소형동물 전임상실험을 위한 하이퍼스펙트럼 영상장비 연구

Research about Hyperspectral Imaging System for Pre-Clinical testing of Small Animal

  • 발행 : 2007.12.01

초록

In this study we have developed a hyperspectrum imaging system for highly sensitive and effective imaging analysis. An optical setup was designed using acoustic optical tunable filter (AOTF) for high sensitive hyperspectrum imaging. Light emitted by mercury lamp gets split in to diffracted and undiffracted beams while passing though AOTF. GFP transfected HEK-293 cell line was used as a model for in vitro imaging analysis. Cells were first, analyzed by fluorescence microscope followed by flow cytometric analysis. Flow cytometric analysis showed 66.31% transfection yield in GFP transfected HEK-293 cells. Various images of GFP transfected HEK-293 cell were grabbed by collecting the diffracted light using a CCD over a dynamic range of frequency of 129-171 MHz with an interval of 3 MHz. Subsequently, for in vivo image analysis of GFP transfected cells in mouse, a whole-body-imaging system was constructed. The blue light of 488 nm wavelength was obtained from a Xenon arc lamp using an appropriate filter and transmitted through an optical cable to a ring illuminator. To check the efficacy of the newly developed whole-body-imaging system, a comparative imaging analysis was performed on a normal mouse in presence and absence of Xenon arc irradiation. The developed hyperspectrum imaging analysis with AOTF showed the highest intensity of green fluorescent protein at 153 MHz of frequency and 494 nm of wavelength. However, the fluorescence intensity remained same as that of the background below 138 MHz (475 nm) and above 162 MHz (532 nm). The mouse images captured using the constructed whole-body-imaging system appeared monochromatic in absence of Xenon arc irradiation and blue when irradiated with Xenon arc lamp. Nevertheless, in either case mouse images appeared clearly.

키워드

참고문헌

  1. 이우길, 분자세포생물학뉴스, '신약개발에서 최근 스크리닝 기술', 17권, 4호, pp. 36-49, 2005
  2. 민정준, 분자세포생물학뉴스, '생체 분자 광 영상', 17권 3호, pp. 21-35, 2005
  3. Arion F. Chatziioannou, Proc. 'Instrumentation for Molecular Imaging in Preclinical Research: Micro-PET and Micro-SPECT' Am. Thorac. Soc. Vol. 2. pp. 533-536, 2005 https://doi.org/10.1513/pats.200508-079DS
  4. Weissleder, R. and Mahmood, U. 'Molecular imaging', Radiology 219, pp, 316-333, 2001 https://doi.org/10.1148/radiology.219.2.r01ma19316
  5. K. Chao, P. Mehl, and Y. R. Chen, 'Use of hyperand multi-spectral imaging for detection of chicken skin. tumors', Applied Engineering in Agriculture, Vol. 18(1), pp. 113-119, 2002
  6. MediSpectra Inc., http://www.medispectra.com/news/news.html. 2006
  7. G. Shaw and D. Manolakis, 'Signal Processing for Hyperspectral. Image Exploitation', IEEE Signal Processing Magazine, Vol. 19(1), pp. 12-16, 2002
  8. D. Landgrebe, 'Hyperspectral Image Data Analysis as a High Dimensional Signal Processing Problem', IEEE Signal Processing Magazine, Vol. 19(1), pp. 17-28, 2002
  9. C. Chang, Q. Du, T. Sun, and M. Althouse, 'A joint band prioritization and band decorrelation approach to band selection for hyperspectral image classification', IEEE Trans. Geoscience and Remote Sensing, Vol. 37(6), pp. 2631-2641, 1999 https://doi.org/10.1109/36.803411
  10. S.G. Kong, Y.R. Chen, I. Kim, and M.S. Kim, 'Analysis of. Hyperspectral Fluorescence Images for Poultry Skin Tumor. Inspection', Applied Optics, Vol. 43(4), pp. 824-833, 2004 https://doi.org/10.1364/AO.43.000824
  11. T. Dinh, B. Cullum and P. Kasili, 'Development of a multispectral imaging system for medical applications', J. Phys. D: Appl. Phys. 36, pp. 1663-1668, 2003 https://doi.org/10.1088/0022-3727/36/14/302