• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.177-193
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• 2014

Over the past decade, there has been a rapid diffusion of electronic commerce and a rising number of interconnected networks, resulting in an escalation of security threats and privacy concerns. Electronic commerce has a built-in trade-off between the necessity of providing at least some personal information to consummate an online transaction, and the risk of negative consequences from providing such information. More recently, the frequent disclosure of private information has raised concerns about privacy and its impacts. This has motivated researchers in various fields to explore information privacy issues to address these concerns. Accordingly, the necessity for information privacy policies and technologies for collecting and storing data, and information privacy research in various fields such as medicine, computer science, business, and statistics has increased. The occurrence of various information security accidents have made finding experts in the information security field an important issue. Objective measures for finding such experts are required, as it is currently rather subjective. Based on social network analysis, this paper focused on a framework to evaluate the process of finding experts in the information security field. We collected data from the National Discovery for Science Leaders (NDSL) database, initially collecting about 2000 papers covering the period between 2005 and 2013. Outliers and the data of irrelevant papers were dropped, leaving 784 papers to test the suggested hypotheses. The co-authorship network data for co-author relationship, publisher, affiliation, and so on were analyzed using social network measures including centrality and structural hole. The results of our model estimation are as follows. With the exception of Hypothesis 3, which deals with the relationship between eigenvector centrality and performance, all of our hypotheses were supported. In line with our hypothesis, degree centrality (H1) was supported with its positive influence on the researchers' publishing performance (p<0.001). This finding indicates that as the degree of cooperation increased, the more the publishing performance of researchers increased. In addition, closeness centrality (H2) was also positively associated with researchers' publishing performance (p<0.001), suggesting that, as the efficiency of information acquisition increased, the more the researchers' publishing performance increased. This paper identified the difference in publishing performance among researchers. The analysis can be used to identify core experts and evaluate their performance in the information privacy research field. The co-authorship network for information privacy can aid in understanding the deep relationships among researchers. In addition, extracting characteristics of publishers and affiliations, this paper suggested an understanding of the social network measures and their potential for finding experts in the information privacy field. Social concerns about securing the objectivity of experts have increased, because experts in the information privacy field frequently participate in political consultation, and business education support and evaluation. In terms of practical implications, this research suggests an objective framework for experts in the information privacy field, and is useful for people who are in charge of managing research human resources. This study has some limitations, providing opportunities and suggestions for future research. Presenting the difference in information diffusion according to media and proximity presents difficulties for the generalization of the theory due to the small sample size. Therefore, further studies could consider an increased sample size and media diversity, the difference in information diffusion according to the media type, and information proximity could be explored in more detail. Moreover, previous network research has commonly observed a causal relationship between the independent and dependent variable (Kadushin, 2012). In this study, degree centrality as an independent variable might have causal relationship with performance as a dependent variable. However, in the case of network analysis research, network indices could be computed after the network relationship is created. An annual analysis could help mitigate this limitation.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.149-161
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• 2014

The export of domestic public services to overseas markets contains many potential obstacles, stemming from different export procedures, the target services, and socio-economic environments. In order to alleviate these problems, the business incubation platform as an open business ecosystem can be a powerful instrument to support the decisions taken by participants and stakeholders. In this paper, we propose an ontology model and its implementation processes for the business incubation platform with an open and pervasive architecture to support public service exports. For the conceptual model of platform ontology, export case studies are used for requirements analysis. The conceptual model shows the basic structure, with vocabulary and its meaning, the relationship between ontologies, and key attributes. For the implementation and test of the ontology model, the logical structure is edited using Prot$\acute{e}$g$\acute{e}$ editor. The core engine of the business incubation platform is the simulator module, where the various contexts of export businesses should be captured, defined, and shared with other modules through ontologies. It is well-known that an ontology, with which concepts and their relationships are represented using a shared vocabulary, is an efficient and effective tool for organizing meta-information to develop structural frameworks in a particular domain. The proposed model consists of five ontologies derived from a requirements survey of major stakeholders and their operational scenarios: service, requirements, environment, enterprise, and county. The service ontology contains several components that can find and categorize public services through a case analysis of the public service export. Key attributes of the service ontology are composed of categories including objective, requirements, activity, and service. The objective category, which has sub-attributes including operational body (organization) and user, acts as a reference to search and classify public services. The requirements category relates to the functional needs at a particular phase of system (service) design or operation. Sub-attributes of requirements are user, application, platform, architecture, and social overhead. The activity category represents business processes during the operation and maintenance phase. The activity category also has sub-attributes including facility, software, and project unit. The service category, with sub-attributes such as target, time, and place, acts as a reference to sort and classify the public services. The requirements ontology is derived from the basic and common components of public services and target countries. The key attributes of the requirements ontology are business, technology, and constraints. Business requirements represent the needs of processes and activities for public service export; technology represents the technological requirements for the operation of public services; and constraints represent the business law, regulations, or cultural characteristics of the target country. The environment ontology is derived from case studies of target countries for public service operation. Key attributes of the environment ontology are user, requirements, and activity. A user includes stakeholders in public services, from citizens to operators and managers; the requirements attribute represents the managerial and physical needs during operation; the activity attribute represents business processes in detail. The enterprise ontology is introduced from a previous study, and its attributes are activity, organization, strategy, marketing, and time. The country ontology is derived from the demographic and geopolitical analysis of the target country, and its key attributes are economy, social infrastructure, law, regulation, customs, population, location, and development strategies. The priority list for target services for a certain country and/or the priority list for target countries for a certain public services are generated by a matching algorithm. These lists are used as input seeds to simulate the consortium partners, and government's policies and programs. In the simulation, the environmental differences between Korea and the target country can be customized through a gap analysis and work-flow optimization process. When the process gap between Korea and the target country is too large for a single corporation to cover, a consortium is considered an alternative choice, and various alternatives are derived from the capability index of enterprises. For financial packages, a mix of various foreign aid funds can be simulated during this stage. It is expected that the proposed ontology model and the business incubation platform can be used by various participants in the public service export market. It could be especially beneficial to small and medium businesses that have relatively fewer resources and experience with public service export. We also expect that the open and pervasive service architecture in a digital business ecosystem will help stakeholders find new opportunities through information sharing and collaboration on business processes.

• The Journal of Korean Society for Radiation Therapy
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• v.16 no.2
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• pp.9-17
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• 2004

Purpose : Although Improve of CT, MRI Radio-diagnosis and Radiation Therapy Planing, but we still use ICRU38 Planning system(2D film-based) broadly. 3-Dimensional ICR plan(CT image based) is not only offer tumor and normal tissue dose but also support DVH information. On this study, we plan irradiation-goal dose on CTV(CTV plan) and irradiation-goal dose on ICRU 38 point(ICRU38 plan) by use CT image. And compare with tumor-dose, rectal-dose, bladder-dose on both planning, and analysis DVH Method and Material : Sample 11 patients who treated by Ir-192 HDR. After 40Gy external radiation therapy, ICR plan established. All the patients carry out CT-image scanned by CT-simulator. And we use PLATO(Nucletron) v.14.2 planing system. We draw CTV, rectum, bladder on the CT image. And establish plan irradiation-$100\%$ dose on CTV(CTV plan) and irradiation-$100\%$ dose on A-point(ICRU38 plan) Result : CTV volume($average{\pm}SD$) is $21.8{\pm}26.6cm^3$, rectum volume($average{\pm}SD$) is $60.9{\pm}25.0cm^3$, bladder volume($average{\pm}SD$) is $116.1{\pm}40.1cm^3$ sampled 11 patients. The volume including $100\%$ dose is $126.7{\pm}18.9cm^3$ on ICRU plan and $98.2{\pm}74.5cm^3$ on CTV plan. On ICRU planning, the other one's $22.0cm^3$ CTV volume who residual tumor size excess 4cm is not including $100\%$ isodose. 8 patient's $12.9{\pm}5.9cm^3$ tumor volume who residual tumor size belows 4cm irradiated $100\%$ dose. Bladder dose(recommended by ICRU 38) is $90.1{\pm}21.3\%$ on ICRU plan, $68.7{\pm}26.6\%$ on CTV plan, and rectal dose is $86.4{\pm}18.3\%,\;76.9{\pm}15.6\%$. Bladder and Rectum maximum dose is $137.2{\pm}50.1\%,\;101.1{\pm}41.8\%$ on ICRU plan, $107.6{\pm}47.9\%,\;86.9{\pm}30.8\%$ on CTV plan. Therefore CTV plan more less normal issue-irradiated dose than ICRU plan. But one patient case who residual tumor size excess 4cm, Normal tissue dose more higher than critical dose remarkably on CTV plan. $80\%$over-Irradiated rectal dose(V80rec) is $1.8{\pm}2.4cm^3$ on ICRU plan, $0.7{\pm}1.0cm^3$ on CTV plan. $80\%$over-Irradiated bladder dose(V80bla) is $12.2{\pm}8.9cm^3$ on ICRU plan, $3.5{\pm}4.1cm^3$ on CTV plan. Likewise, CTV plan more less irradiated normal tissue than ICRU38 plan. Conclusion : Although, prove effect and stability about previous ICRU plan, if we use CTV plan by CT image, we will reduce normal tissue dose and irradiated goal-dose at residual tumor on small residual tumor case. But bigger residual tumor case, we need more research about effective 3D-planning.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.141-154
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• 2019

Rapid growth of internet technology and social media is progressing. Data mining technology has evolved to enable unstructured document representations in a variety of applications. Sentiment analysis is an important technology that can distinguish poor or high-quality content through text data of products, and it has proliferated during text mining. Sentiment analysis mainly analyzes people's opinions in text data by assigning predefined data categories as positive and negative. This has been studied in various directions in terms of accuracy from simple rule-based to dictionary-based approaches using predefined labels. In fact, sentiment analysis is one of the most active researches in natural language processing and is widely studied in text mining. When real online reviews aren't available for others, it's not only easy to openly collect information, but it also affects your business. In marketing, real-world information from customers is gathered on websites, not surveys. Depending on whether the website's posts are positive or negative, the customer response is reflected in the sales and tries to identify the information. However, many reviews on a website are not always good, and difficult to identify. The earlier studies in this research area used the reviews data of the Amazon.com shopping mal, but the research data used in the recent studies uses the data for stock market trends, blogs, news articles, weather forecasts, IMDB, and facebook etc. However, the lack of accuracy is recognized because sentiment calculations are changed according to the subject, paragraph, sentiment lexicon direction, and sentence strength. This study aims to classify the polarity analysis of sentiment analysis into positive and negative categories and increase the prediction accuracy of the polarity analysis using the pretrained IMDB review data set. First, the text classification algorithm related to sentiment analysis adopts the popular machine learning algorithms such as NB (naive bayes), SVM (support vector machines), XGboost, RF (random forests), and Gradient Boost as comparative models. Second, deep learning has demonstrated discriminative features that can extract complex features of data. Representative algorithms are CNN (convolution neural networks), RNN (recurrent neural networks), LSTM (long-short term memory). CNN can be used similarly to BoW when processing a sentence in vector format, but does not consider sequential data attributes. RNN can handle well in order because it takes into account the time information of the data, but there is a long-term dependency on memory. To solve the problem of long-term dependence, LSTM is used. For the comparison, CNN and LSTM were chosen as simple deep learning models. In addition to classical machine learning algorithms, CNN, LSTM, and the integrated models were analyzed. Although there are many parameters for the algorithms, we examined the relationship between numerical value and precision to find the optimal combination. And, we tried to figure out how the models work well for sentiment analysis and how these models work. This study proposes integrated CNN and LSTM algorithms to extract the positive and negative features of text analysis. The reasons for mixing these two algorithms are as follows. CNN can extract features for the classification automatically by applying convolution layer and massively parallel processing. LSTM is not capable of highly parallel processing. Like faucets, the LSTM has input, output, and forget gates that can be moved and controlled at a desired time. These gates have the advantage of placing memory blocks on hidden nodes. The memory block of the LSTM may not store all the data, but it can solve the CNN's long-term dependency problem. Furthermore, when LSTM is used in CNN's pooling layer, it has an end-to-end structure, so that spatial and temporal features can be designed simultaneously. In combination with CNN-LSTM, 90.33% accuracy was measured. This is slower than CNN, but faster than LSTM. The presented model was more accurate than other models. In addition, each word embedding layer can be improved when training the kernel step by step. CNN-LSTM can improve the weakness of each model, and there is an advantage of improving the learning by layer using the end-to-end structure of LSTM. Based on these reasons, this study tries to enhance the classification accuracy of movie reviews using the integrated CNN-LSTM model.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.27-42
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• 2020

Traditional companies with offline stores were unable to secure large display space due to the problems of cost. This limitation inevitably allowed limited kinds of products to be displayed on the shelves, which resulted in consumers being deprived of the opportunity to experience various items. Taking advantage of the virtual space called the Internet, online shopping goes beyond the limits of limitations in physical space of offline shopping and is now able to display numerous products on web pages that can satisfy consumers with a variety of needs. Paradoxically, however, this can also cause consumers to experience the difficulty of comparing and evaluating too many alternatives in their purchase decision-making process. As an effort to address this side effect, various kinds of consumer's purchase decision support systems have been studied, such as keyword-based item search service and recommender systems. These systems can reduce search time for items, prevent consumer from leaving while browsing, and contribute to the seller's increased sales. Among those systems, recommender systems based on association rule mining techniques can effectively detect interrelated products from transaction data such as orders. The association between products obtained by statistical analysis provides clues to predicting how interested consumers will be in another product. However, since its algorithm is based on the number of transactions, products not sold enough so far in the early days of launch may not be included in the list of recommendations even though they are highly likely to be sold. Such missing items may not have sufficient opportunities to be exposed to consumers to record sufficient sales, and then fall into a vicious cycle of a vicious cycle of declining sales and omission in the recommendation list. This situation is an inevitable outcome in situations in which recommendations are made based on past transaction histories, rather than on determining potential future sales possibilities. This study started with the idea that reflecting the means by which this potential possibility can be identified indirectly would help to select highly recommended products. In the light of the fact that the attributes of a product affect the consumer's purchasing decisions, this study was conducted to reflect them in the recommender systems. In other words, consumers who visit a product page have shown interest in the attributes of the product and would be also interested in other products with the same attributes. On such assumption, based on these attributes, the recommender system can select recommended products that can show a higher acceptance rate. Given that a category is one of the main attributes of a product, it can be a good indicator of not only direct associations between two items but also potential associations that have yet to be revealed. Based on this idea, the study devised a recommender system that reflects not only associations between products but also categories. Through regression analysis, two kinds of associations were combined to form a model that could predict the hit rate of recommendation. To evaluate the performance of the proposed model, another regression model was also developed based only on associations between products. Comparative experiments were designed to be similar to the environment in which products are actually recommended in online shopping malls. First, the association rules for all possible combinations of antecedent and consequent items were generated from the order data. Then, hit rates for each of the associated rules were predicted from the support and confidence that are calculated by each of the models. The comparative experiments using order data collected from an online shopping mall show that the recommendation accuracy can be improved by further reflecting not only the association between products but also categories in the recommendation of related products. The proposed model showed a 2 to 3 percent improvement in hit rates compared to the existing model. From a practical point of view, it is expected to have a positive effect on improving consumers' purchasing satisfaction and increasing sellers' sales.

• Journal of Korean Society of Transportation
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• v.20 no.7
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• pp.155-166
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• 2002

Since 1990s. there has been an increasing number of traffic accidents at intersection. which requires more urgent measures to insure safety on intersection. This study set out to analyze the road conditions, traffic conditions and traffic operation conditions on signalized intersection. to identify the elements that would impose obstructions in safety, and to develop a traffic accident prediction model to evaluate the safety of an intersection using the cop relation between the elements and an accident. In addition, the focus was made on suggesting appropriate traffic safety policies by dealing with the danger elements in advance and on enhancing the safety on the intersection in developing a traffic accident prediction model fir a signalized intersection. The data for the study was collected at an intersection located in Wonju city from January to December 2001. It consisted of the number of accidents, the road conditions, the traffic conditions, and the traffic operation conditions at the intersection. The collected data was first statistically analyzed and then the results identified the elements that had close correlations with accidents. They included the area pattern, the use of land, the bus stopping activities, the parking and stopping activities on the road, the total volume, the turning volume, the number of lanes, the width of the road, the intersection area, the cycle, the sight distance, and the turning radius. These elements were used in the second correlation analysis. The significant level was 95% or higher in all of them. There were few correlations between independent variables. The variables that affected the accident rate were the number of lanes, the turning radius, the sight distance and the cycle, which were used to develop a traffic accident prediction model formula considering their distribution. The model formula was compared with a general linear regression model in accuracy. In addition, the statistics of domestic accidents were investigated to analyze the distribution of the accidents and to classify intersections according to the risk level. Finally, the results were applied to the Spearman-rank correlation coefficient to see if the model was appropriate. As a result, the coefficient of determination was highly significant with the value of 0.985 and the ranks among the intersections according to the risk level were appropriate too. The actual number of accidents and the predicted ones were compared in terms of the risk level and they were about the same in the risk level for 80% of the intersections.

• Radiation Oncology Journal
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• v.19 no.3
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• pp.237-244
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• 2001

Purpose : To assess the tolerance, complete response rate, bladder preservation rate and survival rate in patients with muscle-invading bladder cancer treated with selective bladder preservation protocol. Method and Materials : From October 1990 to June 1998, twenty six patients with muscle-invading bladder cancer (clinical stage T2-4, N0-3, M0) were enrolled for the treatment protocol of bladder preservation. They were treated with maximal TURBT (transurethral resection of bladder tumor) and 2 cycles of MCV chemotherapy (methotrexate, crisplatin, and vinblastine) followed by $39.6\~45\;Gy$ pelvic irradiation with concomitant cisplatin. After complete urologic evaluation (biopsy or cytology), the patients who achieved complete response were planed for bladder preservation treatment and treated with consolidation cisplatin and radiotherapy (19.8 Gy). The patients who had incomplete response were planed to immediate radical cystectomy. If they refused radical cystectomy, they were treated either with TURBT followed by MCV or cisplatin chemotherapy and radiotherapy. The median follow-up duration is 49.5 months. Results : The Patients with stage T2-3a and T3b-4a underwent complete removal of tumor or gross tumor removal by TURBT, respectively. Twenty one out of 26 patients $(81\%)$ successfully completed the protocol of the planned chemo-radiotherapy. Seven patients had documented complete response. Six of them were treated with additional consolidation cisplatin and radiotherapy. One patient was treated with 2 cycles of MCV chemotherapy due to refusal of chemo-radiotherapy. Five of 7 complete responders had functioning tumor-free bladder. Fourteen patients of incomplete responders were further treated with one of the followings : radical cystectomy (1 patient), or TURBT and 2 cycles of MCV chemotherapy (3 patients), or cisplatin and radiotherapy (10 patients). Thirteen patients of them were not treated with planned radical cystectomy due to patients' refusal (9 patients) or underlying medical problems (4 patients). Among twenty one patients, 12 patients $(58\%)$ were alive with their preserved bladder, 8 patients died with the disease, 1 patient died of intercurrent disease. The 5 years actuarial survival rates according to CR and PR after MCV chemotherapy and cisplatin chemoradiotherapy were $80\%\;and\;14\%$, respectively (u=0.001). Conclusion : In selected patients with muscle-invading bladder cancer, the bladder preservation could be achieved by MCV chemotherapy and cisplatin chemo-radiotherapy. All patients tolerated well this bladder preservation protoco. The availability of complete TURBT and the responsibility of neoadjuvant chemotherapy and chemoradiotherapy were important predictors for bladder preservation and survival. The patients who had not achieved complete response after neoadjuvant chemotherapy and chemoradiotherapy should be immediate radical cystectomy. A randomized prospective trial might be essential to determine more accurate indications between cystectomy or bladder preservation.

• Childhood Kidney Diseases
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• v.7 no.2
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• pp.166-173
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• 2003

Purpose : The cause and pathogenesis of $Henoch-Sch\"{o}nlein$ purpura has been studied for many years but the results are disappointing. Recently the hypothesis that abnormalities involving the glycosylation of the hinge region of immunoglobulin Al(IgAl) may have an important role in the pathogenesis of $Henoch-Sch\"{o}nlein$ purpura is being approved. $Henoch-Sch\"{o}nlein$ purpura is the most common vasculitis Ihat affects children and the prognosis is good. But if kidney invovement occurs, the course may be chronic and troublesome. So we evaluated children with $Henoch-Sch\"{o}nlein$ purpura especially from the point of epidemiology and clinical manifestations. Methods : Investigation of 124 children who were diagnosed with $Henoch-Sch\"{o}nlein$ purpura at Inje University Ilsan Paik Hospital from December 1999 to July 2003 was performed retrospectively through chart review. Efforts were made to get informations about the profile, epidemiology, clinical manifestations, progress of the disease and recurrence rate of patients. Results : The patients were 69 boys and 55 girls, with a mean age of $6.1{\pm}2.7$ years at the time of data collection. The male to female ratio was 1.25 : 1. The occurrence rate was much higher in autumn(from September to November, 31.5%) and winter(from December to February, 28.2%) than in spring and summer, with a peak in November. Joint involvement was shown in 66.9% of patients mostly on the foot/ankle(75.9%), knee(39.8%). Seventy(56.5%) out of 124 patients had abdominal pain and 10 patients(8.1%) showed bloody stools. Renal involvement was observed in 24 patients(19.4%) after 21.1 days on the average. IgA was elevated in 10 of 21 patients(47.6%). $C_3$ and $C_4$ levels were normal in 40 of 49 patients (81.7%) and 47 of 48 patients(97.9%), respectively Antistreptolysin-O(ASO) titer was elevated over 250 Todd units in 29 of 62 Patients(46.8%). Mycoplasma antibody titer was elevated in 21 of 49 patients(42.9%) equal or greater than 1:80. Radiologic studies were peformed in 23 patients. Seven patients(30.4%) showed bowel wall thickening and one of them received intestinal resection and anastomosis operation due to terminal ileum necrosis. Eighty four patients took steroid 1.4 mg/kg/day in average. Recurrence rate was 2.5 in 37 patients(29.8%). Conclusion : $Henoch-Sch\"{o}nlein$ purpura in childhood appears most in about 6 years of age. The occurrence rate is much higher in autumn and winter relatively. Diagnosis can be made through the perspective history taking and the inspection of clinical manifestations, but the laboratory findings are not of great help. A small portion of the patients might show abdominal pain or arthritis before purpura develops, therfore various diagnosis can be made. Radiologic evaluation should be performed to avoid surgical complications in cases accompanying abdominal pain, and long term follow up should be needed especially in patients suffering from kidney involvement. In about 30% of the patients $Henoch-Sch\"{o}nlein$ purpura would recur. Steroid can be used safely without side effects.

• Nuclear Medicine and Molecular Imaging
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• v.42 no.4
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• pp.301-306
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• 2008

Purpose: Recently, a number of patients needed total thyroidectomy and high dose radioiodine therapy (HD-RAI) get increased more. The aim of this study is to evaluate whether pathological staging (PS) and serum thyroglobulin (sTG) level could replace the diagnostic I-123 scan for the determination of therapeutic dose of HD-RAI in patients with differentiated thyroid cancer. Materials and Methods: Fifty eight patients (M:F=13;45, age $44.5{\pm}11.5\;yrs$) who underwent total thyroidectomy and central or regional lymph node dissection due to differentiated thyroid cancer were enrolled. Diagnostic scan of I-123 and sTG assay were also performed on off state of thyroid hormone. The therapeutic doses of I-131 (TD) were determined by the extent of uptakes on diagnostic I-123 scan as a gold standard. PS was graded by the criteria recommended in 6th edition of AJCC cancer staging manual except consideration of age. For comparison of the determination of therapeutic doses, PS and sTG were compared with the results of I-123 scan. Results: All patients were underwent HD-RAI. Among them, five patients (8.6%) were treated with 100 mCi of I-131, fourty three (74.1%) with 150 mCi, six (10.3%) with 180 mCi, three (5.2%) with 200 mCi, and one (1.7%) with 250 mCi, respectively. On the assessment of PS, average TDs were $154{\pm}25\;mCi$ in stage I (n=9), $175{\pm}50\;mCi$ in stage II (n=4), $149{\pm}21\;mCi$ in stage III (n=38), and $161{\pm}20\;mCi$ in stage IV (n=7). The statistical significance was not shown between PS and TD (p=0.169). Among fifty two patients who had available sTG, 25 patients (48.1%) having below 2 ng/mL of sTG were treated with $149{\pm}26\;mCi$ of I-131, 9 patients (17.3%) having $2{\leq}\;sTG\;<5\;ng/mL$ with $156{\pm}17\;mCi$, 5 patients (9.6%) having $5{\leq}\;sTG\;<10\;ng/mL$ with $156{\pm}13\;mCi$, 7 patients (13.5%) having $10{\leq}sTG\;<50\;ng/mL$ with $147{\pm}24\;mCi$, and 6 patients (11.5%) having above 50 ng/mL with $175{\pm}42\;mCi$. The statistical significance between sTG level and TD (p=0.252) was not shown. Conclusion: In conclusion, PS and sTG could not replace the determination of TD using I-123 scan for first HD-RAI in patients with differentiated thyroid cancer.

• The Korean Journal of Nuclear Medicine Technology
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• v.24 no.1
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• pp.27-32
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• 2020

Purpose Glomerular Filtration Rate(GFR) is an important indicator for evaluating renal function and monitoring the progress of renal disease. Currently, the method of measuring GFR in clinical trials by using serum creatinine value and ^99mTc-DTPA(diethylenetriamine pentaacetic acid) renal dynamic scan is still useful. After the Gates method of formula was announced, when ^99mTc-DTPA Renal dynamic scan is taken, it is applied the GFR is measured using a gamma camera. The purpose of this paper is to measure the GFR by applying the Gates method of formula. It is according to effect activity and matrix size that is related in the GFR. Materials and Methods Data from 5 adult patients (patient age = 62 ± 5, 3 males, 2 females) who had been examined ^99mTc-DTPA Renal dynamic scan were analyzed. A dynamic image was obtained for 21 minutes after instantaneous injection of ^99mTc-DTPA 15 mCi into the patient's vein. To evaluate the glomerular filtration rate according to changes in activity and matrix size, total counts were measured after setting regions of interest in both kidneys and tissues in 2-3 minutes. The distance from detector to the table was maintained at 30cm, and the capacity of the pre-syringe (PR) was set to 15, 20, 25, 30 mCi, and each the capacity of post-syringe (PO) was 1, 5, 10, 15 mCi is set to evaluate the activity change. And then, each matrix size was changed to 32 × 32, 64 × 64, 128 × 128, 256 × 256, 512 × 512, and 1024 × 1024 to compare and to evaluate the values. Results As the activity increased in matrix size, the difference in GFR gradually decreased from 52.95% at the maximum to 16.67% at the minimum. The GFR value according to the change of matrix size was similar to 2.4%, 0.2%, 0.2% of difference when changing from 128 to 256, 256 to 512, and 512 to 1024, but 54.3% of difference when changing from 32 to 64 and 39.43% of difference when changing from 64 to 128. Finally, based on the presently used protocol, 256 × 256, PR 15 mCi and PO 1 mCi, the GFR value was the largest difference with 82% in PR 15 mCi and PO 1 mCi. conditions, and at the least difference is 0.2% in the conditions of PR 30 mCi and PO 15 mCi. Conclusion Through this paper, it was confirmed that when measuring the GFR using the gate method in the ^99mTc-DTPA renal dynamic scan. The GFR was affected by activity and matrix size changes. Therefore, it is considered that when taking the ^99mTc-DTPA renal dynamic scan, is should be careful by applying appropriate parameters when calculating GFR in the every hospital.