Modeling fourier transform infrared spectroscopic imaging of Prostate and Breast Cancer tissue specimens

Fourier transform infrared (FT-IR) spectroscopic imaging is an emerging technique that provides both spatially and chemically resolved information. The rich chemical content of data may be utilized for computer-aided determinations of structure and pathologic state (cancer diagnosis) in histological tissue sections for Prostate and Breast Cancer. Recent results show that tissue type (histological) classification can be performed to an accuracy of 94% to 99% and cancer diagnosis can be performed with an accuracy of about 80% on a microscopic (≈ 6μm) length scale. One of the primary causes of reduction in classification accuracy is the systematic errors caused by distortions in the infrared spectra of tissues resulting from the nature of data acquisition. Here, we present a rigorous model for the interaction of infrared light with the tissue sample using coupled wave analysis and characterize the nature of these distortions. In particular, we demonstrate the spectral effects of changing the thickness of homogeneous samples and scattering from boundaries of two regions in spatially heterogeneous samples. Modeling these optical distortions provides a fundamental understanding of systematic errors in FT-IR measurements and is important to improving accuracy of automated cancer tissue histopathology.