeuroradiologyUniversity HospitalRennesFrance
  3. 3.Centre Toul-arC’hoatChateaulinFrance
  4. 4.LAS-EA 2241, European University of Brittany-Rennes 2RennesFrance
  5. 5.Regional center for language and learning disordersUniversity HospitalRennesFrance

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