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A Thesis
entitled
Evaluation of Phantoms Used in Image Quality Performance Testing of Dental Cone
Beam Computed Tomography Systems
by
Haitham N Alahmad
Submitted to the Graduate Faculty as partial fulfillment of the requirements for the
Master of Science in Biomedical Science Degree in
Medical Physics
________________________________________
E. Ishmael Parsai, Ph.D, Committee Chair
________________________________________
Kerry Krugh, Ph.D, Committee Member
________________________________________
Diana Shvydka, Ph.D, Committee Member
________________________________________
Patricia Komuniecki, Ph.D , Dean
College of Graduate Studies
The University of Toledo
August 2015
Copyright 2015, Haitham N Alahmad
This document is copyrighted material. Under copyright law, no parts of this document
may be reproduced without the expressed permission of the author.
An Abstract of
Evaluation of Phantoms Used in Image Quality Performance Testing of Dental Cone
Beam Computed Tomography Systems
by
Haitham N Alahmad
Submitted to the Graduate Faculty as partial fulfillment of the requirements for the
Master of Science in Biomedical Science Degree in
Medical Physics
The University of Toledo
August 2015
Cone beam computed tomography (CBCT) units dedicated for dental and
maxillofacial imaging have gained widespread use in recent years. So far there are no
standardized testing methods to evaluate the image quality or the dose on these units.
Although the vendors commonly provide an image quality phantom with the machine,
the procedures, image quality parameters evaluated, and performance criteria are limited
and specific to the vendors. The goal of this study is to evaluate the available phantoms
as a testing tool for image quality assessment of dental CBCT units. In addition, the
optimal diameter and features of a QA phantom for dental CBCT testing was assessed.
Two commercially available phantoms were evaluated to assess the adequacy of
each for use in the standardized testing procedures. These included ACR CT phantom
(Gammex 464) and CATPHAN (Phantom Laboratory). Additionally, a prototype dental
CT phantom (CIRS Inc.) was evaluated. Scans were made on three different machines; iCAT Classic (Imaging Sciences International), ILUMA (IMTEC/3M) and GALILEOS
Comfort (Sirona). A CT scan of the three phantoms were also performed with a
conventional CT scanner (Toshiba Aquilion 16) to verify the pixel values. The image
quality parameters that were evaluated included: image noise, image uniformity, pixel
value accuracy, pixel value linearity, contrast scale, and high contrast spatial resolution.
There is not one phantom evaluated that provided superior results for all image
quality tests. The prototype phantom was adequate for all tests with the exception of the
high contrast resolution test whereas the ACR phantom and the CATPHAN due to larger
diameter relative to the prototype demonstrated higher noise and non-uniformity, pixel
value inaccuracy, and lower contrast scale because of more beam hardening artifact
occurring with the large diameter. The optimal diameter for a phantom specialized in
dental CBCT testing was found to be between 16 and 17 cm in diameter.
To my parents, Nasser and Norah: I hope that you will always be proud of me.
Acknowledgements
I would like to express my gratitude to Dr. Kerry Krugh. This thesis would not
have been possible without your support and mentoring. Thank you for introducing the
topic to me and thank you for all the remarks and comments that were very helpful.
I would like also to send a special thank you for Dr. Parsai and Dr. Shvydka. You
have been nothing but supportive of me since I started the program.
I would like to thank Whittaker Family Dental (Defiance, OH), Dr. Matthew Lark
dental (Toledo, OH), and Harbor Light Oral & Maxillofacial Surgeons (Toledo, OH) for
allowing us to work on their CBCT machines. Also I would like to thank Vladimir
Varchena of CIRS Inc. (Norfolk, VA) for lending us the prototype phantom.
At last but not the least, this project would also not have been possible without the
love and support from my Dad, Mom, my wife Ayesha, and my sister Ghada. Thank you
guys for your support and I love you all so much.
v
Table of Contents
Abstract……………………………………………………..…………………………….iii
Acknowledgements…………………………………………………………………..........v
Table of Contents……………………………………………………………...………….vi
List of Tables…………………………………………………………………...……….viii
List of Figures…………………………………………………………………………….ix
List of Abbreviations…………………………………………….…………………….…xi
1. Introduction…………………………………………………………………..………..1
1.1. Radiographic imaging in dentistry………………………………………………..1
1.2. Computed tomography…………………………………………………..……….2
1.3. Dental Cone Beam Computed Tomography (CBCT) Technology……………....4
1.4. Quality assurance in dental CBCT………………………………………..…..….9
1.4.1. Radiation dosimetry…………………………………………...…………..9
1.4.2. Image quality testing in dental CBCT…………………………………...11
1.5. Existing phantoms designed for dental CBCT……………………………….…18
1.6. Determination of water-equivalent diameter for human dental and maxillofacial
region………………………………………………………………………..…..21
1.7. Objectives of the Study ……………………………………………………...….23
2. Materials and Methods……………………………………………………………….25
vi
2.1. Dental CBCT units………………………………………………………….…..25
2.2. Protocols………………………………………………………………….……..27
2.3. Set up and Positioning…………………………………………………………..27
2.4. Phantoms………………………………………………………………....……..28
2.5. Image Quality Analysis………………………………………………………....34
2.6. Calculation of water-equivalent diameter (Dw) for human dental and
maxillofacial region……………………………………………………………..37
3. Results………………………………………………………………………………..39
4. Discussion……………………………………………………………………………52
5. Conclusion………………….………………………………………………………..55
References………………………………………………………………………………..57
vii
List of Tables
1.1
Quantitative image quality testing of dental CBCT systems suggested by
the SEDENTEXCT project………………………………………………...
19
2.1
Technical differences between the i-CAT, ILUMA, and GALILEOS …..
25
2.2
Scan protocols used in scanning the phantoms………………….………...
28
3.1
Noise levels measured in uniformity sections in the phantoms……………
39
3.2
Normalization factors for noise……………………………………………. 41
3.3
Normalized noise levels……………………………………………………
3.4
Average noise for each phantom on each machine………………………... 42
3.5
Average difference between the average mean pixel value of the
41
peripheral ROIs and the central ROI……………………………………..... 43
3.6
Pixel values of the ACR phantoms materials ……………………………... 45
3.7
Pixel values of the CATPHAN materials ……………………………......... 45
3.8
Pixel values of the CIRS prototype materials …………………………......
45
3.9
Values of y-intercept in the three phantoms……………..…….…………..
48
3.10 Contrast scale of the three phantoms………………………………………
49
3.11 Calculation of the water-equivalent diameter of the dental and
maxillofacial region………………………………………………………..
viii
51
List of Figures
1.1
Principle of computed tomography……………………………………….. 3
1.2
Dental cone beam computed tomography………………………………...
4
1.3
Difference between conventional CT and CBCT…………………………
5
1.4
Phantom proposed by SEDENTEXCT project by Leeds Test Objects Inc.
18
1.5
QUART DVT AP phantom designed……………………………………..
19
1.6
Phantom suggested by Torgersen et al……………………………………
20
2.1
Set up and positioning of the phantoms in dental CBCT units…………… 27
2.2
Modules of CT ACR accreditation phantom……………………………...
30
2.3
Modules of CATPHAN504……………………………………………….
31
2.4
CIRS prototype phantom for dental CBCT units…………………………
32
2.5
Sections of the CIRS prototype phantom…………………………………
33
2.6
Measuring noise in the uniformity section in each phantom on image
acquired by i-CAT………………………………………………………...
2.7
34
Measuring the difference in pixel values of the periphery from the center
in the uniformity sections in each phantom on images acquired by
ILUMA…………………………………………………………………....
2.8
35
Measuring the mean pixel values of different materials in each phantoms
on images acquired by i-CAT…………………………………………….. 35
ix
2.9
The high contrast spatial resolution section in each phantom on images
acquired by i-CAT………………………………………………………...
36
2.10
Measuring the mean CT number from head CT scan…………………......
37
3.1
Noise levels measured in the three phantoms…………………………….. 40
3.2
Average noise levels for each phantom in each machine…………………
3.3
Average difference between the periphery and the center in the
42
uniformity section in each phantom………………………………………. 44
3.4
Pixel values of different materials in the phantoms (i-CAT vs. CT)……... 46
3.5
Pixel values of different materials in the phantoms (ILUMA vs. CT)…....
3.6
Pixel values of different materials in the phantoms (GALILEOS vs. CT).. 47
3.7
Contrast scale of the three phantoms for each machine………………....... 49
3.8
The high contrast resolution of the three phantoms…..……………….….. 50
x
47
List of Abbreviations
3D……………………...
AAPM…………………
ACR…………………...
AEC…………………...
CBCT………………….
CCD…………………...
CT.............................. ...
CTDI………………......
CS……………………...
DAP……………………
DLP……………………
FOV……………………
FPD……………………
Gy……………………...
HU……………………...
ICRP……………………
II……………………….
kVp…………………….
mA……………………..
mAs…………………….
MDCT………………….
MSCT………………….
NCRP………………….
QA……………………..
QC……………………..
ROI………………..……
Sv ………………..…….
TFT……………..……...
TLD……………..……..
Three Dimensional
American Association of Physicists in Medicine
American College of Radiology
Automatic Exposure Control
Cone Beam Computed Tomography
Charged Coupled Device
Computed Tomography
CT dose Index
Contrast Scale
Dose Area Product
Dose Length Product
Field of View
Flat Panel Detector
Gray
Hounsfield Unit
International Commission on Radiation Protection
Image Intensifier
killoVoltage Peak
milliAmprege
milliamprege - second
.Multidetector CT
Multislice CT
National Commission on Radiation Protection & Measurments
Quality Assurance
Quality Control
Region of Interest
Sievert
Thin Film Transistor
Thermolumenence Detector
xi
Chapter 1
Introduction
1.1. Radiographic Imaging in Dentistry
X-rays has been always used in dentistry to help doctors assess patient condition
and plan treatments. Intraoral radiography is the technique that has been commonly used
where a small dental film or digital sensor is placed in the mouth and an external x-ray
source is used to expose the image receptor. However, there was always the need for a
more comprehensive imaging technique; a method that enables the imaging of both of the
jaws and adjacent structures on one image. Therefore, panoramic imaging was introduced
and first made commercially available in the 1960s. Panoramic imaging was considered
the most comprehensive test used in dental practice.
Panoramic imaging uses the principle of tomography to produce a two-dimensional
image of a curved structure. The x-ray tube and the image receptor rotate simultaneously
around an imaginary fulcrum trough located in the patient. The structures that are in the
focal trough (the jaws and teeth) will appear in the image while the structures in the other
layers will be blurred out.
1
Panoramic images, however, suffer from the shortcomings that all plain film
radiography techniques suffer from; “magnification, distortion, superimposition, and
misrepresentation of structures” (Scarfe & Farman, 2008).
Analog tomography was also used in dental applications. There are even some
panoramic units that have the capabilities of producing tomograms. This mode of
imaging had the advantage of removing the superimposition of structures that is present
in the panoramic images. However, imaging by this mode of scanning is limited to only
one slice, and there was no capability for three-dimensional (3D) reconstruction or
multiplanar viewing. Therefore, the idea of utilizing 3D imaging techniques in the dental
practice came up to the surface.
1.2. Computed Tomography
In 1972, Hounsfield and Cormack revolutionized medicine when their work lead
to the invention of computed tomography. Computed tomography (CT) is an imaging
modality in which the x-ray tube produces a thin fan beam of x-rays while rotating
around the patient. An array of detectors on the opposite side rotates with the tube in
synchrony and collects the beam transmitted through the patient. These transmission
measurements can then be reconstructed to give a cross-sectional image of the scanned
object. Most of the current commercially available CT scanners use multidetector
systems where multiple rows of detectors (e.g. 8, 16, or 64) are used to scan multiple
slices per one tube rotation. With the aid of slip ring technology, the tube can be
continuously rotated in one direction. The gantry rotations can be progressed through the
2
longitudinal axis of the patient in a step-and-shoot fashion which is known as axial
scanning mode, or the gantry can be continuously rotated during the scan while moving
the table in the longitudinal axis to cover the area of interest. This simultaneous motion of
the gantry and the table results in a spiral or helical trajectory of the tube rotation around
the patient. This technique helps to cover more anatomical area in less time (Figure 1-1).
A set of reconstructed CT images can be post-processed to result in axial, sagittal and/or
coronal images. 3D images of the area of interest can be also formed by stacking the
reconstructed 2D images.
CT is one of the most common imaging procedures requested by physicians in the
United States. About 67 million CT scans were performed in the year of 2006 in the
United States (NRCP report No. 160, 2009). One of the reasons for such a higher number
of CT exams is the many clinical applications in which CT can be utilized. There is no
doubt that CT is a strong diagnostic tool that was made possible by the advancements in
computers. In addition to the well-known diagnostic role of CT to detect injuries and
abnormalities, it can be also utilized to give information about the stage of cancer, plan
radiation treatments and surgeries, guide interventional
procedures, and monitor the effectiveness of radiation
treatment plans.
CT has several advantages over general
radiography. It removes the superimposition of structures
that plain radiography suffers from. It also produces
images with high contrast sensitivity; structures in the
same slice that differ in their density by only 0.6% can be
3
Figure 1-1: Principle of Computed
Tomography. (Taken from
www.fda.gov)
easily differentiated. Also the CT technology enables viewing images in different planes
(axial, coronal, and sagittal) by using the multiplaner reformation tool (MPR).
However, due to radiation dose concerns, the use of conventional CT in dentistry
has been limited. Other reasons for this limited role are high acquisition and operating
cost and large space requirement. Thus cone beam computed tomography (CBCT) units
dedicated for dental imaging were introduced.
1.3. Dental Cone Beam Computed Tomography (CBCT) Technology
The dental (maxillofacial) CBCT technology was made commercially available in
early 2000s. It produces cross-sectional images and reconstructed 3D images of the area
of interest. The CBCT technology was initially developed for angiographic applications.
Now this technology is being used in many clinical applications such as radiation
therapy, surgery, and fluoroscopy. It is also used in many dental applications such as
implant planning, endodontics, maxillofacial surgery, and orthodontics (Pauwels et al.,
2015).
There are two types of dental CBCT equipment
arrangement. The first is the upright CBCT where the
patient sits on a chair or stands up while the scanning
occurs (Figure 1-2). The second configuration is where
the patient lies in the supine position during the scan.
The latter looks like a conventional CT scan but smaller
Figure 1-2: patient sitting in chair while
scanning in dental CBCT unit
in size. The upright configuration is more common for dental CBCT units.
4
CBCT is considered a new generation of computed tomography. The major
difference between the CBCT and the conventional CT is the geometry of the x-ray
beam. Figure 1-3 shows the difference in the beam geometry; in conventional CT, a
collimator restricts the x-ray beam into a fan-beam geometry, while CBCT uses conical
or pyramidal shaped x-ray beams. Unlike conventional CT, an area detector is used in
CBCT (rectangular mostly or circular in shape).
In CBCT the gantry rotates around a fulcrum point in the patient only one time. A
complete volumetric data set can be collected during this single rotation. The rotation
might be a full 360° rotation or a partial rotation (180° plus the fan angle) taking in the
range of 10 to 40 seconds. The size of the rotation angle can be fixed or variable
depending on the manufacturer. For most manufacturers smaller rotation angles usually
are preset with lower mAs which means less dose and nosier images. During the single
rotation of the gantry, about 150 to 600 planar projections, also called basis images, are
collected. The basis images (projections) look like a series of radiographic images, each
captured from a slightly different angle than the next.
Figure 1-3: Conventional
CT beam geometry (left),
CBCT beam geometry
(right). (Taken from
Journal of Canadian
Dental Association)
Figure 2-1:
sedentexCTIQ phantom
by Leeds Test Objects
Inc.Figure 1-2:
Conventional CT beam
geometry (left), CBCT
beam geometry (right).
(Taken from Journal of
Canadian Dental
Association)
5
Figure 3-1:
sedentexCTIQ phantom
by Leeds Test Objects
Inc.
The number of projections usually depends on the scan time, frame rate, angle of
gantry rotation and the speed of rotation. The number of projections can be fixed or
variable. When more projections are collected, better image quality can be obtained at the
expense of higher radiation dose and longer reconstruction times. Also more projections
lead to an increase in the signal-to-noise and reduction of metallic artifacts (Scarfe and
Farman, 2008).
The tube potential used in dental CBCT typically ranges from 60 to 120 kVp and it
is fixed for most vendors. Tubes are usually filtered with aluminum of thickness ranging
from 2.5 to 10 mm. The tube current applied typically ranges from 1 to 10 mA which, in
some models, can be manually varied by the operator depending on the patient size and
desired image quality. Some vendors apply automatic exposure control (AEC) in which a
suitable mA value can be obtained from the scout image. Other vendors apply non-patient
specific mA modulation in which certain mA values are preset for each scan angle.
The x-ray generation in CBCT might be continuous or pulsed. The continuous
production of x-ray contributes to a higher dose to the patient. The x-ray beam can be
made pulsed to correspond with the sampling of the detector. By this way the dose to the
patient is dramatically reduced. In the pulsed mode, the real exposure time is less than the
scanning time. For example, the exposure time for a 20-second scan on the i-CAT, a
dental CBCT unit by Imaging Sciences International (Hatfield, PA), is only 3.6 seconds.
That means that the x-ray turns on for 11.76 ms for each of the 306 projections (Imaging
Sciences International Inc., 2006). Pulsed systems may show improved image quality due
to the reduced motion effect from the gantry rotation (Pauwels et al., 2015).
6
When CBCT systems were first developed, the detector used, and still for some
models, was an image intensifier (II) paired with charged coupled device (CCD). This
type has some technical problems. For example, its circular field of view (FOV) suffers
from truncation artifacts at the periphery. Also because of the gantry rotation, the
sensitivity of the image intensifier can be easily affected by the magnetic field of the
earth (Scarfe & Farman, 2008).
Now, the flat panel detector (FPD) is the most commonly used in CBCT systems.
The FPD is an amorphous silicon panel which consists of a single scintillation phosphor
(typically cesium iodide doped with thallium) coupled with a thin film transistor (TFT)
array. It detects radiation by indirect capture; the scintillator converts the incident
radiation into visible light and the light photons are converted into electric charge by the
photoconductor layer (amorphous silicon). The signal is then registered by the TFT panel.
The FPD produces image quality superior to the images by the II/CCD detector
type. The reconstructed CBCT images obtained using FPD have less noise than the
images obtained using II/CCD detector type (Baba, Ueda and Okabe, 2004). In addition,
the FPD is less bulky and it has higher resolution, greater dynamic range and shows less
peripheral artifacts in the FOV (Scarfe & Farman, 2008). More recently, complementary
metal-oxide-semiconductor (CMOS) detectors are being incorporated in dental CBCT
(Pauwels et al., 2015).
The reconstruction technique used in conventional CT is called the filtered back
projection. In this technique each axial slice is reconstructed separately from the 2D
projection data. For CBCT, the most common reconstruction technique used is the
modified Feldkamp algorithm (or the FDK method) which is a variation of the filtered
7
back projection to keep track of the beam divergence in both cone and fan angles. In this
method the 3D images are reconstructed from the 2D projection data that is collected
during a single rotation around the patient. Further image processing can be performed to
produce 3D images by stacking the reconstructed 2D images.
Each element in this 3D volumetric data is called a volume element or a voxel. The
minimum size of the voxel that can be reconstructed is determined by the size of the
pixelated elements of the detector. Each voxel is assigned a value which represents the
attenuation properties of the material in that voxel. Also 2D cross-sectional images can be
viewed using the multiplanar reformation tool. CBCT reconstruction time depends on the
voxel size chosen, the FOV, and the number of projections images collected. Typical
reconstruction time is less than 2 minutes.
The FOV size in dental CBCT differs according to the manufacturers. Some units
have an option for extended view which is used when trying to scan areas that are larger
than the detector size. There are two ways for extended view imaging. The first way is by
obtaining two separate scans and then fusing the two data sets to result in volumetric data
for the large area of interest. This method has the disadvantage of overexposing the
overlapping area. The second way is to shift the position of the detector laterally and
collimate the beam asymmetrically (Scarfe and Farman, 2008).
8
1.4. Quality assurance for dental CBCT
A typical quality assurance program for evaluating the performance of an imaging
system that utilizes ionization radiation for image formation involves two components;
image quality and radiation dosimetry.
1.4.1.
Radiation dosimetry
Radiation dose assessment for any radiation emitting devoice is necessary for the
safety of patients. It provides a method of monitoring and estimation of the radiation dose
delivered to the patients. In conventional CT, the standardized method of choice to
characterize the dose is the CT Dose Index (CTDI). However, because of the nature of
the geometry of the beam in CBCT and the amount of scatter, the CTDI cannot be
properly adapted in CBCT (Pauwels et al., 2012). The pencil ionization chamber that is
used in measuring the dose in conventional CT is 10 cm long which may be useful for
CBCT machines with height FOV up to 6 cm. However, it is not ideal for machines with
FOV larger than 8 cm because the scatter produced would not be measured which would
lead to an underestimation of the dose (Araki et al., 2013). Also, a range of FOV sizes
can be chosen which can exceed the size of the pencil chamber. Large FOV can affect the
dose distribution (Pauwels et al., 2012). In addition, the iso-center of the scan can be
changed from central to peripheral in some scans, which in turns produces an asymmetric
dose distribution (Pauwels et al., 2012). Similarly, choosing a full arc rotation of the tube
versus a partial arc will affect the dose distribution. (Pauwels et al., 2012).
9
The issues discussed in the prior paragraph lead to an inaccurate estimation of the
dose when using the concept of CTDI in dental CBCT. Therefore there is not yet a
standardized method for evaluation of the radiation dose in dental CBCT and the most
accurate way to characterize the dose is by point-by-point measurement using TLDs in an
anthropomorphic phantom (e.g., the RANDO phantom) which is not practical for routine
QA radiation dosimetry measurement.
Effective dose, measured in Sievert (Sv), allows for the assessment of patient risk
and also allows for comparing different types of medical imaging modalities. Dental
CBCT offers relatively lower effective dose than conventional CT but higher effective
dose when it is compared to panoral radiography.
A study done by Dr. Ludlow et al compared the effective dose for 3 commercially
available CBCT units: CB Mercury, NewTom 3G, and i-CAT. Twenty-four TLDs were
placed throughout the layers of a head and neck RANDO phantom. After taking the
measurements, they calculated the total body effective dose by summing the doses for
individual organs calculated using both of the 1990 and 2005 ICRP tissue weighting
factors. The results showed that the effective doses produced by these CBCT scanners
were 4 to 42 times greater than equivalent panoramic images (Ludlow et al., 2006).
Based on the results, a 12-inch FOV scan on the i-CAT is equivalent to a dose of 21
single panoramic exposures. Also the results showed lower doses when using smaller
FOV and reduced values of kV and mA. They concluded that “CBCT dose varies
substantially depending on the device, FOV and selected technique factors. Effective
dose detriment is several to many times higher than conventional panoramic imaging and
10
an order of magnitude or more less than reported doses for conventional CT” (Ludlow et
al., 2006).
Another study that supports the findings of Dr. Ludlow was done byJ A Roberts et
al (2009). They studied the effective dose delivered to patients during a CBCT
examination placing TLDs in a RANDO phantom and scanning it using the i-CAT dental
CBCT. They calculated the effective dose using both the 1990 and the 2007 ICRP tissueweighting factors. They concluded that “doses from CBCT are low compared with
conventional CT but significantly higher than conventional dental radiography
techniques.”
The SEDENTEXCT project established by the European Atomic Energy
Community (Euratom) under the European Commission on Radiation Protection
proposed a new method that enables a more accurate estimation of the dose using a
specially designed phantom. The dose indices suggested are dose index 1 (DI1), dose
index2 (DI2) and dose area product (DAP). However, this method yet to be accepted
amongst the medical physics community as the standard method for assessing the dose in
dental CBCT.
1.4.2.
Image quality testing in dental CBCT
The second component of routine QA evaluation of dental CBCT is an assessment
of image quality. The image quality parameters that are important for assessment are
image noise and low contrast detectability, image uniformity, pixel value accuracy and
linearity, contrast scale, high contrast spatial resolution, and image artifacts.
11
1.4.2.1 Image noise and low contrast detectability
Noise is defined as a random or stochastic variation in the signal that, in ideal
situations, follows Poisson distribution. According to Poisson statistics the quantum noise
per pixel in an image is given by √𝑁 where N is the number of photons. Thus, quantum
noise is determined by those factors impacting the amount of photons used per pixel for
image formation (kVp, mAs, filtration, voxel size, and number of projections). In
addition, there are a variety of other sources of image noise, most notably in CT, the
image reconstruction kernel.
Noise strongly impacts low contrast detectability which is defined as the ability to
evaluate structures that have attenuation properties that are slightly different than that of
the background.
Due to the low mAs and small voxel size that are typically used in dental CBCT
systems, images contain relatively high noise levels.
In addition, the nature of the beam in CBCT produces a large amount of scatter
radiation. Both the relatively high noise levels and increased scatter radiation result in a
reduced contrast detectability of dental CBCT images in comparison with conventional
CT.
1.4.2.2 Image uniformity
Uniformity across an image is an important parameter to evaluate and quantify.
Ideally, tissues that have the same attenuation properties should have same pixel value in
any location in the image. Due to the divergence of the x-ray beam used in CBCT, there
12
is a variation in the intensity of the incident x-rays which causes a non-uniform
absorption and detection.
In addition, dental CBCT images suffer from non-uniformities whenever there is a
mass outside the FOV, often called exo-mass. The exo-mass causes beam hardening
which reduces the image intensities in parts of the image (Bryant, Drage and Richmond,
2008).
1.4.2.3. Pixel value accuracy and linearity
In conventional CT, each voxel in the image is assigned a certain value. This
value is calculated using the measured attenuation coefficient of the tissues in that voxel
normalized to the attenuation coefficient of water and is called CT number (expressed in
Hounsfield units). The following equation used to calculate the CT number of a voxel of
tissues:
𝐶𝑇# =
𝜇𝑡𝑖𝑠𝑠𝑢𝑒 −𝜇𝑤𝑎𝑡𝑒𝑟
𝜇𝑤𝑎𝑡𝑒𝑟
𝑥1000
(1-1)
Where:
CT#: the CT number of a given material in Hounsfield units
µtissue: linear attenuation coefficient of a given material
µwater: linear attenuation coefficient of water
Any material that possesses absorption properties that are higher than water takes
a positive value. Similarly any material that has absorption properties that are lower than
13
water takes a negative value. For example, the CT number of air is -1000, while the CT
number of dense bone is approximately +1000.
The pixel intensity values measured in dental CBCT images may not accurately
represent the true Hounsfield unit values (Scarfe et al., 2012). The reasons of such
discrepancy in the pixel values between conventional CT and CBCT are the high amount
of scatter, the applied reconstruction algorithm utilized in CBCT, and the reduced
technique factors that are usually used. In addition, great variability of the pixel values
can be seen in CBCT images from different machines manufacturers (Pauwels et al.,
2015).
In conventional CT, the CT number values across the image possess a linear
relationship with respect to the linear attenuation coefficient of the materials in the image.
In dental CBCT, the pixel values should also have a linear relationship with the beam
attenuation. One method to assess this relationship is to compare the measured dental
CBCT pixel values of a variety of materials with known HU values as determined from
conventional CT scan. The linearity of the relationship can be measured by means of the
correlation coefficient from linear regression analysis.
14
1.4.2.4. Contrast Scale (CS)
The contrast scale (CS) in conventional CT is defined as the change in linear
attenuation coefficient relative to the change in CT number and is expressed in the
following equation:
𝜇 (𝐸)−𝜇 (𝐸)
𝐶𝑆 = 𝐶𝑇1 (𝐸)−𝐶𝑇2 (𝐸)
1
2
(1-2)
Where,
µ1: linear attenuation coefficient of the first material for a specific beam energy
µ2: linear attenuation coefficient of the second material for a specific beam energy
CT1: the CT number of the first material for a specific beam energy
CT2: the CT number of the second material for a specific beam energy
In this project, however, the CS is defined as the change in the pixel value
between certain materials in the dental CBCT image relative to the change in the HU
measured in a conventional CT image for the same materials and is expressed in the
following equation:
𝐶𝑆 =
𝑃𝑉1 (𝐸)−𝑃𝑉2 (𝐸)
𝐶𝑇1 (𝐸)−𝐶𝑇2 (𝐸)
(1-3)
where
PV1: the pixel value of the first material in the dental CBCT image
PV2: the pixel value of the second material in the dental CBCT image
CT1: the HU of the first material in the conventional CT image
CT2: the HU of the second material in the conventional CT image
15
Ideally, the contrast scale (i.e., slope) should be equal to unity which means any
change in the pixel values measured in the CBCT image corresponds to the same amount
of change in the HU measured in the conventional CT image.
1.4.2.5.High contrast spatial resolution
The spatial resolution is defined as “the ability of an image system to distinctly
depict two objects as they become smaller and closer together” (Bushberg, 2002). The
smallest object that can be resolved is known as the limiting spatial resolution.
The spatial resolution in dental CBCT is mostly dependent on the reconstructed
voxel size, the physical size of the pixelated detector, and the reconstruction kernel.
CBCT is capable of reconstructing isotropic voxels meaning that voxels have equivalent
dimensions in the x,y, and z directions. Typical voxel size that can be reconstructed in
dental CBCT varies between 0.08 mm to 0.4 mm.
The limiting spatial resolution can be evaluated visually by using a line pair
pattern which consists of an alternating strip and space arrangement of different widths.
In literature, the line pair per distance values that have been reported for dental CBCT
images range between 0.6 and 2.8 lp/mm (Brüllmann and Schulze, 2015).
In addition, the spatial resolution of an imaging system can be quantified by the
modulation transfer function (MTF). The MTF can be calculated by applying a Fourier
Transform (FT) on a point spread function or a line spread function obtained by the
imaging system. The limiting spatial resolution of the system would be empirically
16
considered at the 10% MTF. The 10% MTF for dental CBCT found in literature is in the
range from 0.5 to 2.3 cycles/mm (Brüllmann and Schulze, 2015).
1.4.2.6.Artifacts
Dental CBCT images may suffer from cone beam artifacts. The cone beam artifacts
result from undersampling the cone angle direction. This affects the image quality in the
upper and lower edges of the reconstructed volume. The image quality improves
gradually towards the center (Schulze et al., 2011). In addition, the beam divergence
causes other artifacts such as aliasing and high amounts of scatter.
17
1.5.
Existing phantoms designed for dental CBCT
During the past few years some efforts were made to the purpose of designing a
comprehensive quality assurance program for dental CBCT. The Safety and Efficacy of a
New and Emerging Dental X-ray CT scanners, or the SEDENTEXCT, project established
by the European Atomic Energy Community (Euratom) under the European Commission
on Radiation Protection was one of the firsts who addressed this issue. The objective of
the SEDENTEXCT project was to “develop evidence-based guidelines dealing with
justification, optimization and referral criteria for users of dental CBCT.” They published
provisional guidelines in report 172 in 2008 and published an updated version in 2011.
The report included a chapter about quality standards and quality assurance and
recommended that a QA program should include six topics; x-ray tube generator
performance, quantitative assessment of image quality, display screen performance,
patient dose assessment, clinical image quality assessment and clinical audit .
They proposed an image quality program using the SEDENTEXCT phantom
designed by Leeds Test Objects Inc. This phantom is a PMMA cylinder of 16 cm in
diameter and a height of 16.2 cm (Figure 1-4). Nine
image quality characteristics can be evaluated using
this phantom and these parameters are noise,
uniformity, pixel value accuracy contrast resolution,
spatial resolution, geometrical accuracy, and metal
artifacts. Table (1-1) summarizes the test and their
frequency. Since there are no action or tolerance
18
Figure1-4: sedentexCTIQ phantom by Leeds
Test Objects Inc.
levels so far, they suggested to establish baseline values during the acceptance testing and
then monitor these values in the routine testing.
Table (1-1 ): testing of image quality of dental CBCT as suggested by the SEDENTEXCT project. (Taken
from report 172)
Table (2-1 ): testing of image quality of dental CBCT as suggested by the SEDENTEXCT project. (Taken
from report 172)
Table (2-1 ): testing of image quality of dental CBCT as suggested by the SEDENTEXCT project. (Taken
from report 172)
Table (2-1 ): testing of image quality of dental CBCT as suggested by the SEDENTEXCT project. (Taken
from report 172)
Pauwels et al (2011) conducted a study where they evaluated the SEDENTEXCT
proposed phantom and stated that it showed promising potential for technical image
quality evaluation of CBCT. J Bamba et al (2013) also used this phantom to evaluate
three dental CBCT systems and stated that all the essential image quality parameters can
be assessed using this phantom.
QUART, a German company, also designed a
special phantom for testing dental CBCT systems
(Figure 1-5). The QUART DVT AP phantom is
cylindrical in design with a 16 cm diameter and 15
cm in height. It is designed to evaluate image
Figure 1-5: Quart DVT AP phantom (taken
from Quart website)
uniformity, image noise, contrast resolution and CNR, MTF, limiting spatial resolution
and image geometry.
19
The center for Evidence-Based Purchasing CEP, a part of the department of
health in the United Kingdom, conducted a comparative evaluation of dental CBCT
systems in 2010 where they compared the dose and image quality for several CBCT
systems from different vendors. For image quality comparison they used CATPHAN
424. They were able to test the high contrast spatial resolution, uniformity, CT number
accuracy, and geometric accuracy. However, low contrast detectability module of the
CATPHAN was not adequately visualized on any of the systems they evaluated.
Another phantom which is not commercially available and was designed for
research purposes by Torgersen et al (2014) is shown in Figure 1-6. They tried to design
an inexpensive phantom for simplified image quality assurance for image quality
assessment of dental CBCT. All of the tests performed by this phantom were objective.
They also developed software that can be used to evaluate the images of this phantom.
The tests included low and high contrast resolution, uniformity, noise, and geometric
linearity. The phantom has a diameter of 16 cm and a height of 70 cm.
The SEDENTEXCT phantom and the QUART phantom are the only
commercially available phantoms designed for dental CBCT but may not be cost
effective for every diagnostic medical physicist to purchase.
Figure 1-6: QA phantom designed by
Torgersen et al for dental CBCT
testing
20
1.6.
Determination of water equivalent diameter (Dw) for human dental and
maxillofacial region.
The phantom that is ideally used in the assessment of image quality parameters of
dental CBCT scanners would have the same attenuation properties as the dental and
maxillofacial region of the human head. Most phantoms in radiologic testing are made of
water-equivalent material. The optimal diameter of a cylindrical phantom can be
determined by calculating the diameter of water that has similar photon attenuations as
the dental and maxillofacial tissues.
The CT number values in CT images expressed in Hounsfield units are calculated
by using the linear attenuation coefficients of the materials in the image. The CT number
is thus representative of the attenuation properties of a voxel of a tissue and can be used
to calculate the diameter of water that would have equivalent attenuation. The
methodology and calculation of the water-equivalent diameter (Dw) have been discussed
in detail in AAPM task group report 220 report. The following equation was used:
1
𝐷𝑤 = 2√[1000 𝐶𝑇(𝑥, 𝑦)𝑅𝑂𝐼 + 1]
𝐴𝑅𝑂𝐼
(1-4) (AAPM Task Group 220, 2014)
𝜋
where,
Dw: water-equivalent diameter
CT(x,y)ROI: the mean CT number in a chosen ROI
AROI: the area of the ROI
21
In addition, by rearranging the previous equation and solving for area (A=
𝜋(D/2)2), an attenuation equivalent diameter of materials other than water can be
determined as in the following equation:
𝐷𝑚𝑎𝑡𝑒𝑟𝑖𝑎𝑙 = 2√{
2
𝐷
( 𝑤)
(
2
𝐶𝑇𝑚𝑎𝑡𝑒𝑟𝑖𝑎𝑙
+1)
1000
}
(1-5)
where,
Dmaterial: the attenuation equivalent diameter of material other than water
CTmaterial: the HU of the material of interest
Dw: the water-equivalent diameter calculated from Formula 1-4
22
1.7.
Objectives of the Study
When dental CBCT was first introduced there was no requirement for medical
physics acceptance testing or annual quality control testing of dental CBCT. Since that
time only some States have mandated that medical physicists perform testing on these
units. Ohio Administrative Code rule 3701:1-66-10 was revised in July 2014 to include
CBCT scanners and hybrid imaging systems. Paragraph D of that rule states that a QA
testing should be performed annually for CBCT units. The annual testing should be
performed by a radiation expert. To date there are no standardized test methods,
phantoms, or test criteria for these units
The American Association of physicists in medicine (AAPM) has recently formed
a task group (TG261) for discussing this issue. Its main objective is to establish a
standardized procedures and techniques for the quality control of dental and maxillofacial
imaging systems.
With this rising interest to comply with the regulations, there is a necessity to
develop guidelines and recommendations regarding routine quality control testing of
CBCT scanners.
The following are the objectives of this study:
1. Evaluate the feasibility of using phantoms common to conventional CT
testing for use in dental CBCT quality control testing. These phantoms
include the ACR CT phantom and CATPHAN. Both of these phantoms
are available and familiar to most diagnostic medical physicists. It would
be more economical and convenient if these phantoms were found to be
23
suitable for testing dental CBCT units. Purchasing specially designed QA
phantoms for dental CBCT testing may not be cost effective, especially for
small dental offices or small medical physics consultancy companies.
2. Evaluate a prototype phantom designed specifically for dental CBCT QC
phantom (the CIRS prototype phantom).
3. Evaluate the optimal dimensions of a QA phantom for dental CBCT based
on the radiation attention properties of the dental and maxillofacial region
of the human head and propose alterations and features for appropriate
phantom design based on observations from objectives 1 and 2.
24
Chapter 2
Materials & Methods
Evaluation of QA phantoms
2.1 Dental CBCT units
Image quality testing was performed on three commercially available CBCT
scanners: i-CAT Classic (Imaging sciences International), ILUMA (IMTEC/3M), and
GALILEOS Comfort (Sirona). Table 2-1 summarizes specifications for each scanner:
Table ( 2-1 ): technical differences between the i-CAT, ILUMA, and GALILEOS.
Scanner
iCAT classic
(Imaging Sciences)
ILLUMA
(3M/IMTEC)
GALILEOS comfort
(Sirona)
Focal spot
(mm)
Detector
Exposure
mode
kVp
mA
FOV
DxH (cm)
0.5
FPD
Pulsed
120
3-7
16x13
0.3
FPD
Continuous
120
1 or 3.8
17x14
0.5
II
pulsed
85
5-7
15x15
FPD: Flat panel detector. II: Image intensifier. FOV: Field of view.
25
Figure 3-1: the platform and the tripod used to position the phantoms
Figure 3-1: the platform and the tripod used to position the phantoms
2.1.1
i-CAT Classic (Imaging Sciences International)
The i-CAT utilizes an x-ray tube with a 0.5 mm focal spot size and 15° anode
angle. Technical factors for x-ray generation on this units are 120 kVp (fixed tube
voltage) and a tube current that can be varied from 3 to 7 mA. The tube has filtration
equivalent to 10 mm of aluminum at 120 kVp.
The i-CAT utilizes an amorphous silicon flat panel for detection with a readable
area with dimensions of 24 cm by 20 cm. This detector allows for a maximum field of
view of 16 cm in image diameter and 13 cm in height which can be collimated down to
cover areas of smaller size.
2.1.2
ILUMA (IMTEC/3M)
The ILUMA utilizes an x-ray tube with a 0.3 focal spot size and has a filtration of
1.27 mm of copper. The tube voltage is fixed to 120 kV and the tube current has two
settings; 1 or 3.8 mA. The ILUMA utilizes a flat panel detector with dimensions of 20 cm
by 24 cm which allows a reconstructed FOV of 17 cm in image diameter and 14 cm in
height. The exposure mode in the ILUMA is continuous, which means the scan time
equals the exposure time.
26
2.1.3
GALILEOS comfort (Sirona)
This unit uses an x-ray tube with a 0.5 mm focal spot and has a 2.5 mm of
aluminum thickness for filtration. The tube voltage is fixed to 85 kV and the tube current
can be varied between 5 and7 mA. The GALILEOS uses an image intensifier for
detection with an input window of 21.5 diameter which allow a reconstructed FOV is 15
cm in both diameter and height. The GALILEOS has two programs that can be used for
scanning; VO1 and VO2. The difference between the two programs is with the image
reconstruction algorithm and thus acquisition parameters are equivalent.
2.2 Protocols
A total of eight protocols were chosen to scan the
phantoms. The protocols chosen for scanning in this project were
those that were commonly used in the clinical setting. Table (2-2)
summarizes the scan protocols used. Note that in the following
chapters the protocols will simply be referred to by the Reference
number in Table 2-2.
2.3 Set up and positioning
Figure 2-1: the platform and the
tripod used to position the
phantoms
The phantoms were positioned vertically on a custom- made stand inserted on a
tripod. The platform was leveled and lasers were used to center the phantoms
FOV.
Figure 3-1: in
the the
platform
and the
27
tripod used to position the
phantoms
Figure 3-1: the platform and the
tripod used to position the
phantoms
Table (2-2 ): protocols used in scanning the phantoms
Reconstructed volume
Protocol
scan
(diameter x height)
Ref
(cm)
#
time
(s)
voxel
arc
(mm)
(°)
projections
120
6.9
10
0.3
332
160
2
120
6.6
20
0.4
332
306
3
120
3.8
7.8
0.3
190
117
17x14
4
120
3.8
20
0.3
360
302
cylindrical
5
120
1
20
0.3
360
302
6
120
3.8
40
0.3
360
602
16x13
(Imaging Sciences)
cylindrical
(IMTEC/3M)
mA
1
iCAT classic
ILUMA
kV
Galileos Comfort
15
7
85
7
14
0.29
204
200
(Sirona)
Spherical
8
85
7
14
0.29
204
200
2.4 Phantoms
Three phantoms were evaluated for dental CBCT testing. The phantoms evaluated
were the ACR phantom and the CATPHAN which are commonly used in testing
conventional CT. The third phantom evaluated is the CIRS prototype which is specially
designed for testing dental CBCT phantoms. The details for the each phantom are as
follows:
28
2.4.1
CT ACR Phantom
Gammex 464 is the only phantom that is authorized by the American College of
Radiology to be used in the accreditation process of conventional CT scanners. It can be
used for initial QA assessment and routine monthly QA testing for CT machines. Several
image quality parameters of CT can be evaluated using this phantom. The CT ACR
phantom is 20 cm in diameter and has a height of 16 cm. It consists of 4 modules or
sections. Each section has a thickness of 4 cm.
The first module is used to evaluate positioning and alignment, CT number
accuracy, and slice thickness (Figure 2-2: A). In this module there are 5 cylinders of
different materials. These different materials are used to evaluate CT number accuracy.
This module also includes two ramps each consists with a series of wires that can be used
to assess the slice thickness.
The second module is used to evaluate low contrast detectability and contrast-tonoise ratio. This module consists of multiple cylinders of different diameters (Figure 22:B)
The third module is made of a uniform tissue-equivalent material used to assess
uniformity and noise. This module also has 2 small BBs 10 cm apart which can be
measured to assess the geometric accuracy (Figure 2-2:C)
The fourth module is used to evaluate high contrast spatial resolution. It has 8 square
line pair regions. The limiting spatial resolutions that can be measured are 4, 5, 6, 7, 8, 9,
10 and 12 lp/cm (Figure 2-2: D)
29
B
A
C
D
Figure 2-2: the four modules of the ACR CT phantom. Taken from the CT ACR
accreditation phantom instructions.
Figure 3-2: the four modules of the ACR CT phantom. Taken from the CT
accreditation phantom instructions.
CATPHAN504
2.4.2
Figure504
3-2: the
four modules
of thePhantoms
ACR CT phantom.
Taken from
the CT
The CATPHAN
designed
by The
Laboratory
Inc.
and is commonly
accreditation phantom instructions.
used to evaluate image quality and system performance for both CT and CBCT scanners.
It is 20 cm in both diameter and height. It consists of 4 modules (Figure 2-3). Module
Figure 3-2: the four modules of the ACR CT phantom. Taken from the CT
accreditation phantom instructions.
CTP528 (Figure 2-3A) is used to test spatial resolution. It consists of high contrast line
pairs ranging from 1 to 21 lp/cm. Module CTP 515 (Figure 2-3B) is used to assess low
contrast detectability.
30
B
A
C
Figure 2-3: modules of Catphan 504 (taken from the phantom laboratory manual)
It consists of three groups of supra-slice low contrast targets with nominal
contrast levels of 0.3%, 0.5%, and 1.0%. Each group has 9 circles with diameters ranging
from 2 to 15 mm. It also consists of three sub-slice groups each having 4 circles of
diameters 3,5,7 and 9mm. Module CTP 404 (Figure 2-3C) has 8 targets of different
materials (Air, PMP, LDPE, Polystyrene, Acrylic, Derlin, and Teflon) which can be used
to assess the accuracy and linearity of the Hounsfield unit scale. This section also
contains 4 wire ramps with 23° angulation. The wire ramps can be used to assess
alignment and slice thickness. Also the section has 4 3mm holes positioned at 50mm
from each other. These can be used to evaluate the measurement accuracy. In the center
of this module there are 5 acrylic spheres of different diameters to evaluate the machine’s
ability to image volumes.
31
The last module is made of a uniform material (CTP486) module and is used to
evaluate image uniformity, noise and artifact.
2.4.3
CIRS QA Phantom prototype
This phantom was designed in 2010 by Computerized Imaging Reference systems
(CIRS) Inc. which is still under investigation and subject to further development. This
prototype is designed to be used in CBCT acceptance and periodic QA testing. It has 5
sections and can be used to measure seven dental CBCT performance parameters. It can
also provide a range of bone mineral density references. It has a triangular shape with a
height of 17 cm (Figure 2-4).
The second layer of the phantom is used to evaluate uniformity and noise. It is
made of a water-equivalent material and has a thickness of 20 mm (Figure 2-5).
Figure 2-4 : Dental CBCT prototype QA
phantom by CIRS Inc.
32
Figure 3-4 : Dental CBCT prototype QA
phantom by CIRS Inc.
The third section is used to evaluate low contrast detectability. This section has a
thickness of 30 mm and its background is made to be water equivalent. There are three
sets in this sections. Each set has 8 cylindrical targets and 8 spherical targets. The
cylinders are 30 mm long and have diameters of 10, 7, 5, 3.5, 2.5, 1.8, 1.2 and 0.9 mm.
The spheres have diameters of 10, 8, 6.5, 5, 4, 3.2, 2.5, and 2 mm. Each set has a different
density than the other; the first set is 5 HU, the second is 10 HU and the third is 20 HU
above the background (Figure 2-5).
The fourth section is used to evaluate CT number linearity, alignment and slice
thickness. This layer also is 30 mm in thickness. To assess the CT number linearity, this
section has 6 cylinders each with 13 mm diameter and 30 mm in length. Each cylinder
has different density to mimic different material; adipose tissue, brain, muscle, bone,
dense bone. To assess the slice thickness this section also has 3 stainless steel wires that
are angled 30° from the axial plane (Figure 2-5).
Figure 2-5: the layers of the dental CBCT prototype (taken from the manual provided by CIRS)
33
2.5 Image Quality analysis
All image analysis was done using ImageJ software freely available from NIH
(National Institute of Health).
Image noise was measured as the standard deviation of a central ROI drawn in the
uniformity section for each phantom used. To eliminate slice to slice variation the noise
was averaged over twenty consecutive slices.
a
b
c
Figure 2-6: measuring noise in the uniformity section in each phantom on i-CAT images. a) ACR phantom. b)CATPHAN.
C) CIRS prototype.
For measuring the image uniformity, 5 equal circular ROIs were drawn in center,
12, 3, 6, and 9 o’clock positions in the uniformity section in each phantom. The image
uniformity was calculated as the mean difference in pixel values of the four periphery
positions from that of the center. This again was averaged over twenty consecutive slices
34
a
b
c
Figure 2-7: measuring the difference of the peripheral mean pixel value from the center in the uniformity section in each
phantom on the ILUMA images. a) ACR phantom. b) CATPHAN. c)CIRS prototype.
The mean pixel value for all materials in each phantom was measured with an
ROI. The pixel values were plotted against the “true” HU values obtained from a
conventional CT scan. Linear regression was used to fit a line to the data. From the linear
equation the Y-intercept was used as an assessment of pixel value accuracy, the slope as
an assessment of contrast scale, and the correlation coefficient (R2) as an assessment of
pixel value linearity.
a
b
c
Figure 2-8: measuring the mean pixel values for different materials on the i-CAT images of each phantom
35
a
c
b
Figure 2-9: high contrast spatial;; resolution section of phantoms acquired on i-CAT scanner. A)ACR phantom. b)
CATPHAN. c) CIRS prototype
For evaluating the high contrast spatial resolution, the smallest line pair that could be
visually resolved in each phantom was recorded.
36
Diameter of dental CBCT QA phantom
2.6 Calculation of water-equivalent diameter (Dw) for human dental and
maxillofacial region
Ten conventional CT scans of the head area were chosen for this calculation.
Since the goal is to measure the equivalent attenuation of the dental and maxillofacial
tissues only, the images that had foreign objects, such as metallic implants or bismuth
shields, were avoided. Such highly attenuating materials affect the accuracy of the Dw
calculation (AAPM Task Group 220, 2014).
In each head scan the slices from the inferior of the orbit to the inferior edge of
the mandible were selected. An ROI was drawn to include the tissues in each slice.
a
b
c
Figure 2-10: measuring the mean CT number value in the CT scans. ROI was drawn to include all
tissues in the slice. a) Orbits level. b) mid-level. c) Mandible level
The ROI was drawn in such a way to include the entire cross-section. Irrelevant
objects such as the patient table was not included in the ROI since it can lead to an
overestimation of the attenuation of the ROI (AAPM Task Group 220, 2014).
37
The mean CT number of each ROI was recorded and the average across all the
slices was determined.
38
Chapter 3
Results
Evaluation of QA phantoms
3.1 Image noise
Table 3-1 shows the noise levels measured in each phantom using scan protocols 1
to 8 referenced in Table 2-2. Figure 3-1 depicts the difference in noise between the
protocols used.
Table 3-1: noise levels measured as the standard deviation of an ROI of uniformity section in each phantom
Scan Protocol
Machine
ACR Phantom
CATPHAN
1
iCAT
91.4
91.9
CIRS
prototype
47.7
2
iCAT
69.3
72.4
38.8
3
ILUMA
92.5
88.9
51.5
4
ILUMA
62.9
58.8
32.3
5
ILUMA
128.4
115.8
60.5
6
ILUMA
55.5
44.1
24.5
7
GALILEOS
32.4
48.0
10.1
8
GALILEOS
N/A
152.0
35.5
39
160.0
140.0
Noise
120.0
100.0
80.0
60.0
40.0
20.0
0.0
iCAT
iCAT
ILUMA
ILUMA
ILUMA
ILUMA
GAL
GAL
1
2
3
4
5
6
7
8
Scan Protocols
ACR
CAT
CIRS
Figure 3-1: noise levels measured in the phantoms
Since image noise is a function of the number of photons used for image
formation it is possible to normalize the noise to the image technique. The normalization
removes the variability in noise for a given machine for changing technique factors. In
particular the noise was normalized to the tube current (mA) and number of projections
used for image formation. The mA normalization factor is the square root of the mA in
each protocol divided by 7 mA (the highest mA amongst the protocols). The
normalization factor of the number of projections is the square root of the number of
projections used in each protocol divided by 300. This number was chosen because many
protocols used number of projections close to 300. The following equation is for
calculating the noise normalization factor (NNF):
𝑚𝐴
𝑁𝑁𝐹 = √(
7
# 𝑜𝑓 𝑓𝑟𝑎𝑚𝑒𝑠
)(
300
40
)
(3-1)
The calculation of the noise normalization factor is presented in Table 3-2. The
noise normalization factor is multiplied by the noise levels in Table 3-1. The normalized
noise levels are presented in Table 3-3. In Tables 3-2 and 3-3 only one protocol was used
for the GALIEOS since protocol 7 and 8 differ only in the reconstruction kernel and not
in the technical factors. Thus no normalization of the mA or the number of projection can
be used for the GALILEOS.
Table 3-2: Noise Normalization Factor (NNF)
Scan
Protocol
Machine
mA
projections
mA
Normalization
factor
No. of projections
Normalization
factor
NNF
1
iCAT
6.9
160
0.993
0.730
0.725
2
iCAT
6.6
306
0.971
1.010
0.981
3
ILUMA
3.8
117
0.737
0.624
0.460
4
ILUMA
3.8
302
0.737
1.003
0.739
5
ILUMA
1.0
302
0.378
1.003
0.379
6
ILUMA
3.8
602
0.737
1.417
1.040
7
GAL
7.0
200
1.000
1.000
1.000
Table 3-3: normalized noise levels
Scan Protocol
Machine
ACR Phantom
CATPHAN
CIRS prototype
1
iCAT
66.3
66.6
34.6
2
iCAT
68.0
71.0
38.1
3
ILUMA
42.6
40.9
23.7
4
ILUMA
46.5
43.5
23.8
5
ILUMA
48.7
43.9
22.9
6
ILUMA
57.9
46.1
25.5
7
GAL
32.4
48.0
10.1
41
An average of the normalized noise of the phantoms was calculated for the i-CAT
and the ILUMA. The normalized noise values of the three phantoms from protocols 1 and
2 were averaged and the error bars were determined as the standard deviation of the
average. Similarly, the normalized noise values of the phantoms from protocols 3,4,5 and
6 were averaged and the error bars were determined. No averaging was performed on the
normalized noise for the GALILEOS as explained above and thus only protocol 7 was
used for comparison. Table 3-4 presents the average noise with the error bars and Figure
3-2 shows these values.
Table 3-4: Average noise in each phantom for each machine
i-CAT
ILUMA
GALILEOS
Averaged
Protocols’ data
1 and 2
3,4,5 and 6
7 only
ACR Phantom
CATPHAN
CIRS Prototype
67.1±1.2
48.9±6.5
32.4
68.8±3.1
43.6±2.1
48.0
36.4±2.5
24.0±1.1
10.1
80.00
Normalized noise
70.00
60.00
50.00
40.00
30.00
20.00
10.00
0.00
i-CAT
ILUMA
ACR
CAT
GALILEOS
CIRS
Figure 3-2: average noise in each phantom for each machine.
42
In general, the noise from the ACR phantom and CATPHAN for a given scanner
were comparable. The noise on these two phantoms was within 2.5% in the i-CAT, 12%
in the ILUMA and 38% in the GALILEOS.
The noise of the CIRS prototype was significantly lower than that in the other two
phantoms due to the significant difference in the phantom’s diameter. The noise in the
CIRS phantom was lower than that in the the ACR phantom and CATPHAN by 47% for
the i-CAT and ILUMA and by 75% on the GALILEOS.
3.2 Image uniformity
Table 3-5 shows the calculation of image uniformity in each phantom for the
protocols 1 to 8. Figure 3-3 depicts the average difference in pixel value between the
center and the periphery in the phantoms.
Table 3-5: the average difference between the peripheral ROIs and the central ROI inn the uniformity section in each
phantom
Scan protocol
scanner
ACR phantom
CATPHAN
CIRS prototype
1
iCAT
122.8
127.4
83.2
2
iCAT
144.6
129.2
81.6
3
ILUMA
10.3
31.2
79.7
4
ILUMA
9.0
31.6
2.7
5
ILUMA
9.5
28.8
6.9
6
ILUMA
12.9
31.9
1.9
7
GALILEOS
46.4
106.6
5.2
8
GALILEOS
NA
109.8
5.9
43
Uniformity
Pixel Value Difference
160
140
120
100
80
60
40
20
0
i-CAT
i-CAT
ILUMA
ILUMA
ILUMA
1
2
3
4
5
ACR
CAT
ILUAM GALILEOS GALILEOS
6
7
8
CIRS
Figure 3-3: the average difference between the periphery and center for protocols 1 to 8.
For a given scanner, the images of the CIRS prototype show the highest
uniformity as compared to the other two phantoms with the exception of protocol 3 which
was affected by artifacts.
On average the difference in pixel values between the center and periphery in the
CIRS phantom, with the exception of protocol 3, was around 60% less than that in the
ACR phantom and around 75% less than that in the CATPHAN.
3.3 Pixel value accuracy and linearity
Tables 3-6, 3-7 and 3-8 show the pixel values for each material in the ACR
phantom, CATPHAN and CIRS prototype, respectively, measured in protocols 1 to 7
referenced in Table 2-2. The tables also show the CT number of each material measured
in the CT images by the Toshiba Aquilion 16 conventional CT scanner.
44
Table 3-6: pixel values measured in the ACR phantom
ILUMA
iCAT
GAL
Toshiba
CT #
P1
P2
Avr
P3
P4
P5
P6
Avr
P7
Air
Polyethylene
Acrylic
-989
-999.9
-1000
-999.9
-1048.8
-1053.9
-1043.8
-1032.9
-1044.8
1430.8
-93
-656.4
-647.5
-651.9
-181.2
-158.6
-169.9
-127.9
-159.4
2130.1
120
-478.5
-479.9
21.8
39.1
28.7
60.2
940
171.3
172.7
504.2
513.2
497.2
545.2
Water
0
-502.6
-523.5
-113.3
-67.6
-78.3
-46.6
37.4
514.9
-76.5
2106.2
Bone
-479.2
172.0
-513.1
Material
2525.8
2120.5
Table 3-7: pixel values measured in the CATPHAN
ILUMA
iCAT
GAL
Material
Toshiba
CT #
P1
P2
Avr
P3
P4
P5
P6
Avr
P7
Acrylic
120
-488.6
-486.7
-116.1
-133.4
-175.0
-135.7
319
-375.3
-338.4
-11.7
-18.2
-59.2
-18.9
Teflon
936
13.8
18.5
259.6
296.4
247.8
298.8
-794.8
-847.8
-865.2
-849.6
-292.9
-320.3
-350.6
-319.6
-251.0
-232.8
-265.0
-232.0
-224.3
-207.2
-242.5
-211.1
-140.1
-27.0
275.6
-839.3
-320.8
-245.2
-221.3
2040.31
Delrin
-487.6
-356.8
16.2
-994.4
-689.9
-634.5
-599.8
Air
-1009
-994.1
-994.6
PMP
-190
-689.9
-689.8
LDPE
-99
-636.3
-632.7
Polystyrene
-41
-598.4
-601.1
2168.06
2404.22
1767.40
2079.51
2027.21
1952.82
Table 3-8: Pixel values measured in the CIRS phantom
ILUMA
iCAT
GAL
Material
Toshiba
CT #
P1
P2
Avr
P3
P4
P5
P6
Avr
P7
Bone
240
280.4
283.2
84.8
151.0
112.5
152.9
1053
1096.3
1102.1
707.1
730.2
665.2
735.7
Adipose
-69
-103.4
-107.5
-61.3
-105.4
-131.1
-104.1
Air
-1008
-995.8
-999.3
-923.9
-911.4
-901.3
-914.9
Muscle
55
35.6
36.8
8.9
-15.3
-46.4
-15.6
Brain
45
-4.5
-9.2
-22.8
-17.3
-42.8
-14.7
125.3
709.6
-100.4
-912.9
-17.1
-24.4
2389.3
Dense Bone
281.8
1099.2
-105.5
-997.5
36.2
-6.8
45
3016.8
2355.6
1655.4
2367.6
2355.1
Figure 3-4 shows the pixel values as measured in the i-CAT images compared to
their values as measured in the CT images. A linear fit was used with the data points. The
pixel values in the CIRS prototype were the most linear with an R2 value of 0.99. The
pixel values of the ACR phantom and CATPHAN were slightly less linear with R2 values
of 0.95 and 0.97, respectively.
i-CAT vs CT: Pixel Value Linearity
Pixel Value in i-CAT images
1500
y = 1.0219x - 2.592
R² = 0.9968
y = 0.6064x - 491.77
R² = 0.9558
1000
500
0
-1500
-1000
-500
0
500
1000
1500
-500
y = 0.5267x - 537.97
R² = 0.9728
-1000
-1500
CT number by Toshiba Acquilion 16
ACR phanotm
CATPHAN
CIRS prototype
Figure 3-4: pixel values measured in the i-CAT images vs the CT number measured in CT images
Figure 3-5 shows the pixel values in the ILUMA images as compared to their
values in the CT images for the three phantoms. The data points from the three phantoms
were fit to a linear equation. The data points from the ILUMA images of the CIRS
prototype phantom and ACR phantom were fairly linear with an R2 value of 0.99. The
CATPHAN pixel values, however, showed the least linearity with an R2 value of 0.97.
Figure 3-6 shows the pixel values in the GALILEOS images plotted against the
real CT numbers of the materials measured in the CT images. The GALILEOS system
46
uses all positive pixel value scale. The pixel values of the CIRS prototype phantom were
linear ( R2=0.98). The CATPHAN showed the least linearity of the pixel values
(R2=0.90).
ILUMA vs CT: Pixel Value Linearity
1000
y = 0.7878x - 78.152
R² = 0.996
y = 0.8137x - 142.08
R² = 0.9722
0
-1500
-1000
-500
0
500
-500
1000
1500
y = 0.5742x - 219.83
R² = 0.9925
-1000
-1500
CT number from Toshiba Aquilion 16
ACR phanotm
CATPHAN
CIRS Prototype
Figure 3-5: pixel values in the ILUMA images vs CT number (Hounsfield units) in CT
GALILEOS vs CT: Pixel Value Linearityy = 0.6483x + 2322.5
R² = 0.9845
3500
3000
PV from GALILEOS
PV in ILUMA
500
y = 0.562x + 2065.2
R² = 0.9547
2500
2000
y = 0.3175x + 2061.2
R² = 0.9057
1500
1000
500
0
-1500
-1000
-500
0
500
1000
1500
CT number from Toshiba
ACR phantom
Catphan
CIRS Prototype
Figure 3-6: pixel values in the GALILEOS images vs CT number (Hounsfield units) in CT
47
The pixel value accuracy of the images can be evaluated by using the y-intercept
values from the previous graphs and are summarized in Table 3-9. Ideally the y-intercept
would equal zero and the larger the deviation from zero the more inaccurate the pixel
values.
Table 3-9: the values of the y-intercept in the three phantoms
Scanner
ACR
CAT
CIRS
i-CAT
-491
-537
-2.5
ILUMA
-142
-219
-78
GALILEOS
2065
2061
2322
The y-intercept of the CIRS phantom for the i-CAT and ILUMA was the closest
to zero indicating a better pixel accuracy in this phantom. The y-intercepts in the ACR
phantom and CATPHAN significantly deviates from zero thus indicating poorer pixel
value accuracy. The pixel value accuracy cannot be evaluated in the GALILEOS as it
does not use a calibrated Hounsfield scale. The better accuracy observed in the CIRS
phantom is likely due to the reduced beam hardening effect compared to the ACR
phantom and CATPHAN.
3.4 Contrast Scale (CS)
The contrast scale measured in each phantom can be taken as the slope from
Figures 3-4, 3-5 and 3-6 and are summarized in Table 3-10. Figure 3-7 depicts the
difference in contrast scale between the phantoms.
48
Table 3-10: Contrast scale: the slope of the fitted lines in the pixel linearity graphs
i-CAT
ILUMA
GALELEOS
ACR phantom
0.61
0.81
0.56
Catphan
0.53
0.57
0.32
CIRS prototype
1.02
0.80
0.65
Contrast scale
1.2
1.02
1
CS (the slope)
0.81
0.8
0.8
0.61
0.6
0.57
0.53
0.65
0.56
0.32
0.4
0.2
0
i-CAT
ACR phantom
ILUMA
Catphan
GALELEOS
CIRS prototype
Figure 3-7: the contrast scale of the three phantoms
In the i-CAT images of the CIRS prototype the contrast scale (CS) is 1.02 which
Figure 4-10: the contrast scale of the three phantoms
indicates contrast sensitivity similar to that found in CT images. On the contrary, the CS
of the i-CAT images on the CATPHAN is 0.53 which means a change in the pixel value
Figure 4-10: the contrast scale of the three phantoms
in the conventional CT image would correspond significantly less change in the pixel
value measured in the CBCT image. The reduced contrast scale in the ACR phantom and
Figure 4-10: the contrast scale of the three phantoms
the CATPHAN is due to difference in phantom diameter from that of the CIRS phantom.
The larger diameter causes more beam hardening and increased noise levels.
49
In general, the CS in dental CBCT is less that optimal and the images from the
GALILEOS showed the worst CS among the three machines. The low contrast scale
would cause reduced low contrast detectability.
3.5 High contrast spatial resolution
The high contrast test objects in the CIRS Prototype, made of epoxy resin, did not
show enough contrast to be visualized in all of the images from the three scanners. The
high contrast test objects in the ACR phantom are located towards the edge of the
phantom which made it difficult to be assessed, especially in the GALILEOS images due
to the smaller FOV. Figure 3-8 show the smallest line pairs resolved in each phantom for
the i-CAT, ILUMA and GALILEOS images.
10
9
line pair/cm
8
7
6
5
4
3
2
1
0
iCAT
iCAT
ILUMA
ILUMA
ILUMA
1
2
3
4
5
ACR phantom
CATPHAN
ILUMA GALILEOS GALILEOS
6
7
CIRS phantom
Figure 3-8: the high contrast spatial resolution of the three phantoms.
50
8
Diameter of dental CBCT QA phantom
3.6 Calculation of water-equivalent diameter (Dw) for human dental and maxillofacial
region
Table 3-11 summarizes the calculation of Dw using equation 1-1. The minimum
Dw calculated was 156 mm while the maximum was 192 mm. The average Dw was 173±
12 mm. Thus a water cylinder with diameter of 173±12 mm will have the same
attenuation properties as the dental and maxillofacial scans that were selected.
Table 3-11: calculation of water-equivalent diameter of the dental and maxillofacial regions from CT images
Scan
subject 1
subject 2
subject 3
subject 4
subject 5
subject 6
subject 7
subject 8
subject 9
Subject 10
AROI (mm2)
24056
26973
28890
32510
26028
31815
29938
29908
27894
27985
Mean CT number
-200
-126
-215
-171
-268
-91
-171
-156
-223
-123
Dw (mm)
156
173
170
185
156
192
178
179
166
177
173 ±12
The calculation of the diameter of acrylic that would have similar photon
attenuation properties as the CT images chosen can be calculated using equation 1-2.
Both the Dw value (173 cm) and CT number of acrylic (120 HU) was plugged in equation
1-2 which resulted in an acrylic-equivalent diameter of 164 cm.
51
Chapter 4
Discussion
The results demonstrate that the phantom diameter has a significant impact on
image quality evaluation. In particular, measurement of the image noise, image
uniformity, and pixel value accuracy are all significantly impacted by the phantom
diameter. The presence of phantom material outside the image FOV (referred to as “exomass”) causes additional attenuation and beam hardening such that the evaluation of
these image quality parameters is compromised. Additionally, the larger diameter of the
ACR and CATPHAN phantoms often caused test objects to be at the very periphery of
the image FOV which complicated the assessment (e.g., the line pair objects for the ACR
phantom). All of these factors lead to the conclusion that the ACR and CATPHAN
phantoms are not ideal for routine assessment of dental CBCT since their diameter is
larger than the typical dental CBCT image FOV.
On the other hand, the CIRS prototype had its own limitations in that the line pair
test objects did not contain enough contrast for adequate evaluation of limiting spatial
resolution. Additionally, the relatively small diameter of the phantom did not allow for
assessment of image uniformity across a significant portion of the image FOV. Therefore,
design modifications are certainly necessary to make it a viable option for routine QA.
In comparison to conventional CT images the dental CBCT images possess higher
image noise, higher non-uniformities, larger pixel value inaccuracies, and reduced
52
contrast scale. All of these factors contribute to an overall reduced low contrast
detectability. Additionally, there is a much larger variation in measured image quality
parameters from manufacturer to manufacturer compared to that of conventional CT.
with that being said, the ability to define a standardized set of image quality performance
criteria, irrespective of dental CBCT scanner manufacturer, may not be possible. Instead,
baseline data may need to be established for each manufacturer’s scanner and thus used
as performance criteria.
The inadequacies of the phantoms that were tested prompted an investigation into
the optimal diameter of a phantom to be used for dental CBCT. An optimal phantom
would possess attenuation characteristics comparable to the human head as well as fit
within the typical FOV for a dental CBCT scanner. Using the methodology established in
AAPM Task Group Report 220; the equivalent diameter to achieve attenuation
comparable to the human head was found to be 173 mm for water and 164 mm for
acrylic. Given a standard FOV for a dental CBCT scanner to be 16 to 17 cm it is
recommended that an optimal phantom be approximately 16 cm in diameter and 13 cm to
15 cm in height. This concurs with the dimensions utilized in the commercially available
SEDENTEXCT and QUART phantoms.
The reduced contrast scale and relatively high noise levels in dental CBCT caused
the low contrast detectability objects in each of the tested phantoms to be undetectable.
Also, as discussed above, the line pair test objects to assess the spatial resolution in the
CIRS phantom were not discernable (they are quoted as 150 HU different from
background). Therefore, it is recommended that the test objects for both low contrast
53
detectability and high contrast spatial resolution possess enough attenuation difference to
allow for an adequate assessment of these image quality parameters.
.
54
Chapter 5
Conclusion
1. The ACR and CATPHAN phantoms have limited capability for use as a
routine quality assurance phantom. This is principally due to their
relatively larger diameter (20 cm for each phantom) and the presence of a
portion of the phantom outside the FOV for the dental CBCT units tested.
This caused beam hardening and excessive attenuation that compromised
evaluation of several of the image quality parameters.
2. The CIRS prototype was also limited in its functionality as a dental CBCT
phantom due to some design flaws. The primary problems involved the
inability to evaluate the line pair objects for limiting spatial resolution due
to their low contrast. In addition, the low contrast detectability objects
were not discerned and the relatively small diameter meant that image
uniformity was assessed over a relatively small FOV.
3. Based on the Dw for dental and maxillofacial region of the head and the
typical diameter of the FOV for CBCT scanners, an optimal phantom
diameter is between 15 to 17 cm and the height is 13 to 15 cm.
4. Due to reduced contrast scale and relatively high levels of image noise the
low contrast detectability and high contrast resolution test objects must
contain adequate contrast from that of background. In particular, the low
55
contrast test objects used in conventional CT scanners are inadequate for
the assessment in dental CBCT and must be on the order of 10%
attenuation difference (100HU) from that of background material.
56
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