Landmarking the brain for geometric morphometric analysis: An error study

Madeleine B. Chollet, Kristina Aldridge, Nicole Pangborn, Seth M. Weinberg, Valerie B. DeLeon

Research output: Contribution to journalArticle

Abstract

Neuroanatomic phenotypes are often assessed using volumetric analysis. Although powerful and versatile, this approach is limited in that it is unable to quantify changes in shape, to describe how regions are interrelated, or to determine whether changes in size are global or local. Statistical shape analysis using coordinate data from biologically relevant landmarks is the preferred method for testing these aspects of phenotype. To date, approximately fifty landmarks have been used to study brain shape. Of the studies that have used landmark-based statistical shape analysis of the brain, most have not published protocols for landmark identification or the results of reliability studies on these landmarks. The primary aims of this study were two-fold: (1) to collaboratively develop detailed data collection protocols for a set of brain landmarks, and (2) to complete an intra- and inter-observer validation study of the set of landmarks. Detailed protocols were developed for 29 cortical and subcortical landmarks using a sample of 10 boys aged 12 years old. Average intra-observer error for the final set of landmarks was 1.9 mm with a range of 0.72 mm-5.6 mm. Average inter-observer error was 1.1 mm with a range of 0.40 mm-3.4 mm. This study successfully establishes landmark protocols with a minimal level of error that can be used by other researchers in the assessment of neuroanatomic phenotypes.

Original languageEnglish (US)
Article numbere86005
JournalPLoS One
Volume9
Issue number1
DOIs
StatePublished - Jan 28 2014

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

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    Chollet, M. B., Aldridge, K., Pangborn, N., Weinberg, S. M., & DeLeon, V. B. (2014). Landmarking the brain for geometric morphometric analysis: An error study. PLoS One, 9(1), [e86005]. https://doi.org/10.1371/journal.pone.0086005