Computational Analysis of Pathological Image Enables Interpretable Prediction for Microsatellite Instability.

ABSTRACT:

Background

Microsatellite instability (MSI) is associated with several tumor types and has become increasingly vital in guiding patient treatment decisions; however, reasonably distinguishing MSI from its counterpart is challenging in clinical practice.

Methods

In this study, interpretable pathological image analysis strategies are established to help medical experts to identify MSI. The strategies only require ubiquitous hematoxylin and eosin-stained whole-slide images and perform well in the three cohorts collected from The Cancer Genome Atlas. Equipped with machine learning and image processing technique, intelligent models are established to diagnose MSI based on pathological images, providing the rationale of the decision in both image level and pathological feature lev

SUBMITTER: Zhu J 

PROVIDER: S-EPMC9355712 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature