Deep Learning Enabled Scoring of Pancreatic Neuroendocrine Tumors Based on Cancer Infiltration Patterns.

ABSTRACT: Pancreatic neuroendocrine tumors (PanNETs) are a heterogeneous group of neoplasms that include tumors with different histomorphologic characteristics that can be correlated to sub-categories with different prognoses. In addition to the WHO grading scheme based on tumor proliferative activity, a new parameter based on the scoring of infiltration patterns at the interface of tumor and non-neoplastic parenchyma (tumor-NNP interface) has recently been proposed for PanNET categorization. Despite the known correlations, these categorizations can still be problematic due to the need for human judgment, which may involve intra- and inter-observer variability. Although there is a great need for automated systems working on quantitative metrics to reduce observer variability, there are no such syste

SUBMITTER: Koc S 

PROVIDER: S-EPMC11757657 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature