AI-based digital histopathology for perihilar cholangiocarcinoma: A step, not a jump.

ABSTRACT:

Introduction

Perihilar cholangiocarcinoma (PHCC) is a rare malignancy with limited survival prediction accuracy. Artificial intelligence (AI) and digital pathology advancements have shown promise in predicting outcomes in cancer. We aimed to improve prognosis prediction for PHCC by combining AI-based histopathological slide analysis with clinical factors.

Methods

We retrospectively analyzed 317 surgically treated PHCC patients (January 2009-December 2018) at the University Hospital of Essen. Clinical data, surgical details, pathology, and outcomes were collected. Convolutional neural networks (CNN) analyzed whole-slide images. Survival models incorporated clinical and histological features.

Results

Among 142 eligible patients, independent survival predictors were tumo

SUBMITTER: Hoyer DP 

PROVIDER: S-EPMC10698537 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature