• The Korean Journal of Nuclear Medicine
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• v.39 no.3
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• pp.182-190
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• 2005

Purpose: There are differences between Standard Uptake Value (SUV) of CT attenuation corrected PET and that of $^{137}Cs$. Since various causes lead to difference of SUV, it is important to know what is the cause of these difference. Since only the X-ray CT and $^{137}Cs$ transmission data are used for the attenuation correction, in Philips GEMINI PET/CT scanner, proper transformation of these data into usable attenuation coefficients for 511 keV photon has to be ascertained. The aim of this study was to evaluate the accuracy in the CT measurement and compare the CT and $^{137}Cs$-based attenuation correction in this scanner. Methods: For all the experiments, CT was set to 40 keV (120 kVp) and 50 mAs. To evaluate the accuracy of the CT measurement, CT performance phantom was scanned and Hounsfield units (HU) for those regions were compared to the true values. For the comparison of CT and $^{137}Cs$-based attenuation corrections, transmission scans of the elliptical lung-spine-body phantom and electron density CT phantom composed of various components, such as water, bone, brain and adipose, were performed using CT and $^{137}Cs$. Transformed attenuation coefficients from these data were compared to each other and true 511 keV attenuation coefficient acquired using $^{68}Ge$ and ECAT EXACT 47 scanner. In addition, CT and $^{137}Cs$-derived attenuation coefficients and SUV values for $^{18}F$-FDG measured from the regions with normal and pathological uptake in patients' data were also compared. Results: HU of all the regions in CT performance phantom measured using GEMINI PET/CT were equivalent to the known true values. CT based attenuation coefficients were lower than those of $^{68}Ge$ about 10% in bony region of NEMA ECT phantom. Attenuation coefficients derived from $^{137}Cs$ data was slightly higher than those from CT data also in the images of electron density CT phantom and patients' body with electron density. However, the SUV values in attenuation corrected images using $^{137}Cs$ were lower than images corrected using CT. Percent difference between SUV values was about 15%. Conclusion: Although the HU measured using this scanner was accurate, accuracy in the conversion from CT data into the 511 keV attenuation coefficients was limited in the bony region. Discrepancy in the transformed attenuation coefficients and SUV values between CT and $^{137}Cs$-based data shown in this study suggests that further optimization of various parameters in data acquisition and processing would be necessary for this scanner.

• Journal of the Korean Society of Radiology
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• v.16 no.6
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• pp.771-778
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• 2022

The purpose of this study is to present a method of measuring noise by the percentage of effective line attenuation coefficient of water that can be used for quality control of CT image noise using AAPM CT performance phantom in clinical practice. In the CT images obtained by scanning the AAPM CT performance phantom with a 120 kVp CT X-ray beam, the mean CT number was measured for each pin and water in the CT number linearity insert part. The effective energy was determined as the photon energy with the largest correlation coefficient from the correlation coefficients of the linear regression analysis of the measured mean CT number for each pin and water and the linear attenuation coefficient for each photon energy. And for water and acrylic, the contrast scale was calculated as 0.000188 cm^-1 · HU^-1 from the measured mean CT number and effective line attenuation coefficient. Using the calculated contrast scale, the effective line attenuation coefficient of water, and the standard deviation measured in the water of the alignment pin part of the AAPM CT performance phantom, The noise measurement value by the percentage of effective line attenuation coefficient of water obtained 0.31 ~ 0.52% in the range of 100 ~ 300 mAs.

• Journal of the Korean Society of Radiology
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• v.13 no.4
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• pp.517-522
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• 2019

The purpose of this study is to determine the effective energy of CT X-ray beams by using the CT slice images of a CT number calibration insert part in the AAPM CT performance phantom. The CT number calibration insert part in the AAPM CT performance phantom was scanned five times by using a CT canner for 80, 100 and 120 kVp X-ray beams. The average value of CT numbers of each pin were measured for each CT slice image. The correlation coefficients were obtained by linear fit between the average value of CT numbers measured and liner attenuation coefficient under different energy at each pin calculated from data of NIST. A photon energy corresponding to the maximum value of the obtained correlation coefficient was determined as an effective energy. As a result, the effective energy was 56, 62 and 66~67 keV, respectively, for 80, 100 and 120 kVp X-ray beams.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.437-444
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• 2021

The aim of this study was to compare the cardiac CT and cardiac MRI in calculating and correcting the left ventricle ejection fraction by analyzing the physical and temporal resolution for reducing the misdiagnosis rate. One hundred thirty-eight patients with aortic value regurgitation who underwent both cardiac CT and cardiac MRI were analyzed. Left ventricle ejection fractions calculated from each exam were corrected based on the physical and temporal resolution differences and the reliability test evaluated whether the misdiagnosis rate of cardiac CT was improved after the correction. As a result of the study, the misdiagnosis rate of cardiac CT ejection fraction before correcting the difference in physical and temporal resolution was 38.4%(53 persons). In addition, it can be seen that the corrected cardiac CT ejection fraction confirmed in the Bland-Altman plot was highly consistent with the ejection fraction of cardiac MRI. In conclusion, as the cardiac CT is less well suited for measuring ejection fraction, physical characteristics and the time resolution correction using cardiac MRI is needed and the misdiagnosis rate after correction decreased to 14.5%(20 persons). Therefore, this study appears more appropriate for better prediction of ejection fraction and clinical utility.

• The Korean Journal of Nuclear Medicine Technology
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• v.20 no.2
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• pp.21-26
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• 2016

Purpose Because of many advantages, PET-CT Scanners generally use CT Data for attenuation correction. By using CT based attenuation correction, we can get anatomical information, reduce scan time and make more accurate correction of attenuation. However in case metal artifact occurred during CT scan, CT-based attenuation correction can induce artifacts and quantitative errors that can affect the PET images. Therefore this study infers true SUV of metal artifact region from attenuation corrected image count -to- non attenuation corrected image count ratio. Materials and Methods Micro phantom inserted $^{18}F-FDG$ 4mCi was used for phantom test and Biograph mCT S(40) is used for medical test equipment. We generated metal artifact in micro phantom by using metal. Then we acquired both metal artifact region of correction factor and non metal artifact region of correction factor by using attenuation correction image count -to- non attenuation correction image count ratio. In case of clinical image, we reconstructed both attenuation corrected images and non attenuation corrected images of 10 normal patient($66{\pm}15age$) who examined PET-CT scan in SNUH. After that, we standardize several organs of correction factor by using attenuation corrected image count -to- non attenuation corrected count ratio. Then we figured out metal artifact region of correction factor by using metal artifact region of attenuation corrected image count -to- non attenuation corrected count ratio And we compared standard organs correction factor with metal artifact region correction factor. Results according to phantom test results, metal artifact induce overestimation of correction factor so metal artifact region of correction factors are 12% bigger than the non metal artifact region of correction factors. in case of clinical test, correction factor of organs with high CT number(>1000) is $8{\pm}0.5%$, correction factor of organs with CT number similar to soft tissue is $6{\pm}2%$ and correction factor of organs with low CT number(-100>) is $3{\pm}1%$. Also metal artifact correction factors are 20% bigger than soft tissue correction factors which didn't happened metal artifact. Conclusion metal artifact lead to overestimation of attenuation coefficient. because of that, SUV of metal artifact region is overestimated. Thus for more accurate quantitative evaluation, using attenuation correction image count -to-non attenuation correction image count ratio is one of the methods to reduce metal artifact affect.

• Journal of the Korean Society of Radiology
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• v.3 no.3
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• pp.13-21
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• 2009

PET/CT is a machine for imaging in vivo functions or metabolic activities after the administration of radiopharmaceuticals labeled with radioisotope emitting positrons in the body. Recently the number of PET/CT installed in Korean medical institutions is increasing rapidly. In response, the number of PET/CT tests to be used in the diagnosis and treatment of tumors is also increasing every year, and this is increasing the necessity for developing the methods of PET/CT performance evaluation and quality control. Among the test items for the performance evaluation and quality control of PET/CT suggested in NU 2-2007, this study examined spatial resolution test, sensitivity test, image quality, attenuation accuracy & scatter correction test, scatter fraction, count losses and randoms test and accuracy( correction for count losses and randoms).

• Korean Journal of Digital Imaging in Medicine
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• v.9 no.1
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• pp.21-30
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• 2007

Our objective was to evaluate the CT attenuation coefficient and noise of spatial domain filtering as an alternative to additional image reconstruction using different kernels in abdominal CT. Derived from thin collimated source images was generated using abdomen B10 (very smooth), B20 (smooth), B30 (medium smooth), B40 (medium), B50 (medium sharp), B60 (sharp), B70 (very sharp) and B80 (ultra sharp) kernels. Quantitative CT coefficient and noise measurements provided comparable HU (hounsfield) units in this respect. CT attenuation coefficient (mean HU) values in the abdominal were 60.4$\sim$62.2 HU and noise (7.6$\sim$63.8 HU) in the liver parenchyma. In the stomach a mean (CT attenuation coefficient) of -2.2$\sim$0.8 HU and noise (10.1$\sim$82.4 HU) was measured. Image reconstructed with a convolution kernel led to an increase in noise, whereas the results for CT attenuation coefficient were comparable. Image medications of image sharpness and noise eliminate the need for reconstruction using different kernels in the future. CT images increase the diagnostic accuracy may be controlled by adjusting CT various kernels, which should be adjusted to take into account the kernels of the CT undergoing the examination.

• The Korean Journal of Nuclear Medicine Technology
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• v.13 no.3
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• pp.31-42
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• 2009

Purpose: As the number of domestic medical institutions installing PET/CT is increasing rapidly, the transfer of PET/CT images among medical institutions is also increasing. Thus, it is necessary to collect the comparative SUV data from several medical institutions' PET/CT systems through a phantom study which semi-quantitatively compares the SUV on one bed, the change scale of the SUV on the slices, and the time of measuring. The phantom study to find differences among the SUVs from various PET/CT offers the opportunity to obtain the reliability of the SUV in PET/CT images. Materials and Methods: Ten PET/CT systems from medical institutions in Korea were used. To obtain the accurate data, the study has been using the radiation detector of Korea Research Institute of Standards and Science to verify. The internal structures of NEMA $phantom^{TM}$ were removed and Six thousand milliliters of distilled water which has 1mCi of $^{18}F$-FDG put into the phantom. The water was properly integrated with $^{18}F$-FDG using magnetic stirrer. The images were acquired at 60, 70, 80, 90, 100, 110 and 120-minutes for 3 minute each. Two hundred square centimeters of region of interests were placed and analyzed. To confirm the usefulness, the correction-table came out from patients' data. Results: The coefficient of variability of the SUV from -11.0 to 9.90 % fell into the range of international standards(${\pm}10%$) along with the SUV on a bed, the change scale of the SUV on the slices, and the time of measuring, except one PET/CT system. Using the data of the differences among the SUVs, we came to withdraw the correction-table ranging from 0.803 to 1.246. The correction-table was confirmed its usefulness through Linear Regression Analysis which was applied to normal cases. Conclusions: Although studies have been made on the variation of the SUV, there is little attention on the standardization of the SUV. Based on this study of the quantitatively comparable data about the SUV accommodating the correction-table, it would help to have more corrective diagnosis.

• The Korean Journal of Nuclear Medicine Technology
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• v.19 no.2
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• pp.93-101
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• 2015

Purpose In SPECT image, scatter count is the cause of quantitative count error and image quality degradation. Thus, a wide range of scatter correction(SC) methods have been studied and this study is to evaluate the accuracy of CT based SC(CTSC) used in SPECT/CT as the comparison with existing energy window based SC(EWSC). Materials and Methods SPECT/CT images were obtained after filling air in order to acquire a reference image without the influence of scatter count inside the Triple line insert phantom setting hot rod(74.0 MBq) in the middle and each SPECT/CT image was obtained each separately after filling water instead of air in order to derive the influence of scatter count under the same conditions. In both conditions, Astonish(iterative : 4 subset : 16) reconstruction method and CT attenuation correction were commonly applied and three types of SC methods such as non-scatter correction(NSC), EWSC, CTSC were used in images filled with image. For EWSC, 9 sub-energy windows were set additionally in addition to main(=peak) energy window(140 keV, 20%) and then, images were acquired at the same time and five types of EWSC including DPW(dual photo-peak window)10%, DEW(dual energy window)20%, TEW(triple energy window)10%, TEW5.0%, TEW2.5% were used. Under the condition without fluctuations in primary count, total count was measured by drawing volume of interest (VOI) in the images of the two conditions and then, the ratio of scatter count of total counts was calculated as percent scatter fraction(%SF) and the count error with image filled with water was evaluated with percent normalized mean-square error(%NMSE) based on the image filled with air. Results Based on the image filled with air, %SF of images filled with water to which each SC method was applied is NSC 37.44, DPW 27.41, DEW 21.84, TEW10% 19.60, TEW5% 17.02, TEW2.5% 14.68, CTSC 5.57 and the most scattering counts were removed in CTSC and %NMSE is NSC 35.80, DPW 14.28, DEW 7.81, TEW10% 5.94, TEW5% 4.21, TEW2.5% 2.96, CTSC 0.35 and the error in CTSC was found to be the lowest. Conclusion In SPECT/CT images, the application of each scatter correction method used in the experiment could improve the quantitative count error caused by the influence of scatter count. In particular, CTSC showed the lowest %NMSE(=0.35) compared to existing EWSC methods, enabling relatively accurate scatter correction.

• Journal of radiological science and technology
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• v.31 no.1
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• pp.71-81
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• 2008

Our objective was to evaluate the image of spatial domain filtering as an alternative to additional image reconstruction using different kernels in MDCT. Derived from thin collimated source images were generated using water phantom and abdomen B10(very smooth), B20(smooth), B30(medium smooth), B40 (medium), B50(medium sharp), B60(sharp), B70(very sharp) and B80(ultra sharp) kernels. MTF and spatial resolution measured with various convolution kernels. Quantitative CT attenuation coefficient and noise measurements provided comparable HU(Hounsfield) units in this respect. CT attenuation coefficient(mean HU) values in the water were values in the water were $1.1{\sim}1.8\;HU$, air($-998{\sim}-1000\;HU$) and noise in the water($5.4{\sim}44.8\;HU$), air($3.6{\sim}31.4\;HU$). In the abdominal fat a CT attenuation coefficient($-2.2{\sim}0.8\;HU$) and noise($10.1{\sim}82.4\;HU$) was measured. In the abdominal was CT attenuation coefficient($53.3{\sim}54.3\;HU$) and noise($10.4{\sim}70.7\;HU$) in the muscle and in the liver parenchyma of CT attenuation coefficient($60.4{\sim}62.2\;HU$) and noise ($7.6{\sim}63.8\;HU$) in the liver parenchyma. Image reconstructed with a convolution kernel led to an increase in noise, whereas the results for CT attenuation coefficient were comparable. Image scanned with a high convolution kernel(B80) led to an increase in noise, whereas the results for CT attenuation coefficient were comparable. Image medications of image sharpness and noise eliminate the need for reconstruction using different kernels in the future. Adjusting CT various kernels, which should be adjusted to take into account the kernels of the CT undergoing the examination, may control CT images increase the diagnostic accuracy.