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Complementary X-ray tomography techniques for histology-validated 3D imaging of soft and hard tissues using plaque-containing blood vessels as examples

Abstract

A key problem in X-ray computed tomography is choosing photon energies for postmortem specimens containing both soft and hard tissues. Increasing X-ray energy reduces image artifacts from highly absorbing hard tissues including plaque, but it simultaneously decreases contrast in soft tissues including the endothelium. Therefore, identifying the lumen within plaque-containing vessels is challenging. Destructive histology, the gold standard for tissue evaluation, reaches submicron resolution in two dimensions, whereas slice thickness limits spatial resolution in the third. We present a protocol to systematically analyze heterogeneous tissues containing weakly and highly absorbing components in the original wet state, postmortem. Taking the example of atherosclerotic human coronary arteries, the successively acquired 3D data of benchtop and synchrotron radiation–based tomography are validated by histology. The entire protocol requires 20 working days, enables differentiation between plaque, muscle and fat tissues without using contrast agents and permits blood flow simulations in vessels with plaque-induced constrictions.

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Figure 1: Schematics of setups for μCT imaging.
Figure 2: XGI phase SRμCT setup at ESRF.
Figure 3: 3D representations of four characteristic plaque morphologies with different degrees of stenosis obtained from SkyScan 1174 compact micro-CT.
Figure 4: Absorption SRμCT visualization of plaque and cardiac muscle.
Figure 5: Histograms, cross-sectional tomograms, and histological slices show different tissue types.
Figure 6: The lumen mesh segmented from the absorption SRμCT data set requires further treatment before being used in flow simulations.
Figure 7
Figure 8: AWSS derived from the transient flow simulations by using the absorption SRμCT data, as prepared for Figure 7.

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References

  1. Lloyd-Jones, D. et al. Heart disease and stroke statistics—2009 update: a report from the American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Circulation 119, e21–e181 (2009).

    Google Scholar 

  2. Knight, J. et al. Choosing the optimal wall shear parameter for the prediction of plaque location, a patient-specific computational study in human right coronary arteries. Atherosclerosis 211, 445–450 (2010).

    Article  CAS  PubMed  Google Scholar 

  3. Cheng, C. et al. Large variations in absolute wall shear stress levels within one species and between species. Atherosclerosis 195, 225–235 (2007).

    Article  CAS  PubMed  Google Scholar 

  4. Holme, M.N. et al. Shear-stress sensitive lenticular vesicles for targeted drug delivery. Nat. Nanotechnol. 7, 536–543 (2012).

    Article  CAS  PubMed  Google Scholar 

  5. Korin, N. et al. Shear-activated nanotherapeutics for drug targeting to obstructed blood vessels. Science 337, 738–742 (2012).

    Article  CAS  PubMed  Google Scholar 

  6. Goderie, T.P.M. et al. Combined optical coherence tomography and intravascular ultrasound radio frequency data analysis for plaque characterization. Classification accuracy of human coronary plaques in vitro. Int. J. Cardiovasc. Imaging 26, 843–850 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Holme, M.N. et al. Morphology of atherosclerotic coronary arteries. Proc. SPIE 8506, 850609 (2012).

    Article  Google Scholar 

  8. Coombs, B.D., Rapp, J.H., Ursell, P.C., Reilly, L.M. & Saloner, D. Structure of plaque at carotid bifurcation high-resolution MRI with histological correlation. Stroke 32, 2516–2521 (2001).

    Article  CAS  PubMed  Google Scholar 

  9. Stock, S.R. Microcomputed Tomography: Methodology and Applications (CRC Press, 2008).

  10. Drews, S. et al. Comparative micro computed tomography study of a vertebral body. Proc. SPIE 7078, 70780C (2008).

    Article  Google Scholar 

  11. Germann, M. et al. Strain fields in histological slices of brain tissue determined by synchrotron radiation-based micro computed tomography. J. Neurosci. Meth. 170, 149–155 (2008).

    Article  Google Scholar 

  12. Fitzgerald, R. Phase-sensitive X-ray imaging. Phys. Today 53, 23–26 (2000).

    Article  Google Scholar 

  13. Momose, A. Recent advances in X-ray phase imaging. Jpn. J. Appl. Phys. 44, 6355–6367 (2005).

    Article  CAS  Google Scholar 

  14. Momose, A., Takeda, T., Itai, Y. & Hirano, K. Phase-contrast X-ray computed tomography for observing biological soft tissues. Nat. Med. 2, 473–475 (1996).

    Article  CAS  PubMed  Google Scholar 

  15. Beckmann, F., Bonse, U., Busch, F. & Günnewig, O. X-ray microtomography (μCT) using phase contrast for the investigation of organic matter. J. Comput. Assist. Tomo. 21, 539–553 (1997).

    Article  CAS  Google Scholar 

  16. Förster, E., Goetz, K. & Zaumseil, P. Double-crystal diffractometry for the characterization of targets for laser fusion experiments. Krist. Tech. 15, 937–945 (1980).

    Article  Google Scholar 

  17. Davis, T., Gao, D., Gureyev, T., Stevenson, A. & Wilkins, S. Phase-contrast imaging of weakly absorbing materials using hard X-rays. Nature 373, 595–598 (1995).

    Article  CAS  Google Scholar 

  18. Koch, A., Raven, C., Spanne, P. & Snigirev, A. X-ray imaging with submicrometer resolution employing transparent luminescent screens. J. Opt. Soc. Am. A 15, 1940–1951 (1998).

    Article  CAS  Google Scholar 

  19. Cloetens, P. et al. Holotomography: quantitative phase tomography with micrometer resolution using hard synchrotron radiation X-rays. Appl. Phys. Lett. 75, 2912–2914 (1999).

    Article  CAS  Google Scholar 

  20. Weitkamp, T. et al. X-ray phase imaging with a grating interferometer. Optics Exp. 13, 6296–6304 (2005).

    Article  Google Scholar 

  21. Koyama, I., Momose, A., Wu, J., Lwin, T.T. & Takeda, T. Biological imaging by X-ray phase tomography using diffraction-enhanced imaging. Jpn. J. Appl. Phys. 1 44, 8219–8221 (2005).

    Article  CAS  Google Scholar 

  22. Schulz, G. et al. High-resolution tomographic imaging of a human cerebellum: comparison of absorption and grating-based phase contrast. J. R. Soc. Interface 7, 1665–1676 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  23. Pfeiffer, F. et al. High-sensitivity phase-contrast tomography of rat brain in phosphate-buffered saline. J. Phys. Conf. Ser. 186, 012046 (2009).

    Article  CAS  Google Scholar 

  24. Pfeiffer, F. et al. High-resolution brain tumor visualization using three-dimensional X-ray phase-contrast tomography. Phys. Med. Biol. 52, 6923–6930 (2007).

    Article  CAS  PubMed  Google Scholar 

  25. Rikhtegar, F. et al. Compound ex vivo and in silico method for hemodynamic analysis of stented arteries. PLoS ONE 8, e58147 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Galonska, M. et al. Characterization of atherosclerotic plaques in human coronary arteries with 16-slice multidetector-row computed tomography by analysis of attenuation profiles. Acad. Radiol. 15, 222–230 (2008).

    Article  PubMed  Google Scholar 

  27. Zachrisson, H. et al. Soft tissue discrimination ex vivo by dual energy computed tomography. Eur. J. Radiol. 75, e124–e128 (2010).

    Article  CAS  PubMed  Google Scholar 

  28. Müller, B. et al. Grating-based tomography of human tissues. AIP Conf. Proc. 1466, 107–112 (2012).

    Article  Google Scholar 

  29. Pfeiffer, F., Weitkamp, T., Bunk, O. & David, C. Phase retrieval and differential phase-contrast imaging with low-brilliance X-ray sources. Nat. Phys. 2, 258–261 (2006).

    Article  CAS  Google Scholar 

  30. Tapfer, A. et al. Experimental results from a preclinical X-ray phase-contrast CT scanner. Proc. Natl. Acad. Sci. USA 109, 15691–15696 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Müller, B. et al. Three-dimensional evaluation of biocompatible materials by microtomography using synchrotron radiation. Proc. SPIE 4503, 178–188 (2002).

    Article  Google Scholar 

  32. Schulz, G. et al. Evaluating the microstructure of human brain tissues using synchrotron radiation–based micro-computed tomography. Proc. SPIE 7804, 78040F (2010).

    Article  Google Scholar 

  33. Schulz, G. et al. Multimodal imaging of human cerebellum—merging X-ray phase microtomography, magnetic resonance microscopy and histology. Sci. Rep. 2, 826 (2012).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  34. Schulz, G. et al. Asymmetric rotational axis reconstruction of grating-based X-ray phase-contrast tomography of the human cerebellum. Proc. SPIE 8506, 850604 (2012).

    Article  Google Scholar 

  35. Herzen, J. et al. X-ray grating interferometer for imaging at a second-generation synchrotron radiation source. Proc. SPIE 7804, 780407 (2010).

    Article  Google Scholar 

  36. Maes, F., Collignon, A., Vandermeulen, D., Marchal, G. & Suetens, P. Multi-modality image registration maximization of mutual information. IEEE 16, 187–198 (1997).

    CAS  Google Scholar 

  37. Viola, P. & Wells, W.M. III Alignment by maximization of mutual information. Int. J. Computer Vision 24, 137–154 (1997).

    Article  Google Scholar 

  38. Schulz, G. et al. Three-dimensional strain fields in human brain resulting from formalin fixation. J. Neurosci. Meth. 202, 17–27 (2011).

    Article  Google Scholar 

  39. Stalder, A. et al. Combining micro computed tomography and histology to assess the efficacy of bone augmentation materials. Int. J. Mater. Res. 10.3139/146.111050 (2014).

  40. Grabherr, S. et al. Angiofil: a novel radio-contrast agent for postmortem micro-angiography. Proc. SPIE 7078, 70781O (2008).

    Article  Google Scholar 

  41. Müller, B., Fischer, J., Dietz, U., Thurner, P.J. & Beckmann, F. Blood vessel staining in the myocardium for 3D visualization down to the smallest capillaries. Nucl. Instrum. Meth. Phys, Res, B Beam Interact, Mater, Atoms 246, 254–261 (2006).

    Article  CAS  Google Scholar 

  42. Plouraboué, F. et al. X-ray high-resolution vascular network imaging. J. Microsc. 215, 139–148 (2004).

    Article  PubMed  Google Scholar 

  43. Stephenson, R.S. et al. Contrast enhanced micro-computed tomography resolves the 3-dimensional morphology of the cardiac conduction system in mammalian hearts. PLoS ONE 7, e35299 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Pai, V.M. et al. Coronary artery wall imaging in mice using osmium tetroxide and micro-computed tomography (μ-CT). J. Anat. 220, 514–524 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Stockman, G. & Shapiro, L.G. Computer Vision 1st edn. (Prentice Hall PTR, 2001).

  46. Frangi, A.F., Niessen, W.J., Vincken, K.L. & Viergever, M.A. In Medical Image Computing and Computer-Assisted Intervention—Miccai'98, Vol. 1496 (eds. Wells, W.M., Colchester, A. & Delp, S.) 130–137 (Springer-Verlag, 1998).

  47. Pratt, W.K. Digital Image Processing: Piks Scientific Inside (John Wiley & Sons, 2007).

  48. Grodzins, L. Optimum energies for X-ray transmission tomography of small samples—applications of synchrotron radiation to computerized-tomography 1. Nucl. Instrum. Methods 206, 541–545 (1983).

    Article  CAS  Google Scholar 

  49. Thurner, P., Beckmann, F. & Müller, B. An optimization procedure for spatial and density resolution in hard X-ray micro-computed tomography. Nucl. Instrum. Meth. B 225, 599–603 (2004).

    Article  CAS  Google Scholar 

  50. Müller, B. et al. Three-dimensional registration of tomography data for quantification in biomaterials science. Int. J. Mater. Res. 103, 242–249 (2012).

    Article  CAS  Google Scholar 

  51. Weitkamp, T. et al. Recent developments in X-ray Talbot interferometry at ESRF-ID19. Proc. SPIE 7804, 780406 (2010).

    Article  Google Scholar 

  52. Beckmann, F., Herzen, J., Haibel, A., Müller, B. & Schreyer, A. High density resolution in synchrotron-radiation-based attenuation-contrast microtomography. Proc. SPIE 7078, 70781D (2008).

    Article  Google Scholar 

  53. Huesman, R.H. RECLBL Library Users Manual: Donner Algorithms for Reconstruction Tomography (Lawrence Berkeley Laboratory, University of California, 1977).

  54. Pfeiffer, F., Bunk, O., Kottler, C. & David, C. Tomographic reconstruction of three-dimensional objects from hard X-ray differential phase-contrast projection images. Nucl. Instrum. Meth. A 580, 925–928 (2007).

    Article  CAS  Google Scholar 

  55. Weitkamp, T., David, C., Kottler, C., Bunk, O. & Pfeiffer, F. Tomography with grating interferometers at low-brilliance sources. Proc. SPIE 6318, 63180S (2006).

    Article  Google Scholar 

  56. Preibisch, S., Saalfeld, S. & Tomancak, P. Globally optimal stitching of tiled 3D microscopic image acquisitions. Bioinformatics 25, 1463–1465 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Walter, T. et al. Visualization of image data from cells to organisms. Nat. Methods 7, 479–479 (2010).

    Article  CAS  Google Scholar 

  58. Andronache, A., von Siebenthal, M., Székely, G. & Cattin, P. Non-rigid registration of multi-modal images using both mutual information and cross-correlation. Med. Image Anal. 12, 3–15 (2008).

    Article  CAS  PubMed  Google Scholar 

  59. Fierz, F.C. et al. The morphology of anisotropic 3D-printed hydroxyapatite scaffolds. Biomaterials 29, 3799–3806 (2008).

    Article  CAS  PubMed  Google Scholar 

  60. Kroon, D.-J. & Slump, C.H. MRI modality transformation in demon registration. IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI '09 (June 28–July 1, 2009, Boston, Massachusetts, USA) 963–966 (2009).

  61. Olgac, U., Poulikakos, D., Saur, S.C., Alkadhi, H. & Kurtcuoglu, V. Patient-specific three-dimensional simulation of LDL accumulation in a human left coronary artery in its healthy and atherosclerotic states. Am. J. Phys. 296, H1969–H1982 (2009).

    CAS  Google Scholar 

  62. Moyle, K.R., Antiga, L. & Steinman, D.A. Inlet conditions for image-based CFD models of the carotid bifurcation: is it reasonable to assume fully developed flow? J. Biomech. Eng. 128, 371–379 (2006).

    Article  PubMed  Google Scholar 

  63. Rikhtegar, F. et al. Choosing the optimal wall shear parameter for the prediction of plaque location—a patient-specific computational study in human left coronary arteries. Atherosclerosis 221, 432–437 (2012).

    Article  CAS  PubMed  Google Scholar 

  64. van der Giessen, A.G. et al. The influence of boundary conditions on wall shear stress distribution in patients specific coronary trees. J. Biomech. 44, 1089–1095 (2011).

    Article  PubMed  Google Scholar 

  65. La Disa, J.F. et al. Alterations in regional vascular geometry produced by theoretical stent implantation influence distributions of wall shear stress: Analysis of a curved coronary artery using 3D computational fluid dynamics modeling. Biomed. Eng. Online 5, 40 (2006).

    Article  Google Scholar 

  66. Donath, T. et al. Toward clinical X-ray phase-contrast CT demonstration of enhanced soft-tissue contrast in human specimen. Invest. Radiol. 45, 445–452 (2010).

    Article  PubMed  Google Scholar 

  67. Hetterich, H. et al. Grating-based X-ray phase-contrast tomography of atherosclerotic plaque at high photon energies. Z. Med. Phys. 23, 194–203 (2013).

    Article  PubMed  Google Scholar 

  68. Als-Nielsen, J. & McMorrow, D. Elements of Modern X-ray Physics (John Wiley & Sons, 2011).

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Acknowledgements

This work was primarily funded by the Swiss National Science Foundation (SNSF) in the National Research Program (NRP) 62 'Smart Materials' framework within the project number 406240_126090 'NO-Stress'. Synchrotron beamtime from the ESRF (MD-498 and MI-983) and the HASYLAB at DESY (I-20100181 EC) is gratefully appreciated. We thank K. Püschel of the Institute of Forensic Medicine, University Medical Center, Hamburg-Eppendorf, who provided the human arteries. T.W. acknowledges support from the French research networks (RTRA) ′Digiteo′ and ′Triangle de la Physique′ (grants 2009-034T and 2009-79D), and V.K. acknowledges support from SNSF through the Swiss National Centre of Competence in Research (NCCR) Kidney.CH. T.W. and B.M. acknowledge support from the Agence Nationale de la Recherche (France) via the EQUIPEX grant number ANR-11-EQPX-0031 (project NanoimagesX). M.N.H. and B.M. thank S. Hieber for training in image segmentation and for her contributions to the related part of the manuscript introduction. We further acknowledge the Karlsruhe Nano Micro Facility (KNMF) of the Karlsruhe Institute of Technology (KIT), Eggenstein-Leopoldshafen, Germany, and J. Mohr and his collaborators at the Institute for Microstructure Technology (IMT) of KIT for providing the analyzer grating.

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M.N.H. and B.M. wrote the manuscript with sections provided by T.W. and V.K. G.S., I.Z., M.N.H. and T.W. set up and performed the phase-contrast SRμCT measurements. F.B., G.S., H.D. and M.N.H. set up and performed the absorption-contrast SRμCT measurements. G.S., H.D. and M.N.H. performed the benchtop μCT measurements. F.B., M.N.H., G.S. and H.D. performed data processing, reconstruction and analysis, excluding the flow simulations (Steps 21–27), which were performed by F.R. and V.K. Histology slides were prepared by J.A.L. T.S. and J.A.L. provided a clinical perspective for data analysis. T.W., J.A.L., V.K. and I.Z. provided technical and conceptual advice. B.M. and T.S. designed the study. All authors contributed to editing the manuscript, including tables and figures.

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Correspondence to Bert Müller.

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Holme, M., Schulz, G., Deyhle, H. et al. Complementary X-ray tomography techniques for histology-validated 3D imaging of soft and hard tissues using plaque-containing blood vessels as examples. Nat Protoc 9, 1401–1415 (2014). https://doi.org/10.1038/nprot.2014.091

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