ArticleFrontiers in oncology2022
Diagnostic value of dual-layer spectral detector CT in differentiating lung adenocarcinoma from squamous cell carcinoma.
Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed, 13 citations in OpenAlex.
- Nomogram combining spectral dual-layer detector CT radiomics and deep learning features predicts alveolar tumor spread.Frontiers in oncology · 2026Article
- Spectral computed tomography iodine concentration spatial distribution and multi-parameter quantitative analysis in the differential diagnosis of central small cell lung cancer from squamous cell carcinoma.Translational cancer research · 2025Article
- Improving Diagnostic Accuracy in Acute Pulmonary Embolism: Insights from Spectral Dual-energy CT.Current medical imaging · 2025Article
- Comparison between community-acquired pneumonia and post-obstructive pneumonia associated with endobronchial tumors.BMC pulmonary medicine · 2024Article
- The diagnosis value of dual-energy computed tomography (DECT) multi-parameter imaging in lung adenocarcinoma and squamous cell carcinoma.BMC pulmonary medicine · 2024Article
- Differentiating between benign and malignant breast lesions using dual-energy CT-based model: development and validation.Insights into imaging · 2024Article
- Comparison of the diagnostic efficacy between imaging features and iodine density values for predicting microvascular invasion in hepatocellular carcinoma.Frontiers in oncology · 2024Article
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11 authors at 3 institutions in 1 country.
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Abstract
Background and objective: The pathological type of non-small cell lung cancer is considered to be an important factor affecting the treatment and prognosis. The purpose of this study was to investigate the diagnostic value of spectral parameters of dual-layer spectral detector computed tomography (DLCT) in determining efficacy to distinguish adenocarcinoma (AC) and squamous cell carcinoma (SC), and their combined diagnostic efficacy was also analyzed. Methods: This is a single-center prospective study, and we collected 70 patients with lung SC and 127 patients with lung AC confirmed by histopathological examination. Morphological parameters, plain scan CT value, biphasic enhanced CT value, and spectral parameters were calculated. The diagnostic efficiency of morphological parameters, spectral parameters, and spectral parameters combined with morphological parameters was obtained by statistical analysis. Results: In univariate analysis, seven morphological CT features differed significantly between SC and AC: tumor location (distribution), lobulation, spicule, air bronchogram, vacuole sign, lung atelectasis and/or obstructive pneumonia, and vascular involvement (all Conclusion: The quantitative parameters of the DLCT spectrum are of great value in the diagnosis of SC and AC, and the combination of morphological parameters and spectral parameters is helpful to distinguish SC from AC.
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