IR imaging-based AI offers a label-free and automated approach to identify lung tumor types
Infrared spectroscopy can automatically distinguish between various types of lung cancer and genetic mutations, allowing quick and reliable statements to be made regarding prognosis and treatment decisions.
The prognosis and effective therapies differ based on the type of lung cancer. While it previously took several days to precisely determine the underlying mutation, a research team at the Centre for Protein Diagnostics (PRODI) at Ruhr-Universität Bochum (RUB) has been able to reliably perform this determination in just one step using a combination of quantum cascade laser-based infrared microscopy and artificial intelligence. The examined tissue does not need to be marked for this. The analysis only takes around half an hour. “This is a major step that shows that infrared imaging can be a promising methodology in future diagnostic testing and treatment prediction,” says Professor Klaus Gerwert, director of PRODI. The study is published in the American Journal of Pathology on 1 July 2021.