대한영상의학회지 (Journal of the Korean Society of Radiology)

  • 제63권1호
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  • Pages.49-56
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  • 2010
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  • 1738-2637(pISSN)
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  • 2288-2928(eISSN)
대한영상의학회 (The Korean Society of Radiology)
권호 표지

서포트 벡터 머신을 이용한 영상기반의 임상 결정 보조 시스템에 근거한 전립선암의 정낭침습 판단: 1.5T와 3.0T 전립선 자기공명영상에서의 임상 결정 보조 시스템의 정확성 비교

Comparison of Accuracies for Image-based 1.5T and 3T MRI Using a Clinical Decision Support System Driven by a Support Vector Machine to Detect Seminal Vesicle Invasion of Prostate Cancer

  • 김상윤 (서울대학교 의과대학 영상의학과) ;
  • 이학종 (서울대학교 의과대학 영상의학과) ;
  • 정대철 (국립암센터 영상의학과) ;
  • 황성일 (서울대학교 의과대학 영상의학과) ;
  • 성창규 (서울대학교 의과대학 영상의학과) ;
  • 조정연 (서울대학교 의과대학 영상의학과) ;
  • 김승협 (서울대학교 의과대학 영상의학과)
  • Kim, Sang-Youn (Department of Radiology, Seoul National University College of Medicine) ;
  • Lee, Hak-Jong (Department of Radiology, Seoul National University College of Medicine) ;
  • Jung, Dae-Chul (Department of Radiology, Research Institute and Hospital, National Cancer Center) ;
  • Hwang, Sung-Il (Department of Radiology, Seoul National University College of Medicine) ;
  • Sung, Chang-Kyu (Department of Radiology, Seoul National University College of Medicine) ;
  • Cho, Jeong-Yeon (Department of Radiology, Seoul National University College of Medicine) ;
  • Kim, Seung-Hyup (Department of Radiology, Seoul National University College of Medicine)
  • 투고 : 2010.01.18
  • 심사 : 2010.03.21
  • 발행 : 2010.07.01
⟨ 이전 논문 다음 논문 ⟩

초록

목적: 서포트 벡터 머신을 이용한 영상기반의 임상 결정 보조 시스템을 만들고, 이를 이용하여 정낭침습의 진단에 있어 1.5T와 3.0T 기기 간 보조 시스템의 진단 정확성을 비교하였다.대상과 방법: 전립선암으로 진단받고 1.5T 혹은 3.0T 자기공명영상을 시행하고 나서 전립선절제술을 받은 548명 환자를 대상으로 하였다. 1.5T 및 3.0T 기기로 검사한 집단을 각각 임의로 훈련 대상군과 테스트 대상군으로 분류하였다. 영상소견은 2명의 영상의학전문의가 합의로 결정하였다 서포트 벡터 머신을 이용하여 훈련 대상군의 정낭의 모양, 나이, 전립선 특이 항원 수치를 입력 값으로, 전립선암의 정낭침습 가능성을 출력 값으로 하는 임상 결정 보조 시스템을 만들었다. 이 모델을 각 테스트 대상군에 적용시켜 출력 값의 정확성을 분석하였다. 병리조직학적 소견을 고려하여, 1.5T와 3.0T에서 정낭침습 진단에 있어 민감도, 특이도, 정확도를 비교하였다. 결과: 1.5T 모델의 특이도, 정확도는 73.1%, 74.6%이었고, 3.0T 모델의 특이도, 정확도는 90.4%, 88.7%이었다. 정낭침습 진단에 있어 3.0T 모델의 특이도 및 정확도가 1.5T 모델보다 유의하게 높았다(p < 0.05). 결론: 전립선암의 정낭침습에 대해 서포트 벡터 머신을 이용하여 영상기반의 임상 결정 보조 시스템을 만들 수 있었다. 정낭침습 진단능의 비교에서, 1.5T보다는 3.0T 기기를 이용한 보조 시스템이 더 높은 특이도와 정확도를 보였다.

Purpose: The purpose of this study is to develop image-based clinical decision support systems (CDSSs) using support vector machine models (SVMs) for the detection of seminal vesicle invasion (SVI) of prostate cancer and to compare the accuracies of 1.5T and 3.0T MR CDSSs. Materials and Methods: A total of 548 prostate cancer patients who underwent a prostatectomy and preoperative MR using 1.5T or 3.0T were enrolled in this study. Each 1.5T and 3.0T group was subdivided into the training group and test group, arbitrarily. Images were analyzed in consensus by two radiologists. CDSS was constructed with input data that has the appearance of a seminal vesicle, PSA level and age in each training group, and with the output data of the probability for SVI using SVMs. The accuracy of the output data were evaluated with data of each test group. After a histopathologic correlation, the sensitivity, specificity and accuracy for the detection of SVI were compared in both 1.5T and 3.0T. Results: For the diagnosis of SVI, the specificity and the accuracy of the 3.0T model were all statistically superior to those of the 1.5T model (90.4% vs. 73.1%; 88.7% vs. 74.6%) (p<0.05). Conclusion: The image-based CDSS for the detection of SVI was successfully constructed using SVM. According to our CDSSs, the specificity and accuracy of 3.0T were superior to those of 1.5T.

키워드

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