A Novel Method for High-Dimensional Anatomical Mapping of Extra-Axial Cerebrospinal Fluid: Application to the Infant Brain

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  • Mostapha, M.
    • Affiliation: College of Arts and Sciences, Department of Computer Science
  • Kim, S.H.
    • Affiliation: School of Medicine, Department of Psychiatry
  • Evans, A.C.
    • Other Affiliation: McGill University
  • Dager, S.R.
    • Other Affiliation: University of Washington
  • Estes, A.M.
    • Other Affiliation: University of Washington
  • McKinstry, R.C.
    • Other Affiliation: Washington University School of Medicine
  • Botteron, K.N.
    • Other Affiliation: Washington University School of Medicine
  • Gerig, G.
    • Other Affiliation: New York University
  • Pizer, S.M.
    • Affiliation: College of Arts and Sciences, Department of Computer Science
  • Schultz, R.T.
    • Other Affiliation: University of Pennsylvania
  • Hazlett, H.C.
    • Affiliation: School of Medicine, Department of Psychiatry
  • Piven, J.
    • Affiliation: School of Medicine, Department of Psychiatry
  • Girault, J.B.
    • Affiliation: School of Medicine, Department of Psychiatry
  • Shen, M.D.
    • Affiliation: School of Medicine, Department of Psychiatry
  • Styner, M.A.
    • Affiliation: College of Arts and Sciences, Department of Computer Science
Abstract
  • Cerebrospinal fluid (CSF) plays an essential role in early postnatal brain development. Extra-axial CSF (EA-CSF) volume, which is characterized by CSF in the subarachnoid space surrounding the brain, is a promising marker in the early detection of young children at risk for neurodevelopmental disorders. Previous studies have focused on global EA-CSF volume across the entire dorsal extent of the brain, and not regionally-specific EA-CSF measurements, because no tools were previously available for extracting local EA-CSF measures suitable for localized cortical surface analysis. In this paper, we propose a novel framework for the localized, cortical surface-based analysis of EA-CSF. The proposed processing framework combines probabilistic brain tissue segmentation, cortical surface reconstruction, and streamline-based local EA-CSF quantification. The quantitative analysis of local EA-CSF was applied to a dataset of typically developing infants with longitudinal MRI scans from 6 to 24 months of age. There was a high degree of consistency in the spatial patterns of local EA-CSF across age using the proposed methods. Statistical analysis of local EA-CSF revealed several novel findings: several regions of the cerebral cortex showed reductions in EA-CSF from 6 to 24 months of age, and specific regions showed higher local EA-CSF in males compared to females. These age-, sex-, and anatomically-specific patterns of local EA-CSF would not have been observed if only a global EA-CSF measure were utilized. The proposed methods are integrated into a freely available, open-source, cross-platform, user-friendly software tool, allowing neuroimaging labs to quantify local extra-axial CSF in their neuroimaging studies to investigate its role in typical and atypical brain development.
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  • Article
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  • In Copyright
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  • Attribution 3.0 United States
Journal title
  • Frontiers in Neuroscience
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  • 14
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  • 1662-4548
Publisher
  • Frontiers Media S.A.

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