Radiological Technology (13:30 ～16:10 Lecture Room 2)
Session chairs: Prof. Yoshie Kodera
Associate Prof. Masatoshi Tsuzaka

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ADVANCEMENT OF MEDICAL IMAGING AND INSTRUMENTATION IN
RADIOLOGICAL SCIENCE
Hee-Joung Kim1)
1) Department of Radiological Science and Research Institute of Health Science, Yonsei University, Korea

Background
Clinical applications as well as research activities inmedical imaging and instrumentation are rapidly growing fields
in radiological science. Recent trends of clinical research of
SPECT/CT, PET/CT, and PET/MRI as well as advanced
imaging modalities indicate that clinical applications of various
imaging modalities are very active, and have been triggeringresearch activities of medical imaging and instrumentation inradiological science. Dept. of radiological science at Yonsei
University is relatively new and has been focusing on bothresearch of new technologies in medical imaging andinstrumentation, and education and training of practical as wellas advanced technologies in radiological science.
Methods
Recently, two international congress meetings were held
and one international conference meeting will be held in 2013
in Seoul. One was the World Congress on Medical Physics andBiomedical Engineering 2006 with the theme of “Imaging thefuture medicine” and the other one was “9th Congress of theWorld Federation of Nuclear Medicine & Biology with thetheme of “Global harmonization and new horizon of nuclear
medicine” at the same place of Coex, Seoul, Korea. These twocongress meetings may cover worldwide major research
activities in medical imaging and instrumentation and played avery important role to have nationwide attention including
governmental level in Korea. Recently, it’s been decided tohave 2013 IEEE NSS/MIC conference meeting in Seoul, Korea,
and our Dept. will play a major role to host this prestigious
conference meeting for the 1st time in Asia and Oceania. There
are 4 Laboratories in our Dept. including medical physics andimaging Lab (MPIL), iTOMO Lab, Molecular Imaging Lab(MoIL), and magnetic resonance imaging Lab (MRIL). Major
interests of iTOMO Lab includes dental panorama imaging
technique, dental CT technique, dual-energy radiography
imaging technique, tomosynthesis imaging algorithm, design
digital processing filter and algorithm to improve image quality,
and image quality estimate technique of digital radiography.
MRIL has been researching on functional MRI, diffusion tensor
imaging & fiber tractography, and phase contrast MR
angiography. MoIL has been researching on developing both
small gamma camera and small PET, and image optimization.
Research interests of MPIL includes the measurements ofphysical characteristics of SPECT/PET/X-ray & CT, and theirquantitation, imaging physics and instrumentation, andsimulation of multi-modality imaging techniques. Recently, ourDept. awarded government grant of “Basic Atomic Energy
Research Institute (BAERI)” which will support for next 6
years to develop functional and anatomical multi-imaging
technology based on multi-energy photon counting. The
purpose of this project is to develop the image acquisition
technique for the optimization of multi-energy photon counting
images included in functional/anatomical information and toresearch the functional and anatomical fused imaging on thestate-of the art technologies.
Results
With these activities, in recent years, medical imaging andinstrumentation, such as digital x-ray radiography, computed
tomography, nuclear magnetic resonance, emission tomography,
animal imaging devices, multi-modality systems, and modelingand evaluation of imaging systems, have been rapidly
advancing in Korea. The Korean government has been trying tolay a foundation for medical devices and information by
providing policies and systematic funding supports on the
product and technology development. Based on thegovernment’s supports, there are strenuous and growing efforts
to improve the nation’s international competence made in
research and development of medical imaging technology andits applications by universities, industries, and national science
research institutes, although major research activities have beenleading by academic side compared to industry side. The
figure1 shows the scope of the BAERI project to be developed.
Figure 1. The scope of the development of multi-imaging
technology based on photon counting
Conclusion
Summaries of the current achievements and the future
prospects in the realm of medical imaging and instrumentationin our Dept. will be presented with overview of clinicalapplications in advanced imaging technologies. Summaries of
educational system in radiological science as well as medical
physics in our Dept. will also be presented.

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Memo

NONINVASIVE ESTIMATION OF REGIONAL CEREBRAL BLOOD FLOW USING
123I-IMP ACQUISITION DATA

Shinji Abe1) 2), Katsuhiko Kato3), Yoshitake Takahashi4), Masato Yamashita2), Naotoshi Fujita2), Naotoshi Ohta5),
Yasukazu Kajita6), Shinji Naganawa5).
1)

4)

Department of Radiological Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan
2) Department of Radiological Technology, Nagoya University Hospital, Nagoya, Japan
3) Department of Radiological Technology, Nagoya University School of Health Sciences, Nagoya, Japan
Department of Medical Engineering, Division of Allied Health Sciences,Osaka University Medical School, Osaka,Japan5) Department of Radiology, Nagoya University Graduate School of Medicine, Nagoya, Japan
6) Department of Neurosurgery, Nagoya University Graduate School of Medicine, Nagoya, Japan

Introduction
N-isopropyl-p [I-123] iodoamphetamin (123I-IMP) is
widely used as a tracer for the measurement of regional
cerebral blood flow (rCBF) by single-photon emission
computed tomography (SPECT). 123I-IMP is one of the mostsuitableavailable
SPECT
tracers
becausetheradiopharmaceuticals excel in the contrast between the
cerebral normal and defective parts.
Measurement ofrCBF is necessary for evaluation of the cerebral circulation tounderstand abnormalities of blood flow and the targetchanges due to disease processes. In the quantification, 123IIMP has a higher first-pass extraction fraction and negligible
back diffusion from cerebral tissue immediately after
injection. Therefore, it is not easily influenced by metabolic
activity of the tissues and indicates the good linearity of theradioactivity distribution in rCBF.
In general, arterial blood sampling and an integral of
input function are needed to calculate rCBF. SPECT andcontinuous arterial blood sampling on the basis of the
microsphere model described by Kurl et al. were used tomeasure rCBF with 123I-IMP (1-2). Moreover, several
studies have been made using a two-compartment model
analysis which correlates with back diffusion of 123I-IMP (3).
These methods require arterial blood sampling which isinvasive for patients and demanding in a daily clinical setting.
To date, there have been some reports on the estimationof rCBF by observing pharmacokinetics of 123I-IMP without
arterial blood sampling (4-5). However, the rCBF values
estimated in these studies have not been compared with thoseobtained by other methods. 15O-water seems to be moresuitable for rCBF quantification than 123I-IMP because it is
not metabolized inside of the body and the extraction fraction
is comparatively high (0.85-0.95) (6).
The purpose of this study was to evaluate a newnoninvasive method using 123I-IMP for estimation of rCBF
without any blood sampling and to compare the new methodwith the conventional method using 15O-water PET.
Materials and Methods
Consecutive 8 patients with suspected CBF disorders(age: 58±19y, male/female:4/4) underwent PET and SPECT
examinations on the same day. Procedures for dataacquisition by PET and gamma camera are summarized in
Fig.1.
The study was performed according to the approval of
the Ethics Committee of Medicine at Nagoya University for
Human Studies, and informed consent was obtained from all
patients before the study.

Fig.1 Outlines of the procedure of 15O-water PET and 123I-IMP
data acquisition with gamma camera.

CBF measurement by PET was performed using 15O bolus
administration autoradiography method by Kanno et al. (6).
PET scanner SET2400 (Shimadzu Corporation, Kyoto, Japan)
and two gamma cameras E.CAM for two-detector type and
GCA9300A/UI for three-detector type (Toshiba Medical
systems company respectively, Nasu, Japan) were used. First,
CBF measurement by PET was performed. Next, dynamic
lung and static head images were acquired after injection of 123I
-IMP, followed by brain SPECT. Lung washout counts and thetime course of brain counts were used for explanatory variables,and rCBF measured by 15O-water PET is used for the dependent
variables. The regression equation was calculated with bothvariables. The rCBF was estimated using the regression
equation.
The PET and SPECT images were matched to a standard
cerebral template by analytical three dimensions ROI software(7), and the accumulation ratios were calculated on each regionof the brain.
Results
Examples of lung and brain images and lung washout
curve for a study patient are shown in Fig. 2. Fig. 3 shows
comparison of the rCBF values estimated by 123I-IMP SPECTand those actually measured by 15O-water PET autoradiography.
A significant correlation (r=0.93, p<0.001) was detected
between rCBF values measured by 15O-water PET and thoseestimated with 123I-IMP.

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A

B

Discussion
We demonstrated that rCBF can be estimated by using the123
I-IMP initial circulation images of the lungs and brain
without any blood sampling, and that the rCBF values obtainedby this method showed accuracy similar to those actually
measured by 15O-water PET.
Furthermore, the new method proposed in this study ismore useful for daily clinical rCBF quantification than theconventional methods which require arterial blood sampling.
Conclusion
The noninvasive method proposed in this study canreliably estimate rCBF using brain 123I-IMP SPECT data
without any blood sampling.

Fig.2 Data acquired after intravenous injection of 123I-IMP.
(A) Lung planar image approximately 3 min after injection.
(B) Time course of radioactivity of the lungs after injection.
(C) Brain static images at 5 min, 13 min (pre-SPECT) and
45-50 min (post-SPECT) after injection.

References[1]Kuhl DE, Barrio JR, Huang SC, et al. Quantifying local
cerebral
blood
flow
by
N-isopropyl-p[I-123]
iodoamphetamin (IMP) tomography. J Nucl Med 1982;
23:196-203.
[2]Matsuda H, Seki H, Sumiya H, et al. Quantitative local
cerebral blood flow by N-isopropyl- (iodine 123) piodoamphetamine and single photon emission computed
tomography with rotating gamma camera. Am J physiol
Imaging 1986; 1: 186-194.
[3]Iida H, Itoh H, Uemura K, et al. Quantitative mapping ofregional cerebral blood flow using iodine-123-IMP and
SPECT. J Nucl Med 1994; 35:2019-2030.
[4]Yonekura Y, Sugihara H, Taniguchi Y, et al. Quantificationof brain perfusion SPECT with N-isopropyl-piodoamphetamin using noninvasive microsphere method:
estimation of arterial input by dynamic imaging. Jpn J Nucl
Med 1997; 34:901-908.
[5]Okamoto K, Ushijima Y, Okuyama C, et al. Measurement of
cerebral blood flow using graph plot analysis and I-123
iodoamphetamine. C Nucl Med 2002; 27:191-196.
[6]Kanno I, Iida H, Miura S, et al. A system for cerebral bloodflow measurement using an H215O autoradiographic method
and positron emission tomography. J Cereb Blood Flow
Metab 1987; 7:143-153.
[7]Takeuchi R, Yonekura Y, Matsuda H, et al. Usefulness of athree-dimentional stereotaxic ROI template on anatomicallystandardised 99mTc-ECD SPET. Eur J Nucl Mol Imaging
2002; 29:331-341
Author address

Shinji Abe
65 Tsurumai-Cho, Showa-Ku, Nagoya, 466-8560, Japan
Tel: +81-52-744-2553
abeshin-ngy@umin.ac.jp
Fig.3 Comparison of the rCBF values estimated by 123I-IMP
SPECT and those measured by 15O-water PET. There is asignificant correlation between the regional CBF values
obtained by these two methods (r=0.94: p<0.001).

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AN INFLUENCE OF THE BEAM QUALITY ON THE NOISE OF
THE IMAGE IN DIGITAL MAMMOGRAPHY
Maki Yamada1), Yuri Kato1) Naotoshi Fujita2), Yoshie Kodera3)
1) Department of Radiological Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan2)Department of Radiological Technology, Nagoya University Hospital, Nagoya, Japan
3) Department of Radiological Technology, Nagoya University School of Health Sciences, Nagoya, Japan

Introduction
The uses of digital mammography systems have become
widespread recently. However, the optimal exposure
parameters are uncertain in clinical. We need to optimize theexposure parameter in digital mammography withmaximization of the image quality and minimization ofpatient dose. The purpose of this study is to investigate an
influence of the x-ray energy on the noise of the image. We
obtained images for various tube voltage and the thickness ofcompressed breast. The noise properties of these images were
evaluated with these indices: Wiener spectrum (WS), thenoise equivalent number of quanta (NEQ), and signal-tonoise ratios derived from the perceived statistical decision
theory model with the internal noise of eye-brain system(SNRi). We measure them under the fixed average glandular
dose (ADG).

Table 1. EUREF dose acceptable level for each thickness
of PMMA and its equivalent breast thickness
PMMA
Equivalent
Dosethicknessbreastacceptable[cm]
thickness [cm] level [mGy]
2
2.1
0.6
4
4.5
1.6
5
6.0
2.4
7
9.0
5.1
Table 2. Exposure level for 4-cm-thick PMMA with Mo/Mo
AGD
25 kV
28 kV
30 kV
32 kV
[mGy]
Exposure level [mAs]
1.3
80
50
40
32
1.7
100
63
50
40

Materials and Methods
Equipment used in this study ; The mammographyequipment used in this study was Mermaid model MGU100B. The computed radiography (CR) reader used was
REGIUS V stage, Model 190. The CR plate used was
CP1M200 (with the columnar crystal phosphors). These
equipments were manufactured by Konica Minolta MG. The
x-ray images of low contrast objects were obtained for themeasurement of the SNRi. To measure the contrasts and to
calculate Wiener spectrum, we obtained images of acrylic
steps (thickness: 1-10 mm) and uniformly exposed x-ray
images. We used acrylic plates (thickness: 2, 4, 5 and 7 cm)
as breast phantoms. Mo/Mo and Mo/Rh were chosen for thetarget/filter combinations. As the source of low contrast
signal, we used a resinous disc (diameter: 4.2mm, thickness:
4.5mm). To measure the presampled modulation transfer
function (MTF) for NEQ, we obtained images of thetungstenium edge.
Measurement of the average glandular dose ; We
measured the average glandular dose (AGD) and chose theexposure level which gave the European Reference
Organization for Quality Assured Breast Screening (EUREF)
dose acceptable level for every combination of the
thicknesses of phantoms and the tube voltages (25, 28, 30, 32,
35 kV). Actually, we could not adjust the exposure level for
the AGD strictly because of the restriction of the machine.
Therefore we selected the exposure level for EUREF dose
acceptable level as near as possible (Table.1 and Table.2).
Measurement of image contrasts ; WS depends on theimage contrast, and the image contrast changes with the tube
voltage. For this reason, we evaluated WS under fixed image
contrast. In order to do this, the image contrast of each tube
voltage was measured. We obtained the images of the acrylic
plates and the acrylic steps, which were put on the chest wallside of the table for the contrast evaluation (Fig. 1). We readout the raw data of the acrylic step images and found thecontrast by the pixel value of each step.

(a) Overview(b) Overhead viewFig. 1 Layout of measurement of the contrast

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Calculation of WS ; We calculated the WS by the twodimensional fast Fourier transform method. When weevaluated the WS values at 25, 30, 32 and 35 kV, we
adjusted the contrasts under these tube voltages to that under
28 kV. To tune the image contrasts, we computed the WS
and multiplied the following correction factor k.

SN
Ri

ｋ=(image contrast at 28 kV/image contrast at another tube voltage)2
Calculation of NEQ ; The NEQ is described as shown
below:
25

NEQ={(G･log10e)2MTF2}/{WSΔPV}In these figure, G means the gradient of the characteristic
curve for the detector.
Calculation of SNRi ; The SNRi, which takes the spatial
frequency response of the human visual system and theinternal noise of eye-brain system into consideration, is
written as
SNRi=SNRp/{1+(Ni/Np)2}1/2
In this formula, the SNRp represents the ratio of signal (Sp)to noise (Np). The value of the Sp and the Np were
calculated in consideration of the visual spatial frequency
response of the human observer 3) . The Ni means the internal
noise 4) which is inherent in an observer, for instance, thenoise in relation to the neurophysiological unstableness andto fluctuations of the observer’s memory.
Results
WS ; The WS was almost stable when the tube voltagechanged between 2-cm and 4-cm-thick phantoms. There
were few differences in the WS values for each tube voltage
with 5-cm-thick phantom, and we observed the tendency thathigh tube voltage improves the noise property of the image.
This trend was more remarkable for 7-cm-thick phantom. As
the combination of target/filter, Mo/Rh was more beneficial
than Mo/Mo for phantoms thicker than 4 cm. This trend was
also more conspicuous for thicker phantom.
NEQ ; For 2-cm-thick phantoms, the NEQ did not changewith the tube voltage and filtration except for 32 and 35 kV
with Rh filter. The NEQ values on these two exposure
conditions were lower than that on others. Also, 35 kV with
Rh filter gave the highest NEQ for phantom thicker than 4
cm. In these cases, the superiority of Rh filter to Mo filter
became clearer for thicker phantom.
SNRi ; The SNRi is shown in Figure 2. For 2-cm and 4-cmthick objects, we recognized the tendency that the SNRi
value with Mo filter was larger than that with Rh filter. The
SNRi increased when the tube voltage decreased.

Discussion
The results of WS and NEQ indicate that when the image
contrast and AGD was constant, for a phantom thinner than 5
cm, an increase of the tube voltage did not improve the noise

28

30
32
Tube voltage[kV]35

Fig.2 The results of SNRi for each thickness of phantoms
property of images very much. The results also showed thatimage property with the target/filter Mo/Rh was better than thatwith Mo/Mo for the phantom thicker than 4 cm. In general, it issaid that high tube voltage delivers fine noise property. The
result of our study contradicted this common theory on the x-ray
energy level for mammography.
The result of SNRi differers from the results of WS and NEQ.
In this study, the SNRi depends on the contrast of signal. We
should make accuracy high with the low contrast object that has
another intensity.
Conclusions
In conclusion, when the image contrast and AGD was constant,
for the phantom thinner than 5 cm, an increase of the tube
voltage did not improve the noise property of images very much.
The results also showed that image property with thetarget/filter Mo/Rh was superior to that with Mo/Mo for thephantom thicker than 4 cm. Our result signified that high tube
voltages did not improve the noise property of images with the
x-ray energy level for mammography.
The result of SNRi conflicted with the results of WS andNEQ. We need to examine SNRi with the low contrast signal
which have various intensity.
References[1]Leh-Nien D Loo, Kunio Doi, Charles E Metz. A comparisonof physical image	  quality indices and observer performancein the radiographic detection of nylon beads. Phys. Med. Biol.,
1984;29, No. 7;837-856[2]Masamitsu Ishida, Kunio Doi, Leh-Nien Loo, et al. Digital
Image Processing: Effect on Detectability of Simulated Low
Contrast Radiographic Patterns. Radiology 1984; 150: 569575[3]Anil K. Jain. Fundamentals of Digital Image Processing.
Prentice Hall. 1989
[4]Ken Ohara, Heang-Ping Chan, Kunio Doi, et al.Investigationof basic imaging properties in digital radiography. 8.
Detection of simulated low-contrast objects in subtraction
angiographic images. Med. Phys 1986; 13(3): 304-311
Author address

E-Mail:yamada.maki@h.mbox.nagoya-u.ac.jp

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MULTI-MATERIAL DECOMPOSITION IMAGING IN THE PHOTON COUNTING
DETECTOR
Hyo-Min Cho1), Yu-Na Choi1), Hee-Joung Kim1)
1) Department of Radiological Science and Research Institute of Health Science, Yonsei University, Korea

Introduction
The photon counting detectors such as cadmium zinctelluride (CZT) and cadmium telluride (CdTe) have powerfuladvantages compared to energy integrating detectors. CZT or
CdTe can detect individual gamma-ray or x-ray photon withenergy discrimination. In recent years, energy-resolving andmaterial decomposition x-ray imaging based on photon
counting detectors has attracted attention from biomedical
imaging researchers. One group has reported two contrast
agents could be distinguished by the k-edge CT image using
photon counting detectors.
Monte Carlo simulation is an essential tool in emission andtransmission imaging that can assist in the design of new
medical imaging devices, the optimization of acquisition
protocols and the development or assessment of image
reconstruction algorithms and correction techniques. This year,
the OpenGATE collaboration has released GATE 6.0,
supporting simulations of radiotherapy and computed
tomography. They provide geometry of computed tomography
with photon counting based readout.
We evaluated a large-area CZT detector originally built as aradionuclide detector for a small animal SPECT/CT system incombination of a microfocus x-ray source with a general goalof developing a material-decomposition imaging method. In
addition, the characteristic study of two photon counting
materials, CZT and CdTe were evaluated in the GATE
environment.
Materials and Methods
The presentation will describe the basic principles of multimaterial decomposition imaging based on photon counting
detector. The experimental results from a feasibility study ofmulti-material decomposition imaging using the developed
small animal SPECT/CT system will be presented. In addition,
the simulation results for the characteristic of photon counting
detector and multi-energy imaging of multi-material phantom
will be presented.
Experimental feasibility of multi-material decomposition
imaging
The characteristics of x-ray tube from Oxford Instruments(Scotts Valley, CA, USA) are; tungsten anode, source size 80
μm x 70 μm, maximum operating current 1 mA, and maximum
accelerating voltage 60 kV. The 2 mm thick aluminum filter
was used to attenuate x-rays with energies below the noise
floor of the detector.
The large area photon counting CZT detector manufactured
by Gamma Medica Ideas (Northridge, CA, USA) was used.
The detector has an active detection area of 20 x 20 cm2, withmultiple modules tiled together. The detector is configured as a
5 x 5 array of CZT modules, each with a 16 x 16 array of pixels
and a pixel width of 2.5 mm. Thus, the used CZT detector is an
80 x 80 pixel array covering an active area of 20 x 20 cm2 witha crystal thickness of 2.5 mm.
For the feasibility study of multi-material decomposition
imaging a phantom that included various materials was built.

We designed the phantom using a 15 x 15 cm2 piece ofcellophane. We had attached 7 materials, with a range ofdensities and atomic numbers, on the cellophane. The materials
are including glass (silicon dioxide), highly ordered pyrolytic
graphite (HOPG), clay, titanium, plastic, aluminum, buffalo
nickels, walking liberty half dollar coin.
The CZT detector was positioned 84.3 cm from the x-ray
tube focal spot. The phantom was taped in contact with, andcentered on, the CZT detector. The multi-material x-ray images
were obtained at 50 kVp, 0.5 mA, and images were acquiredfor 140 sec/image. Acquired images corrected for bad pixels,
gain, and offset. The attenuation of each material was obtainedby the ratio of the emergent and incident radiation intensities
I/I0 according to the x-ray energy.
CZT detector in x-ray spectroscopy with different pixel sizes
and pitches
GATE version 6.0 was used to perform an accurate
simulation of the different pixel sizes. In this simulation study,
charge sharing and pulse pileup were not considered. The Cd1xZnxTe detector (x = 0.1, density = 5.68 g/cm3) used in thisstudy. The CZT detector was 10x10 mm2 and thickness of 3
mm. The thickness was chosen since it allows >90% absorptionof the photons at 120 kVp. In an attempt to evaluate thedetection ability, we designed the CZT detector with different
pixel size on GATE. The pixels with sizes of 0.09 ×0.09, 0.45
×0.45, and 0.90×0.90 mm2 were simulated.
Energy resolved photon counting x-ray imaging with CZT
detector
We designed a cylindrical PMMA phantom including three
Iodines in concentration of 140, 40, and 8 mg/cm3 and one
Gadolinium in concentration of 39.3 mg/cm3. We studied theability to separate different materials from the multi-energy
windows. We obtained images from 23-32, 33-42, 40-49 and
50-59 keV energy windows. For each energy windows thecontrast-to-noise ratio (CNR) was considered to be the image
quality.
Results
Measured attenuation of each material was in a good
agreement with the reference data of the NIST physics
laboratory. The attenuation of x-rays in the various materials isdependent on the energy of the x-rays and the atomic
composition of the material.
Three different pixel spectrums were distorted towards thelower energy region. Because the characteristic x-rays add
counts in the range of 20-40 keV. The photoelectric effect isdominant at Cd and Te of CZT material due to the high Z
numbers. The Z numbers of Cd and Te are 48 and 52. Ascharacteristic x-rays of Cd and Te process quite high energy,
they escape from crystals. Especially, these effects are evident
in the small pixel sizes.
For Iodine, the CNR was found to dramatic increase in therange of 33-42 keV. For Gadolinium, the calculated value of

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the CNR in the range of 50-59 keV was higher than thosebelow 50 keV. Because the photons with energy levels justabove the K-edge energy are more likely to be absorbed thanphotons with energy levels just below the K-edge energy.
Conclusions
We demonstrated that multi-material decomposition
imaging is experimentally feasible using the photon-counting
CZT detector and polychromatic x-ray. The photon counting
based functional and anatomical imaging system will be
designed in the GATE.

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DOSIMETRIC CHARACTERIZATON OF FLATTENING FILTER FREE LINAC
USING MONTE CARLO SIMULATION
Takuma Matsunaga1), Tomohiro Shimozato2), Yuichi Aoyama3), Hiroshi Fukuma4), Ryuichi Yada5), Hiraku Fuse1),
Yusuke Oribe1), Masataka Komori2), Yasunori Obata2)
1) Department of Radiological Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan
2) Department of Radiological Technology, Nagoya University School of Health Sciences, Nagoya, Japan
3) Department of Radiology, Nagoya University Hospital, Nagoya, Japan4) Central Department of Radiology, Nagoya City University Hospital, Nagoya, Japan
5) Department of Radiology, Seirei Hamamatsu General Hospital, Hamamatsu, Japan

Introduction
The flattening filter (FF) of medical linac is placed in thephoton beamline to produce a flat beam profile at the given
depth, but it decreases primary beam intensity by scatteringand absorption. Recently some researches have shown thatremoving FF from medical linac can increase dose rateconsiderably, and reduce out-of-field doses [1-4]. In thisstudy, we provide dosimetric properties of 6 MV and 10 MV
photon beams from FF free (FFF) linac using Monte Carlo(MC) simulation.
Materials and Methods
MC modeling of medical linac with and without FF: We
have developed 6 MV and 10 MV photon beam model forthe linac head of Varian Clinac series accelerator using
EGSnrc/BEAMnrc MC code [5]. The linac head components,
including target, primary collimator, vacuum window, FF,monitor ion chamber, mirror, and X and Y jaws, were
simulated on the basis of manufacturer-provided information.
To calculate dose distributions in water phantom, we applied
EGSnrc/DOSXYZnrc MC code [6].
The initial electron beam incident on the target have the
distribution of the electron energy and the radial intensity
assumed Gaussian in shape[7], and mean energy andintensity distribution of the initial electron is not clearly andvaries among the same model of linacs. To determine
electron energy, we comparing the measured and calculated
percentage depth dose (PDD) for 30 x 30 cm2 field size.
After initial electron energy selection, we determined
intensity distribution comparing the measured and calculated
off-center ratio (OCR) at the depth of 10 cm for 5 x 5, 10 x
10, 20 x 20, and 30 x 30 cm2 field sizes. To compare themeasured and calculated dose, local dose difference were
calculated by following equation:

Dosimetric properties of FFF linac: To find out thecharacteristic of FFF linac, we compared PDD and OCR forvaried field sizes, dose per incident electron, planer fluence,
energy fluence, and energy spectrum with standard linac using
EGSnrc/DOSXYZnrc and BEAMDP sub code [8].
Results and Discussion
Validation of MC modeling: To validate our MC simulation,
calculated PDD and OCR were compared with measurement
data. There were good agreement between MC andmeasurement results, and local differences were less than 3% in
all region. The examples of calculated and measured PDD and
OCR are shown in Fig. 1 and 2, respectively.

Fig. 1 PDD for 10 x 10 cm2 field size of 6 MV and 10 MV.
Monte Carlo is circle and measurement is solid.

The mean energy of the initial electron and the
distributions of the electron energy and the radial intensity
are shown in Table 1. Using determined initial electron, thephase-space (PS) file, containing data relating to particle
position, direction, charge, and energy for 5 x 5, 10 x 10, 20
x 20, and 30 x 30 cm2 field sizes at source surface distance(SSD) of 100 cm with and without FF were produced.
Table 1 Initial electron parameters. The energy andintensity spread is given at FWHM
Nominalenergy (MV)6
10

Derived energy
(MeV)
6.0
10.5

Energy spread
FWHM
3%
3%

Intensity spread
FWHM (cm)
0.15
0.15

Fig. 2 OCR at the depth of 5 cm, 10 cm, 20 cm, and 30 cm
for 10 x 10 cm2 field size of 6 MV. Monte Carlo is circle andmeasurement is solid.

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Dosimetric properties of FFF linac: We considered dose
per initial electron at the depth of 10 cm for dose ratecomparison. For 10 x 10 cm2 field size, the ratios of dose per
initial electron for FFF linac to standard linac were 2.38, 5.17
for 6 MV, 10 MV, respectively.
The depth dose and OCR were calculated for field sizesof 5 x 5, 10 x 10, 20 x 20, and 30 x 30 cm2. The depth dose
curves of FFF linac for 10 x 10 cm2 field for 6 MV and 10
MV, are shown in Fig. 3 and 4, respectively. The depth dose
was normalized at maximum point of measurement with FF.
In the beyond maximum dose region, the dose for standard
linac is higher than that for FFF linac due to the beamhardening effect of the FF. In the build up region, because ofsofter spectra and contamination low-energy electron, FFF
linac delivers higher dose than standard linac. Especially, for
10 MV, significant increasing dose in the build up region isobserved due to the excessive contamination electron. It
seems that more penetrating electron through the target reachthe phantom for 10 MV than for 6 MV, because the target of
6 MV is tungsten and copper, but that of 10 MV is copper
only.

fluence was reduced with distance from central axis as a resultthat removing FF reduced scattering radiation from linac head.

Fig. 5 Comparison of OCR at the depth of 10 cm for withand without FF for 10 x 10 cm2 field size of 10 MV. without
FF, MC is circle and with FF, measurement is solid.
Conclusions
The MC model of Varian Clinac series accelerator with andwithout FF were developed and compared. Our results showsthat removing FF can increase dose rate and decrease out-offield dose. These could be an advantage of FFF linac, but forclinical usage, FFF linac should equip the filter to remove theexcessive contamination electron.

Fig. 3 Comparison of depth dose for with and without FF
for 10 x 10 cm2 field size of 6 MV. without FF, MC iscircle and with FF, measurement is solid.

Fig. 4 Comparison of depth dose for with and without FF
for 10 x 10 cm2 field size of 10 MV. without FF, MC iscircle and with FF, measurement is solid.
The OCR at the depth of 10 cm of 10MV FFF linac for
10 x 10 cm2 is shown in Fig. 5. OCR was normalized at thecentral axis dose. By removing of FF, the dose was reducedwith distance from the central axis. In addition, removed FF
reduced the out-of-field dose. For example, in Fig. 5, at a
distance of 7 cm from the central axis, the ratio of doses for
FFF linac to standard linac was 0.8. This is because photon

References[1]Oleg N Vassiliev, Uwe Titt, Falk Pönisch, Stephen F Kry,
Radhe Mohan, Michael T Gillin. Dosimetric properties ofphoton beams from a flattening filter free clinical accelerator.
Phys. Med. Biol. 2006;51:1907-1917.
[2]Oleg N Vassiliev, Uwe Titt, Stephen F Kry, Falk Pönisch,Michael T Gillin, Radhe Mohan. Monte Carlo study ofphoton fields from a flattening filter-free clinical accelerator.
Med. Phys. 2006;33:820-827.
[3]Asghar Mesbahi. Dosimetric characteristics of unflattened 6
MV photon beams of a clinical linear accelerator. Appl.
Radiat. Isot. 2007;65:1029-1036.
[4]Gabriele Kragl, Sacha af Wetterstedt, Barbara Knäusl,Mårten Lind, Patrick McCavana, Tommy Knöös, Brendan
McClean, Dietmar Georg. Dosimetric characteristics of 6 and
10 MV unflattened photon beams. Radiother Oncol.
2009;93:141-146.
[5]D.W.O. Rogers, B. Walters, I. Kawrakow. BEAMnrc Users
Manual. NRCC Report PIRS-509 (A) revK. 2009.
[6]B. Walters, I. Kawrakow, D.W.O. Rogers. DOSXYZnrc
Users Manual. NRCC Report PIRS-794 revB, 2009.
[7]Daryoush Sheikh-Bagheri, D. W. O. Rogers. Sensitivity of
megavoltage photon beam Monte Carlo simulations toelectron beam and other parameters. Med. Phys.
2002;29:379-390.
[8]C.-M. Ma, D.W.O. Rogers. BEAMDP Users Manual. NRCC
Report PIRS-0509 (C) revA. 2009.
Author address

E-Mail: matsunaga.takuma@h.mbox.nagoya-u.ac.jp

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ESTIMATION OF RADIATION DOSES FROM X-RAY CT
USING MONTE CARLO SIMULATION
Yuki Morishita 1), Shuji Koyama 1)
1) Department of Radiological Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan
2) Department of Radiological Technology, Nagoya University School of Health Sciences, Nagoya, Japan
Introduction
The purpose of this study is to calculate accurate
radiation dose in patient from CT examination using voxel
phantom. In the calculation, scanner-specific descriptions
that include filtration designs, an orbital overlap and theabsorption of CT table are necessary. A special filter called“beam-shaping filter” which is positioned in front of the xray tube of the CT units causes less uniform x-ray fanbeam(Figure 1). We took into account the effect of the filter
based on measured data in this simulation.
A standard Japanese Model can be developed by using
the voxel phantom from CT DICOM(Digital Imaging andCommunication in Medicine) format data. In-phantom
dosimetry system, as will hereinafter be described in detail,was used to compare the measurements and the calculations.

sparsedence

sparseFig.1 Incident photon number at each beam angle
3. Specific factors related to the CT device

All simulations were performed using the EGS5
(Electron Gamma Shower ver.5) Monte Carlo code, which isa general purpose package for the Monte Carlo simulation of
the coupled transport of electrons and photons in an arbitrarygeometry for particles with energies above a few keV up to
several hundred GeV. For measurements and simulations, a
Non-helical X-ray CT unit TCT-300 (Toshiba Medical
Systems, Tochigi, JAPAN) was used in this study. The x-ray
tube voltage was 120kV.

There are several specific factors that are related to the CT
scanner. Non-helical CT scanner has x-ray tube orbital overlapthat cause the positions of the x-ray beam overlap on the patient.
The overlap angle was adjusted to match the measured CTDI
values in the simulation because the information of the actual
overlap angles wasn’t published by the manufacturer. A full of
x-ray tube rotation was estimated at 376 degrees including
overlap of -/+8 degrees.
The table top is usually made of carbon fiber due to its
strength and low x-ray attenuation properties. In this simulation,
the CT table was composed of density adjusted carbon. The
density of the carbon was adjusted to correspond with the actual
dose ratio table(+)/(-). These factors were also incorporated in
the simulation code.

2. Effect of beam-shaping filter

4. Measurement and calculation of CTDI

A typical CT scanner is equipped with x-ray beamfiltration that includes the beam-shaping filter. This filtration
modifies a number of x-ray beam properties (effective energy,
flux, first and second order statistics), making them nonuniform across the fan beam. The beam-shaping filter is used
to adjust the beam quality of x-rays after passing through apatient. There is no such published data on the design ofbeam-shaping filter, which may vary considerably fromscanner to scanner. We measured aluminum Half Value
Layer(AL HVL) and dose value after passing through thebeam-shaping filter and incorporated measured values in thesimulation. New type of semiconductor dosimeter called
Rapidose(Radcal, Monrovia, CA) was used for themeasurements. Rapidose has functions that can measure doseand AL HVL at the same time and it is suitable formeasurement of relatively high energy x-ray such as x-ray
CT. In the measurement of the effect of beam-shaping filter,
x-ray tube was fixed on the 0:00 position on its orbital.
Along a fan beam of x-ray CT, Rapidose was moved up to 19
degrees measured at every one degree. In the simulation,
photon number at each beam angle along the fan beam wasdetermined by dose profiles and energy spectrums weregenerated by Birch’s formula based on AL HVL measured
on each angle was used.

Computed Tomography Dose Index (CTDI) measured byusing a CT acrylic phantom was used for comparison between
the measurement and the calculation. The CTDI phantom is 15
cm in length with a diameter of 30 cm. CTDI values are shownin air kerma (kinetic energy released in matter ; mGy) in thephantom's center hole and four peripheral holes(0°,90°,180°,270°). In order to determine the air kerma from CT
examination, simulated deposit energies in units of
MeV/gram/source-particle were converted to air kerma in unitsof mGy by a conversion factor(Cf) [1]. An in-air normalization
method that is based on pencil-chamber exposure reading for asingle axial scan was taken at the isocenter of the CT gantry freein air. The conversion factor was defined as

Materials and Methods
1. Overview

Cf =(CTDI 100,air , measured per mAs )(CTDI 100,air , simulated per particle)(1)

where CTDI100, air , measured per mAs is measured by an ion chamber
free in air of the x-ray CT isocenter, and CTDI100, air , simulated perparticle is obtained by simulation.
The absorbed dose Dab is calculated by
Dab = Dsim× Cf(2)

where Dsim is the calculated dose in the simulation.

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value, those of CTU-41 phantom were converted from
deposited energy for each of whole organ by simulation.
Calculated dose of the organ in the scan area such as lung wasapproximately equal to measurement dose, but the organ dose ofproximity to the end of scan area such as thyroid resulted insignificantly different from measured dose. In the calculation,
the deposited energy in whole organ was divided by the organ
mass and this value was presented as an average organ dose.
When the organ was partially irradiated in the end of the scanarea, average organ dose was smaller than the whole-organ
irradiated case. In the measurement, the organ dose waspresented maximum value as is the case in whole-organ
irradiation if the evaluated point as a centroid of the organ fellwithin the scan area.

5. Development of voxel phantom

1.2

80

(a)

1

(b)

75

effective energy

relative photon number

Two different types of voxel phantoms were developed
based on CT image. One of them(THRA-1, Kyoto Kagaku
Co., Kyoto, JAPAN) is only composed of lung, bone and soft
tissue but can obtain organ doses using a number of internal
semiconductor dosimeter installed at the position of tissues
and organs [2]. The semiconductor dosimeter is implanted in
the centroid of the organ and tissue. This system is called“in-phantom dosimetry system” and was used to compare
measurements and calculations.
Measurements andcalculations were perfomed on thoracic scan protocol. The
resolution of the axial simulation matrix was decreased from512 × 512 to 170 × 170 to decrease runtime of the simulation.
The size of each voxel was 0.1875×0.1875×1.0 cm3.
Another phantom called CTU-41(Kyoto Kagaku Co.,
Kyoto, JAPAN) includes the shapes of organs withindividual densities. The average radiation dose to eachorgan was estimated in CTU-41 phantom. Both “in-phantom
dosimetry system” and CTU-41 phantom were scanned by xray CT, and image data was output as DICOM format. The
organs and tissues were assigned in each voxels using digitalvalue(Hounsfield Unit).

0.8
0.6
0.4
0.2

70
65
60
55

50
45

0

-18 -15 -12 -9 -6 -3 0

-18 -15 -12 -9 -6 -3 0 3 6 9 12 15 18
beam angle

1. Effects of the beam-shaping filter

measurement
[mGy]
21.0
11.7
16.6
16.0
14.8

Absorbed dose[mGy]

(a)

40
35
30
25
20
15
10
5
0

in-phantom dosimetry system(measurement)
in-phantom dosimetry system(calculation)

Thymus Lung Liver Breast Heartsimulation
[mGy]
20.8
11.5
16.5
16.5
14.5

difference
[%]
-1.2
-1.4
-0.4
2.8
-2.4

(b)

CTU-41 simulation(calculation)

35

In-phantom dosimetry system(measurement)

Absorbed dose[mGy]position of thedosimeter
top
centerleft
rightbottom

30
25
20

15
10

5
0

Point of the dosimeterFig.3 Comparison of measurement and calculation(a) point dose evaluation with same phantom (b)whole organdose versus point dose

3. The result of calculation using voxel phantom
The result of the comparison of measurement andcalculation of the in-phantom dosimetry system is shown in
Figure 3(a). Locations of the calculation point were accordedwith that of semiconductor dosimeters in the phantom.
Measurement and calculation shown the same tendency on
the same location in the phantom, but calculated values weregenerally slightly greater than measured values.
Figure 3(b) shows comparison of the organ doses
between in-phantom dosimetry system and CTU-41 phantom.
Dose values of in-phantom dosimetry system were measured

9 12 15 18

Table 1 Comparison of measurements andcalculations of the CTDI.

Figure 2 shows the dose distributions and energy changes
along the beam angle. The effective energy of x-ray beam
determined using the measured AL HVL. Relative dose value
maintained the same level from 0 degree to ±4 degree, andafter that it rapidly decreased as the angle became bigger.
Similarly, effective energy maintained up to ±4 degree, andthen it rapidly increased as the angle became bigger and was
saturated up from ±9 degrees. The cause of the effect wasthat the thickness of the filter was bigger as the beam angle
was bigger.

Table 1 shows comparison of measurements andcalculations of the CTDI.
The agreement between
measurements and calculations was within 2.8 %. The CTDI
at 0° position was highest due to x-ray tube orbital overlap
and lowest at 180° position due to absorption of the CTtable. The simulated CTDI values were approximately equal
to measured CTDI values. With this result, the x-ray source
and the geometry of x-ray CT could be incorporated in thesimulation successfully.

6

Fig.2 Relative dose and effective energy measured by
Rapidose at each beam angle. (a)The relative dose at eachbeam angle. (b)The effective energy calculated bymeasured Half Value Layer at each beam angle.

Results and Discussions

2. Comparison of CTDI between measurements andcalculations

3

beam angle

References[1]J Gu et al , The development, validation and application of amulti-detector CT(MDCT) scanner model for assessing organ
doses to the pregnant and the fetus using Monte Carlosimulations, Physics in medicine and biology[2] Radiation dose evaluation in 64-slice CT examinations withadult and paediatric anthropomorphic phantoms
Author address

E-Mail: morishita.yuki@e.mbox.nagoya-u.ac.jp

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EVALUATION OF THE DISTRIBUTION OF INTRACRANIAL NAVIGATION ACCURACY
IN IMAGE-GUIDED NEUROSURGERY
Takashi Mitsui1), Masatoshi Tsuzaka2), Yuichiro Hayashi3), Yoshinori Asahina1),
Kentaro Sugiura1), Masazumi Fujii3), Toshihiko Wakabayashi3)
１）Department of Radiological Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan２）Department of Radiological Technology, Nagoya University School of Health Sciences, Nagoya, Japan３）Department of Neurosurgery, Nagoya University Graduate School of Medicine, Nagoya, Japan
Introduction
NagoyaUniversity
Hospitalhas
introducedaneuronavigation system for accurate resection of malignant
brain tumors. Surgeons can confirm the positional
relationship between tumors and normal tissue by using thissystem. Especially, this system is very useful in the resectionof tumors located near the functional areas.
Accuracy of a neuronavigation system is very important toensure a safe and accurate resection [1]. Various factors
influence the navigation accuracy [2]; one of the importantfactors is the configuration of the fiducial markers that are
positioned on the patient's head. A fiducial marker is thereference point of the navigation system (Fig. 1). The
configuration of fiducial markers varies among institutions,and it can influence intracranial navigation accuracy. In thisstudy, we investigated the effect of the configuration of
fiducial markers on the distribution of intracranial navigation
accuracy.

using 27 fiducial markers positioned inside the phantom (Fig. 3).
The phantom was filled with nickel chloride, and magnetic
resonance images were acquired. MR imaging was performed
with 0.4T MRI (APERTO Inspire; Hitachi Medical Co., Chiba,
Japan). MR images were transferred to a planning system fornavigation (iPLAN cranial; BrainLAB AG, Heimstetten,
Germany), and registration points were set up on each fiducial
marker positioned surface of the phantom. Registration is
performed before surgery and is the process of integrating
image-space coordinates with real-space coordinates. The stepsof registration are as follows: (1) The operator registers thecenter of the fiducial markers as registration points by using the
iPLAN software. (2) Registration is completed by pointing thecenter of each fiducial marker by using a navigation pointer.
After registration was carried out using a navigation system(VectorVision Compact; BrainLAB AG), intracranial
navigation accuracy was measured.

Fig. 1 Fiducial marker (doughnut shape)
A fiducial marker is used as a reference point of thenavigation. They are positioned on the patient's head before
surgical operation.

Fig. 2 Skull-shaped phantom with fiducial markers
For the scattered configuration, the fiducial markers wereplaced on the forehead, temple, and mastoid regions (left). For
the clustered configuration, the fiducial markers were placed on
the frontal, temporal, and occipital bones (right).

Materials and Methods
We evaluated intracranial navigation accuracy for 2 different
configurations of fiducial markers (the clustered andscattered patterns) by using a skull-shaped phantom (Fig. 2).
Because this phantom structurally resembles the human head,intracranial navigation accuracy can be measured in keepingwith the clinical situation. We also measured the navigation
accuracy by varying the number of fiducial markers. We set
4, 5, or 6 markers on the surface of the phantom for eachconfiguration. In the clustered configuration, the markers
were placed on the frontal, temporal, and occipital bones. In
the scattered pattern, they were placed on the forehead,
temple, and mastoid regions, same as Nagoya University
Hospital's method. To measure the navigation accuracy,
fiducial markers were positioned on the bottom of thephantom. And to measure the navigation accuracy on thecentral portion of the phantom, 5 columns and 2 circularplates were constructed inside the phantom. We caninvestigate the distribution of the navigation accuracy by

Fig. 3 Measurement point of the phantom
We can investigate the navigation accuracy by using 27 fiducial
markers positioned inside the phantom. Eight fiducial markers

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were positioned on each circular plate. Also, 4, 2, and 5
fiducial markers were positioned on the anterior, middle,
posterior cranial fossa respectively.
Results
The mean intracranial navigation accuracy for the clusteredpattern with markers placed on the frontal bone was 2.13 ±1.15 mm with 4 markers, 1.92 ± 1.28 mm with 5 markers,
and 2.01 ± 1.02 mm with 6 markers. The mean intracranial
navigation accuracy for the scattered pattern was 1.51 ± 0.88mm with 4 markers, 1.68 ± 0.75 mm with 5 markers, and1.24 ± 0.37 mm with 6 markers (Table 1). The scatteredpatterns were significantly better than the clustered pattern (p< 0.05). We calculated the navigation accuracy on the central
portion of the phantom and bottom of the phantom separately(Table 2). The accuracy for the clustered pattern with 6
markers was 1.60 ± 0.53 mm on the central portion and 2.59
± 1.26 mm on the bottom of the phantom (p < 0.05). The
clustered pattern could maintain the accuracy only within anarrow region near the fiducial markers positioned on thesurface of the phantom. In addition, the clustered patterns
with markers positioned on the temporal and occipital bones
indicated a similar tendency. However, the accuracy for the
scattered pattern with 6 markers was 1.17 ± 0.37 mm on thecentral portion and 1.37 ± 0.35 mm on the bottom of thephantom, and there was no significant difference. Thus, thescattered pattern could maintain the accuracy over a wide
region of the phantom.
Table 1 Intracranial navigation accuracy

Discussion
The configuration of the fiducial markers varies among
institutions and it influence the distribution of the navigation
accuracy. It is difficult to measure intracranial navigation
accuracy in clinical practice [1]. Therefore, we evaluated theeffect of the configuration of the markers on the navigation
accuracy by using a skull-shaped phantom. Because thisphantom structurally resembles the human head, intracranial
navigation accuracy can be measured in keeping with theclinical situation.
The clustered pattern, regardless of the installation location,
could maintain the navigation accuracy only within the narrow
region near the fiducial markers. The navigation accuracy
decreased with an increase in the distance from the fiducial
markers positioned on the surface of the phantom. However, thescattered pattern showed high accuracy on the entire phantom,
with two exceptions: the scattered pattern with 4 and 5 markers
could not maintain high accuracy on the bottom of the phantom
because fiducial markers positioned on the mastoid were notused. To maintain a high accuracy on the entire phantom, it isnecessary to position the fiducial markers across a wide area on
the head. If a tumor exists on the base of skull or if the tumor ishuge, the scattered configuration is appropriate for safe surgery.
Conclusions
In this study, we evaluated the effect of the configuration of thefiducial markers on the distribution of the navigation accuracy
by using a skull-shaped phantom. It is important to position thefiducial markers across a wide area on the head for accurate
resection of the tumor.
References[1] Fitzpatrick JM, West JB, Maurer CR Jr : Predicting Error in
Rigid-Body Point-Based Registration, IEEE Trans Med
Imaging, 17(5), 694-702, 1998.
[2] Steinmeier R, Rachinger J, Kaus M, Ganslandt O, Huk W,
Fahlbusch R. : Factors Influencing the Application Accuracy of
Neuronavigation System. Stereotact Funct Neurosurg, 75:188202, 2000.

Table 2 Navigation accuracy on the central and bottom of
the phantom

Author address
E-Mail: mitsui.takashi@e.mbox.nagoya-u.ac.jp

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