Three-Dimensional Prediction of the Nose for Facial Approximation in a Thai Population

© 2019 American Academy of Forensic Sciences Most of the previous studies about nose prediction were concentrated only some landmarks of the nose. This study aimed to generate prediction equations for ten landmarks of the nose in the midline and alar regions for forensic facial approximation. The si...

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Bibliographic Details
Main Authors: Sumon Thitiorul, Pasuk Mahakkanukrauh, Sukon Prasitwattanaseree, Kriskrai Sitthiseripratip, Anak Iamaroon, Sakarat Na Lampang, Sangsom Prapayasatok
Format: Journal
Published: 2020
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Online Access:https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85076849478&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/67641
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Institution: Chiang Mai University
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Summary:© 2019 American Academy of Forensic Sciences Most of the previous studies about nose prediction were concentrated only some landmarks of the nose. This study aimed to generate prediction equations for ten landmarks of the nose in the midline and alar regions for forensic facial approximation. The six midline landmarks were the sellion, nasion–pronasale posterior, nasion–pronasale anterior, pronasale, nasal drop, and subnasale. The four landmarks of the alar region were the alare, superior alar groove, posterior alar groove, and inferior alar groove. We used the skull landmarks in the nasal, zygomatic, and maxillary bone to predict the landmarks of the nose. Cone-beam computed tomography scans of 108 Thai subjects with normal BMI and age ranging from 21.0 to 50.9 years were obtained in a sitting position. The data were converted into three-dimensional (3-D) images of the skull and face. The Cartesian coordinates of the landmarks of the skull and nose were used to formulate the multiple regression equations. The formulated equations were tested in 24 new subjects. The mean differences in the predicted midline landmarks varied between −0.4 mm and 0.5 mm, whereas those for bilateral landmarks varied between −1.0 mm and 1.4 mm. In conclusion, the prediction equations formulated here will be beneficial for facial approximation of the nose in a Thai population.