• Radiation Oncology Journal
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• v.22 no.4
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• pp.237-246
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• 2004

Purpose: To investigate the effects of radiation dose-escalation on the treatment outcome, complications and the other prognostic variables for glioblastoma patients treated with 3D-conformal radiotherapy (3D-CRT). Materials and Methods: Between Jan 1997 and July 2002, a total of 75 patients with histologically proven diagnosis of glioblastoma were analyzed. The patients who had a Karnofsky Performance Score (KPS) of 60 or higher, and received at least 50 Gy of radiation to the tumor bed were eligible. All the patients were divided into two arms; Arm 1, the high-dose group was enrolled prospectively, and Arm 2, the low-dose group served as a retrospective control. Arm 1 patients received $63\~70$ Gy (Median 66 Gy, fraction size $1.8\~2$ Gy) with 3D-conformal radiotherapy, and Arm 2 received 59.4 Gy or less (Median 59.4 Gy, fraction size 1.8 Gy) with 2D-conventional radiotherapy. The Gross Tumor Volume (GTV) was defined by the surgical margin and the residual gross tumor on a contrast enhanced MRI. Surrounding edema was not included in the Clinical Target Volume (CTV) in Arm 1, so as to reduce the risk of late radiation associated complications; whereas as in Arm 2 it was included. The overall survival and progression free survival times were calculated from the date of surgery using the Kaplan-Meier method. The time to progression was measured with serial neurologic examinations and MRI or CT scans after RT completion. Acute and late toxicities were evaluated using the Radiation Therapy Oncology Group neurotoxicity scores. Results: During the relatively short follow up period of 14 months, the median overall survival and progression free survival times were $15{\pm}1.65$ and $11{\pm}0.95$ months, respectively. The was a significantly longer survival time for the Arm 1 patients compared to those in Arm 2 (p=0.028). For Arm 1 patients, the median survival and progression free survival times were $21{\pm}5.03$ and $12{\pm}1.59$ months, respectively, while for Arm 2 patients they were $14{\pm}0.94$ and $10{\pm}1.63$ months, respectively. Especially in terms of the 2-year survival rate, the high-dose group showed a much better survival time than the low-dose group; $44.7\%$ versus $19.2\%$. Upon univariate analyses, age, performance status, location of tumor, extent of surgery, tumor volume and radiation dose group were significant factors for survival. Multivariate analyses confirmed that the impact of radiation dose on survival was independent of age, performance status, extent of surgery and target volume. During the follow-up period, complications related directly with radiation, such as radionecrosis, has not been identified. Conclusion: Using 3D-conformal radiotherapy, which is able to reduce the radiation dose to normal tissues compared to 2D-conventional treatment, up to 70 Gy of radiation could be delivered to the GTV without significant toxicity. As an approach to intensify local treatment, the radiation dose escalation through 3D-CRT can be expected to increase the overall and progression free survival times for patients with glioblastomas.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.143-163
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• 2016

The demographics of Internet users are the most basic and important sources for target marketing or personalized advertisements on the digital marketing channels which include email, mobile, and social media. However, it gradually has become difficult to collect the demographics of Internet users because their activities are anonymous in many cases. Although the marketing department is able to get the demographics using online or offline surveys, these approaches are very expensive, long processes, and likely to include false statements. Clickstream data is the recording an Internet user leaves behind while visiting websites. As the user clicks anywhere in the webpage, the activity is logged in semi-structured website log files. Such data allows us to see what pages users visited, how long they stayed there, how often they visited, when they usually visited, which site they prefer, what keywords they used to find the site, whether they purchased any, and so forth. For such a reason, some researchers tried to guess the demographics of Internet users by using their clickstream data. They derived various independent variables likely to be correlated to the demographics. The variables include search keyword, frequency and intensity for time, day and month, variety of websites visited, text information for web pages visited, etc. The demographic attributes to predict are also diverse according to the paper, and cover gender, age, job, location, income, education, marital status, presence of children. A variety of data mining methods, such as LSA, SVM, decision tree, neural network, logistic regression, and k-nearest neighbors, were used for prediction model building. However, this research has not yet identified which data mining method is appropriate to predict each demographic variable. Moreover, it is required to review independent variables studied so far and combine them as needed, and evaluate them for building the best prediction model. The objective of this study is to choose clickstream attributes mostly likely to be correlated to the demographics from the results of previous research, and then to identify which data mining method is fitting to predict each demographic attribute. Among the demographic attributes, this paper focus on predicting gender, age, marital status, residence, and job. And from the results of previous research, 64 clickstream attributes are applied to predict the demographic attributes. The overall process of predictive model building is compose of 4 steps. In the first step, we create user profiles which include 64 clickstream attributes and 5 demographic attributes. The second step performs the dimension reduction of clickstream variables to solve the curse of dimensionality and overfitting problem. We utilize three approaches which are based on decision tree, PCA, and cluster analysis. We build alternative predictive models for each demographic variable in the third step. SVM, neural network, and logistic regression are used for modeling. The last step evaluates the alternative models in view of model accuracy and selects the best model. For the experiments, we used clickstream data which represents 5 demographics and 16,962,705 online activities for 5,000 Internet users. IBM SPSS Modeler 17.0 was used for our prediction process, and the 5-fold cross validation was conducted to enhance the reliability of our experiments. As the experimental results, we can verify that there are a specific data mining method well-suited for each demographic variable. For example, age prediction is best performed when using the decision tree based dimension reduction and neural network whereas the prediction of gender and marital status is the most accurate by applying SVM without dimension reduction. We conclude that the online behaviors of the Internet users, captured from the clickstream data analysis, could be well used to predict their demographics, thereby being utilized to the digital marketing.

• Korean Journal of Ecology and Environment
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• v.45 no.2
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• pp.158-173
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• 2012

The objectives of this study were to analyze the longitudinal gradient and temporal variations of water quality in Daecheong Reservoir in relation to the major inflowing streams from the watershed, during 2001~2010. For the study, we selected 7 main-stream sites of the reservoir along the main axis of the reservoir, from the headwater to the dam and 8 tributary streams. In-reservoir nutrients of TN and TP showed longitudinal declines from the headwater to the dam, which results in a distinct zonation of the riverine ($R_z$, M1~M3), transition ($T_z$, M4~M6), and lacustrine zone ($L_z$, M7) in water quality, as shown in other foreign reservoirs. Chlorophyll-a (CHL) and BOD as an indicator of organic matter, were maximum in the $T_z$. Concentration of total phosphorus (TP) was the highest (8.52 $mg\;L^{-1}$) on March in the $R_z$, and was the highest (165 ${\mu}g\;L^{-1}$) in the $L_z$ on July. Values of TN was the maximum (377 ${\mu}g\;L^{-1}$) on August in the $R_z$, and was the highest (3.76 $mg\;L^{-1}$) in the $L_z$ on August. Ionic dilution was evident during September~October, after the monsoon rain. The mean ratios of TN : TP, as an indicator of limiting factor, were 88, which indicates that nitrogen is a surplus for phytoplankton growth in this system. Nutrient analysis of inflowing streams showed that major nutrient sources were headwater streams of T1~T2 and Ockcheon-Stream of T5, and the most influential inflowing stream to the reservoir was T5, which is located in the mid-reservoir, and is directly influenced by the waste-water treatment plants. The key parameters, influenced by the monsoon rain, were TP and suspended solids (SS). Empirical models of trophic variables indicated that variations of CHL in the $R_z$ ($R^2$=0.044, p=0.264) and $T_z$ ($R^2$=0.126, p=0.054) were not accounted by TN, but were significant (p=0.032) in the $L_z$. The variation of the log-transformed $I_r$-CHL was not accounted ($R^2$=0.258, p=0.110) by $I_w$-TN of inflowing streams, but was determined ($R^2$=0.567, p=0.005) by $I_w$-TP of inflowing streams. In other words, TP inputs from the inflowing streams were the major determinants on the in-reservoir phytoplankton growth. Regression analysis of TN : TP suggested that the ratio was determined by P, rather than N. Overall, our data suggest that TP and suspended solids, during the summer flood period, should be reduced from the eutrophication control and P-input from Ockcheon-Stream should be controlled for water quality improvement.

• Radiation Oncology Journal
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• v.20 no.3
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• pp.221-227
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• 2002

Purpose : To evaluate the role of postoperative chemoradiotherapy in locally advanced rectal cancer, we retrospectively analyzed the treatment results of patients treated by curative surgical resection and postoperative chemoradiotherapy. Materials and Methods : From April 1989 through December 1998, 119 patients were treated with curative surgery and postoperative chemoradiotherapy for rectal carcinoma in Gyeongsang National University Hospital. Patient age ranged from 32 to 73 years, with a median age of 56 years. Low anterior resection was peformed in 59 patients, and abdominoperineal resection in 60. Forty-three patients were AJCC stage II and 76 were stage III. Radiation was delivered with 6 MV X rays using either AP-PA two fields, AP-PA both lateral four fields, or PA both lateral three fields. Total radiation dose ranged from 40 Gy to 56 Gy. In 73 patients, bolus infusions of 5-FU $(400\;mg/m^2)$ were given during the first and fourth weeks of radiotherapy. After completion of radiotherapy, an additional four to six cycles of 5-FU were given. Oral 5-FU (Furtulone) was given for nine months in 46 patients. Results : Forty $(33.7\%)$ of the 119 patients showed treatment failure. Local failure occurred in 16 $(13.5\%)$ patients, 1 $(2.3\%)$ of 43 stage II patients and 15 $(19.7\%)$ of 76 stage III patients. Distant failure occurred in 31 $(26.1\%)$ patients, among whom 5 $(11.6\%)$ were stage II and 26 $(34.2\%)$ were stage III. Five-year actuarial survival was $56.2\%$ overall, $71.1\%$ in stage II patients and $49.1\%$ in stage III patients (p=0.0008). Five-year disease free survival was $53.3\%$ overall, $68.1\%$ in stage II and $45.8\%$ in stage III (p=0.0006). Multivariate analysis showed that T stage and N stage were significant prognostic factors for five year survival, and that T stage, N stage, and preoperative CEA value were significant prognostic factors for five year disease free survival. Bowel complication occurred in 22 patients, and was treated surgically in 15 $(12.6\%)$, and conservatively in 7 $(5.9\%)$. Conclusion : Postoperative chemoradiotherapy was confirmed to be an effective modality for local control of rectal cancer, but the distant failure rate remained high. More effective modalities should be investigated to lower the distant failure rate.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.139-156
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• 2021

The biggest reason for using a deep learning model in image classification is that it is possible to consider the relationship between each region by extracting each region's features from the overall information of the image. However, the CNN model may not be suitable for emotional image data without the image's regional features. To solve the difficulty of classifying emotion images, many researchers each year propose a CNN-based architecture suitable for emotion images. Studies on the relationship between color and human emotion were also conducted, and results were derived that different emotions are induced according to color. In studies using deep learning, there have been studies that apply color information to image subtraction classification. The case where the image's color information is additionally used than the case where the classification model is trained with only the image improves the accuracy of classifying image emotions. This study proposes two ways to increase the accuracy by incorporating the result value after the model classifies an image's emotion. Both methods improve accuracy by modifying the result value based on statistics using the color of the picture. When performing the test by finding the two-color combinations most distributed for all training data, the two-color combinations most distributed for each test data image were found. The result values were corrected according to the color combination distribution. This method weights the result value obtained after the model classifies an image's emotion by creating an expression based on the log function and the exponential function. Emotion6, classified into six emotions, and Artphoto classified into eight categories were used for the image data. Densenet169, Mnasnet, Resnet101, Resnet152, and Vgg19 architectures were used for the CNN model, and the performance evaluation was compared before and after applying the two-stage learning to the CNN model. Inspired by color psychology, which deals with the relationship between colors and emotions, when creating a model that classifies an image's sentiment, we studied how to improve accuracy by modifying the result values based on color. Sixteen colors were used: red, orange, yellow, green, blue, indigo, purple, turquoise, pink, magenta, brown, gray, silver, gold, white, and black. It has meaning. Using Scikit-learn's Clustering, the seven colors that are primarily distributed in the image are checked. Then, the RGB coordinate values of the colors from the image are compared with the RGB coordinate values of the 16 colors presented in the above data. That is, it was converted to the closest color. Suppose three or more color combinations are selected. In that case, too many color combinations occur, resulting in a problem in which the distribution is scattered, so a situation fewer influences the result value. Therefore, to solve this problem, two-color combinations were found and weighted to the model. Before training, the most distributed color combinations were found for all training data images. The distribution of color combinations for each class was stored in a Python dictionary format to be used during testing. During the test, the two-color combinations that are most distributed for each test data image are found. After that, we checked how the color combinations were distributed in the training data and corrected the result. We devised several equations to weight the result value from the model based on the extracted color as described above. The data set was randomly divided by 80:20, and the model was verified using 20% of the data as a test set. After splitting the remaining 80% of the data into five divisions to perform 5-fold cross-validation, the model was trained five times using different verification datasets. Finally, the performance was checked using the test dataset that was previously separated. Adam was used as the activation function, and the learning rate was set to 0.01. The training was performed as much as 20 epochs, and if the validation loss value did not decrease during five epochs of learning, the experiment was stopped. Early tapping was set to load the model with the best validation loss value. The classification accuracy was better when the extracted information using color properties was used together than the case using only the CNN architecture.

• Journal of the Korean Institute of Landscape Architecture
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• v.41 no.6
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• pp.107-116
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• 2013

This study was undertaken to investigate the characteristics of retention and evapotranspiration in the extensive greening module of sloped and flat rooftops for stormwater management and urban heat island mitigation. A series of 100mm depth's weighing lysimeters planted with Sedum kamtschaticum. were constructed on a 50% slope facing four orientations(north, east, south and west) and a flat rooftop. Thereafter the retention and evapotranspiration from the greening module and the surface temperature of nongreening and greening rooftop were recorded beginning in September 2012 for a period of 1 year. The characteristics of retention and evapotranspiration in the greening module were as follows. The water storage of the sloped and flat greening modules increased to 8.7~28.4mm and 10.6~31.8mm after rainfall except in the winter season, in which it decreased to 3.3mm and 3.9mm in the longer dry period. The maximum stormwater retention of the sloped and flat greening modules was 22.2mm and 23.1mm except in the winter season. Fitted stormwater retention function was [Stormwater Retention Ratio(%)=-18.42 ln(Precipitation)+107.9, $R^2$=0.80] for sloped greening modules, and that was [Stormwater Retention Ratio(%)=-22.64 ln(X)+130.8, $R^2$=0.81] for flat greening modules. The daily evapotranspiration(mm/day) from the greening modules after rainfall decreased rapidly with a power function type in summer, and with a log function type in spring and autumn. The daily evapotranspiration(mm/day) from the greening modules after rainfall was greater in summer > spring > autumn > winter by season. This may be due to the differences in water storage, solar radiation and air temperature. The daily evapotranspiration from the greening modules decreased rapidly from 2~7mm/day to less than 1mm/day for 3~5 days after rainfall, and that decreased slowly after 3~5 days. This indicates that Sedum kamtschaticum used water rapidly when it was available and conserved water when it was not. The albedo of the concrete rooftop and greening rooftop was 0.151 and 0.137 in summer, and 0.165 and 0.165 in winter respectively. The albedo of the concrete rooftop and greening rooftop was similar. The effect of the daily mean and highest surface temperature decrease by greening during the summer season showed $1.6{\sim}13.8^{\circ}C$(mean $9.7^{\circ}C$) and $6.2{\sim}17.6^{\circ}C$(mean $11.2^{\circ}C$). The difference of the daily mean and highest surface temperature between the greening rooftop and concrete rooftop during the winter season were small, measuring $-2.4{\sim}1.3^{\circ}C$(mean $-0.4^{\circ}C$) and $-4.2{\sim}2.6^{\circ}C$(mean $0.0^{\circ}C$). The difference in the highest daily surface temperature between the greening rooftop and concrete rooftop during the summer season increased with an evapotranspiration rate increase by a linear function type. The fitted function of the highest daily surface temperature decrease was [Temperature Decrease($^{\circ}C$)=$1.4361{\times}$(Evapotranspiration rate(mm/day))+8.83, $R^2$=0.59]. The decrease of the surface temperature by greening in the longer dry period was due to sun protection by the sedum canopy. The results of this study indicate that the extensive rooftop greening will assist in managing stormwater runoff and urban heat island through retention and evapotranspiration. Sedum kamtschaticum would be the ideal plant for a non-irrigated extensive green roof. The shading effects of Sedum kamtschaticum would be important as well as the evapotranspiration effects of that for the long-term mitigation effects of an urban heat island.

• Radiation Oncology Journal
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• v.15 no.4
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• pp.349-356
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• 1997

Purpose : To evaluate the efficacy of hyperfractionated radiation therapy in carcinoma of the cervix, especially on huge exophytic and endophytic stage Ib, IIa and IIb Materials and Materials : Fourty one patients with carcinoma of the cervix treated with hyperfractionated radiation therapy at the Department of Therapeutic Radiology, Dongsan Hospital, Keimyung University. School of Medicine from Jul, 1991 to Apr, 1994. According to FIGO s1aging system, therewere stage Ib (3 patients) IIa (6 patients) with exophytic ($\geq$5cm in dinmeter) and huge endophytic mass. and IIb (32 patients) with median age of 55 yeavs old. Radiation therapy consisted of hyperfractionated external irradition to the whole pelvis (120cGy/fraction, 2 fraction/day (minimum interval of 6 hours), 3600-5520cGy) and boost parametrial doses (for a total of 4480-6480cGy) with midline shield $(4\times10cm)$, and combined with intracavitary irradiation (up to 7480-8520cGy in Ib, IIa and 8480-9980cGy in IIb to point A). The maximum and mean follow up durations were 70 and 47 months respectively . Results : Five year local control rate was $78\%$ and the actuarial overall five year survival rate was $66.1\%$ for all patients, $44.4\%$ for stage Ib, IIa and $71.4\%$ for stage IIb. In bulky IIb (above 5cm in tumor size, 11 patients) five year local control rate and five rear survival rate was $88.9\%,\;73\%$ respectively Pelvic lymph node status (negative : $74\%,\;positive:25\%$, p=0.0015) was significant Prognostic factor affecting to five rear survival rate. There was marginally significant survival difference by total dose to A point ($>84Gy\;:\;70\%,\;>84Gy\;:\;42.8\%$, p=0.1). We consider that the difference of total dose to A point by stage (mean Ib,IIa : 79Gy. IIb 89Gy P=0.001) is one of the causes in worse local control and survival of Ib,IIa than IIb The overall recurrence rate was $39\%$ (16/41). The rates of local failure alone. distant failure alone. and combined local and distant failure were $9.7\%,\;19.5\%,\;and\;9.7\%$, respectively. Two Patients developed leukopenia ($\geq$ grade 3) and Three patients develoued grade 3 gastrointestinal complication. Above grade 3 complication was not noted. There was no treatment related death noted. Conclusion : We thought that it may be necessary to increase A point dose to more than 85Gy in hyperfractionated radiotherapy of huge exophytic and endophvtic stage Ib,IIa. We considered that hyperfractionated radiation therapy may be tolerable in huge exophytic and endophytic stage IIb cervical carcinoma with acceptable morbidity and possible survival gain but this was results in small patient group and will be confirmed by long term follow up in many patients.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.93-111
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• 2013

As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.177-189
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• 2013

In Smart Education, the roles of digital textbook is very important as face-to-face media to learners. The standardization of digital textbook will promote the industrialization of digital textbook for contents providers and distributers as well as learner and instructors. In this study, the following three objectives-oriented digital textbooks are looking for ways to standardize. (1) digital textbooks should undertake the role of the media for blended learning which supports on-off classes, should be operating on common EPUB viewer without special dedicated viewer, should utilize the existing framework of the e-learning learning contents and learning management. The reason to consider the EPUB as the standard for digital textbooks is that digital textbooks don't need to specify antoher standard for the form of books, and can take advantage od industrial base with EPUB standards-rich content and distribution structure (2) digital textbooks should provide a low-cost open market service that are currently available as the standard open software (3) To provide appropriate learning feedback information to students, digital textbooks should provide a foundation which accumulates and manages all the learning activity information according to standard infrastructure for educational Big Data processing. In this study, the digital textbook in a smart education environment was referred to open digital textbook. The components of open digital textbooks service framework are (1) digital textbook terminals such as smart pad, smart TVs, smart phones, PC, etc., (2) digital textbooks platform to show and perform digital contents on digital textbook terminals, (3) learning contents repository, which exist on the cloud, maintains accredited learning, (4) App Store providing and distributing secondary learning contents and learning tools by learning contents developing companies, and (5) LMS as a learning support/management tool which on-site class teacher use for creating classroom instruction materials. In addition, locating all of the hardware and software implement a smart education service within the cloud must have take advantage of the cloud computing for efficient management and reducing expense. The open digital textbooks of smart education is consdered as providing e-book style interface of LMS to learners. In open digital textbooks, the representation of text, image, audio, video, equations, etc. is basic function. But painting, writing, problem solving, etc are beyond the capabilities of a simple e-book. The Communication of teacher-to-student, learner-to-learnert, tems-to-team is required by using the open digital textbook. To represent student demographics, portfolio information, and class information, the standard used in e-learning is desirable. To process learner tracking information about the activities of the learner for LMS(Learning Management System), open digital textbook must have the recording function and the commnincating function with LMS. DRM is a function for protecting various copyright. Currently DRMs of e-boook are controlled by the corresponding book viewer. If open digital textbook admitt DRM that is used in a variety of different DRM standards of various e-book viewer, the implementation of redundant features can be avoided. Security/privacy functions are required to protect information about the study or instruction from a third party UDL (Universal Design for Learning) is learning support function for those with disabilities have difficulty in learning courses. The open digital textbook, which is based on E-book standard EPUB 3.0, must (1) record the learning activity log information, and (2) communicate with the server to support the learning activity. While the recording function and the communication function, which is not determined on current standards, is implemented as a JavaScript and is utilized in the current EPUB 3.0 viewer, ths strategy of proposing such recording and communication functions as the next generation of e-book standard, or special standard (EPUB 3.0 for education) is needed. Future research in this study will implement open source program with the proposed open digital textbook standard and present a new educational services including Big Data analysis.

• Radiation Oncology Journal
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• v.13 no.4
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• pp.359-368
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• 1995

Purpose : This is a retrospective analysis for pattern of failure, survival rate and prognostic factors of 114 patients with histologically proven invasive cancer of the uterine cervix treated with definitive irradiation. Materials and Methods : One hundred fourteen patients with invasive carcinoma of the cervix were treated with a combination of intracavitary irradiation using Fletcher-Suit applicator and external beam irradiation by 6MV X-ray at the Ewha Womans University Hospital between March 1982 and Mar 1990. The median age was 53 years(range:30-77 years). FIGO stage distribution was 19 for IB, 23 for IIA, 42 for IIB, 12 for IIIA and 18 for IIIB. Summation dose of external beam and intracavitary irradiation to point A was 80-90 Gy(median:8580 cGy) in early stage(IB-IIA) and 85-100 Gy(median:8850 cGy) in advanced stage(IIB-IIIB). Kaplan-Meier method was used to estimate the survival rate and multivariate analysis for progrostic factors was performed using the Log likelihood for Weibull Results : The pelvic failure rates by stage were $10.5{\%}$ for IB. $8.7{\%}$ for IIA, $23.8{\%}$ for IIB, $50.0{\%}$ for IIIA and $38.9{\%}$ for IIIB. The rate of distant metastasis by stage were $0{\%}$ for IB, $8.7{\%}$ for IIA, $4.8{\%}$ for IIB. $0{\%}$ for IIIA and $11.1{\%}$ for IIIB. The time of failure was from 3 to 50 months and with median of 15 months after completion of radiation therapy. There was no significant coorelation between dose to point A($\leq$90 Gy vs >90 Gy) and pelvic tumor control(P>0.05). Incidence rates of grade 2 rectal and bladder complications were $3.5{\%}$(4/114) and $7{\%}$(8/114), respectively and 1 patient had sigmoid colon obstruction and 1 patient had severe cystitis. Overall 5-year survival rate was $70.5{\%}$ and disease-free survival rate was $53.6{\%}$. Overall 5-year survival rate by stage was $100{\%}$ for IB, $76.9{\%}$ for IIA, $77.6{\%}$ for IIB $87.5{\%}$ for IIIA and $69.1{\%}$ for IIIB. Five-rear disease-free survival rate by stage was $81.3{\%}$ for IB, $67.9{\%}$ for IIA, $46.8{\%}$ for IIB, $45.4{\%}$ for IIIA and $34.4{\%}$ for IIIB. The prognostic factors for disease-free survival rate by multivariate analysis was performance status(p= 0.0063) and response rate after completion of radiation therapy(p= 0.0026) but stage, age and radiation dose to point A were not siginificant. Conclusion : The result of radiation therapy for early stage of the uterine cervix cancer was relatively good but local control rate and survival rate in advanced stage were poor inspite of high dose irradiation to point A above 90 Gy. Prospective randomized studies are recommended to establish optimal tumor doses for various stages and volume of carcinoma of uterine cervix, And ajuvant chemotherapy or radiation-sensitizing agents must be considered to increase the pelvic control and survival rate in advanced cancer of uterine cervix.