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Describing the application of statistical shape modelling to DXA images to quantify the shape of the proximal femur at ages 14 and 18 years in the Avon Longitudinal Study of Parents and Children
Bones are complex objects with considerable variation in the shape and structure often attributed to anatomical, environmental or genetic differences. In addition, bone shape has been of interest in relation to its associations with disease processes. Hip shape is an important determinant of hip ost...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
F1000 Research Limited
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6733378/ https://www.ncbi.nlm.nih.gov/pubmed/31523721 http://dx.doi.org/10.12688/wellcomeopenres.15092.2 |
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author | Frysz, Monika Gregory, Jenny S. Aspden, Richard M. Paternoster, Lavinia Tobias, Jonathan H. |
author_facet | Frysz, Monika Gregory, Jenny S. Aspden, Richard M. Paternoster, Lavinia Tobias, Jonathan H. |
author_sort | Frysz, Monika |
collection | PubMed |
description | Bones are complex objects with considerable variation in the shape and structure often attributed to anatomical, environmental or genetic differences. In addition, bone shape has been of interest in relation to its associations with disease processes. Hip shape is an important determinant of hip osteoarthritis and osteoporotic hip fracture; however, its quantification is difficult. While previous studies largely focused on individual geometrical indices of hip geometry such as neck-shaft angle or femoral neck width, statistical shape modelling offers the means to quantify the entire contour of the proximal femur, including lesser trochanter and acetabular eyebrow. We describe the derivation of independent modes of variation (hip shape mode scores) to characterise variation in hip shape from dual-energy X-ray absorptiometry (DXA) images in the Avon Longitudinal Study of Parents and Children (ALSPAC) offspring, using statistical shape modelling. ALSPAC is a rich source of phenotypic and genotypic data which provides a unique opportunity to investigate the environmental and genetic influences on hip shape in adolescence, as well as comparison with adult hip shape. |
format | Online Article Text |
id | pubmed-6733378 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | F1000 Research Limited |
record_format | MEDLINE/PubMed |
spelling | pubmed-67333782019-09-13 Describing the application of statistical shape modelling to DXA images to quantify the shape of the proximal femur at ages 14 and 18 years in the Avon Longitudinal Study of Parents and Children Frysz, Monika Gregory, Jenny S. Aspden, Richard M. Paternoster, Lavinia Tobias, Jonathan H. Wellcome Open Res Data Note Bones are complex objects with considerable variation in the shape and structure often attributed to anatomical, environmental or genetic differences. In addition, bone shape has been of interest in relation to its associations with disease processes. Hip shape is an important determinant of hip osteoarthritis and osteoporotic hip fracture; however, its quantification is difficult. While previous studies largely focused on individual geometrical indices of hip geometry such as neck-shaft angle or femoral neck width, statistical shape modelling offers the means to quantify the entire contour of the proximal femur, including lesser trochanter and acetabular eyebrow. We describe the derivation of independent modes of variation (hip shape mode scores) to characterise variation in hip shape from dual-energy X-ray absorptiometry (DXA) images in the Avon Longitudinal Study of Parents and Children (ALSPAC) offspring, using statistical shape modelling. ALSPAC is a rich source of phenotypic and genotypic data which provides a unique opportunity to investigate the environmental and genetic influences on hip shape in adolescence, as well as comparison with adult hip shape. F1000 Research Limited 2019-08-27 /pmc/articles/PMC6733378/ /pubmed/31523721 http://dx.doi.org/10.12688/wellcomeopenres.15092.2 Text en Copyright: © 2019 Frysz M et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Data Note Frysz, Monika Gregory, Jenny S. Aspden, Richard M. Paternoster, Lavinia Tobias, Jonathan H. Describing the application of statistical shape modelling to DXA images to quantify the shape of the proximal femur at ages 14 and 18 years in the Avon Longitudinal Study of Parents and Children |
title | Describing the application of statistical shape modelling to DXA images to quantify the shape of the proximal femur at ages 14 and 18 years in the Avon Longitudinal Study of Parents and Children |
title_full | Describing the application of statistical shape modelling to DXA images to quantify the shape of the proximal femur at ages 14 and 18 years in the Avon Longitudinal Study of Parents and Children |
title_fullStr | Describing the application of statistical shape modelling to DXA images to quantify the shape of the proximal femur at ages 14 and 18 years in the Avon Longitudinal Study of Parents and Children |
title_full_unstemmed | Describing the application of statistical shape modelling to DXA images to quantify the shape of the proximal femur at ages 14 and 18 years in the Avon Longitudinal Study of Parents and Children |
title_short | Describing the application of statistical shape modelling to DXA images to quantify the shape of the proximal femur at ages 14 and 18 years in the Avon Longitudinal Study of Parents and Children |
title_sort | describing the application of statistical shape modelling to dxa images to quantify the shape of the proximal femur at ages 14 and 18 years in the avon longitudinal study of parents and children |
topic | Data Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6733378/ https://www.ncbi.nlm.nih.gov/pubmed/31523721 http://dx.doi.org/10.12688/wellcomeopenres.15092.2 |
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