Accuracy and efficiency of an artificial intelligence tool when counting breast mitoses.

ABSTRACT:

Background

The mitotic count in breast carcinoma is an important prognostic marker. Unfortunately substantial inter- and intra-laboratory variation exists when pathologists manually count mitotic figures. Artificial intelligence (AI) coupled with whole slide imaging offers a potential solution to this problem. The aim of this study was to accordingly critique an AI tool developed to quantify mitotic figures in whole slide images of invasive breast ductal carcinoma.

Methods

A representative H&E slide from 320 breast invasive ductal carcinoma cases was scanned at 40x magnification. Ten expert pathologists from two academic medical centers labeled mitotic figures in whole slide images to train and validate an AI algorithm to detect and count mitoses. Thereafter, 24 readers of v

SUBMITTER: Pantanowitz L 

PROVIDER: S-EPMC7335442 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature