SynthesisInternational journal of molecular sciences2023
Systematic Review, Meta-Analysis and Radiomics Quality Score Assessment of CT Radiomics-Based Models Predicting Tumor EGFR Mutation Status in Patients with Non-Small-Cell Lung Cancer.
Synthesis in International journal of molecular sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 7 of them syntheses that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
25 citing papers in PubMed, 7 syntheses or guidelines pooled it.
- Preoperative radiomics models using CT and MRI for microsatellite instability in colorectal cancer: a systematic review and meta-analysis.Abdominal radiology (New York) · 2025Pooled it
- Preoperative radiomics models using CT and MRI for microsatellite instability in colorectal cancer: a systematic review and meta-analysis.Abdominal radiology (New York) · 2025Pooled it
- Diagnostic accuracy of CT and PET/CT radiomics in predicting lymph node metastasis in non-small cell lung cancer.European radiology · 2025Pooled it
- The potential of MRI radiomics based on extrapulmonary metastases in predicting EGFR mutations: a systematic review and meta-analysis.Biomedical engineering online · 2025Pooled it
- Diagnostic accuracy of MRI-based radiomic features for EGFR mutation status in non-small cell lung cancer patients with brain metastases: a meta-analysis.Frontiers in oncology · 2024Pooled it
- CT-based radiomics for predicting Ki-67 expression in lung cancer: a systematic review and meta-analysis.Frontiers in oncology · 2024Pooled it
- Preoperative magnetic resonance imaging-radiomics in cervical cancer: a systematic review and meta-analysis.Frontiers in oncology · 2024Pooled it
- Quality over quantity: biopsy-anchored CT radiogenomics models outperform all-lesion training in a multi-tumour cohort despite a smaller sample size.European radiology · 2026Article
- Radiomics in Lung Cancer Imaging: A Narrative Review of Current Evidence.Journal of imaging · 2026Review
- A CT imaging-based deep learning model for predicting EGFR and KRAS mutations in non-small cell lung cancer: toward personalized treatment approaches.Translational lung cancer research · 2026Article
- Radiomics meets pathology: Building the bridge for precision oncology.CytoJournal · 2026Article
- Quantitative analysis for identifying molecular subtypes of small cell lung cancer via two-dimensional and three-dimensional contrast-enhanced computed tomography images: a preliminary study.Journal of thoracic disease · 2025Article
- Prediction of EGFR mutation status in non-small cell lung cancer based on multiparametric MRI radiomics.BMC medical imaging · 2025Article
- Radiomics Quality Score 2.0: towards radiomics readiness levels and clinical translation for personalized medicine.Nature reviews. Clinical oncology · 2025Review
- The Impact of Artificial Intelligence on Lung Cancer Diagnosis and Personalized Treatment.International journal of molecular sciences · 2025Review
- Cardiac Troponin I Promotes the Development of NSCLC Cells Through the Expression of Notch and Kras Proteins.Iranian journal of biotechnology · 2025Article
- Development of AI-Based Predictive Models for Osteoporosis Diagnosis in Postmenopausal Women from Panoramic Radiographs.Journal of clinical medicine · 2025Article
- Perioperative Strategies in Resectable Non-Squamous Non-Small Cell Lung Cancer with EGFR Mutations and ALK Rearrangement.Cancers · 2025Review
- Radiogenomics-based prediction ofZhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2025Article
- Radiomics based on dual-layer spectral detector CT for predicting EGFR mutation status in non-small cell lung cancer.Journal of applied clinical medical physics · 2025Article
Corrections and comments
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8 authors.
Funding
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Abstract
Assessment of the quality and current performance of computed tomography (CT) radiomics-based models in predicting epidermal growth factor receptor (EGFR) mutation status in patients with non-small-cell lung carcinoma (NSCLC). Two medical literature databases were systematically searched, and articles presenting original studies on CT radiomics-based models for predicting EGFR mutation status were retrieved. Forest plots and related statistical tests were performed to summarize the model performance and inter-study heterogeneity. The methodological quality of the selected studies was assessed via the Radiomics Quality Score (RQS). The performance of the models was evaluated using the area under the curve (ROC AUC). The range of the Risk RQS across the selected articles varied from 11 to 24, indicating a notable heterogeneity in the quality and methodology of the included studies. The average score was 15.25, which accounted for 42.34% of the maximum possible score. The pooled Area Under the Curve (AUC) value was 0.801, indicating the accuracy of CT radiomics-based models in predicting the EGFR mutation status. CT radiomics-based models show promising results as non-invasive alternatives for predicting EGFR mutation status in NSCLC patients. However, the quality of the studies using CT radiomics-based models varies widely, and further harmonization and prospective validation are needed before the generalization of these models.
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