Bone density and texture from minimally post-processed knee radiographs in subjects with knee osteoarthritis
Hirvasniemi, Jukka; Niinimäki, Jaakko; Thevenot, Jérôme; Saarakkala, Simo (2019-02-14)
Hirvasniemi, J., Niinimäki, J., Thevenot, J. et al. Ann Biomed Eng (2019) 47: 1181. https://doi.org/10.1007/s10439-019-02227-y
© The Author(s) 2019 Open Access This 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.
https://creativecommons.org/licenses/by/4.0/
https://urn.fi/URN:NBN:fi-fe2019060618830
Tiivistelmä
Abstract
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 FDVer texture parameter and between −0.10 and 0.97 for FDHor. 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.
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