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Measurement of mass attenuation coefficients of Rhizophora spp. binderless particleboards in the 16.59–25.26 keV photon energy range and their density profile using x-ray computed tomography
Applied Radiation and Isotopes 70 (2012) 656–662
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Measurement of mass attenuation coefficients of Rhizophora spp. binderless particleboards in the 16.59–25.26 keV photon energy range and their density profile using x-ray computed tomography M.W. Marashdeh a,n, S. Bauk b, A.A. Tajuddin a, R. Hashim c a
School of Physics, Universiti Sains Malaysia, 11800 USM, Penang, Malaysia Physics Section, P.P.P. Jarak Jauh, Universiti Sains Malaysia, 11800 USM, Penang, Malaysia c Division of Bio-resource, Paper and Coatings Technology, School of Industrial Technology, Universiti Sains Malaysia, 11800 USM, Penang, Malaysia b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 17 July 2011 Received in revised form 6 December 2011 Accepted 10 January 2012 Available online 20 January 2012
The mass attenuation coefficients of Rhizophora spp. binderless particleboard with four different particle sizes (samples A, B, C and D) and natural raw Rhizophora spp. wood (sample E) were determined using single-beam photon transmission in the energy range between 16.59 and 25.26 keV. This was done by determining the attenuation of Ka1 X-ray fluorescent (XRF) photons from niobium, molybdenum, palladium, silver and tin targets. The results were compared with theoretical values of young-age breast (Breast 1) and water calculated using a XCOM computer program. It was found that the mass attenuation coefficient of Rhizophora spp. binderless particleboards to be close to the calculated XCOM values in water than natural Rhizophora spp. wood. Computed tomography (CT) scans were then used to determine the density profile of the samples. The CT scan results showed that the Rhizophora spp. binderless particleboard has uniform density compared to natural Rhizophora spp. wood. In general, the differences in the variability of the profile density decrease as the particle size of the pellet samples decreases. & 2012 Elsevier Ltd. All rights reserved.
Keywords: Rhizophora spp. Binderless particleboard Attenuation coefficient Computed tomography Density profile
1. Introduction The mass attenuation coefficient of various elements and compounds of biological and dosimetric materials have been treated by some authors (Hubbell, 1982; Seltzer, 1993). However, many of the so-called tissue equivalent materials fail to provide a good agreement to the mass attenuation coefficient of water at low and high energies. Several authors had investigated the suitability of local Malaysian woods as tissue-equivalent materials. Che Wan Sudin (1993) had established that a type of mangrove wood, Rhizophora spp. exhibited the characteristics of ionizing radiation interactions similar to that of water. In addition, Bradley et al. (1991) had determined that the attenuation of the Rhizophora spp. at photon energy 59.54 keV was in a good agreement with the attenuation results of water. Percentage depth-dose study obtained at 60Co photon energies showed that data obtained in Rhizophora spp. were within 2% to that of tabulated values for water (Bradley et al., 1991). Further investigation of this wood by Tajuddin et al. (1996) showed Rhizophora spp. to have similar scattering and radiographic
n
Corresponding author. Tel.: þ60 174 723 120. E-mail address: [email protected] (M.W. Marashdeh).
0969-8043/$ - see front matter & 2012 Elsevier Ltd. All rights reserved. doi:10.1016/j.apradiso.2012.01.008
properties to that of water and modified rubber. The measurement of dose distribution around 137Cs and 192Ir brachytherapy sources was studied by Eid (1999), and the results were found to be in good agreement with dose distribution in a water phantom. Shakhreet et al. (2009) measured the mass attenuation coefficients of natural Rhizophora spp. wood in the 15.77–25.27 keV photon energy range, and found that Rhizophora spp. has similar values to the calculated XCOM (Berger and Hubbell, 1987) values for young breast tissue (Breast 1) (Constantinou, 1982). Overall, these results lead to the suggestions that the Rhizophora spp. wood showed similarities in dosimetric properties with other standard phantom materials in radiation dosimetry. Nevertheless, we found that untreated Rhizophora spp. wood has some hindrances if it was to be used as a phantom material, as the Rhizophora spp. raw wood has the propensity to warp and split with time. In addition, it is difficult to control the uniformity of the density throughout the board or slab. Therefore, we propose that the Rhizophora spp. to be milled into small size particles and compressed into binderless particleboards. A particleboard is a wood based composite basically consisting of cellulosic particles of various shape and sizes that are bonded together with adhesive or binder under heat and pressure (Carll, 1986). Most of the resin currently used in the particleboard industry is formaldehyde-based adhesives (Harper, 2002; Rokiah et al., 2009). To ensure a uniform distribution of density of the
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final product, fabricated particleboard were made from the same type of material without the use of any type of resin and is known as binderless particleboard. Marashdeh et al. (2011) had fabricated binderless particleboards made from Rhizophora spp. wood and studied the effect of the particle size on their physical characterizations. The density distribution profile in this experiment was carried out using X-ray Computed Tomography (CT) scanner. The computed tomography (CT) is a powerful nondestructive scanning technique which uses X-ray radiation to determine the density distribution of an object from flat X-ray images taken around a single axis of rotation (Cormack, 1964). In plants, Fromm et al. (2001) pointed out that X-ray CT has been shown to be capable of measuring the interior properties of wood. Several authors (Taylor et al., 1984; Funt and Bryant, 1987; Lindgren, 1991; Le´onard et al., 2004; Alkan et al., 2007) reported of CT scanning of wood, showing that the CT system can be used to detect defects in log and nondestructive measurements of wood density. For binderless particleboard, Marashdeh et al. (2011) had also studied the density distribution profile for Rhizophora spp. binderless particleboards using CT. In the present study, the mass attenuation coefficient for raw Rhizophora spp. binderless particleboard in the photon energy range of 16.59–25.26 keV using a single-beam transmission method was measured experimentally and calculated theoretically. These results were compared with the calculated results from the XCOM program by Berger and Hubbell (1987). In addition, the density distribution profile in the Rhizophora spp. binderless particleboard samples was determined.
2. Experimental procedure
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synthetic adhesive was used as we fabricate binderless particleboard. In addition, for each particle size, pellets with four different thicknesses (7 mm, 5 mm, 4 mm and 2 mm) were fabricated. The thicknesses were determined based on the target density 1.00 g/cm3 as shown in Fig. 1. The pellets had an area of 44.89p mm2. The raw Rhizophora spp. wood was cut into four samples with same dimension (3 3 cm2) and different thicknesses (12 mm, 10 mm, 7 mm and 5 mm). Table 1 shows the classification of Rhizophora spp. particles based on particle sizes and the measured densities after pelletization. The measured density of the pellet samples was calculated simply by dividing the sample mass (g) to the sample volume (cm3) (Table 1). 2.2. Mass attenuation coefficient measurements The mass attenuation coefficients were determined by measuring the transmission of the X-ray fluorescent photons through samples of known thickness. The experimental setup in the present
Table 1 Rhizophora spp. pellet samples with different particle sizes and measured densities. Sample
A B C D E
Measured density (g/cm3)
Particle size (lm)
Average
Max.
Min.
Standard deviation
4147 147-74 74–50 o 50 raw wood
0.997 1.006 1.007 1.068 0.958
1.031 1.029 1.038 1.089 0.985
0.954 0.966 0.951 1.032 0.933
0.033 0.028 0.039 0.026 0.023
2.1. Samples preparation The Rhizophora spp. particles were prepared according to (Marashdeh et al. 2011). The middle part of the Rhizophora spp. tree trunks was used based on Shakhreet et al. (2009) study. The Rhizophora spp. trunks were cut into smaller segments before they were chipped using a grinder machine. The Rhizophora spp. chips were then reduced into particles using hammer-milling, and it was repeated for many times to get different particle sizes. The Rhizophora spp. particles were dried in an oven until its moisture content was about 7–8%. For classifying the particle size a horizontal screening machine with three sieves opening of 147 mm, 74 mm and 50 mm were used. Then, the Rhizophora spp. particles were compressed into pellets for 10 s at 31 MPa using a manual hydraulic press machine. No
A
B
C
Lead Shielding
Pb collimator Sample
241Am
annular source Metal plate
LEGe Detector
Fig. 2. Schematic diagram showing the arrangement of the apparatus for the experiment.
D
E
Fig. 1. Experimental samples used in this experiment. Samples A, B, C and D are pellets of Rhizophora spp. binderless particleboard, each sample has four different thicknesses of 7 mm, 5 mm, 4 mm and 2 mm. Sample E is raw Rhizophora spp. with four different thicknesses of 12 mm, 10 mm, 7 mm and 5 mm.
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Table 2 The metal plate materials and their Ka1 fluorescence energies in keV and their intensities in counts s 1. Element
Atomic no. (Z)
Plate size (mm mm)
Weight (g)
Thickness (mm)
Purity (%)
Ka1 (keV)
Io (counts s 1)
Niobium Molybdenum Palladium Silver Tin
41 42 46 47 50
Radius¼ 25 mm Radius¼ 25 mm 50 50 25 25 Radius¼ 25 mm
2.25 2.06 3.00 13.20 3.80
0.14 0.11 0.10 2.00 0.28
99.8 99.9 99.9 99.99 99.999
16.59 17.46 21.21 22.20 25.26
845 831 996 962 1095
work is shown in Fig. 2. A 59.5 keV g-ray of a 100 mCi 241Am annular radioactive source was used to irradiate high-purity metal targets to produce the x-ray fluorescence (XRF) photons. The targets used were niobium (Nb), molybdenum (Mo), palladium (Pd), silver (Ag) and tin (Sn) producing Ka1 fluorescent x-rays with effective energies of 16.59, 17.46, 21.21, 22.20 and 25.26 keV, respectively. Table 2 summarizes the information of metal plates used in the experiment. The energy intensities were measured using a Low-Energy Germanium (LEGe) detector with an active area and diameter of 200 mm2 and 16 mm, respectively. The crystal is 10 mm thick with a resolution (FWHM) of 400 eV at the 241Am 60 keV emission line. The signals were collected into a spectroscopy amplifier and multichannel analyzer. The detector shielding was designed in the form of a cylindrical lead collimator housing the detector as shown in Fig. 2, to reduce background and scattered radiations. The diameter of the collimator was 3 mm. The distances between the metal plate and the sample and between the sample and the detector were 70 and 89 mm, respectively. When an X-ray beam passes through an sample of thickness x (cm), the intensity of the beam will be attenuated through the absorber according to the Beer–Lambert’s law which is given by
Table 3 Elemental composition by relative weight and relative density of the Breast 1, water, Rhizophora spp. raw wood and Rhizophora spp. binderless particleboard. Material
H C O N K Ca Na S P Cl Mg Relative density (g/cm3)
Breast 1 (25% fat: 75% muscle) Young-age a
Water
10.71 28.25 57.6 2.63 0.23 0.01 0.06 0.38 0.15 0.06 0.02 1.02a
11.11 – 88.89 – – – – – – – – 1.00b
b
Rhizophora spp. raw wood c
Rhizophora spp. binderless particleboard e
5.41 40.16 54.4 0.03 – – – – – – – 1.04d
– 48.32 47.9 3.78 – – – – – – – 1.068f
a
Constantinou (1982). AAPM (1983). Che Wan Sudin (1993). d Bradley et al. (1991). e Marashdeh et al. (2011). f Present study. b c
I ¼ Io emx
ð1Þ
where Io denotes the photon intensity without attenuation; I the photon intensity after attenuation. m (cm 1) is the linear attenuation coefficient of the sample material and may be determined by rearranging 1 I ð2Þ m ¼ ln o x I When the linear attenuation coefficient is divided by the density of the sample, we have the density-independent mass attenuation coefficient m/r (cm2/g) 1 I ð3Þ m=r ¼ ln o rx I where rx is the area density also known as the mass thickness. The results obtained experimentally in the present investigation were compared with the mass attenuation coefficient of water, and young-age breast (Breast 1) (Constantinou, 1982) calculated using XCOM computer program (Berger and Hubbell, 1987). Table 3 provides a comparison between water, Breast 1, Rhizophora spp. raw wood and Rhizophora spp. binderless particleboard sample with respect to their elemental compositions. 2.3. X-ray computed tomography (CT) scanner An X-ray computed tomography scanner (Somaton Sensation Open, Siemens) was used to investigate the density distribution inside the samples. The maximum voltage and current of machine setting were 120 kVp and 33 mA, respectively. The target used for X-ray was tungsten. X-ray CT provides an image pixel value in CT scans, called CT number. The CT number is defined as CT ¼ K
mmw mw
ð4Þ
where m, mw is the linear attenuation coefficient of the sample and linear attenuation coefficient of water, respectively, and K is a magnification contrast ( ¼1000) (Curry et al., 1990). The CT number is represented as the Hounsfield unit (HU), which is related to the density. Water and air corresponding to HU values of 0 and 1000, respectively. Davis and Wells (1992) established the linear relationship between attenuation and density. The CT numbers could well be explained as density values. This relation was developed by Lindgren (1991). Nevertheless, the CT numbers have being different among scanners from different manufacturers. Therefore, this relationship could not be applied directly to another experiment. Accordingly, Levi et al. (1982) stressed that a calibration curve is needed by scanning reference test samples with known densities. From the calibration curve, the relationship between the CT number and the density can be obtained experimentally. In this experiment, several standard materials with known densities were scanned, in order to demonstrate the linear correlation of the calibration curve. Table 4 shows the standard samples with known densities and measured CT numbers. The calibration curve for this experiment is shown in Fig. 3. According to the calibration curve in Fig. 3 the density could be determined by
r ¼ ðCT þ 927:2Þ=890:32
ð5Þ
The sample pellets were scanned using about 22 rays scanning each 0.6 mm thick. The area of interest was studied as a circular area of 0.05 cm2. There were two area of interests in the cross section for each slice scan. The average of CT number for the two
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interested areas were recorded. The CT number values were not recorded at the beginning and end scans, in order to reduce the pixel averaging effect at the interface of wood–air in the edge area. The 18 or 19 other average CT number values were computed. From the CT number values, the density of each slice level of the Rhizophora spp. pellet samples was estimated using Eq. (5). Subsequently, the density distribution profile was investigated.
Table 4 Standard samples used for the calibration curve with their densities and CT numbers. Standard samples
Aluminum Pyrex glass Teflon Solid water phantom Perspex Water Air
Density (g/cm3)
2.70 2.23 2.2 1.04 1.19 1.00 0.00
CT Number
1266 1166 1127 4.80 205.5 12.0 1024
Standard deviation CT number
%
25.6 33.8 13.6 0.90 2.90 0.56 0.40
2.02 2.90 1.21 18.75 1.41 4.67 0.04
Mean standard deviation
4.43
659
3. Results and discussion 3.1. Mass attenuation coefficient measurements The mass attenuation coefficients of the Rhizophora spp. pellets obtained in the photon energy range of 16.59–25.26 keV is as shown in Table 5 using the different X-ray fluorescent beam (XRF) energies from niobium, molybdenum, palladium, silver and tin within given errors between 0.042% and 0.406%. The intensities of the incident and transmitted beams were determined from the net counts under the Ka1 peak. The comparison between Rhizophora spp. pellet results with XCOM calculated mass attenuation coefficients of water is plotted in Fig. 4. It was found that the mass attenuation coefficient of the Rhizophora spp. pellets samples A, C and D with different XRF beam energies was close to the calculated value of water, especially sample D was very close. Samples B and E are the least close to the value of water. In addition, the mass attenuation coefficient results of samples D and E were compared with theoretical values for young-age breast tissue (Breast 1), and water calculated using XCOM computer program (Berger and Hubbell, 1987) is as shown in Fig. 5. It was found that sample E as a raw Rhizophora spp. confirms with the results obtained by Shakhreet et al. (2009), and equivalent to the calculated Breast 1 (Fig. 5). Sample D was
Fig. 3. Calibration curve between CT numbers and standard sample densities.
Fig. 4. Mass attenuation coefficient at different Ka1 XRF peak energies of the Rhizophora spp. pellet samples.
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Table 5 Measured linear and mass attenuation coefficients of Rhizophora spp. pellet samples based on the characteristic x-ray of the targets. Sample Nb 16.59 keV
Mo 17.46 keV
Pd 21.21 keV
Ag 22.20 keV
Sn 25.26 keV
l/q Error (cm 1) (cm2 g 1) (7 %)
l
l/q Error (cm 1) (cm2 g 1) (7 %)
l
l/q Error (cm 1) (cm2 g 1) (7 %)
l
l/q Error (cm 1) (cm2 g 1) (7 %)
l
1.151 0.929 1.225 1.295 0.969
1.023 0.999 1.008 1.173 0.835
0.678 0.646 0.690 0.800 0.551
0.636 0.578 0.683 0.663 0.4884
0.483 0.476 0.505 0.532 0.412
l
A B C D E
1.154 0.923 1.216 1.213 1.011
0.272 0.406 0.110 0.191 0.129
1.026 0.993 1.001 1.099 0.871
0.050 0.085 0.075 0.075 0.062
0.680 0.642 0.685 0.750 0.575
0.068 0.147 0.130 0.090 0.065
0.638 0.574 0.678 0.621 0.510
0.052 0.095 0.130 0.211 0.136
l/q Error (cm 1) (cm2 g 1) (7 %) 0.484 0.473 0.501 0.498 0.430
0.049 0.046 0.081 0.042 0.101
Fig. 5. Mass attenuation coefficient at different energies for samples D and E compared with raw wood of Rhizophora spp. sample by Shakhreet et al. (2009) and calculated XCOM for water and Breast 1.
very close to the calculated mass attenuation coefficient for water. Measures of goodness of fit were used with Rhizophora spp. pellets and water to summarize the discrepancy between them. w2 test was done to check for the goodness of fit, the quantity w2 is a set of N measurements of the squared difference between the observed values yi and their theoretical predictions xi (Barlow, 1989), suitably weighted by the expected errors si of measurement. The quantity of w2 is given by
w2 ¼
2 N X y f ðxi Þ i
i¼1
si
ð6Þ
If the function really agrees well with the actual values then w2 will be small. The result of a w2-test on the experimental data is shown in Table 6. It is evident that the binderless particleboard samples A, B, C and D were close to the XCOM calculated water with w2 values of 4.35, 4.08, 2.95 and 0.66, respectively. Sample of D is the closest one to water with an insignificant difference. Raw wood of Rhizophora spp. sample E has a high w2 value of 25.77 with XCOM calculated water. These results indicate that the Rhizophora spp. in the form of binderless particleboard has attenuation properties close to water, better than the raw wood form. This indicates that binderless particleboard has the potential to be used as a phantom material in hospitals. The percentage deviation of the mass attenuation coefficient for samples A, B, C, D and E, from the calculated value of water were determined and are shown in Fig. 6. It was found that there is no large significant of deviation between binderless particleboard samples A, B, C and D and calculated water. Most of the
Table 6 The w2-test of the mass attenuation coefficient of Rhizophora spp. pellet samples to XCOM calculated water. (yi xi)2/ri2 with water Energy
Sample A
Sample B
Sample C
Sample D
Sample E
16.59 17.46 21.21 22.2 25.26
0.22 3.78 0.22 0.02 0.10
0.77 2.24 0.21 0.53 0.32
0.34 2.51 0.04 0.07 0.00
0.37 0.08 0.19 0.01 0.00
3.93 16.04 4.36 0.96 0.47
w2
4.35
4.08
2.95
0.66
25.77
deviations of binderless particleboard samples are within 10% from the calculated water, except for the large deviation of about 27.88% due to sample B at 16.59 keV. In another hand, raw wood of Rhizophora spp. sample E has the largest deviation of about 13.89%–22.19% from the calculated water at all energies (Fig. 6). 3.2. Density distribution profile The density distribution profile of binderless particleboard samples A, B, C and D and raw Rhizophora spp. sample E of thickness (7 mm) were studied. The calculated density of the CT scan samples was determined simply by dividing the mass (g) to measured volume (cm3) as shown in Table 7. The average, maximum, minimum and standard deviation of the CT number value for experimental samples are listed in Table 7. It can be noted from Table 7 that the average CT number increases as the
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Fig. 6. The percentage deviation of the mass attenuation coefficient of Rhizophora spp. pellet samples from the calculated water (XCOM).
Table 7 Calculated densities and the mean, maximum, minimum and standard deviation of the CT numbers for the 7 mm thick samples. Sample
A B C D E
CT Number
Calculated density (g/cm3)
Mean
Maximum
Minimum
Standard deviation
161.77 208.81 227.31 240.84 131.73
217.15 230.80 239.30 264.65 100.80
14.10 140.00 174.30 190.50 184.10
74.19 27.02 19.31 18.80 25.39
1.031 1.029 1.038 1.084 0.969
Fig. 7. Relative density profiles along the plane of the binderless particleboard samples A, B, C and D and natural Rhizophora spp. sample E. All densities were normalized at the center of the samples.
particle size of sample decreases, where the smallest particle size sample D has the largest CT number value with a standard deviation of 18.80 compared with samples A, B and C with a standard deviation of 74.19, 27.02 and 19.31, respectively. In addition, the natural Rhizophora spp. wood sample E has generally less CT number value compared with the CT number values of Rhizophora spp. binderless particleboard samples. According to
the variability of CT number between samples, it shows a considerable effect of particle size on the sample density. So that smaller particle size results in higher density of sample. The relative density distribution profile across the width of the binderless particleboard samples and natural Rhizophora spp. sample are shown in Fig. 7. The density distribution for each measuring point (mm) was calculated using Eq. (5). It was found
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Table 8 Results of statistical analyses showing the calculated COV, the maximum and minimum density values of the Rhizophora spp. pellet samples using CT scan for interest region along the samples of 1.8–12.6 mm. Sample
COV (%)
Universiti Sains Malaysia. We are also grateful to the Medical Imaging Unit of Mt. Miriam Cancer Center, Penang, Malaysia for the use of their computed tomography (CT) scanner.
Density (g/cm3)
References A B C D E
6.87 2.40 1.69 1.62 3.23
Max.
Min.
1.275 1.291 1.300 1.329 0.918
1.047 1.189 1.227 1.245 0.825
that all the samples had varying density distribution along the samples. The CT number values at the beginning and end scans were not considered, in order to reduce the effect of degeneration the density at the edge of samples. Therefore, the interest region across the pellet samples was 1.8–12.6 mm. It can be obviously seen that all binderless particleboard samples have uniform density distribution than raw wood of Rhizophora spp. except sample A. Whereas largest particle size of binderless particleboard sample A results bigger overlapping areas, larger voids between particles and less possibility for randomization. This explains why the large decadence of density in a particular region of sample A, between 10 and 12 mm measuring point in Fig. 7. The coefficient of variation (COV) was used to clarify the ratio of variation of density distribution for samples. COV is defined as the ratio of density standard deviation to its average density. The calculated COV’s along the samples with the maximum and minimum density values are presented in Table 8. It shows that the samples B, C and D were considerably uniform than the density distribution of samples A and E. The smaller particle size of pellet samples C and D have low COV values 1.69% and 1.62%, respectively. Sample B has a considerable COV value of 2.40%. The Rhizophora spp. raw wood sample E has 3.23% COV value, which refers to large variation of density distribution than the binderless particleboard samples except sample A with 6.87% COV value. This indicates that particle size has a strong effect on the density distribution of sample as was established by Steiner and Wei (1995) and Kruse et al. (2000).
4. Conclusion The mass attenuation coefficient of Rhizophora spp. binderless particleboard with smaller particle size in the 16.59–25.26 keV photon energies range was found to be very close to the calculated XCOM value from water. On the other hand, the density profile of Rhizophora spp. binderless particleboard improved with the decrease in the particle size. These results indicate that Rhizophora spp. binderless particleboard might be able to be used as diagnostic and therapeutic phantom material.
Acknowledgment We would like to acknowledge the financial support of the Research University Grant no. 1001/PJJAUH/813007 from the
AAPM, 1983. Task Group-21. A protocol for the determination of absorbed dose from high-energy photon and electron beams. Med. Phys. 10, 741–771. Alkan, S., Zhang, Y., Lam, F., 2007. Moisture distribution changes and wetwood behavior in subalpine fir wood during drying using high X-ray energy industrial CT scanner. Drying Technol. 25, 483–488. Barlow, R.J., 1989. Statistics: A Guide To The Use Of Statistical Methods In The Physical Sciences. John Wiley & Sons Inc. (79–99). Berger, M.J., Hubbell, J.H., 1987. XCOM: Photon Cross-Sections On A Personal Computer. U.S. Department of Commerce. pp. 1–10. Bradley, D.A., Tajuddin, A.A., Che Wan Sudin, C.W.A., Bauk, S., 1991. Photon attenuation studies on tropical hard woods. Appl. Radiat. Isot. 42, 771–773. Carll, C., 1986. Wood Particleboard and Flakeboard Types, Grades, and Uses. USDA Forest Service, Forest Products Laboratory. General Technical Report FPL-GTR53, 8. Che Wan Sudin, C.W.A., 1993. Kayu Tropika Sebagai Bahantara Setaraan Tisu Untuk Kajian Dosimetri. M.Sc. Thesis. Universiti Sains Malaysia. Constantinou, C., 1982. Phantom materials for radiation dosimetry. I. Liquids and gels. Br. J. Radiol. 55, 217–224. Cormack, A.M., 1964. Representation of a function by its line integrals, with some radiological applications. II. J. Appl. Phys. 35, 2908–2913. Curry, T.S., Dowdey, J.E., Murry, R.C., Christensen, E.E., 1990. Christensen’s physics of diagnostic radiology, fourth ed. Lippincott Williams & Wilkins. (307–309). Davis, J., Wells, P., 1992. Computed tomographymeasurements on wood. Ind. Metrol. 2, 195–218. Eid, M.E.A.M., 1999. Radiation Dose Distribution Measurements Around Brachytherapy Sources in Water and Rhizophora spp. Phantoms. M.Sc. Thesis. Universiti Sains Malaysia. Fromm, J.H., Sautter, I., Matthies, D., Kremer, J., Schumacher, P., Ganter, C., 2001. Xylem water content and wood density in spruce and oak trees detected by high-resolution computed tomography. Plant Physiol. 127, 416–425. Funt, B.V., Bryant, E.C., 1987. Detection of internal log defects by automatic interpretation of computer tomography images. For. Prod. J. 37, 56–62. Harper, C.A., 2002. Handbook of Plastics, Elastomers, and Composites. McGrawHill Professional. Hubbell, J., 1982. Photon mass attenuation and energy-absorption coefficients from 1 keV to 20 MeV. Int. J. Appl. Radiat. Isot. 33, 1269–1290. Kruse, K., Dai, C., Pielasch, A., 2000. An analysis of strand and horizontal density distributions in oriented strand board (OSB). Eur. J. Wood Wood Prod. 58, 270–277. Le´onard, A., Blacher, S., Marchot, P., Pirard, J.P., Crine, M., 2004. Measurement of shrinkage and cracks associated to convective drying of soft materials by X-ray microtomography. Drying Technol. 22, 1695–1708. Levi, C., Gray, J.E., McCullough, E., Hattery, R., 1982. The unreliability of CT numbers as absolute values. Am. J. Roentgenol. 139, 443–447. Lindgren, L., 1991. Medical CAT-scanning: x-ray absorption coefficients, CTnumbers and their relation to wood density. Wood Sci. Technol. 25, 341–349. Marashdeh, M.W., Hashim, R., Tajuddin, A.A., Bauk, S., Sulaiman, O., 2011. Effect of particle size on the characterization of binderless particleboard made from Rhizophora spp. Mangrove wood for use as phantom material. BioResources 6 (4), 4028–4044. Rokiah, H., Hazneza, A.H.S., Othman, S., Norli, I., Hakimi, I.M., Hasnah, M., Salmiah, U., 2009. Extractable formaldehyde from waste medium density fibreboard. J. Trop. For. Sci. 21, 25–33. Seltzer, S.M., 1993. Calculation of photon mass energy-transfer and mass energyabsorption coefficients. Radiat. Res. 136, 147–170. Shakhreet, B., Bauk, S., Tajuddin, A.A., Shukri, A., 2009. Mass attenuation coefficients of natural Rhizophora spp. wood for X-rays in the 15.77–25.27 keV range. Radiat. Prot. Dosimetry 135, 47–53. Steiner, P.R., Wei, X., 1995. Influence of flake characteristics on horizontal density distribution of flakeboard. For. Prod. J. 45, 61–66. Tajuddin, A.A., Che Wan Sudin, C.W.A., Bradley, D.A., 1996. Radiographic and scattering investigation on the suitability of Rhizophora spp. as tissue-equivalent medium for dosimetric study. Radiat. Phys. Chem. 47, 739–740. Taylor, F.W., Wagner Jr., F.G., McMillin, C.W., Morgan, I.L., Hopkins, F.F., 1984. Locating knots by industrial tomography. A feasibility study. For. Prod. J. 34, 42–46.
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Applied Radiation and Isotopes journal homepage: www.elsevier.com/locate/apradiso
Measurement of mass attenuation coefficients of Rhizophora spp. binderless particleboards in the 16.59–25.26 keV photon energy range and their density profile using x-ray computed tomography M.W. Marashdeh a,n, S. Bauk b, A.A. Tajuddin a, R. Hashim c a
School of Physics, Universiti Sains Malaysia, 11800 USM, Penang, Malaysia Physics Section, P.P.P. Jarak Jauh, Universiti Sains Malaysia, 11800 USM, Penang, Malaysia c Division of Bio-resource, Paper and Coatings Technology, School of Industrial Technology, Universiti Sains Malaysia, 11800 USM, Penang, Malaysia b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 17 July 2011 Received in revised form 6 December 2011 Accepted 10 January 2012 Available online 20 January 2012
The mass attenuation coefficients of Rhizophora spp. binderless particleboard with four different particle sizes (samples A, B, C and D) and natural raw Rhizophora spp. wood (sample E) were determined using single-beam photon transmission in the energy range between 16.59 and 25.26 keV. This was done by determining the attenuation of Ka1 X-ray fluorescent (XRF) photons from niobium, molybdenum, palladium, silver and tin targets. The results were compared with theoretical values of young-age breast (Breast 1) and water calculated using a XCOM computer program. It was found that the mass attenuation coefficient of Rhizophora spp. binderless particleboards to be close to the calculated XCOM values in water than natural Rhizophora spp. wood. Computed tomography (CT) scans were then used to determine the density profile of the samples. The CT scan results showed that the Rhizophora spp. binderless particleboard has uniform density compared to natural Rhizophora spp. wood. In general, the differences in the variability of the profile density decrease as the particle size of the pellet samples decreases. & 2012 Elsevier Ltd. All rights reserved.
Keywords: Rhizophora spp. Binderless particleboard Attenuation coefficient Computed tomography Density profile
1. Introduction The mass attenuation coefficient of various elements and compounds of biological and dosimetric materials have been treated by some authors (Hubbell, 1982; Seltzer, 1993). However, many of the so-called tissue equivalent materials fail to provide a good agreement to the mass attenuation coefficient of water at low and high energies. Several authors had investigated the suitability of local Malaysian woods as tissue-equivalent materials. Che Wan Sudin (1993) had established that a type of mangrove wood, Rhizophora spp. exhibited the characteristics of ionizing radiation interactions similar to that of water. In addition, Bradley et al. (1991) had determined that the attenuation of the Rhizophora spp. at photon energy 59.54 keV was in a good agreement with the attenuation results of water. Percentage depth-dose study obtained at 60Co photon energies showed that data obtained in Rhizophora spp. were within 2% to that of tabulated values for water (Bradley et al., 1991). Further investigation of this wood by Tajuddin et al. (1996) showed Rhizophora spp. to have similar scattering and radiographic
n
Corresponding author. Tel.: þ60 174 723 120. E-mail address: [email protected] (M.W. Marashdeh).
0969-8043/$ - see front matter & 2012 Elsevier Ltd. All rights reserved. doi:10.1016/j.apradiso.2012.01.008
properties to that of water and modified rubber. The measurement of dose distribution around 137Cs and 192Ir brachytherapy sources was studied by Eid (1999), and the results were found to be in good agreement with dose distribution in a water phantom. Shakhreet et al. (2009) measured the mass attenuation coefficients of natural Rhizophora spp. wood in the 15.77–25.27 keV photon energy range, and found that Rhizophora spp. has similar values to the calculated XCOM (Berger and Hubbell, 1987) values for young breast tissue (Breast 1) (Constantinou, 1982). Overall, these results lead to the suggestions that the Rhizophora spp. wood showed similarities in dosimetric properties with other standard phantom materials in radiation dosimetry. Nevertheless, we found that untreated Rhizophora spp. wood has some hindrances if it was to be used as a phantom material, as the Rhizophora spp. raw wood has the propensity to warp and split with time. In addition, it is difficult to control the uniformity of the density throughout the board or slab. Therefore, we propose that the Rhizophora spp. to be milled into small size particles and compressed into binderless particleboards. A particleboard is a wood based composite basically consisting of cellulosic particles of various shape and sizes that are bonded together with adhesive or binder under heat and pressure (Carll, 1986). Most of the resin currently used in the particleboard industry is formaldehyde-based adhesives (Harper, 2002; Rokiah et al., 2009). To ensure a uniform distribution of density of the
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final product, fabricated particleboard were made from the same type of material without the use of any type of resin and is known as binderless particleboard. Marashdeh et al. (2011) had fabricated binderless particleboards made from Rhizophora spp. wood and studied the effect of the particle size on their physical characterizations. The density distribution profile in this experiment was carried out using X-ray Computed Tomography (CT) scanner. The computed tomography (CT) is a powerful nondestructive scanning technique which uses X-ray radiation to determine the density distribution of an object from flat X-ray images taken around a single axis of rotation (Cormack, 1964). In plants, Fromm et al. (2001) pointed out that X-ray CT has been shown to be capable of measuring the interior properties of wood. Several authors (Taylor et al., 1984; Funt and Bryant, 1987; Lindgren, 1991; Le´onard et al., 2004; Alkan et al., 2007) reported of CT scanning of wood, showing that the CT system can be used to detect defects in log and nondestructive measurements of wood density. For binderless particleboard, Marashdeh et al. (2011) had also studied the density distribution profile for Rhizophora spp. binderless particleboards using CT. In the present study, the mass attenuation coefficient for raw Rhizophora spp. binderless particleboard in the photon energy range of 16.59–25.26 keV using a single-beam transmission method was measured experimentally and calculated theoretically. These results were compared with the calculated results from the XCOM program by Berger and Hubbell (1987). In addition, the density distribution profile in the Rhizophora spp. binderless particleboard samples was determined.
2. Experimental procedure
657
synthetic adhesive was used as we fabricate binderless particleboard. In addition, for each particle size, pellets with four different thicknesses (7 mm, 5 mm, 4 mm and 2 mm) were fabricated. The thicknesses were determined based on the target density 1.00 g/cm3 as shown in Fig. 1. The pellets had an area of 44.89p mm2. The raw Rhizophora spp. wood was cut into four samples with same dimension (3 3 cm2) and different thicknesses (12 mm, 10 mm, 7 mm and 5 mm). Table 1 shows the classification of Rhizophora spp. particles based on particle sizes and the measured densities after pelletization. The measured density of the pellet samples was calculated simply by dividing the sample mass (g) to the sample volume (cm3) (Table 1). 2.2. Mass attenuation coefficient measurements The mass attenuation coefficients were determined by measuring the transmission of the X-ray fluorescent photons through samples of known thickness. The experimental setup in the present
Table 1 Rhizophora spp. pellet samples with different particle sizes and measured densities. Sample
A B C D E
Measured density (g/cm3)
Particle size (lm)
Average
Max.
Min.
Standard deviation
4147 147-74 74–50 o 50 raw wood
0.997 1.006 1.007 1.068 0.958
1.031 1.029 1.038 1.089 0.985
0.954 0.966 0.951 1.032 0.933
0.033 0.028 0.039 0.026 0.023
2.1. Samples preparation The Rhizophora spp. particles were prepared according to (Marashdeh et al. 2011). The middle part of the Rhizophora spp. tree trunks was used based on Shakhreet et al. (2009) study. The Rhizophora spp. trunks were cut into smaller segments before they were chipped using a grinder machine. The Rhizophora spp. chips were then reduced into particles using hammer-milling, and it was repeated for many times to get different particle sizes. The Rhizophora spp. particles were dried in an oven until its moisture content was about 7–8%. For classifying the particle size a horizontal screening machine with three sieves opening of 147 mm, 74 mm and 50 mm were used. Then, the Rhizophora spp. particles were compressed into pellets for 10 s at 31 MPa using a manual hydraulic press machine. No
A
B
C
Lead Shielding
Pb collimator Sample
241Am
annular source Metal plate
LEGe Detector
Fig. 2. Schematic diagram showing the arrangement of the apparatus for the experiment.
D
E
Fig. 1. Experimental samples used in this experiment. Samples A, B, C and D are pellets of Rhizophora spp. binderless particleboard, each sample has four different thicknesses of 7 mm, 5 mm, 4 mm and 2 mm. Sample E is raw Rhizophora spp. with four different thicknesses of 12 mm, 10 mm, 7 mm and 5 mm.
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Table 2 The metal plate materials and their Ka1 fluorescence energies in keV and their intensities in counts s 1. Element
Atomic no. (Z)
Plate size (mm mm)
Weight (g)
Thickness (mm)
Purity (%)
Ka1 (keV)
Io (counts s 1)
Niobium Molybdenum Palladium Silver Tin
41 42 46 47 50
Radius¼ 25 mm Radius¼ 25 mm 50 50 25 25 Radius¼ 25 mm
2.25 2.06 3.00 13.20 3.80
0.14 0.11 0.10 2.00 0.28
99.8 99.9 99.9 99.99 99.999
16.59 17.46 21.21 22.20 25.26
845 831 996 962 1095
work is shown in Fig. 2. A 59.5 keV g-ray of a 100 mCi 241Am annular radioactive source was used to irradiate high-purity metal targets to produce the x-ray fluorescence (XRF) photons. The targets used were niobium (Nb), molybdenum (Mo), palladium (Pd), silver (Ag) and tin (Sn) producing Ka1 fluorescent x-rays with effective energies of 16.59, 17.46, 21.21, 22.20 and 25.26 keV, respectively. Table 2 summarizes the information of metal plates used in the experiment. The energy intensities were measured using a Low-Energy Germanium (LEGe) detector with an active area and diameter of 200 mm2 and 16 mm, respectively. The crystal is 10 mm thick with a resolution (FWHM) of 400 eV at the 241Am 60 keV emission line. The signals were collected into a spectroscopy amplifier and multichannel analyzer. The detector shielding was designed in the form of a cylindrical lead collimator housing the detector as shown in Fig. 2, to reduce background and scattered radiations. The diameter of the collimator was 3 mm. The distances between the metal plate and the sample and between the sample and the detector were 70 and 89 mm, respectively. When an X-ray beam passes through an sample of thickness x (cm), the intensity of the beam will be attenuated through the absorber according to the Beer–Lambert’s law which is given by
Table 3 Elemental composition by relative weight and relative density of the Breast 1, water, Rhizophora spp. raw wood and Rhizophora spp. binderless particleboard. Material
H C O N K Ca Na S P Cl Mg Relative density (g/cm3)
Breast 1 (25% fat: 75% muscle) Young-age a
Water
10.71 28.25 57.6 2.63 0.23 0.01 0.06 0.38 0.15 0.06 0.02 1.02a
11.11 – 88.89 – – – – – – – – 1.00b
b
Rhizophora spp. raw wood c
Rhizophora spp. binderless particleboard e
5.41 40.16 54.4 0.03 – – – – – – – 1.04d
– 48.32 47.9 3.78 – – – – – – – 1.068f
a
Constantinou (1982). AAPM (1983). Che Wan Sudin (1993). d Bradley et al. (1991). e Marashdeh et al. (2011). f Present study. b c
I ¼ Io emx
ð1Þ
where Io denotes the photon intensity without attenuation; I the photon intensity after attenuation. m (cm 1) is the linear attenuation coefficient of the sample material and may be determined by rearranging 1 I ð2Þ m ¼ ln o x I When the linear attenuation coefficient is divided by the density of the sample, we have the density-independent mass attenuation coefficient m/r (cm2/g) 1 I ð3Þ m=r ¼ ln o rx I where rx is the area density also known as the mass thickness. The results obtained experimentally in the present investigation were compared with the mass attenuation coefficient of water, and young-age breast (Breast 1) (Constantinou, 1982) calculated using XCOM computer program (Berger and Hubbell, 1987). Table 3 provides a comparison between water, Breast 1, Rhizophora spp. raw wood and Rhizophora spp. binderless particleboard sample with respect to their elemental compositions. 2.3. X-ray computed tomography (CT) scanner An X-ray computed tomography scanner (Somaton Sensation Open, Siemens) was used to investigate the density distribution inside the samples. The maximum voltage and current of machine setting were 120 kVp and 33 mA, respectively. The target used for X-ray was tungsten. X-ray CT provides an image pixel value in CT scans, called CT number. The CT number is defined as CT ¼ K
mmw mw
ð4Þ
where m, mw is the linear attenuation coefficient of the sample and linear attenuation coefficient of water, respectively, and K is a magnification contrast ( ¼1000) (Curry et al., 1990). The CT number is represented as the Hounsfield unit (HU), which is related to the density. Water and air corresponding to HU values of 0 and 1000, respectively. Davis and Wells (1992) established the linear relationship between attenuation and density. The CT numbers could well be explained as density values. This relation was developed by Lindgren (1991). Nevertheless, the CT numbers have being different among scanners from different manufacturers. Therefore, this relationship could not be applied directly to another experiment. Accordingly, Levi et al. (1982) stressed that a calibration curve is needed by scanning reference test samples with known densities. From the calibration curve, the relationship between the CT number and the density can be obtained experimentally. In this experiment, several standard materials with known densities were scanned, in order to demonstrate the linear correlation of the calibration curve. Table 4 shows the standard samples with known densities and measured CT numbers. The calibration curve for this experiment is shown in Fig. 3. According to the calibration curve in Fig. 3 the density could be determined by
r ¼ ðCT þ 927:2Þ=890:32
ð5Þ
The sample pellets were scanned using about 22 rays scanning each 0.6 mm thick. The area of interest was studied as a circular area of 0.05 cm2. There were two area of interests in the cross section for each slice scan. The average of CT number for the two
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interested areas were recorded. The CT number values were not recorded at the beginning and end scans, in order to reduce the pixel averaging effect at the interface of wood–air in the edge area. The 18 or 19 other average CT number values were computed. From the CT number values, the density of each slice level of the Rhizophora spp. pellet samples was estimated using Eq. (5). Subsequently, the density distribution profile was investigated.
Table 4 Standard samples used for the calibration curve with their densities and CT numbers. Standard samples
Aluminum Pyrex glass Teflon Solid water phantom Perspex Water Air
Density (g/cm3)
2.70 2.23 2.2 1.04 1.19 1.00 0.00
CT Number
1266 1166 1127 4.80 205.5 12.0 1024
Standard deviation CT number
%
25.6 33.8 13.6 0.90 2.90 0.56 0.40
2.02 2.90 1.21 18.75 1.41 4.67 0.04
Mean standard deviation
4.43
659
3. Results and discussion 3.1. Mass attenuation coefficient measurements The mass attenuation coefficients of the Rhizophora spp. pellets obtained in the photon energy range of 16.59–25.26 keV is as shown in Table 5 using the different X-ray fluorescent beam (XRF) energies from niobium, molybdenum, palladium, silver and tin within given errors between 0.042% and 0.406%. The intensities of the incident and transmitted beams were determined from the net counts under the Ka1 peak. The comparison between Rhizophora spp. pellet results with XCOM calculated mass attenuation coefficients of water is plotted in Fig. 4. It was found that the mass attenuation coefficient of the Rhizophora spp. pellets samples A, C and D with different XRF beam energies was close to the calculated value of water, especially sample D was very close. Samples B and E are the least close to the value of water. In addition, the mass attenuation coefficient results of samples D and E were compared with theoretical values for young-age breast tissue (Breast 1), and water calculated using XCOM computer program (Berger and Hubbell, 1987) is as shown in Fig. 5. It was found that sample E as a raw Rhizophora spp. confirms with the results obtained by Shakhreet et al. (2009), and equivalent to the calculated Breast 1 (Fig. 5). Sample D was
Fig. 3. Calibration curve between CT numbers and standard sample densities.
Fig. 4. Mass attenuation coefficient at different Ka1 XRF peak energies of the Rhizophora spp. pellet samples.
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Table 5 Measured linear and mass attenuation coefficients of Rhizophora spp. pellet samples based on the characteristic x-ray of the targets. Sample Nb 16.59 keV
Mo 17.46 keV
Pd 21.21 keV
Ag 22.20 keV
Sn 25.26 keV
l/q Error (cm 1) (cm2 g 1) (7 %)
l
l/q Error (cm 1) (cm2 g 1) (7 %)
l
l/q Error (cm 1) (cm2 g 1) (7 %)
l
l/q Error (cm 1) (cm2 g 1) (7 %)
l
1.151 0.929 1.225 1.295 0.969
1.023 0.999 1.008 1.173 0.835
0.678 0.646 0.690 0.800 0.551
0.636 0.578 0.683 0.663 0.4884
0.483 0.476 0.505 0.532 0.412
l
A B C D E
1.154 0.923 1.216 1.213 1.011
0.272 0.406 0.110 0.191 0.129
1.026 0.993 1.001 1.099 0.871
0.050 0.085 0.075 0.075 0.062
0.680 0.642 0.685 0.750 0.575
0.068 0.147 0.130 0.090 0.065
0.638 0.574 0.678 0.621 0.510
0.052 0.095 0.130 0.211 0.136
l/q Error (cm 1) (cm2 g 1) (7 %) 0.484 0.473 0.501 0.498 0.430
0.049 0.046 0.081 0.042 0.101
Fig. 5. Mass attenuation coefficient at different energies for samples D and E compared with raw wood of Rhizophora spp. sample by Shakhreet et al. (2009) and calculated XCOM for water and Breast 1.
very close to the calculated mass attenuation coefficient for water. Measures of goodness of fit were used with Rhizophora spp. pellets and water to summarize the discrepancy between them. w2 test was done to check for the goodness of fit, the quantity w2 is a set of N measurements of the squared difference between the observed values yi and their theoretical predictions xi (Barlow, 1989), suitably weighted by the expected errors si of measurement. The quantity of w2 is given by
w2 ¼
2 N X y f ðxi Þ i
i¼1
si
ð6Þ
If the function really agrees well with the actual values then w2 will be small. The result of a w2-test on the experimental data is shown in Table 6. It is evident that the binderless particleboard samples A, B, C and D were close to the XCOM calculated water with w2 values of 4.35, 4.08, 2.95 and 0.66, respectively. Sample of D is the closest one to water with an insignificant difference. Raw wood of Rhizophora spp. sample E has a high w2 value of 25.77 with XCOM calculated water. These results indicate that the Rhizophora spp. in the form of binderless particleboard has attenuation properties close to water, better than the raw wood form. This indicates that binderless particleboard has the potential to be used as a phantom material in hospitals. The percentage deviation of the mass attenuation coefficient for samples A, B, C, D and E, from the calculated value of water were determined and are shown in Fig. 6. It was found that there is no large significant of deviation between binderless particleboard samples A, B, C and D and calculated water. Most of the
Table 6 The w2-test of the mass attenuation coefficient of Rhizophora spp. pellet samples to XCOM calculated water. (yi xi)2/ri2 with water Energy
Sample A
Sample B
Sample C
Sample D
Sample E
16.59 17.46 21.21 22.2 25.26
0.22 3.78 0.22 0.02 0.10
0.77 2.24 0.21 0.53 0.32
0.34 2.51 0.04 0.07 0.00
0.37 0.08 0.19 0.01 0.00
3.93 16.04 4.36 0.96 0.47
w2
4.35
4.08
2.95
0.66
25.77
deviations of binderless particleboard samples are within 10% from the calculated water, except for the large deviation of about 27.88% due to sample B at 16.59 keV. In another hand, raw wood of Rhizophora spp. sample E has the largest deviation of about 13.89%–22.19% from the calculated water at all energies (Fig. 6). 3.2. Density distribution profile The density distribution profile of binderless particleboard samples A, B, C and D and raw Rhizophora spp. sample E of thickness (7 mm) were studied. The calculated density of the CT scan samples was determined simply by dividing the mass (g) to measured volume (cm3) as shown in Table 7. The average, maximum, minimum and standard deviation of the CT number value for experimental samples are listed in Table 7. It can be noted from Table 7 that the average CT number increases as the
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661
Fig. 6. The percentage deviation of the mass attenuation coefficient of Rhizophora spp. pellet samples from the calculated water (XCOM).
Table 7 Calculated densities and the mean, maximum, minimum and standard deviation of the CT numbers for the 7 mm thick samples. Sample
A B C D E
CT Number
Calculated density (g/cm3)
Mean
Maximum
Minimum
Standard deviation
161.77 208.81 227.31 240.84 131.73
217.15 230.80 239.30 264.65 100.80
14.10 140.00 174.30 190.50 184.10
74.19 27.02 19.31 18.80 25.39
1.031 1.029 1.038 1.084 0.969
Fig. 7. Relative density profiles along the plane of the binderless particleboard samples A, B, C and D and natural Rhizophora spp. sample E. All densities were normalized at the center of the samples.
particle size of sample decreases, where the smallest particle size sample D has the largest CT number value with a standard deviation of 18.80 compared with samples A, B and C with a standard deviation of 74.19, 27.02 and 19.31, respectively. In addition, the natural Rhizophora spp. wood sample E has generally less CT number value compared with the CT number values of Rhizophora spp. binderless particleboard samples. According to
the variability of CT number between samples, it shows a considerable effect of particle size on the sample density. So that smaller particle size results in higher density of sample. The relative density distribution profile across the width of the binderless particleboard samples and natural Rhizophora spp. sample are shown in Fig. 7. The density distribution for each measuring point (mm) was calculated using Eq. (5). It was found
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Table 8 Results of statistical analyses showing the calculated COV, the maximum and minimum density values of the Rhizophora spp. pellet samples using CT scan for interest region along the samples of 1.8–12.6 mm. Sample
COV (%)
Universiti Sains Malaysia. We are also grateful to the Medical Imaging Unit of Mt. Miriam Cancer Center, Penang, Malaysia for the use of their computed tomography (CT) scanner.
Density (g/cm3)
References A B C D E
6.87 2.40 1.69 1.62 3.23
Max.
Min.
1.275 1.291 1.300 1.329 0.918
1.047 1.189 1.227 1.245 0.825
that all the samples had varying density distribution along the samples. The CT number values at the beginning and end scans were not considered, in order to reduce the effect of degeneration the density at the edge of samples. Therefore, the interest region across the pellet samples was 1.8–12.6 mm. It can be obviously seen that all binderless particleboard samples have uniform density distribution than raw wood of Rhizophora spp. except sample A. Whereas largest particle size of binderless particleboard sample A results bigger overlapping areas, larger voids between particles and less possibility for randomization. This explains why the large decadence of density in a particular region of sample A, between 10 and 12 mm measuring point in Fig. 7. The coefficient of variation (COV) was used to clarify the ratio of variation of density distribution for samples. COV is defined as the ratio of density standard deviation to its average density. The calculated COV’s along the samples with the maximum and minimum density values are presented in Table 8. It shows that the samples B, C and D were considerably uniform than the density distribution of samples A and E. The smaller particle size of pellet samples C and D have low COV values 1.69% and 1.62%, respectively. Sample B has a considerable COV value of 2.40%. The Rhizophora spp. raw wood sample E has 3.23% COV value, which refers to large variation of density distribution than the binderless particleboard samples except sample A with 6.87% COV value. This indicates that particle size has a strong effect on the density distribution of sample as was established by Steiner and Wei (1995) and Kruse et al. (2000).
4. Conclusion The mass attenuation coefficient of Rhizophora spp. binderless particleboard with smaller particle size in the 16.59–25.26 keV photon energies range was found to be very close to the calculated XCOM value from water. On the other hand, the density profile of Rhizophora spp. binderless particleboard improved with the decrease in the particle size. These results indicate that Rhizophora spp. binderless particleboard might be able to be used as diagnostic and therapeutic phantom material.
Acknowledgment We would like to acknowledge the financial support of the Research University Grant no. 1001/PJJAUH/813007 from the
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