Researchers have added infrared (IR) capability to a standard optical microscope, with the goal of digital biopsy for cancer diagnosis. Pairing IR measurements with high-resolution optical images and machine learning algorithms, they created digital biopsies that closely correlated with traditional pathology techniques and also outperformed state-of-the-art infrared microscopes.
The advantage is that no stains are required, and both the organization of cells and their chemistry can be measured. Measuring the chemistry of tumor cells and their microenvironment can lead to better cancer diagnoses and better understanding of the disease.
The researchers plan to continue refining the computational tools used to analyze the hybrid images. They are working to optimize machine-learning programs that can measure multiple IR wavelengths, creating images that readily distinguish between multiple cell types, and integrate that data with the detailed optical images to precisely map cancer within a sample. They also plan to explore further applications for hybrid microscope imaging, such as forensics, polymer science, and other biomedical applications.