ArticleBMC medical imaging2022
Analysis of the value of enhanced CT combined with texture analysis in the differential diagnosis of pulmonary sclerosing pneumocytoma and atypical peripheral lung cancer: a feasibility study.
Article in BMC medical imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- 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
- Symptomatic Sclerosing Pneumocytoma of Lung: A Diagnostic Challenge with Diverse Morphological Patterns.Iranian journal of pathology · 2026Article
- Combining computed tomography features and histogram analysis facilitates differentiation between solitary pulmonary invasive mucinous and non-mucinous adenocarcinomas.Frontiers in radiology · 2026Article
- Nomogram combining spectral dual-layer detector CT radiomics and deep learning features predicts alveolar tumor spread.Frontiers in oncology · 2026Article
- Pulmonary sclerosing pneumocytoma with rapid progression: a case description of serial images.Quantitative imaging in medicine and surgery · 2025Article
- Characterization of Pulmonary Sclerosing Pneumocytoma Assessed byThoracic cancer · 2025Article
- Development of a radiomics and clinical feature-based nomogram for preoperative prediction of pathological grade in bladder cancer.Frontiers in oncology · 2025Article
- Giant Cystic Pneumocytoma in a Young Male: Rare Diagnostic Conundrum with Clinicoradiological and Histopathological Features.The Indian journal of radiology & imaging · 2025Article
- Case Report: Pulmonary sclerosing pneumocytoma mimicking as a neuroendocrine tumor onFrontiers in oncology · 2025Article
- Mediastinal epithelioid sarcoma: a case report.Frontiers in medicine · 2025Article
- Noninvasive assessment of significant liver fibrosis in rabbits by spectral CT parameters and texture analysis.Japanese journal of radiology · 2023Article
- Giant pulmonary sclerosing pneumocytoma with potentially malignant biological behavior: a case report and literature review.Annals of translational medicine · 2023Article
- Prediction of histologic types in solid lung lesions using preoperative contrast-enhanced CT.European radiology · 2023Article
- The adding value of contrast-enhanced CT radiomics: Differentiating tuberculosis from non-tuberculous infectious lesions presenting as solid pulmonary nodules or masses.Frontiers in public health · 2022Article
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7 authors.
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Abstract
backgroundAs a rare benign lung tumour, pulmonary sclerosing pneumocytoma (PSP) is often misdiagnosed as atypical peripheral lung cancer (APLC) on routine imaging examinations. This study explored the value of enhanced CT combined with texture analysis to differentiate between PSP and APLC.
methodsForty-eight patients with PSP and fifty patients with APLC were retrospectively enrolled. The CT image features of the two groups of lesions were analysed, and MaZda software was used to evaluate the texture of CT venous phase thin-layer images. Independent sample t-test, Mann-Whitney U tests or χ
resultsLogistic regression analysis based on CT image features showed that calcification and arterial phase CT values were independent factors for distinguishing PSP from APLC. The results of logistic regression analysis based on CT texture parameters showed that WavEnHL_s-1 and Perc.01% were independent influencing factors to distinguish the two. Compared with the single-factor model (models A and B), the classification accuracy of the model based on image features combined with texture parameters was 0.84 ± 0.04, the AUC was 0.84 ± 0.03, and the sensitivity and specificity were 0.82 ± 0.13 and 0.87 ± 0.12, respectively.
conclusionEnhanced CT combined with texture analysis showed good diagnostic value for distinguishing PSP and APLC, which may contribute to clinical decision-making and prognosis evaluation.
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