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Article

Ensemble learning strategy-based 18 F-FDG PET/CT metabolic habitats radiomics for predicting EGFR mutation and prognosis in LA-NSCLC: a multi-center study.

BMC medical imaging - 19 Jan 2026

Ji Yu, Wang Jiaqi, Wang Yaru, Zhang Juntao, Dai Zhengjun, Cui Yong, Zheng Jingsong, Yu Dexin

Abstract excerpt

BACKGROUND: Epidermal growth factor receptor (EGFR) status critically guides tyrosine kinase inhibitor therapy in locally advanced non-small cell lung cancer (LA-NSCLC). This study aimed to develop and validate an 18 F-FDG PET/CT-based stacking ensemble model leveraging metabolic habitat radiomics to noninvasively predict EGFR mutations of LA-NSCLC and stratify prognosis in the patients. METHODS: This multicenter...

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Identifiers

PMID: 41555270
DOI: 10.1186/s12880-026-02163-z
PMCID: PMC12895722

Genes

EGFR

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 5 Sept 2026.

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