Automatic Assessment of Craniofacial Growth in a Mouse Model of Crouzon Syndrome | Signe Strann Thorup, Rasmus Larsen, Tron Andre Darvann, Hildur Olafsdottir, Rasmus Reinhold Paulsen, Nuno Vibe Hermann, Per Larsen, Chad A. Perlyn, Sven Kreiborg
| | Abstract | BACKGROUND & PURPOSE: Crouzon syndrome is characterized by growth disturbances caused by premature craniosynostosis. A mouse model with mutation Fgfr2C342Y, equivalent to the most common Crouzon syndrome mutation (henceforth called the Crouzon mouse model), has a phenotype showing many parallels to the human counterpart. Quantifying growth in the Crouzon mouse model could test hypotheses of the relationship between craniosynostosis and dysmorphology, leading to better understanding of the causes of Crouzon syndrome as well as providing knowledge relevant for surgery planning. METHODS: Automatic non-rigid volumetric image registration was applied to micro-CT scans of ten 4-week and twenty 6-week euthanized mice for growth modeling. Each age group consisted of 50% normal and 50% Crouzon mice. Four 3D mean shapes, one for each mouse-type and age group were created. Extracting a dense field of growth vectors for each mouse-type; growth models were created using linear interpolation and visualized as 3D animations. Spatial regions of significantly different growth were identified using the local False Discovery Rate method, estimating the expected percentage of false predictions in a set of predictions. For all image registrations, the Image Registration Toolkit was used under Licence from Ixico Ltd. RESULTS: Investigation proved growth in the Crouzon group to be inhibited, especially in the nasal and posterior regions of the skull compared to the growth in the normal group, and showed an expansion vertically and laterally in the middle and anterior part of the calvaria. Image registration was used to automatically obtain landmarks, thus, different skull measures could be performed e.g. length, width, height. The registrations were quantitatively validated using expert-placed landmarks. CONCLUSIONS: Image registrations made it possible to automatically quantify and visualize average craniofacial growth in normal and Crouzon mouse models, and significantly different growth patterns were found between the two. The methodology generalizes to quantification of shape and growth in other mouse models, and provides a tool for spatially detailed automatic phenotyping. MAIN OBJECTIVES OF PRESENTATION: We will present a 3D growth model of normal and Crouzon mice, and differences will be statistically and visually compared. | | Type | Conference paper [Abstract] | | Conference | Proceedings of the 66th meeting of the American Cleft Palate-Craniofacial Association | | Year | 2009 pp. 74-75 | | BibTeX data | [bibtex] | | IMM Group(s) | Image Analysis & Computer Graphics |
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