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Trabecular bone structure parameters from 3D image processing of clinical multi-slice and cone-beam computed tomography data
Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.ORCID iD: 0000-0002-7750-1917
Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Health Sciences.ORCID iD: 0000-0001-5765-2964
Karolinska University Hospital, Stockholm, Sweden.
2014 (English)In: Skeletal Radiology, ISSN 0364-2348, E-ISSN 1432-2161, Vol. 43, no 2, p. 197-204Article in journal (Refereed) Published
Abstract [en]

Objective

Bone strength depends on both mineral content and bone structure. The aim of this in vitro study was to develop a method of quantitatively assessing trabecular bone structure by applying three-dimensional image processing to data acquired with multi-slice and cone-beam computed tomography using micro-computed tomography as a reference.

Materials and Methods

Fifteen bone samples from the radius were examined. After segmentation, quantitative measures of bone volume, trabecular thickness, trabecular separation, trabecular number, trabecular nodes, and trabecular termini were obtained.

Results

The clinical machines overestimated bone volume and trabecular thickness and underestimated trabecular nodes and number, but cone-beam CT to a lesser extent. Parameters obtained from cone beam CT were strongly correlated with μCT, with correlation coefficients between 0.93 and 0.98 for all parameters except trabecular termini.

Conclusions

The high correlation between cone-beam CT and micro-CT suggest the possibility of quantifying and monitoring changes of trabecular bone microarchitecture in vivo using cone beam CT.

Place, publisher, year, edition, pages
Springer, 2014. Vol. 43, no 2, p. 197-204
Keywords [en]
Trabecular bone structure; Cone-beam computed tomography; Micro computed tomography; Multi-slice computed tomography; Bone segmentation
National Category
Radiology, Nuclear Medicine and Medical Imaging
Identifiers
URN: urn:nbn:se:liu:diva-102880DOI: 10.1007/s00256-013-1766-5ISI: 000329108500011OAI: oai:DiVA.org:liu-102880DiVA, id: diva2:683858
Available from: 2014-01-07 Created: 2014-01-07 Last updated: 2017-12-06Bibliographically 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)
Opponent
Supervisors
Available from: 2017-10-20 Created: 2017-10-20 Last updated: 2019-10-28Bibliographically approved

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Klintström, EvaSmedby, ÖrjanMoreno, Rodrigo

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Center for Medical Image Science and Visualization (CMIV)Division of Radiological SciencesFaculty of Health SciencesDepartment of Radiology in Linköping
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