A gyrification analysis approach based on Laplace Beltrami eigenfunction level sets

Rosita Shishegar; Fabrizio Pizzagalli; Nellie Georgiou-Karistianis; Gary F Egan; Neda Jahanshad; Leigh A Johnston

doi:10.1016/j.neuroimage.2021.117751

A gyrification analysis approach based on Laplace Beltrami eigenfunction level sets

Neuroimage. 2021 Apr 1:229:117751. doi: 10.1016/j.neuroimage.2021.117751. Epub 2021 Jan 15.

Authors

Rosita Shishegar¹, Fabrizio Pizzagalli², Nellie Georgiou-Karistianis³, Gary F Egan⁴, Neda Jahanshad⁵, Leigh A Johnston⁶

Affiliations

¹ School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Melbourne, Australia; Monash Biomedical Imaging, Monash University, Melbourne, Australia; Department of Biomedical Engineering, University of Melbourne, Melbourne, Australia; The Australian e-Health Research Centre, CSIRO, Melbourne, Australia. Electronic address: rosita.shishegar@monash.edu.
² Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA; Department of Neurosciences, University of Turin, Italy.
³ School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Melbourne, Australia.
⁴ School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Melbourne, Australia; Monash Biomedical Imaging, Monash University, Melbourne, Australia.
⁵ Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA.
⁶ Department of Biomedical Engineering, University of Melbourne, Melbourne, Australia; Melbourne Brain Centre Imaging Unit, University of Melbourne, Melbourne, Australia.

Abstract

An accurate measure of the complexity of patterns of cortical folding or gyrification is necessary for understanding normal brain development and neurodevelopmental disorders. Conventional gyrification indices (GIs) are calculated based on surface curvature (curvature-based GI) or an outer hull surface of the cortex (outer surface-based GI). The latter is dependent on the definition of the outer hull surface and a corresponding function between surfaces. In the present study, we propose the Laplace Beltrami-based gyrification index (LB-GI). This is a new curvature-based local GI computed using the first three Laplace Beltrami eigenfunction level sets. As with outer surface-based GI methods, this method is based on the hypothesis that gyrification stems from a flat surface during development. However, instead of quantifying gyrification with reference to corresponding points on an outer hull surface, LB-GI quantifies the gyrification at each point on the cortical surface with reference to their surrounding gyral points, overcoming several shortcomings of existing methods. The LB-GI was applied to investigate the cortical maturation profile of the human brain from preschool to early adulthood using the PING database. The results revealed more detail in patterns of cortical folding than conventional curvature-based methods, especially on frontal and posterior tips of the brain, such as the frontal pole, lateral occipital, lateral cuneus, and lingual. Negative associations of cortical folding with age were observed at cortical regions, including bilateral lingual, lateral occipital, precentral gyrus, postcentral gyrus, and superior frontal gyrus. The results also indicated positive significant associations between age and the LB-GI of bilateral insula, the medial orbitofrontal, frontal pole and rostral anterior cingulate regions. It is anticipated that the LB-GI will be advantageous in providing further insights in the understanding of brain development and degeneration in large clinical neuroimaging studies.

Keywords: Brain development; Cortical folding; Curvature; Laplace Beltrami operator; Local gyrification index.

MeSH terms

Adolescent
Cerebral Cortex / diagnostic imaging*
Cerebral Cortex / growth & development*
Child
Child, Preschool
Female
Humans
Image Processing, Computer-Assisted / methods*
Magnetic Resonance Imaging / methods*
Male
Young Adult

Grants and funding

P41 EB015922/EB/NIBIB NIH HHS/United States