Application of an automated parcellation method to the analysis of pediatric brain volumes

Desmond M. Kaplan, Alex M.C. Liu, Michael T. Abrams, Ilana S. Warsofsky, Wendy R. Kates, Christopher D. White, Walter E. Kaufmann, Allan L. Reiss

Research output: Contribution to journalArticlepeer-review

Abstract

New techniques in quantitative imaging are needed to accelerate understanding of brain development and function in children. In this study we evaluate the reliability and validity of an automated parcellation method for the measurement of large and small brain regions in normal and developmentally disabled children. We utilized an adaptation of the Talairach atlas to semi-automatically quantify brain volumes from 10 children with fragile X syndrome, 10 age- and gender-matched controls and 10 adult controls comparing them to 'gold standard' manually delineated regions. Excellent sensitivity, specificity, intra-class correlation and positive predictive value were achieved for large structures although results were less satisfactory for smaller structures, illustrating the limits of resolution of the method. Statistically significant differences in regional brain volumes were shown between males and females, children and adults, and individuals with fragile X and matched controls. This study demonstrates an automated method which rapidly and accurately quantifies large neuroanatomical structures, but not smaller structures. This method is sufficiently accurate to demonstrate some known anatomical differences in individuals with fragile X; the results suggest that this method could be applied to the assessment of brain volume in other neurodevelopmental disabilities.

Original languageEnglish (US)
Pages (from-to)15-27
Number of pages13
JournalPsychiatry Research - Neuroimaging
Volume76
Issue number1
DOIs
StatePublished - Nov 28 1997

Keywords

  • Magnetic resonance imaging
  • Morphometric analysis
  • Talairach atlas

ASJC Scopus subject areas

  • Neuroscience (miscellaneous)
  • Radiology Nuclear Medicine and imaging
  • Psychiatry and Mental health

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