Quantum Cascade Laser-Based Infrared Microscopy for Label-Free and Automated Cancer Classification in Tissue Sections

Abstract

A feasibility study using a quantum cascade laser-based infrared microscope for the rapid and label-free classification of colorectal cancer tissues is presented. Infrared imaging is a reliable, robust, automated, and operator-independent tissue classification method that has been used for differential classification of tissue thin sections identifying tumorous regions. However, long acquisition time by the so far used FT-IR-based microscopes hampered the clinical translation of this technique. Here, the used quantum cascade laser-based microscope provides now infrared images for precise tissue classification within few minutes. We analyzed 110 patients with UICC-Stage II and III colorectal cancer, showing 96% sensitivity and 100% specificity of this label-free method as compared to histopathology, the gold standard in routine clinical diagnostics. The main hurdle for the clinical translation of IR-Imaging is overcome now by the short acquisition time for high quality diagnostic images, which is in the same time range as frozen sections by pathologists.

Video-rate, mid-infrared hyperspectral upconversion imaging

“…Moreover, for HSI, large data storage and complex postprocessing software is currently needed to transform raw data into useful information [14]. Recent developments in mid-IR hyperspectral microscopy include tunable quantum cascade laser (QCL) illumination combined with either raster scanning [15] or microbolometer array detectors [16]. These systems have shown their potential to outperform FTIR systems for special applications; however, they still rely on direct detection of the mid-IR signal.…”

“…We report on the use of mid-IR upconversion imaging using a silicon-based camera, demonstrating unsupervised computerassisted classification of biopsy sections in the 3-4 μm wavelength range. It is generally recognized that the 5-12 μm range is preferred in terms of chemical specificity [15,16]; however, the 3-4 μm wavelength range has also shown relevant chemical features [26] and has the additional advantage of being compatible with existing glass substrates (microscope slides) used presently in clinics [27]. Using the k-means algorithm, an unsupervised spectral clustering method based on spectral similarity of different regions of the sample, each pixel acquired from the tissue sample were segmented into groups, comparable to the histotypes identified by an expert gastrointestinal histopathologist.…”

Upconversion raster scanning microscope for long-wavelength infrared imaging of breast cancer microcalcifications

“…However, FTIR is currently too slow for real-time imaging for the delivery of rapid hyperspectral pathology. In recent years, discrete frequency IR microscopes with tunable mid-IR laser sources, such as quantum cascade lasers, optical parametric oscillators or filtered supercontinuum light sources, enabling label-free classification of cancerous tissue have been demonstrated [15][16][17][18][19][20]. By tuning to a molecular absorbance wavelength of interest, real-time molecular imaging can be utilized for immediate unstained tissue analysis.…”

Label-free, automated classification of microsatellite status in colorectal cancer by infrared imaging

“…1A. The first and second RF were presented previously with 96% sensitivity and 100% specificity 44 . In the present feasibility study we wanted to demonstrate a subsequent RF that was able to differentiate MSI-H and MSS based on the spectra recognized as tumor cells by the previously presented cancer classifier.…”