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Computer Simulation for X-ray Breast Elastography

X선 유방 탄성 영상을 위한 컴퓨터 모의 실험

  • Kim, Hyo-Geun (Dept. of Biomedical Engineering, Kyung Hee University) ;
  • Aowlad Hossain, A.B.M. (Dept. of Biomedical Engineering, Kyung Hee University) ;
  • Lee, Soo-Yeol (Dept. of Biomedical Engineering, Kyung Hee University) ;
  • Cho, Min-Hyoung (Dept. of Biomedical Engineering, Kyung Hee University)
  • 김효근 (경희대학교 생체의공학과) ;
  • ;
  • 이수열 (경희대학교 생체의공학과) ;
  • 조민형 (경희대학교 생체의공학과)
  • Received : 2010.12.17
  • Accepted : 2011.03.31
  • Published : 2011.04.30

Abstract

Breast cancer is the most frequently appearing cancer in women, these days. To reduce mortality of breast cancer, periodic check-up is strongly recommended. X-ray mammography is one of powerful diagnostic imaging systems to detect 50~100 um micro-calcification which is the early sign of breast cancer. Although x-ray mammography has very high spatial resolution, it is not easy yet to distinguish cancerous tissue from normal tissues in mammograms and new tissue characterizing methods are required. Recently ultrasound elastography technique has been developed, which uses the phenomenon that cancerous tissue is harder than normal tissues. However its spatial resolution is not enough to detect breast cancer. In order to develop a new elastography system with high resolution we are developing x-ray elasticity imaging technique. It uses the small differences of tissue positions with and without external breast compression and requires an algorithm to detect tissue displacement. In this paper, computer simulation is done for preliminary study of x-ray elasticity imaging. First, 3D x-ray breast phantom for modeling woman's breast is created and its elastic model for FEM (finite element method) is generated. After then, FEM experiment is performed under the compression of the breast phantom. Using the obtained displacement data, 3D x-ray phantom is deformed and the final mammogram under the compression is generated. The simulation result shows the feasibility of x-ray elasticity imaging. We think that this preliminary study is helpful for developing and verifying a new algorithm of x-ray elasticity imaging.

Keywords

References

  1. C.H. Lee and J.W. Nho, "Current opinion for breast cancer screening," Korean journal of obstetrics and gynecology, vol. 51, no. 9, pp. 933-942, 2008.
  2. C. Zyganitidis, K. Bliznakova and N. Pallikarakis, "A novel simulation algorithm for soft tissue compression," Med. Bio. Eng. Comput. vol. 45, no. 7, pp. 661-669, 2007. https://doi.org/10.1007/s11517-007-0205-y
  3. K. Bliznakova, Z. Bliznakov, V. Bravou, Z. Kolitsi and N. Pallikarakis, "A three-dimensional breast software phantom for mammography simulation," Phys. Med. Biol, vol. 48, no. 22, pp. 3699-3719, 2003. https://doi.org/10.1088/0031-9155/48/22/006
  4. http://people.ee.duke.edu/-jshorey/BreastPhantom.htm
  5. J.F. Veenland, J.L. Grashuis, F. van der Meer, A.L. Beckers A and E.S. Gelsema, "Estimation of fractal dimension in radiographs," Med. Phys. vol. 23, no. 4, pp. 585-594, 1996. https://doi.org/10.1118/1.597816
  6. F.O. Bochud, J.F. Valley, F.R. Verdun, C. Hessler, P. Schnyder, "Estimation of the noisy component of anatomical backgrounds.," Med. Phys, vol. 26, no. 7, pp. 1365-1370, 1999. https://doi.org/10.1118/1.598632
  7. J.E. Bresenham, "Algorithm for computer control of a digital plotter.," IBM System Journal, vol. 4, no. 1, pp. 25-30, 1965. https://doi.org/10.1147/sj.41.0025
  8. F. Lefebvre, H. Benali, R. Gilles and R. Di Paola, "A Simulation model of clustered breast microcalcifications," Med. Phys, vol. 21, no. 12, pp. 1865-74, 1994. https://doi.org/10.1118/1.597186
  9. A. Samani, J. Zubovits and D. Plewes, "Elastic moduli of normal and pathological human breast tissues: an inversion-technique-based investigation of 169 samples," Phys. Med. Biol., vol. 52, no. 6, pp. 1565-1573, 2007. https://doi.org/10.1088/0031-9155/52/6/002