The automatic identification of craniosynostosis using 3D stereophotogrammetry.

Meulstee JW, Verhamme LM, Borstlap WA, Van der Heijden F, De Jong GA, Xi T, Bergé SJ, Delye H, Maal TJ. A new method for three-dimensional evaluation of the cranial shape and the automatic identification of craniosynostosis using 3D stereophotogrammetry. Int J Oral Maxillofac Surg. 2017 Apr 6. pii:S0901-5027(17)31362-0. doi: 10.1016/j.ijom.2017.03.017. [Epub ahead of print]

Abstract

Craniosynostosis is a congenital defect which can result in abnormal cranial morphology. Three dimensional (3D) stereophotogrammetry is potentially an ideal technique for the evaluation of cranial morphology and diagnosis of craniosynostosis because it is fast and harmless. This study presents a new method for objective characterization of the morphological abnormalities of scaphocephaly and trigonocephaly patients using 3D photographs of patients and healthy controls. Sixty 3D photographs of healthy controls in the age range of 3-6 months were superimposed and scaled. Principal component analysis (PCA) was applied to find the mean cranial shape and the cranial shape variation in this normal population. 3D photographs of 20 scaphocephaly and 20 trigonocephaly patients were analysed by this PCA model to test whether cranial deformities of scaphocephaly and trigonocephaly patients could be objectively identified. PCA was used to find the mean cranial shape and the cranial shape variation in the normal population. The PCA model was able to significantly distinguish scaphocephaly and trigonocephaly patients from the normal population. 3D stereophotogrammetry in combination with the presented method can be used to objectively identify and classify the cranial shape of healthy newborns, scaphocephaly and trigonocephaly patients.

Courtesy of:  https://www.mdlinx.com/neurology/medical-news-article/2017/04/19/3d-stereophotogrammetry-3d-imaging-principal-component/7126740/?category=latest&page_id=3