Image-based assessment of extracellular mucin in colorectal cancer

Dr. Inti Zlobec, professor of digital pathology at the Institute of Pathology in the University of Bern, discusses her team’s recent publication in Modern Pathology on the role of image analysis in assessing area of extracellular mucin and predicting consensus molecular subtypes (CMS) in colorectal carcinoma. The utilized deep learning algorithm had an excellent agreement with pathologists’ estimates of mucin areas. Coupled with MSI, mucinous area estimates may predict CMS classification using only histopathology. This highlights the great potential of Image based classifier of molecular subtypes of colon cancer. Study by Nguyen, HG., Lundström, O., Blank, A. et al. Image-based assessment of extracellular mucin-to-tumor area predicts consensus molecular subtypes (CMS) in colorectal cancer. Mod Pathol 35, 240–248 (2022)