University of Oulu

Karhula, S.S., Finnilä, M.A.J., Rytky, S.J.O. et al. Quantifying Subresolution 3D Morphology of Bone with Clinical Computed Tomography. Ann Biomed Eng 48, 595–605 (2020). https://doi.org/10.1007/s10439-019-02374-2

Quantifying subresolution 3D morphology of bone with clinical computed tomography

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Author: Karhula, S. S.1,2; Finnilä, M. A. J.1,3; Rytky, S. J. O.1;
Organizations: 1Research Unit of Medical Imaging, Physics and Technology, University of Oulu, POB 5000, 90014, Oulu, Finland
2Infotech, University of Oulu, Oulu, Finland
3Medical Research Center, University of Oulu, Oulu, Finland
4Department of Anatomy Physiology and Pharmacology, University of Saskatchewan, Saskatoon, SK, Canada
5Department of Surgery and Intensive Care, Oulu University Hospital, Oulu, Finland
6Department of Laboratory Medicine and Pathobiology, Surgery University of Toronto, Toronto, ON, Canada
7Mount Sinai Hospital, Toronto, ON, Canada
8Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
9Department of Orthopaedics, Traumatology and Hand Surgery, Kuopio University Hospital, Kuopio, Finland
10Department of Anatomy and Cell Biology, University of Oulu, Oulu, Finland
11Department of Applied Physics, University of Eastern Finland, Kuopio, Finland
12Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 1.1 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2020041718949
Language: English
Published: Springer Nature, 2020
Publish Date: 2020-04-17
Description:

Abstract

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.

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Series: Annals of biomedical engineering
ISSN: 0090-6964
ISSN-E: 1573-9686
ISSN-L: 0090-6964
Volume: 48
Issue: 2
Pages: 595 - 605
DOI: 10.1007/s10439-019-02374-2
OADOI: https://oadoi.org/10.1007/s10439-019-02374-2
Type of Publication: A1 Journal article – refereed
Field of Science: 3126 Surgery, anesthesiology, intensive care, radiology
Subjects:
Funding: Open access funding provided by University of Oulu including Oulu University Hospital. The financial support from the Academy of Finland (Grants No. 268378, and 303786); Sigrid Juselius Foundation; European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013)/ERC Grant Agreement No. 336267; and the strategic funding of the University of Oulu are acknowledged.
EU Grant Number: (336267) 3D-OA-HISTO - Development of 3D Histopathological Grading of Osteoarthritis
Academy of Finland Grant Number: 268378
303786
Detailed Information: 268378 (Academy of Finland Funding decision)
303786 (Academy of Finland Funding decision)
Copyright information: © 2019, Springer Nature. 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.
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