Regional brain development analysis through registration using anisotropic similarity, a constrained affine transformation

• Published in: PloS one Vol. 15; no. 2; p. e0214174
• Main Authors: Legouhy, Antoine, Commowick, Olivier, Proisy, Maïa, Rousseau, François, Barillot, Christian
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 24.02.2020; Public Library of Science (PLoS)
• Subjects: Adolescent; Affine transformations; Age; Algorithms; Anisotropy; Automation; Bioengineering; Biology and Life Sciences; Brain; Brain - diagnostic imaging; Brain - growth & development; Child; Child, Preschool; Female; Females; Human health and pathology; Humans; Image Processing, Computer-Assisted - methods; Imaging; Infant; Infant, Newborn; Life Sciences; Magnetic Resonance Imaging - methods; Male; Medical imaging equipment; Medicine and Health Sciences; Neuroimaging; Neurons and Cognition; Novels; Open source software; Optimization; Pediatrics; Physical Sciences; Regional analysis; Regional development; Registration; Research and Analysis Methods; Scaling; Scaling factors; Similarity; Transformation; Volumetric analysis; Young Adult; France
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0214174

We propose a novel method to quantify brain growth in 3 arbitrary orthogonal directions of the brain or its sub-regions through linear registration. This is achieved by introducing a 9 degrees of freedom (dof) transformation called anisotropic similarity which is an affine transformation with constrained scaling directions along arbitrarily chosen orthogonal vectors. This gives the opportunity to extract scaling factors describing brain growth along those directions by registering a database of subjects onto a common reference. This information about directional growth brings insights that are not usually available in longitudinal volumetric analysis. The interest of this method is illustrated by studying the anisotropic regional and global brain development of 308 healthy subjects betwen 0 and 19 years old. A gender comparison of those scaling factors is also performed for four age-intervals. We demonstrate through these applications the stability of the method to the chosen reference and its ability to highlight growth differences accros regions and gender.