Fig. 1.

Landscape of AI applications in colorectal cancer pathology. AI applications can be useful for several scenarios in CRC pathology, namely, in rendering the diagnosis and assessing morphological features such as the assessment of TSR, TILs, and invasion front biomarkers like budding or DR. Moreover, AI tools can directly infer (some) molecular features, such as mutational, MMR/MSI status, and CMS subtyping, from H&E slides, without (or with less) further molecular wet laboratory testing needed. Additionally, AI tools can help assess clinical meaningful outcomes directly from histologic slides, such as survival and recurrence, therapy response, and metastatic potential, for example, lymph node metastasis. For all these different applications, immediate clinical use cases are conceivable. AI, artificial intelligence; TILs, tumor-infiltrating lymphocytes; DR, desmoplastic reaction; MMR, mismatch repair (p, proficient; d, deficient); MSI, microsatellite instable; MSS, microsatellite stable; CMS, consensus molecular subtype; H&E, hematoxylin and eosin. Histologic H&E slides were obtained from https://portal.gdc.cancer.gov/ (TCGA-COAD, TCGA-READ) [70–72]. Created with BioRender.com.