Cargando…

Body height estimation from automated length measurements on standing long leg radiographs using artificial intelligence

Artificial-intelligence (AI) allows large-scale analyses of long-leg-radiographs (LLRs). We used this technology to derive an update for the classical regression formulae by Trotter and Gleser, which are frequently used to infer stature based on long-bone measurements. We analyzed calibrated, standi...

Descripción completa

Detalles Bibliográficos
Autores principales: Simon, Sebastian, Fischer, Barbara, Rinner, Alexandra, Hummer, Allan, Frank, Bernhard J. H., Mitterer, Jennyfer A., Huber, Stephanie, Aichmair, Alexander, Schwarz, Gilbert M., Hofstaetter, Jochen G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10213042/
https://www.ncbi.nlm.nih.gov/pubmed/37231033
http://dx.doi.org/10.1038/s41598-023-34670-2
_version_ 1785047543233642496
author Simon, Sebastian
Fischer, Barbara
Rinner, Alexandra
Hummer, Allan
Frank, Bernhard J. H.
Mitterer, Jennyfer A.
Huber, Stephanie
Aichmair, Alexander
Schwarz, Gilbert M.
Hofstaetter, Jochen G.
author_facet Simon, Sebastian
Fischer, Barbara
Rinner, Alexandra
Hummer, Allan
Frank, Bernhard J. H.
Mitterer, Jennyfer A.
Huber, Stephanie
Aichmair, Alexander
Schwarz, Gilbert M.
Hofstaetter, Jochen G.
author_sort Simon, Sebastian
collection PubMed
description Artificial-intelligence (AI) allows large-scale analyses of long-leg-radiographs (LLRs). We used this technology to derive an update for the classical regression formulae by Trotter and Gleser, which are frequently used to infer stature based on long-bone measurements. We analyzed calibrated, standing LLRs from 4200 participants taken between 2015 and 2020. Automated landmark placement was conducted using the AI-algorithm LAMA™ and the measurements were used to determine femoral, tibial and total leg-length. Linear regression equations were subsequently derived for stature estimation. The estimated regression equations have a shallower slope and larger intercept in males and females (Femur-male: slope = 2.08, intercept = 77.49; Femur-female: slope = 1.9, intercept = 79.81) compared to the formulae previously derived by Trotter and Gleser 1952 (Femur-male: slope = 2.38, intercept = 61.41; Femur-female: slope = 2.47, intercept = 54.13) and Trotter and Gleser 1958 (Femur-male: slope = 2.32, intercept = 65.53). All long-bone measurements showed a high correlation (r ≥ 0.76) with stature. The linear equations we derived tended to overestimate stature in short persons and underestimate stature in tall persons. The differences in slopes and intercepts from those published by Trotter and Gleser (1952, 1958) may result from an ongoing secular increase in stature. Our study illustrates that AI-algorithms are a promising new tool enabling large-scale measurements.
format Online
Article
Text
id pubmed-10213042
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-102130422023-05-27 Body height estimation from automated length measurements on standing long leg radiographs using artificial intelligence Simon, Sebastian Fischer, Barbara Rinner, Alexandra Hummer, Allan Frank, Bernhard J. H. Mitterer, Jennyfer A. Huber, Stephanie Aichmair, Alexander Schwarz, Gilbert M. Hofstaetter, Jochen G. Sci Rep Article Artificial-intelligence (AI) allows large-scale analyses of long-leg-radiographs (LLRs). We used this technology to derive an update for the classical regression formulae by Trotter and Gleser, which are frequently used to infer stature based on long-bone measurements. We analyzed calibrated, standing LLRs from 4200 participants taken between 2015 and 2020. Automated landmark placement was conducted using the AI-algorithm LAMA™ and the measurements were used to determine femoral, tibial and total leg-length. Linear regression equations were subsequently derived for stature estimation. The estimated regression equations have a shallower slope and larger intercept in males and females (Femur-male: slope = 2.08, intercept = 77.49; Femur-female: slope = 1.9, intercept = 79.81) compared to the formulae previously derived by Trotter and Gleser 1952 (Femur-male: slope = 2.38, intercept = 61.41; Femur-female: slope = 2.47, intercept = 54.13) and Trotter and Gleser 1958 (Femur-male: slope = 2.32, intercept = 65.53). All long-bone measurements showed a high correlation (r ≥ 0.76) with stature. The linear equations we derived tended to overestimate stature in short persons and underestimate stature in tall persons. The differences in slopes and intercepts from those published by Trotter and Gleser (1952, 1958) may result from an ongoing secular increase in stature. Our study illustrates that AI-algorithms are a promising new tool enabling large-scale measurements. Nature Publishing Group UK 2023-05-25 /pmc/articles/PMC10213042/ /pubmed/37231033 http://dx.doi.org/10.1038/s41598-023-34670-2 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Simon, Sebastian
Fischer, Barbara
Rinner, Alexandra
Hummer, Allan
Frank, Bernhard J. H.
Mitterer, Jennyfer A.
Huber, Stephanie
Aichmair, Alexander
Schwarz, Gilbert M.
Hofstaetter, Jochen G.
Body height estimation from automated length measurements on standing long leg radiographs using artificial intelligence
title Body height estimation from automated length measurements on standing long leg radiographs using artificial intelligence
title_full Body height estimation from automated length measurements on standing long leg radiographs using artificial intelligence
title_fullStr Body height estimation from automated length measurements on standing long leg radiographs using artificial intelligence
title_full_unstemmed Body height estimation from automated length measurements on standing long leg radiographs using artificial intelligence
title_short Body height estimation from automated length measurements on standing long leg radiographs using artificial intelligence
title_sort body height estimation from automated length measurements on standing long leg radiographs using artificial intelligence
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10213042/
https://www.ncbi.nlm.nih.gov/pubmed/37231033
http://dx.doi.org/10.1038/s41598-023-34670-2
work_keys_str_mv AT simonsebastian bodyheightestimationfromautomatedlengthmeasurementsonstandinglonglegradiographsusingartificialintelligence
AT fischerbarbara bodyheightestimationfromautomatedlengthmeasurementsonstandinglonglegradiographsusingartificialintelligence
AT rinneralexandra bodyheightestimationfromautomatedlengthmeasurementsonstandinglonglegradiographsusingartificialintelligence
AT hummerallan bodyheightestimationfromautomatedlengthmeasurementsonstandinglonglegradiographsusingartificialintelligence
AT frankbernhardjh bodyheightestimationfromautomatedlengthmeasurementsonstandinglonglegradiographsusingartificialintelligence
AT mittererjennyfera bodyheightestimationfromautomatedlengthmeasurementsonstandinglonglegradiographsusingartificialintelligence
AT huberstephanie bodyheightestimationfromautomatedlengthmeasurementsonstandinglonglegradiographsusingartificialintelligence
AT aichmairalexander bodyheightestimationfromautomatedlengthmeasurementsonstandinglonglegradiographsusingartificialintelligence
AT schwarzgilbertm bodyheightestimationfromautomatedlengthmeasurementsonstandinglonglegradiographsusingartificialintelligence
AT hofstaetterjocheng bodyheightestimationfromautomatedlengthmeasurementsonstandinglonglegradiographsusingartificialintelligence