Deep learning model shows pathologist-level detection of sentinel node metastasis of melanoma and intra-nodal nevi on whole slide images.

ABSTRACT:

Introduction

Nodal metastasis (NM) in sentinel node biopsies (SNB) is crucial for melanoma staging. However, an intra-nodal nevus (INN) may often be misclassified as NM, leading to potential misdiagnosis and incorrect staging. There is high discordance among pathologists in assessing SNB positivity, which may lead to false staging. Digital whole slide imaging offers the potential for implementing artificial intelligence (AI) in digital pathology. In this study, we assessed the capability of AI to detect NM and INN in SNBs.

Methods

A total of 485 hematoxylin and eosin whole slide images (WSIs), including NM and INN from 196 SNBs, were collected and divided into training (279 WSIs), validation (89 WSIs), and test sets (117 WSIs). A deep learning model was trained with 5,956 ma

SUBMITTER: Siarov J 

PROVIDER: S-EPMC11374739 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature