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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학위논문
- 저자정보
- 지도교수
- 박현진
- 발행연도
- 2014
- 저작권
- 성균관대학교 논문은 저작권에 의해 보호받습니다.
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초록· 키워드
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Accurate assessment of viability of hepatocellularcarcinoma (HCC) after transcatheter arterial chemoembolization(TACE) is important for therapy planning. The purpose of this study is to determine the diagnostic value of a novel image analysis method called parametric response mapping (PRM) in predicting viability of tumor in HCC treated with TACE for dynamic CT images. In method, 35 patients who had 35 iodized-oil defect areas(IODAs) in HCCs treated with TACE were included in our study. These patients were divided into two groups, one group with viable tumors (n = 22) and the other group with non-viable tumors (n = 13) in the IODA. All patients were followed up using triple-phase dynamic CT after the treatment. We compared (a) manual analysis, (b) using PRM results, and (c) using PRM results with automatic classifier to distinguish between two tumor groups based on dynamic CT images from two longitudinal exams. Two radiologists performed the manual analysis. The PRM approach was implemented using prototype software. We adopted an off-the-shelf k nearest neighbor (kNN) classifier and leave-one-out cross-validation for the third approach. The area under the curve(AUC) values were compared for three approaches. Manual analysis yielded AUC of 0.74, using PRM results yielded AUC of 0.84, and using PRM results with an automatic classifier yielded AUC of 0.87. In conclusions, we improved upon the standard manual analysis approach by adopting a novel image analysis method of PRM combined with an automatic classifier.
목차
Abstract 1Ⅰ. Introduction 3Ⅱ. Material and Methods 72.1. Patients 72.2 CT imaging 92.3 Transcatheter arterial chemoembolization 112.4 Image-processing software and PRM 122.5 Automatic classifier based on PRM 202.6 Image analysis; manual approach 22Ⅲ. Results 253.1 Group Difference using PRM Analysis 253.2 Comparison of Approaches to Distinguish Tumor Groups 28Ⅳ. Discussion 31Ⅴ. Contribution 35References 37Korean Abstract 47
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