Bone Density and Texture from Minimally Post-Processed Knee Radiographs in Subjects with Knee Osteoarthritis

• Published in: Annals of biomedical engineering Vol. 47; no. 5; pp. 1181 - 1190
• Main Authors: Hirvasniemi, Jukka, Niinimäki, Jaakko, Thevenot, Jérôme, Saarakkala, Simo
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.05.2019; Springer Nature B.V
• Subjects: Aged; Arthritis; Biochemistry; Biocompatibility; Biological and Medical Physics; Biomedical and Life Sciences; Biomedical Engineering and Bioengineering; Biomedicine; Biophysics; Bone Density; Bone marrow; Classical Mechanics; Classification; Correlation analysis; Female; Fractal analysis; Humans; Image Processing, Computer-Assisted; Knee; Learning algorithms; Lesions; Machine learning; Male; Middle Aged; Models, Biological; Osteoarthritis; Osteoarthritis, Knee - diagnostic imaging; Post-production processing; Radiographs; Radiography; Signature analysis; Texture; Tibia - diagnostic imaging; Radiography; Knee; Bone texture; Bone density; Osteoarthritis; Bone marrow lesion
• ISSN: 0090-6964; 1573-9686; 1573-9686
• DOI: 10.1007/s10439-019-02227-y

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.