ArticleEuropean radiology2019
Identification of epidermal growth factor receptor mutations in pulmonary adenocarcinoma using dual-energy spectral computed tomography.
Article in European radiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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27 citing papers in PubMed, 37 citations in OpenAlex.
- Systematic review of spectral computed tomography quantitative parameters for predictingQuantitative imaging in medicine and surgery · 2026Review
- Dual-layer spectral CT for predicting spread through air spaces in lung adenocarcinoma: a dual-center study.European radiology · 2026Article
- Radiogenomic landscape of the hallmarks of cancer.Biomarker research · 2026Review
- An Integrated Clinical-Radiomics-Deep Learning Model Based onCancer medicine · 2025Article
- From Images to Genes: Radiogenomics Based on Artificial Intelligence to Achieve Non-Invasive Precision Medicine in Cancer Patients.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
- Differentiation of pathological subtypes and Ki-67 and TTF-1 expression by dual-energy CT (DECT) volumetric quantitative analysis in non-small cell lung cancer.Cancer imaging : the official publication of the International Cancer Imaging Society · 2024Article
- Diagnosis of newly developed multiple myeloma without bone disease detectable on conventional computed tomography (CT) scan by using dual-energy CT.Journal of bone oncology · 2024Article
- Three-dimensional iodine mapping quantified by dual-energy CT for predicting programmed death-ligand 1 expression in invasive pulmonary adenocarcinoma.Scientific reports · 2024Article
- Does dual-layer spectral detector CT provide added value in predicting spread through air spaces in lung adenocarcinoma? A preliminary study.European radiology · 2024Article
- CT-based radiomics and clinical characteristics for predicting bone metastasis in lung adenocarcinoma patients.Translational lung cancer research · 2024Article
- Predicting epidermal growth factor receptor mutations in non-small cell lung cancer through dual-layer spectral CT: a prospective study.Insights into imaging · 2024Article
- Dual-energy CT-based radiomics in predicting EGFR mutation status non-invasively in lung adenocarcinoma.Heliyon · 2024Article
- Value of spectral computed tomography-derived quantitative parameters based on full volume analysis in the diagnosis of benign/malignant and pathological subtypes of solitary pulmonary nodules.Quantitative imaging in medicine and surgery · 2023Article
- Prediction of EGFR mutation status in lung adenocarcinoma based onAmerican journal of nuclear medicine and molecular imaging · 2023Article
- Diagnosis of benign and malignant thyroid nodules by a dual-layer spectral detector CT-based nomogram.Frontiers in oncology · 2023Article
- Dual-energy CT-based radiomics for predicting invasiveness of lung adenocarcinoma appearing as ground-glass nodules.Frontiers in oncology · 2023Article
- Prediction of EGFR Mutation Status in Non-Small Cell Lung Cancer Based on Ensemble Learning.Frontiers in pharmacology · 2022Article
- Quantitative dual-energy CT for evaluating hepatocellular carcinoma after transarterial chemoembolization.Scientific reports · 2021Article
- Differentiating malignant and benign necrotic lung lesions using kVp-switching dual-energy spectral computed tomography.BMC medical imaging · 2021Article
- Imaging of synchronous multiple primary lung adenocarcinoma with concomitantTranslational cancer research · 2021Article
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Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
Abstract
objectivesTo explore the role of dual-energy spectral computed tomography (DESCT) quantitative characteristics for the identification of epidermal growth factor receptor (EGFR) mutation status in a cohort of East Asian patients with pulmonary adenocarcinoma. MATERIALS AND
methodsPatients with lung adenocarcinoma who underwent both DESCT chest examination and EGFR test were retrospectively selected from our institution's database. The DESCT visual morphological features and quantitative parameters, including the CT number at 70 keV, normalized iodine concentration (NIC), normalized water concentration, and slopes of the spectral attenuation curves (slope λ HU [Hounsfield unit]), were evaluated or calculated. The patients were divided into two groups: the EGFR mutation group and EGFR wild-type group. Statistical analyses were performed to identify the DESCT quantitative parameters for diagnosis of EGFR mutation status.
resultsEGFR mutations were detected in 66 (55.0%) of the 120 enrolled patients. The univariate analysis revealed that sex, smoking history, CT texture, NIC, and slope λ HU were significantly associated with EGFR mutation status (p = 0.037, 0.001, 0.047, 0.010, and 0.018, respectively). The multivariate logistic analysis revealed that smoking history (odds ratio [OR] = 3.23, p = 0.005) and NIC (OR = 58.026, p = 0.049) were the two significant predictive factors associated with EGFR mutations. Based on this analysis, the smoking history and NIC were combined to determine the predictive value for EGFR mutations with the area under the curve of 0.702.
conclusionsNIC may be a potential quantitative DESCT parameter for predicting EGFR mutations in patients with pulmonary adenocarcinoma. KEY POINTS: • DESCT can provide multiple quantitative image parameters compared to conventional CT. • Identification of the radio-genomic relation between DESCT and EGFR status can help to define molecular subcategories of lung adenocarcinoma, which is valuable for personalized clinical targeted therapy. • NIC may be a potential DESCT quantitative parameter for predicting EGFR mutations in pulmonary adenocarcinoma.
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