• Progress in Medical Physics
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• v.20 no.4
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• pp.216-224
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• 2009

$^{131}I$ is a radiological isotope being used widely for treatment of cancer as emitting gamma-ray and it is also applied to estimate the function of thyroid for its accumulation in thyroid. However, $^{131}I$ is more difficult to quantitate comapred to $^{99m}Tc$, because $^{131}I$ has multiple energy gamma-ray emissions compared to $^{99m}Tc$ which is a mono energetic gamma-ray source. Especially, scattered ray and septal penetration resulted by high energy gamma ray have a bad influence upon nuclear medicine image. The purpose of this study was to estimate scatter components depending on the different source locations within a phantom using Monte Carlo simulation (GATE). The simulation results were validated by comparing with the results of real experiments. Dual-head gamma camera (ECAM, Chicago, Illinois Siemens) with high energy, general-purpose, and parallel hole collimators (hole radius: 0.17 cm, septal thickness: 0.2 cm, length: 5.08 cm) was used in this experiment. The NaI crystal is $44.5{\times}59.1\;cm$ in height and width and 0.95 cm in thickness. The diameter and height of PMMA phantom were 16 cm and 15 cm, respectively. The images were acquired at 5 different locations of $^{131}I$ point source within the phantom and the images of $^{99m}Tc$ were also acquired for comparison purpose with low energy source. The simulation results indicated that the scattering was influenced by the location of source within a phantom. The scattering effects showed the same tendency in both simulation and actual experiment, and the results showed that the simulation was very adequate for further studies. The results supported that the simulation techniques may be used to generalize the scattering effects as a function of a point source location within a phantom.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.1
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• pp.122-126
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• 2010

Purpose: F-18-FPCIT that shows strong familiarity with DAT located at a neural terminal site offers diagnostic information about DAT density state in the region of the striatum especially Parkinson's disease. In this study, we altered the iteration and subset and measured SUV${\pm}$SD and Contrasts from phantom images which set up to specific iteration and subset. So, we are going to suggest the appropriate range of the iteration and subset. Materials and Methods: This study has been performed with 10 normal volunteers who don't have any history of Parkinson's disease or cerebral disease and Flangeless Esser PET Phantom from Data Spectrum Corporation. $5.3{\pm}0.2$ mCi of F-18-FPCIT was injected to the normal group and PET Phantom was assembled by ACR PET Phantom Instructions and it's actual ratio between hot spheres and background was 2.35 to 1. Brain and Phantom images were acquired after 3 hours from the time of the injection and images were acquired for ten minutes. Basically, SIEMENS Bio graph 40 True-point was used and True-X method was applied for image reconstruction method. The iteration and Subset were set to 2 iterations, 8 subsets, 3 iterations, 16 subsets, 6 iterations, 16 subsets, 8 iterations, 16 subsets and 8 iterations, 21 subsets respectively. To measure SUVs on the brain images, ROIs were drawn on the right Putamen. Also, Coefficient of variance (CV) was calculated to indicate the uniformity at each iteration and subset combinations. On the phantom study, we measured the actual ratio between hot spheres and back ground at each combinations. Same size's ROIs were drawn on the same slide and location. Results: Mean SUVs were 10.60, 12.83, 13.87, 13.98 and 13.5 at each combination. The range of fluctuation by sets were 22.36%, 10.34%, 1.1%, and 4.8% respectively. The range of fluctuation of mean SUV was lowest between 6 iterations 16 subsets and 8 iterations 16 subsets. CV showed 9.07%, 11.46%, 13.56%, 14.91% and 19.47% respectively. This means that the numerical value of the iteration and subset gets higher the image's uniformity gets worse. The range of fluctuation of CV by sets were 2.39, 2.1, 1.35, and 4.56. The range of fluctuation of uniformity was lowest between 6 iterations, 16 subsets and 8 iterations, 16 subsets. In the contrast test, it showed 1.92:1, 2.12:1, 2.10:1, 2.13:1 and 2.11:1 at each iteration and subset combinations. A Setting of 8 iterations and 16 subsets reappeared most close ratio between hot spheres and background. Conclusion: Findings on this study, SUVs and uniformity might be calculated differently caused by variable reconstruction parameters like filter or FWHM. Mean SUV and uniformity showed the lowest range of fluctuation at 6 iterations 16 subsets and 8 iterations 16 subsets. Also, 8 iterations 16 subsets showed the nearest hot sphere to background ratio compared with others. But it can not be concluded that only 6 iterations 16 subsets and 8 iterations 16 subsets can make right images for the clinical diagnosis. There might be more factors that can make better images. For more exact clinical diagnosis through the quantitative analysis of DAT density in the region of striatum we need to secure healthy people's quantitative values.

• The Korean Journal of Nuclear Medicine Technology
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• v.15 no.1
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• pp.17-24
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• 2011

Purpose: Presently in the nuclear medicine field, the high-speed image reconstruction algorithm like the OSEM algorithm is widely used as the alternative of the filtered back projection method due to the rapid development and application of the digital computer. There is no to relate and if it applies the optimal parameter be clearly determined. In this research, the quality change of the Jaszczak phantom experiment and brain SPECT patient data according to the iteration times and subset number change try to be been put through and analyzed in 3D OSEM reconstruction method of applying 3D beam modeling. Materials and Methods: Patient data from August, 2010 studied and analyzed against 5 patients implementing the brain SPECT until september, 2010 in the nuclear medicine department of ASAN medical center. The phantom image used the mixed Jaszczak phantom equally and obtained the water and 99mTc (500 MBq) in the dual head gamma camera Symbia T2 of Siemens. When reconstructing each image altogether with patient data and phantom data, we changed iteration number as 1, 4, 8, 12, 24 and 30 times and subset number as 2, 4, 8, 16 and 32 times. We reconstructed in reconstructed each image, the variation coefficient for guessing about noise of images and image contrast, FWHM were produced and compared. Results: In patients and phantom experiment data, a contrast and spatial resolution of an image showed the tendency to increase linearly altogether according to the increment of the iteration times and subset number but the variation coefficient did not show the tendency to be improved according to the increase of two parameters. In the comparison according to the scan time, the image contrast and FWHM showed altogether the result of being linearly improved according to the iteration times and subset number increase in projection per 10, 20 and 30 second image but the variation coefficient did not show the tendency to be improved. Conclusion: The linear relationship of the image contrast improved in 3D OSEM reconstruction method image of applying 3D beam modeling through this experiment like the existing 1D and 2D OSEM reconfiguration method according to the iteration times and subset number increase could be confirmed. However, this is simple phantom experiment and the result of obtaining by the some patients limited range and the various variables can be existed. So for generalizing this based on this results of this experiment, there is the excessiveness and the evaluation about 3D OSEM reconfiguration method should be additionally made through experiments after this.

• The Korean Journal of Nuclear Medicine Technology
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• v.15 no.1
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• pp.10-16
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• 2011

Purpose: The partial volume effect occurs because of limit of the spatial resolution. It makes partial loss of intensity and causes SUV to be lower than it should actually be. So the purpose of this study is to calculate recovery coefficient for correcting PVE from phantom study and to compare before and after SUV correction applying to PET/CT examination. Materials and Methods: The flangeless Esser PET phantom consisting of four hot cylinders was used for this study. All of the hot cylinders were filled with FDG solution of 20.72 MBq per 1000 ml, and the phantom background was filled with FDG solution of different concentrations (33.30, 22.20, 16.65 MBq per 6440 ml) to yield H/B ratios of around 4:1, 6:1 and 8:1. Using the Biograph Truepoint 40(SIEMENS, Germany), we applied recovery coefficient method to 30 patients who were diagnosed with lung cancer after PET/CT exam. And then we analyzed and compared SUV before and after correcting partial volume effect. Results: The smaller the diameter of hot cylinder becomes, the more recovery coefficient decreased. When we applied recovery coefficient to clinical patients and compared SUV before and after correcting PVE, before the correction all lesions gave an average max SUV of 7.83. And after the correction, the average max SUV increases to 10.31. The differences in the max SUV between before and after correction were analyzed by paired t test. As a result, there were statistically significant differences (t=7.21, p=0.000). Conclusion: The SUV for quantification should be measured precisely to give consistent information of tumor uptake. But PVE is one of factors that causes SUV to be lower and to be underestimated. We can correct this PVE and calculate corrected SUV using the recovery coefficient from phantom study. And if we apply this correction method to clinical patients, we can finally assess and provide quantitative analysis more accurately.

• Korean Journal of Digital Imaging in Medicine
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• v.14 no.1
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• pp.1-6
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• 2012

This round of tests in patients with UGI and Esophagography data collected by national and international reference levels based on the original set of guidelines and fluoroscopy, through the provision of medical radiation exposure reduction and further optimization of Defense to realize that is intended. 359 names in our hospital underwent Esophagography 302 patients who underwent UGI average fluoroscopy time and number of images to calculate the average 21 cm Acryl phantom dose for 10 seconds and 20 seconds, average area dose and the area dose of 1 spot image, 5 spot consecutive images by measuring the patient dose and third quartile of the mean area dose was set seonryangin reference dose. Esophagography average patient dose was set to 30.05 $Gy{\cdot}cm^2$, DRL was set at a 25.37 $Gy{\cdot}cm^2$. Average dose of UGI patients were selected as 45.33 $Gy{\cdot}cm^2$, DRL was set at a 34 $Gy{\cdot}cm^2$. UGI patients with established average dose recommended in the 2008 national recommendation from the UGI examination with a dose of less than 49.7 $Gy{\cdot}cm^2$ seonryangin is evaluated. This Note examines the dose of self-aware through education recognizes the importance of dose reduction and examine if their efforts and further reduce patient dose could achieve optimization of the medical exposure is considered.

• Imaging Science in Dentistry
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• v.48 no.1
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• pp.31-39
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• 2018

Purpose: This study aimed to evaluate the effect of field-of-view (FOV) size on the gray values derived from cone-beam computed tomography (CBCT) compared with the Hounsfield unit values from multidetector computed tomography (MDCT) scans as the gold standard. Materials and Methods: A radiographic phantom was designed with 4 acrylic cylinders. One cylinder was filled with distilled water, and the other 3 were filled with 3 types of bone substitute: namely, Nanobone, Cenobone, and Cerabone. The phantom was scanned with 2 CBCT systems using 2 different FOV sizes, and 1 MDCT system was used as the gold standard. The mean gray values(MGVs) of each cylinder were calculated in each imaging protocol. Results: In both CBCT systems, significant differences were noted in the MGVs of all materials between the 2 FOV sizes(P<.05) except for Cerabone in the Cranex3D system. Significant differences were found in the MGVs of each material compared with the others in both FOV sizes for each CBCT system. No significant difference was seen between the Cranex3D CBCT system and the MDCT system in the MGVs of bone substitutes on images obtained with a small FOV. Conclusion: The size of the FOV significantly changed the MGVs of all bone substitutes, except for Cerabone in the Cranex3D system. Both CBCT systems had the ability to distinguish the 3 types of bone substitutes based on a comparison of their MGVs. The Cranex3D CBCT system used with a small FOV had a significant correlation with MDCT results.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2006.08a
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• pp.91-91
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• 2006

• Proceedings of the Korean Society of Medical Physics Conference
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• 2003.09a
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• pp.67-67
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• 2003

It is crucial to minimize setup errors of a cancer treatment machine using a high energy and to perform precise radiation therapy. Usually, port film has been used for verifying errors. The Korea Cancer Center Hospital (KCCH) has manufactured digital electronic portal imaging device (EPID) system to verify treatment machine errors as a Quality Assurance (Q.A) tool. This EPID was consisted of a metal/fluorescent screen, 45$^{\circ}$ mirror, a camera and an image grabber and could display the portal image with near real time KIRAMS has also made the acrylic phantom that has lead line of 1mm width for ligh/radiation field congruence verification and reference points phantom for using as an isocenter on portal image. We acquired portal images of 10$\times$10cm field size with this phantom by EPID and portal film rotating treatment head by 0.3$^{\circ}$, 0.6$^{\circ}$ and 0.9$^{\circ}$. To check field size, we acquired portal images with 18$\times$18cm, 19$\times$19cm and 20$\times$20cm field size with collimator angle 0$^{\circ}$ and 0.5$^{\circ}$ individually. We have performed Flatness comparison by displaying the line intensity from EPID and film images. The 0.6$^{\circ}$ shift of collimator angle was easily observed by edge detection of irradiated field size on EPID image. To the extent of one pixel (0.76mm) difference could be detected. We also have measured field size by finding optimal threshold value, finding isocenter, finding field edge and gauging distance between isocenter and edge. This EPID system could be used as a Q.A tool for checking field size, light/radiation congruence and flatness with a developed video based EPID.

• Progress in Medical Physics
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• v.10 no.2
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• pp.73-81
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• 1999

Scatter correction for single photon emission computed tomography (SPECT) plays an important role to improve image quality and quantitation. The purpose of this study was to investigate three scatter correction methods using Monte Carlo simulation. Point source and Jaszack phantom filled with Tc-99m were simulated by Monte Carlo code, SIMIND. For scatter correction, we applied three methods, Compton window (CW) method, triple window (TW) method, and dual photopeak window (DPW) method. Point sources located at various depths along the center line within a 20-cm phantom were simulated to calculate the window ratios and corresponding scatter fractions by evaluating the polynomial coefficients for DPW method. Energy windows were located in W$_1$=92-125 keV, W$_2$=124-126 keV, W$_3$=136-140 keV, W$_4$=140-141 keV, and W$_{5}$=154-156 keV. The results showed that in Jaszack phantom with cold sphere and hot sphere, the TW gave the closest contrast and percentage recovery to the ideal image, respectively, while CW overestimated and DPW underestimated the contrast of ideal one. All three scatter correction methods showed an improved image contrast. In conclusion, scatter correction is essential for improving image contrast and accurate quantification. The choice of scatter correction method should be made on the basis of accuracies and ease of implementation.

• Progress in Medical Physics
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• v.19 no.3
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• pp.178-185
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• 2008

Living donor liver transplantation is increasingly performed as an alternative to cadaveric transplantation. Preoperative screening of the donor candidates is very important. The quality, size, and vascular and biliary anatomy of the liver are best assessed with magnetic resonance (MR) imaging or computed tomography (CT). In particular, the volume of the potential graft must be measured to ensure sufficient liver function after surgery. Preoperative liver segmentation has proved useful for measuring the graft volume before living donor liver transplantations in previous studies. In these studies, the liver segments were manually delineated on each image section. The delineated areas were multiplied by the section thickness to obtain volumes and summed to obtain the total volume of the liver segments. This process is tedious and time consuming. To compensate for this problem, automatic segmentation techniques have been proposed with multiplanar CT images. These methods involve the use of sequences of thresholding, morphologic operations (ie, mathematic operations, such as image dilation, erosion, opening, and closing, that are based on shape), and 3D region growing methods. These techniques are complex but require a few computation times. We made a phantom for volume measurement with pig and evaluated actual volume of spleen and liver of phantom. The results represent that our semiautomatic volume measurement algorithm shows a good accuracy and repeatability with actual volume of phantom and possibility for clinical use to assist physician as a measuring tool.