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Article

Deep learning radiopathomics predicts targeted therapy sensitivity in EGFR-mutant lung adenocarcinoma.

Journal of translational medicine - 29 Apr 2025

Yang Taotao, Wang Xianqi, Jin Yuan, Yao Xiaohong, Sun Zhiyuan, Chen Pinzhen, Zhou Suyi, Zhu Wentao, Chen Wei

Abstract excerpt

BACKGROUND: Ttyrosine kinase inhibitors (TKIs) represent the standard first-line treatment for patients with epidermal growth factor receptor (EGFR)-mutant lung adenocarcinoma. However, not all patients with EGFR mutations respond to TKIs. This study aims to develop a deep learning radiological-pathological-clinical (DLRPC) model that integrates computed tomography (CT) images, hematoxylin and eosin (H&E)-stained...

Read the complete abstract on PubMed

Topics

Humans
Adenocarcinoma of Lung
ErbB Receptors
Deep Learning
Mutation
Male

Methodology Data sources Editorial policy Privacy Delete account & data About Contact Helena Bioinformatics

Female

Lung Neoplasms

Middle Aged

Tomography, X-Ray Computed

Aged

Molecular Targeted Therapy

Protein Kinase Inhibitors

Retrospective Studies

Source

Open in PubMed Open full text

Identifiers

PMID: 40301933
DOI: 10.1186/s12967-025-06480-9
PMCID: PMC12039126

Genes

EGFR

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 23 Oct 2026.

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