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Image Analysis for Trabecular Bone Properties on Cone-Beam CT 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 Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping.ORCID iD: 0000-0003-0884-899X
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: urn:nbn:se:liu:diva-142066DOI: 10.3384/diss.diva-142066ISBN: 9789176854341 (print)OAI: oai:DiVA.org:liu-142066DiVA, id: diva2:1150905
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: 2018-03-01Bibliographically approved
List of papers
1. Trabecular bone structure parameters from 3D image processing of clinical multi-slice and cone-beam computed tomography data
Open this publication in new window or tab >>Trabecular bone structure parameters from 3D image processing of clinical multi-slice and cone-beam computed tomography data
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
Keywords
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:nbn:se:liu:diva-102880 (URN)10.1007/s00256-013-1766-5 (DOI)000329108500011 ()
Available from: 2014-01-07 Created: 2014-01-07 Last updated: 2017-12-06Bibliographically approved
2. Trabecular bone histomorphometric measurements and contrast-to-noise ratio in CBCT
Open this publication in new window or tab >>Trabecular bone histomorphometric measurements and contrast-to-noise ratio in CBCT
Show others...
2014 (English)In: Dento-Maxillo-Facial Radiology, ISSN 0250-832X, E-ISSN 1476-542X, Vol. 43, no 8, p. 20140196-Article in journal (Refereed) Published
Abstract [en]

Objectives: The aim of this study was to evaluate how imaging parameters at clinical dental CBCT affect the accuracy in quantifying trabecular bone structures, contrast-to-noise ratio (CNR) and radiation dose.

Methods: 15 radius samples were examined using CBCT (Accuitomo FPD; J. Morita Mfg., Kyoto, Japan). Nine imaging protocols were used, differing in current, voltage, rotation degree, voxel size, imaging area and rotation time. Radiation doses were measured using a KAP-meter. After segmentation, six bone structure parameters and CNR were quantified. Micro-CT images with an isotropic resolution of 20 microns were used as a gold standard.

Results: Structure parameters obtained by CBCT were strongly correlated to those by micro CT, with correlation coefficients .0.90 for all studied parameters. Bone volume and trabecular thickness were not affected by changes in imaging parameters. Increased tube current from 5 to 8 mA, decreased isotropic voxel size from 125 to 80 microns and decreased rotation anglefrom 360° to 180° affected correlations for trabecular termini negatively. Decreasing rotation degree also weakened correlations for trabecular separation and trabecular number at 80 microns voxel size. Changes in the rotation degree and tube current affected CNR significantly. The radiation dose varied between 269 and 1284 mGy cm2.

Conclusions: Trabecular bone structure can be accurately quantified by clinical dental CBCT in vitro, and the obtained structure parameters are strongly related to those obtained by micro CT. A fair CNR and strong correlations can be obtained with a low radiation dose, indicating the possibility for monitoring trabecular bone structure also in vivo.

Place, publisher, year, edition, pages
British Institute of Radiology, 2014
Keywords
CBCT; micro-computed tomography; trabecular 7 bone; histomorphometry; bone segmentation; osteoporosis
National Category
Radiology, Nuclear Medicine and Medical Imaging
Identifiers
urn:nbn:se:liu:diva-111163 (URN)10.1259/dmfr.20140196 (DOI)000346231400002 ()25168811 (PubMedID)
Available from: 2014-10-09 Created: 2014-10-09 Last updated: 2017-12-05Bibliographically approved
3. Predicting Trabecular Bone Stiffness from Clinical Cone-Beam CT and HR-pQCT Data; an In Vitro Study Using Finite Element Analysis
Open this publication in new window or tab >>Predicting Trabecular Bone Stiffness from Clinical Cone-Beam CT and HR-pQCT Data; an In Vitro Study Using Finite Element Analysis
Show others...
2016 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 11, no 8, article id 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
National Category
Clinical Medicine
Identifiers
urn:nbn:se:liu:diva-130798 (URN)10.1371/journal.pone.0161101 (DOI)000381381100120 ()27513664 (PubMedID)
Available from: 2016-08-24 Created: 2016-08-24 Last updated: 2018-03-26Bibliographically approved

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