Journal of the Korean Society of Radiology (대한영상의학회지)

The Korean Society of Radiology (대한영상의학회)
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Adaptive Image Rescaling for Weakly Contrast-Enhanced Lesions in Dedicated Breast CT: A Phantom Study

약하게 조영증강된 병변의 유방 전용 CT 영상의 대조도 개선을 위한 적응적 영상 재조정 방법: 팬텀 연구

  • Bitbyeol Kim (School of Mechanical Engineering and the Center for Advanced Medical Engineering Research, Pusan National University) ;
  • Ho Kyung Kim (School of Mechanical Engineering and the Center for Advanced Medical Engineering Research, Pusan National University) ;
  • Jinsung Kim (Department of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of Medicine) ;
  • Yongkan Ki (Department of Radiation Oncology, Pusan National University School of Medicine) ;
  • Ji Hyeon Joo (Department of Radiation Oncology and Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital) ;
  • Hosang Jeon (Department of Radiation Oncology and Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital) ;
  • Dahl Park (Department of Radiation Oncology, Pusan National University Hospital) ;
  • Wontaek Kim (Department of Radiation Oncology, Pusan National University School of Medicine) ;
  • Jiho Nam (Department of Radiation Oncology, Pusan National University Hospital) ;
  • Dong Hyeon Kim (Department of Radiation Oncology, Pusan National University Hospital)
  • 김빛별 (부산대학교 기계공학부) ;
  • 김호경 (부산대학교 기계공학부) ;
  • 김진성 (연세대학교 의과대학 방사선종양학교실) ;
  • 기용간 (부산대학교 의과대학 방사선종양학교실) ;
  • 주지현 (양산부산대학교병원 방사선종양학과, 의생명융합연구소) ;
  • 전호상 (양산부산대학교병원 방사선종양학과, 의생명융합연구소) ;
  • 박달 (부산대학교병원 방사선종양학과) ;
  • 김원택 (부산대학교 의과대학 방사선종양학교실) ;
  • 남지호 (부산대학교병원 방사선종양학과) ;
  • 김동현 (부산대학교병원 방사선종양학과)
  • Received : 2020.11.18
  • Accepted : 2021.06.22
  • Published : 2021.11.01
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Abstract

Purpose Dedicated breast CT is an emerging volumetric X-ray imaging modality for diagnosis that does not require any painful breast compression. To improve the detection rate of weakly enhanced lesions, an adaptive image rescaling (AIR) technique was proposed. Materials and Methods Two disks containing five identical holes and five holes of different diameters were scanned using 60/100 kVp to obtain single-energy CT (SECT), dual-energy CT (DECT), and AIR images. A piece of pork was also scanned as a subclinical trial. The image quality was evaluated using image contrast and contrast-to-noise ratio (CNR). The difference of imaging performances was confirmed using student's t test. Results Total mean image contrast of AIR (0.70) reached 74.5% of that of DECT (0.94) and was higher than that of SECT (0.22) by 318.2%. Total mean CNR of AIR (5.08) was 35.5% of that of SECT (14.30) and was higher than that of DECT (2.28) by 222.8%. A similar trend was observed in the subclinical study. Conclusion The results demonstrated superior image contrast of AIR over SECT, and its higher overall image quality compared to DECT with half the exposure. Therefore, AIR seems to have the potential to improve the detectability of lesions with dedicated breast CT.

목적 Dedicated breast CT (이하 DBCT)는 유방 압박의 고통이 없는 영상 진단 기법으로 최근 주목받고 있다. 본 연구에서는 DBCT 영상에서 약하게 조영증강된 작은 병변의 검출률을 높이기 위해 피사체의 기하학적 정보를 이용하여 최적의 영상 문턱값을 제공하는 adaptive image rescaling (이하 AIR) 기법을 제안하였다. 대상과 방법 5개의 동일 크기의 구멍과 서로 다른 크기의 구멍을 가지는 두 개의 디스크를 각각 제작하고, 이를 60 kVp와 100 kVp로 스캔하여 single-energy CT (이하 SECT), dual-energy CT (이하 DECT), 그리고 AIR 영상을 생성하였다. 전임상 평가를 위해 돼지 조직 영상도 획득하였다. Image contrast (이하 IC)와 contrast-to-noise ratio (이하 CNR)로 화질을 평가하였으며, student's t test를 이용하여 영상 간 화질의 차이를 검증하였다. 결과 AIR의 평균 IC (0.70)는 DECT (0.94)의 74.5%로 나타났으며, SECT (0.22) 보다 318.2% 높았다. 또한 AIR의 평균 CNR (5.08)은 SECT (14.30)의 35.5%로 나타났고 DECT (2.28) 보다 222.8% 높게 측정되었다. 돼지 조직의 전임상 평가 결과도 비슷한 양상을 보였다. 결론 AIR은 SECT보다 높은 영상 대조도를 가지며, 50% 선량만으로도 DECT에 비견할 만한 화질 성능을 제공할 수 있음을 확인하였다. 따라서 AIR은 DBCT 영상에서 약하게 조영증강된 병변의 검출률을 개선할 수 있을 것으로 생각된다.

Keywords

Acknowledgement

This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Korean government (2017R1D1A1B03031351 and 2015M3A9E2067002).

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