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Proceedings Paper

Histologic models for optical tomography and spectroscopy of tissues
Author(s): Rohit Bhargava; Brynmor J. Davis
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Paper Abstract

Histologic information is often the ground truth against which imaging technology performance is measured. Typically, this information is limited, however, due to the need to excise tissue, stain it and have the tissue section manually reviewed. As a consequence, histologic models of actual tissues are difficult to acquire and are generally prohibitively expensive. Models and phantoms for imaging development, hence, have to be simple and reproducible for concordance between different groups developing the same imaging methods but may not reflect tissue structure. Here, we propose a route to histologic information that does not involve the use of human review nor does it require specialized dyes or stains. We combine mid-infrared Fourier transform infrared (FT-IR) spectroscopy with imaging to record data from tissue sections. Attendant numerical algorithms are used to convert the data to histologic information. Additionally, the biochemical nature of the recorded information can be used to generate contrast for other modalities. We propose that this histologic model and spectroscopic generation of contrast can serve as standard for testing and design aid for tomography and spectroscopy of tissues. We discuss here the biochemical and statistical issues involved in creating histologic models and demonstrate the use of the approach in generating optical coherence tomography (OCT) images of prostate tissue samples.

Paper Details

Date Published: 23 February 2009
PDF: 8 pages
Proc. SPIE 7174, Optical Tomography and Spectroscopy of Tissue VIII, 71742H (23 February 2009); doi: 10.1117/12.810119
Show Author Affiliations
Rohit Bhargava, Univ. of Illinois at Urbana-Champaign (United States)
Brynmor J. Davis, Univ. of Illinois at Urbana-Champaign (United States)

Published in SPIE Proceedings Vol. 7174:
Optical Tomography and Spectroscopy of Tissue VIII
Bruce J. Tromberg; Arjun G. Yodh; Mamoru Tamura; Eva M. Sevick-Muraca; Robert R. Alfano, Editor(s)

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