Strategies for Absolute Calibration of Near Infrared Tomographic Tissue Imaging

  • Troy O. McBride
  • Brian W. Pogue
  • Ulf L. Österberg
  • Keith D. Paulsen
Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 530)

Abstract

Quantitative near infrared (NIR) imaging of tissue requires the use of a diffusion model-based reconstruction algorithm, which solves for the absorption and scattering coefficients of a tissue volume by matching transmission measurements of light to the predictive diffusion equation solution. Calibration problems as well as other practical considerations arise for an imaging system when using a model-based method for a real system. For example, systematic noise in the data acquisition hardware and source/detector fibers must be removed to prevent spurious results in the reconstructed image. Practical considerations for a NIR diffuse tomographic imaging system include: (1) calibration with a homogeneous phantom, (2) use of a homogeneous fitting algorithm to arrive at an initial optical property estimate for image reconstruction of a heterogeneous medium, and (3) correction for fluctuations in source strength and initial phase offset during data acquisition. These practical considerations, which rely on an accurate homogeneous fitting algorithm are described. They have allowed demonstration of a prototype imaging system that has the ability to quantitatively reconstruct heterogeneous images of hemoglobin concentrations within a highly scattering medium with no a priori information.

Key words

blood calibration hemoglobin photon migration reconstruction tomography 

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References

  1. 1.
    Jiang H, Paulsen KD, Österberg UL, Pogue BW, Patterson MS. Optical image reconstruction using frequency-domain data: simulations and experiments. J Opt Soc Am A 1996;13:253–266.CrossRefGoogle Scholar
  2. 2.
    Arridge SR, Schweiger M. Image reconstruction in optical tomography. Phil Trans R. Soc Lond B 1997;352:717–726.CrossRefGoogle Scholar
  3. 3.
    Profio AF, Navarro GA. Scientific basis of breast diaphanography. Med Phys 1989; 16:60–65.PubMedCrossRefGoogle Scholar
  4. 4.
    Vaupel P, Kallinowski F, Okunieff P. Blood flow, oxygen and nutrient supply, and metabolic microenvironment of human tumors: a review. Cancer Research 1989;49: 6449–6465.PubMedGoogle Scholar
  5. 5.
    McBride TO, Pogue BW, Gerety ED, Poplack SB, Osterberg UL, Paulsen KD. Spectroscopic diffuse optical tomography for quantitatively assessing hemoglobin concentration and oxygenation in breast tissue. Appl Opt 1999;38:5480–5490.PubMedCrossRefGoogle Scholar
  6. 6.
    Pogue BW, Testorf M, McBride T, Österberg U, Paulsen K. Instrumentation and design of a frequency-domain diffuse optical tomography imager for breast cancer detection. Optics Express 1997;1:391–403.PubMedCrossRefGoogle Scholar
  7. 7.
    Pogue BW, McBride TO, Österberg UL, Paulsen KD. Spatially variant regularization improves diffuse optical tomography. Appl Opt 1999;38:2950–2961.PubMedCrossRefGoogle Scholar
  8. 8.
    Wray S, Cope M, Delpy DT, Wyatt JS, Reynolds EOR. Characterization of the near infrared absorption spectra of cytochrome aa3 and haemoglobin for the non-invasive monitoring of cerebral oxygenation. Biochim Biophys Acta 1988;933:184–192.PubMedCrossRefGoogle Scholar
  9. 9.
    Quaresima V, Matcher SJ, Ferrari M. Identification and quantification of intrinsic optical contrast for near-infrared mammography. Photochem Photobiol 1998;67:4–14.PubMedCrossRefGoogle Scholar
  10. 10.
    Hale GM, Querry MR, Optical constants of water in the 200-nm to 200- pm wavelength region. Appl Opt 1973;12:555–563.PubMedCrossRefGoogle Scholar
  11. 11.
    Pogue BW, Patterson MS, Frequency-domain optical absorption spectroscopy of finite element tissue volumes using diffusion theory. Phys Med Bio 1994;39:1157–1180CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2003

Authors and Affiliations

  • Troy O. McBride
    • 1
  • Brian W. Pogue
    • 1
  • Ulf L. Österberg
    • 1
  • Keith D. Paulsen
    • 1
  1. 1.Thayer School of Engineering, 8000 Cummings HallDartmouth College HanoverHanoverUK

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