Long wavelength identification of microcalcifications in breast cancer tissue using a quantum cascade laser and upconversion detection

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.