• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.95-108
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• 2017

Recently, AlphaGo which is Bakuk (Go) artificial intelligence program by Google DeepMind, had a huge victory against Lee Sedol. Many people thought that machines would not be able to win a man in Go games because the number of paths to make a one move is more than the number of atoms in the universe unlike chess, but the result was the opposite to what people predicted. After the match, artificial intelligence technology was focused as a core technology of the fourth industrial revolution and attracted attentions from various application domains. Especially, deep learning technique have been attracted as a core artificial intelligence technology used in the AlphaGo algorithm. The deep learning technique is already being applied to many problems. Especially, it shows good performance in image recognition field. In addition, it shows good performance in high dimensional data area such as voice, image and natural language, which was difficult to get good performance using existing machine learning techniques. However, in contrast, it is difficult to find deep leaning researches on traditional business data and structured data analysis. In this study, we tried to find out whether the deep learning techniques have been studied so far can be used not only for the recognition of high dimensional data but also for the binary classification problem of traditional business data analysis such as customer churn analysis, marketing response prediction, and default prediction. And we compare the performance of the deep learning techniques with that of traditional artificial neural network models. The experimental data in the paper is the telemarketing response data of a bank in Portugal. It has input variables such as age, occupation, loan status, and the number of previous telemarketing and has a binary target variable that records whether the customer intends to open an account or not. In this study, to evaluate the possibility of utilization of deep learning algorithms and techniques in binary classification problem, we compared the performance of various models using CNN, LSTM algorithm and dropout, which are widely used algorithms and techniques in deep learning, with that of MLP models which is a traditional artificial neural network model. However, since all the network design alternatives can not be tested due to the nature of the artificial neural network, the experiment was conducted based on restricted settings on the number of hidden layers, the number of neurons in the hidden layer, the number of output data (filters), and the application conditions of the dropout technique. The F1 Score was used to evaluate the performance of models to show how well the models work to classify the interesting class instead of the overall accuracy. The detail methods for applying each deep learning technique in the experiment is as follows. The CNN algorithm is a method that reads adjacent values from a specific value and recognizes the features, but it does not matter how close the distance of each business data field is because each field is usually independent. In this experiment, we set the filter size of the CNN algorithm as the number of fields to learn the whole characteristics of the data at once, and added a hidden layer to make decision based on the additional features. For the model having two LSTM layers, the input direction of the second layer is put in reversed position with first layer in order to reduce the influence from the position of each field. In the case of the dropout technique, we set the neurons to disappear with a probability of 0.5 for each hidden layer. The experimental results show that the predicted model with the highest F1 score was the CNN model using the dropout technique, and the next best model was the MLP model with two hidden layers using the dropout technique. In this study, we were able to get some findings as the experiment had proceeded. First, models using dropout techniques have a slightly more conservative prediction than those without dropout techniques, and it generally shows better performance in classification. Second, CNN models show better classification performance than MLP models. This is interesting because it has shown good performance in binary classification problems which it rarely have been applied to, as well as in the fields where it's effectiveness has been proven. Third, the LSTM algorithm seems to be unsuitable for binary classification problems because the training time is too long compared to the performance improvement. From these results, we can confirm that some of the deep learning algorithms can be applied to solve business binary classification problems.

• The Korean Journal of Nuclear Medicine
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• v.1 no.1
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• pp.55-66
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• 1967

In view of its prevalence in the Far East area, a more detailed knowledge on the hookworm infection is one of the very important medical problems. The present study was aimed to; determine the infectivity of the artificially hatched ancylostoma duodenale larvae in man after its oral administration, evaluate the clinical symptomatology of such infection, determine the date of first appearance of the ova in the stool, calculate the blood loss per worm per day, assess the relation-ships between the ova count, infectivity(worm load), blood loss and severity of anemia. An erythrokinetic study was also done to analyse the characteristics of hookworm anemia by means of $^{59}Fe\;and\;^{51}Cr$. Materials and Methods Ten healthy male volunteers(doctors, medical students and laboratory technicians) with the ages ranging from 21 to 40 years were selected as the experimental materials. They had no history of hookworm infection for preceding several years, and care was taken not to be exposed to reinfection. A baseline study including a through physical examinations and laboratory investigations such as complete blood counts, stool examination and estimation of the serum iron levels was done, and a vermifuge, bephenium hydroxynaphoate, was given 10 days prior to the main experiment. The ancylostoma duodenale filariform larvae were obtained in the following manner; The pure ancylostoma duodenale ova were obtained from the hookworm anemia patients and a modified filter paper method was adopted to harvest larger number of infective larvae, which were washed several times with saline. The actively moving mature larvae were put into the gelatine capsules, 150 in each, and were given to the volunteers in the fasting state with 300ml. of water. The volunteers were previously treated with intramuscular injection of 15mg. of chlorpromazine in order to prevent the eventual nausea and vomiting after the larvae intake. The clinical symptoms and signs mainly of the respiratory and gastrointestinal tracts, appearance of the ova and occult blood in the stool etc. were checked every day for the first 20 days and then twice weekly until the end of the experiment, which usually lasted for about 3 months. Roentgenological survey of the lungs was also done. The hematological changes such as the red blood cell, white blood cell and eosinophil cell counts, hemoglobin content and serum iron levels were studied. The appearance of the ova in the stool was examined by the formalin ether method and the ova were counted in triplicate on two successive days using the Stoll's dilution method. The ferrokinetic data were calculated by the modified Huff's method and the apparent half survival time of the red blood cells by the modified Gray's method. The isotopes were simultaneously tagged and injected intravenously, and then the stool and blood samples were collected as was described by Roche et al., namely, three separate 4-day stool samples with the blood sample drawing before each 4-day stool collection. The radio-activities of the stools ashfied and the blood were separately measured by the pulse-height analyser. The daily blood loss was calculated with the following formula; daily blood loss in $ml.=\frac{cpm/g\;stool{\times}weight\;in\;g\;of\;4-day\;stool}{cpm/ml\;blood{\times}4}$ The average of these three 4-day periods was given as the daily blood loss in each patient. The blood loss per day per worm was calculated by simply dividing the daily blood loss by the number of the hookworm recovered after the vermifuge given twice a week at the termination of the experiment. The iron loss in mg. through the gastrointestinal tract was estimated with the daily iron loss in $mg=\frac{g\;Hgb/100ml{\times}ml\;daily\;blood\;loss{\times}3.40}{100}$ 3.40=mg of iron per g Hgb following formula; Results 1. The respiratory symptoms such as cough and sputum were noted in almost all cases within a week after the infection, which lasted about 2 weeks. The roentgenological findings of the chest were essentially normal. A moderate degree of febril reaction appeared within 2 weeks with a duration of 3 or 4 days. 2. The gastrointestinal symptoms such as nausea, epigastric fullness, abdominal pain and loose bowel appeared in all cases immediately after the larvae intake. 3. The reduction of the red blood cell count was not remarkable, however, the hemoglobin content and especially the serum iron level showed the steady decreases until the end of the experiment. 4. The white blood cells and eosinophil cells, on the contrary, showed increases in parallel and reached peaks in 20 to 30 days after the infection. A small secondary rise was noted in 2 months. 5. The ova first appeared in the stool in 40. 1 days after the infection, ranging from 29 to 51 days, during which the occult blood reaction of the stool became also positive in almost cases. 6. The number of ova recovered per day was 164, 320 on the average, ranging from 89,500 to 253,800. The number of the worm evacuated by vermifuge was in rough correlation with the number of ova recovered. 7. The infectivity of ancylostoma duodenale was 14% on the average, ranging from 7.3 to 20.0%, which is relatively lower than those reported by other workers. 8. The mean fecal blood loss was 5.78ml. per day, with a range of from 2.6 to 11.7ml., and the mean blood loss per worm per day was 0.30ml., with a range of from 0.13 to 0.73ml., which is in rough coincidence with those reported by other authors. There appeared to exist, however, no correlation between the blood loss and the number of ova recovered. 9. The mean fecal iron loss was 2.02mg. per day, with a range of from 1.20 to 3.89mg., which is less than those appeared in the literature. 10. The mean plasma iron disappearance rate was 0.80hr., with a range of from 0.62 to 0.95hr., namely, a slight accerelation. 11. The hookworm anemia appeared to be iron deficiency in origin caused by continuous intestinal blood loss.

• The Korean Journal of Nuclear Medicine Technology
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• v.13 no.3
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• pp.102-109
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• 2009

Purpose: Flash 3D (pixon(R) method; 3D OSEM) was developed as a software program to shorten exam time and improve image quality through reconstruction, it is an image processing method that usefully be applied to nuclear medicine tomography. If perfoming brain diamox perfusion scan by reconstructing subtracted images by Flash 3D with shortened image acquisition time, there was a problem that SNR of subtracted image is lower than basal image. To increase SNR of subtracted image, we use LEAP collimators, and we emphasized on sensitivity of vessel dilatation than resolution of brain vessel. In this study, our purpose is to confirm possibility of application of LEAP collimators at brain diamox perfusion tomography, identify proper reconstruction factors by using Flash 3D. Materials and methods: (1) The evaluation of phantom: We used Hoffman 3D Brain Phantom with $^{99m}Tc$. We obtained images by LEAP and LEHR collimators (diamox image) and after 6 hours (the half life of $^{99m}Tc$: 6 hours), we use obtained second image (basal image) by same method. Also, we acquired SNR and ratio of white matters/gray matters of each basal image and subtracted image. (2) The evaluation of patient's image: We quantitatively analyzed patients who were examined by LEAP collimators then was classified as a normal group and who were examined by LEHR collimators then was classified as a normal group from 2008. 05 to 2009. 01. We evaluate the results from phantom by substituting factors. We used one-day protocol and injected $^{99m}Tc$-ECD 925 MBq at both basal image acquisition and diamox image acquisition. Results: (1) The evaluation of phantom: After measuring counts from each detector, at basal image 41~46 kcount, stress image 79~90 kcount, subtraction image 40~47 kcount were detected. LEAP was about 102~113 kcount at basal image, 188~210 kcount at stress image and 94~103 at subtraction image kcount were detected. The SNR of LEHR subtraction image was decreased than LEHR basal image about 37%, the SNR of LEAP subtraction image was decreased than LEAP basal image about 17%. The ratio of gray matter versus white matter is 2.2:1 at LEHR basal image and 1.9:1 at subtraction, and at LEAP basal image was 2.4:1 and subtraction image was 2:1. (2) The evaluation of patient's image: the counts acquired by LEHR collimators are about 40~60 kcounts at basal image, and 80~100 kcount at stress image. It was proper to set FWHM as 7 mm at basal and stress image and 11mm at subtraction image. LEAP was about 80~100 kcount at basal image and 180~200 kcount at stress image. LEAP images could reduce blurring by setting FWHM as 5 mm at basal and stress images and 7 mm at subtraction image. At basal and stress image, LEHR image was superior than LEAP image. But in case of subtraction image like a phantom experiment, it showed rough image because SNR of LEHR image was decreased. On the other hand, in case of subtraction LEAP image was better than LEHR image in SNR and sensitivity. In all LEHR and LEAP collimator images, proper subset and iteration frequency was 8 times. Conclusions: We could archive more clear and high SNR subtraction image by using proper filter with LEAP collimator. In case of applying one day protocol and reconstructing by Flash 3D, we could consider application of LEAP collimator to acquire better subtraction image.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.167-181
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• 2018

Over the past decade, deep learning has been in spotlight among various machine learning algorithms. In particular, CNN(Convolutional Neural Network), which is known as the effective solution for recognizing and classifying images or voices, has been popularly applied to classification and prediction problems. In this study, we investigate the way to apply CNN in business problem solving. Specifically, this study propose to apply CNN to stock market prediction, one of the most challenging tasks in the machine learning research. As mentioned, CNN has strength in interpreting images. Thus, the model proposed in this study adopts CNN as the binary classifier that predicts stock market direction (upward or downward) by using time series graphs as its inputs. That is, our proposal is to build a machine learning algorithm that mimics an experts called 'technical analysts' who examine the graph of past price movement, and predict future financial price movements. Our proposed model named 'CNN-FG(Convolutional Neural Network using Fluctuation Graph)' consists of five steps. In the first step, it divides the dataset into the intervals of 5 days. And then, it creates time series graphs for the divided dataset in step 2. The size of the image in which the graph is drawn is $40(pixels){\times}40(pixels)$, and the graph of each independent variable was drawn using different colors. In step 3, the model converts the images into the matrices. Each image is converted into the combination of three matrices in order to express the value of the color using R(red), G(green), and B(blue) scale. In the next step, it splits the dataset of the graph images into training and validation datasets. We used 80% of the total dataset as the training dataset, and the remaining 20% as the validation dataset. And then, CNN classifiers are trained using the images of training dataset in the final step. Regarding the parameters of CNN-FG, we adopted two convolution filters ($5{\times}5{\times}6$ and $5{\times}5{\times}9$) in the convolution layer. In the pooling layer, $2{\times}2$ max pooling filter was used. The numbers of the nodes in two hidden layers were set to, respectively, 900 and 32, and the number of the nodes in the output layer was set to 2(one is for the prediction of upward trend, and the other one is for downward trend). Activation functions for the convolution layer and the hidden layer were set to ReLU(Rectified Linear Unit), and one for the output layer set to Softmax function. To validate our model - CNN-FG, we applied it to the prediction of KOSPI200 for 2,026 days in eight years (from 2009 to 2016). To match the proportions of the two groups in the independent variable (i.e. tomorrow's stock market movement), we selected 1,950 samples by applying random sampling. Finally, we built the training dataset using 80% of the total dataset (1,560 samples), and the validation dataset using 20% (390 samples). The dependent variables of the experimental dataset included twelve technical indicators popularly been used in the previous studies. They include Stochastic %K, Stochastic %D, Momentum, ROC(rate of change), LW %R(Larry William's %R), A/D oscillator(accumulation/distribution oscillator), OSCP(price oscillator), CCI(commodity channel index), and so on. To confirm the superiority of CNN-FG, we compared its prediction accuracy with the ones of other classification models. Experimental results showed that CNN-FG outperforms LOGIT(logistic regression), ANN(artificial neural network), and SVM(support vector machine) with the statistical significance. These empirical results imply that converting time series business data into graphs and building CNN-based classification models using these graphs can be effective from the perspective of prediction accuracy. Thus, this paper sheds a light on how to apply deep learning techniques to the domain of business problem solving.

• Tuberculosis and Respiratory Diseases
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• v.40 no.3
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• pp.236-249
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• 1993

Background: Among the injurious agents to which the lung airspaces are constantly exposed are reactive species of oxygen. It has been widely believed that reactive oxygen species may be implicated in the etiology of lung injuries. In order to elucidated how this oxidant causes lung cell injury, we investigated the effects of exogenous $H_2O_2$ on alveolar epithelial barrier characteristics. Methods: Rat type II alveolar epithelial cells were plated onto tissue culture-treated polycarbonate membrane filters. The resulting confluent monolayers on days 3 and 4 were mounted in a modified Ussing chamber and bathed on both sides with HEPES-buffered Ringer solution. The changes in short-circuit current (Isc) and monolayer resistance (R) in response to the exogenous hydroperoxide were measured. To determine the degree of cellular catalase participation in protection against $H_2O_2$ injury to the barrier, experiments were repeated in the presence of 20 mM aminotriazole (ATAZ, an inhibitor of catalase) in the same bathing fluid as the hydroperoxide. Results: These monolayers have a high transepithelial resistance (>2000 ohm-$cm^2$) and actively transport $Na^+$ from apical fluid. $H_2O_2$(0-100 mM) was then delivered to either apical or basolateral fluid. Resulting indicated that $H_2O_2$ decreased Isc and R gradually in dose-dependent manner. The effective concentration of apical $H_2O_2$ at which Isc (or R) was decreased by 50% at one hour ($ED_{50}$) was about 4 mM. However, basolateral $H_2O_2$ exposure led to $ED_{50}$ for Isc (and R) of about 0.04 mM. Inhibition of cellular catalase yielded $ED_{50}$ for Isc (and R) of about 0.4 mM when $H_2O_2$ was given apically, while $ED_{50}$ for basolateral exposure to $H_2O_2$ did not change in the presence of ATAZ. The rate of $H_2O_2$ consumption in apical and basolateral bathing fluids was the same, while cellualr catalase activity rose gradually with time in culture. Conclusion: Our data suggest that basolateral $H_2O_2$ may affect directly membrane component (e.g., $Na^+,\;K^+$-ATPase) located on the basolateral cell surface. Apical $H_2O_2$, on the other hand, may be largely degraded by catalase as it passes through the cells before reaching these membrane components. We conclude that alveolar epithelial barrier integrity as measured by Isc and R are compromised by $H_2O_2$ being relatively sensitive to basolateral (and insensitive to apical) $H_2O_2$.

• The Korean Journal of Nuclear Medicine
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• v.38 no.3
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• pp.259-267
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• 2004

Purpose: NEMA NU2-2001 was proposed as a new standard for performance evaluation of whole body PET scanners. in this study, system performance of Siemens CTI ECAT EXACT 47 PET scanner including spatial resolution, sensitivity, scatter fraction, and count rate performance in 2D and 3D mode was evaluated using this new standard method. Methods: ECAT EXACT 47 is a BGO crystal based PET scanner and covers an axial field of view (FOV) of 16.2 cm. Retractable septa allow 2D and 3D data acquisition. All the PET data were acquired according to the NEMA NU2-2001 protocols (coincidence window: 12 ns, energy window: $250{\sim}650$ keV). For the spatial resolution measurement, F-18 point source was placed at the center of the axial FOV((a) x=0, and y=1, (b)x=0, and y=10, (c)x=70, and y=0cm) and a position one fourth of the axial FOV from the center ((a) x=0, and y=1, (b)x=0, and y=10, (c)x=10, and y=0cm). In this case, x and y are transaxial horizontal and vertical, and z is the scanner's axial direction. Images were reconstructed using FBP with ramp filter without any post processing. To measure the system sensitivity, NEMA sensitivity phantom filled with F-18 solution and surrounded by $1{\sim}5$ aluminum sleeves were scanned at the center of transaxial FOV and 10 cm offset from the center. Attenuation free values of sensitivity wire estimated by extrapolating data to the zero wall thickness. NEMA scatter phantom with length of 70 cm was filled with F-18 or C-11solution (2D: 2,900 MBq, 3D: 407 MBq), and coincidence count rates wire measured for 7 half-lives to obtain noise equivalent count rate (MECR) and scatter fraction. We confirmed that dead time loss of the last flame were below 1%. Scatter fraction was estimated by averaging the true to background (staffer+random) ratios of last 3 frames in which the fractions of random rate art negligibly small. Results: Axial and transverse resolutions at 1cm offset from the center were 0.62 and 0.66 cm (FBP in 2D and 3D), and 0.67 and 0.69 cm (FBP in 2D and 3D). Axial, transverse radial, and transverse tangential resolutions at 10cm offset from the center were 0.72 and 0.68 cm (FBP in 2D and 3D), 0.63 and 0.66 cm (FBP in 2D and 3D), and 0.72 and 0.66 cm (FBP in 2D and 3D). Sensitivity values were 708.6 (2D), 2931.3 (3D) counts/sec/MBq at the center and 728.7 (2D, 3398.2 (3D) counts/sec/MBq at 10 cm offset from the center. Scatter fractions were 0.19 (2D) and 0.49 (3D). Peak true count rate and NECR were 64.0 kcps at 40.1 kBq/mL and 49.6 kcps at 40.1 kBq/mL in 2D and 53.7 kcps at 4.76 kBq/mL and 26.4 kcps at 4.47 kBq/mL in 3D. Conclusion: Information about the performance of CTI ECAT EXACT 47 PET scanner reported in this study will be useful for the quantitative analysis of data and determination of optimal image acquisition protocols using this widely used scanner for clinical and research purposes.

• Radiation Oncology Journal
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• v.19 no.1
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• pp.53-65
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• 2001

Purpose : To improve the local control of patients with nasopharyngeal cancer, we have implemented 3-D conformal radiotherapy and forward intensity modulated radiation therapy (IMRT) to used of compensating filters. Three dimension conformal radiotherapy with intensity modulation is a new modality for cancer treatments. We designed 3-D treatment planning with 3-D RTP (radiation treatment planning system) and evaluation dose distribution with tumor control probability (TCP) and normal tissue complication probability (NTCP). Material and Methods : We have developed a treatment plan consisting four intensity modulated photon fields that are delivered through the compensating tilters and block transmission for critical organs. We get a full size CT imaging including head and neck as 3 mm slices, and delineating PTV (planning target volume) and surrounding critical organs, and reconstructed 3D imaging on the computer windows. In the planning stage, the planner specifies the number of beams and their directions including non-coplanar, and the prescribed doses for the target volume and the permissible dose of normal organs and the overlap regions. We designed compensating filter according to tissue deficit and PTV volume shape also dose weighting for each field to obtain adequate dose distribution, and shielding blocks weighting for transmission. Therapeutic gains were evaluated by numerical equation of tumor control probability and normal tissue complication probability. The TCP and NTCP by DVH (dose volume histogram) were compared with the 3-D conformal radiotherapy and forward intensity modulated conformal radiotherapy by compensator and blocks weighting. Optimization for the weight distribution was peformed iteration with initial guess weight or the even weight distribution. The TCP and NTCP by DVH were compared with the 3-D conformal radiotherapy and intensitiy modulated conformal radiotherapy by compensator and blocks weighting. Results : Using a four field IMRT plan, we have customized dose distribution to conform and deliver sufficient dose to the PTV. In addition, in the overlap regions between the PTV and the normal organs (spinal cord, salivary grand, pituitary, optic nerves), the dose is kept within the tolerance of the respective organs. We evaluated to obtain sufficient TCP value and acceptable NTCP using compensating filters. Quality assurance checks show acceptable agreement between the planned and the implemented MLC(multi-leaf collimator). Conclusion : IMRT provides a powerful and efficient solution for complex planning problems where the surrounding normal tissues place severe constraints on the prescription dose. The intensity modulated fields can be efficaciously and accurately delivered using compensating filters.

• Journal of Chest Surgery
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• v.38 no.7 s.252
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• pp.489-495
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• 2005

In the surgical treatment of aortic dissection, aortic arch replacement under total circulatory arrest is often performed after careful inspection to determine the severity of disease progression. Under circulatory arrest, antegrade or retrograde cerebral perfusion is required for brain protection. Recently, antegrade cerebral perfusion has been used more, because of the limitation of retrograde cerebral perfusion. This study is to compare these two methods especially in the respect to neurological complications. Material and Method: Forty patients with aortic dissection involving aortic arch from May 2000 to May 2004 were enrolled in this study, and the methods of operation, clinical recovery, and neurological complications were retrospectively reviewed. Result: In the ACP (antegrade cerebral perfusion) group, axillary artery cannulation was performed in 10 out of 15 cases. In the RCP (retrograde cerebral perfusion) group, femoral artery Cannulation was performed in 24 out of 25 cases. The average esophageal and rectal temperature under total circulatory arrest was $17.2^{\circ}C\;and\;22.8^{\circ}C$ in the group A, and $16.0^{\circ}C\;and\;19.7^{\circ}C$ in the group B, respectively. Higher temperature in the ACP group may have brought the shorter operation and cardiopulmonary bypass time. However, the length of period for postoperative clinical recovery and admission duration did not show any statistically significant differences. Eleven out of the total 15 cases in the ACP group and thirteen out of the total 25 cases in the RCP group showed neurological complication but did not show statistically significant difference. In each group, there were 5 cases with permanent neurological complications. All 5 cases in the ACP group showed some improvements that enabled routine exercise. However all 5 cases in RCP group did not show significant improvements. Conclusion: The Antegrade, cerebral perfusion, which maintains orthordromic circulation, brings moderate degree of hypothermia and, therefore, shortens the operation time and cardiopulmonary bypass time. We concluded that Antegrade cerebral perfusion is safe and can be used widely under total circulatory arrest.

• The Korean Journal of Nuclear Medicine
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• v.38 no.4
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• pp.318-324
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• 2004

Purpose: Philips GEMINI is a newly introduced whole-body GSO PET/CT scanner. In this study, performance of the scanner including spatial resolution, sensitivity, scatter fraction, noise equivalent count ratio (NECR) was measured utilizing NEMA NU2-2001 standard protocol and compared with performance of LSO, BGO crystal scanner. Methods: GEMINI is composed of the Philips ALLEGRO PET and MX8000 D multi-slice CT scanners. The PET scanner has 28 detector segments which have an array of 29 by 22 GSO crystals ($4{\times}6{\times}20$ mm), covering axial FOV of 18 cm. PET data to measure spatial resolution, sensitivity, scatter fraction, and NECR were acquired in 3D mode according to the NEMA NU2 protocols (coincidence window: 8 ns, energy window: $409[\sim}664$ keV). For the measurement of spatial resolution, images were reconstructed with FBP using ramp filter and an iterative reconstruction algorithm, 3D RAMLA. Data for sensitivity measurement were acquired using NEMA sensitivity phantom filled with F-18 solution and surrounded by $1{\sim}5$ aluminum sleeves after we confirmed that dead time loss did not exceed 1%. To measure NECR and scatter fraction, 1110 MBq of F-18 solution was injected into a NEMA scatter phantom with a length of 70 cm and dynamic scan with 20-min frame duration was acquired for 7 half-lives. Oblique sinograms were collapsed into transaxial slices using single slice rebinning method, and true to background (scatter+random) ratio for each slice and frame was estimated. Scatter fraction was determined by averaging the true to background ratio of last 3 frames in which the dead time loss was below 1%. Results: Transverse and axial resolutions at 1cm radius were (1) 5.3 and 6.5 mm (FBP), (2) 5.1 and 5.9 mm (3D RAMLA). Transverse radial, transverse tangential, and axial resolution at 10 cm were (1) 5.7, 5.7, and 7.0 mm (FBP), (2) 5.4, 5.4, and 6.4 mm (3D RAMLA). Attenuation free values of sensitivity were 3,620 counts/sec/MBq at the center of transaxial FOV and 4,324 counts/sec/MBq at 10 cm offset from the center. Scatter fraction was 40.6%, and peak true count rate and NECR were 88.9 kcps @ 12.9 kBq/mL and 34.3 kcps @ 8.84 kBq/mL. These characteristics are better than that of ECAT EXACT PET scanner with BGO crystal. Conclusion: The results of this field test demonstrate high resolution, sensitivity and count rate performance of the 3D PET/CT scanner with GSO crystal. The data provided here will be useful for the comparative study with other 3D PET/CT scanners using BGO or LSO crystals.

• The Journal of Korean Society for Radiation Therapy
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• v.26 no.1
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• pp.137-147
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• 2014

Purpose : The purpose of this study is to verify the accuracy of dose delivery according to the patient's breathing cycle in Gated Volumetric Modulated Arc Therapy Materials and Methods : TrueBeam STxTM(Varian Medical System, Palo Alto, CA) was used in this experiment. The Computed tomography(CT) images that were acquired with RANDO Phantom(Alderson Research Laboratories Inc. Stamford. CT, USA), using Computerized treatment planning system(Eclipse 10.0, Varian, USA), were used to create VMAT plans using 10MV FFF with 1500 cGy/fx (case 1, 2, 3) and 220 cGy/fx(case 4, 5, 6) of doserate of 1200 MU/min. The regular respiratory period of 1.5, 2.5, 3.5 and 4.5 sec and the patients respiratory period of 2.2 and 3.5 sec were reproduced with the $QUASAR^{TM}$ Respiratory Motion Phantom(Modus Medical Devices Inc), and it was set up to deliver radiation at the phase mode between the ranges of 30 to 70%. The results were measured at respective respiratory conditions by a 2-Dimensional ion chamber array detector(I'mRT Matrixx, IBA Dosimetry, Germany) and a MultiCube Phantom(IBA Dosimetry, Germany), and the Gamma pass rate(3 mm, 3%) were compared by the IMRT analysis program(OmniPro I'mRT system software Version 1.7b, IBA Dosimetry, Germany) Results : The gamma pass rates of Case 1, 2, 3, 4, 5 and 6 were the results of 100.0, 97.6, 98.1, 96.3, 93.0, 94.8% at a regular respiratory period of 1.5 sec and 98.8, 99.5, 97.5, 99.5, 98.3, 99.6% at 2.5 sec, 99.6, 96.6, 97.5, 99.2, 97.8, 99.1% at 3.5 sec and 99.4, 96.3, 97.2, 99.0, 98.0, 99.3% at 4.5 sec, respectively. When a patient's respiration was reproduced, 97.7, 95.4, 96.2, 98.9, 96.2, 98.4% at average respiratory period of 2.2 sec, and 97.3, 97.5, 96.8, 100.0, 99.3, 99.8% at 3.5 sec, respectively. Conclusion : The experiment showed clinically reliable results of a Gamma pass rate of 95% or more when 2.5 sec or more of a regular breathing period and the patient's breathing were reproduced. While it showed the results of 93.0% and 94.8% at a regular breathing period of 1.5 sec of Case 5 and 6, it could be confirmed that the accurate dose delivery could be possible on the most respiratory conditions because based on the results of 100 patients's respiratory period analysis as no one sustained a respiration of 1.5 sec. But, pretreatment dose verification should be precede because we can't exclude the possibility of error occurrence due to extremely short respiratory period, also a training at the simulation and careful monitoring are necessary for a patient to maintain stable breathing. Consequently, more reliable and accurate treatments can be administered.