MEASUREMENT OF INTERNAL RADIATION DOSE DISTRIBUTION IN CT EXAMINATIONS USING POLYETHYLENE TEREPHTHALATE RESIN

MEASUREMENT OF INTERNAL RADIATION DOSE DISTRIBUTION IN CT EXAMINATIONS USING POLYETHYLENE... ABSTRACT This study proposes a new dosimetry method for the estimation of the internal radiation dose distribution of a subject undergoing computed tomography (CT) examinations. In this novel method, dose distribution of a subject by CT scans was estimated based on radiophotoluminance distribution with polyethylene terephthalate (PET) resin which was cut to the average head size of a Japanese 1-year-old child. The difference in dose distribution depending on the type of bowtie filter was visualized by imaging luminance distribution with the PET phantom using a charge-coupled device camera. Dose distribution images simulated from a water phantom of the same size as the PET phantom were compared with the luminance distribution images. The linear correlation was demonstrated between luminance of the PET phantom and the simulated water dose. In comparison with the simulated water doses and the converted water doses from luminance of the PET phantom, the relative differences were within 20%. INTRODUCTION In recent years the potential risk of radiation exposure in pediatric computed tomography (CT) examinations has become a major concern worldwide. This is because the carcinogenic risk for pediatric patients who underwent CT examinations has been confirmed in a couple of epidemiological studies. Pearce et al.(1,) reported that when the cumulative dose of brain or red bone marrow in a pediatric patient undergoing CT examinations becomes ~50–60 mGy, the risk of brain tumors or leukemia becomes almost three times greater compared with patients who received <5 mGy. Mathews et al.(2) showed that cancer incidence in the group undergoing CT examinations became 24% higher than that in the group in which CT examinations were not performed for children. In light of such knowledge, any medical staff must understand the importance of justification and optimization for pediatric CT examinations. In the optimization of the CT examination, it is necessary to fully understand the relationship between image quality and radiation dose. To this end, we have investigated organ doses and effective doses for pediatric patients undergoing CT examinations using in-phantom dosimetry systems consisting of small-sized photodiode dosimeters installed at various organ locations within pediatric physical phantoms(3–5). However, in these in-phantom dosimetry systems, only the point absorbed dose at the center of the gravity within each organ of a phantom is obtained. It is important to know the spatial dose distribution to implement better optimization of CT examinations. In general, the internal dose distribution in a phantom is often measured with X-ray film, imaging plate (IP) or Gafchromic film. Although these conventional methods can obtain dose distribution conveniently, special reading devices are required which are often expensive. Recently, we discovered that acrylic resin and water emit feeble light by X-ray irradiation at energy lower than 120 keV(6). We then tried imaging of luminescence from an acrylic plate during CT scans with effective energy of 50 keV. However, the luminance distribution in the acrylic plate was not detected as a result of the noise based on scattered rays from the CT gantry. Then, it occurred to us to use polyethylene terephthalate (PET) resin in place of acrylic resin, because it is known that PET resin has excellent performance as a plastic scintillator in radiation dosimetry(7). Therefore, in the present study, we devised a new dosimetry measurement method to estimate the internal dose distribution of a subject by imaging luminescence from PET resin using a high-sensitivity CCD camera. MATERIALS AND METHODS Dose distribution measurement system Figure 1 shows the schematic representation of the dose distribution imaging system we developed in the current study. The PET resin was commercially available clear resin plate of 1 cm thickness with the specific gravity of 1.27. The PET resin plate was circularly cut into a disk with the diameter of 15 cm, which represent the average head size(8) of Japanese 1-year-old patients. The high-sensitivity charge-coupled device (CCD) camera (BITRAN BS-40L, Japan) used in this study was monochrome type, the pixel size of 368 × 290 with 16 bit depth. The sensitivity of the CCD camera was highest for 500-nm light and lower than 60% of the peak sensitivity below 400 nm. To minimize background light detection by the CCD camera, a PET phantom was installed with the CCD camera in a black box (Figure 1). The CCD camera with a C-mount f-1.4 lens (Computar, Japan) was cooled to 3°C and set ~40 cm from the PET phantom surface. In addition, the cooled CCD camera was made with radiation protection using lead plates of 3 mm thickness and a lead glass of 12 mm thickness. The black box set the PET phantom and the CCD camera was arranged on a bed so that the center of the PET phantom aligned with the isocentre of a CT scanner. Imaging of luminescence from the PET phantom was conducted for 20 s under X-ray irradiations, and the luminescence images were automatically saved to a personal computer in Tagged Image File Format (TIFF) without compression. Figure 1. View largeDownload slide Schematic representation of the devised dose distribution imaging system. Figure 1. View largeDownload slide Schematic representation of the devised dose distribution imaging system. X-ray irradiation conditions X-ray irradiation to the PET phantom was performed with GE LightSpeed VCT (GE Healthcare, USA) (1) with the X-ray tube fixed at the 12 o'clock position and (2) with the X-ray tube rotated. The irradiation parameters were as follows: tube potential of 120 kVp, tube current of 200 mA, beam width of 0.625 mm × 64 (=40 mm) and irradiation time of 10 s. In the GE LightSpeed VCT, three types of bowtie filters: small, medium and large, were loaded. To investigate the difference in dose distribution in various bowtie filters, we evaluated the luminance distribution in the PET phantom under X-ray irradiation with and without the three types of bowtie filters. Image analysis All acquired images were processed using public domain software, ImageJ (National Institutes of Health, Bethesda, USA) on a personal computer. Since high-luminance noise spots were included in all images due to the direct detection of scattered X-ray photons by the CCD image sensor, the noise spots which are >50 pixels were eliminated and replaced by the median of the surrounding pixels. Background images acquired after X-ray irradiation were subtracted from each luminescence image after the noise removal processing to correct the non-uniformity and offset of the CCD camera. Dose calculation To estimate the absorbed dose in the human body from luminescence of PET resin, we investigated the correlation between luminance distribution in a PET phantom and dose distribution with water as a human body tissue-equivalent material. A water phantom of 15 cm diameter×10 cm was made with acrylic resin of 3 mm in thickness, and the dose distribution in the water phantom was estimated using a Monte Carlo simulation software: ImpactMC (Advanced Breast-CT GmbH, Germany). This simulation tool can automatically construct the voxelized computational phantoms from acquired CT images of patients or physical phantoms and provide quantitative 3D dose distribution of those subjects based on the geometrical characteristics of the CT scanner, X-ray spectrum and filteration(9). The geometrical characteristics in GE LightSpeed VCT were set based on the values reported in the previous paper of Chen et al.(10). The source-to-isocentre distance is 541 mm and the source-to-detector distance is 949 mm(10). According to the Technical Reference Manual: LightSpeed VCT 2008(11), the target angle is 7° and the focal spot size 0.6 × 0.7 mm2. The fan beam angle is 56°. The X-ray spectrum was estimated from a semi-empirical model developed by Tucker et al.(12). In the current study, we assumed that the bowtie filter is made of aluminum. The shape of each bowtie filter was estimated from measurements of aluminum attenuation and the dose profile along the fan angle direction. Aluminum attenuation measurements were performed with a 10-cm pencil ionization chamber (model 10X5-3CT; Radcal Corporation, USA) connected to an electrometer (model 9015; Radcal Corporation, USA) fixed at the isocentre. Aluminum filters with different thicknesses were placed between the chamber and the stationary X-ray source. Dose profiles in the fan beam angle direction were measured with the X-ray output analyzer (Piranha, RTI Electronics, Sweden) according to the method of McKenney et al.(13) The dose estimation with ImpactMC also requires a computational model of the object(14). In this study, 3D voxelized data of the produced water phantom were derived from the acquired CT images. The image data were converted to density values based on the linear relationship determined with an electron density phantom (Gammex, model 467, Middleton, USA). Each CT value for the water phantom images was assigned as air and water according to a user-defined segmentation of the Hounsfield units scale. The number of photons used for each simulation was 1.0 × 1010. In this study, the repeated error of the dose simulation in a water phantom was <1%. Simulated dose images were obtained in binary format and displayed as dose distribution images in which each pixel shows a dose value. RESULTS AND DISCUSSION Performance evaluation of bowtie filter based on luminance distribution of a PET phantom CT scanners are equipped with various functions to reduce the patient doses without loss of image quality. In particular, the bowtie filter has an important function to homogenize X-ray intensity distribution across the patient anatomy and the quality after having penetrated a subject. CT vendors provide several bowtie filters matched to the subject size. To investigate whether a bowtie filter matches the subject size and shape, the comparison of dose distribution between a simulation method and measurements is necessary. However, the quality of materials and the shape of bowtie filters have never been officially announced by any CT vendor. In GE LightSpeed VCT, available in small, medium and large filters, a small filter has been routinely used for infant head CT examinations. Figure 2 shows the equivalent Al thicknesses of the bowtie filters as a function of a fan beam angle measured in GE LightSpeed VCT according to the method of McKenney et al.(13) In the current study, the performance of these bowtie filters was evaluated based on luminance distribution of the PET phantom which imitated the average head size of a Japanese 1-year-old child. Figure 3 shows the pseudo images of luminance distribution in the PET phantom which were observed for X-ray tube fixed/rotated irradiation with and without bowtie filters. It is shown that the luminance distribution changed depending on the shape of bowtie filters. Figure 4 shows the plot profile of the mean pixel value of longitudinal 10 pixels in the region of interest (ROI) with the rectangular shape of 10 × 193 pixels put on each rotating image in Figure 3. Each pixel value was normalized at the maximum pixel value in each plot profile. It was found from Figure 4 that the luminance distribution is the most uniform in tube rotated irradiation with a small filter. Therefore, it was clearly defined from luminance distribution images of a PET phantom that the use of a small filter is suitable for infant head CT examinations. Figure 2. View largeDownload slide Equivalent aluminum (Al) thickness of the bowtie filter as a function of fan beam angle measured according to the method of McKenney et al.(13) in GE LightSpeed VCT. Figure 2. View largeDownload slide Equivalent aluminum (Al) thickness of the bowtie filter as a function of fan beam angle measured according to the method of McKenney et al.(13) in GE LightSpeed VCT. Figure 3. View largeDownload slide Pseudo color images of luminance distribution in a PET phantom. Upper row shows the luminance images in tube fixed irradiation at the 12 o'clock position with and without bowtie filter. Lower row shows the luminance images in tube rotated irradiation with and without bowtie filter. There are three kinds of bowtie filters; small, medium and large. The scale bar in the image is 30 mm. Figure 3. View largeDownload slide Pseudo color images of luminance distribution in a PET phantom. Upper row shows the luminance images in tube fixed irradiation at the 12 o'clock position with and without bowtie filter. Lower row shows the luminance images in tube rotated irradiation with and without bowtie filter. There are three kinds of bowtie filters; small, medium and large. The scale bar in the image is 30 mm. Figure 4. View largeDownload slide Comparison of relative luminance profiles in a PET phantom by tube rotated irradiation with and without bowtie filter. The scale bar in the image is 30 mm. Figure 4. View largeDownload slide Comparison of relative luminance profiles in a PET phantom by tube rotated irradiation with and without bowtie filter. The scale bar in the image is 30 mm. Correlation between luminance and dose distribution To convert luminance values of a PET phantom into absorbed doses for water as a human body equivalence material, it is necessary to investigate the correlation between luminance values of a PET phantom and the simulated absorbed doses in a water phantom. From Figure 3, however, the background brightness of each luminance distribution image was found to be different. This is because the air around the PET phantom is also luminous by X-ray irradiation. Therefore, the luminance distribution in the PET phantom itself might be affected by the luminescence of the air because the PET resin was clear. To remove the luminance effect in the air, the mean pixel value in the background region was subtracted from all pixel values within each tube fixed irradiation images using the ImageJ. The mean pixel value in the background was calculated in four ROIs with the square size of 20 × 20 pixels as shown in Figure 5a. Figure 5b shows a luminance distribution image after having subtracted the mean pixel value of the background from Figure 5a. On the other hand, Figure 5c shows dose simulation images in a water phantom by tube fixed irradiation without a bowtie filter. To investigate the correlation between the luminance value in a PET phantom and absorbed dose in a water phantom, the ROIs of 5 mm × 5 mm were set in the central location of luminance image/dose simulation image as shown in Figure 5b and the mean pixel values in each ROI in the luminance image and dose simulation image were compared. Figure 5d shows the correlation between the luminance value and the simulated absorbed dose for water in tube fixed irradiation without the bowtie filter and with the small filter. It is seen from Figure 5d that the simulated absorbed dose in the water phantom was proportional to the luminance value in the PET phantom, regardless of the presence or absence of the bowtie filter. Two linear regression equations were, respectively, y = 0.23x+31.6 (R2 = 0.996) without the bowtie filter and y = 0.23x+32.0 (R2 = 0.996) with the small filter. On the basis of these applied regression lines, we converted the luminance distribution image in a PET phantom into the water dose distribution image using the ImageJ. In Figure 6, the water dose distribution images which were converted from luminance distribution images in a PET phantom were compared with the dose simulation images in the water phantom without the bowtie filter and with the small filter. The dose distribution in the conversion images (Figure 6a and c) visually analogized with those in the dose simulation images (Figure 6b and d). Then, to investigate the relative differences (RDs) of dose values between conversion images and simulation images, the ROIs of 10 mm × 10 mm square were set at the illustrated positions in Figure 7 and the mean dose at each ROI in both images was compared. Table 1 shows the mean dose at each ROI in conversion images and simulation images without the bowtie filter and with the small filter and the RDs between both images. Here, the dose values in Table 1 were normalized to 100 mAs, and the RDs were calculated in the following equation: RD(%) = (converted doses − simulated doses)/simulated doses × 100. From Figure 7 and Table 1, it was found that the maximum RD was, respectively, −17.7% without bowtie filter and −19.5% with small filter. Also the mean RD was, respectively, −9.8% without bowtie filter and −10.6% with small filter. Furthermore, it is found from Table 1 that the RDs in the posterior side of the phantom were relatively larger than those in the anterior side. These differences in the positions would be due to the presence or absence of a bed in two dose evaluation methods. In this study, the dose simulation using ImpactMC did not consider the absorption of X-rays in a bed. However, the RDs between the converted water doses and the simulated water doses were within 20% in this study. Robert et al.(14) have shown that the accuracy of film dosimetry for CT dose measurements is ±15%. It also has been reported that the maximum differences between radiochromic film measurements and TLDs measurements was 25% in dental CT dosimetry(15). Therefore, we concluded that the dose distribution measurement method based on luminescence of a PET phantom has the similar accuracy as conventional methods. Figure 5. View largeDownload slide Correlation between luminance value in a PET phantom and the simulated absorbed dose in a water phantom. (a) The luminescence image in tube fixed irradiation without bowtie filter. The size of a ROI on the image is 20 × 20 pixels. (b) The luminescence image after having subtracted the mean pixel value in background from all pixel values in the image. White squares on the image show the positions which set ROIs of 5 mm × 5 mm for the measurement of the mean pixel value. (c) The dose simulation image in a water phantom by tube fixed irradiation without bowtie filter. (d) Graphs when plotted as luminance value vs absorbed dose without bowtie filter (black dot) and with small filter (white dot). The scale bar in the image is 30 mm. Figure 5. View largeDownload slide Correlation between luminance value in a PET phantom and the simulated absorbed dose in a water phantom. (a) The luminescence image in tube fixed irradiation without bowtie filter. The size of a ROI on the image is 20 × 20 pixels. (b) The luminescence image after having subtracted the mean pixel value in background from all pixel values in the image. White squares on the image show the positions which set ROIs of 5 mm × 5 mm for the measurement of the mean pixel value. (c) The dose simulation image in a water phantom by tube fixed irradiation without bowtie filter. (d) Graphs when plotted as luminance value vs absorbed dose without bowtie filter (black dot) and with small filter (white dot). The scale bar in the image is 30 mm. Figure 6. View largeDownload slide Comparison of the conversion images from luminance value to dose value and dose simulation images in a water phantom by tube rotated irradiation. (a) and (c) Conversion images from luminance value to dose value without bowtie filter and with small filter. (b) and (d) Dose simulation images without bowtie filter and with small filter. The scale bar in the image is 30 mm. Figure 6. View largeDownload slide Comparison of the conversion images from luminance value to dose value and dose simulation images in a water phantom by tube rotated irradiation. (a) and (c) Conversion images from luminance value to dose value without bowtie filter and with small filter. (b) and (d) Dose simulation images without bowtie filter and with small filter. The scale bar in the image is 30 mm. Figure 7. View largeDownload slide ROI positions for dose comparison with conversion images and simulation images. White squares on the image show the positions which set ROIs of 10 mm × 10 mm for the measurement of the mean pixel value on both images. The scale bar in the image is 30 mm. Figure 7. View largeDownload slide ROI positions for dose comparison with conversion images and simulation images. White squares on the image show the positions which set ROIs of 10 mm × 10 mm for the measurement of the mean pixel value on both images. The scale bar in the image is 30 mm. Table 1. Comparison of luminance measurements (LM) and MC simulations (MCS) for water doses normalized to 100 mAs with and without bowtie filter and relative differences (RD). No. of ROIs in Figure 7 BF(−) Small filter LM (mGy) MCS (mGy) RD (%) LM (mGy) MCS (mGy) RD (%) 1 23.4 23.0 1.7 16.4 16.3 0.6 2 22.7 22.8 −0.7 15.9 16.2 −1.9 3 21.9 23.2 −5.7 15.1 16.1 −6.2 4 20.2 22.8 −11.5 13.6 15.9 −14.5 5 20.1 23.2 −13.5 13.2 16.0 −17.5 6 20.4 22.7 −10.2 13.5 15.9 −15.1 7 22.2 23.0 −3.6 15.2 16.1 −5.6 8 22.7 22.6 0.3 15.8 16.1 −1.9 9 15.2 16.6 −8.3 12.5 13.5 −7.4 10 14.8 16.6 −10.4 12.2 13.4 −9.0 11 14.5 16.7 −13.0 11.7 13.4 −12.7 12 13.7 16.6 −17.2 11.1 13.3 −16.5 13 13.7 16.7 −17.7 10.8 13.4 −19.4 14 13.7 16.6 −17.0 11.0 13.3 −17.3 15 14.4 16.6 −13.5 11.7 13.4 −12.7 16 14.7 16.5 −10.7 12.2 13.4 −9.0 17 12.7 14.8 −14.2 10.6 12.3 −13.8 No. of ROIs in Figure 7 BF(−) Small filter LM (mGy) MCS (mGy) RD (%) LM (mGy) MCS (mGy) RD (%) 1 23.4 23.0 1.7 16.4 16.3 0.6 2 22.7 22.8 −0.7 15.9 16.2 −1.9 3 21.9 23.2 −5.7 15.1 16.1 −6.2 4 20.2 22.8 −11.5 13.6 15.9 −14.5 5 20.1 23.2 −13.5 13.2 16.0 −17.5 6 20.4 22.7 −10.2 13.5 15.9 −15.1 7 22.2 23.0 −3.6 15.2 16.1 −5.6 8 22.7 22.6 0.3 15.8 16.1 −1.9 9 15.2 16.6 −8.3 12.5 13.5 −7.4 10 14.8 16.6 −10.4 12.2 13.4 −9.0 11 14.5 16.7 −13.0 11.7 13.4 −12.7 12 13.7 16.6 −17.2 11.1 13.3 −16.5 13 13.7 16.7 −17.7 10.8 13.4 −19.4 14 13.7 16.6 −17.0 11.0 13.3 −17.3 15 14.4 16.6 −13.5 11.7 13.4 −12.7 16 14.7 16.5 −10.7 12.2 13.4 −9.0 17 12.7 14.8 −14.2 10.6 12.3 −13.8 Table 1. Comparison of luminance measurements (LM) and MC simulations (MCS) for water doses normalized to 100 mAs with and without bowtie filter and relative differences (RD). No. of ROIs in Figure 7 BF(−) Small filter LM (mGy) MCS (mGy) RD (%) LM (mGy) MCS (mGy) RD (%) 1 23.4 23.0 1.7 16.4 16.3 0.6 2 22.7 22.8 −0.7 15.9 16.2 −1.9 3 21.9 23.2 −5.7 15.1 16.1 −6.2 4 20.2 22.8 −11.5 13.6 15.9 −14.5 5 20.1 23.2 −13.5 13.2 16.0 −17.5 6 20.4 22.7 −10.2 13.5 15.9 −15.1 7 22.2 23.0 −3.6 15.2 16.1 −5.6 8 22.7 22.6 0.3 15.8 16.1 −1.9 9 15.2 16.6 −8.3 12.5 13.5 −7.4 10 14.8 16.6 −10.4 12.2 13.4 −9.0 11 14.5 16.7 −13.0 11.7 13.4 −12.7 12 13.7 16.6 −17.2 11.1 13.3 −16.5 13 13.7 16.7 −17.7 10.8 13.4 −19.4 14 13.7 16.6 −17.0 11.0 13.3 −17.3 15 14.4 16.6 −13.5 11.7 13.4 −12.7 16 14.7 16.5 −10.7 12.2 13.4 −9.0 17 12.7 14.8 −14.2 10.6 12.3 −13.8 No. of ROIs in Figure 7 BF(−) Small filter LM (mGy) MCS (mGy) RD (%) LM (mGy) MCS (mGy) RD (%) 1 23.4 23.0 1.7 16.4 16.3 0.6 2 22.7 22.8 −0.7 15.9 16.2 −1.9 3 21.9 23.2 −5.7 15.1 16.1 −6.2 4 20.2 22.8 −11.5 13.6 15.9 −14.5 5 20.1 23.2 −13.5 13.2 16.0 −17.5 6 20.4 22.7 −10.2 13.5 15.9 −15.1 7 22.2 23.0 −3.6 15.2 16.1 −5.6 8 22.7 22.6 0.3 15.8 16.1 −1.9 9 15.2 16.6 −8.3 12.5 13.5 −7.4 10 14.8 16.6 −10.4 12.2 13.4 −9.0 11 14.5 16.7 −13.0 11.7 13.4 −12.7 12 13.7 16.6 −17.2 11.1 13.3 −16.5 13 13.7 16.7 −17.7 10.8 13.4 −19.4 14 13.7 16.6 −17.0 11.0 13.3 −17.3 15 14.4 16.6 −13.5 11.7 13.4 −12.7 16 14.7 16.5 −10.7 12.2 13.4 −9.0 17 12.7 14.8 −14.2 10.6 12.3 −13.8 Limitations Our study had some limitations in the process that converted luminance distribution of a PET resin into the distribution of the absorbed dose for water. Generally, in dose simulation of CT examinations, it is difficult to perfectly reconstruct the highly complex CT geometries and scan parameters. In the previous studies(9, 16), the CTDI values which simulated using ImpactMC had been compared with the CTDI values which measured using head and body PMMA phantom of 16 and 32 cm in diameter and a 10-cm pencil-shaped ionization chamber. It was found that the RDs between the simulated and measured CTDI values were within ~10%. Hence, the simulated doses with a water phantom in our study would also have some uncertainties. Moreover, the correlation between luminance and dose may be different depending on scan parameters, the energy of X-rays, the scattered rays from CT gantry, the CT geometries such as the shape and materials of bowtie filters and so on. Another limitation of our study is that the dose measurement method developed in the current study only provides cross-sectional dose distribution of a phantom slice. It is impossible to evaluate the doses at the surface or the whole body of an anthropomorphic phantom. However, our method might be useful for the evaluation of internal dose distribution of patients in CT examinations with organ-based tube current modulation(17). Evaluating the dose distribution at a cross-section of the human body would be a help to estimate the homogeneity/heterogeneity of image quality in CT images because image noise depends on the absorbed dose. CONCLUSION We devised a new method to estimate internal dose distribution by imaging luminescence phenomenon in the PET resin with low-energy X-ray irradiation. This method makes it possible to measure dose distribution repeatedly without requiring special reading devices. Moreover, the PET resin is flexible to be fabricated into different shapes at relatively low cost. Since our method does not involve insertion between the slices of an anthropomorphic phantom, there is no need to worry about sensitivity unevenness due to air gaps and insufficient adhesion. Hence, by using our method, the estimation of dose distribution depending on the various shapes of patients could be carried out relatively easily. Since the head and abdominal cavity of infants have little fat, the border of the tissue and organ is unclear, and the size of the organ is much smaller than that of adults. Therefore, it is important to carefully investigate the internal dose distribution of infants undergoing CT examinations from the perspective of radiation protection. The new method for estimating the internal dose distribution devised in this study may well reduce radiation exposure in infant CT examinations. FUNDING This work was supported by Japan Society for the Promotion of Science (JSPS) KAKENHI (Grant number JP16K09014). REFERENCES 1 Pearce , M. S. et al. . 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Prot. Dosim. 165 ( 1-4 ), 166 – 171 ( 2015 ). Google Scholar CrossRef Search ADS 17 Yamauchi-Kawaura , C. , Yamauchi , M. , Imai , K. , Ikeda , M. and Aoyama , T. Image quality and age-specific dose estimation in head and chest CT examinations with organ-based tube-current modulation . Radiat. Prot. Dosim. 157 ( 2 ), 193 – 205 ( 2013 ). Google Scholar CrossRef Search ADS © The Author(s) 2018. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Radiation Protection Dosimetry Oxford University Press

MEASUREMENT OF INTERNAL RADIATION DOSE DISTRIBUTION IN CT EXAMINATIONS USING POLYETHYLENE TEREPHTHALATE RESIN

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© The Author(s) 2018. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com
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Abstract

ABSTRACT This study proposes a new dosimetry method for the estimation of the internal radiation dose distribution of a subject undergoing computed tomography (CT) examinations. In this novel method, dose distribution of a subject by CT scans was estimated based on radiophotoluminance distribution with polyethylene terephthalate (PET) resin which was cut to the average head size of a Japanese 1-year-old child. The difference in dose distribution depending on the type of bowtie filter was visualized by imaging luminance distribution with the PET phantom using a charge-coupled device camera. Dose distribution images simulated from a water phantom of the same size as the PET phantom were compared with the luminance distribution images. The linear correlation was demonstrated between luminance of the PET phantom and the simulated water dose. In comparison with the simulated water doses and the converted water doses from luminance of the PET phantom, the relative differences were within 20%. INTRODUCTION In recent years the potential risk of radiation exposure in pediatric computed tomography (CT) examinations has become a major concern worldwide. This is because the carcinogenic risk for pediatric patients who underwent CT examinations has been confirmed in a couple of epidemiological studies. Pearce et al.(1,) reported that when the cumulative dose of brain or red bone marrow in a pediatric patient undergoing CT examinations becomes ~50–60 mGy, the risk of brain tumors or leukemia becomes almost three times greater compared with patients who received <5 mGy. Mathews et al.(2) showed that cancer incidence in the group undergoing CT examinations became 24% higher than that in the group in which CT examinations were not performed for children. In light of such knowledge, any medical staff must understand the importance of justification and optimization for pediatric CT examinations. In the optimization of the CT examination, it is necessary to fully understand the relationship between image quality and radiation dose. To this end, we have investigated organ doses and effective doses for pediatric patients undergoing CT examinations using in-phantom dosimetry systems consisting of small-sized photodiode dosimeters installed at various organ locations within pediatric physical phantoms(3–5). However, in these in-phantom dosimetry systems, only the point absorbed dose at the center of the gravity within each organ of a phantom is obtained. It is important to know the spatial dose distribution to implement better optimization of CT examinations. In general, the internal dose distribution in a phantom is often measured with X-ray film, imaging plate (IP) or Gafchromic film. Although these conventional methods can obtain dose distribution conveniently, special reading devices are required which are often expensive. Recently, we discovered that acrylic resin and water emit feeble light by X-ray irradiation at energy lower than 120 keV(6). We then tried imaging of luminescence from an acrylic plate during CT scans with effective energy of 50 keV. However, the luminance distribution in the acrylic plate was not detected as a result of the noise based on scattered rays from the CT gantry. Then, it occurred to us to use polyethylene terephthalate (PET) resin in place of acrylic resin, because it is known that PET resin has excellent performance as a plastic scintillator in radiation dosimetry(7). Therefore, in the present study, we devised a new dosimetry measurement method to estimate the internal dose distribution of a subject by imaging luminescence from PET resin using a high-sensitivity CCD camera. MATERIALS AND METHODS Dose distribution measurement system Figure 1 shows the schematic representation of the dose distribution imaging system we developed in the current study. The PET resin was commercially available clear resin plate of 1 cm thickness with the specific gravity of 1.27. The PET resin plate was circularly cut into a disk with the diameter of 15 cm, which represent the average head size(8) of Japanese 1-year-old patients. The high-sensitivity charge-coupled device (CCD) camera (BITRAN BS-40L, Japan) used in this study was monochrome type, the pixel size of 368 × 290 with 16 bit depth. The sensitivity of the CCD camera was highest for 500-nm light and lower than 60% of the peak sensitivity below 400 nm. To minimize background light detection by the CCD camera, a PET phantom was installed with the CCD camera in a black box (Figure 1). The CCD camera with a C-mount f-1.4 lens (Computar, Japan) was cooled to 3°C and set ~40 cm from the PET phantom surface. In addition, the cooled CCD camera was made with radiation protection using lead plates of 3 mm thickness and a lead glass of 12 mm thickness. The black box set the PET phantom and the CCD camera was arranged on a bed so that the center of the PET phantom aligned with the isocentre of a CT scanner. Imaging of luminescence from the PET phantom was conducted for 20 s under X-ray irradiations, and the luminescence images were automatically saved to a personal computer in Tagged Image File Format (TIFF) without compression. Figure 1. View largeDownload slide Schematic representation of the devised dose distribution imaging system. Figure 1. View largeDownload slide Schematic representation of the devised dose distribution imaging system. X-ray irradiation conditions X-ray irradiation to the PET phantom was performed with GE LightSpeed VCT (GE Healthcare, USA) (1) with the X-ray tube fixed at the 12 o'clock position and (2) with the X-ray tube rotated. The irradiation parameters were as follows: tube potential of 120 kVp, tube current of 200 mA, beam width of 0.625 mm × 64 (=40 mm) and irradiation time of 10 s. In the GE LightSpeed VCT, three types of bowtie filters: small, medium and large, were loaded. To investigate the difference in dose distribution in various bowtie filters, we evaluated the luminance distribution in the PET phantom under X-ray irradiation with and without the three types of bowtie filters. Image analysis All acquired images were processed using public domain software, ImageJ (National Institutes of Health, Bethesda, USA) on a personal computer. Since high-luminance noise spots were included in all images due to the direct detection of scattered X-ray photons by the CCD image sensor, the noise spots which are >50 pixels were eliminated and replaced by the median of the surrounding pixels. Background images acquired after X-ray irradiation were subtracted from each luminescence image after the noise removal processing to correct the non-uniformity and offset of the CCD camera. Dose calculation To estimate the absorbed dose in the human body from luminescence of PET resin, we investigated the correlation between luminance distribution in a PET phantom and dose distribution with water as a human body tissue-equivalent material. A water phantom of 15 cm diameter×10 cm was made with acrylic resin of 3 mm in thickness, and the dose distribution in the water phantom was estimated using a Monte Carlo simulation software: ImpactMC (Advanced Breast-CT GmbH, Germany). This simulation tool can automatically construct the voxelized computational phantoms from acquired CT images of patients or physical phantoms and provide quantitative 3D dose distribution of those subjects based on the geometrical characteristics of the CT scanner, X-ray spectrum and filteration(9). The geometrical characteristics in GE LightSpeed VCT were set based on the values reported in the previous paper of Chen et al.(10). The source-to-isocentre distance is 541 mm and the source-to-detector distance is 949 mm(10). According to the Technical Reference Manual: LightSpeed VCT 2008(11), the target angle is 7° and the focal spot size 0.6 × 0.7 mm2. The fan beam angle is 56°. The X-ray spectrum was estimated from a semi-empirical model developed by Tucker et al.(12). In the current study, we assumed that the bowtie filter is made of aluminum. The shape of each bowtie filter was estimated from measurements of aluminum attenuation and the dose profile along the fan angle direction. Aluminum attenuation measurements were performed with a 10-cm pencil ionization chamber (model 10X5-3CT; Radcal Corporation, USA) connected to an electrometer (model 9015; Radcal Corporation, USA) fixed at the isocentre. Aluminum filters with different thicknesses were placed between the chamber and the stationary X-ray source. Dose profiles in the fan beam angle direction were measured with the X-ray output analyzer (Piranha, RTI Electronics, Sweden) according to the method of McKenney et al.(13) The dose estimation with ImpactMC also requires a computational model of the object(14). In this study, 3D voxelized data of the produced water phantom were derived from the acquired CT images. The image data were converted to density values based on the linear relationship determined with an electron density phantom (Gammex, model 467, Middleton, USA). Each CT value for the water phantom images was assigned as air and water according to a user-defined segmentation of the Hounsfield units scale. The number of photons used for each simulation was 1.0 × 1010. In this study, the repeated error of the dose simulation in a water phantom was <1%. Simulated dose images were obtained in binary format and displayed as dose distribution images in which each pixel shows a dose value. RESULTS AND DISCUSSION Performance evaluation of bowtie filter based on luminance distribution of a PET phantom CT scanners are equipped with various functions to reduce the patient doses without loss of image quality. In particular, the bowtie filter has an important function to homogenize X-ray intensity distribution across the patient anatomy and the quality after having penetrated a subject. CT vendors provide several bowtie filters matched to the subject size. To investigate whether a bowtie filter matches the subject size and shape, the comparison of dose distribution between a simulation method and measurements is necessary. However, the quality of materials and the shape of bowtie filters have never been officially announced by any CT vendor. In GE LightSpeed VCT, available in small, medium and large filters, a small filter has been routinely used for infant head CT examinations. Figure 2 shows the equivalent Al thicknesses of the bowtie filters as a function of a fan beam angle measured in GE LightSpeed VCT according to the method of McKenney et al.(13) In the current study, the performance of these bowtie filters was evaluated based on luminance distribution of the PET phantom which imitated the average head size of a Japanese 1-year-old child. Figure 3 shows the pseudo images of luminance distribution in the PET phantom which were observed for X-ray tube fixed/rotated irradiation with and without bowtie filters. It is shown that the luminance distribution changed depending on the shape of bowtie filters. Figure 4 shows the plot profile of the mean pixel value of longitudinal 10 pixels in the region of interest (ROI) with the rectangular shape of 10 × 193 pixels put on each rotating image in Figure 3. Each pixel value was normalized at the maximum pixel value in each plot profile. It was found from Figure 4 that the luminance distribution is the most uniform in tube rotated irradiation with a small filter. Therefore, it was clearly defined from luminance distribution images of a PET phantom that the use of a small filter is suitable for infant head CT examinations. Figure 2. View largeDownload slide Equivalent aluminum (Al) thickness of the bowtie filter as a function of fan beam angle measured according to the method of McKenney et al.(13) in GE LightSpeed VCT. Figure 2. View largeDownload slide Equivalent aluminum (Al) thickness of the bowtie filter as a function of fan beam angle measured according to the method of McKenney et al.(13) in GE LightSpeed VCT. Figure 3. View largeDownload slide Pseudo color images of luminance distribution in a PET phantom. Upper row shows the luminance images in tube fixed irradiation at the 12 o'clock position with and without bowtie filter. Lower row shows the luminance images in tube rotated irradiation with and without bowtie filter. There are three kinds of bowtie filters; small, medium and large. The scale bar in the image is 30 mm. Figure 3. View largeDownload slide Pseudo color images of luminance distribution in a PET phantom. Upper row shows the luminance images in tube fixed irradiation at the 12 o'clock position with and without bowtie filter. Lower row shows the luminance images in tube rotated irradiation with and without bowtie filter. There are three kinds of bowtie filters; small, medium and large. The scale bar in the image is 30 mm. Figure 4. View largeDownload slide Comparison of relative luminance profiles in a PET phantom by tube rotated irradiation with and without bowtie filter. The scale bar in the image is 30 mm. Figure 4. View largeDownload slide Comparison of relative luminance profiles in a PET phantom by tube rotated irradiation with and without bowtie filter. The scale bar in the image is 30 mm. Correlation between luminance and dose distribution To convert luminance values of a PET phantom into absorbed doses for water as a human body equivalence material, it is necessary to investigate the correlation between luminance values of a PET phantom and the simulated absorbed doses in a water phantom. From Figure 3, however, the background brightness of each luminance distribution image was found to be different. This is because the air around the PET phantom is also luminous by X-ray irradiation. Therefore, the luminance distribution in the PET phantom itself might be affected by the luminescence of the air because the PET resin was clear. To remove the luminance effect in the air, the mean pixel value in the background region was subtracted from all pixel values within each tube fixed irradiation images using the ImageJ. The mean pixel value in the background was calculated in four ROIs with the square size of 20 × 20 pixels as shown in Figure 5a. Figure 5b shows a luminance distribution image after having subtracted the mean pixel value of the background from Figure 5a. On the other hand, Figure 5c shows dose simulation images in a water phantom by tube fixed irradiation without a bowtie filter. To investigate the correlation between the luminance value in a PET phantom and absorbed dose in a water phantom, the ROIs of 5 mm × 5 mm were set in the central location of luminance image/dose simulation image as shown in Figure 5b and the mean pixel values in each ROI in the luminance image and dose simulation image were compared. Figure 5d shows the correlation between the luminance value and the simulated absorbed dose for water in tube fixed irradiation without the bowtie filter and with the small filter. It is seen from Figure 5d that the simulated absorbed dose in the water phantom was proportional to the luminance value in the PET phantom, regardless of the presence or absence of the bowtie filter. Two linear regression equations were, respectively, y = 0.23x+31.6 (R2 = 0.996) without the bowtie filter and y = 0.23x+32.0 (R2 = 0.996) with the small filter. On the basis of these applied regression lines, we converted the luminance distribution image in a PET phantom into the water dose distribution image using the ImageJ. In Figure 6, the water dose distribution images which were converted from luminance distribution images in a PET phantom were compared with the dose simulation images in the water phantom without the bowtie filter and with the small filter. The dose distribution in the conversion images (Figure 6a and c) visually analogized with those in the dose simulation images (Figure 6b and d). Then, to investigate the relative differences (RDs) of dose values between conversion images and simulation images, the ROIs of 10 mm × 10 mm square were set at the illustrated positions in Figure 7 and the mean dose at each ROI in both images was compared. Table 1 shows the mean dose at each ROI in conversion images and simulation images without the bowtie filter and with the small filter and the RDs between both images. Here, the dose values in Table 1 were normalized to 100 mAs, and the RDs were calculated in the following equation: RD(%) = (converted doses − simulated doses)/simulated doses × 100. From Figure 7 and Table 1, it was found that the maximum RD was, respectively, −17.7% without bowtie filter and −19.5% with small filter. Also the mean RD was, respectively, −9.8% without bowtie filter and −10.6% with small filter. Furthermore, it is found from Table 1 that the RDs in the posterior side of the phantom were relatively larger than those in the anterior side. These differences in the positions would be due to the presence or absence of a bed in two dose evaluation methods. In this study, the dose simulation using ImpactMC did not consider the absorption of X-rays in a bed. However, the RDs between the converted water doses and the simulated water doses were within 20% in this study. Robert et al.(14) have shown that the accuracy of film dosimetry for CT dose measurements is ±15%. It also has been reported that the maximum differences between radiochromic film measurements and TLDs measurements was 25% in dental CT dosimetry(15). Therefore, we concluded that the dose distribution measurement method based on luminescence of a PET phantom has the similar accuracy as conventional methods. Figure 5. View largeDownload slide Correlation between luminance value in a PET phantom and the simulated absorbed dose in a water phantom. (a) The luminescence image in tube fixed irradiation without bowtie filter. The size of a ROI on the image is 20 × 20 pixels. (b) The luminescence image after having subtracted the mean pixel value in background from all pixel values in the image. White squares on the image show the positions which set ROIs of 5 mm × 5 mm for the measurement of the mean pixel value. (c) The dose simulation image in a water phantom by tube fixed irradiation without bowtie filter. (d) Graphs when plotted as luminance value vs absorbed dose without bowtie filter (black dot) and with small filter (white dot). The scale bar in the image is 30 mm. Figure 5. View largeDownload slide Correlation between luminance value in a PET phantom and the simulated absorbed dose in a water phantom. (a) The luminescence image in tube fixed irradiation without bowtie filter. The size of a ROI on the image is 20 × 20 pixels. (b) The luminescence image after having subtracted the mean pixel value in background from all pixel values in the image. White squares on the image show the positions which set ROIs of 5 mm × 5 mm for the measurement of the mean pixel value. (c) The dose simulation image in a water phantom by tube fixed irradiation without bowtie filter. (d) Graphs when plotted as luminance value vs absorbed dose without bowtie filter (black dot) and with small filter (white dot). The scale bar in the image is 30 mm. Figure 6. View largeDownload slide Comparison of the conversion images from luminance value to dose value and dose simulation images in a water phantom by tube rotated irradiation. (a) and (c) Conversion images from luminance value to dose value without bowtie filter and with small filter. (b) and (d) Dose simulation images without bowtie filter and with small filter. The scale bar in the image is 30 mm. Figure 6. View largeDownload slide Comparison of the conversion images from luminance value to dose value and dose simulation images in a water phantom by tube rotated irradiation. (a) and (c) Conversion images from luminance value to dose value without bowtie filter and with small filter. (b) and (d) Dose simulation images without bowtie filter and with small filter. The scale bar in the image is 30 mm. Figure 7. View largeDownload slide ROI positions for dose comparison with conversion images and simulation images. White squares on the image show the positions which set ROIs of 10 mm × 10 mm for the measurement of the mean pixel value on both images. The scale bar in the image is 30 mm. Figure 7. View largeDownload slide ROI positions for dose comparison with conversion images and simulation images. White squares on the image show the positions which set ROIs of 10 mm × 10 mm for the measurement of the mean pixel value on both images. The scale bar in the image is 30 mm. Table 1. Comparison of luminance measurements (LM) and MC simulations (MCS) for water doses normalized to 100 mAs with and without bowtie filter and relative differences (RD). No. of ROIs in Figure 7 BF(−) Small filter LM (mGy) MCS (mGy) RD (%) LM (mGy) MCS (mGy) RD (%) 1 23.4 23.0 1.7 16.4 16.3 0.6 2 22.7 22.8 −0.7 15.9 16.2 −1.9 3 21.9 23.2 −5.7 15.1 16.1 −6.2 4 20.2 22.8 −11.5 13.6 15.9 −14.5 5 20.1 23.2 −13.5 13.2 16.0 −17.5 6 20.4 22.7 −10.2 13.5 15.9 −15.1 7 22.2 23.0 −3.6 15.2 16.1 −5.6 8 22.7 22.6 0.3 15.8 16.1 −1.9 9 15.2 16.6 −8.3 12.5 13.5 −7.4 10 14.8 16.6 −10.4 12.2 13.4 −9.0 11 14.5 16.7 −13.0 11.7 13.4 −12.7 12 13.7 16.6 −17.2 11.1 13.3 −16.5 13 13.7 16.7 −17.7 10.8 13.4 −19.4 14 13.7 16.6 −17.0 11.0 13.3 −17.3 15 14.4 16.6 −13.5 11.7 13.4 −12.7 16 14.7 16.5 −10.7 12.2 13.4 −9.0 17 12.7 14.8 −14.2 10.6 12.3 −13.8 No. of ROIs in Figure 7 BF(−) Small filter LM (mGy) MCS (mGy) RD (%) LM (mGy) MCS (mGy) RD (%) 1 23.4 23.0 1.7 16.4 16.3 0.6 2 22.7 22.8 −0.7 15.9 16.2 −1.9 3 21.9 23.2 −5.7 15.1 16.1 −6.2 4 20.2 22.8 −11.5 13.6 15.9 −14.5 5 20.1 23.2 −13.5 13.2 16.0 −17.5 6 20.4 22.7 −10.2 13.5 15.9 −15.1 7 22.2 23.0 −3.6 15.2 16.1 −5.6 8 22.7 22.6 0.3 15.8 16.1 −1.9 9 15.2 16.6 −8.3 12.5 13.5 −7.4 10 14.8 16.6 −10.4 12.2 13.4 −9.0 11 14.5 16.7 −13.0 11.7 13.4 −12.7 12 13.7 16.6 −17.2 11.1 13.3 −16.5 13 13.7 16.7 −17.7 10.8 13.4 −19.4 14 13.7 16.6 −17.0 11.0 13.3 −17.3 15 14.4 16.6 −13.5 11.7 13.4 −12.7 16 14.7 16.5 −10.7 12.2 13.4 −9.0 17 12.7 14.8 −14.2 10.6 12.3 −13.8 Table 1. Comparison of luminance measurements (LM) and MC simulations (MCS) for water doses normalized to 100 mAs with and without bowtie filter and relative differences (RD). No. of ROIs in Figure 7 BF(−) Small filter LM (mGy) MCS (mGy) RD (%) LM (mGy) MCS (mGy) RD (%) 1 23.4 23.0 1.7 16.4 16.3 0.6 2 22.7 22.8 −0.7 15.9 16.2 −1.9 3 21.9 23.2 −5.7 15.1 16.1 −6.2 4 20.2 22.8 −11.5 13.6 15.9 −14.5 5 20.1 23.2 −13.5 13.2 16.0 −17.5 6 20.4 22.7 −10.2 13.5 15.9 −15.1 7 22.2 23.0 −3.6 15.2 16.1 −5.6 8 22.7 22.6 0.3 15.8 16.1 −1.9 9 15.2 16.6 −8.3 12.5 13.5 −7.4 10 14.8 16.6 −10.4 12.2 13.4 −9.0 11 14.5 16.7 −13.0 11.7 13.4 −12.7 12 13.7 16.6 −17.2 11.1 13.3 −16.5 13 13.7 16.7 −17.7 10.8 13.4 −19.4 14 13.7 16.6 −17.0 11.0 13.3 −17.3 15 14.4 16.6 −13.5 11.7 13.4 −12.7 16 14.7 16.5 −10.7 12.2 13.4 −9.0 17 12.7 14.8 −14.2 10.6 12.3 −13.8 No. of ROIs in Figure 7 BF(−) Small filter LM (mGy) MCS (mGy) RD (%) LM (mGy) MCS (mGy) RD (%) 1 23.4 23.0 1.7 16.4 16.3 0.6 2 22.7 22.8 −0.7 15.9 16.2 −1.9 3 21.9 23.2 −5.7 15.1 16.1 −6.2 4 20.2 22.8 −11.5 13.6 15.9 −14.5 5 20.1 23.2 −13.5 13.2 16.0 −17.5 6 20.4 22.7 −10.2 13.5 15.9 −15.1 7 22.2 23.0 −3.6 15.2 16.1 −5.6 8 22.7 22.6 0.3 15.8 16.1 −1.9 9 15.2 16.6 −8.3 12.5 13.5 −7.4 10 14.8 16.6 −10.4 12.2 13.4 −9.0 11 14.5 16.7 −13.0 11.7 13.4 −12.7 12 13.7 16.6 −17.2 11.1 13.3 −16.5 13 13.7 16.7 −17.7 10.8 13.4 −19.4 14 13.7 16.6 −17.0 11.0 13.3 −17.3 15 14.4 16.6 −13.5 11.7 13.4 −12.7 16 14.7 16.5 −10.7 12.2 13.4 −9.0 17 12.7 14.8 −14.2 10.6 12.3 −13.8 Limitations Our study had some limitations in the process that converted luminance distribution of a PET resin into the distribution of the absorbed dose for water. Generally, in dose simulation of CT examinations, it is difficult to perfectly reconstruct the highly complex CT geometries and scan parameters. In the previous studies(9, 16), the CTDI values which simulated using ImpactMC had been compared with the CTDI values which measured using head and body PMMA phantom of 16 and 32 cm in diameter and a 10-cm pencil-shaped ionization chamber. It was found that the RDs between the simulated and measured CTDI values were within ~10%. Hence, the simulated doses with a water phantom in our study would also have some uncertainties. Moreover, the correlation between luminance and dose may be different depending on scan parameters, the energy of X-rays, the scattered rays from CT gantry, the CT geometries such as the shape and materials of bowtie filters and so on. Another limitation of our study is that the dose measurement method developed in the current study only provides cross-sectional dose distribution of a phantom slice. It is impossible to evaluate the doses at the surface or the whole body of an anthropomorphic phantom. However, our method might be useful for the evaluation of internal dose distribution of patients in CT examinations with organ-based tube current modulation(17). Evaluating the dose distribution at a cross-section of the human body would be a help to estimate the homogeneity/heterogeneity of image quality in CT images because image noise depends on the absorbed dose. CONCLUSION We devised a new method to estimate internal dose distribution by imaging luminescence phenomenon in the PET resin with low-energy X-ray irradiation. This method makes it possible to measure dose distribution repeatedly without requiring special reading devices. Moreover, the PET resin is flexible to be fabricated into different shapes at relatively low cost. Since our method does not involve insertion between the slices of an anthropomorphic phantom, there is no need to worry about sensitivity unevenness due to air gaps and insufficient adhesion. Hence, by using our method, the estimation of dose distribution depending on the various shapes of patients could be carried out relatively easily. Since the head and abdominal cavity of infants have little fat, the border of the tissue and organ is unclear, and the size of the organ is much smaller than that of adults. Therefore, it is important to carefully investigate the internal dose distribution of infants undergoing CT examinations from the perspective of radiation protection. The new method for estimating the internal dose distribution devised in this study may well reduce radiation exposure in infant CT examinations. FUNDING This work was supported by Japan Society for the Promotion of Science (JSPS) KAKENHI (Grant number JP16K09014). REFERENCES 1 Pearce , M. S. et al. . 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Google Scholar CrossRef Search ADS PubMed 13 McKenney , S. E. , Nosratieh , A. , Gelskey , D. , Yang , K. , Huang , S. Y. , Chen , L. and Boone , J. M. Experimental validation of a method characterizing bow tie filters in CT scanners using a real-time dose probe . Med. Phys. 38 , 1406 – 1415 ( 2011 ). Google Scholar CrossRef Search ADS PubMed 14 Dixon , R. L. and Ekstrand , K. E. A film dosimetry system for use in computed tomography . Radiology 127 ( 1 ), 255 – 258 ( 1978 ). Google Scholar CrossRef Search ADS PubMed 15 Rampado , O. , Bianchi , S. D. , Peruzzo Cornetto , A. , Rossetti , V. and Ropolo , R. Radiochromic films for dental CT dosimetry: a feasibility study . Phys. Med. 30 , 18 – 24 ( 2014 ). Google Scholar CrossRef Search ADS PubMed 16 Fujii , K. , Nomura , K. , Muramatsu , Y. , Takahashi , K. , Obara , S. , Akahane , K. and Satake , M. Evaluation of organ doses in adult and paediatric CT examinations based on Monte Carlo simulations and in-phantom dosimetry . Radiat. Prot. Dosim. 165 ( 1-4 ), 166 – 171 ( 2015 ). Google Scholar CrossRef Search ADS 17 Yamauchi-Kawaura , C. , Yamauchi , M. , Imai , K. , Ikeda , M. and Aoyama , T. Image quality and age-specific dose estimation in head and chest CT examinations with organ-based tube-current modulation . Radiat. Prot. Dosim. 157 ( 2 ), 193 – 205 ( 2013 ). Google Scholar CrossRef Search ADS © The Author(s) 2018. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

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Radiation Protection DosimetryOxford University Press

Published: Feb 12, 2018

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