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Journal of the Optical Society of America A

Journal of the Optical Society of America A


  • Vol. 18, Iss. 12 — Dec. 1, 2001
  • pp: 3018–3036

Optical tomographic imaging of dynamic features of dense-scattering media

Randall L. Barbour, Harry L. Graber, Yaling Pei, Sheng Zhong, and Christoph H. Schmitz  »View Author Affiliations

JOSA A, Vol. 18, Issue 12, pp. 3018-3036 (2001)

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Methods used in optical tomography have thus far proven to produce images of complex target media (e.g., tissue) having, at best, relatively modest spatial resolution. This presents a challenge in differentiating artifact from true features. Further complicating such efforts is the expectation that the optical properties of tissue for any individual are largely unknown and are likely to be quite variable due to the occurrence of natural vascular rhythms whose amplitudes are sensitive to a host of autonomic stimuli that are easily induced. We recognize, however, that rather than frustrating efforts to validate the accuracy of image features, the time-varying properties of the vasculature can be exploited to aid in such efforts, owing to the known structure-dependent frequency response of the vasculature and to the fact that hemoglobin is a principal contrast feature of the vasculature at near-infrared wavelengths. To accomplish this, it is necessary to generate a time series of image data. In this report we have tested the hypothesis that through analysis of time-series data, independent contrast features can be derived that serve to validate, at least qualitatively, the accuracy of imaging data, in effect establishing a self-referencing scheme. A significant finding is the observation that analysis of such data can produce high-contrast images that reveal features that are mainly obscured in individual image frames or in time-averaged image data. Given the central role of hemoglobin in tissue function, this finding suggests that a wealth of new features associated with vascular dynamics can be identified from the analysis of time-series image data.

© 2001 Optical Society of America

OCIS Codes
(100.2960) Image processing : Image analysis
(100.2980) Image processing : Image enhancement
(100.6950) Image processing : Tomographic image processing
(170.3880) Medical optics and biotechnology : Medical and biological imaging
(170.4580) Medical optics and biotechnology : Optical diagnostics for medicine
(170.5380) Medical optics and biotechnology : Physiology

Original Manuscript: October 19, 2000
Revised Manuscript: March 16, 2001
Manuscript Accepted: January 10, 2001
Published: December 1, 2001

Randall L. Barbour, Harry L. Graber, Yaling Pei, Sheng Zhong, and Christoph H. Schmitz, "Optical tomographic imaging of dynamic features of dense-scattering media," J. Opt. Soc. Am. A 18, 3018-3036 (2001)

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  1. B. Chance, R. R. Alfano, B. J. Tromberg, M. Tamura, E. M. Sevick-Muraca, eds., Optical Tomography and Spectroscopy of Tissue IV, Proc. SPIE4250 (2001).
  2. H. Liu, D. A. Boas, Y. Zhang, A. G. Yodh, B. Chance, “Determination of optical properties and blood oxygenation in tissue using continuous NIR light,” Phys. Med. Biol. 40, 1983–1993 (1995). [CrossRef] [PubMed]
  3. H. Liu, B. Chance, A. H. Hielscher, S. L. Jacques, F. K. Tittel, “Influence of blood vessels on the measurement of hemoglobin oxygenation as determined by time-resolved reflectance spectroscopy,” Med. Phys. 22, 1209–1217 (1995). [CrossRef] [PubMed]
  4. J. W. Covell, “Cardiovascular control and integrated responses,” in (Best and Taylor’s) Physiological Basis of Medical Practice, 11th ed., J. B. West, ed. (Williams and Wilkins, Baltimore, Md., 1985), Chap. 16.
  5. C. E. Elwell, R. Springett, E. Hillman, D. T. Delpy, “Oscillations in cerebral haemodynamics,” in Oxygen Transport to Tissue XXI, Vol. 471 of Advances in Experimental Medicine and Biology, A. Eke, D. T. Delpy, eds. (Kluwer Academic/Plenum, New York, 1999), pp. 57–65.
  6. J. E. W. Mayhew, S. Askew, Y. Zheng, J. Porrill, G. W. M. Westby, P. Redgrave, D. M. Rector, R. M. Harper, “Cerebral vasomotion: a 0.1-Hz oscillation in reflected light imaging of neural activity,” Neuroimage 4, 183–193 (1996). [CrossRef] [PubMed]
  7. M. A. Franceschini, V. Toronov, M. E. Filiaci, E. Gratton, S. Fantini, “On-line optical imaging of the human brain with 160-ms temporal resolution,” Opt. Express 6, 49–57 (2000). http://www.opticsexpress.org . [CrossRef] [PubMed]
  8. A. Zourabian, A. Siegel, B. Chance, N. Ramanujan, M. Rode, D. A. Boas, “Trans-abdominal monitoring of fetal arterial blood oxygenation using pulse oximetry,” J. Biomed. Opt. 5, 391–405 (2000). [CrossRef] [PubMed]
  9. A. Villringer, B. Chance, “Non-invasive optical spectroscopy and imaging of human brain function,” Trends Neurosci. 20, 435–442 (1997). [CrossRef] [PubMed]
  10. E. M. C. Hillman, J. C. Hebden, F. E. W. Schmidt, S. R. Arridge, M. E. Fry, M. Schweiger, D. T. Delpy, “Initial clinical testing of the UCL 32 channel time-resolved instrument for optical tomography,” in Biomedical Topical Meetings, OSA Technical Digest (Optical Society of America, Washington D.C., 2000), pp. 100–102.
  11. T. O. McBride, B. W. Pogue, E. D. Gerety, S. B. Poplack, U. L. Österberg, K. D. Paulsen, “Spectroscopic diffuse optical tomography for the quantitative assessment of hemoglobin concentration and oxygen saturation in breast tissue,” Appl. Opt. 38, 5480–5490 (1999). [CrossRef]
  12. C. H. Schmitz, H. L. Graber, H. Luo, I. Arif, J. Hira, Y. Pei, A. Bluestone, S. Zhong, R. Andronica, I. Soller, N. Ramirez, S.-L. S. Barbour, R. L. Barbour, “Instrumentation and calibration protocol for imaging dynamic features in dense-scattering media by optical tomography,” Appl. Opt. 39, 6466–6486 (2000). [CrossRef]
  13. H. L. Graber, C. H. Schmitz, Y. Pei, S. Zhong, S.-L. S. Barbour, S. Blattman, T. Panetta, R. L. Barbour, “Spatiotemporal imaging of vascular reactivity,” in Physiology and Function from Multidimensional Imaging, A. V. Clough, C.-T. Chen, eds., Proc. SPIE3978, 32–43 (2000).
  14. H. L. Graber, S. Zheng, Y. Pei, C. H. Schmitz, I. Arif, J. Hira, R. L. Barbour, “Dynamic imaging of muscle activity by optical tomography,” in Biomedical Topical Meetings, OSA Technical Digest (Optical Society of America, Washington, D.C., 2000), pp. 407–408.
  15. R. L. Barbour, H. L. Graber, S. Zheng, Y. Pei, J. Hira, I. Arif, “Optical imaging of the response of vascular dynamics to a cold shock,” in Biomedical Topical Meetings, OSA Technical Digest (Optical Society of America, Washington, D.C., 2000), pp. 430–432.
  16. S. Blattman, H. L. Graber, S. Zheng, Y. Pei, J. Hira, I. Arif, R. L. Barbour, “Imaging of differential reactivity of the vascular tree in the human forearm by optical tomography,” in Biomedical Topical Meetings, OSA Technical (Optical Society of America, Washington D.C., 2000), pp. 458–460.
  17. D. W. Fawcett, Bloom and Fawcett’s A Textbook of Histology, 12th ed. (Chapman & Hall, New York, 1994).
  18. J. Folkman, “Angiogenesis and breast cancer,” J. Clin. Oncol. 12, 441–443 (1994). [PubMed]
  19. C. W. Song, A. Lokshina, J. G. Rhee, M. Patten, S. H. Levitt, “Implication of blood flow in hyperthermic treatment of tumors,” IEEE Trans. Biomed. Eng. 31, 9–16 (1984). [CrossRef] [PubMed]
  20. T. L. Troy, D. L. Page, E. M. Sevick-Muraca, “Optical properties of normal and diseased breast tissues: prognosis for optical mammography,” J. Biomed. Opt. 1, 343–355 (1996). [CrossRef]
  21. A. H. Hielscher, R. E. Alcouffe, R. L. Barbour, “Comparison of finite-difference transport and diffusion calculations for photon migration in homogeneous and heterogeneous tissues,” Phys. Med. Biol. 43, 1285–1302 (1998). [CrossRef] [PubMed]
  22. O. W. van Assendelft, Spectrophotometry of Haemoglobin Derivatives, (Thomas, Springfield, Ill., 1970).
  23. H. J. van Staveren, C. J. M. Moes, J. van Marle, S. A. Prahl, M. J. C. van Gemert, “Light scattering in Intralipid-10% in the wavelength range of 400-1100 nm,” Appl. Opt. 30, 4507–4514 (1991). [CrossRef] [PubMed]
  24. I. Driver, J. W. Feather, P. R. King, J. B. Dawson, “The optical properties of aqueous suspensions of Intralipid, a fat emulsion,” Phys. Med. Biol. 34, 1927–1930 (1989). [CrossRef]
  25. S. T. Flock, S. L. Jacques, B. C. Wilson, W. M. Star, M. J. C. van Gemert, “Optical properties of Intraplipid: a phantom medium for light propagation studies,” Lasers Surg. Med. 12, 510–519 (1992). [CrossRef]
  26. G. M. Hale, M. R. Querry, “Optical constants of water in the 200-nm to 200-µm wavelength region,” Appl. Opt. 12, 555–563 (1973). [CrossRef] [PubMed]
  27. R. L. Barbour, R. Andronica, Q. Sha, H. L. Graber, I. Soller, “Development and evaluation of the IRIS-OPTIscanner, a general-purpose optical tomographic imaging system,” in Advances in Optical Imaging and Photon MigrationJ. G. Fujimoto, M. S. Patterson, eds., Vol. 21 of OSA Trends in Optics and Photonics Series (Optical Society of America, Washington, D.C., 1998), pp. 251–255.
  28. Y. Pei, H. L. Graber, R. L. Barbour, “Influence of systematic errors in reference states on image quality and on stability of derived information for DC optical imaging,” Appl. Opt. 40, 5755–5769 (2001). [CrossRef]
  29. H. L. Graber, Y. Pei, R. L. Barbour, “Imaging of spatiotemporal coincident states by dynamic optical tomography,” in Ref. 1, pp. 153–163.
  30. R. L. Barbour, H. L. Graber, Y. Pei, C. H. Schmitz, “Imaging of vascular chaos,” in Ref. 1, pp. 577–590.
  31. Using MATLAB Version 5, (The Mathworks, Inc., Natick, Mass., 1998) Chap. 5; http://www.mathworks.com/access/helpdesk/help/techdoc/ref/griddata.shtml .
  32. Ref. 31; http://www.mathworks.com/access/helpdesk/help/techdoc/ref/delaunay.shtml .
  33. J. S. Bendat, A. G. Piersol, Engineering Applications of Correlation and Spectral Analysis, 2nd ed. (Wiley, New York, 1993).
  34. G. M. Jenkins, D. G. Watts, Spectral Analysis and its Applications (Holden-Day, Oakland, Calif., 1968).
  35. Signal Processing Toolbox User’s Guide (Version 4) (The Mathworks, Inc., Natick, Mass., 1998) Chap. 6; http://www.mathworks.com/access/helpdesk/help/toolbox/signal/fft.shtml .
  36. Ref. 35; http://www.mathworks.com/access/helpdesk/help/toolbox/signal/xcorr.shtml .
  37. As the temporal variations of the target media used in the studies considered here were perfectly periodic, the length and number of records can be set to any desired value. The effects of record number and length (and also other considerations such as filtering and windowing) lie outside the scope of the present report.
  38. Ref. 35; http://www.mathworks.com/access/helpdesk/help/toolbox/signal/csd.shtml .
  39. Ref. 35; http://www.mathworks.com/access/helpdesk/help/toolbox/signal/csd.shtml .
  40. The last interpretation given is particularly intriguing for us, as it immediately brings to mind an analogy between this general concept of signal coherence and the particular physical meaning of “coherence” that applies to light. It suggests that the “coherence radius” and “coherence time” that could be defined for each pixel in an image time series may be parameters worth considering.
  41. M. Schweiger, S. R. Arridge, D. T. Delpy, “Application of the finite-element method for the forward and inverse models in optical tomography,” J. Math. Imag. Vision 3, 263–283 (1993). [CrossRef]
  42. H. Jiang, K. D. Paulsen, U. L. Österberg, M. S. Patterson, “Frequency-domain optical image reconstruction in turbid media: an experimental study of single-target detectability,” Appl. Opt. 36, 52–63 (1997). [CrossRef] [PubMed]
  43. V. Ntziachristos, B. Chance, A. G. Yodh, “Differential diffuse optical tomography,” Opt. Express 5, 230–242 (1999), http://www.opticsexpress.org . [CrossRef] [PubMed]
  44. P. Vaupel, “Vascularization, blood flow, oxygenation, tissue pH, and bioenergetic status of human breast cancer,” in Oxygen Transport to Tissue XVIII (Advances in Experimental Medicine and Biology)E. M. Nemoto, J. C. LaManna, eds. (Plenum, New York, 1997), Vol. 411, pp. 243–254.
  45. S. Sunberg, M. Castrén, “Drug- and temperature-induced changes in peripheral circulation measured by laser-Doppler flowmetry and digital-pulse plethysmography,” Scand. J. Clin. Lab. Invest. 46, 359–365 (1986). [CrossRef]
  46. C. Holvombe, N. Pugh, K. Lyons, A. Douglas-Jones, R. E. Mansel, K. Horgan, “Blood flow in breast cancer and fibroadenoma estimated by colour Doppler ultrasonography,” Br. J. Surg. 82, 787–788 (1995). [CrossRef]
  47. A. T. Johnson, C. G. Lausted, J. D. Bronzino, “Respiratory system,” in The Biomedical Engineering Handbook, 2nd ed., J. D. Bronzino, ed. (CRC Press, Boca Raton, Fla., 2000), Chap. 7.
  48. M. H. Sherebrin, R. Z. Sherebrin, “Frequency analysis of the peripheral pulse wave detected in the finger with a photoplethysmograph,” IEEE Trans. Biomed. Eng. 37, 313–317 (1990). [CrossRef] [PubMed]
  49. G. Drzewiecki, “Noninvasive arterial blood pressure and mechanics,” in The Biomedical Engineering Handbook, 2nd ed., J. D. Bronzino, ed. (CRC Press, Boca Raton, Fla., 2000), Chap. 71.
  50. S. Blattman, H. L. Graber, S. Zheng, Y. Pei, J. Hira, I. Arif, R. L. Barbour, “Imaging of tissue reperfusion by dynamic optical tomography,” in Biomedical Topical Meetings, OSA Technical Digest (Optical Society of America, Washington D.C., 2000), pp. 409–410.
  51. B. Endrich, P. Vaupel, “The role of the microcirculation in the treatment of malignant tumors: facts and fiction,” in Blood Perfusion and Microenvironments of Human Tumors: Implications for Clinical Radiooncology, M. Molls, P. Vaupel, eds. (Springer–Verlag, Berlin, 1998), pp. 19–39.
  52. C. Sohn, F. Beldermann, H. Frey, S. Reinhart, J. Sohn, G. Bastert, “Durchblutungsdiagnostik von Mammatumoren unter Blutdruckerhöhung: neue Möglichkeiten in der Dignitätsdiagnostik,” Radiologe 37, 643–650 (1997). [CrossRef] [PubMed]
  53. C. Franssen, H. Wollershein, A. de Haan, T. Thien, “The influence of different beta-blocking drugs on the peripheral circulation in Raynaud’s phenomenon and in hypertension,” J. Clin. Pharm. 32, 652–659 (1992). [CrossRef]
  54. D. T. Kaplan, A. L. Goldberger, “Chaos in cardiology,” J. Cardiovasc. Electrophys. 2, 342–354 (1991). [CrossRef]
  55. T. M. Griffith, “Chaos and fractals in vascular biology,” Vasc. Med. Rev. 5, 161–182 (1994).
  56. J. Bélair, L. Glass, U. an der Heiden, J. Milton, “Dynamical disease: identification, temporal aspects and treatment strategies of human illness,” Chaos 5, 1–7 (1995). [CrossRef] [PubMed]
  57. J. N. Weiss, A. Garfinkel, M. L. Spano, W. L. Ditto, “Chaos and chaos control in biology,” J. Clin. Invest. 93, 1355–1360 (1994). [CrossRef] [PubMed]
  58. J. K. Kantors, M. V. Højgaard, E. Agner, N.-H. Holstein-Rathlou, “Short- and long-term variations in non-linear dynamics of heart rate variability,” Cardiovasc. Res. 31, 400–409 (1996). [CrossRef]
  59. P. Mansier, J. Clairambault, N. Charlotte, C. Médigue, C. Vermeiren, G. LePape, F. Carré, A. Gounaropoulou, B. Swynghedauw, “Linear and non-linear analyses of heart rate variability: a minireview,” Cardiovasc. Res. 31, 371–379 (1996). [CrossRef] [PubMed]
  60. S. F. Glotzbach, R. L. Ariagno, R. M. Harper, “Sleep and the sudden infant death syndrome,” in Principles and Practice of Sleep Medicine in the Child, R. Ferber, M. H. Kryger, eds. (Saunders, Philadelphia, Pa., 1995), pp. 231–244.
  61. J. Theiler, “On the evidence for low-dimensional chaos in an epileptic electroencephalogram,” Phys. Lett. A 196, 334–341 (1995). [CrossRef]
  62. C. G. Ellis, S. M. Wrigley, A. C. Groom, “Heterogeneity of red blood cell perfusion in capillary networks supplied by a single arteriole in resting skeletal muscle,” Circ. Res. 75, 357–368 (1994). [CrossRef] [PubMed]
  63. T. F. Budinger, H. F. VanBrocklin, “Positron-emission tomography (PET),” in The Biomedical Engineering Handbook, 2nd ed., J. D. Bronzino, ed. (CRC Press, Boca Raton, Fla., 2000), Chap. 67.
  64. B. Y. Croft, B. M. W. Tsui, “Nuclear medicine,” in The Biomedical Engineering Handbook, 2nd ed., J. D. Bronzino, ed. (CRC Press, Boca Raton, Fla., 2000), Chap. 64.
  65. EEG and MEG imaging techniques have temporal resolutions sufficiently fine to respond to variations resulting from the respiratory and cardiac cycles, but these are limited to functional studies of the brain; even here, their purpose is to assess neuronal, not circulatory, function.
  66. R. R. Alfano, S. G. Demos, P. Galland, S. K. Gayen, Y. Guo, P. P. Ho, X. Liang, F. Liu, L. Wang, Q. Z. Wang, W. B. Wang, “Time-resolved and nonlinear optical imaging for medical applications,” in Advances in Optical Biopsy and Optical Mammography, Vol. 838 of the Annals of the New York Academy of Sciences (New York Academy of Sciences, New York, 1998), pp. 14–27.
  67. K. Wells, J. C. Hebden, F. E. W. Schmidt, D. T. Delpy, “The UCL multichannel time-resolved system for optical tomography,” in Optical Tomography and Spectroscopy of Tissue: Theory, Instrumentation, Model, and Human Studies II, B. Chance, R. R. Alfano, eds., Proc. SPIE2979, 599–607 (1997). [CrossRef]
  68. S. R. Arridge, W. R. B. Lionheart, “Nonuniqueness in diffusion-based optical tomography,” Opt. Lett. 23, 882–884 (1998). [CrossRef]
  69. I. T. Joliffe, B. J. T. Morgan, “Principal component analysis and exploratory factor analysis,” Stat. Meth. Med. Res. 1, 69–95 (1992). [CrossRef]
  70. J. Mayhew, D. Hu, Y. Zheng, S. Askew, Y. Hou, J. Berwick, P. J. Coffey, N. Brown, “An evaluation of linear model analysis techniques for processing images of microcirculation activity,” Neuroimage 7, 49–71 (1998). [CrossRef] [PubMed]
  71. L. McMackin, R. J. Hugo, R. E. Pierson, C. R. Truman, “High speed optical tomography system for imaging dynamic transparent media,” Opt. Express 1, 302–311 (1997). http://www.opticsexpress.org . [CrossRef] [PubMed]
  72. While addition of a spectral windowing operation to the time-series analysis would likely yield better frequency resolution than that seen in this figure, none was actually used while the results presented in this report were being generated.

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