Literature DB >> 17418714

Morphometric evaluation of soft-tissue profile shape.

Demetrios J Halazonetis1.   

Abstract

INTRODUCTION: Soft-tissue facial outline has been studied by conventional cephalometric methods, and differences between the 2 sexes have been identified, mainly related to size and timing of growth. However, shape per se was not sufficiently evaluated, especially regarding variability, age-related changes, and sexual dimorphism. The purpose of this study was to evaluate shape variability and sexual dimorphism of the soft-tissue outline by using morphometric methods.
METHODS: Pretreatment lateral cephalograms from 170 consecutive patients (82 male, 88 female) aged 7 to 17 years were used. Fifteen skeletal and 22 soft-tissue landmarks were digitized and processed with Procrustes superimposition and principal component analysis. The principal components (PCs) of the soft-tissue shape were analyzed in relation to age and sex.
RESULTS: The first 8 PCs explained approximately 90% of the total shape variability. The first coefficient (PC1) related to lip, nose, and chin prominence and included 36% of total shape variability. It was significantly correlated to age, but with a low coefficient of determination (r2 = 13%). The second coefficient (PC2) related to facial convexity and explained 18% of shape variability. The next 2 coefficients were mainly related to lower lip shape. Statistically significant sexual dimorphism was detected, but the overall shape differences between the average profiles of boys and girls were minor and barely detectable visually. Shape dimorphism was present both before and after the age of 12 years.
CONCLUSIONS: Shape variability related mainly to relative lip protrusion, convexity of the face, and lower lip shape. Shape differences between the sexes seemed to exist even before the pubertal growth spurt, but they were small. Age changes in shape appeared more significant.

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Year:  2007        PMID: 17418714     DOI: 10.1016/j.ajodo.2005.06.031

Source DB:  PubMed          Journal:  Am J Orthod Dentofacial Orthop        ISSN: 0889-5406            Impact factor:   2.650


  5 in total

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Journal:  Angle Orthod       Date:  2019-08-30       Impact factor: 2.079

2.  A sparse principal component analysis of Class III malocclusions.

Authors:  Tae-Joo Kang; Soo-Heang Eo; HyungJun Cho; Richard E Donatelli; Shin-Jae Lee
Journal:  Angle Orthod       Date:  2019-03-21       Impact factor: 2.079

3.  Components of Adult Class III Malocclusion in an Iranian Population.

Authors:  Roodabeh Koodaryan; Ali Rafighi; Ali Hafezeqoran
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4.  A population-based cross-sectional study of the association between facial morphology and cardiometabolic risk factors in adolescence.

Authors:  Jelena Djordjevic; Debbie A Lawlor; Alexei I Zhurov; Arshed M Toma; Rebecca Playle; Stephen Richmond
Journal:  BMJ Open       Date:  2013-05-28       Impact factor: 2.692

5.  Sub-clustering in skeletal class III malocclusion phenotypes via principal component analysis in a southern European population.

Authors:  L de Frutos-Valle; C Martin; J A Alarcón; J C Palma-Fernández; R Ortega; A Iglesias-Linares
Journal:  Sci Rep       Date:  2020-10-21       Impact factor: 4.379

  5 in total

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