Journal article
Radiomics for Detection of the EGFR Mutation in Liver Metastatic NSCLC
Academic radiology
27 Jul 2022
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
RATIONALE AND OBJECTIVESThe research aims to investigate whether MRI radiomics on hepatic metastasis from primary nonsmall cell lung cancer (NSCLC) can be used to differentiate patients with epidermal growth factor receptor (EGFR) mutations from those with EGFR wild-type, and develop a prediction model based on combination of primary tumor and the metastasis. MATERIALS AND METHODSA total of 130 patients were enrolled between Aug. 2017 and Dec. 2021, all pathologically confirmed harboring hepatic metastasis from primary NSCLC. The pyradiomics was used to extract radiomics features from intra- and peritumoral areas of both primary tumor and metastasis. The least absolute shrinkage and selection operator (LASSO) regression was applied to identify most predictive features and to develop radiomics signatures (RSs) for prediction of the EGFR mutation status. The receiver operating characteristic (ROC) curve analysis was performed to assess the prediction capability of the developed RSs. RESULTSA RS-Primary and a RS-Metastasis were derived from the primary tumor and metastasis, respectively. The RS-Combine by combination of the primary tumor and metastasis achieved the highest prediction performance in the training (AUCs, RS-Primary vs. RS-Metastasis vs. RS-Combine, 0.826 vs. 0.821 vs. 0.908) and testing (AUCs, RS-Primary vs. RS-Metastasis vs. RS-Combine, 0.760 vs. 0.791 vs. 0.884) set. The smoking status showed significant difference between EGFR mutant and wild-type groups (p < 0.05) in the training set. CONCLUSIONThe study indicates that hepatic metastasis-based radiomics can be used to detect the EGFR mutation. The developed multiorgan combined radiomics signature may be helpful to guide individual treatment strategies for patients with metastatic NSCLC.
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Details
- Title
- Radiomics for Detection of the EGFR Mutation in Liver Metastatic NSCLC
- Creators
- Shaoping HouYing FanXiaoyu WangJuan SuMeihong RenYujiao WuJie ZhouMinghui QuYahong LuoWenyan Jiang
- Publication Details
- Academic radiology
- Publisher
- Elsevier
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Neurobiology and Anatomy; College of Medicine; Drexel University
- Web of Science ID
- WOS:001001871100001
- Other Identifier
- 991020100072704721
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- Web of Science research areas
- Radiology, Nuclear Medicine & Medical Imaging