Proximal caries detection using digital subtraction radiography in the artificial caries activity model

인공 치아우식 발생 모델에서 디지털 방사선 공제술을 이용한 인접면 치아우식증의 진단

  • Park, Jeong-Hoon (Department of Biomedical Engineering, School of Medicine, Kyung Hee University, Healthcare Industry Research Institute, Kyung Hee University) ;
  • Choi, Yong-Suk (Department of Oral and Maxillofacial Radiology, Institute of Oral Biology, School of Dentistry, Kyung Hee University) ;
  • Hwang, Eui-Hwan (Department of Oral and Maxillofacial Radiology, Institute of Oral Biology, School of Dentistry, Kyung Hee University) ;
  • Lee, Gi-Ja (Department of Biomedical Engineering, School of Medicine, Kyung Hee University, Healthcare Industry Research Institute, Kyung Hee University) ;
  • Choi, Sam-Jin (Department of Biomedical Engineering, School of Medicine, Kyung Hee University, Healthcare Industry Research Institute, Kyung Hee University) ;
  • Park, Young-Ho (Department of Biomedical Engineering, School of Medicine, Kyung Hee University, Healthcare Industry Research Institute, Kyung Hee University) ;
  • Kim, Kyung-Sook (Department of Biomedical Engineering, School of Medicine, Kyung Hee University, Healthcare Industry Research Institute, Kyung Hee University) ;
  • Jin, Hyun-Seok (Department of Biomedical Engineering, School of Medicine, Kyung Hee University, Healthcare Industry Research Institute, Kyung Hee University) ;
  • Hong, Kyung-Won (Department of Biomedical Engineering, School of Medicine, Kyung Hee University, Healthcare Industry Research Institute, Kyung Hee University) ;
  • Oh, Berm-Seok (Department of Biomedical Engineering, School of Medicine, Kyung Hee University, Healthcare Industry Research Institute, Kyung Hee University) ;
  • Park, Hun-Kuk (Department of Biomedical Engineering, School of Medicine, Kyung Hee University, Healthcare Industry Research Institute, Kyung Hee University)
  • 박정훈 (경희대학교 의과대학 의공학교실, 경희대학교 의료산업연구원) ;
  • 최용석 (경희대학교 치의학전문대학원 구강악안면방사선학교실, 구강생물학연구소) ;
  • 황의환 (경희대학교 치의학전문대학원 구강악안면방사선학교실, 구강생물학연구소) ;
  • 이기자 (경희대학교 의과대학 의공학교실, 경희대학교 의료산업연구원) ;
  • 최삼진 (경희대학교 의과대학 의공학교실, 경희대학교 의료산업연구원) ;
  • 박영호 (경희대학교 의과대학 의공학교실, 경희대학교 의료산업연구원) ;
  • 김경숙 (경희대학교 의과대학 의공학교실, 경희대학교 의료산업연구원) ;
  • 진현석 (경희대학교 의과대학 의공학교실, 경희대학교 의료산업연구원) ;
  • 홍경원 (경희대학교 의과대학 의공학교실, 경희대학교 의료산업연구원) ;
  • 오범석 (경희대학교 의과대학 의공학교실, 경희대학교 의료산업연구원) ;
  • 박헌국 (경희대학교 의과대학 의공학교실, 경희대학교 의료산업연구원)
  • Published : 2009.03.31

Abstract

Purpose: The purpose of the experiment was to evaluating the diagnostic ability of dental caries detection using digital subtraction in the artificial caries activity model. Materials and Methods: Digital radiographies of five teeth with 8 proximal surfaces were obtained by CCD sensor (Kodak RVG 6100 using a size #2). The digital radiographic images and subtraction images from artificial proximal caries were examined and interpreted. In this study, we proposed novel caries detection method which could diagnose the dental proximal caries from single digital radiographic image. Results: In artificial caries activity model, the range of lesional depth was $572-1,374{\mu}m$ and the range of lesional area was $36.95-138.52mm^2$. The lesional depth and the area were significantly increased with demineralization time (p<0.001). Furthermore, the proximal caries detection using digital subtraction radiography showed high detection rate compared to the proximal caries examination using simple digital radiograph. Conclusion: The results demonstrated that the digital subtraction radiography from single radiographic image of artificial caries was highly efficient in the detection of dental caries compared to the data from simple digital radiograph.

Keywords

References

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