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Bone Density and Texture from Minimally Post-Processed Knee Radiographs in Subjects with Knee Osteoarthritis
Plain radiography is the most common modality to assess the stage of osteoarthritis. Our aims were to assess the relationship of radiography-based bone density and texture between radiographs with minimal and clinical post-processing, and to compare the differences in bone characteristics between co...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6453872/ https://www.ncbi.nlm.nih.gov/pubmed/30767134 http://dx.doi.org/10.1007/s10439-019-02227-y |
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author | Hirvasniemi, Jukka Niinimäki, Jaakko Thevenot, Jérôme Saarakkala, Simo |
author_facet | Hirvasniemi, Jukka Niinimäki, Jaakko Thevenot, Jérôme Saarakkala, Simo |
author_sort | Hirvasniemi, Jukka |
collection | PubMed |
description | Plain radiography is the most common modality to assess the stage of osteoarthritis. Our aims were to assess the relationship of radiography-based bone density and texture between radiographs with minimal and clinical post-processing, and to compare the differences in bone characteristics between controls and subjects with knee osteoarthritis or medial tibial bone marrow lesions (BMLs). Tibial bone density and texture was evaluated from radiographs with both minimal and clinical post-processing in 109 subjects with and without osteoarthritis. Bone texture was evaluated using fractal signature analysis. Significant correlations (p < 0.001) were found in all regions (between 0.94 and 0.97) for calibrated bone density between radiographs with minimal and clinical post-processing. Correlations varied between 0.51 and 0.97 (p < 0.001) for FD(Ver) texture parameter and between − 0.10 and 0.97 for FD(Hor). Bone density and texture were different (p < 0.05) between controls and subjects with osteoarthritis or BMLs mainly in medial tibial regions. When classifying healthy and osteoarthritic subjects using a machine learning-based elastic net model with bone characteristics, area under the receiver operating characteristics (ROCAUC) curve was 0.77. For classifying controls and subjects with BMLs, ROCAUC was 0.85. In conclusion, differences in bone density and texture can be assessed from knee radiographs when using minimal post-processing. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10439-019-02227-y) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6453872 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-64538722019-04-26 Bone Density and Texture from Minimally Post-Processed Knee Radiographs in Subjects with Knee Osteoarthritis Hirvasniemi, Jukka Niinimäki, Jaakko Thevenot, Jérôme Saarakkala, Simo Ann Biomed Eng Article Plain radiography is the most common modality to assess the stage of osteoarthritis. Our aims were to assess the relationship of radiography-based bone density and texture between radiographs with minimal and clinical post-processing, and to compare the differences in bone characteristics between controls and subjects with knee osteoarthritis or medial tibial bone marrow lesions (BMLs). Tibial bone density and texture was evaluated from radiographs with both minimal and clinical post-processing in 109 subjects with and without osteoarthritis. Bone texture was evaluated using fractal signature analysis. Significant correlations (p < 0.001) were found in all regions (between 0.94 and 0.97) for calibrated bone density between radiographs with minimal and clinical post-processing. Correlations varied between 0.51 and 0.97 (p < 0.001) for FD(Ver) texture parameter and between − 0.10 and 0.97 for FD(Hor). Bone density and texture were different (p < 0.05) between controls and subjects with osteoarthritis or BMLs mainly in medial tibial regions. When classifying healthy and osteoarthritic subjects using a machine learning-based elastic net model with bone characteristics, area under the receiver operating characteristics (ROCAUC) curve was 0.77. For classifying controls and subjects with BMLs, ROCAUC was 0.85. In conclusion, differences in bone density and texture can be assessed from knee radiographs when using minimal post-processing. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10439-019-02227-y) contains supplementary material, which is available to authorized users. Springer US 2019-02-14 2019 /pmc/articles/PMC6453872/ /pubmed/30767134 http://dx.doi.org/10.1007/s10439-019-02227-y Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Article Hirvasniemi, Jukka Niinimäki, Jaakko Thevenot, Jérôme Saarakkala, Simo Bone Density and Texture from Minimally Post-Processed Knee Radiographs in Subjects with Knee Osteoarthritis |
title | Bone Density and Texture from Minimally Post-Processed Knee Radiographs in Subjects with Knee Osteoarthritis |
title_full | Bone Density and Texture from Minimally Post-Processed Knee Radiographs in Subjects with Knee Osteoarthritis |
title_fullStr | Bone Density and Texture from Minimally Post-Processed Knee Radiographs in Subjects with Knee Osteoarthritis |
title_full_unstemmed | Bone Density and Texture from Minimally Post-Processed Knee Radiographs in Subjects with Knee Osteoarthritis |
title_short | Bone Density and Texture from Minimally Post-Processed Knee Radiographs in Subjects with Knee Osteoarthritis |
title_sort | bone density and texture from minimally post-processed knee radiographs in subjects with knee osteoarthritis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6453872/ https://www.ncbi.nlm.nih.gov/pubmed/30767134 http://dx.doi.org/10.1007/s10439-019-02227-y |
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