Automated Talairach atlas-based parcellation and measurement of cerebral lobes in children

Wendy R. Kates, Ilana S. Warsofsky, Anil Patwardhan, Michael T. Abrams, Alex M.C. Liu, Sakku Bai Naidu, Walter E. Kaufmann, Allan L. Reiss

Research output: Contribution to journalArticlepeer-review

Abstract

This study applied a Talairach-based automated parcellation method, originally proposed for adults, to the measurement of lobar brain regions in pediatric study groups. Manual measures of lobar brain regions in a sample of 15 healthy boys, girls and adults were used initially to revise the original Talairach-based grid to increase its applicability to pediatric brains. The applicability of the revised Talairach grid was then tested on an independent sample of five girls with Rett syndrome. As Tables 3 and 4 in the text demonstrate, sensitivity, specificity and positive predictive values either remained unchanged or increased as a result of revising the sectors to fit the brains of children. High levels of sensitivity and specificity were achieved for all revised Talairach-based calculations in relation to the manual measures. Both positive predictive values and intraclass correlations between volumetric measures produced by the revised automated and manual methods varied with the relative size of the brain region. Values were relatively low for smaller structures such as the brainstem and subcortical region, and high for lobar regions. These results suggest that the automated Talairach atlas-based parcellation method can produce sensitive and specific volumetric measures of lobar brain regions in both normal children and children with brain disorders. Accordingly, the method holds much promise for facilitating quantitative pediatric neuroimaging research. Copyright (C) 1999 Elsevier Science Ireland Ltd.

Original languageEnglish (US)
Pages (from-to)11-30
Number of pages20
JournalPsychiatry Research - Neuroimaging
Volume91
Issue number1
DOIs
StatePublished - Dec 1 1999

Keywords

  • Brain parcellation
  • Pediatric
  • Positive predictive value
  • Sensitivity
  • Specificity

ASJC Scopus subject areas

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

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