Craniofacial morphometric analysis

TC Tiffany Chern
AA Annita Achilleos
XT Xuefei Tong
MH Matthew C. Hill
AS Alexander B. Saltzman
LR Lucas C. Reineke
AC Arindam Chaudhury
SD Swapan K. Dasgupta
YR Yushi Redhead
DW David Watkins
JN Joel R. Neilson
PT Perumal Thiagarajan
JG Jeremy B. A. Green
AM Anna Malovannaya
JM James F. Martin
DR David S. Rosenblatt
RP Ross A. Poché
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Landmark-free morphometrics analysis was performed as previously described45. Briefly, micro-CT scans were converted into three-dimensional meshes and then aligned using a Procrustes superimposition removing scale differences. The software Deformetrica was then used to “atlas” the entire population to quantify the shape of each individual and visualized graphically through principal component analysis (PCA) to find the principal modes of shape variation80. Morphs were generated by projecting the average mesh into the PCA shape space and deforming towards the means. Centroid sizes were measured and normalized as the square root of the sum of the squared means from each node of the mesh to the centroid divided by the number of nodes81. Heat maps were generated in paraview (ISBN-13: 978-0123875822) using the average morph and color coding whether the mesh polygons decrease or increase in area. Stretch heatmaps were generated by calculating local mesh node density changes under the Deformetrica-generated displacements using previously written code45. Nasal angles were measured by the deviation from the midline from the superior views of each skull using ImageJ. Linear measurements of the craniofacial bones were performed as previously described using ImageJ44. One-way ANOVA with post-hoc Tukey’s multiple comparisons test was used to determine differences between more than 2 groups. Adjusted P values of <0.05 were considered significantly different.

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