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Predicting Trabecular Bone Stiffness from Clinical Cone-Beam CT and HR-pQCT Data; an In Vitro Study Using Finite Element Analysis
Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).ORCID iD: 0000-0003-0884-899X
Linköping University, Center for Medical Image Science and Visualization (CMIV).
KTH Royal Institute of Technology, School of Technology and Health, Huddinge, Stockholm, Sweden.
Department of Clinical Science, Intervention and Technology at Karolinska Institutet, Stockholm, Sweden; Department of Radiology, Karolinska University Hospital, Huddinge, Stockholm, Sweden.
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2016 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 11, no 8, e0161101Article in journal (Refereed) Published
Abstract [en]

Stiffness and shear moduli of human trabecular bone may be analyzed in vivo by finite element (FE) analysis from image data obtained by clinical imaging equipment such as high resolution peripheral quantitative computed tomography (HR-pQCT). In clinical practice today, this is done in the peripheral skeleton like the wrist and heel. In this cadaveric bone study, fourteen bone specimens from the wrist were imaged by two dental cone beam computed tomography (CBCT) devices and one HR-pQCT device as well as by dual energy X-ray absorptiometry (DXA). Histomorphometric measurements from micro-CT data were used as gold standard. The image processing was done with an in-house developed code based on the automated region growing (ARG) algorithm. Evaluation of how well stiffness (Young’s modulus E3) and minimum shear modulus from the 12, 13, or 23 could be predicted from the CBCT and HR-pQCT imaging data was studied and compared to FE analysis from the micro-CT imaging data. Strong correlations were found between the clinical machines and micro-CT regarding trabecular bone structure parameters, such as bone volume over total volume, trabecular thickness, trabecular number and trabecular nodes (varying from 0.79 to 0.96). The two CBCT devices as well as the HR-pQCT showed the ability to predict stiffness and shear, with adjusted R2 -values between 0.78 and 0.92, based on data derived through our in-house developed code based on the ARG algorithm. These findings indicate that clinically used CBCT may be a feasible method for clinical studies of bone structure and mechanical properties in future osteoporosis research.

Place, publisher, year, edition, pages
Public library of science , 2016. Vol. 11, no 8, e0161101
National Category
Clinical Medicine
Identifiers
URN: urn:nbn:se:liu:diva-130798DOI: 10.1371/journal.pone.0161101ISI: 000381381100120PubMedID: 27513664OAI: oai:DiVA.org:liu-130798DiVA: diva2:955082
Available from: 2016-08-24 Created: 2016-08-24 Last updated: 2017-11-28Bibliographically approved
In thesis
1. Image Analysis for Trabecular Bone Properties on Cone-Beam CT Data
Open this publication in new window or tab >>Image Analysis for Trabecular Bone Properties on Cone-Beam CT Data
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Trabecular bone structure as well as bone mineral density (BMD) have impact on the biomechanical competence of bone. In osteoporosis-related fractures, there have been shown to exist disconnections in the trabecular network as well as low bone mineral density. Imaging of bone parameters is therefore of importance in detecting osteoporosis. One available imaging device is cone-beam computed tomography (CBCT). This device is often used in pre-operative imaging of dental implants, for which the trabecular network also has great importance.

Fourteen or 15 trabecular bone specimens from the radius were imaged for conducting this in vitro project.

The imaging data from one dual-energy X-ray absorptiometry (DXA), two multi-slice computed tomography (MSCT), one high-resolution peripheral quantitative computed tomography (HR-pQCT) and four CBCT devices were segmented using an in-house developed code based on homogeneity thresholding. Seven trabecular microarchitecture parameters, as well as two trabecular bone stiffness parameters, were computed from the segmented data. Measurements from micro-computed tomography (micro-CT) data of the same bone specimens were regarded as gold standard.

Correlations between MSCT and micro-CT data showed great variations, depending on device, imaging parameters and between the bone parameters. Only the bone-volume fraction (BV/TV) parameter was stable with strong correlations. Regarding both HR-pQCT and CBCT, the correlations to micro-CT were strong for bone structure parameters as well as bone stiffness parameters. The CBCT device 3D Accuitomo showed the strongest correlations, but overestimated BV/TV more than three times compared to micro-CT. The imaging protocol most often used in clinical imaging practice at our clinic demonstrated strong correlations as well as low radiation dose.

CBCT data of trabecular bone can be used for analysing trabecular bone properties, like bone microstructure and bone biomechanics, showing strong correlations to the reference method of micro-CT. The results depend on choice of CBCT device as well as segmentation method used. The in-house developed code based on homogeneity thresholding is appropriate for CBCT data. The overestimations of BV/TV must be considered when estimating bone properties in future clinical dental implant and osteoporosis research.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2017
Series
Linköping University Medical Dissertations, ISSN 0345-0082 ; 1594
National Category
Medical Image Processing
Identifiers
urn:nbn:se:liu:diva-142066 (URN)10.3384/diss.diva-142066 (DOI)9789176854341 (ISBN)
Public defence
2017-10-26, Hugo Theorell, Norra entrén, Campus US, Linköping, 09:00 (Swedish)
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Available from: 2017-10-20 Created: 2017-10-20 Last updated: 2017-10-20Bibliographically approved

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Klintström, EvaSmedby, Örjan

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Division of Radiological SciencesFaculty of Medicine and Health SciencesCenter for Medical Image Science and Visualization (CMIV)Department of Radiology in Linköping
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