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High energy x-ray phase contrast CT using glancing-angle grating interferometers
1. F. Pfeiffer, T. Weitkamp, O. Bunk, and C. David, “Phase retrieval and differential phase-contrast imaging with low-brilliance X-ray sources,” Nat. Phys. 2, 258–261 (2006).
3. F. Pfeiffer, M. Bech, O. Bunk, P. Kraft, E. F. Eikenberry, Ch. Brönnimann, C. Grünzweig, and C. David, “Hard-X-ray dark-field imaging using a grating interferometer,” Nat. Mater. 7, 134–137 (2008).
5. P. B. Noel, J. Herzen, A. A. Fingerle, M. Willner, M. K. Stockmar, D. Hahn, M. Settles, E. Drecoll, I. Zanette, T. Weitkamp, E. J. Rummeny, and F. Pfeiffer, “Evaluation of the potential of phase-contrast computed tomography for improved visualization of cancerous human liver tissue,” Z. Med. Phys. 23(3), 204–211 (2013).
6. F. Pfeiffer, O. Bunk, C. David, M. Bech, G. Le Duc, A. Bravin, and P. Cloetens, “High-resolution brain tumor visualization using three-dimensional x-ray phase contrast tomography,” Phys. Med. Biol. 52, 6923 (2007).
7. A. Tapfer, R. Braren, M. Bech, M. Willner, I. Zanette, T. Weitkamp, M. Trajkovic-Arsic, J. T. Siveke, M. Settles, M. Aichler, A. Walch, and F. Pfeiffer, “X-ray phase-contrast CT of a pancreatic ductal adenocarcinoma mouse model,” PLoS One 8, e58439 (2013).
9. H. Hetterich, S. Fill, J. Herzen, M. Willner, I. Zanette, T. Weitkamp, A. Rack, U. Schüller, M. Sadeghi, R. Brandl, S. Adam-Neumair, M. Reiser, F. Pfeiffer, F. Bamberg, and T. Saam, “Grating-based X-ray phase-contrast tomography of atherosclerotic plaque at high photon energies,” Z. Med. Phys. 23(3), 194–203 (2013).
10. A. Momose, W. Yashiro, Y. Takeda, Y. Suzuki, and T. Hattori, “Phase tomography by x-ray talbot interferometry for biological imaging,” Jpn. J. Appl. Phys. 45, 5254–5262 (2006).
11. R. Raupach and T. Flohr, “Performance evaluation of x-ray differential phase contrast computed tomography (PCT) with respect to medical imaging,” Med. Phys. 39, 4761–4774 (2012).
12. S. Grandl, M. Willner, J. Herzen, D. Mayr, S. D. Auweter, A. Hipp, F. Pfeiffer, M. Reiser, and K. Hellerhoff, “Evaluation of phase-contrast CT of breast tissue at conventional x-ray sources – presentation of selected findings,” Z. Med. Phys. 23(3), 212–221 (2013).
13. F. Pfeiffer, J. Herzen, M. Willner, M. Chabior, S. Auweter, M. Reiser, and F. Bamberg, “Grating-based x-ray phase contrast for biomedical imaging applications,” Z. Med. Phys. 23(3), 176–185 (2013).
15. X. Tang, Y. Yang, and S. Tang, “Characterization of imaging performance in differential phase contrast CT compared with the conventional CT: Spectrum of noise equivalent quanta NEQ(k),” Med. Phys. 39, 4467–4482 (2012).
16. D. Stutman and M. Finkenthal, “Glancing angle Talbot-Lau grating interferometers for phase contrast imaging at high x-ray energy,” Appl. Phys. Lett. 101, 091108 (2012).
17. T. Donath, M. Chabior, F. Pfeiffer, O. Bunk, E. Reznikova, J. Mohr, E. Hempel, S. Popescu, M. Hoheisel, M. Schuster, J. Baumann, and C. David, “Inverse geometry for grating-based x-ray phase-contrast imaging,” J. Appl. Phys. 106, 054703 (2009).
18. D. Stutman, J. W. Stayman, M. Finkenthal, and J. H. Siewerdsen, “High energy x-ray phase-contrast imaging using glancing angle grating interferometers,” Proc. SPIE 8668, 866814 (2013).
19. X. Wu, A. E. Deans, and H. Liu, “X-ray diagnostic techniques” in Biomedical Photonics Handbook (CRC Press, 2003), pp. 26–2526–28.
20. I. Zanette, M. Bech, A. Rack, G. Le Duc, P. Tafforeau, C. David, J. Mohr, F. Pfeiffer, and T. Weitkamp, “Trimodal low-dose x-ray tomography,” Proc. Natl. Acad. Sci. U.S.A. 109, 10199–10204 (2012).
21. A. E. Anderson, B. J. Ellis, C. L. Peters, and J. A. Weiss, “Cartilage thickness: Factors influencing multi-detector CT measurements in a phantom study,” Radiology 246, 133–141 (2008).
22. M. Tapiovaara and T. Siiskonen, “A Monte Carlo program for calculating patient doses in medical x-ray examinations (2nd Ed.),” Report No. STUK-A231 (STUK Helsinki, Finland, 2008).
23. W. Zbijewski, P. De Jean, P. Prakash, Y. Ding, J. W. Stayman, N. Packard, R. Senn, D. Yang, J. Yorkston, A. Machado, J. A. Carrino, and J. H. Siewerdsen, “A dedicated cone-beam CT system for musculoskeletal extremities imaging: Design, optimization, and initial performance characterization,” Med. Phys. 38, 4700–4713 (2011).
24. R. Raupach and T. Flohr, “Analytical evaluation of the signal and noise propagation in x-ray differential phase-contrast computed tomography,” Phys. Med. Biol. 2219, 2219–2244 (2011).
25. T. Pflederer, L. Rudofsky, D. Ropers, S. Bachmann, M. Marwan, W. G. Daniel, and S. Achenbach, “Image quality in a low radiation exposure protocol for retrospectively ECG-gated coronary CT angiography,” AJR, Am. J. Roentgenol. 192, 1045–1050 (2009).
27. J. B. Thibault, K. D. Sauer, C. A. Bouman, and J. Hsieh, “A three-dimensional statistical approach to improved image quality for multislice helical CT,” Med. Phys. 34, 4526–4544 (2007).
28. S. Singh, M. K. Kalra, S. Do, J. B. Thibault, H. Pien, O. J. O’Connor, and M. A. Blake, “Comparison of hybrid and pure iterative reconstruction techniques with conventional filtered back projection: Dose reduction potential in the abdomen,” J. Comput. Assist. Tomogr. 36, 347–353 (2012).
29. M. A. Yoon, S. H. Kim, J. M. Lee, H. S. Woo, E. S. Lee, S. J. Ahn, and J. K. Han, “Adaptive statistical iterative reconstruction and Veo: Assessment of image quality and diagnostic performance in CT colonography at various radiation doses,” J. Comput. Assist. Tomogr. 36, 596–601 (2012).
30. K. Lange, “Convergence of EM image reconstruction algorithms with Gibbs smoothing,” IEEE Trans. Med. Imaging 9, 439–446 (1990).
31. T. Hebert and R. Leahy, “A generalized EM algorithm for 3-D Bayesian reconstruction from Poisson data using Gibbs priors,” IEEE Trans. Med. Imaging. 8, 194–202 (1989).
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The authors present initial progress toward a clinically compatible x-ray phase contrast CT system, using glancing-angle x-ray grating interferometry to provide high contrast soft tissue images at estimated by computer simulation dose levels comparable to conventional absorption based CT.
DPC-CT scans of a joint phantom and of soft tissues were performed in order to answer several important questions from a clinical setup point of view. A comparison between high and low fringe visibility systems is presented. The standard phase stepping method was compared with sliding window interlaced scanning. Using estimated dose values obtained with a Monte-Carlo code the authors studied the dependence of the phase image contrast on exposure time and dose.
Using a glancing angle interferometer at high x-ray energy (∼45 keV mean value) in combination with a conventional x-ray tube the authors achieved fringe visibility values of nearly 50%, never reported before. High fringe visibility is shown to be an indispensable parameter for a potential clinical scanner. Sliding window interlaced scanning proved to have higher SNRs and CNRs in a region of interest and to also be a crucial part of a low dose CT system. DPC-CT images of a soft tissue phantom at exposures in the range typical for absorption based CT of musculoskeletal extremities were obtained. Assuming a human knee as the CT target, good soft tissue phase contrast could be obtained at an estimated absorbed dose level around 8 mGy, similar to conventional CT.
DPC-CT with glancing-angle interferometers provides improved soft tissue contrast over absorption CT even at clinically compatible dose levels (estimated by a Monte-Carlo computer simulation). Further steps in image processing, data reconstruction, and spectral matching could make the technique fully clinically compatible. Nevertheless, due to its increased scan time and complexity the technique should be thought of not as replacing, but as complimentary to conventional CT, to be used in specific applications.
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