Construction and verification of a physical chest phantom from suitable tissue equivalent materials for computed tomography examinations

Author’s Accepted Manuscript Construction and verification of a physical chest phantom from suitable tissue equivalent materials for computed tomography examinations Iman Amini, Parisa Akhlaghi, Parvin Sarbakhsh www.elsevier.com/locate/radphyschem

PII: DOI: Reference:

S0969-806X(17)30743-0 https://doi.org/10.1016/j.radphyschem.2018.04.020 RPC7827

To appear in: Radiation Physics and Chemistry Received date: 25 July 2017 Revised date: 16 April 2018 Accepted date: 18 April 2018 Cite this article as: Iman Amini, Parisa Akhlaghi and Parvin Sarbakhsh, Construction and verification of a physical chest phantom from suitable tissue equivalent materials for computed tomography examinations, Radiation Physics and Chemistry, https://doi.org/10.1016/j.radphyschem.2018.04.020 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Construction and verification of a physical chest phantom from suitable tissue equivalent materials for computed tomography examinations Iman Amini1,2,3, Parisa Akhlaghi1,2*, Parvin Sarbakhsh4 1

Immunology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran

2

Department of Medical Physics, School of Medicine, Tabriz University of Medical

Sciences, Tabriz, Iran 3

Students’ Research Committee, Tabriz University of Medical Sciences, Tabriz, Iran

4

Department of Biostatistics and Epidemiology, School of Public Health, Tabriz University

of Medical Sciences, Tabriz, Iran

* Corresponding Author: Parisa Akhlaghi Department of Medical Physics, School of Medicine, Tabriz University of Medical Sciences, Golgasht Av., Tabriz, Iran. Tel-Fax: 98-41-33364660. Email address of corresponding author: [email protected] Email address of first author: [email protected] Email address of third author: [email protected]

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Construction and verification of a physical chest phantom from suitable tissue equivalent materials for computed tomography examinations

Abstract Physical phantoms are used to optimize various imaging modalities (e.g. computed tomography) in terms of X-ray image quality and absorbed dose. In this regard, this study tried to design and construct a suitable physical phantom with high accuracy and low price in diagnostic energy range. The phantom geometry was selected to be similar to a 5 cm thick cross-sectional slice of an adult human chest. To choose the appropriate tissue-equivalent materials, the physical properties (mass density, electron density and effective atomic number) of a wide range of available polymers were discussed and their accordance with those

of

human

tissues

were

investigated.

Phantom

body

was

made

of

polymethylmethacrylate and 17 holes were considered in the phantom for placement of different tissue-equivalent materials. According to the physical properties, polypropylene, polyethylene,

acrylonitrile

butadiene

styrene,

polyurethane,

polyamide

and

polyoxymethylene were selected and prepared for replacement of adipose, breasts, muscle, liver, cartilage and ribs, respectively. In addition, two different polyurethane foams were made of their raw materials for replacement of the lungs in inhalation and exhalation modes. Then, the prepared phantom was scanned by Siemens somatom sensation 64-slice scanner at tube voltage of 120 kVp and Hounsfield units of tissue-equivalent materials were measured. In addition, using theoretical relationships and goodness of fit test, their Hounsfield units were calculated. It was observed that, the calculated values were able to predict the measured values with the accuracy of 99%. Finally, the Hounsfield units of real human tissues were determined by the mathematical relationship obtained in the previous step; and in order to verify the outcomes, they were compared with other published reports. It was found that the

1

Hounsfield units of real human tissues obtained using this physical phantom and Gammex RMI 465 phantom (scanned by Siemens somatom sensation 64) had the least differences. This demonstrated the high precision of the phantom and selected tissue substitutes, so it could be used in diagnostic energy range.

Keywords: Physical chest phantom; Tissue equivalent materials; Hounsfield unit; Effective atomic number; Electron density

1. Introduction A wide variety of anthropomorphic physical phantoms constructed from tissue-equivalent materials have been developed for radiation dosimetry studies, quality assurance of medical imaging devices and radiotherapy treatment planning systems (Hintenlang et al., 2010). The main purpose of constructing these phantoms is to model the human body as precis as possible, so one can study the radiation interactions with biological tissues of the body more accurately (Fisher, 2006). The most important principle in designing a high precision physical phantom is selection of equivalent materials, which closely match with original body tissues in terms of physical properties and chemical composition (Bower, 1997). Thus, the interactions of beam and therefore the amount of absorbed dose in each organ/region of phantom will be consistent with the related organ/region of the human body; and the similar image and dose will be achieved (Fisher, 2006). The second important principle, is the similarity of the external and internal geometry of the phantom to those of real human organ/region of interest. The attenuation properties of overlaying tissues and the depth of organs from body surface (i.e. organ location) significantly influence dose, so more compliance in these two factors leads to the similar X-ray spectrum hardening and therefore dose estimation (Akhlaghi et al., 2015a). So far, many companies and individuals around the

2

world fabricated the physical phantoms for different purposes. The most important goal that each designer follows is to make a phantom with high precision for the desired radiation activities (Constantinou et al., 1992; Vassileva, 2002; Winslow et al., 2009). In some of physical phantoms, because of its low cost and similarity to soft tissues of human body in terms of physical properties, water was used for dosimetry applications (Hill et al., 2014). For many years, tissue equivalent materials were constructed based on the combination of epoxy resin and another molecular composition for achieving the considered physical property; but as reported, it was hard to work with (Hintenlang et al., 2010). A wide variety of physical phantoms used for radiation activities, only simulate a specific area of the human body with a very simple anatomy (Xu, 2014). An example of this type of phantom is CIRS model 062 phantom, which models the chest and head of the human body, and contains 17 holes for the placement of different tissue substitutes. Two commercially available phantoms used for most dosimetry activities in diagnostic imaging are RANDO and ATOM, however due to their high costs most centers do not have access to them (Winslow et al., 2009). RANDO and its new generation named ART were designed and constructed by Alderson Research Laboratories, USA (http://www.rsdphantoms.com) and ATOM family was developed by Computerized Imaging Reference Systems (CIRS), Inc., USA (http://www.cirsinc.com). Both phantoms contain tissue equivalent materials for replacing lungs, soft tissue, breasts, and bones (Xu, 2014). Given the mentioned limitations, designing and constructing a physical phantom with low cost and high accuracy in diagnostic energy range for dosimetry, calibration and quality control purposes is a desirable choice. In this regard, the aim of this research was to design and construct a physical phantom, which had the similar geometry to the adult normal chest, and also contained tissue-equivalent materials with greatest accordance to the body's real tissues in terms of physical properties (such as density, electron density and effective atomic number). In addition, it was tried to

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construct phantom with more reasonable cost than the other available physical phantoms; so that it could be prepared and used easily by all imaging centers. To check the accuracy of constructed phantom in diagnostic energy range, it was scanned under computed tomography (CT) imaging, and the CT number of each tissue-equivalent material was measured and compared with the CT number calculated using theoretical equations of total attenuation coefficients (Schneider et al., 1996). For a more detailed study, the CT numbers of real human tissues were also determined and compared with those reported in the literature.

2. Materials and Methods 2.1 Phantom geometry In present study, an elliptic cylindrical phantom similar to CIRS phantom model 062 (CIRS Tissue Simulation Technology, Norfolk, VA) with small diameter of 27 cm, large diameter of 33 cm and a thickness of 5 cm (Fig. 1) was designed and constructed. This phantom is physically very close to a 5 cm slice of a normal adult chest. A total of 17 holes were embedded in the phantom body to place various tissue-equivalent materials. The diameter of 3 cm was considered for each hole.

2.2 Tissue-equivalent materials Considering the availability of polymer materials as tissue substitutes, in the process of selecting tissue-equivalent materials, it was tried to select materials with physical properties (mass density, electron density and effective atomic number) as close as those of real human tissues.

4

Fig. 1. The geometry of physical chest phantom.

In some of physical phantoms used for dosimetry purposes, one tissue-equivalent material (like water, which has close physical properties to human soft tissues) was considered (Winslow et al., 2009; Hill et al., 2014; Aburjaile et al., 2017). In this study, in order to increase accuracy, different soft tissue equivalent materials were selected as substitutes for real human soft tissues locate in the chest region (e.g. adipose, breasts, muscle, and liver). Also, according to the bones found in the chest region of an adult, a tissue substitute was considered for ribs 2 to 6 in the phantom. As known, in CT diagnostic process, the patients hold their breath during the exposure, so in most phantoms, an average of inhalation and exhalation modes of lung tissue is considered for replacement (Winslow et al., 2009). In the present project, to increase the accuracy, the lung tissue in both inhale and exhale modes was designed and constructed.

2.3 Physical properties of tissue-equivalent materials 5

Tissue-equivalent materials must have physical properties similar to real tissues in the body, so they would have the proper response in diagnostic energy range. The physical properties, which should be investigated in photonic studies are mass density, electron density, effective atomic number, and CT numbers (it represents the mass attenuation coefficient in each pixel of CT image).

2.3.1 Electron density and effective atomic number Relative electron density (number of electrons per gram) of each material was calculated from:

(1) where

is mass density (in gram per unit volume) and

is the number of electrons per unit

volume of material and was calculated by (Schneider et al., 1996): ∑ (2) where

is Avogadro's number,

,

and

are elemental weight fraction, atomic number

and atomic mass of each element, respectively. Effective atomic number for each material was obtained from the following relationship (Chang et al., 2012): ∑ ∑

(3)

6

Table 1 shows the physical properties of the real tissues locate in the chest region and those of suggested tissue-equivalent materials available in the literature. These data were rounded to two decimal places.

Table 1. Physical properties of human real tissues taken from Schneider et al. (1996) and ICRP publication 110 (ICRP, 2009) together with those of tissue substitutes taken from literature. ⁄

Material

⁄

Lung tissue (inflated) (Schneider et al,. 1996)

0.26

0.26

3.38

Cork (Chang et al., 2012)

0.27

0.26

3.52

Polyurethane foam (Kim et al., 2006)

0.28

0.27

3.43

White suggested lung tissue (White, 1978)

0.32

0.30

4.01

Adipose tissue (ICRP, 2009)

0.93

0.93

3.00

Polypropylene (ICRU, 1989)

0.90

0.92

2.66

Ethylene bis stearamide (Akhlaghi et al., 2015b)

0.90

0.91

2.83

Paraffin wax (ICRU, 1989)

0.93

0.96

2.60

Brest tissue (ICRP, 2009)

0.99

0.98

3.15

Polyethylene (ICRU, 1989)

0.96

0.99

2.66

White suggested soft tissue (White, 1978)

1.00

0.99

3.41

Water (Pallotta et al., 2007)

1.00

1.00

3.33

Solid water (ICRU, 1989)

1.02

0.99

7.80

Muscle tissue (Schneider et al,. 1996)

1.05

1.04

3.39

Polystyrene (ICRU, 1989)

1.05

1.02

3.50

Acrylonitrile butadiene styrene (Kumar et al., 2010)

1.03

1.00

3.44

Liver tissue (Schneider et al,. 1996)

1.06

1.05

3.39

Polyurethane (Kim et al., 2006)

1.08

1.06

3.39

Cartilage (Schneider et al,. 1996)

1.10

1.08

3.52

Polyamide (ICRU, 1989)

1.13

1.11

3.25

A-150 (Shonka, 1958)

1.13

1.12

3.18

Skeleton-ribs (2nd,6th) (Schneider et al,. 1996)

1.41

1.35

4.23

7

Polyvinylchloride (Akhlaghi et al., 2015b)

1.36

1.26

5.33

Polyoxymethylene (Jose et al., 2012)

1.42

1.36

3.99

B-100 (Shonka, 1958)

1.45

1.38

4.16

Teflon (ICRU, 1989)

2.10

1.82

8.00

Due to the wide range of suggested materials as tissue substitutes (Table 1), the process of selecting tissue-equivalent materials should be based on their physical properties, availability, and prices. Among the available polymers, polypropylene, polyethylene, polyurethane, acrylonitrile butadiene styrene, polyamide and polyoxymethylene were considered to replace the adipose, breasts, liver, muscle, cartilage and ribs 2 to 6 tissues, respectively. On the other hand, to consider lung tissue in both inhale and exhale modes, polyurethane foam was constructed out of its raw materials with two different mass densities. This means that different amounts of polyol and isocyanate were combined to achieve the desired density. Next, considering the fact that polyol and isocyanate contain oxygen, hydrogen, nitrogen and carbon, elemental analysis for CHNO elements was performed to obtain the percentage of each element. The properties of these materials are given in Table 2. It should be mentioned that following properties of polymethylmethacrylate (PMMA) make it a proper option as tissue substitute in phantom body: 1. Closeness of its mass density (1.18 g/cm3) to the average density (of all bones, lungs and soft tissues) of the adult human body (1.16 g/cm3). 2. High resistance of this material against bumps and scratches that results in less beam scattering. 3. The availability of pure samples (96%), which leads to more accurate results. 4. Easy handling of this material, when it is used for dosimetry application (Mann et al., 2012; Shope et al., 1981).

8

Table 2. Chemical composition, weight fraction in percent and physical properties of selected tissues substitutes. Equivalent material

H1

C6

N7

O8

⁄

Polypropylene

14.37

85.63

-

-

0.90

0.93

Polyethylene

14.37

85.63

-

-

0.96

0.99

Water

11.19

-

-

88.81

1.00

1.00

Acrylonitrile butadiene styrene

8.11

85.26

6.63

-

1.03

1.01

Polyurethane

9.07

64.35

6.00

20.57

1.08

1.06

Polyurethane foam (inhale mode)

6.94

67.27

8.31

17.00

0.24

0.23

Polyurethane foam (exhale mode)

6.94

67.27

8.31

17.00

0.33

0.32

Polyamide

9.80

63.69

12.38

14.14

1.13

1.12

Polyoxymethylene

6.71

40.00

-

53.28

1.42

1.36

PMMA

8.05

59.98

-

31.96

1.18

1.15

⁄

Finally, to insert the materials in their locations, water was poured in the central hole, and caps made of PMMA were used on both sides of the hole to prevent water spillage. Then, mentioned tissue-equivalent materials were located in the other 16 holes in the phantom body. It should be mentioned that, both of the left and right lungs in inhale and exhale modes were considered in the phantom separately (four different locations). Fig. 2 displays the arrangement of tissue-equivalent material in the phantom. To avoid the air gap, tissue-equivalent materials were placed inside the phantom body by the press machine. It is possible to reduce the costs of this process by fitting the materials manually using a hammer. 9

Fig. 2. Arrangement of tissue-equivalent materials inserted in the phantom body.

2.3.2 Measuring the CT numbers The CT numbers, known as Hounsfield Unit (HU) values, were measured in the constructed phantom using a Siemens somatom sensation 64-slice CT scanner (Siemens Medical Systems, Erlangen, Germany) operated at a tube voltage of 120 kVp and tube loading of 200 mAs. The field of view diameter and pixel size was 382 mm and 0.746 mm, respectively. Moreover, the slice thickness of 1 mm was considered for all scans. The average HU of each tissue-equivalent material was determined in the selected regions of interest (ROI) with areas of approximately 3 cm2. The average HU in each ROI was measured by eFilm Lite software (Merge Technologies; Milwaukee, WI, USA). eFilm Lite is an application used for viewing and manipulating digital images from various sources (including CT scan). Using this software, users can display, analyze, process, and store digital

10

images (Merge Technologies Inc., 2005). Given that two locations were assigned for each material, the average HU of these two sites was considered as final HU of that material.

2.3.3 Calculating the CT numbers HU value was obtained from the following equation:

(

where

)

(4)

is linear attenuation coefficient and

is the linear attenuation coefficient of

water. The total linear attenuation coefficient of photon in diagnostic energy range passing through a certain thickness of the material could be written in the following form (Jackson et al., 1981): (

)

(5) where

is electron density, and

,

and

are the cross sections of photoelectric

effect, coherent scattering and non-coherent scattering, respectively. For a material contained a combination of various elements, attenuation coefficient was calculated using the following equation (Rutherford et al., 1976; Schneider et al., 2000; Yohannes et al., 2012): ̅

∑

where photon

̅

(

and

̅

̅

)

are constant coefficients and are related to photon absorption and

scattering cross-section, respectively.

coefficient.

,

(6)

and

is Klein-Nishina

cross-section

are elemental weight, atomic number and mass number of each

element, respectively. The exponents m and n in equation 6 depend on photon energy and composition of the mixture and are determined by fitting cross section data over an energy 11

range (Jackson et al., 1981). In diagnostic energy range and for real human tissues the values of m and n were estimated 2.86 and 4.62, respectively (Rutherford et al., 1976). So, in another form, equation 6 could be written as: ∑ ̅

̅

(

(

̅

̅

̅

̅

To simplify, we considered the ratio of

̅ ̅

))

(7)

as constant k1 and the ratio of

̅

as constant

̅

k2. Since k1 and k2 represent photonic cross sections, they depend on the spectra of CT scanner and are determined empirically by a linear regression fit. According to these two constants, equation 7 was converted to: ∑ ̅

̅

(

)

(8)

Considering equation 4, to obtain HU of any arbitrary material, the relative attenuation coefficient of that material ( ̅

̅

) should be defined. Therefore, using equation 8 and

elemental composition of water (H2O), the relative attenuation coefficient of each material was obtained as below: ∑

̅

⁄

⁄

̅

⁄

(9)

If

and

are known, attenuation coefficient ( ̅ ) and therefore

̅ ̅

, for each material with

specified chemical composition can be easily calculated (Schneider et al., 2000). We were seeking for the values of )

and

for which, the calculated CT numbers ((

̅

) had the smallest differences with measured CT numbers i.e. HU (meas.). In this

regard, the values of

and

were determined by carrying out a goodness of fitness test 12

with least squares method, so that ∑

(̅

̅

)

(

)

was

minimized. In this relation n varied from 1 to 10, which illustrated the number of tissue equivalent materials considered in the physical phantom. It could be said that, using linear least square method by R statistical software package (R Development Core Team, available at: https://www.r-project.org), together with the relative attenuation coefficients and measured HUs of those ten tissue substitutes, the

and

values for the best fitting straight

line through a set of points were obtained. Finally, by combining equation (9) and equation (4), the CT number of each material with a certain chemical composition was calculated at the mentioned radiation exposure condition. This means that a general and specific relationship was specified for this CT machine to calculate the CT numbers of each material with certain chemical composition before scanning at different tube voltages.

2.4 CT numbers of human tissues To investigate the validity of the constructed phantom in diagnostic X-ray energy range, HU values of 20 real human tissues were also calculated and compared with those reported in literature. For this reason, the physical and chemical data of human tissues were used to obtain electron densities and effective atomic numbers (Schneider et al., 1996; Yohannes et al., 2012). Finally, applying k1 and k2 values from previous step and equations 4 and 9, the HU values of these tissues were acquired. In order to compare the results, six different investigations on CT scanner calibration by physical phantoms were also studied. Considering the fact that k1 and k2 depend on the CT machine, HUs of real human tissues were also obtained from these studies by their own reported values. Table 3 contains the type of scanner, physical phantom, and k1/k2 values of six different researches.

13

2.5 Statistical analysis In all the measurements, dispersion of the data from their mean value was expressed by standard deviation (SD). To investigate the linearity of the relationship existed between the calculated and measured CT numbers, R-squared test was performed, which determined how close the data locate to the fitted regression line. On the other words, by this criterion the similarity of the measured and calculated CT numbers was studied. Moreover, in order to determine the significance of the results P-value less than 0.05 was checked.

Table 3. Studies used physical phantom for CT scanner calibration at tube voltage of 120 kVp. Reference

CT scanner

Phantom

k1

k2

(Schneider et al., 1996)

GE 9000

6 different phantom materials

8.57×10-5

2.45×10-4

(Schneider et al., 2000)

Siemens SOMATOM plus 4

16 different phantom materials

1.24×10-3

3.06×10-5

(Vanderstraeten et al., 2007)

Siemens SOMATOM Sensation 64

Gammex RMI 465

-2.84 × 10-4

2.65 × 10-5

(Yang et al., 2008)

GE 9000

Gammex RMI 467

8.56×10-4

2.45×10-5

(Yohannes et al., 2011)

Siemens SOMATOM Definition Flash

6 equivalent materials located in 100 mm water phantom

3.67×10-5

1.31×10-3

(Shih and Wu, 2017)

GE light speed 16

Gammex RMI 467

-5.74×10-4

3.16×10-5

3. Results Determination of CT numbers Fig. 3 shows the final form of the constructed phantom used for CT imaging. Moreover, one of the CT images along with the average HU and SD at four different ROIs are displayed in Fig. 4.

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Table 4 contains the measured CT numbers of each material scanned at tube voltage of 120 kVp. Moreover, using the mentioned theoretical equations, and

and

values were determined

, respectively.

Fig. 3. The elliptical physical chest phantom with ten different tissue equivalent materials constructed for diagnostic imaging.

15

Fig. 4. A view of selecting ROIs and determining the average HU.

Since, at higher energies (80-120 keV) the attenuation coefficient of scattering is almost 100 times greater than that of photoelectric absorption (Korea Atomic Energy Research Institute, 2018), and the contribution of scattering in the image formation is higher relative to photoelectric absorption (Akhlaghi et al., 2015b), this discrepancy between the values of (constant of scattering) and

(constant of absorption) seems logical.

Table 4. CT numbers of the tissue substitutes in 17 locations of the phantom. Measured HU values were obtained at tube voltage of 120 kVp and the calculated values were determined by means of equation 9 using k1=

Tissue substitutes

Polyurethane foam (inhale mode) Polyurethane foam

and k2=

Measured HU

.

Calculated HU

(Mean ± SD)

Difference in mean HU (ΔHU)

-747.5 ± 35.3

-774.0

26.5

-702.0 ± 35.9

-689.5

12.5

(exhale mode) 16

Water

-2.0 ± 50.7

0.0

2.0

Polypropylene

-90.0 ± 39.7

-101.0

11.0

Polyethylene

-65.4 ± 36.8

-41.0

24.4

Acrylonitrile butadiene

-19.5 ± 39.7

-17.5

2.0

styrene Polyurethane

81.0 ± 43.6

45.0

36.0

Polyamide

92.0 ± 33.7

94.0

2.0

PMMA

126.0 ± 41.2

126.6

0.6

Polyoxymethylene

334.0 ± 36.9

353.0

19.0

The HUs of real human tissues, and also their differences with other published values are tabulated in Table 5.

Table 5. HUs of 20 real human tissues, and the differences in calculated HUs of this study and six other investigations. Difference between calculated HUs of this study and:

AbdomenPelvis

Chest

Scan region

Real tissue

HUs (This study) Schneider et al (1996)

Schneider et al (2000)

Vanderstraeten et al (2007)

Yang et al (2008)

Yohannes et al (2011)

Shih and Wu (2016)

Lung (inflated)

-741.87

0.43

0.66

0.50

0.42

0.07

0.74

Adipose

-65.06

5.19

1.90

4.04

5.16

22.23

3.98

Breast

5.79

2.49

0.59

0.49

2.47

0.27

0.41

Muscle

40.68

1.62

2.87

2.82

1.62

1.61

3.61

Liver

59.67

8.43

7.25

5.34

8.43

11.43

8.43

Heart

52.69

2.54

4.01

3.54

2.53

0.71

4.63

Cartilage

92.03

6.27

7.50

4.45

6.23

7.24

6.30

Ribs (2nd,6th)

515.24

79.99

108.75

60.54

79.55

71.41

95.43

Skin

75.00

0.14

1.17

2.31

0.14

5.21

2.72

Kidney

41.59

1.49

2.65

2.59

1.49

1.48

3.33

Pancreas

32.08

0.32

1.57

2.35

0.32

4.07

2.84

Ovary

43.88

1.35

2.18

1.97

1.34

0.56

2.56

17

Head-Neck

Testis

34.42

1.10

1.96

1.92

1.10

1.12

2.47

Spleen

52.12

1.72

2.76

2.49

1.71

0.67

3.24

Vertebral (D6, L3)

417.90

58.82

82.86

44.57

58.47

48.84

73.02

Brain

35.27

1.81

3.21

3.15

1.80

1.83

4.05

Eye lens

51.02

0.87

0.07

1.34

0.87

0.96

1.51

Thyroid

66.26

7.61

16.06

7.37

7.55

8.19

18.27

Mandible

868.09

138.08

185.00

100.76

137.34

131.93

159.66

Cranium

773.60

129.32

171.88

76.30

128.65

122.57

149.43

4. Discussion Our previous preliminary study emphasized on selecting three tissue equivalent materials for lungs, bones and soft tissues based on theoretical method suggested in the literature for choosing best tissue substitutes in photonic exposures (Akhlaghi et al., 2015b). However, when it comes to experiment and phantom construction, besides the physical properties, the availability, price, and flexibility are other important factors. Therefore, in this study, a broader range of possible materials were investigated theoretically and ten different tissue substitutes were considered in the phantom as adipose, breasts, liver, muscle, cartilage, bones, lung in inhalation mode, lung in exhalation mode, averaged soft tissue and also water. It was tried to consider all the tissues located in the chest region, so it contained more details than a three-tissue phantom. Constructed physical phantom was equivalent to a 5 cm slice of an adult chest and its body was made of PMMA. Given the advantages of polymer materials over epoxy resins, they were used as tissue substitutes. For instance, the polymers used in this study are less viscous than epoxy resin tissue substitutes, so they are easier to work with. On the other hand, these polymeric materials are more pliable and strong when they are cured, while the epoxy resin tissue substitutes are brittle and can break under stress or drop. Due to more flexibility of

18

polymers, it is possible to cut a thin slit into these materials, so TLDs could be easily inserted for dosimetry activities (Winslow et al., 2009). The selection criteria for all available polymers was the suitability of their physical properties (i.e. mass density, electron density and effective atomic number) as tissue substitutes. In many phantom construction projects for each groups of soft tissues, bone tissues and lung tissue only one material was considered. However, in this study, polypropylene, polyethylene, polyurethane, acrylonitrile butadiene styrene and polyamide were considered in order to replace the adipose, breasts, liver, muscle and cartilage tissues, respectively. Also, for replacing bone tissues in this region (ribs), the polyoxymethylene was considered. Polyurethane foams with two different densities were used for replacement of lung tissue in inspiration and expiration modes. Given the data in table 4, a graph of calculated CT numbers compared to measured CT numbers is plotted in Fig. 5.

Fig. 5. A linear fit for plot of calculated HU versus measured HU.

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As observed in Fig.5, calculated values are able to predict the measured values with an accuracy of 99%. Since the calculated CT numbers from equation 9, have been obtained according to the chemical composition and physical properties of tissue-equivalent materials in the phantom, the high agreements between the measured and calculated CT numbers represents the accuracy in selection of tissue-equivalent materials. From Table 5, whereas the physical phantom of this study was constructed for chest specifically, on average, the differences in HUs for organs locate in this region were less than those in other regions. On the other hand, because most equivalent materials were soft tissue substitutes (only polyoxymethylene was considered as bone), so as expected, the phantom precision for soft tissues was higher. This point resulted in notable agreements also for soft tissues locate in abdomen-pelvis and head-neck regions. According to the reports of table, even for the same CT scanner, and physical phantom with similar tissue substitutes, HUs differed notably (Schneider et al., 1996; Yang et al., 2008). For the similar physical phantom, the discrepancy in HUs of six studies for each organ might be due to the differences in beam filtration, and beam-hardening corrections during image reconstruction (Cropp et al., 2013). CT scanner, phantom geometry and tissue substitutes of this research had the most similarity with those of Vanderstraeten et al. (2007), (in which standard and commercially available Gammex RMI 465 phantom was scanned by Siemens somatom sensation 64), and as observed the HU values of these two studies had the least differences. As stated, the accordance in HUs of two materials demonstrates their similar beam attenuation, and as the absorbed dose in an organ directly depends on total attenuation coefficient (Akhlaghi et al., 2015b), therefore, this phantom is applicable for calibration and dosimetry purposes in CT imaging especially for chest region. If a person or group decides to make a phantom with these specifications using mentioned tissue-equivalent materials, total cost of the project would be less than $1,000.

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5. Conclusion A physical phantom of adult chest region was designed and fabricated for dosimetry purposes. This phantom could be applied for radiotherapy treatment planning system by calibration of CT number to electron density of each organ. Phantom geometry had the most similarity to a 5 cm thick cross-sectional slice of adult human chest. Tissue-equivalent materials were chosen among the polymers based on their physical characteristics such as mass density, electron density and effective atomic number. Therefore, to replace tissues of adipose, breasts, liver, muscle, cartilage, lungs and ribs, polypropylene, polyethylene, polyurethane, acrylonitrile butadiene styrene, polyamide, polyurethane foams and polyoxymethylene were selected and prepared, respectively. Due to significant agreement between calculated and measured CT numbers of tissue substitutes, and also accordance of the constructed phantom with the Gammex 465 phantom in predicting the HUs of most tissues, high accuracy of the phantom and its tissue equivalent materials was proved. Thus, this low cost phantom could be used for calibration and dosimetric activities in diagnostic energy range.

Acknowledgments This research is financially supported by a research grant from the Immunology Research Center in Tabriz University of Medical Sciences, Tabriz, Iran (Grant #94/43). The authors wish to acknowledge Mr Yaghoob Khaleghifard the head radiologist of Iran Radiology Center

in

Tabriz

for

his

cooperation

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in

imaging

the

constructed

phantom.

References Aburjaile, W. N., Mourao, A. P., 2017. Development of a chest phantom for testing in Computed

Tomography

scans. Rad.

Phys.

Chem.

DOI:

10.1016/j.radphyschem.2017.01.031 Akhlaghi, P., Miri Hakimabad, H., Rafat Motavalli, L., 2015a. Evaluation of dose conversion coefficients for an eight-year-old Iranian male phantom undergoing computed tomography, Radiat. Environ. Biophys. 54: 465- 474 Akhlaghi, P., Miri Hakimabad, H., Rafat Motavalli, L., 2015b. Determination of tissue equivalent materials of a physical 8-year-old phantom for use in computed tomography, Rad. Phys. Chem. 112: 169-176. Bower, M.W., 1997. A Physical anthropomorphic phantom of a one-year-old child with realtime dosimetry (PhD thesis). University of Florida, FL, USA, pp. 1-225. Chang, K. P., Hung, S. H., Chie, Y. H., et al., 2012. A comparison of physical and dosimetric properties of lung substitute materials. Med. Phys. 39, 2013-2020. Constantinou, C., Harrington, J. C., DeWerd, L. A., 1992. An electron density calibration phantom for CT‐based treatment planning computers. Med. Phys. 19, 325-327. Cropp, R. J., Seslija, p., Tso, D., Thakur, Y., 2013. Scanner and kVp dependence of measured CT numbers in the ACR CT phantom. J. Appl. Clin. Med. Phys. 14, 338-349. Fisher, R. F., 2006. Tissue equivalent phantoms for evaluating in-plane tube current modulated CT dose and image quality (MS thesis). University of Florida, FL, USA, pp. 1-78. Hill, R., Healy, B., Holloway, L., Kuncic, Z., Thwaites, D., Baldock, C., 2014. Advances in kilovoltage x-ray beam dosimetry. Phys. Med. Biol. 59, 183-231.

22

Hintenlang, D. E., Moloney, W. E., Winslow, J., 2010. Physical phantoms for experimental radiation dosimetry. In: Xu, X. G., Eckerman, K. F. (Eds.), Handbook of anatomical models For radiation dosimetry. Taylor and Francis, NewYork, pp. 389-409. ICRP, 2009. ICRP Publication 110: Adult reference computational phantoms. Elsevier: International Commission on Radiological Protection, Amesterdam. ICRU, 1989. Report No. 44: Tissue substitutes in radiation dosimetry and measurement. International Commission on Radiation Units and Measurement, Bethesda. Jackson, D. F., Hawkes, D. J., 1981. X-ray attenuation coefficients of elements and mixtures. Phys. Rep. 70, 169-233. Jose, A. J., Alagar, M., 2012. Fabrication of bioactive polyoxymethylene nanocomposites for bone tissue replacement. Macromolecular Symposia 320, 24-37. Kim, J. I., Choi, H., Lee, B. I., et al., 2006. Physical phantom of typical Korean male for radiation protection purpose. Radiat. Prot. Dosim. 118, 131-136. Korea

Atomic

Energy

Research

Institute.

Nuclear

Data

Center.

〈http://atom.kaeri.re.kr:8080/cgi-bin/w3xcom〉 (accessed March 2018). Kumar, R., Sharma, S., Despande, S., et al., 2010. Acrylonitrile Butadiene Styrene (ABS) plastic-based low cost tissue equivalent phantom for verification dosimetry in IMRT. J. Appl. Clin. Med. Phys. 11, 24-32. Mann, K. S., Kurudirek, M., Sidhu, G., 2012. Verification of dosimetric materials to be used as tissue-substitutes in radiological diagnosis. Appl. Radiat. and Isot. 70, 681-691. Merge

Technologies

Inc.

eFilm

Lite

User

Guide,

〈https://estore.merge.com/na/resources/eFilmLite%20UserGuide.pdf〉 March 2018).

23

2005. (accessed

Pallotta, S., Marrazzo, L., Bucciolini, M., 2007. Design and implementation of a water phantom

for

IMRT,

arc

therapy,

and

tomotherapy

dose

distribution

measurements. Med. Phys. 34, 3724-3731. Rutherford, R., Pullan, B., Isherwood, I., 1976. Measurement of effective atomic number and electron density using an EMI scanner. Neuroradiology, 11, 15-21. Schneider, U., Pedroni, E., Lomax, A., 1996. The calibration of CT Hounsfield units for radiotherapy treatment planning. Phys. Med. Biol. 41, 111-124. Schneider, W., Bortfeld, T., Schlegel, W., 2000. Correlation between CT numbers and tissue parameters needed for Monte Carlo simulations of clinical dose distributions. Phys. Med. Biol. 45, 459-478. Shih, C. T., Wu, J., 2017. Converting computed tomography images into photon interaction coefficients by using stoichiometric calibration and parametric fit models. Med. Phys. 44, 510-521. Shonka, F. R., Rose, J. E., Failla, G., 1958. Conducting plastic equivalent to tissue, air, and polystyrene. In: Proceedings of the Second International Conference on the Peaceful Uses of Atomic Energy. Geneva. Shope, T. B., Gagne, R. M., Johnson, G. C., 1981. A method for describing the doses delivered by transmission x‐ ray computed tomography. Med. Phys. 8, 488-495. Vanderstraeten, B., Chin, P. W., Fix, M., et al., 2007. Conversion of CT numbers into tissue parameters for Monte Carlo dose calculations: a multi-centre study. Phys. Med. Biol. 52, 539-562. Vassileva, J., 2002. A phantom for dose-image quality optimization in chest radiography. Br. J. Radiol. 75, 837-842. White, D. R., 1978. Tissue substitutes in experimental radiation physics. Med. Phys. 5, 467479.

24

White, D., Woodard, H., Hammond, S., 1987. Average soft-tissue and bone models for use in radiation dosimetry. Br. J. Radiol. 60, 907-913. Winslow, J. F., Hyer, D. E., Fisher, R. F., et al., 2009. Construction of anthropomorphic phantoms for use in dosimetry studies. J. Appl. Clin. Med. Phys. 10, 195-204. Xu, X. G., 2014. An exponential growth of computational phantom research in radiation protection, imaging, and radiotherapy: a review of the fifty-year history. Phys. Med. Biol. 59, 233-302. Yang, M., Virshup, G., Mohan, R., et al., 2008. Improving accuracy of electron density measurement in the presence of metallic implants using orthovoltage computed tomography. Med. Phys. 35, 1932-1941. Yohannes, I., Kolditz, D., Kalender, W. A., 2011. Semiempirical analysis of materials' elemental composition to formulate tissue-equivalent materials: a preliminary study. Phys. Med. Biol. 56, 2963-2977. Yohannes, I., Kolditz, D., Langner, O., Kalender, W. A., 2012. A formulation of tissue-and water-equivalent materials using the stoichiometric analysis method for CT-number calibration in radiotherapy treatment planning. Phys. Med. Biol. 57, 1173-1190.

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Highlights 

A physical chest phantom with ten tissue equivalent materials was constructed.



Tissue equivalent materials were selected based on their physical properties.



Phantom was scanned by a 64-slice CT scanner and Hounsfield units were measured.



Hounsfield units were calculated by theoretical equations of attenuation coefficient and goodness of fit test.



High agreement (99%) between the results of measurements and calculations indicated the suitability of the phantom.

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