Dark-Field Imaging: Recent developments and potential clinical applications |
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Affiliation: | 1. Center for Information Storage Device, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea;2. School of Mechanical Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea;3. Department of Mechanical Engineering, Konyang University, 121 Daehak-ro, Nonsan-si, Chungcheongnam-do 32992, Korea |
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Abstract: | This paper describes an X-ray phase contrast imaging technique using analyzer-based optics called X-ray Dark-Field Imaging that has been under development for the past 10 years. We describe the theory behind XDFI, the X-ray optics required for implementing it in practice, and algorithms used for 2D, 2.5D, and 3D image reconstruction. The XDFI optical chain consists of an asymmetrically cut, Bragg-type monochromator-collimator that provides a planar monochromatic X-ray beam, a positioning stage for the specimens, a Laue-case angle analyzer, and one or two cameras to capture the dark and bright field images. We demonstrate the soft-tissue discrimination capabilities of XDFI by reconstructing images with absorption and phase contrast. By using a variety of specimens such as breast tissue with cancer, joints with articular cartilage, ex-vivo human eye specimen, and others, we show that refraction-based contrast derived from XDFI is more effective in characterizing anatomical features, articular pathology, and neoplastic disease than conventional absorption-based images. For example, XDFI of breast tissue can discriminate between the normal and diseased terminal duct lobular unit, and between invasive and in-situ cancer. The final section of this paper is devoted to potential future developments to enable clinical and histo-pathological applications of this technique. |
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Keywords: | X-ray dynamical diffraction Monochromator Laue angle analyzer Refraction contrast Phase contrast Medical imaging Human soft tissue Breast cancer Articular cartilage Artery damage Synchrotron radiation High contrast High spatial resolution |
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