28 February 2013 An optimal set of landmarks for metopic craniosynostosis diagnosis from shape analysis of pediatric CT scans of the head
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Proceedings Volume 8670, Medical Imaging 2013: Computer-Aided Diagnosis; 86702T (2013) https://doi.org/10.1117/12.2008039
Event: SPIE Medical Imaging, 2013, Lake Buena Vista (Orlando Area), Florida, United States
Abstract
Craniosynostosis (premature fusion of skull sutures) is a severe condition present in one of every 2000 newborns. Metopic craniosynostosis, accounting for 20-27% of cases, is diagnosed qualitatively in terms of skull shape abnormality, a subjective call of the surgeon. In this paper we introduce a new quantitative diagnostic feature for metopic craniosynostosis derived optimally from shape analysis of CT scans of the skull. We built a robust shape analysis pipeline that is capable of obtaining local shape differences in comparison to normal anatomy. Spatial normalization using 7-degree-of-freedom registration of the base of the skull is followed by a novel bone labeling strategy based on graph-cuts according to labeling priors. The statistical shape model built from 94 normal subjects allows matching a patient's anatomy to its most similar normal subject. Subsequently, the computation of local malformations from a normal subject allows characterization of the points of maximum malformation on each of the frontal bones adjacent to the metopic suture, and on the suture itself. Our results show that the malformations at these locations vary significantly (p<0.001) between abnormal/normal subjects and that an accurate diagnosis can be achieved using linear regression from these automatic measurements with an area under the curve for the receiver operating characteristic of 0.97.
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Carlos S. Mendoza, Nabile Safdar, Emmarie Myers, Tanakorn Kittisarapong, Gary F. Rogers, Marius George Linguraru, "An optimal set of landmarks for metopic craniosynostosis diagnosis from shape analysis of pediatric CT scans of the head", Proc. SPIE 8670, Medical Imaging 2013: Computer-Aided Diagnosis, 86702T (28 February 2013); doi: 10.1117/12.2008039; https://doi.org/10.1117/12.2008039
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