• Radiation Oncology Journal
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• v.22 no.4
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• pp.316-324
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• 2004

Purpose : In radiotherapy of tumors in liver, enough planning target volume (PTV) margins are necessary to compensate breathing-related movement of tumor volumes. To overcome the problems, this study aims to obtain patients' body movements by using a moving phantom and an ultrasonic sensor, and to develop respiration sating techniques that can adjust patients' beds by using reversed values of the data obtained. Materials and Methods : The phantom made to measure patients' body movements is composed of a microprocessor (BS II, 20 MHz, 8K Byte), a sensor (Ultra-Sonic, range $3\~3$ m), host computer (RS232C) and stepping motor (torque 2.3 Kg) etc., and the program to control and operate it was developed. The program allows the phantom to move within the maximum range of 2 cm, its movements and corrections to take place In order, and x, y and z to move successively. After the moving phantom was adjusted by entering random movement data (three dimensional data form with distance of 2 cm), and the phantom movements were acquired using the ultra sonic sensor, the two data were compared and analyzed. And then, after the movements by respiration were acquired by using guinea pigs, the real-time respiration gating techniques were drawn by operating the phantom with the reversed values of the data. Results : The result of analyzing the acquisition-correction delay time the three types of data values and about each value separately shows that the data values coincided with one another within $1\%$ and that the acquisition-correction delay time was obtained real-time $(2.34{\times}10^{-4}sec)$. Conclusion : This study successfully confirms the clinic application possibility of respiration gating techniques by using a moving phantom and an ultrasonic sensor. With ongoing development of additional analysis system, which can be used in real-time set-up reproducibility analysis, it may be beneficially used in radiotherapy of moving tumors.

• Clinical and Experimental Pediatrics
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• v.49 no.3
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• pp.317-325
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• 2006

Purpose : This study was carried out to elucidate the effects of nitric oxide synthase(NOS) inhibitor, NG-monomethyl-L-arginine(L-NMMA) and nitric oxide precursor, L-arginine(L-Arg) on cerebral hemodynamics and energy metabolism during reoxygenation-reperfusion(RR) after hypoxia-ischemia(HI) in newborn piglets. Methods : Twenty-eight newborn piglets were divided into 4 groups; Sham normal control(NC), experimental control(EC), L-NMMA(HI & RR with L-NMMA), and L-Arg(HI & RR with L-Arg) groups. HI was induced by occlusion of bilateral common carotid arteries and simultaneously breathing with 8 percent oxygen for 30 mins, and followed RR by release of carotid occlusion and normoxic ventilation for one hour. All groups were monitored with cerebral hemodynamics and cytochrome $aa_3$ (Cyt $aa_3$) using near infrared spectroscopy(NIRS). $Na^+$, $K^+$-ATPase activity, lipid peroxidation products, and tissue high energy phosphate levels were determined biochemically in the cerebral cortex. Results : In experimental groups, mean arterial blood pressure, $PaO_2$, and pH decreased, and base excess and blood lactate level increased after HI compared to NC group(P<0.05). These variables subsequently returned to baseline after RR except pH. There were no differences among the experimental groups. In NIRS, oxidized hemoglobin($HbO_2$) decreased and hemoglobin(Hb) increased during HI(P<0.05) but returned to base line immediately after RR; 40 min after RR, the $HbO_2$ had decreased significantly compared to NC group(P<0.05). Changes of Cyt $aa_3$ decreased significantly compared to NC after HI and recovered at the end of the experiment. Significantly reduced cerebral cortical cell membrane $Na^+$, $K^+$-ATPase activity and increased lipid peroxidation products(P<0.05) were not improved with L-NMMA or L-Arg. Conclusion : These findings suggest that NO is not involved in the mechanism of HI and RR brain damage during the early acute phase of RR.

• Journal of Internet Computing and Services
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• v.14 no.5
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• pp.69-76
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• 2013

The incidence of globally infectious and pathogenic diseases such as H1N1 (swine flu) and Avian Influenza (AI) has recently increased. An infectious disease is a pathogen-caused disease, which can be passed from the infected person to the susceptible host. Pathogens of infectious diseases, which are bacillus, spirochaeta, rickettsia, virus, fungus, and parasite, etc., cause various symptoms such as respiratory disease, gastrointestinal disease, liver disease, and acute febrile illness. They can be spread through various means such as food, water, insect, breathing and contact with other persons. Recently, most countries around the world use a mathematical model to predict and prepare for the spread of infectious diseases. In a modern society, however, infectious diseases are spread in a fast and complicated manner because of rapid development of transportation (both ground and underground). Therefore, we do not have enough time to predict the fast spreading and complicated infectious diseases. Therefore, new system, which can prevent the spread of infectious diseases by predicting its pathway, needs to be developed. In this study, to solve this kind of problem, an integrated monitoring system, which can track and predict the pathway of infectious diseases for its realtime monitoring and control, is developed. This system is implemented based on the conventional mathematical model called by 'Susceptible-Infectious-Recovered (SIR) Model.' The proposed model has characteristics that both inter- and intra-city modes of transportation to express interpersonal contact (i.e., migration flow) are considered. They include the means of transportation such as bus, train, car and airplane. Also, modified real data according to the geographical characteristics of Korea are employed to reflect realistic circumstances of possible disease spreading in Korea. We can predict where and when vaccination needs to be performed by parameters control in this model. The simulation includes several assumptions and scenarios. Using the data of Statistics Korea, five major cities, which are assumed to have the most population migration have been chosen; Seoul, Incheon (Incheon International Airport), Gangneung, Pyeongchang and Wonju. It was assumed that the cities were connected in one network, and infectious disease was spread through denoted transportation methods only. In terms of traffic volume, daily traffic volume was obtained from Korean Statistical Information Service (KOSIS). In addition, the population of each city was acquired from Statistics Korea. Moreover, data on H1N1 (swine flu) were provided by Korea Centers for Disease Control and Prevention, and air transport statistics were obtained from Aeronautical Information Portal System. As mentioned above, daily traffic volume, population statistics, H1N1 (swine flu) and air transport statistics data have been adjusted in consideration of the current conditions in Korea and several realistic assumptions and scenarios. Three scenarios (occurrence of H1N1 in Incheon International Airport, not-vaccinated in all cities and vaccinated in Seoul and Pyeongchang respectively) were simulated, and the number of days taken for the number of the infected to reach its peak and proportion of Infectious (I) were compared. According to the simulation, the number of days was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days when vaccination was not considered. In terms of the proportion of I, Seoul was the highest while Pyeongchang was the lowest. When they were vaccinated in Seoul, the number of days taken for the number of the infected to reach at its peak was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days. In terms of the proportion of I, Gangneung was the highest while Pyeongchang was the lowest. When they were vaccinated in Pyeongchang, the number of days was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days. In terms of the proportion of I, Gangneung was the highest while Pyeongchang was the lowest. Based on the results above, it has been confirmed that H1N1, upon the first occurrence, is proportionally spread by the traffic volume in each city. Because the infection pathway is different by the traffic volume in each city, therefore, it is possible to come up with a preventive measurement against infectious disease by tracking and predicting its pathway through the analysis of traffic volume.