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1.
Sci Rep ; 11(1): 12175, 2021 06 09.
Artigo em Inglês | MEDLINE | ID: mdl-34108542

RESUMO

Craniofacial dysmorphism is associated with thousands of genetic and environmental disorders. Delineation of salient facial characteristics can guide clinicians towards a correct clinical diagnosis and understanding the pathogenesis of the disorder. Abnormal facial shape might require craniofacial surgical intervention, with the restoration of normal shape an important surgical outcome. Facial anthropometric growth curves or standards of single inter-landmark measurements have traditionally supported assessments of normal and abnormal facial shape, for both clinical and research applications. However, these fail to capture the full complexity of facial shape. With the increasing availability of 3D photographs, methods of assessment that take advantage of the rich information contained in such images are needed. In this article we derive and present open-source three-dimensional (3D) growth curves of the human face. These are sequences of age and sex-specific expected 3D facial shapes and statistical models of the variation around the expected shape, derived from 5443 3D images. We demonstrate the use of these growth curves for assessing patients and show that they identify normal and abnormal facial morphology independent from age-specific facial features. 3D growth curves can facilitate use of state-of-the-art 3D facial shape assessment by the broader clinical and biomedical research community. This advance in phenotype description will support clinical diagnosis and the understanding of disease pathogenesis including genotype-phenotype relations.


Assuntos
Anormalidades Múltiplas/patologia , Anormalidades Craniofaciais/patologia , Face/patologia , Imageamento Tridimensional/métodos , Modelos Estatísticos , Atrofia Muscular/patologia , Anormalidades Múltiplas/genética , Anormalidades Múltiplas/metabolismo , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Antropometria , Estudos de Casos e Controles , Criança , Pré-Escolar , Anormalidades Craniofaciais/genética , Anormalidades Craniofaciais/metabolismo , Face/anormalidades , Feminino , Seguimentos , Gráficos de Crescimento , Humanos , Lactente , Masculino , Pessoa de Meia-Idade , Atrofia Muscular/genética , Atrofia Muscular/metabolismo , Fenótipo , Prognóstico , Adulto Jovem
2.
Front Public Health ; 5: 31, 2017.
Artigo em Inglês | MEDLINE | ID: mdl-28443272

RESUMO

Precision public health is a new field driven by technological advances that enable more precise descriptions and analyses of individuals and population groups, with a view to improving the overall health of populations. This promises to lead to more precise clinical and public health practices, across the continuum of prevention, screening, diagnosis, and treatment. A phenotype is the set of observable characteristics of an individual resulting from the interaction of a genotype with the environment. Precision (deep) phenotyping applies innovative technologies to exhaustively and more precisely examine the discrete components of a phenotype and goes beyond the information usually included in medical charts. This form of phenotyping is a critical component of more precise diagnostic capability and 3-dimensional facial analysis (3DFA) is a key technological enabler in this domain. In this paper, we examine the potential of 3DFA as a public health tool, by viewing it against the 10 essential public health services of the "public health wheel," developed by the US Centers for Disease Control. This provides an illustrative framework to gage current and emergent applications of genomic technologies for implementing precision public health.

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