Clinical pathological diagnosis and prognosis for cancer is often confounded by spatial tissue heterogeneity. This study investigates the utility of entropy as a robust quantitative metric of spatial disorder within Fourier Transform Infrared (FTIR) chemical images of breast cancer tissue. The use of entropy is grounded in its capacity to encapsulate the complexities of pixel-wise spectral intensity distributions, thus providing a detailed assessment of the spatial variations in biochemistry within tissue samples.
Here we explore the use of Shannon’s entropy as a single image-based metric of spectral biochemical heterogeneity within FTIR chemical images of breast cancer tissue. This metric was then analyzed statistically with respect to hormone receptor status. Our results suggest that while entropy effectively captures the heterogeneity of tissue samples, its role as a standalone predictor for diagnostic subtyping may be limited without considering additional variables or interaction effects. This work emphasizes the need for a multifaceted approach in leveraging entropy with chemical imaging for diagnostic subtyping in cancer.
Spectral imaging in the long-wave infrared regime has great potential for medical diagnostics. Breast cancer is the most common cancer amongst females in the US. The pathological features and the occurrence of the microcalcifications are still poorly understood. However, two types of microcalcifications have been identified as unique biomarkers: type I consisting of calcium oxalate (benign lesions) and type II composed of hydroxyapatite (benign or invasive lesions). In this study, we propose a new approach based on vibrational spectroscopy that is non-destructive, label-free and chemically specific for breast cancer detection. Long-wave infrared spectroscopy combining quantum cascade lasers (QCL) and upconversion detection, offer to improve signal-to-noise ratios compared to standard long-wave infrared spectroscopy. We demonstrated long-wave identification of synthetic samples of carbonated hydroxyapatite and of microcalcification in breast cancer tissue using upconversion detection. Absorbance spectra and upconverted images of in situ breast cancer biopsy are compared with that of Fourier-transform infrared (FTIR) spectroscopy.
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