Copyright ©The Author(s) 2020.
Artif Intell Gastroenterol. Sep 28, 2020; 1(3): 51-59
Published online Sep 28, 2020. doi: 10.35712/aig.v1.i3.51
Table 1 Summary of main applications and findings of artificial intelligence in colorectal cancer digital pathology
Cancer cell shape and organization to predict N+Digital assessment of cancer cells using Feret’s diameters allows to predict lymph node metastasis in pT1 colon cancer[11]
Assessment of anti-cancer immune responseSimultaneous assessment of all immune cell subpopulations and demonstration that eosinophils, other than T cells, may play a role in CRC immune response[12,14,15,17]
Identification of Microsatellite instable tumorsRapid and large size screening of histopathologic features in conventional HE-stained slides increasing the probability of being a MSI-H tumor, without the need of specific immunohistochemical or molecular testing[18]
Quantification of stroma within the tumorAlgorithms for tissue –specific recognition, even when sparse within the tumor mass have been development. These algorithms have allowed the validation of “deep stroma score” which is significantly associated with survival in CRC[20]
Biology-agnostic prediction of survivalDevelopment of tissue “digital” profiles without specific underlying biologic background or significance that are predictive of distinct survivals, bad vs good outcome[21]