• Korean Journal of Radiology
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• v.22 no.8
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• pp.1279-1288
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• 2021

Objective: To assess the diagnostic performance of the Liver Imaging Reporting and Data System (LI-RADS) version 2018 treatment response algorithm (TRA) for the evaluation of hepatocellular carcinoma (HCC) treated with transarterial radioembolization. Materials and Methods: This retrospective study included patients who underwent transarterial radioembolization for HCC followed by hepatic surgery between January 2011 and December 2019. The resected lesions were determined to have either complete (100%) or incomplete (< 100%) necrosis based on histopathology. Three radiologists independently reviewed the CT or MR images of pre- and post-treatment lesions and assigned categories based on the LI-RADS version 2018 and the TRA, respectively. Diagnostic performances of LI-RADS treatment response (LR-TR) viable and nonviable categories were assessed for each reader, using histopathology from hepatic surgeries as a reference standard. Inter-reader agreements were evaluated using Fleiss κ. Results: A total of 27 patients (mean age ± standard deviation, 55.9 ± 9.1 years; 24 male) with 34 lesions (15 with complete necrosis and 19 with incomplete necrosis on histopathology) were included. To predict complete necrosis, the LR-TR nonviable category had a sensitivity of 73.3-80.0% and a specificity of 78.9-89.5%. For predicting incomplete necrosis, the LR-TR viable category had a sensitivity of 73.7-79.0% and a specificity of 93.3-100%. Five (14.7%) of 34 treated lesions were categorized as LR-TR equivocal by consensus, with two of the five lesions demonstrating incomplete necrosis. Interreader agreement for the LR-TR category was 0.81 (95% confidence interval: 0.66-0.96). Conclusion: The LI-RADS version 2018 TRA can be used to predict the histopathologic viability of HCCs treated with transarterial radioembolization.

• Journal of Radiation Protection and Research
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• v.28 no.1
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• pp.59-63
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• 2003

Purpose : Measurement of transmission dose is useful for in vivo dosimetry of QA purpose. The objective of this study is to develope an algorithm for estimation of tumor dose using measured transmission dose for open radiation field. Materials and Methods : Transmission dose was measured with various field size (FS), phantom thickness (Tp), and phantom chamber distance (PCD) with a acrylic phantom for 6 MV and 10 MV X-ray Source to chamber distance (SCD) was set to 150 cm. Measurement was conducted with a 0.6 cc Farmer type ion chamber. Using measured data and regression analysis, an algorithm was developed for estimation of expected reading of transmission dose. Accuracy of the algorithm was tested with flat solid phantom with various settings. Results : The algorithm consisted of quadratic function of log(A/P) (where A/P is area-perimeter ratio) and tertiary function of PCD. The algorithm could estimate dose with very high accuracy for open square field, with errors within ${\pm}0.5%$. For elongated radiation field, the errors were limited to ${\pm}1.0%$. Conclusion : The developed algorithm can accurately estimate the transmission dose in open radiation fields with various treatment settings.

• Korean Journal of Biological Psychiatry
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• v.7 no.2
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• pp.131-139
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• 2000

Even the pharmacotherapy is more effective than placebo for the treatment of depression, the outcome of pharmacoltherapy remains unsatisfactory for many patients. Apart from side effects, there are two major limitations of antidepressant therapy. One is the delayed onset of improvement and another is partial response. In order to address these clinical dilemmas, many psychiatrists more commonly employ add-on therapy. In past, the practice of using multiple drugs to enhance treatment response was called polypharamcy, and was disparaged as poor clinical practice. However, with improved understanding of how drugs affects the central nervous system and increased communication in journals and on computer networks about the relative merits of specific combinations, the scientific basis for the combining drugs is being defined. Indeed, the use of multiple medications as a stratege to enhance response has become both acceptable and widespread now a days. It is now referred to more positively as add-on therapy, co-medication, combination therapy, or drug augmentation. Thus, as the methods of practical strategies for treatment of depression, switching classes antidepressant drugs, combination therapy, augmentation strategies and brief treatment algorithm will be presented with items of considerations. However, when combination of drugs being tried, knowledges about the action of mechanism, pharamcokinetics, and pharmacodynamics are essential to cope with the possible adversive reactions and to get the appropriate responses for the treatment of depressive symptoms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.9
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• pp.2013-2018
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• 2011

Coronary angioplasty and coronary artery bypass graft, both are for the treatment of myocardial infarction widely used methods. For these procedures, there are especially difficulties in stenosis of blood vessels to diagnose accurately. To remedy this problem, by several researchers by using edge detection to detect stenosis of blood vessels has been studying. However, the results of using these methods vary defend on the vascular structure and the quality of the image. In this study, to improve these problems, the new algorithm is proposed. The proposed algorithm consists of methods to detect bifurcation of blood vessels and its ending point by using multi sampling, threshold and fuzzy algorithm. To evaluate the performance of the proposed algorithm, angiography was used for the different results of the blood vessels of the proposed algorithm, and the result was effective in detecting bifurcation of blood vessels and its ending point.

• Imaging Science in Dentistry
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• v.48 no.4
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• pp.245-254
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• 2018

Purpose: To assess the effects of object position in the field of view (FOV) and application of a metal artifact reduction (MAR) algorithm on the diagnostic accuracy of cone-beam computed tomography (CBCT) for the detection of vertical root fractures(VRFs). Materials and Methods: Sixty human single-canal premolars received root canal treatment. VRFs were induced in 30 endodontically treated teeth. The teeth were then divided into 4 groups, with 2 groups receiving metal posts and the remaining 2 only having an empty post space. The roots from different groups were mounted in a phantom made of cow rib bone, and CBCT scans were obtained for the 4 different groups. Three observers evaluated the images independently. Results: The highest frequency of correct diagnoses of VRFs was obtained with the object positioned centrally in the FOV, using the MAR algorithm. Peripheral positioning of the object without the MAR algorithm yielded the highest sensitivity for the first observer (66.7%). For the second and third observers, a central position improved sensitivity, with or without the MAR algorithm. In the presence of metal posts, central positioning of the object in the FOV significantly increased the diagnostic sensitivity and accuracy compared to peripheral positioning. Conclusion: Diagnostic accuracy was higher with central positioning than with peripheral positioning, irrespective of whether the MAR algorithm was applied. However, the effect of the MAR algorithm was more significant with central positioning than with peripheral positioning of the object in the FOV. The clinical experience and expertise of the observers may serve as a confounder in this respect.

• International Journal of Control, Automation, and Systems
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• v.1 no.1
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• pp.101-110
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• 2003

This paper introduces an identification method for nonlinear models in the form of rule-based Fuzzy-Neural Networks (FNN). In this study, the development of the rule-based fuzzy neural networks focuses on the technologies of Computational Intelligence (CI), namely fuzzy sets, neural networks, and genetic algorithms. The FNN modeling and identification environment realizes parameter identification through synergistic usage of clustering techniques, genetic optimization and a complex search method. We use a HCM (Hard C-Means) clustering algorithm to determine initial apexes of the membership functions of the information granules used in this fuzzy model. The parameters such as apexes of membership functions, learning rates, and momentum coefficients are then adjusted using the identification algorithm of a GA hybrid scheme. The proposed GA hybrid scheme effectively combines the GA with the improved com-plex method to guarantee both global optimization and local convergence. An aggregate objective function (performance index) with a weighting factor is introduced to achieve a sound balance between approximation and generalization of the model. According to the selection and adjustment of the weighting factor of this objective function, we reveal how to design a model having sound approximation and generalization abilities. The proposed model is experimented with using several time series data (gas furnace, sewage treatment process, and NOx emission process data from gas turbine power plants).

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.6
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• pp.1057-1064
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• 2009

This paper introduces a new approach based on a quantum-inspired evolutionary algorithm (QEA) to solve unit commitment (UC) problems. The UC problem is a complicated nonlinear and mixed-integer combinatorial optimization problem with heavy constraints. This paper proposes a bounded quantum evolutionary algorithm (BQEA) to effectively solve the UC problems. The proposed BQEA adopts both the bounded rotation gate, which is simplified and improved to prevent premature convergence and increase the global search ability, and the increasing rotation angle approach to improve the search performance of the conventional QEA. Furthermore, it includes heuristic-based constraint treatment techniques to deal with the minimum up/down time and spinning reserve constraints in the UC problems. Since the excessive spinning reserve can incur high operation costs, the unit de-commitment strategy is also introduced to improve the solution quality. To demonstrate the performance of the proposed BQEA, it is applied to the large-scale power systems of up to 100-unit with 24-hour demand.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.230-233
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• 2011

Chronic disease is linked to patient's' lifestyle. Therefore, doctor has to monitor his/her patient over time. This may involve reviewing many reports, finding any changes, and modifying several treatments. One solution to optimize the burden is using a visualizing tool over time such as a timeline-based visualization tool where all reports and medicine are integrated in a problem centric and time-based style to enable the doctor to predict and adjust the treatment plan. This solution was proposed by Bui et. al. [2] to observe the medical history of a patient. However, there was limitation of studying the diabetes patient's history to find out what was the cause of the current development in patient's condition; moreover what would be the prediction of current implication in one of the diabetes' related factors (such as fat, cholesterol, or potassium). In this paper, we propose a Grid-based Interactive Diabetes System (GIDS) to support bioinformatics analysis application for diabetes diseases. GIDS used an agglomerative clustering algorithm as clustering correlation algorithm as primary algorithm to focus medical researcher in the findings to predict the implication of the undertaken diabetes patient. The algorithm was Chronological Clustering proposed by P. Legendre [11] [12].

• Progress in Medical Physics
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• v.30 no.4
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• pp.150-154
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• 2019

The objective of this study is to monitor the radiation doses delivered to a cardiac implantable electronic device (CIED) by comparing the absorbed doses calculated by a commercial treatment planning system (TPS) to those measured by an in vivo dosimeter. Accurate monitoring of the radiation absorbed by a CIED during radiotherapy is necessary to prevent damage to the device. We conducted this study on three patients, who had the CIED inserted and were to be treated with radiotherapy. Treatment plans were generated using the Eclipse system, with a progressive resolution photon optimizer algorithm and the Acuros XB dose calculation algorithm. Measurements were performed on the patients using optically stimulated luminescence detectors placed on the skin, near the CIED. The results showed that the calculated doses from the TPS were up to 5 times lower than the measured doses. Therefore, it is recommended that in vivo dosimetry be conducted during radiotherapy for CIED patients to prevent damage to the CIED.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.208-210
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• 2002

In a treatment planning for actual patients with a complex internal structure, we often expect that proton beams, which pass through both a bolus and the heterogeneity in body, will form complex dose distributions. Therefore, the accuracy of the calculated dose distributions has to be verified for such a complex object. Then dose distributions formed by proton beams passing through both the bolus and phantoms simulating a clinical heterogeneity in patients were measured using a silicon semiconductor detector. The calculated results by the range-modulated pencil beam algorithm (RMPBA) produced large errors compared with the measured dose distributions since dose calculation using the RMPBA could not predict accurately the edge-scattering effect both in the bolus and in clinical heterogeneous phantoms. On the other hand, in spite of this troublesome heterogeneity, calculated results by the simplified Monte Carlo (SMC) method reproduced the experimental ones well. It is obvious that the dose-calculations by the SMC method will be more useful for application to the treatment planning for proton therapy.