Document Type

Article

Publication Date

10-2005

Publication Title

Technology in Cancer Research & Treatment

Department

Thayer School of Engineering

Abstract

Multi-wavelength Near-Infrared (NIR) Tomography was utilized in this study to non-invasively quantify physiological parameters of breast tumors using direct spectral reconstruction. Frequency domain NIR measurements were incorporated with a new spectrally constrained direct chromophore and scattering image reconstruction algorithm, which was validated in simulations and experimental phantoms. Images of total hemoglobin, oxygen saturation, water, and scatter parameters were obtained with higher accuracy than previously reported. Using this spectral approach, in vivo NIR images are presented and interpreted through a series of case studies (n=6 subjects) having differing abnormalities. The corresponding mammograms and ultrasound images are also evaluated. Three of six cases were malignant (infiltrating ductal carcinomas) and showed higher hemoglobin (34–86% increase), a reduction in oxygen saturation, an increase in water content as well as scatter changes relative to surrounding normal tissue. Three of six cases were benign, two of which were diagnosed with fibrocystic disease and showed a dominant contrast in water, consistent with fluid filled cysts. Scatter amplitude was the main source of contrast in the volunteer with the benign condition fibrosis, which typically contains denser collagen tissue. The changes monitored correspond to physiological changes associated with angiogenesis, hypoxia and cell proliferation anticipated in cancers. These changes represent potential diagnostic indicators, which can be assessed to characterize breast tumors.

DOI

10.1177/153303460500400505

Original Citation

Srinivasan S, Pogue BW, Brooksby B, Jiang S, Dehghani H, Kogel C, Wells WA, Poplack SP, Paulsen KD. Near-infrared characterization of breast tumors in vivo using spectrally-constrained reconstruction. Technol Cancer Res Treat. 2005 Oct;4(5):513-26. doi: 10.1177/153303460500400505. PMID: 16173822.

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