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Journal of Biomedical Optics • Open Access

Diagnostic imaging of breast cancer using fluorescence-enhanced optical tomography: phantom studies

Paper Abstract

Molecular targeting with exogenous near-infrared excitable fluorescent agents using time-dependent imaging techniques may enable diagnostic imaging of breast cancer and prognostic imaging of sentinel lymph nodes within the breast. However, prior to the administration of unproven contrast agents, phantom studies on clinically relevant volumes are essential to assess the benefits of fluorescence-enhanced optical imaging in humans. Diagnostic 3-D fluorescence-enhanced optical tomography is demonstrated using 0.5 to 1 cm3 single and multiple targets differentiated from their surroundings by indocyanine green (micromolar) in a breast-shaped phantom (10-cm diameter). Fluorescence measurements of referenced ac intensity and phase shift were acquired in response to point illumination measurement geometry using a homodyned intensified charge-coupled device system modulated at 100 MHz. Bayesian reconstructions show artifact-free 3-D images (3857 unknowns) from 3-D boundary surface measurements (126 to 439). In a reflectance geometry appropriate for prognostic imaging of lymph node involvement, fluorescence measurements were likewise acquired from the surface of a semi-infinite phantom (8×8×8 cm3) in response to area illumination (12 cm2) by excitation light. Tomographic 3-D reconstructions (24,123 unknowns) were recovered from 2-D boundary surface measurements (3194) using the modified truncated Newton's method. These studies represent the first 3-D tomographic images from physiologically relevant geometries for breast imaging.

Paper Details

Date Published: 1 May 2004
PDF: 9 pages
J. Biomed. Opt. 9(3) doi: 10.1117/1.1691027
Published in: Journal of Biomedical Optics Volume 9, Issue 3
Show Author Affiliations
Anuradha Godavarty, Florida International Univ. (United States)
Alan B. Thompson, Texas A&M Univ. (United States)
Ranadhir Roy, Texas A&M Univ. (United States)
Mikhail Gurfinkel, Texas A&M Univ. (United States)
Margaret J Eppstein, University of Vermont (United States)
Chaoyang Zhang, Univ. of Vermont (United States)
Eva Marie Sevick-Muraca, Texas A&M Univ. (United States)

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