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Applying an automated method of classifying lip morphological traits

OBJECTIVE: To apply an automated computerised method to categorise and determine the prevalence of different types of lip traits, and to explore associations between lip traits and sex differences. DESIGN: Observational descriptive study utilising an automated method of facial assessment. SETTING AN...

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Autores principales: Davies, Kristian James Michael, Richmond, Stephen, Medeiros-Mirra, Renata Jorge, Abbas, Hawraa Hassan, Wilson-Nagrani, Caryl Eleri, Davis, Megan Gael, Zhurov, Alexei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9679330/
https://www.ncbi.nlm.nih.gov/pubmed/35796491
http://dx.doi.org/10.1177/14653125221106489
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author Davies, Kristian James Michael
Richmond, Stephen
Medeiros-Mirra, Renata Jorge
Abbas, Hawraa Hassan
Wilson-Nagrani, Caryl Eleri
Davis, Megan Gael
Zhurov, Alexei
author_facet Davies, Kristian James Michael
Richmond, Stephen
Medeiros-Mirra, Renata Jorge
Abbas, Hawraa Hassan
Wilson-Nagrani, Caryl Eleri
Davis, Megan Gael
Zhurov, Alexei
author_sort Davies, Kristian James Michael
collection PubMed
description OBJECTIVE: To apply an automated computerised method to categorise and determine the prevalence of different types of lip traits, and to explore associations between lip traits and sex differences. DESIGN: Observational descriptive study utilising an automated method of facial assessment. SETTING AND PARTICIPANTS: A total of 4747 children from the Avon Longitudinal Study of Parents and Children (ALSPAC) who each had 3D facial scans carried out at 15 years of age. METHODS: Each of the participants was automatically categorised regarding predetermined lip morphological traits. Descriptive statistics were applied to report the prevalence of the different types of each trait, and chi-square tests were used to investigate sex differences and associations between traits. RESULTS: A total of 4730 individuals were assessed (47% male, 53% female). Eight predetermined lip traits have been reported previously. There were differences in prevalence for all lip traits in male and female patients (all P ⩽ 0.0002), with differences between the sexes described for each trait. For example, a deeply grooved philtrum of average width was more prevalent in boys, and an indentation near the upper vermilion border was more prevalent in girls. Each of the traits was significantly associated with the other traits (all P < 0.0001), with particularly strong associations seen between traits in the same region (e.g. upper lip). Individual associations between traits are reported; for example, a straight lip contour was found to be associated with no true vermilion border in both the upper and lower lip regions. CONCLUSION: The automated computerised method described is an invaluable tool for the categorisation of lip morphological traits. The prevalence of various types of traits has been described. Sexual dimorphism exists for all the lip traits assessed. Generally, each of the traits are associated with all other traits, with individual associations reported.
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spelling pubmed-96793302022-11-23 Applying an automated method of classifying lip morphological traits Davies, Kristian James Michael Richmond, Stephen Medeiros-Mirra, Renata Jorge Abbas, Hawraa Hassan Wilson-Nagrani, Caryl Eleri Davis, Megan Gael Zhurov, Alexei J Orthod Scientific Section OBJECTIVE: To apply an automated computerised method to categorise and determine the prevalence of different types of lip traits, and to explore associations between lip traits and sex differences. DESIGN: Observational descriptive study utilising an automated method of facial assessment. SETTING AND PARTICIPANTS: A total of 4747 children from the Avon Longitudinal Study of Parents and Children (ALSPAC) who each had 3D facial scans carried out at 15 years of age. METHODS: Each of the participants was automatically categorised regarding predetermined lip morphological traits. Descriptive statistics were applied to report the prevalence of the different types of each trait, and chi-square tests were used to investigate sex differences and associations between traits. RESULTS: A total of 4730 individuals were assessed (47% male, 53% female). Eight predetermined lip traits have been reported previously. There were differences in prevalence for all lip traits in male and female patients (all P ⩽ 0.0002), with differences between the sexes described for each trait. For example, a deeply grooved philtrum of average width was more prevalent in boys, and an indentation near the upper vermilion border was more prevalent in girls. Each of the traits was significantly associated with the other traits (all P < 0.0001), with particularly strong associations seen between traits in the same region (e.g. upper lip). Individual associations between traits are reported; for example, a straight lip contour was found to be associated with no true vermilion border in both the upper and lower lip regions. CONCLUSION: The automated computerised method described is an invaluable tool for the categorisation of lip morphological traits. The prevalence of various types of traits has been described. Sexual dimorphism exists for all the lip traits assessed. Generally, each of the traits are associated with all other traits, with individual associations reported. SAGE Publications 2022-07-07 2022-12 /pmc/articles/PMC9679330/ /pubmed/35796491 http://dx.doi.org/10.1177/14653125221106489 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Scientific Section
Davies, Kristian James Michael
Richmond, Stephen
Medeiros-Mirra, Renata Jorge
Abbas, Hawraa Hassan
Wilson-Nagrani, Caryl Eleri
Davis, Megan Gael
Zhurov, Alexei
Applying an automated method of classifying lip morphological traits
title Applying an automated method of classifying lip morphological traits
title_full Applying an automated method of classifying lip morphological traits
title_fullStr Applying an automated method of classifying lip morphological traits
title_full_unstemmed Applying an automated method of classifying lip morphological traits
title_short Applying an automated method of classifying lip morphological traits
title_sort applying an automated method of classifying lip morphological traits
topic Scientific Section
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9679330/
https://www.ncbi.nlm.nih.gov/pubmed/35796491
http://dx.doi.org/10.1177/14653125221106489
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