Perineural Invasion Detection in Multiple Organ Cancer Based on Deep Convolutional Neural Network

TL;DR

This paper introduces a CNN-based algorithm for automated detection of perineural invasion in colon, prostate, and pancreas cancers, aiming to improve diagnostic efficiency and accuracy in pathology.

Contribution

The study develops a novel deep learning method specifically designed for detecting PNI across multiple cancer types, addressing labor-intensive manual assessments.

Findings

Effective detection of PNI in multiple cancers

Potential to reduce pathologist workload

Improved diagnostic consistency

Abstract

Perineural invasion (PNI) by malignant tumor cells has been reported as an independent indicator of poor prognosis in various cancers. Assessment of PNI in small nerves on glass slides is a labor-intensive task. In this study, we propose an algorithm to detect the perineural invasions in colon, prostate, and pancreas cancers based on a convolutional neural network (CNN).