Department of Radiation Physics,
the Sahlgrenska Academy at University of
Gothenburg, Gothenburg
Exploring the usage of fast kV-switching dual
energy CT for external photon beam
radiotherapy treatment planning
M.Sc. Thesis
Erik Pettersson
Supervisors:
Anne Thilander-Klang
Ulrika Lindencrona
Ninni Drugge
June 2015
Abstract
Introduction
In the context of radiotherapy, computed tomography (CT) images are used for target delineation
in treatment planning and to form an electron density map for the absorbed dose calculation. The
purpose of this master thesis is to compare CT images from a large bore polychromatic CT with
virtual monoenergetic (VME) images from a Dual Energy CT (DECT) system with and without
metal artefact reduction software (MARS), to evaluate how MARS depends on the choice of
reconstruction parameters, and to test the accuracy of effective Z images of metal pellets.
Materials and methods
The comparison was performed with regards to image quality and CT number accuracy in a
phantom with metal inserts, simulating a patient with bilateral titanium or stainless steel hip
prostheses. The depiction of prosthesis geometry and CT numbers were evaluated, as well as the
effect of metal artefact reduction with reconstruction diameter (DFOV) and differentiation of
metal pellets in effective z images.
Results
For titanium inserts the least amount of streaking was seen in VME images at 110 keV without
MARS. However, MARS was needed to remove streaks between the steel inserts and no energy
dependence in image quality was seen. The CT numbers of both titanium and steel inserts were
reduced to similar Hounsfield units when MARS was used. While the external diameter of titanium
inserts are underestimated with MARS, this was not the case for steel inserts. The geometric
accuracy was degraded by MARS at DFOV smaller than 20 cm. Effective Z images could not be used
to identify metal pellets in a water phantom.
Conclusions
In order to visualize the intraprosthetic region in patients with bilateral hip prostheses of
unknown metal, two sets of VME images at 110 keV should be reconstructed; with MARS in the
case of steel, and without MARS in case of titanium. Both can be reconstructed from a single DECT
scan. Correct CT numbers for the prostheses can be obtained given that the 16-bit HU range is
enabled during the reconstruction. A DFOV smaller than 20 cm should be avoided when using
MARS, and effective Z images could not distinguish metals with atomic numbers higher than
aluminium (Z=13).
1
Contents
Abstract ..................................................................................................................................................................................1
Abbreviations and acronyms ........................................................................................................................................4
Background...........................................................................................................................................................................5
Aims .........................................................................................................................................................................................5
Theory.....................................................................................................................................................................................6
Electron density .............................................................................................................................................................6
Effective atomic number ............................................................................................................................................6
Photons traversing matter ........................................................................................................................................6
Computed Tomography ..............................................................................................................................................7
Dual Energy Computed Tomography (DECT) ...................................................................................................8
Material decomposition..............................................................................................................................................9
Metal artefacts in CT images .................................................................................................................................. 13
Metal artefact reduction .......................................................................................................................................... 14
Radiotherapy absorbed dose calculation ......................................................................................................... 14
Materials and Methods ................................................................................................................................................. 14
Simulating hip prostheses ...................................................................................................................................... 15
CT number variation ............................................................................................................................................ 18
CT number to Relative Electron Density ..................................................................................................... 18
Severity of the streaks ......................................................................................................................................... 19
CT number profiles over inserts .......................................................................................................................... 19
MARS and DFOV.......................................................................................................................................................... 19
Effective Z ...................................................................................................................................................................... 20
Results ................................................................................................................................................................................. 21
Simulating hip prostheses ...................................................................................................................................... 21
Image appearance ................................................................................................................................................. 21
CT number variation ............................................................................................................................................ 25
CT number to RED................................................................................................................................................. 26
Severity of the streaks ......................................................................................................................................... 27
CT number profiles over inserts .......................................................................................................................... 28
MARS and DFOV.......................................................................................................................................................... 31
Effective Z ...................................................................................................................................................................... 32
Discussion .......................................................................................................................................................................... 33
Simulating hip prostheses ...................................................................................................................................... 33
Image appearance ................................................................................................................................................. 33
CT number variation ............................................................................................................................................ 34
CT number to RED................................................................................................................................................. 34
2
Severity of the streaks ......................................................................................................................................... 35
CT number profiles over inserts .......................................................................................................................... 35
MARS and DFOV.......................................................................................................................................................... 36
Effective Z ...................................................................................................................................................................... 37
Conclusions........................................................................................................................................................................ 37
Topics of Further Research ......................................................................................................................................... 37
References .......................................................................................................................................................................... 38
Appendix............................................................................................................................................................................. 40
3
Abbreviations and acronyms
ASIR
CT
CTDI
DECT
DFOV
FBP
FKS
FOV
GE
GOS
GSI
HU
MAR
MARS
MD
POM
RED
ROI
SFOV
SNR
VME
VOI
4
Adaptive Statistical Iterative Reconstruction
Computed Tomography
CT Dose Index
Dual Energy CT
Display Field Of View
Filtered Backprojection
Fast Kilovoltage Switching
Field Of View
General Electric
Gadolinium Oxysulfide
Gemstone Spectral Imaging
Hounsfield Unit
Metal Artifact Reduction
Metal Artefact Reduction Software
Material Density
Polyoxymethylene
Relative Electron Density (to water)
Region Of Interest
Scan Field Of View
Signal to Noise Ratio
Virtual Monoenergetic
Volume Of Interest
Background
Computed Tomography (CT) have two main uses in the context external photon beam
radiotherapy. The first is identification and delineation of the clinical target volume (CTV) and
organs at risk (OAR) volumes in the patient. The second is to form a base for the therapeutic dose
calculation. CT-scans produce images from projections through the patient, based on the
attenuation of the X-rays in the body. If a patient has large metal implants such as bilateral hip
prostheses near the target area and/or OAR, the images can be severely degraded by dark and
light streaks because of the high attenuation of metals. These so called image artefacts result in
loss of information and can significantly reduce the possibility to delineate the volumes
corresponding to the target and OAR volumes.
Errors in the CT numbers in the images will also lead to increased uncertainties in the calculated
dose to the patient. The dose calculation is based on the conversion of CT numbers in the images
to electron density relative water (RED), based on phantom measurements.
In the case of a patient with unilateral hip prosthesis it is often possible to avoid irradiation
through the prosthesis by choosing suitable field angles. This is not always possible in the case of
bilateral prostheses. It is therefore of interest to be able to differentiate between the metal and
the surrounding tissue, and to determine which material (titanium, stainless steel or Co-Cr alloys)
the implant in the CT image is made of. This information is needed for calculation of the
attenuation of the therapeutic beam through the prostheses.
This work will investigate how a Dual Energy CT (DECT) scanner could reduce metal artefacts and
acquire the RED of patients with bilateral hip prostheses, compared to a large bore polychromatic
CT scanner that is currently used for this purpose.
Aims
5

Evaluate how the streaking in images of patients with bilateral metal hip prostheses could
be improved with Fast kilovoltage switching (FKS) DECT and enable delineation of
structures between the prostheses. Study how these images are affected by the choice of
photon energy in virtual monoenergetic (VME) images.

Investigate how to improve the formation of electron density maps from CT images using
an electron density phantom with and without metal implants.

Evaluate how the CT numbers and the geometric depiction of titanium and stainless steel
implants vary with image reconstruction parameters, such as; an extended (16-bit)
Hounsfield unit scale, GE’s metal artefact reduction software (MARS) and the
reconstruction diameter (DFOV).

Investigate the quantification of different metallic materials with similar geometry in a
water phantom by the use of effective Z images.
Theory
Electron density
The electron density 𝑛𝑒 [cm-3] of a medium is given by
𝑍
𝑛𝑒 = 𝜌𝑁𝐴 ( )
𝐴 𝑚𝑒𝑑
(1)
𝑍
Where 𝜌 is the material mass density, 𝑁𝐴 is the Avogadro constant [𝑚𝑜𝑙 −1 ] and (𝐴)
number of electrons per molecular mass in the medium given by
𝑍
𝑍
( )
= ∑ 𝑤𝑖𝐴𝑖
𝑖
𝐴 𝑚𝑒𝑑
𝑚𝑒𝑑
is the
(2)
𝑖
where 𝑤𝑖 is the fractional weight of element 𝑖 in the medium, such that ∑𝑖 𝑤𝑖 = 1.
The relative electron density to water (RED) is formed by dividing 𝑛𝑒 with the electron density of
water 𝑛𝑒,𝑤 . [1]
𝑍
𝜌𝑒 ( )
𝑛𝑒
𝐴 𝑚𝑒𝑑
𝑅𝐸𝐷 =
=
𝑛𝑒,𝑤 𝜌 (𝑍 )
𝑒,𝑤 𝐴
𝑤
(3)
Effective atomic number
In materials composed of a mix of elements, the constituent element atomic numbers can be
combined as an effective atomic number 𝑍𝑒𝑓𝑓 as described by the Mayneord formula.
𝑘
𝑁
𝑍𝑒𝑓𝑓 = √∑ 𝑎𝑖 𝑍𝑖𝑘
(4)
𝑖=1
Where N is the number of elements present in the material, and 𝑎𝑖 is the mass fraction of the
element. The constant 𝑘 depends both on the atomic numbers 𝑍𝑖 and the photon energy but is
empirically fitted to 2.94 [2]. This is an approximate method for determining 𝑍𝑒𝑓𝑓 , more rigourous
method are described by Taylor et al. in [3] and [4]. As can be seen in equation 3, 𝑍𝑒𝑓𝑓 contributes
most to µ at low photon energies.
Photons traversing matter
The probability P of a photon with energy E to be stopped when traversing through a
homogeneous material with thickness d, is described by the linear attenuation coefficient µ in the
Lambert-Beer law.
𝑃(𝐸) = 𝑒 −µ(𝐸)𝑑
(5)
The energy dependence of µ is a consequence of the energy dependent interaction mechanisms.
Photoelectric effect and Compton scattering are the main interaction mechanisms for photons
with energies ranging from 20 to 200 keV. Rayleigh scattering is usually ignored because of the
limited cross section, as are pair production and photonuclear reactions that require photon
energies in excess of 1.022 MeV and 10 MeV respectively.[5]
For photon energies below 1.02 MeV, µ can be expressed as a function of the electron density 𝑛𝑒 ,
the electronic cross sections for photoelectric effect 𝜎𝑒,𝑝 and Compton scattering 𝜎𝑒,𝐶 .
µ(𝐸) = 𝑛𝑒 [𝜎𝑒,𝑝 + 𝜎𝑒,𝐶 ]
6
(6)
Where 𝜎𝑒,𝑝 is dependent on both the atomic number Z of the material and the photon energy E.
𝜎𝑒,𝑝 (𝐸) ∝
𝑍𝑛
𝐸𝑚
(7)
The exponent n varies between 3 to 4 for increasing Z and m is approximately equal to 3 [2].
The electronic Compton scattering cross section 𝜎𝑒,𝐶 depends simply on the photon energy
through the Klein-Nishina function 𝑓𝐾𝑁 .
𝜎𝑒,𝐶 (𝐸) ∝ 𝑓𝐾𝑁 (𝐸) =
3𝜎0 1 + 𝛼 2(1 + 𝛼) 𝑙𝑛(1 + 2𝛼)
𝑙𝑛(1 + 2𝛼)
1 + 3𝛼
{( 2 ) (
−
)+
−
}
(1 + 2𝛼)2
4
𝛼
1 + 2𝛼
𝛼
2𝛼
(8)
𝐸
where 𝛼 = 511 [𝑘𝑒𝑉] , and 𝜎0 is the Thomson cross section [2].
With only the photoelectric and Compton interactions in mind, equation 2 can now be written as
a function of position r and photon energy E.
µ(𝒓, 𝐸) = 𝑛𝑒 (𝒓) [𝛼
𝑍 𝑛 (𝒓)
+ 𝛽𝑓𝐾𝑁 (𝐸)]
𝐸𝑚
(9)
where 𝑛𝑒 (𝒓) is the electron density at position r and constants α, β, n and m are fitted to the photon
energies and materials used in the application of interest [1].
Computed Tomography
Computed Tomography (CT) in the context of medical imaging is the principle of taking
projections through the patient from a multitude of directions, and from these projections
reconstruct a map of the linear attenuation coefficient µ(r) of the X-rays inside the patient at
position r. Modern CT scanners reconstruct volumes with discrete values of µ in the object
examined. These volume elements are called voxels, in analogy to the term pixel used for picture
elements. The smallest size of the voxels are determined by the size of the detector elements in
the z (longitudinal) direction of the scanner, the display field of view (DFOV) and the image matrix
size. The choice of voxel size is decided with respect to the resolution needed for the application,
tolerated partial volume effects and noise levels in the images. The estimated µ is most often
presented as the CT number, expressed in Hounsfield units (HU),
CT number =
µ(𝒓) − µ𝐻2𝑂
1000 [𝐻𝑈]
µ𝐻2𝑂 − µ𝑎𝑖𝑟
(10)
where the attenuation in a voxel µ(𝒓) is compared to the attenuation in water at the effective
energy of the X-ray spectrum. This definition results in a CT number of zero for water, and -1000
HU for air. The CT numbers have historically been limited to a 12-bit domain of -1024 to 3071 HU
because of limited dynamic range of the digital signal processing electronics conducting the fast
Fourier transform during the reconstruction process. The interval from -1024 up to 3071 HU will
cover most of the CT numbers of materials inside the human body, excluding dense objects like
metal implants and gold or amalgam in teeth. These dense materials will be assigned the
maximum voxel value of 3071 HU, thus they cannot be separated by their CT numbers. Most metal
implants have CT numbers in the range of 8000 HU to 20000 HU [6]. Modern CT scanners are
equipped with an extended range of 16-bit CT numbers that covers a domain of 65536 values
[-32767, 32768] HU. This extended bit depth is standard on the [Aquilion LB (Toshiba Medical
Systems)] and can be selected on the [Discovery CT750 HD (General Electric)] used in this thesis.
7
Dual Energy Computed Tomography (DECT)
The concept of using multiple X-ray spectra to determine elemental composition of tissues in the
body was presented by Hounsfield as early as 1973. By performing two consecutive scans with
different tube voltages, 100 kV and 140 kV, and comparing the two sets of images. A map of the
effective atomic number in the tissues of the body could be extracted due to the energy
dependency of the linear attenuation coefficient µ. [7]
This image based concept was verified by Rutherford in 1976 where images of electron density
and effective atomic numbers of brain tissue could be obtained by scanning with two X-ray spectra
given enough separation of their respective mean energies. [8]
This method was sensitive to patient movement between the two scans, which caused
misregistration of the images. The two separate sets of images also needed separate beam
hardening corrections, which adds to the error of the dual energy images. [9]
A projection based method was introduced by Alvarez and Macovski in 1976, where projection
rays with different energies are compared to each other prior to image reconstruction, instead of
comparing the reconstructed images [10]. This concept is utilized in the Fast kV Switching (FKS)
method, where the tube voltage is modulated between the high and low kVp such that the
projection from every angle is measured two times with different X-ray spectra. FKS was first
introduced in a clinical CT system with the [Somatom DR (Siemens Healthcare)] in the 1980’s [9,
11].
General Electric (GE) has since then developed the FKS concept further with the Discovery CT750
HD scanner (Figure 1). The GE marketing name for FKS is Gemstone Spectral Imaging (GSI), where
Gemstone™ is the name for the garnet crystal scintillator material in the detector elements.
Gemstone features a shorter decay time of the scintillation light output compared to the standard
Gadolinium oxysulfide (GOS) scintillators often used in CT scanners. With a fast decay of the light
signal, the sampling rate of projection rays can be increased, thereby achieving both high temporal
and spatial resolution [12].
Figure 1. Principle of the FKS method, where every other projection is performed with high
and low energy spectra (green and blue) during rotation of the scanner gantry. (Image
courtesy of GE Healthcare)
When scanning with GE’s Discovery CT750 HD in a GSI scan mode, the tube voltage is modulated
at a frequency of up to 4.8 kHz such that projections with the 80 kVp or 140 kVp spectra can be
8
sampled in 150 µs [13]. To account for the change in angles between high and low energy
projections caused by the gantry rotation between the sampling of projection rays, interpolation
between adjacent projections can be utilized [14].
The radiation dose to the patient is optimized by having similar photon flux to the detectors for
𝑁
the two spectra. The optimal photon flux ratio between adjacent low and high projections 𝑁 𝐿 is
𝐻
given by the following condition.
𝑁𝐿
𝐷𝐻
=√
𝑁𝐻
𝐷𝐿
(11)
Where 𝐷𝐻 and 𝐷𝐿 are the mAs-normalized tube outputs (photons per mAs) at 140 kVp and 80
kVp. As the tube output is about three times higher for spectrum at 140 kVp than at 80 kVp the
optimal flux ratio is about 1.73 higher for the low energy spectrum [15]. This can be achieved by
increasing the tube current for the 80 kVp spectra. However, as it is technically challenging to
modulate the tube current with these high frequencies, the sampling times for the 80 kVp spectra
are instead increased [14].
An increased dose efficiency for FKS DECT has been demonstrated with the use of a K-edge filter
to separate the mean energies of the high and low spectra, at the cost of increases in tube current
or sampling times [16].
The radiation dose (in mGy) expressed in volume CT Dose Index (𝐶𝑇𝐷𝐼𝑣𝑜𝑙 ) is proportional to the
radiation output of the CT system and is defined as
𝐶𝑇𝐷𝐼𝑣𝑜𝑙
1
2
𝐶𝑇𝐷𝐼100 (𝑐𝑒𝑛𝑡𝑟𝑎𝑙) + 𝐶𝑇𝐷𝐼100 (𝑝ℎ𝑒𝑟𝑖𝑝𝑒𝑟𝑎𝑙)
3
3
=
𝑃𝑖𝑡𝑐ℎ
(12)
Where 𝐶𝑇𝐷𝐼100 is the integrated dose based on ionization chamber measurements over 100 mm
in a polymethacrylate (PMMA) phantom. The pitch is the ratio of the table movement over one
gantry rotation and the width of the collimator aperture. [12]
The radiation dose expressed in 𝐶𝑇𝐷𝐼𝑣𝑜𝑙 for the virtual monochromatic images is roughly 14-22%
higher compared to a standard 120 kVp scan with similar low contrast visibility. [17]
Material decomposition
With the FKS method, the measured attenuation coefficient µ(E) for the two tube voltages can be
expressed as a linear combination of basis functions 𝑓𝑖 (𝐸) chosen to fit the measured data. [10]
µ(𝐸) = ∑ 𝑎𝑖 𝑓𝑖 (𝐸)
(13)
𝑖
This method is essentially a mathematical change of variables from two measurements at
different energies to two other basis functions. The basis functions can be interaction mechanisms
(photoelectric and Compton scattering), physiological materials (fat and bone, water and iodine)
or the two largest singular values in a singular value decomposition of the measurement data. [18]
The principle of material decomposition can be illustrated by an idealized example with two
monoenergetic projection rays (Figure 2). The X-ray intensities (𝐼𝐿 ) and (𝐼𝐻 ) are measured for
two different monoenergetic X-ray energies (𝐸𝐿 , 𝐸𝐻 ) along the same ray path through an object,
and then they are compared with the X-ray intensities measured without the object present
(𝐼𝐿0 , 𝐼𝐻0 ).
9
Figure 2. Schematic view of a projection line through an object (𝐼𝐿 , 𝐼𝐻 ) are the measured X-ray intensities when the beam
has passed through the object for the low and high photon energies. (𝐼𝐿0 , 𝐼𝐻0 ) are the measured intensities through air
without any object present.
Using the four measurements and knowledge of the two photon energies, the integrated material
along the projection ray can be decomposed into amounts of two basis materials along the ray
path as given by equation 1.
(14)
𝐼𝐿
𝐼𝐿0 𝑒 − ∫ µ(𝐸𝐿 )𝑑𝑙
]
[ ]=[
𝐼𝐻
𝐼𝐻0 𝑒 − ∫ µ(𝐸𝐻 )𝑑𝑙
Taking the logarithm of the ratio of measured intensities (𝐼𝐿 , 𝐼𝐿0 ) and (𝐼𝐻 , 𝐼𝐻0 ) yields the
logarithmic projections 𝑔𝐿 and 𝑔𝐻 .
[𝑔𝑔𝐿 ]
𝐻
=[
𝐼
𝑙𝑛( 𝐿0 )
µ(𝐸 ) 𝑑𝑙
]=[∫∫ µ(𝐸𝐿 )𝑑𝑙 ]
𝐼𝐿
𝐼𝐻0
𝑙𝑛(
)
𝐼𝐻
𝐻
(15)
The integrals can be expressed as a linear combination of the mass density and mass attenuation
of each of the two basis materials at the different photon energies.
∫(𝜌1 (𝜌µ) (𝐸𝐿 ) + 𝜌2 (𝜌µ) (𝐸𝐿 ))𝑑𝑙
𝑔𝐿
1
2
[ ]=[
]
µ
µ
𝑔𝐻
∫(𝜌1 (𝜌) (𝐸𝐻 ) + 𝜌2 (𝜌) (𝐸𝐻 ))𝑑𝑙
1
(16)
2
Given that the X-rays are monoenergetic, the line integrals can be expressed as the integrated
material densities 𝑑1 and 𝑑2 [g cm-2] of the two basis materials along the projection ray. This
since the mass attenuation coefficients of the basis materials do not vary with position.
𝑑1 (µ𝜌) (𝐸𝐿 ) + 𝑑2 (µ𝜌) (𝐸𝐿 )
𝑔𝐿
1
2
[ ]=[
]
µ
µ
𝑔𝐻
𝑑1 (𝜌) (𝐸𝐻 ) + 𝑑2 (𝜌) (𝐸𝐻 )
1
(17)
2
As the mass attenuation coefficients for different elements are readily available from the National
Institute of Standards and Technology (NIST), the integrated densities 𝑑1 and 𝑑2 can be solved by
inverting the matrix in the following system of linear equations for any basis material.
µ
(𝜌) (𝐸𝐿 )
𝑔𝐿
[ ]=[ µ 1
𝑔𝐻
( ) (𝐸 )
𝜌 1
𝐿
µ
(𝜌) (𝐸𝐻 )
2
] [𝑑1 , 𝑑2 ]
µ
( ) (𝐸𝐻 )
(18)
𝜌 2
In order to invert the matrix of mass attenuation coefficients in the equation above, the photon
energies 𝐸𝐿 and 𝐸𝐻 must be separated enough. However, if any of the materials inside the object
have X-ray absorption between the energies 𝐸𝐿 and 𝐸𝐻 , the material decomposition will fail. A
10
common basis material pair used in clinical applications is water together with a compound with
a higher atomic number, such as iodine and calcium which have K-edges at 33 and 4 keV,
respectively. [19]
Material density (MD) images can be reconstructed when 𝑑1 and 𝑑2 have been computed for all
projection angles around the object in the CT-scanner. The voxels of the MD images are
concentrations of the basis materials in [g cm-3]. It is possible to convert the MD images from one
basis pair to another in the image space, without the need for an extra scan or reconstruction from
the projection raw data. [20]
Given the density of the basis material in the MD images, virtual monoenergetic (VME) images can
be formed from the materials mass attenuation coefficients. [21]
µ(𝐸)
)
𝜌 𝑤𝑎𝑡𝑒𝑟
µ(𝒓, 𝐸) = 𝜌𝑤𝑎𝑡𝑒𝑟 (𝒓) (
µ(𝐸)
)
𝜌 𝑖𝑜𝑑𝑖𝑛𝑒
+ 𝜌𝑖𝑜𝑑𝑖𝑛𝑒 (𝒓) (
(19)
Also, effective Z images can be formed from the material densities, and the effective Z of each basis
material.
4.4 + 𝜌
4.4
𝟒.𝟒 𝜌
𝑤𝑎𝑡𝑒𝑟 (𝒓) ∙ 7.42
𝑖𝑜𝑑𝑖𝑛𝑒 (𝒓) ∙ 53
𝑍𝑒𝑓𝑓 (𝒓) = √
𝜌𝑤𝑎𝑡𝑒𝑟 (𝒓) + 𝜌𝑖𝑜𝑑𝑖𝑛𝑒 (𝒓)
(20)
When dealing with polyenergetic X-ray spectra from real X-ray tubes, and not idealized
monoenergetic sources, the expressions for the integrals 𝐼𝐿 , 𝐼𝐻 becomes somewhat more involved.
The measured projection data needs to be corrected for the spectral response of the system since
the FKS X-ray spectra varies during the sampling time of the signals. This variation is caused by
non-ideal switching of the tube voltage, jitter in the voltage waveform if the clocks in the generator
and data acquisition system are not synchronous [22].
Since the spectrum reaching each detector channel 𝛾 varies with time a spectral calibration of the
detectors is required. The calibration will affect the correction of the heel effect and beam
hardening in the bowtie filter. The resulting spectrum 𝑆(𝐸) is modelled as a weighted
superposition of 𝑁𝑘 intermediate spectra 𝑆𝑘 (𝐸) with constant kVp.
𝑁𝑘
𝑆(𝐸) = ∑ α𝑘 𝑆𝑘 (𝐸)
(21)
𝑘=1
where 𝛼𝑘 is the weighting factor for each spectrum 𝑆𝑘 . The normalized detector response 𝑅(𝛾)
corrects for the variations of the X-ray spectrum caused by variations in the composition of the
bowtie filter in the direction of detector channel 𝛾, which described by the geometry factor 𝐺𝑘 (𝛾).
𝑅(𝛾) =
∑𝑘 α𝑘 𝐺𝑘 (𝛾)
∑𝛾 ∑𝑘 α𝑘 𝐺𝑘 (𝛾)
𝐺𝑘 (𝛾) = ∫ 𝑆𝑘 (𝐸) ∙ 𝐸 ∙ [1 − 𝑒 −µ𝛾(𝐸)∙𝑡𝑑 ] ∙ 𝑒 − ∑𝑏 µ𝑏 (𝐸,𝛾)∙𝐼𝑏 (𝛾) 𝑑𝐸
(22)
(23)
Where 𝐼𝑏 (𝛾) is the thickness of the bowtie filter in the direction of detector channel 𝛾. µ𝑏 (𝐸, 𝛾) is
the linear attenuation coefficient of the bowtie filter at energy E in direction of detector channel 𝛾.
µ𝛾 (𝐸) is the attenuation coefficient of the detector and 𝑡𝑑 its thickness. The coefficients 𝛼𝑘 are
then determined by a least square fit of 𝑅(𝛾) and 𝐺𝑘 (𝛾), where 𝑅(𝛾) is measured from an air scan
and 𝐺𝑘 (𝛾) is calculated from a model of the CT geometry. [22]
11
After the calibration, the low and high energy measurements 𝐼𝐿 and 𝐼𝐻 corresponding to the
spectra 𝑆𝐿 (𝐸) and 𝑆𝐻 (𝐸), can be used to form the projections 𝑔𝐿 and 𝑔𝐻 . Given the previous
expression for the linear attenuation coefficient µ (equation 5), integrated over the normalized
spectra 𝑆𝑖 (𝐸) such that ∫ 𝑆𝑖 (𝐸)𝑑𝐸 = 1.
𝐼𝐿0
𝑍 𝑛 (𝒓)
) = ∫ 𝑆𝐿 (𝐸) ∙ (∫ 𝜌𝑒 (𝒓) [𝛼 𝑚 + 𝛽𝑓𝐾𝑁 (𝐸)] 𝑑𝑙) 𝑑𝐸
𝐼𝐿
𝐸
𝐼𝐻0
𝑍 𝑛 (𝒓)
𝑔𝐻 = 𝑙𝑛 ( ) = ∫ 𝑆𝐻 (𝐸) ∙ (∫ 𝜌𝑒 (𝒓) [𝛼 𝑚 + 𝛽𝑓𝐾𝑁 (𝐸)] 𝑑𝑙) 𝑑𝐸
𝐼𝐻
𝐸
𝑔𝐿 = 𝑙𝑛 (
(24)
As neither 𝜌𝑒 𝑍 𝑛 nor 𝜌𝑒 depend on the photon energy they can be integrated along the projection
line to form the integrals 𝐴𝑃 and 𝐴𝐶 .
(25)
𝐴𝑃 = ∫ 𝛼𝜌𝑒 (𝒓)𝑍 𝑛 (𝒓)𝑑𝑙
(26)
𝐴𝐶 = ∫ 𝛽𝜌𝑒 (𝒓)𝑑𝑙
Then, the projection 𝑔𝑖 and 𝑔𝑖 can be written as an integral over photon energy,
𝐴𝑃
+ 𝑓𝐾𝑁 (𝐸)𝐴𝐶 ] 𝑑𝐸
𝐸𝑚
𝐴𝑃
𝑔𝐻 = ∫ 𝑆𝐻 (𝐸) ∙ [ 𝑚 + 𝑓𝐾𝑁 (𝐸)𝐴𝐶 ] 𝑑𝐸
𝐸
𝑔𝐿 = ∫ 𝑆𝐿 (𝐸) ∙ [
(27)
The equations can now be integrated over the normalized low and high energy spectra 𝑆𝐿 and 𝑆𝐻 .
𝐴𝑃
∫ 𝑆𝐿 (𝐸) ∙ 𝑒 𝐸𝑚 + 𝑓𝐾𝑁 (𝐸)𝐴𝐶 𝑑𝐸
∫ 𝑆𝐿 (𝐸) ∙ 𝑒 µ𝑝(𝐸)𝐴𝑃 + µ𝐶 (𝐸)𝐴𝐶 𝑑𝐸
𝑔𝐿
[ ]=[
]=[
]
𝐴𝑃
𝑔𝐻
+ 𝑓𝐾𝑁 (𝐸)𝐴𝐶
µ
(𝐸)𝐴
+
µ
(𝐸)𝐴
𝑚
𝑝
𝑃
𝐶
𝐶
∫ 𝑆𝐻 (𝐸) ∙ 𝑒
𝑑𝐸
∫ 𝑆𝐻 (𝐸) ∙ 𝑒 𝐸
𝑑𝐸
(28)
This system of nonlinear equations can now be solved numerically for 𝐴𝑃 and 𝐴𝐶 for each
projection. The system can be linearized with the rest terms treated as beam hardening terms
(𝐵𝐻)
(𝐵𝐻)
𝑔𝐿
and 𝑔𝐻 ,
(𝐵𝐻)
µ̅𝐿𝑃 𝐴𝑃 + µ̅𝐿𝐶 𝐴𝐶 − 𝑔𝐿 (𝐴𝑝 , 𝐴𝐶 )
𝑔𝐿
[ ]=[
]
(𝐵𝐻)
𝑔𝐻
µ̅𝐻
̅𝐻
(𝐴𝑝 , 𝐴𝐶 )
𝑃 𝐴𝑃 + µ
𝐶 𝐴𝐶 − 𝑔𝐻
(29)
The beam hardening terms are expressed as
(𝐵𝐻)
𝑔𝐿
𝐿
𝐿
(𝐴𝑝 , 𝐴𝐶 ) = 𝑙𝑛 ∫ 𝑆𝐿 (𝐸, 𝛾) ∙ 𝑒 −𝐴𝑝 ∆µ̅𝑝 (𝐸,𝛾)−𝐴𝐶 ∆µ̅𝐶 (𝐸,𝛾) 𝑑𝐸
(𝐵𝐻)
𝑔𝐻 (𝐴𝑝 , 𝐴𝐶 )
= 𝑙𝑛 ∫ 𝑆𝐻 (𝐸, 𝛾) ∙ 𝑒
̅𝐻
̅𝐻
−𝐴𝑝 ∆µ
𝑝 (𝐸,𝛾)−𝐴𝐶 ∆µ
𝐶 (𝐸,𝛾)
(30)
𝑑𝐸
Where ∆µ̅𝐿,𝐻
̅ 𝐿,𝐻
𝑃,𝐶 (𝐸, 𝛾) = µ𝑃,𝐶 (𝐸, 𝛾) − µ
𝑃,𝐶 (𝛾) is the differences from the average attenuation due to
photoelectric and Compton scattering for each spectrum at detector channel γ.
µ̅𝐿𝑃,𝐶 (𝛾) = ∫ 𝑆𝐿 (𝐸, 𝛾)µ𝑃,𝐶 (𝐸)𝑑𝐸
µ̅𝐻
𝑃,𝐶 (𝛾) = ∫ 𝑆𝐻 (𝐸, 𝛾)µ𝑃,𝐶 (𝐸)𝑑𝐸
12
(31)
The beam hardening corrected projections photoelectric and Compton scattering, 𝐴𝑝 and 𝐴𝐶 are
then solved for iteratively.
(𝐵𝐻)
𝑇
𝑛−1
𝑔𝐿 − 𝑔𝐿 (𝐴𝑛−1
𝐴𝑛𝑝
̅ 𝐿𝐶 −µ̅𝐻
𝑃 , 𝐴𝐶 )
𝐶
−1 µ
][
[ 𝑛] = 𝐷 [ 𝐿
]
(𝐵𝐻)
𝑛−1
−µ̅𝑝 µ̅𝐻
𝐴𝑐
𝑔𝐻 − 𝑔𝐻 (𝐴𝑛−1
𝑝
𝑃 , 𝐴𝐶 )
where D is the determinant of the Jacobian matrix of attenuation coefficients,
𝐷 = µ̅𝐻
̅ 𝐿𝐶 − µ̅𝐿𝑝 µ̅𝐻
𝑝µ
𝐶
(32)
(33)
Given small beam hardening terms, the system should converge quickly in a numerically stable
manner when solved by an iterative method. [23]
Once 𝐴𝑃 and 𝐴𝐶 is acquired, any reconstruction algorithm can be used to obtain photoelectric or
Compton images. As the relations of photoelectric effect and Compton scattering are known for
most chemical elements for photon energies in the X-ray range, these interaction images can then
be scaled to form MD images, as long as the elements do not have absorption edges in the energy
ranges of the spectra 𝑆𝐿 and 𝑆𝐻 .
Metal artefacts in CT images
Dense objects inside patients during the CT image acquisition will attenuate the photon flux much
more than soft tissue. Metal objects in the field of view during CT scan will affect the images in a
number of unwanted ways, these are beam hardening, photon starvation and scattering. These
processes occurs in all materials, albeit to a lesser extent in low Z materials such as tissue. This
since the mass density and variation in µ over the energies in the X-ray spectrum is lower for
tissue compared higher Z materials such as metals.
Beam hardening is the process were the mean photon energy of an X-ray spectrum increases as it
traverses through matter, as low energy photons are attenuated to a higher degree than high
energy photons. Beam hardening is most recognizable in an image of a homogeneous water
phantom. This is the so called cupping artefact, where profiles across the homogeneous cylindrical
phantom resembles a cup with lower CT numbers in the middle of the phantom compared to the
edges [12].
The beam hardening correction is usually performed by weighting down low signal projections
compared to high signal projections. The weighting scheme is determined by calibration
measurements of a water phantom [12]. That is, if we measure a high attenuation (low signal)
through the patient, the attenuation is not as high at is should be, because the mean energy of the
X-ray spectra has increased. The measured signal is higher than it should have been without beam
hardening, as µ is lower for higher energies. This can be corrected for by weighting the signal with
respect to calibration values acquired from a scan with a water phantom [24, 25].
Scattering in CT images causes artefacts similar to those from beam hardening and can be reduced
by scanning with a smaller detector collimation, using an anti-scatter grid in front of the detector.
The scattered photons can also be measured with a detector outside the FOV. These
measurements can be used to correct the projection data for the signal caused by scattered
photons. [25]
Photon starvation, is a manifestation when the detector receives too few photons, resulting in
noisy images with high intensity streaks [26]. The artefacts caused by photon starvation can be
reduced by increasing the photon flux tube over the affected area. This can be done by increasing
the tube current or reducing the rotation time at the cost of increased radiation dose to the patient
[12]. Filtering of noisy measurements can be performed before taking the logarithm of the
measured projections [26].
13
Metal artefact reduction
Although projection based DECT inherently corrects for beam hardening, the images will still
suffer from streaking artefacts when the patient has dense metal objects in the area being scanned.
The streaks can be mitigated by using so called metal artefact reduction (MAR) techniques.
In general, MAR identifies which parts of the measured projections that are corrupted by metal
and a metal only image is then created by thresholding the high CT numbers corresponding to
metal in the images. The corrupted samples are then inpainted with data created from a
combination of the original projection data and a forward projection of the metal only image. The
vendors of CT systems have various MAR methods, such as [MARS and MAR (GE)], [iMAR (Siemens
Healthcare)], [SEMAR (Toshiba Medical systems)] and [O-MAR (Philips Healthcare)].
The GSI scan modes have an option for reduction of metal artefacts, Metal Artefact Reduction
Software (MARS), which is applied in the projection (raw data) domain. MARS can be applied
retrospectively without an additional scan, as long as the raw data from the scan is accessible.
Earlier studies have investigated how MARS is affected by the choice of energy in VME images and
different Display Field of View (DFOV), where the shape of prostheses seems to change when
MARS is applied and DFOV changed. [27]
MARS also removes artefacts from interstitial gold seeds implanted for navigation in stereotactic
radiotherapy. It improves visibility around the seed although the artefacts were worse when the
seeds were oriented in the craniocaudal direction [28]. However, the use of MARS has been shown
to reduce image quality in certain cases, such as in observation of thin metal objects [29]. It also
seems to affect image slices adjacent to slices containing metal, which were not affected by metal
artefacts in images reconstructed without MARS [30].
Radiotherapy absorbed dose calculation
The main interaction process of photons in the therapeutic photon spectra with maximum
energies between 6 MV and 18 MV is Compton scattering. To calculate the absorbed dose
distributions, the CT numbers of the patient CT image is converted to electron density relative to
water. A calibration curve converts CT numbers to electron density [5]. The calibration curve is
different for different CT scanners, as the CT numbers depends on the effective energy of the X-ray
spectra [8].
In radiotherapy treatment planning of patients with bilateral metal hip prostheses, CT images of
the patient are affected by artefacts in images of the area between the prostheses, which is due to
the high attenuation of the metal. The artefacts will make the delineation of the target based on
the CT image much more difficult, if not impossible. However, other imaging modalities can be
used for delineation, i.e. Magnetic Resonance Imaging (MRI), Positron Emission Tomography
(PET) and ultrasound.
Radiotherapy of prostate cancer often includes irradiation in the lateral direction through the
pelvis because these beam orientations will reduce the absorbed dose to the OAR, i.e. the rectum
and the urinary bladder. Information of the material, external contour and internal structure of
the prosthesis are of interest in order to reduce the uncertainty in the dose calculation when
choosing beam directions through hip prostheses.
Materials and Methods
The two CT scanners used in this study were the large bore CT-scanner at the oncology
department of the Sahlgrenska University Hospital, [Aquilion LB (Toshiba Medical Systems,
Tokyo, Japan)] (Figure 3, left), hereon referred to as the “Toshiba scanner”. This CT scanner is
adapted for radiotherapy dose planning with a 90 cm bore and a maximum reconstruction
14
diameter (DFOV) of 85 cm, to be able to image the whole outer contour of the patients, including
immobilization equipment for arms and legs. It also features a 16-bit scale of CT numbers
[-32768 HU, 32767 HU] as standard. This enables quantification of the attenuation by prosthesis
materials from their CT numbers, however, it does not have any option of MAR technique such as
Toshiba’s SEMAR.
The second scanner was a FKS DECT system at the radiology department at the same hospital,
[Discovery CT750 HD, (General Electric Healthcare, Milwaukee, USA)] (Figure 3, right), hereon
referred to as the “GE scanner”. It has a 70 cm bore and a maximum DFOV of 50 cm, an ad hoc flat
table top was made by placing a plywood board on the patient table. This scanner features an
option between the 12-bit and 16-bit scale of CT numbers, with switching between the two by
simply checking a box and restarting the system.
The MARS metal artefact reduction can be selected for the GSI Dual Energy scan modes. VME
images with VME levels between 60 keV and 140 keV, together with MD images can be
reconstructed at the operator console. Effective Z images are obtained from the GSI Viewer, which
is the software that provides visualization and post-processing of GSI images.
Figure 3, (Left) The Aquilion LB scanner (Toshiba) CT scanner at the oncology department at the Sahlgrenska
University hospital, fitted with a flat table top. (Right) the Discovery CT750 HD (GE) scanner with a plywood board
simulating the flat table top CT systems used for radiotherapy treatment planning.
Simulating hip prostheses
The impact on image quality and CT numbers caused by metal prostheses for the two CT scanners
were studied with an electron density phantom with two pairs of metal inserts made of titanium
and stainless steel.
The phantom [062M electron density phantom (Computerized Imaging Reference Systems (CIRS)
Norfolk, Virginia USA)] consisted of two 50 mm thick nested discs made of Plastic Water-LR®, with
17 holes in which 30 mm diameter inserts of different materials can be placed (Figure 4). The
inserts are composed to simulate different tissues in the body, with physical and electron densities
according the specifications provided by CIRS (Table 1).
15
Figure 4. The 062M electron density phantom (CIRS) with the configuration
of electron density inserts as described in Table 3.
The electron density inserts in the phantom were arranged as presented in (Figure 4) with an
addition of a 25 mm diameter test tube protector filled with tap water placed in the upper left in
the phantom. This insert position was filled with a Plastic Water-LR insert in the Toshiba scanner
scans, as this test tube protector was not available at the time of the scan.
Table 1. Properties of the different materials in the 062M electron density phantom (CIRS).
Description
Physical density
Electron density
Electron density
[g/cm3]
[1023
relative to water
electrons/cm3]
Adipose
0.96
3.171
0.949
Body (Outer ring)
1.029
3.333
0.998
Breast (50% Gland, 50% Adipose)
0.99
3.261
0.976
Head Insert (Inner ring)
Liver
Lung (Exhale)
Lung (Inhale)
Muscle
Solid Dense Bone (1250 mg/cm3 HA)
Solid Dense Bone (800 mg/cm3 HA)
Solid Trabecular Bone (200mg/cm3
HA)
1.029
1.07
0.50
0.20
1.06
1.82
1.53
1.16
3.333
3.730
1.632
0.634
3.483
5.663
4.862
3.730
0.998
1.052
0.489
0.190
1.043
1.695
1.456
1.117
The metal hip prostheses were simulated with two additional pairs of inserts, designed to imitate
total hip prostheses, made of metal and plastic (Figure 5). The metals used were titanium and
stainless steel, and the plastic was polyoxymethylene (POM). The inserts were 50 mm long with
an external diameter 30 mm, in order to fit in the holes in the phantom. The outer metal casing
had an 18 mm internal diameter, the diameter of the central metal core was 10 mm, the space
between the outer casing and inner core was filled with POM.
16
Figure 5. A pair of metal/POM inserts made to simulate hip prostheses, two pairs was made of
stainless steel and titanium respectively. The units of the ruler in the picture are in centimetres.
The phantom was scanned three times with the Toshiba scanner, without metal, with bilateral
titanium and steel inserts, respectively, using the 120 kVp “RTP-3.0 Portafas” scan protocol
(Table 2). The images were then reconstructed with the FC17 convolution kernel, a DFOV of
400 mm, and a slice thickness of 3 mm.
Table 2. Scan parameters used when scanning the electron density phantom with the Aquilion LB.
CTDIvol
Average tube
DFOV
Beam collimation
Scan slice thickness
[mGy]
current [mA]
[mm]
[mm]
[mm]
8.8
419
400
16
1
The scans with the GE scanner were performed with the GSI-7 dual energy scan mode. To reduce
the noise by reducing the amount of scattered photons reaching the detector the 20 mm detector
collimation was used. A helical pitch of 0.969 and slice thickness of 2.5 mm was selected. In order
to have similar noise characteristics as the Toshiba scanner, the noise reducing adaptive statistical
iterative reconstruction (ASIR) option available for the GSI scan modes was not used. The average
tube current was 600 mA with a weighted CTDI of 34.87 mGy. As with the Toshiba scanner, three
scans of the phantom were performed; with plastic water, titanium or steel inserts.
VME images were reconstructed with VME levels between 60 keV and 140 keV in increments of
10 keV plus an additional set at 107 keV. This was done due to findings by Lee et al. 2012 where
water ROIs around metal in a water phantom showed least variability of the mean CT number at
this energy [27]. The images from the scans with metal inserts were reconstructed with and
without MARS for each VME level, amounting to a total of 50 reconstructed image stacks.
The images were then evaluated with the in-house developed image quantification platform
RONSO (Tobias Magnander, the Sahlgrenska university hospital). Cylindrical volumes of interest
(VOI) where placed concentrically within the electron density inserts, and at six other positions
in the PlasticWater-LR® of the phantom, to evaluate the CT number variation within the phantom
17
(Figure 6). The VOIs were 18 mm in diameter and 22.5 mm long. Each VOI was copied from an
original VOI in order to achieve identical VOIs.
Figure 6. Positions of the cylindrical volumes of interest in the electron density
inserts (a-h, A-Z) and the PlasticWater-LR (inner and outer) ports of the 062M
phantom (1-6).
The distribution of the electron density inserts in the phantom is listed below (Table 4).
Table 3. Positions of the different electron density materials in the phantom.
Electron density material.
Positions
Adipose
b and d
Breast (50% Gland, 50% Adipose)
e and Z
Liver
g and h
Lung (Exhale)
B and F
Lung (Inhale)
A and E
Muscle
c and f
Plastic Water-LR
1 – 6 and H*
Solid Trabecular Bone
a and D
Tap water
H*
*A Plastic water insert was placed at position H in the Toshiba scans,
while tap water was used in the scan with the GE scanner.
The mean CT number and corresponding standard deviation in the VOIs were extracted from
RONSO and saved in Excel™ spreadsheets.
CT number variation
The mean and standard deviation of CT numbers without any metal inserts present were studied
for the electron density inserts representing soft tissues. The mean VME CT numbers in tap water
were used to estimate how the reconstruction parameters affected the CT number error.
CT number to Relative Electron Density
Calibration curves for CT numbers to electron density were produced for the Toshiba scanner and
the VME images from the GE scanner. The dependence on the VME level in the reconstructed
image was investigated.
18
Severity of the streaks
To estimate the severity of the streaks between the metal inserts, the mean and standard deviation
of the CT numbers in the central electron density insert were compared with the corresponding
non-metal values.
CT number profiles over inserts
Vertical lines were drawn over of the right metal insert of the phantom to visualize the CT
numbers and size of the metal and plastic cylinders in metal inserts in the CT images (Figure 7).
The lines were drawn using the image processing software [ImageJ (National Institute of Health)].
The CT number profiles along the line was extracted to a spreadsheet.
Figure 7. A profile (yellow) laid through the left (in the image) metal insert in the 062M phantom.
The profiles were drawn over the titanium and steel inserts in images from the Toshiba scanner.
The same was done in VME images from the GE scanner at VME levels from 60 keV to 140 keV,
with or without MARS, and 12 or 16-bit Hounsfield unit scale.
MARS and DFOV
A water phantom was devised to verify if the DFOV will change the appearance of metal in images
with MARS, as suggested by Lee et al. 2012 [27]. The phantom was composed of two parallel 4.76
mm hexagonal insex drives [Protanium® (Bondhus, USA)], separated by two 6.35 mm hexagonal
drill bits (Figure 8 left). The insex drives were placed on top of an inverted polypropylene box
[UniPak 3100 cm3 (Superfos, Denmark)] inside a 28x28x17 cm3 polypropylene box [Smartstore
(Orthex, Sweden)], filled with water at room temperature (Figure 8 right).
Figure 8. (Left) Two hexagonal insex drives inside the water phantom spaced by two screw bits. (Right) The water
phantom with the insex drives lying in the z-direction, perpendicular to the bore of the scanner.
19
The water phantom was scanned with the GSI-7 scan mode and VME images at 110 keV were
reconstructed as 2.5 mm slices, with and without MARS. The DFOV was decreased in increments
of 10 cm from 50 to 10 cm (Figure 9). The images were then magnified using ImageJ, in order to
visualize the same area in all images. The 110 keV VME level was chosen due to that these images
contained the least amount of streak artefacts between titanium inserts (Figure 14).
Figure 9. Five images of the same section of the water phantom with insex drives, with DFOV decreasing from 50 cm to 10
cm in increments of 10 cm. Note that each of the five images have the same 512 by 512 pixel matrix image size, such that
the number of pixels per length in the actual phantom increases with decreasing DFOV.
Effective Z
To quantify metals in the GE scanners effective Z images, five cylindrical pellets with identical
geometries (10 mm diameter and 5 mm high), plus two pieces with irregular geometry were
placed on a row in the z-direction of the scanner (Figure 10, left) in the same water phantom as
used for the study of DFOV and MARS (Figure 10, right). The pellets consisted of in turn;
aluminium, titanium, stainless steel, copper and brass. The two additional pieces were made of an
unknown low density metal and lead, respectively. The water phantom was scanned with the
GSI-7 scan mode and reconstructed with a DFOV of 10 cm, slice thickness of 1.25 mm, with and
without MARS.
Figure 10. (Left), the metal pieces used in the effective Z phantom, materials from left to right are; lead, brass, copper, steel,
titanium, aluminium, and an unknown piece of metal. Note that the middle five pieces have identical geometry, whereas the
lead and unknown pieces have irregular geometries. (Right), the metal pieces on a row inside the water phantom, viewed
through the bore of the GE scanner.
The images were then evaluated in the GSI viewer’s effective Z mode, where rectangular ROIs
were placed in centre of the metal pieces in the image slice corresponding to the centre of the
metal pellet (Figure 11).
20
Figure 11. An ROI placed in the centre of an aluminium pellet.
The mean and standard deviations of the effective Z from the ROIs were subsequently noted in an
Excel spreadsheet, and also visualized in a histogram in the GSI Viewer on the CT console. The
measured effective Z of the pellets were then compared to the true effective Z of the metals.
Results
Simulating hip prostheses
Image appearance
The images acquired with the Toshiba scanner show how the streaking artefacts vary with
prosthesis material (Figure 12). The image with plastic water inserts (Figure 12a), is an artefact
free image. With titanium inserts at the lateral positions in the phantom streak artefacts are
present between the inserts and elsewhere in the phantom (Figure 12b). With steel inserts
(Figure 12c), the streaking is increased such that the central electron density insert was not
visible.
Figure 12. a) CT images of the 062M phantom with lateral inserts of plastic water, b) lateral inserts made of titanium and
c) steel. The images are displayed with window level/width at 40/400.
The VME images with titanium inserts without MARS contains the highest amount of streaking at
60 keV (Figure 13). These metal artefacts decrease in magnitude as the VME level approaches
110 keV. Above the 110 keV VME level, additional bright streaks appear over the central electron
density inserts.
21
Figure 13. VME images of the 062M phantom with titanium inserts from the GE scanner, reconstructed without MARS,
with energies ranging from 60 keV to 140 keV in increments of 10 keV, displayed at a window level/width of 40/400 HU
In images reconstructed with MARS the dark streaks between the titanium inserts are removed,
such that the central electron density inserts were visible for all VME levels. However, additional
streaking appear between titanium inserts and the low electron density inserts corresponding to
lung tissue. While these streaks are discernible in the non-MARS images, they are more visible in
the images reconstructed with MARS (Figure 14).
22
Figure 14. VME images of the 062M phantom with titanium inserts from the GE scanner, reconstructed with MARS,
with energies ranging from 60 keV to 140 keV in increments of 10 keV. Displayed at a window level/width of 40/400 HU
The non-MARS images of the phantom with steel inserts contains streaks that obscures the central
electron density inserts for all VME levels (Figure 15), similar to the images acquired from the
Toshiba scanner (Figure 12b). This is also the case for the streaks between metal and lung tissue
inserts. These images do not show the energy dependence seen in images with titanium inserts
(Figure 13).
23
Figure 15. VME images of the 062M phantom with steel inserts from the GE scanner, reconstructed without MARS, with
energies ranging from 60 keV to 140 keV in increments of 10 keV. Displayed at window level/width 40/400 HU.
Images containing steel reconstructed with MARS have improved visibility of the central density
inserts, which were obscured in the non-MARS image and the images from the Toshiba scanner.
The increase of streaking between metal and lung tissue inserts seen with MARS for titanium
inserts, were also present in the images with steel inserts (Figure 16).
Figure 16. VME images of the 062M phantom with steel inserts from the GE scanner, reconstructed with MARS, with
energies ranging from 60 keV to 140 keV in increments of 10 keV. Displayed at window level/width 40/400 HU.
24
CT number variation
The CT numbers obtained with the Toshiba scanner for non-metal, titanium and steel inserts at
the lateral positions in the phantom are presented in Table 4. The largest difference compared to
non-metal images is seen at position Z and 2 which are near the centre of the phantom. Similarly
to the mean CT numbers, the standard deviation in the VOIs vary between the metal inserts, with
the largest variation at position Z and 2. The data from images from the GE scanner is presented
in the appendix.
Table 4. Mean CT numbers in the VOIs in the images acquired with the Toshiba scanner with non-metal, titanium and steel inserts at the
lateral positions, the data for positions in the line between the inserts (Z, g, c and 2) are bolded, to mark their variation with the insert
material.
Mean CT numbers [HU]
Standard deviation [HU]
Non-metal
Titanium
Steel
Non-metal Titanium
Steel
Adipose @b
Adipose @d
-55
-56
-68
-57
-63
-69
Adipose @b
Adipose @d
11
11
13
17
22
29
Breast @Z
-22
-133
-569
Breast @Z
11
61
273
Breast @e
-22
-31
-58
Breast @e
11
15
25
Liver @g
60
-30
-395
Liver @g
12
30
79
61
-511
-508
-812
-812
48
-495
-499
-793
-788
48
-468
-481
-776
-754
Liver @h
Lung exhale @B
Lung exhale @F
Lung inhale @A
Lung inhale @E
11
10
9
10
11
15
12
11
11
11
23
19
26
19
18
Muscle @c
50
-42
-398
Muscle @c
11
29
94
Muscle @f
Plastic Water @3
51
-4
36
2
5
46
Muscle @f
Plastic Water @3
11
11
17
17
33
46
Plastic Water @2
-2
-109
-512
Plastic Water @2
12
43
195
Plastic Water @5
Plastic Water @4
Plastic Water @1
Plastic Water @6
Trab. bone @a
Trab. bone @D
Water @H
11
0
13
20
271
275
3
3
4
18
21
253
254
4
-17
6
28
24
242
234
9
Plastic Water @5
Plastic Water @4
Plastic Water @1
Plastic Water @6
Trab. bone @a
Trab. bone @D
Water @H
10
10
9
9
12
11
9
11
22
11
11
13
15
11
19
47
18
16
21
35
18
Liver @h
Lung exhale @B
Lung exhale @F
Lung inhale @A
Lung inhale @E
The mean CT numbers in the VOIs in non-metal images from the GE scanner were most separated
at 60 keV, and converging with increasing VME level. The standard deviation decreases with
increasing VME level (Figure 17).
Adipose @b
80
Breast @Z
Water @H
Liver @h
60
CT number [HU]
40
20
0
-20
55
65
75
85
95
105
115
125
135
145
-40
-60
-80
VME level [keV]
Figure 17. Mean CT numbers for four VOIs in the phantom for VME images without metal inserts. The error bars are plus
minus one standard deviation of the CT numbers in the VOI (GE scanner).
The mean CT numbers in the tap water VOI at position H varied slightly with VME level, especially
for the non-MARS titanium image at lowest VME level (Figure 18). The mean CT number in the
MARS reconstructed images are below the reference level of 0 for all VME levels.
25
No Metal
3
Steel
Steel MARS
Titanium
Titanium MARS
CT number [HU]
0
60
70
80
90
100
110
120
130
140
-3
-6
-9
-12
-15
VME level [keV]
Figure 18. Mean CT number in tap water VOI without metal inserts, with steel and titanium inserts with/without MARS
(GE scanner).
CT number to RED
The electron density to CT number curve for the Toshiba and GE scanners roughly follows a
straight line for relative electron densities between 0 and 1 (Figure 19). The curves for the
different VME levels diverges at a RED of 0.95, and also for electron RED above 1.1 (Figure 20).
The Toshiba curve follows the 70 keV curve for the highest RED in the phantom.
400
Toshiba
200
60 keV
70 keV
CT number [HU]
0
-200
0
0.2
0.4
0.6
0.8
1
1.2
80 keV
90 keV
-400
100 keV
-600
110 keV
-800
120 keV
130 keV
-1000
Electron density relative to water (RED)
140keV
Figure 19. Toshiba and GE VME CT numbers as function of the electron density relative to water.
Figure 20 is a magnified version of Figure 19, here the variation near a RED of 1 is visualized. The
slope of the curves below of RED of 1 increase with the VME level. The slope decreases with
increasing VME level at RED values above 1.
26
350
300
Toshiba
60 keV
CT number [HU]
250
70 keV
200
80 keV
150
90 keV
100
100 keV
110 keV
50
120 keV
0
130 keV
0.93
0.98
1.03
1.08
1.13
-50
-100
140keV
Electron density relative to water
Figure 20. Mean CT numbers in VOIs placed in various electron density inserts in the 062M phantom, in images acquired
with the Toshiba and GE scanner.
Severity of the streaks
The mean CT number of the breast equivalent insert at the centre of the phantom (position Z),
show the amount of error in the dark streaks caused by the metal inserts in the VME images
(Figure 21). The mean CT number in non-MARS titanium images increases with the VME level and
intercepts the corresponding values from non-metal and MARS reconstructed images near
110 keV. The mean CT number in the steel image was 350 HU below the corresponding non-metal
value. The corresponding mean values for the Toshiba scanner was -133 HU, -569 HU and -22 for
titanium, steel and the non-metal images, respectively.
Steel
Steel MARS
Ti
Ti MARS
No Metal
Mean CT number [HU]
100
0
-100
60
70
80
90
100
110
120
130
140
-200
-300
-400
-500
VME level [keV]
Figure 21. Mean CT number in Breast centre VOI at different energies for the VME images in GSI-7 scan mode (GE
scanner).
The standard deviations in CT numbers in the breast insert at position Z is nearly constant with
varying VME level for the non-metal and MARS reconstructed images (Figure 22). The non-MARS
standard deviations for titanium decrease with VME level with a minimum near 110 keV. With
steel inserts present, the standard deviation increases slightly with the VME level. For the Toshiba
scanner the standard deviations were 61 HU for titanium, 273 HU for steel, compared to 11 HU in
the non-metal images.
27
Steel
Steel MARS
Ti
Ti MARS
No Metal
Standard deviation [HU]
250
200
150
100
50
0
60
70
80
90
100
VME level [keV]
110
120
130
140
Figure 22. Standard deviations of voxel values inside the breast centre VOI in VME images (GE scanner).
CT number profiles over inserts
The titanium CT numbers at the centre of the insert are nearly independent of VME level, while
decreasing with increased VME levels at the lateral parts of the profile. For steel inserts, both the
central and lateral CT numbers increase with the VME level. The difference in CT numbers
between titanium and steel is largest at VME levels above 100 keV, and decreases with the VME
level. At the lowest 60 keV VME level, titanium and steel CT numbers in the centre of the insert
are nearly identical at 5 500 HU. The diameter of the insert with regards to the FWHM of the
profiles are near the true value of 30 mm.
28
Figure 23. Non-MARS 16-bit CT number profiles over the titanium (left) and steel (right)
inserts from the Toshiba scanner and VME images at different VME levels from the GE scanner.
The appearance of a titanium insert from the Toshiba scanner and 110 keV VME images from the
GE scanner (Figure 24), varies whether the reconstruction was made with 12 or 16 bit-depth and
whether MARS was used or not.
The 12-bit CT number profile for titanium are cut at 3 071 HU. This is not the case with the 16-bit
profile which does not suffer from this cut-off. The 16-bit profile does not reach the theoretical
110 keV CT number of titanium of 5 429 HU.
With MARS, the 110 keV metal CT numbers are cut at 1 670 HU for both titanium and steel inserts.
29
13500
Toshiba 16-bit
CT number [HU]
11500
GE 16-bit
9500
GE 12-bit
7500
GE 16-bit MARS
GE 12-bit MARS
5500
3500
1500
-500
-30
-15
0
15
30
Position [mm]
Figure 24. Line profiles through the titanium inserts. All profiles are from four different reconstructions of 110 keV VME images from the
GE scanner except for the Toshiba 16-bit profile. The vertical gridlines show the actual 30 mm external diameter of the metal insert.
For the steel insert, the difference between the 12-bit and 16-bit 110 keV images is larger than for
the titanium insert (Figure 25). The CT numbers in MARS-reconstructed images with both the
12-bit and 16-bit images are cut at identical CT numbers. The steel CT numbers are significantly
lower than the theoretical 110 keV steel CT numbers at 14 525 HU.
13500
Toshiba 16-bit
CT number [HU]
11500
GE 16-bit
9500
GE 12-bit
7500
GE 16-bit MARS
5500
GE 12-bit MARS
3500
1500
-500
-30
-15
0
15
30
Position [mm]
Figure 25. Line profiles of CT numbers through the steel inserts. All profiles are from different reconstructions of
110 keV VME images from the GE scanner except for the Toshiba profile. .
The CT number cut-off level of MARS was investigated by measuring the profiles over the inserts
at various VME levels (Figure 26). The cut-off is decreasing with increased VME level. The FWHM
of the metal insert decreases with increasing VME level.
30
4000
3500
60 keV
70 keV
3000
80 keV
CT number [HU]
2500
90 keV
100 keV
2000
107 keV
110 keV
1500
120 keV
130 keV
1000
140 keV
500
0
-30
-15
0
-500
Position [mm]
15
30
Figure 26. CT number profiles across a titanium insert in images reconstructed with MARS at various VME levels (GE scanner).
The level at which MARS cuts the CT numbers were investigated by plotting central CT numbers
of the profiles for each VME level in 16-bit images with MARS for both steel and titanium inserts
(Figure 27). The cut-off level was identical for titanium and steel at every VME level.
Cut-off CT number [HU]
5000
Steel
4000
Titanium
3000
2000
1000
0
50
60
70
80
90
100 110
VME level [keV]
120
130
140
150
Figure 27. Cut-off CT number in images reconstructed with MARS, the cut-off level is identical for steel and titanium (GE scanner).
MARS and DFOV
The images of two parallel insex drives as reconstructed with five different DFOV with and
without MARS are presented in Figure 28. The top row shows the non-MARS images with DFOV
decreasing from 50 cm to 10 cm. The pixel size is reduced with the DFOV, which is seen in the top
row where the image turns from pixelated at a DFOV of 50 cm to non-pixelated at a DFOV of 10
cm. In the MARS-reconstructed images the insex drives appear pixelated at the largest DFOV of 50
cm. When the DFOV decreases they appear less pixelated as the pixel size decreases with the
DFOV. However, at the 10 cm DFOV the appearance of the insex drives are pixelated even though
the pixel size is smallest at this DFOV.
31
Figure 28. Image of the same scan of two insex drives reconstructed with different five different DFOV
without MARS (top row) and without MARS (bottom row), the numbers are DFOV in centimetres (GE scanner).
Effective Z
The streak artefacts from the metal pieces in the water phantom is illustrated by a 140 keV VME
image (Figure 29). This streaking is similar to the streaking seen in the effective Z images, where
the unknown piece of metal and the aluminium pellet are free from artefacts. The higher Z
materials are subject to streaking with the severity increasing with the Z of the metal.
Figure 29. Sagittal reformatted (and flipped 90 degrees clockwise)
image showing the water phantom with metal pieces with
increasing atomic numbers (Z) from left to right (GE scanner).
The data from the ROIs in four of the metal pieces are visualized in a histogram (Figure 30)
exported from non-MARS data on the GSI-viewer on the CT console. The cyan bars corresponding
to titanium have a mean Z well below the nominal 22 of titanium. For steel, the error in mean Z is
larger. The measured steel mean Z of 13 is less than half of the nominal 26.4.
32
Figure 30. Histogram showing the distributions of effective atomic numbers in metal pellets of steel (blue), titanium
(cyan), aluminium (pink) and a piece of unknown light metal (red).
The data from the ROIs show that the effective Z images underestimate the Z of metals with atomic
numbers higher than 13 (Table 5). The highest mean Z in non-MARS effective Z images is
measured in the titanium ROI. The error in measured Z increases with rising Z reaching a
maximum error for lead. With MARS, the streaking is removed from the effective Z images.
However, the mean Z reaches a maximum at a Z of 16.95 for metals denser than aluminium. The
standard deviation in these ROIs are reduced to values near zero.
Table 5. Mean and standard deviations of effective atomic numbers (Z) in ROIs in pieces of the different metals in effective
Z images reconstructed with and without MARS.
Without MARS
With MARS
Material (Z)
Mean [Z]
Standard deviation [Z]
Mean[Z]
Standard deviation [Z]
Unknown metal (?)
12.15
0.43
11.93
0.67
Aluminium*
(13)
13.16
0.24
13.17
0.21
Titanium*
(22)
18.57
0.43
16.95
0.02
Stainless steel* (26.4)
12.96
1.21
16.95
0.02
Copper*
Brass*
Lead
(29)
10.05
1.97
16.96
0.01
(29.5)
6.41
3.49
16.96
0.01
(82)
1.00
0.00
16.81
0.57
*Metal pellets of identical geometry.
Discussion
Simulating hip prostheses
Image appearance
The images from the Toshiba scanner appear streaky with titanium inserts (Figure 13b) and show
severe streaking with steel inserts (Figure 13c) compared to the non-metal image. The increased
streaking for steel is assumed to be caused by a higher linear attenuation coefficient for stainless
steel (6.7 [cm-1]) compared to titanium (2.4 [cm-1]) at 70 keV, which is expected to be near the
effective energy of the 120 kVp spectrum of the Toshiba scanner. When these streaks are present
in clinical images, delineation from the image is impossible and these streaks will have to be
manually converted to an electron density of water in the dose planning software for the dose
calculation.
VME images from the GE scanner with VME levels below 90 keV contain more streaking with
titanium inserts than the images from the Toshiba scanner (Figure 14). While the most prominent
33
streaking is between the metal, dark streaks partially hide the electron density insert at
“position e” in the 60 keV image. Light streaks appear between the inserts at VME levels above
110 keV, increasing with the VME level. The best image quality for the titanium inserts appears to
be at 110 keV. These images are better for delineation and obtaining the electron density between
titanium prostheses since they contain less streaks compared to the images from the Toshiba
scanner.
With MARS, the dark and light streaks between the titanium inserts are removed at all VME levels.
However, additional streaking across the image is introduced, which reduces the image quality
(Figure 15). The streaks between the metal and the low electron density (lung) inserts, present
only at lower VME levels without MARS, are present at all energies with MARS. These broad
streaks might reduce the low contrast visibility for delineation between titanium prostheses and
bowels containing gas.
With steel inserts, the images from the Toshiba scanner contain large dark streaks obscuring the
central electron density inserts (Figure 13c). The same is true for the non-MARS VME images from
the GE scanner (Figure 16). The image appearance of the VME images does not vary as much with
VME level as with titanium inserts. The dark streaks between inserts, as well as the streaks
between metal and low electron density inserts, are present at all VME levels. These images do
not improve the delineation or dose calculation.
When MARS is applied in the reconstruction of the steel images, the visibility of electron density
inserts between the steel inserts is improved for all VME levels (Figure 17). Thus, MARS is
essential for delineation of structures in the area between steel prostheses. As the steel images do
not vary as much as the titanium images with VME level, an optimal VME level for the steel inserts
cannot be found from these images, due to lack of small structures in the phantom. To further
evaluate the image quality for the different VME levels for the MARS-corrected images with steel
inserts, a small low contrast visibility object should be placed in the centre of the phantom.
When encountering a patient with unknown prosthesis material, two reconstructions should
suffice for delineation and to obtain the electron density between the prostheses. A 110 keV
non-MARS reconstruction would work if the prosthesis material is titanium. If the images from
this reconstruction appears too streaky, a second set of 110 keV images reconstructed with MARS,
should enable delineation between steel prostheses.
CT number variation
The CT number difference, i.e. contrast between different phantom inserts, decreases with
increasing VME level. The same decrease is seen for the noise, estimated by the standard deviation
in the VOI.
The mean CT number in a VOI of water decreased when MARS is applied, this decrease was not
affected by the VME energy. However, the difference is believed to be too small to cause a
significant error in the dose calculation.
CT number to RED
At RED larger than 1, the Toshiba curve was most similar to the curve corresponding to the VME
level of 70 keV (figure 20). This suggests that the effective energy of the Toshiba scanners X-ray
spectrum is between 67 and 70 keV. This finding agrees with the effective energy of 68.7 keV,
subsequently provided by Toshiba. [20]
The CT numbers for air and water are defined and calibrated at -1000 and 0 HU, respectively, and
were thus similar for all VME levels. The observed divergence in the calibration curves is believed
to be due to the variability of CT numbers with the VME level. The CT numbers vary more for the
34
lower VME levels and at higher electron densities due to the higher effective Z in the bone insert.
If the VME images were to be used in clinical practice, each VME level should have its own
calibration curve.
The curve for the VME level of 140 keV follows a straight line since the Compton scattering is
dominant at this photon energy, which is proportional to the electron density for low Z materials.
The 140 keV curve is expected to diverge at higher electron densities corresponding to dense
bone, as the higher effective Z in these inserts should increase the relative contribution of the
photoelectric effect. The 140 keV VME images were the least dependent of the effective Z in the
electron density phantom inserts, since the CT numbers were most linear to the RED.
Severity of the streaks
The CT numbers from the Toshiba scanner between the titanium inserts had a mean of -133 HU
compared to the non-metal mean of -22 HU.
The mean in the non-metal VME images increases from -38 HU at 60 keV, to 0 HU at 140 keV, with
a standard deviation near 10 HU for all VME levels (figure 21).
The mean CT number between titanium inserts in non-MARS VME images was -450 HU at 60 keV,
increasing to 60 HU at 140 keV. This mean intersected the non-metal mean near 110 keV. The
corresponding standard deviation had a minimum near 110 keV. This is consistent with the least
streaking observed in the 110 keV images (figure 13).
The error in CT numbers between steel prostheses in non-MARS VME images was smaller than
for the Toshiba scanner. The errors were increasing from -400 HU to -350 HU from 60 keV to 140
keV, while the mean from the Toshiba scanner was -569 HU. However, as these dark streaks would
be corrected to a RED of 1 in the treatment planning system, the difference would not matter in
clinical practice.
CT number profiles over inserts
The profiles from the Toshiba scanner vary across the titanium insert, showing signs of cupping
with lower CT numbers at the centre of the insert. The maximum CT numbers slightly over 7 000
HU which is lower than the theoretical CT numbers of 11 545 HU at 70 keV. The both the cupping
and low CT numbers can be attributed to beam hardening of the X-ray spectrum traversing the
titanium. The POM content of the insert cannot be quantified from the profile, as the spatial
resolution in this highly attenuating region is expected to be low. The FWHM of the inserts is near
the nominal external diameter 30 mm.
For steel inserts the Toshiba scanner profile show increased cupping compared to the titanium
profiles. The cupping is expected to increase as the effective Z of steel is higher than for titanium.
The peak CT numbers are at 13 500 HU, these are significantly lower than the theoretical CT
numbers at 34 264 HU at 70 keV, which is usually estimated as the effective energy of a 120 kVp
spectrum. This beam hardening effect for polychromatic CT scanners has also been noted by [31],
and has been shown by to be geometry dependant [13].
The non-MARS 16-bit VME CT number profiles for titanium did not vary much with the VME level
at the centre of the inserts. A 2 000 HU difference in CT number with VME level between 60 and
140 keV was seen at the lateral parts of the profile, this is a smaller difference than expected if the
VME images were perfect. The steel inserts had an opposite relation to the VME level, with the
highest CT numbers measured for the highest VME levels. This is counterintuitive, and a question
to look further into. The lower VME levels below 110 keV should be avoided trying to differentiate
between titanium and steel prostheses from VME images, since the difference in measured CT
numbers increased with the VME level. The central CT number difference between titanium and
35
steel at 110 keV VME images were 3 000 HU. The central CT number difference for the Toshiba
scanner was 3 350 HU, with larger differences at the lateral parts of the profile.
The non-MARS 12-bit 110 keV CT number profiles from the GE scanner contain maximum CT
numbers of 3 071 HU for both for titanium and steel inserts, and resulting in FWHM of the insert
larger than 30 mm. These images are not suitable for the quantification of the metal, due to the
cut-off of the CT numbers at 3 071 HU.
The non-MARS 16-bit 110 keV profiles are similar to the 12-bit profiles except that the flat tops at
3 071 HU for the 12-bit images were replaced with Gaussian peaks at the metal containing regions.
The maximum CT numbers in the profiles are 5 282 HU for titanium and 8 600 HU for steel. While
it seems like titanium can be distinguished from steel given the CT numbers, the measured CT
numbers for steel is lower than the theoretical CT number of 14 525 HU at 110 keV. The CT
number error is smaller for titanium, which theoretical 110 keV CT number is 5 429 HU which is
near the measured 5 382 HU. The external diameter of the inserts from these profiles are 30 mm.
The images from the GE scanner lack the cupping seen in the images from the Toshiba scanner
and this might be attributed to the reduction of beam hardening inherent to the projection based
material decomposition used to form the VME images [25].
The profiles in 110 keV VME images reconstructed with MARS depicted the internal POM
structure of the titanium inserts, the CT numbers of the POM in the titanium insert were
underestimated. For steel inserts, no internal structure could be visualized with MARS.
The CT numbers for both titanium and steel were reduced with MARS. A cut-off appeared at the
same HU level for both metals, this cut-off level did depend on the VME level. This does not seem
to have any clinical implications for titanium prosthesis as these could be imaged without MARS.
However, MARS was essential to image the region between the steel prostheses. In the case one
wanted to irradiate through a steel prosthesis, the information about the metal must be obtained
from the non-MARS image while the delineation should be made in the MARS image.
The reduction of metal CT numbers do not seem to occur when using the other MAR techniques
such as Philips’ O-MAR [31] and Siemens’ iMAR [32].
When comparing the external diameter of the insert for the different reconstructions, using the
FWHM of the lateral peaks in the profiles as a measure of the diameter, the Toshiba scanner
measures similar external diameter as the 16-bit non-MARS images with the GE scanner. The
images reconstructed with MARS seem to underestimate the diameter of the titanium inserts, this
is in line with the findings of [27] and [30].
The measured profiles were placed in the anterior-posterior direction in the phantom in order to
avoid the streak artefacts near the metal inserts. This might have resulted in less contrast between
metal and plastic inside the inserts compared to if the profiles were placed in the lateral direction.
MARS and DFOV
The images reconstructed without MARS at five different DFOV ranging from 50 to 10 cm appears
to be similar when magnified and viewed next to each other, with the hexagonal structure of the
insex drives being discernible (Figure 27). When MARS is applied, the insex drives appear to be
depicted by fewer pixels as the DFOV is decreased. Even if the MARS images with the small DFOV
have smaller pixels, the metal in the image seems to consist of much larger pixels. This is
counterintuitive as the number of pixels per length scale in the phantom is inversely proportional
to the DFOV for a fixed matrix size.
36
MARS seems to change the prosthetic shapes and size when the DFOV is reduced. This
phenomenon was studied by of [27], who advise about using MARS on images with DFOVs smaller
than 20 cm, since it could lead to wrong-diagnosis when viewing objects in the peri-prosthetic
region i.e. near metal objects. This might not be relevant for the dose calculation, as the photons
beam radiotherapy in not perturbed by such small variations. However, the delineation of
structures near the prostheses might be affected if a DFOV smaller than 20 cm was to be used.
Effective Z
Out of the five pellets with identical geometry, the effective Z images of the metal pellets were only
able to give a correct mean atomic number for aluminium. The atomic numbers in the other pellets
were underestimated images and did suffer from streak artefacts. The streaks resulted in the
spread in the histogram (Figure 29). The ROI in the piece of unknown metal were near Z of 12,
which would imply that it consisted of magnesium. Or more probable, that it was a piece of
aluminium that suffered from partial volume artefacts from the surrounding water and plastic in
the phantom. MARS reduced streaking artefacts, and resulted in a homogeneous Z of 16.96 for all
metals denser than titanium. Thus, the effective Z images did not suffer from streaking artefacts
but were not able to separate metals even in the relative simple phantom geometry used,
compared to the irregular geometry of a hip prosthesis. In this case the effective Z images do not
seem to be useful for identification of prosthesis materials. Additional comparisons with VME
images of the same phantom might better identify the metals from their CT numbers.
Conclusions
VME images from the GE scanner improve the image quality significantly compared to the Toshiba
scanner, with regards to delineation of structures and CT number error between bilateral metal
prostheses. The optimal image for scanning a patient with bilateral titanium hip prostheses in the
GE scanner is at a VME level of 110 keV, without MARS, with a 16-bit Hounsfield unit scale. In the
case of bilateral steel prosthesis, the preferred parameters is 110 keV, 16-bit Hounsfield unit scale,
with MARS to reduce the streaks between the prostheses.
A non-MARS image is necessary to obtain the steel CT numbers for the dose calculation if one
would like to irradiate through a prosthesis, as MARS reduces the CT numbers of metals. VME
levels lower than 100 keV should be avoided when differentiating between titanium and steel. If
a patient has bilateral hip prostheses of unknown metal, two sets of 110 keV VME images (with
and without MARS) should be used.
A DFOV smaller than 20 cm should not be used when delineating objects near metal objects in
images reconstructed with MARS. As the geometry of metal objects can be distorted by MARS at
small DFOV.
Effective Z images could not be used to identify metal pellets with atomic numbers above 13.
Topics of Further Research
Given the elemental composition of the 062M electron density phantom, theoretical CT numbers
of the phantom inserts can be calculated. Further studies should evaluate the accuracy of the VME
CT numbers if the elemental composition
To further evaluate MARS and other MAR algorithms for other metal geometries in phantoms, and
ultimately in patients with hip prostheses and dental fillings. The latter poses a challenge for the
delineation and treatment of head and neck cancer as they often consist of high Z materials such
as mercury and gold and have irregular geometries.
37
Further work should process the VME images in the treatment planning system for both photon
and proton radiotherapy. And evaluate the accuracy of proton stopping power images formed
from VME, MD and effective Z images, compared to standard polychromatic CT for proton dose
calculation.
Acknowledgements
I’m grateful to my supervisors for their support throughout this work. I want to thank Tobias
Magnander for his support regarding the RONSO software, and to all my fellow students for the
last five years spent together. And lastly, special thanks to Mia Linde for her endless patience with
me.
References
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
38
Bourque, A.E., J.F. Carrier, and H. Bouchard, A stoichiometric calibration method for dual
energy computed tomography. Phys Med Biol, 2014. 59(8): p. 2059-88.
Johns, H.E. and J.R. Cunningham, The physics of radiology. 1983: Charles C. Thomas.
Taylor, M.L., et al., The effective atomic number of dosimetric gels. Australasian Physics &
Engineering Sciences in Medicine, 2008. 31(2): p. 131-138.
Taylor, M.L., et al., Robust calculation of effective atomic numbers: the Auto-Z(eff) software.
Med Phys, 2012. 39(4): p. 1769-78.
Mayles, P., A. Nahum, and J.C. Rosenwald, Handbook of Radiotherapy Physics: Theory and
Practice. 2007: CRC Press.
Lee, M.J., et al., Overcoming artifacts from metallic orthopedic implants at high-field-strength
MR imaging and multi-detector CT. Radiographics, 2007. 27(3): p. 791-803.
Hounsfield, G.N., Computerized transverse axial scanning (tomography). 1. Description of
system. Br J Radiol, 1973. 46(552): p. 1016-22.
Rutherford, R.A., B.R. Pullan, and I. Isherwood, Measurement of effective atomic number and
electron density using an EMI scanner. Neuroradiology, 1976. 11(1): p. 15-21.
Kalender, W.A., et al., Evaluation of a prototype dual-energy computed tomographic
apparatus. I. Phantom studies. Med Phys, 1986. 13(3): p. 334-9.
Alvarez, R.E. and A. Macovski, Energy-selective reconstructions in X-ray computerized
tomography. Phys Med Biol, 1976. 21(5): p. 733-44.
Kalender, W.A., Computed Tomography: Fundamentals, System Technology, Image Quality,
Applications. 2011: Wiley.
Hsieh, J. and SPIE, Computed Tomography: Principles, Design, Artifacts, and Recent Advances.
2009: SPIE.
Axente, M., et al., Clinical evaluation of the iterative metal artifact reduction algorithm for CT
simulation in radiotherapy. Med Phys, 2015. 42(3): p. 1170-83.
Ruoqiao, Z., et al., Model-Based Iterative Reconstruction for Dual-Energy X-Ray CT Using a
Joint Quadratic Likelihood Model. Medical Imaging, IEEE Transactions on, 2014. 33(1): p. 117134.
Li, B., et al. Head and body CTDIw of dual-energy x-ray CT with fast-kVp switching. 2010.
Yao, Y., A.S. Wang, and N.J. Pelc, Efficacy of fixed filtration for rapid kVp-switching dual
energy x-ray systems. Medical Physics, 2014. 41(3): p. -.
Li, B., G. Yadava, and J. Hsieh, Quantification of head and body CTDIVOL of dual-energy x-ray
CTwith fast-kVp switching. Medical Physics, 2011. 38(5): p. 2595-2601.
O'Sullivan, J.A., Dual Energy CT Image Reconstruction Algorithms and Performance, in 51st
AAPM Annual Meeting. 2009: http://vimeo.com/88174731.
Yu, L., S. Leng, and C.H. McCollough, Dual-energy CT-based monochromatic imaging. AJR Am
J Roentgenol, 2012. 199(5 Suppl): p. S9-S15.
Grundén, H., Personal communication, Mean effective energy: Toshiba Aquilion LB. 2015,
Toshiba Medical Systems, Sweden.
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
39
Wu, X., et al. Monochromatic CT image representation via fast switching dual kVp. 2009.
Xu, D., et al. Dual energy CT via fast kVp switching spectrum estimation. 2009.
Zou, Y. and M.D. Silver. Analysis of fast kV-switching in dual energy CT using a prereconstruction decomposition technique. 2008.
Julia F. Barrett, N.K., Artifacts in CT: Recognition and Avoidance. RadioGraphics, 2004. 24(6):
p. 1679-1691.
Boas, F.E. and D. Fleischmann, CT artifacts: causes and reduction techniques. Imaging in
Medicine, 2012. 4(2): p. 229-240.
Mori, I., et al., Photon starvation artifacts of X-ray CT: their true cause and a solution. Radiol
Phys Technol, 2013. 6(1): p. 130-41.
Lee, Y.H., et al., Metal artefact reduction in gemstone spectral imaging dual-energy CT with
and without metal artefact reduction software. Eur Radiol, 2012. 22(6): p. 1331-40.
Brook, O.R., et al., Spectral CT with metal artifacts reduction software for improvement of
tumor visibility in the vicinity of gold fiducial markers. Radiology, 2012. 263(3): p. 696-705.
Wang, F., et al., Reduction of metal artifacts from alloy hip prostheses in computer
tomography. J Comput Assist Tomogr, 2014. 38(6): p. 828-33.
Baojun, L., Dual-Energy CT with Fast-kVp Switching and Its Applications in Orthopedics.
OMICS Journal of Radiology, 2013. 2(6): p. -.
Glide-Hurst, C., et al., Changes realized from extended bit-depth and metal artifact reduction
in CT. Med Phys, 2013. 40(6): p. 061711.
Huang, J.Y., et al., An evaluation of three commercially available metal artifact reduction
methods for CT imaging. Phys Med Biol, 2015. 60(3): p. 1047-67.
Appendix
The tables presented below contain the mean CT numbers and standard deviations in VOIs in VME images of the CIRS 062M phantom. The VME images
were obtained from scans performed with the GSI-7 scan mode without metal inserts; with titanium or steel inserts; with and without MARS. The data
is presented for VME levels between 60 and 140 keV with the VOI positions presented in figure 6.
GSI-7,Witout metal.
VME level [keV]
Mean CT number [HU]
Adipose @b
Adipose @d
Breast @Z
Breast @e
Liver @g
Liver @h
Lung exhale @B
Lung exhale @F
Lung inhale @A
Lung inhale @E
Muscle @c
Muscle @f
Plastic Water @3
Plastic Water @2
Plastic Water @5
Plastic Water @4
Plastic Water @1
Plastic Water @6
Trab. bone @a
Trab. bone @D
Water @H
40
60
70
80
90
100
107
110
120
130
140
-65
-71
-37
-32
60
63
-510
-507
-810
-809
51
49
-7,1
-4,1
2,8
-6,3
6,5
0,2
336
329
-0,1
-55
-59
-27
-26
58
60
-512
-509
-809
-809
48
47
-7,4
-5,1
1,8
-7,4
4,4
0,0
270
265
-0,3
-49
-52
-20
-21
57
58
-513
-511
-810
-810
48
46
-7,6
-5,7
1,3
-7,9
3,2
0,0
227
224
0,3
-45
-47
-16
-18
57
57
-514
-512
-809
-810
47
46
-7,7
-6,0
0,9
-8,2
2,4
0,0
200
197
0,6
-42
-44
-13
-16
56
56
-514
-512
-809
-811
46
45
-7,8
-6,3
0,6
-8,5
1,7
-0,1
180
178
0,5
-41
-42
-12
-15
56
55
-514
-513
-809
-811
45
45
-7,9
-6,4
0,5
-8,6
1,4
-0,1
170
169
0,5
-40
-41
-11
-15
55
55
-514
-513
-809
-811
45
45
-7,9
-6,5
0,4
-8,6
1,3
-0,1
166
165
0,5
-39
-40
-10
-14
55
55
-515
-513
-809
-811
45
44
-8,0
-6,6
0,3
-8,8
1,0
-0,1
156
156
0,5
-38
-38
-9
-13
55
54
-515
-513
-809
-811
45
44
-8,0
-6,8
0,1
-8,9
0,8
-0,2
149
148
0,5
-37
-37
-8
-12
55
54
-515
-513
-809
-811
44
44
-8,0
-6,9
0,1
-8,9
0,6
-0,2
143
143
0,5
VME level [keV]
Standard deviation [HU]
Adipose @b
Adipose @d
Breast @Z
Breast @e
Liver @g
Liver @h
Lung exhale @B
Lung exhale @F
Lung inhale @A
Lung inhale @E
Muscle @c
Muscle @f
Plastic Water @3
Plastic Water @2
Plastic Water @5
Plastic Water @4
Plastic Water @1
Plastic Water @6
Trab. bone @a
Trab. bone @D
Water @H
60
70
80
90
12,4
13,0
13,1
12,3
13,7
13,2
12,8
11,0
13,2
13,4
12,8
12,9
13,0
13,2
12,2
12,2
11,4
11,5
13,5
12,9
11,9
9,2
9,7
9,2
9,3
9,9
9,6
9,8
8,3
10,8
10,9
9,6
9,5
9,3
9,7
9,1
9,1
8,6
8,8
9,7
9,5
8,9
9,4
9,8
9,0
9,6
9,7
9,5
9,9
8,5
11,1
11,1
9,9
9,5
9,4
9,8
9,2
9,4
8,9
9,0
9,6
9,3
9,0
8,6
9,0
8,4
8,7
9,0
8,8
9,1
7,7
10,3
10,4
9,0
8,7
8,6
9,0
8,3
8,5
8,0
8,1
8,8
8,6
8,2
100
107
110
120
130
140
7,9
8,3
7,8
8,1
8,3
8,1
8,4
7,1
9,6
9,7
8,3
8,0
8,0
8,3
7,6
7,8
7,3
7,4
8,1
7,9
7,6
7,6
8,0
7,6
7,9
8,0
7,8
8,0
6,8
9,3
9,5
8,0
7,7
7,7
8,0
7,3
7,5
7,0
7,1
7,8
7,6
7,3
7,5
7,9
7,5
7,7
7,9
7,6
7,9
6,6
9,2
9,3
7,9
7,6
7,6
7,9
7,2
7,4
6,8
7,0
7,6
7,4
7,2
7,2
7,6
7,2
7,4
7,6
7,3
7,5
6,4
8,9
9,1
7,6
7,3
7,3
7,6
6,8
7,0
6,5
6,6
7,3
7,1
6,9
6,9
7,4
7,1
7,2
7,3
7,1
7,2
6,1
8,7
8,9
7,3
7,0
7,1
7,3
6,6
6,8
6,3
6,4
7,1
6,9
6,7
6,8
7,2
6,9
7,1
7,2
6,9
7,1
6,0
8,5
8,7
7,2
6,9
7,0
7,2
6,4
6,6
6,1
6,2
6,9
6,7
6,5
GSI-7, Titanium.
VME level [keV]
Mean CT number [HU]
Adipose @b
Adipose @d
Breast @Z
Breast @e
Liver @g
Liver @h
Lung exhale @B
Lung exhale @F
Lung inhale @A
Lung inhale @E
Muscle @c
Muscle @f
Plastic Water @3
Plastic Water @2
Plastic Water @5
Plastic Water @4
Plastic Water @1
Plastic Water @6
Trab. bone @a
Trab. bone @D
Water @H
41
60
70
80
90
100
107
110
120
130
140
-77
-146
-445
-136
-263
37
-454
-439
-719
-727
-263
-54
70
-384
-62
-28
3
-0,52
310
288
-7
-65
-106
-272
-90
-136
41
-477
-466
-754
-758
-141
-17
37
-233
-39
-21
3
-0,38
251
240
-6
-58
-80
-160
-60
-53
45
-492
-484
-776
-779
-61
8
16
-135
-23
-17
3
0,29
215
211
-3
-54
-65
-89
-42
-1
45
-501
-494
-789
-790
-11
22
3
-73
-14
-14
5
1,54
190
191
-4
-51
-53
-39
-29
36
45
-507
-502
-799
-799
24
33
-6
-29
-8
-12
5
1,85
173
177
-3
-50
-48
-13
-22
55
45
-510
-506
-804
-804
42
38
-11
-7
-4
-11
5
2,03
164
170
-3
-49
-45
-3
-20
62
46
-512
-508
-806
-805
49
40
-13
2
-3
-11
5
2,10
161
167
-3
-48
-40
22
-13
81
46
-515
-511
-811
-810
67
45
-18
24
1
-10
6
2,23
152
160
-3
-47
-35
42
-8
95
46
-517
-514
-815
-813
81
49
-21
40
3
-9
6
2,35
146
155
-3
-46
-32
57
-4
106
46
-519
-517
-818
-816
91
52
-24
54
5
-8
6
2,46
140
151
-3
VME level [keV]
Standard deviation [HU]
Adipose @b
Adipose @d
Breast @Z
Breast @e
Liver @g
Liver @h
Lung exhale @B
Lung exhale @F
Lung inhale @A
Lung inhale @E
Muscle @c
Muscle @f
Plastic Water @3
Plastic Water @2
Plastic Water @5
Plastic Water @4
Plastic Water @1
Plastic Water @6
Trab. bone @a
Trab. bone @D
Water @H
60
70
80
90
100
107
110
120
130
140
25
54
227
32
63
33
28
36
23
21
68
38
36
172
26
65
23
23
31
32
27
17
33
137
21
39
21
20
24
16
16
41
23
23
103
18
42
16
16
21
21
18
13
21
78
16
26
15
16
17
14
14
26
16
17
60
15
28
14
14
16
16
15
13
17
46
15
22
15
16
16
14
14
23
15
15
35
14
22
13
13
15
15
15
12
13
26
13
19
13
15
14
13
13
21
13
13
21
13
17
12
12
13
13
14
11
12
20
12
19
12
14
13
12
12
21
12
12
18
12
14
12
11
13
12
13
11
12
20
12
19
12
14
12
12
12
21
12
12
18
12
14
11
11
12
12
13
10
11
24
11
19
11
13
11
12
11
22
12
12
22
11
12
11
10
11
11
12
10
12
31
11
20
10
13
11
11
11
23
12
11
28
11
11
10
10
11
11
12
10
12
37
10
20
10
12
11
11
11
24
12
11
32
10
11
10
10
11
10
11
GSI-7, Titanium MARS.
VME level [keV]
Mean CT number [HU]
Adipose @b
Adipose @d
Breast @Z
Breast @e
Liver @g
Liver @h
Lung exhale @B
Lung exhale @F
Lung inhale @A
Lung inhale @E
Muscle @c
Muscle @f
Plastic Water @3
Plastic Water @2
Plastic Water @5
Plastic Water @4
Plastic Water @1
Plastic Water @6
Trab. bone @a
Trab. bone @D
Water @H
42
60
70
80
90
100
107
110
120
130
140
-108
-98
-21
-59
83
1
-470
-445
-741
-741
78
5
21
10
-49
-15
9
5
280
301
-12
-96
-86
-13
-53
80
2
-470
-446
-740
-741
74
5
20
9
-50
-15
4
4
221
243
-14
-90
-81
-7
-50
78
2
-471
-447
-740
-741
73
4
19
8
-50
-16
2
4
184
208
-13
-86
-77
-4
-48
77
1
-471
-448
-740
-741
71
4
20
8
-51
-16
1
4
161
185
-13
-83
-74
-2
-46
76
1
-471
-448
-739
-741
70
4
20
7
-51
-16
0
3
143
169
-14
-81
-72
-1
-45
75
2
-471
-448
-739
-741
69
4
20
7
-51
-16
-1
3
135
160
-14
-81
-72
-1
-45
75
2
-471
-448
-739
-741
69
4
20
7
-51
-16
-1
3
131
157
-14
-79
-70
0
-44
74
2
-471
-448
-739
-741
68
4
20
7
-51
-16
-2
3
123
149
-14
-78
-69
1
-43
74
2
-471
-448
-739
-741
68
4
20
7
-51
-16
-2
3
116
142
-14
-77
-68
2
-42
74
2
-471
-449
-739
-741
68
4
20
7
-51
-16
-3
3
111
137
-15
VME level [keV]
Standard deviation [HU]
Adipose @b
Adipose @d
Breast @Z
Breast @e
Liver @g
Liver @h
Lung exhale @B
Lung exhale @F
Lung inhale @A
Lung inhale @E
Muscle @c
Muscle @f
Plastic Water @3
Plastic Water @2
Plastic Water @5
Plastic Water @4
Plastic Water @1
Plastic Water @6
Trab. bone @a
Trab. bone @D
Water @H
60
70
80
90
100
107
110
120
130
140
17
38
22
26
18
25
17
25
16
16
15
34
24
19
21
56
16
21
25
21
14
13
35
17
23
14
20
14
22
13
14
12
31
19
15
18
53
13
19
20
18
11
14
35
16
23
14
20
14
22
13
14
12
31
19
15
18
53
13
19
20
17
11
13
34
15
22
14
19
13
22
13
13
12
30
18
14
17
52
12
18
19
17
10
12
33
14
21
13
18
12
21
12
13
11
29
17
13
16
51
12
18
18
16
10
12
32
13
21
13
17
12
21
12
12
11
29
16
13
16
51
11
18
17
16
9
12
32
13
21
12
17
11
21
11
12
11
29
16
13
16
51
11
18
17
16
9
11
32
13
21
12
17
11
20
11
12
11
28
16
12
16
50
11
17
17
15
9
11
31
12
21
12
16
11
20
11
12
11
28
15
12
15
50
11
17
16
15
9
11
31
12
20
12
16
11
20
11
12
10
28
15
11
15
50
11
17
16
15
9
GSI-7, Steel.
VME level [keV]
Mean CT number [HU]
Adipose @b
Adipose @d
Breast @Z
Breast @e
Liver @g
Liver @h
Lung exhale @B
Lung exhale @F
Lung inhale @A
Lung inhale @E
Muscle @c
Muscle @f
Plastic Water @3
Plastic Water @2
Plastic Water @5
Plastic Water @4
Plastic Water @1
Plastic Water @6
Trab. bone @a
Trab. bone @D
Water @H
43
60
70
80
90
100
107
110
120
130
140
-90
-139
-393
-122
-212
26
-461
-443
-716
-735
-224
-44
50
-326
-55
-25
2
1,93
296
288
-8
-74
-117
-382
-101
-207
31
-467
-452
-733
-744
-216
-33
43
-323
-48
-23
-1
0,26
239
233
-9
-63
-104
-378
-88
-206
35
-473
-459
-745
-752
-212
-26
39
-324
-44
-22
-2
0,60
204
200
-8
-58
-96
-373
-80
-204
36
-476
-462
-752
-755
-208
-22
36
-322
-42
-22
-2
0,43
181
177
-8
-53
-89
-370
-74
-202
37
-477
-464
-757
-757
-205
-19
34
-321
-40
-21
-3
-0,01
164
161
-9
-51
-86
-368
-71
-202
38
-478
-465
-759
-759
-204
-18
33
-320
-38
-21
-3
-0,13
155
153
-9
-50
-85
-367
-70
-201
38
-479
-466
-760
-759
-203
-17
33
-320
-38
-21
-3
-0,22
152
150
-9
-48
-81
-366
-67
-200
39
-479
-467
-763
-760
-202
-16
32
-319
-37
-21
-4
-0,42
144
142
-9
-46
-79
-364
-64
-200
39
-480
-468
-764
-761
-201
-14
31
-319
-36
-21
-4
-0,56
137
135
-10
-45
-77
-363
-63
-199
39
-480
-469
-766
-762
-200
-14
31
-319
-35
-20
-4
-0,67
132
131
-10
VME level [keV]
Standard deviation [HU]
Adipose @b
Adipose @d
Breast @Z
Breast @e
Liver @g
Liver @h
Lung exhale @B
Lung exhale @F
Lung inhale @A
Lung inhale @E
Muscle @c
Muscle @f
Plastic Water @3
Plastic Water @2
Plastic Water @5
Plastic Water @4
Plastic Water @1
Plastic Water @6
Trab. bone @a
Trab. bone @D
Water @H
60
70
80
90
100
107
110
120
130
140
21
48
192
29
57
25
22
35
19
21
60
31
30
147
25
64
19
21
27
27
20
16
39
197
24
53
18
17
28
14
17
55
25
25
162
20
54
14
17
21
22
16
17
35
205
24
56
19
17
27
14
18
58
25
24
174
20
51
14
18
21
22
18
16
33
208
22
55
18
16
25
13
16
56
24
23
179
18
48
13
16
19
21
16
16
30
210
20
55
18
15
23
12
15
55
23
22
183
17
45
12
15
18
19
15
16
29
211
20
54
18
14
22
11
15
55
22
21
185
16
44
11
14
17
19
15
16
28
211
19
54
18
14
22
11
14
55
22
21
186
16
43
11
14
17
19
15
16
27
212
19
54
18
13
21
11
14
54
21
21
188
15
42
11
14
17
18
14
16
26
213
18
55
18
13
20
10
14
54
21
20
190
15
40
10
13
16
18
14
16
26
214
18
55
18
13
20
10
13
54
21
20
191
14
40
10
13
16
17
14
GSI-7, Steel MARS.
VME level [keV]
Mean CT number [HU]
Adipose @b
Adipose @d
Breast @Z
Breast @e
Liver @g
Liver @h
Lung exhale @B
Lung exhale @F
Lung inhale @A
Lung inhale @E
Muscle @c
Muscle @f
Plastic Water @3
Plastic Water @2
Plastic Water @5
Plastic Water @4
Plastic Water @1
Plastic Water @6
Trab. bone @a
Trab. bone @D
Water @H
44
60
70
80
90
100
107
110
120
130
140
-106
-101
-19
-59
80
4
-467
-440
-740
-739
76
2
19
12
-51
-14
9
2,63
279
299
-12
-94
-90
-10
-53
77
5
-468
-441
-739
-739
73
1
18
10
-51
-14
4
1,61
221
242
-13
-87
-84
-4
-49
76
5
-469
-443
-739
-740
71
1
18
9
-52
-14
2
1,69
184
206
-12
-84
-80
-1
-47
75
4
-469
-443
-739
-740
71
1
18
9
-52
-14
1
1,45
160
183
-12
-81
-77
1
-45
74
4
-469
-444
-739
-740
70
0
18
8
-52
-14
-1
1,13
143
167
-12
-79
-76
2
-44
74
4
-469
-444
-738
-740
69
0
18
8
-53
-14
-1
0,96
134
158
-12
-78
-75
3
-44
74
5
-469
-444
-738
-740
69
0
18
8
-53
-14
-2
0,89
131
155
-12
-77
-73
4
-43
73
5
-469
-444
-738
-740
69
0
18
8
-53
-14
-2
0,73
122
146
-13
-75
-72
5
-42
73
5
-469
-445
-738
-740
68
0
18
7
-53
-14
-3
0,61
116
140
-13
-77
-68
2
-42
74
2
-471
-449
-739
-741
68
4
20
7
-51
-16
-3
2,61
111
137
-15
VME level [keV]
Standard deviation [HU]
Adipose @b
Adipose @d
Breast @Z
Breast @e
Liver @g
Liver @h
Lung exhale @B
Lung exhale @F
Lung inhale @A
Lung inhale @E
Muscle @c
Muscle @f
Plastic Water @3
Plastic Water @2
Plastic Water @5
Plastic Water @4
Plastic Water @1
Plastic Water @6
Trab. bone @a
Trab. bone @D
Water @H
60
18
44
23
28
24
22
16
26
15
17
18
36
23
27
23
57
15
20
24
20
14
70
14
41
20
25
22
18
14
24
13
15
16
33
19
24
20
54
12
18
20
17
11
80
15
41
20
25
22
17
13
24
13
15
16
34
19
24
21
54
12
19
20
17
11
90
14
40
19
25
21
16
13
23
12
14
15
33
18
23
20
53
12
18
19
17
10
100
107
110
120
130
140
13
40
19
24
21
16
12
23
11
14
15
33
17
22
19
52
11
17
18
16
10
13
39
18
24
21
15
12
22
11
14
15
32
17
22
19
52
11
17
17
16
9
13
39
18
24
21
15
11
22
11
14
15
32
17
22
19
52
11
17
17
16
9
13
39
18
24
20
15
11
22
11
13
15
32
16
21
18
51
10
17
16
16
9
12
38
18
23
20
14
11
22
10
13
15
32
16
21
18
51
10
17
16
16
9
11
31
12
20
12
16
11
20
11
12
10
28
15
11
15
50
11
17
16
15
9