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Robust estimation of sulcal morphology.

Christopher R Madan1

  • 1School of Psychology, University of Nottingham, Nottingham, NG7 2RD, UK. christopher.madan@nottingham.ac.uk.

Brain Informatics
|June 13, 2019
PubMed
Summary

This study introduces a new computational method for measuring sulcal width and depth in brain images. This approach enhances the accuracy and consistency of cortical morphology analysis, particularly for studies on aging.

Keywords:
AgeAtrophyCerebral sulciCortical structureGyrificationSulcal depthSulcal width

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Area of Science:

  • Neuroimaging
  • Computational Neuroscience
  • Brain Morphology Analysis

Background:

  • Cortical morphology is known to vary with individual factors.
  • Current methods for characterizing cortical morphology, such as volume, thickness, surface area, and gyrification, have limitations.
  • Existing approaches for estimating sulcal morphology often require multiple software packages, leading to inconsistencies in landmark localization and boundary definition.

Purpose of the Study:

  • To develop and validate a novel computational approach for estimating sulcal width and depth.
  • To provide a more consistent and reliable method for analyzing sulcal morphology compared to existing techniques.
  • To make this new computational toolbox freely available to the research community.

Main Methods:

  • The developed approach utilizes cortical surface reconstructions generated by FreeSurfer.
  • Sulcal width and depth are computationally estimated using the new method.
  • The approach was demonstrated and validated on three large adult lifespan samples and one sample for test-retest reliability.

Main Results:

  • The study successfully developed a computational method for estimating sulcal width and depth.
  • The approach demonstrated reliability and was applied to analyze sulcal morphology across the adult lifespan in relation to aging.
  • The findings highlight the potential for more consistent and accurate sulcal morphology analysis.

Conclusions:

  • The new computational approach offers a standardized and reliable method for quantifying sulcal morphology.
  • This tool can advance research into brain structure variations, including those related to aging.
  • The freely available toolbox facilitates broader application and further investigation in neuroimaging studies.