Annals of Biomedical Engineering

, Volume 40, Issue 5, pp 1160–1169 | Cite as

Altered Lung Motion is a Sensitive Indicator of Regional Lung Disease

  • Andreas Fouras
  • Beth J. Allison
  • Marcus J. Kitchen
  • Stephen Dubsky
  • Jayne Nguyen
  • Kerry Hourigan
  • Karen K. W. Siu
  • Rob A. Lewis
  • Megan J. Wallace
  • Stuart B. Hooper
Article

Abstract

Since lung diseases adversely affect airflow during breathing, they must also alter normal lung motion, which can be exploited to detect these diseases. However, standard imaging techniques such as CT and MRI imaging during breath-holds provide little or no information on lung motion and cannot detect diseases that cause subtle changes in lung structure. Phase-contrast X-ray imaging provides images of high contrast and spatial resolution with temporal resolutions that allow multiple images to be acquired throughout the respiratory cycle. Using X-ray phase-contrast imaging, coupled with velocimetry, we have measured lung tissue movement and determined velocity fields that define speed and direction of regional lung motion throughout a breath in normal Balb/c nude male mice and mice exposed to bleomycin. Regional maps of lung tissue motion reveal both the heterogeneity of normal lung motion, as well as abnormal motion induced by bleomycin treatment. Analysed histologically, bleomycin treatment caused pathological changes in lung structure that were heterogenous, occupying less than 12% of the lung at 6 days after treatment. Moreover, plethysmography failed to detect significant changes in compliance at either 36 h or 6 days after treatment. Detailed analysis of the vector fields demonstrated major differences (p < 0.001) in regional lung motion between control and bleomycin-treated mice at both 36 h and 6 days after treatment. The results of this study demonstrate that X-ray phase-contrast imaging, coupled with velocimetry, can detect early stage, subtle and non-uniform lung disease.

Keywords

Velocimetry Functional imaging Lung disease Lung function 

Supplementary material

10439_2011_493_MOESM1_ESM.mov (9.1 mb)
Supplementary material 1 (MOV 9358 kb)

References

  1. 1.
    Adam, J. F., et al. Quantitative functional imaging and kinetic studies with high-Z contrast agents using synchrotron radiation computed tomography. Clin. Exp. Pharmacol. Physiol. 36(1):95–106, 2009.PubMedCrossRefGoogle Scholar
  2. 2.
    Adamson, I. Y. R., and D. H. Bowden. Pathogenesis of bleomycin-induced pulmonary fibrosis in mice. Am. J. Pathol. 77(2):185–199, 1974.PubMedGoogle Scholar
  3. 3.
    Adrian, R. J. Twenty years of particle image velocimetry. Exp. Fluids 39(2):159–169, 2005.CrossRefGoogle Scholar
  4. 4.
    Albert, S. P., et al. The role of time and pressure on alveolar recruitment. J. Appl. Physiol. 106(3):757–765, 2009.PubMedCrossRefGoogle Scholar
  5. 5.
    Allen, G. B., et al. Pulmonary impedance and alveolar instability during injurious ventilation in rats. J. Appl. Physiol. 99(2):723–730, 2005.PubMedCrossRefGoogle Scholar
  6. 6.
    Black, C. L. B., et al. Relationship between dynamic respiratory mechanics and disease heterogeneity in sheep lavage injury. Crit. Care Med. 35(3):870–878, 2007.CrossRefGoogle Scholar
  7. 7.
    Boulet, L. P., M. Belanger, and G. Carrier. Airway responsiveness and bronchial-wall thickness in asthma with or without fixed air-flow obstruction. Am. J. Respir. Crit. Care Med. 152(3):865–871, 1995.PubMedGoogle Scholar
  8. 8.
    Castillo, R., et al. Ventilation from four-dimensional computed tomography: density versus Jacobian methods. Phys. Med. Biol. 55(16):4661–4685, 2010.PubMedCrossRefGoogle Scholar
  9. 9.
    Christensen, G. E., et al. Tracking lung tissue motion and expansion/compression with inverse consistent image registration and spirometry. Med. Phys. 34(6):2155–2163, 2007.PubMedCrossRefGoogle Scholar
  10. 10.
    Dubsky, S., et al. Computed tomographic X-ray velocimetry. Appl. Phys. Lett. 96(2):023702, 2010.CrossRefGoogle Scholar
  11. 11.
    Fouras, A., D. Lo Jacono, and K. Hourigan. Target-free Stereo PIV: a novel technique with inherent error estimation and improved accuracy. Exp. Fluids 44(2):317–329, 2008.CrossRefGoogle Scholar
  12. 12.
    Fouras, A., and J. Soria. Accuracy of out-of-plane vorticity measurements derived from in-plane velocity field data. Exp. Fluids 25(5–6):409–430, 1998.CrossRefGoogle Scholar
  13. 13.
    Fouras, A., et al. Three-dimensional synchrotron X-ray particle image velocimetry. J. Appl. Phys. 102(6):064916, 2007.CrossRefGoogle Scholar
  14. 14.
    Guerrero, T., et al. Quantification of regional ventilation from treatment planning CT. Int. J. Radiat. Oncol. Biol. Phys. 62(3):630–634, 2005.PubMedCrossRefGoogle Scholar
  15. 15.
    Guerrero, T., et al. Dynamic ventilation imaging from four-dimensional computed tomography. Phys. Med. Biol. 51(4):777–791, 2006.PubMedCrossRefGoogle Scholar
  16. 16.
    Hodgson, M. J., D. K. Parkinson, and M. Karpf. Chest X-rays in hypersensitivity pneumonitis—a metaanalysis of secular trend. Am. J. Ind. Med. 16(1):45–53, 1989.PubMedCrossRefGoogle Scholar
  17. 17.
    Hoffman, E. A., et al. Estimation of regional pleural surface expansile forces in intact dogs. J. Appl. Physiol. 55(3):935–948, 1983.PubMedGoogle Scholar
  18. 18.
    Hogg, J. C. Pathophysiology of airflow limitation in chronic obstructive pulmonary disease. Lancet 364(9435):709–721, 2004.PubMedCrossRefGoogle Scholar
  19. 19.
    Hooper, S. B., et al. Imaging lung aeration and lung liquid clearance at birth. FASEB J. 21(12):3329–3337, 2007.PubMedCrossRefGoogle Scholar
  20. 20.
    Hooper, S. B., et al. Imaging lung aeration and lung liquid clearance at birth using phase contrast X-ray imaging. Clin. Exp. Pharmacol. Physiol. 36(1):117–125, 2009.PubMedCrossRefGoogle Scholar
  21. 21.
    Hove, J. R., et al. Intracardiac fluid forces are an essential epigenetic factor for embryonic cardiogenesis. Nature 421(6919):172–177, 2003.PubMedCrossRefGoogle Scholar
  22. 22.
    Hsia, C. C. W., et al. An official research policy statement of the American Thoracic Society/European Respiratory Society: standards for quantitative assessment of lung structure. Am. J. Respir. Crit. Care Med. 181(4):394–418, 2010.PubMedCrossRefGoogle Scholar
  23. 23.
    Im, K. S., et al. Particle tracking velocimetry using fast X-ray phase-contrast imaging. Appl. Phys. Lett. 90(9):3, 2007.CrossRefGoogle Scholar
  24. 24.
    Irvine, S. C., et al. Phase retrieval for improved three-dimensional velocimetry of dynamic X-ray blood speckle. Appl. Phys. Lett. 93(15):153901, 2008.CrossRefGoogle Scholar
  25. 25.
    Jamison, R. A., et al. X-ray velocimetry and haemodynamic forces within a stenosed femoral model at physiological flow rates. Ann. Biomed. Eng. 39(6):1643–1653, 2011.PubMedCrossRefGoogle Scholar
  26. 26.
    Kitchen, M. J., et al. On the origin of speckle in X-ray Phase Contrast images of lung tissue. Phys. Med. Biol. 49(18):4335–4348, 2004.PubMedCrossRefGoogle Scholar
  27. 27.
    Kitchen, M. J., et al. Phase contrast X-ray imaging of mice and rabbit lungs: a comparative study. Br. J. Radiol. 78(935):1018–1027, 2005.PubMedCrossRefGoogle Scholar
  28. 28.
    Kitchen, M. J., et al. Dynamic measures of regional lung air volume using Phase Contrast X-ray Imaging. Phys. Med. Biol. 53(21):6065–6077, 2008.PubMedCrossRefGoogle Scholar
  29. 29.
    Kitchen, M. J., et al. A new design for high stability pressure-controlled ventilation for small animal lung imaging. J. Instrum. 5:T02002, 2010.CrossRefGoogle Scholar
  30. 30.
    Lai-Fook, S. J., and R. E. Hyatt. Effects of age on elastic moduli of human lungs. J. Appl. Physiol. 89(1):163–168, 2000.PubMedGoogle Scholar
  31. 31.
    Lazenby, A. J., et al. Remodeling of the lung in bleomycin-induced pulmonary fibrosis in the rat—an immunohistochemical study of laminin, type-IV collagen, and fibronectin. Am. Rev. Respir. Dis. 142(1):206–214, 1990.PubMedGoogle Scholar
  32. 32.
    Lee, S. J., and G. B. Kim. X-ray particle image velocimetry for measuring quantitative flow information inside opaque objects. J. Appl. Phys. 94(5):3620–3623, 2003.CrossRefGoogle Scholar
  33. 33.
    Lee, S. J., and G. B. Kim. Synchrotron microimaging technique for measuring the velocity fields of real blood flows. J. Appl. Phys. 97(6):6, 2005.CrossRefGoogle Scholar
  34. 34.
    Lewis, R. A. Medical phase contrast x-ray imaging: current status and future prospects. Phys. Med. Biol. 49(16):3573–3583, 2004.PubMedCrossRefGoogle Scholar
  35. 35.
    Lewis, R. A., et al. Dynamic imaging of the lungs using X-ray phase contrast. Phys. Med. Biol. 50(21):5031–5040, 2005.PubMedCrossRefGoogle Scholar
  36. 36.
    Maltais, F., et al. Comparison of static and dynamic measurements of intrinsic peep in mechanically ventilated patients. Am. J. Respir. Crit. Care Med. 150(5):1318–1324, 1994.PubMedGoogle Scholar
  37. 37.
    Manali, E., et al. Static and dynamic mechanics of the murine lung after intratracheal bleomycin. BMC Pulm. Med. 11(1):33, 2011.PubMedCrossRefGoogle Scholar
  38. 38.
    Nesbitt, W. S., et al. A shear gradient-dependent platelet aggregation mechanism drives thrombus formation. Nat. Med. 15(6):665–673, 2009.PubMedCrossRefGoogle Scholar
  39. 39.
    Onodera, M., et al. Determination of ventilatory volume in mice by whole body plethysmography. Jpn. J. Physiol. 47(4):317–326, 1997.PubMedCrossRefGoogle Scholar
  40. 40.
    Pan, T., et al. 4D-CT imaging of a volume influenced by respiratory motion on multi-slice CT. Med. Phys. 31(2):333–340, 2004.PubMedCrossRefGoogle Scholar
  41. 41.
    Poelma, C., et al. In vivo blood flow and wall shear stress measurements in the vitelline network. Exp. Fluids 45(4):703–713, 2008.CrossRefGoogle Scholar
  42. 42.
    Reinhardt, J. M., et al. Registration-based estimates of local lung tissue expansion compared to xenon CT measures of specific ventilation. Med. Image Anal. 12(6):752–763, 2008.PubMedCrossRefGoogle Scholar
  43. 43.
    Robertson, H. T., et al. High-resolution maps of regional ventilation utilizing inhaled fluorescent microspheres. J. Appl. Physiol. 82(3):943–953, 1997.PubMedGoogle Scholar
  44. 44.
    Schrier, D. J., S. H. Phan, and B. M. McGarry. The effects of the nude (nu/nu) mutation on bleomycin-induced pulmonary fibrosis—a biochemical evaluation. Am. Rev. Respir. Dis. 127(5):614–617, 1983.PubMedGoogle Scholar
  45. 45.
    Sethi, S., and T. F. Murphy. Current concepts: infection in the pathogenesis and course of chronic obstructive pulmonary disease. N. Engl. J. Med. 359(22):2355–2365, 2008.PubMedCrossRefGoogle Scholar
  46. 46.
    Siew, M. L., et al. Inspiration regulates the rate and temporal pattern of lung liquid clearance and lung aeration at birth. J. Appl. Physiol. 106(6):1888–1895, 2009.PubMedCrossRefGoogle Scholar
  47. 47.
    Snigirev, A., et al. On the possibilities of X-ray phase contrast microimaging by coherent high-energy synchrotron radiation. Rev. Sci. Instrum. 66(12):5486–5492, 1995.CrossRefGoogle Scholar
  48. 48.
    Sundaram, T. A., and J. C. Gee. Towards a model of lung biomechanics: pulmonary kinematics via registration of serial lung images. Med. Image Anal. 9(6):524–537, 2005.PubMedCrossRefGoogle Scholar
  49. 49.
    Sznitman, J., et al. Visualization of respiratory flows from 3D reconstructed alveolar airspaces using X-ray tomographic microscopy. J. Vis. 13(4):337–345, 2010.CrossRefGoogle Scholar
  50. 50.
    Tustison, N. J., et al. Pulmonary kinematics from tagged hyperpolarized helium-3 MRI. J. Magn. Reson. Imaging 31(5):1236–1241, 2010.PubMedCrossRefGoogle Scholar
  51. 51.
    Tustison, N. J., et al. Pulmonary kinematics from image data: a review. Acad. Radiol. 18(4):402–417, 2011.PubMedCrossRefGoogle Scholar
  52. 52.
    Udalov, S., et al. Effects of phosphodiesterase 4 inhibition on bleomycin-induced pulmonary fibrosis in mice. BMC Pulm. Med. 10:26, 2010.PubMedCrossRefGoogle Scholar
  53. 53.
    Westneat, M. W., J. J. Socha, and W.-K. Lee. Advances in biological structure, function, and physiology using synchrotron X-ray imaging. Annu. Rev. Physiol. 70:119–142, 2008.PubMedCrossRefGoogle Scholar
  54. 54.
    Westneat, M. W., et al. Tracheal respiration in insects visualized with synchrotron X-ray imaging. Science 299(5606):558–560, 2003.PubMedCrossRefGoogle Scholar
  55. 55.
    Wilkins, S. W., et al. Phase-contrast imaging using polychromatic hard X-rays. Nature 384(6607):335–338, 1996.CrossRefGoogle Scholar
  56. 56.
    Yagi, N., et al. Refraction-enhanced X-ray imaging of mouse lung using synchrotron radiation source. Med. Phys. 26(10):2190–2193, 1999.PubMedCrossRefGoogle Scholar
  57. 57.
    Yin, Y. B., et al. Simulation of pulmonary air flow with a subject-specific boundary condition. J. Biomech. 43(11):2159–2163, 2010.PubMedCrossRefGoogle Scholar

Copyright information

© Biomedical Engineering Society 2011

Authors and Affiliations

  • Andreas Fouras
    • 1
  • Beth J. Allison
    • 2
  • Marcus J. Kitchen
    • 3
  • Stephen Dubsky
    • 1
    • 4
  • Jayne Nguyen
    • 1
    • 4
  • Kerry Hourigan
    • 1
    • 4
  • Karen K. W. Siu
    • 3
  • Rob A. Lewis
    • 3
  • Megan J. Wallace
    • 2
  • Stuart B. Hooper
    • 2
  1. 1.Division of Biological EngineeringMonash UniversityClaytonAustralia
  2. 2.Ritchie Centre, Monash Institute of Medical ResearchMonash UniversityClaytonAustralia
  3. 3.School of PhysicsMonash UniversityClaytonAustralia
  4. 4.Department of Mechanical and Aerospace EngineeringMonash UniversityClaytonAustralia

Personalised recommendations