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Leg Med (Tokyo) ; 42: 101646, 2020 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-31751793

RESUMO

The nose is a valuable facial feature for facial recognition and approximation. We propose the use of regression functions to predict nasal profiles comprising the structures around the piriform aperture using CT-based 3D models. We examined craniofacial reconstruction models acquired from computed tomographic images of Korean adults (188 males and 201 females). Eighteen measurements using 16 craniometric landmarks were measured on 3D craniofacial models. We conducted a descriptive analysis with comparisons according to sex, and simple linear regression analyses to obtain regression functions. Using multiple regression analyses with sex and age as independent variables, multiple regression equations were developed with coefficient of determination R2 ranging from 0.314 to 0.724, meaning that the equations for known sex and age were better for the prediction of nasal profiles than equations that assumed only known sex. These equations are useful and practical for reconstructing nasal profiles in forensic analyses.

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