ArticleInternational journal of general medicine2022
Prediction of VEGF and EGFR Expression in Peripheral Lung Cancer Based on the Radiomics Model of Spectral CT Enhanced Images.
Article in International journal of general medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed, 10 citations in OpenAlex.
- Diagnostic Performance and Imaging Features of Dual-Phase Contrast-Enhanced CT in Peripheral Lung Cancer: A Prospective Study With Pathological Correlation.Medical science monitor : international medical journal of experimental and clinical research · 2026Article
- Spectral CT imaging in colorectal cancer: current applications, limitations, and future perspectives.Insights into imaging · 2026Review
- AI-based neoadjuvant immunotherapy response prediction across pan-cancer: a comprehensive review.Cancer cell international · 2025Review
- Computed tomography based radiomics signature for predicting the expression of vascular endothelial growth factor in pediatric patients with nephroblastoma.Scientific reports · 2025Article
- Review of the application of dual-energy CT combined with radiomics in the diagnosis and analysis of lung cancer.Journal of applied clinical medical physics · 2025Review
- Spectral dual-layer detector CT-based radiomics-deep learning for predicting pathological aggressiveness of stage I lung adenocarcinoma: discrimination of precursor glandular lesions and invasive adenocarcinomas.Translational lung cancer research · 2025Article
- Dual-Phase Enhanced CT-Derived Radiomics Nomogram for Progression-Free Survival Prediction in Stage IV Lung Adenocarcinoma.Cancer medicine · 2024Article
- Magnetic resonance imaging-based radiomics in predicting the expression of Ki-67, p53, and epidermal growth factor receptor in rectal cancer.Journal of gastrointestinal oncology · 2024Article
- Machine learning based ultrasomics noninvasive predicting EGFR expression status in hepatocellular carcinoma patients.Frontiers in medicine · 2024Article
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Energy spectrum CT is an effective method to evaluate the biological behavior of lung cancer. Radiomics is a non-invasive technology to obtain histological information related to lung cancer. Purpose: To investigate the value of the radiomics models on the bases of enhanced spectral CT images of peripheral lung cancer to predict the expression of the vascular endothelial growth factor (VEGF) and epidermal growth factor receptor (EGFR). Material and Methods: This study retrospectively analyzed 73 patients with peripheral lung cancer confirmed by postoperative pathology. All patients underwent dual-phase enhanced spectral CT scans before surgery. Regions of interest (ROI) were delineated in the arterial phase and venous phase. Key radiomics features were extracted and models were established to predict the expression of VEGF and EGFR, respectively. All models were established based on the expression levels of VEGF and EGFR in tissues detected by immunohistochemical staining as reference standards. Receiver operating characteristic (ROC) curve and calibration curve were used to evaluate the predictive performance of each model, and decision curve analysis (DCA) was used to evaluate the clinical utility of the models. Results: In predicting the expression level of VEGF, the combined (COMB) model composed of one spectral feature and two radiomics features achieved the best performance with area under ROC (AUC) 0.867 (95% CI: 0.767-0.966), accuracy of 0.812, sensitivity of 0.879, and specificity of 0.667. According to the expression level of EGFR, three importance radiomics features were retained in the arterial and venous phases to establish the multiphase phase model which has the best performance with AUC of 0.950 (95% confidence interval: 0.89-1.00), accuracy of 0.896, sensitivity of 0.868, and specificity of 1. Conclusion: The radiomics model of enhanced spectral CT images of peripheral lung cancer can predict the expression of EGFR and VEGF.
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