Mineral density distribution of bone tissue is altered by active bone modeling and remodeling due to bone complications including bone disease and implantation surgery. Clinical cone beam computed tomography (CBCT) has been examined whether it can assess oral bone mineral density (BMD) in patient. It has been indicated that CBCT has disadvantages of higher noise and lower contrast than conventional medical computed tomography (CT) systems. On the other hand, it has advantages of a relatively lower cost and radiation dose but higher spatial resolution. However, the reliability of CBCT based mineral density measurement has not yet been fully validated. Thus, the objectives of this review are to discuss 1) why assessment of BMD distribution is important and 2) whether the clinical CBCT can be used as a potential tool to measure the BMD. Brief descriptions of image artefacts associated with assessment of gray value, which has been used to account for mineral density, in CBCT images are provided. Techniques to correct local and conversion errors in obtaining the gray values in CBCT images are also introduced. This review can be used as a quick reference for users who may encounter these errors during analysis of CBCT images.
Bone is a connective tissue designed to bear loading generated by muscle movement and body weight during daily activity.[
BMD accounts for bone quantity as the mineral contents within an apparent volume of bone, which includes porosity, bone marrow, as well as bone matrix. On the other hand, the TMD represents mineral contents only in the matrix of bone.[
The CBCT is relatively recent technology, with the first commercial scanner being introduced in 1998 for dental imaging.[
where I0 is the intensity emitted by the source, µ represents the attenuation coefficient, and l is a distance over which the attenuation is integrated. A denser material absorbs more energy resulting in a higher attenuation value. The attenuation values are converted to gray values in a digital (8-bit to 16-bit) image while the scanned image slices are reconstructed. As such, the gray value in the CBCT image is theoretically equivalent to the density of the material. However, in order to obtain a reliable density value using a CBCT image, multiple factors must be considered.
Imaging artefacts associated with general CT systems also occur in CBCT imaging.[
This artefact is appeared as inconsistent gray values with large standard deviations. This result arises from low signal-to-noise ratio of intensity, which needs to maintain the low radiation dose. The noise level can be reduced by increasing the excitation potential and current.
Scattered X-ray photons from the original path can be added to the primary intensity giving rise to an underestimation of attenuation value in Eq. 1. Larger detectors have a greater chance of encountering the scattered X-ray photons leading to streak artefacts during reconstruction process for the CBCT image.
As the energy levels of polychromatic X-ray beams used in the CBCT are not identical, the lower energy photons can be easily absorbed at the edges of the scanned subject resulting in hardening of the X-ray beam, which produces lower gray values toward the center of the subject (cupping artifact) even if the density of the subject is homogenous.
Defects or uncalibrated components in the detector may cause ring artefacts with concentric rings in the CBCT image. The ring voxels have inconsistent gray values that can increase overall errors in the assessment of bone density.
The cubic or rectangular voxels cannot completely delineate the irregular shapes of scanned subjects. Thus, the gray value of voxels at the border between different density materials contains averaged attenuations. If the voxel size of CBCT image increases, it has more incorrect partial volume gray values.
A sinogram is constructed using digital signals from the pixel transistors. This composite image combines each row of each projection in the CBCT image.[
CBCT can improve the image resolution by reducing the FOV while decreasing overall radiation dose. However, variability of gray values is increased by using a smaller FOV (5 cm) compared to larger FOVs (10 to 20 cm).[
The attenuation coefficients of the same material scanned by different CT systems can vary if the scanning conditions are not identical. As the HU can be computed relative to the attenuation coefficient of water (Eq. 2), it has been widely used to compare material density between different CT systems.
It was suggested that the HU should be calibrated in order to obtain a consistent density value when the same material is scanned using different CT systems.[
Scanning dense metallic materials can cause severe streaking artifacts when their gray values exceed the maximum level of operation that the software can handle.[
Shading or streaking artefacts may be observed when the gray values are incorrectly registered due to patient motion during CBCT scanning.[
Noise, ring and streak artefacts can be corrected by improving reconstruction algorithms.[
While the local errors can be visually detected, there are some systematic complications to be considered for CBCT based mineral density measurement. The most debated aspect is that the HU values of subjects are not consistent between different CT systems and between different times scanned even using the same CT system. These discrepancies can arise from the non-uniform process of scaling the HU values during reconstruction. It was indicated that a manufacturer's software imports a gray value range of 1 to 4,096 and rescales from -1,024 to 3,072.[
Many studies found that strong positive correlations of the gray values of CBCT image with known density of reference materials and gray values obtained from the conventional clinical CT.[
The aforementioned methods need external standard phantoms to be scanned to obtain the calibration curve. Another methodology was introduced using an internal reference to compare the mineral density between patients.[
To date, CBCT based BMD measurement has been used mainly to estimate bone properties for dental implantation.[
Mineral density distribution of bone tissue reflects the result of biological activity, which is altered due to bone complications. Clinical CT is an indirect method to measure mineral density distribution based on the X-ray attenuation coefficient of the materials, mainly the mineral, in bone tissue. Hence, CT based density measurement is not as accurate as direct measurement using biopsy. However, it is a very powerful non-destructive tool that allows for longitudinal diagnoses of patients' bone disease. Most of the local artefacts can be corrected by improving the CBCT image reconstruction algorithm and alternative corrective methods can be applied as visualized in the image. However, the image processing errors during converting the attenuation coefficient values to the HUs and gray values should be accurately addressed in order to compare the mineral density in CBCT images scanned under different conditions. This review briefly introduces the types of artefacts that occur and solutions to correct them as a quick reference for users who may find these errors in CBCT images.
No potential conflict of interest relevant to this article was reported.
The author thanks his student, Trenton B. Johnson, for helpful discussions about the subjects described in this review.
(A) Detailed tissue mineral density (TMD) distribution in vertebral trabecular bone. A darker color represents less TMD. (B) A typical TMD histogram of a micro-computed tomography image (voxel size 16×16×16 µm3). The TMD distribution was different between the control sham surgery (black) and ovariectomized (OVX) (gray) groups. [Reprinted from "Increased variability of bone tissue mineral density resulting from estrogen deficiency influences creep behavior in a rat vertebral body", by Kim DG, Navalgund AR, Tee BC, Noble GJ, Hart RT, Lee HR, 2012, Bone, 51(5), pp. 868-75. Copyright 2012 by the Elsevier. Reprinted with permission].
(A) Micro-computed tomography (CT) image (27×27×27 µm3 voxel size) and (B) cone beam CT image (200×200×200 µm3 voxel size) of the same human condyle.
X-ray beam projection scheme comparing acquisition geometry of conventional or "fan" beam (right) and "cone" beam (left) imaging geometry and resultant image production. The amount of scatter generated (sinusoidal lines) and recorded by cone-beam image acquisition is substantially higher, reducing image contrast and increasing image noise. [Reprinted from "What is cone-beam CT and how does it work?", by Scarfe WC, Farman AG, 2008, Dent Clin North Am, 52(4), pp.707-30. Copyright 2008 by the Elsevier. Reprinted with permission].
(A) Strong positive correlations in the calibration curves of gray values for (B) phantoms of bone materials (hydroxyapatite) with 3 different densities (1,000, 1,250, and 1,750 mg/cm3) scanned using 3 different resolutions (200, 300, and 400 µm) of cone beam computed tomography. HU, Hounsfield units.
(A) Degree of bone mineralization parameters determined using a grey level histogram, (B) comparison of grey level histograms between alveolar bone (AB, grey line) and basal cortical bone (CB, black line) regions using a three-dimensional (3D) cone beam computed tomography (CT) image (200×200×200 µm3 voxel size), and (C) using 3D micro-CT image (20×20×20 µm3 voxel size) for the same specimen. COV, coefficient of variation; Highs, grey level at the 95th percentile; LOWs, grey level at the 5th percentile; SD, standard deviation; AB, alveolar bone; CB, control bone. [Modified from "Comparison of micro-CT and cone beam CT-based assessments for relative difference of grey level distribution in a human mandible" by Taylor TT, Gans SI, Jones EM, Firestone AR, Johnston WM, Kim DG, 2013, Dentomaxillofac Radiol, 42(3), pp. 25117764. Copyright 2013 by British Institute of Radiology. Reprinted with permission].
Descriptive summary of X-ray based technologies [
DXA, dual-energy X-ray absorptiometry; MDCT, multidetector computed tomography; CBCT, cone beam computed tomography; Micro-CT, micro-computed tomography.