The predictive value of [18F]FDG PET/CT radiomics combined with clinical features for EGFR mutation status in different clinical staging of lung adenocarcinoma

The predictive value of [18F]FDG PET/CT radiomics combined with clinical features for EGFR mutation status in different clinical staging of lung adenocarcinoma

Abstract Background This study aims to construct radiomics models based on [18F]FDG PET/CT using multiple machine learning methods to predict the EGFR mutation status of lung adenocarcinoma and evaluate whether incorporating clinical parameters can improve the performance of radiomics models. Method...

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Bibliographic Details
Main Authors: Jianxiong Gao, Rong Niu, Yunmei Shi, Xiaoliang Shao, Zhenxing Jiang, Xinyu Ge, Yuetao Wang, Xiaonan Shao
Format: Article
Language:English
Published: SpringerOpen 2023-04-01
Series:EJNMMI Research
Subjects:
lung adenocarcinoma
[18F]FDG PET/CT
Radiomics
Epidermal growth factor receptor
Prediction
Online Access:https://doi.org/10.1186/s13550-023-00977-4

Internet

https://doi.org/10.1186/s13550-023-00977-4

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