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Ann Biomed Eng. 2019 Oct 3. doi: 10.1007/s10439-019-02374-2. [Epub ahead of print]

Quantifying Subresolution 3D Morphology of Bone with Clinical Computed Tomography.

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Research Unit of Medical Imaging, Physics and Technology, University of Oulu, POB 5000, 90014, Oulu, Finland.
Infotech, University of Oulu, Oulu, Finland.
Research Unit of Medical Imaging, Physics and Technology, University of Oulu, POB 5000, 90014, Oulu, Finland.
Medical Research Center, University of Oulu, Oulu, Finland.
Department of Anatomy Physiology and Pharmacology, University of Saskatchewan, Saskatoon, SK, Canada.
Department of Surgery and Intensive Care, Oulu University Hospital, Oulu, Finland.
Department of Laboratory Medicine and Pathobiology, Surgery University of Toronto, Toronto, ON, Canada.
Mount Sinai Hospital, Toronto, ON, Canada.
Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland.
Department of Orthopaedics, Traumatology and Hand Surgery, Kuopio University Hospital, Kuopio, Finland.
Department of Anatomy and Cell Biology, University of Oulu, Oulu, Finland.
Department of Applied Physics, University of Eastern Finland, Kuopio, Finland.
Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland.


The aim of this study was to quantify sub-resolution trabecular bone morphometrics, which are also related to osteoarthritis (OA), from clinical resolution cone beam computed tomography (CBCT). Samples (n = 53) were harvested from human tibiae (N = 4) and femora (N = 7). Grey-level co-occurrence matrix (GLCM) texture and histogram-based parameters were calculated from CBCT imaged trabecular bone data, and compared with the morphometric parameters quantified from micro-computed tomography. As a reference for OA severity, histological sections were subjected to OARSI histopathological grading. GLCM and histogram parameters were correlated to bone morphometrics and OARSI individually. Furthermore, a statistical model of combined GLCM/histogram parameters was generated to estimate the bone morphometrics. Several individual histogram and GLCM parameters had strong associations with various bone morphometrics (|r| > 0.7). The most prominent correlation was observed between the histogram mean and bone volume fraction (r = 0.907). The statistical model combining GLCM and histogram-parameters resulted in even better association with bone volume fraction determined from CBCT data (adjusted R2 change = 0.047). Histopathology showed mainly moderate associations with bone morphometrics (|r| > 0.4). In conclusion, we demonstrated that GLCM- and histogram-based parameters from CBCT imaged trabecular bone (ex vivo) are associated with sub-resolution morphometrics. Our results suggest that sub-resolution morphometrics can be estimated from clinical CBCT images, associations becoming even stronger when combining histogram and GLCM-based parameters.


Cone beam computed tomography; Grey-level co-occurrence matrix; Imaging; Micro-computed tomography; Osteoarthritis; Textural analysis


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