ArticleThe oncologist2019
Computed Tomography-Based Radiomics Signature: A Potential Indicator of Epidermal Growth Factor Receptor Mutation in Pulmonary Adenocarcinoma Appearing as a Subsolid Nodule.
Article in The oncologist, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
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Who cites it
39 citing papers in PubMed.
- A CT-based radiomics model to predict subsequent brain metastasis in patients with ALK-rearranged non-small cell lung cancer undergoing crizotinib treatment.Thoracic cancer · 2022Trial
- The Predictive Value ofCurrent medical imaging · 2026Article
- Predicting the prognosis of patients with lung adenocarcinoma treated with third-generation EGFR-TKI alone using nomograms based on CT radiomic and clinicopathological factors.Translational lung cancer research · 2025Article
- Nomogram to predict the EGFR mutation status in stage III-IV solid lung adenocarcinoma patients.BMC medical imaging · 2025Article
- The value of dual-energy spectral CT in differentiating the pathological grades of T1-size lung adenocarcinoma.Journal of thoracic disease · 2025Article
- Prediction of epidermal growth factor receptor (Quantitative imaging in medicine and surgery · 2024Article
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- The predictive value of [EJNMMI research · 2023Article
- Feature selection methods and predictive models in CT lung cancer radiomics.Journal of applied clinical medical physics · 2023Review
- The application of radiomics in predicting gene mutations in cancer.European radiology · 2022Review
- Review
- Radiomics combined with clinical characteristics predicted the progression-free survival time in first-line targeted therapy for advanced non-small cell lung cancer with EGFR mutation.BMC research notes · 2022Article
- Radiomics/Radiogenomics in Lung Cancer: Basic Principles and Initial Clinical Results.Cancers · 2022Review
- Three-Dimensional Convolutional Neural Network-Based Prediction of Epidermal Growth Factor Receptor Expression Status in Patients With Non-Small Cell Lung Cancer.Frontiers in oncology · 2022Article
- Clinical and CT patterns to predict EGFR mutation in patients with non-small cell lung cancer: A systematic literature review and meta-analysis.European journal of radiology open · 2022Article
- The value of dual-energy spectral CT in differentiating solitary pulmonary tuberculosis and solitary lung adenocarcinoma.Frontiers in oncology · 2022Article
- AI in spotting high-risk characteristics of medical imaging and molecular pathology.Precision clinical medicine · 2021Review
- Molecular typing of lung adenocarcinoma with computed tomography and CT image-based radiomics: a narrative review of research progress and prospects.Translational cancer research · 2021Review
- Combination of computed tomography imaging-based radiomics and clinicopathological characteristics for predicting the clinical benefits of immune checkpoint inhibitors in lung cancer.Respiratory research · 2021Article
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLung adenocarcinoma (LADC) with epidermal growth factor receptor (EGFR) mutation is considered a subgroup of lung cancer sensitive to EGFR-targeted tyrosine kinase inhibitors. We aimed to develop and validate a computed tomography (CT)-based radiomics signature for prediction of EGFR mutation status in LADC appearing as a subsolid nodule. MATERIALS AND
methodsA total of 467 eligible patients were divided into training and validation cohorts (
resultsIn this study, 64.2% (300/467) of the patients showed EGFR mutations. L858R mutation of exon 21 was the most common mutation type (185/301). We identified a CT-based radiomics signature that successfully discriminated between EGFR positive and EGFR negative in the training cohort (AUC = 0.831) and the validation cohort (AUC = 0.789). The radiomics signature combined with the clinical factors model was not superior to the simple radiomics signature in the two cohorts (
conclusionAs a noninvasive method, the CT-based radiomics signature can be used to predict the EGFR mutation status of LADC appearing as a subsolid nodule. IMPLICATIONS FOR PRACTICE: Lung adenocarcinoma (LADC) with epidermal growth factor receptor (EGFR) mutation is considered a subgroup of lung cancer that is sensitive to EGFR-targeted tyrosine kinase inhibitors. However, some patients with inoperable subsolid LADC are unable to undergo tissue sampling by biopsy for molecular analysis in clinical practice. A computed tomography-based radiomics signature may serve as a noninvasive biomarker to predict the EGFR mutation status of subsolid LADCs when mutational profiling is not available or possible.
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