ArticleFuture oncology (London, England)2025
Deep transfer learning radiomics for distinguishing sinonasal malignancies: a preliminary MRI study.
Article in Future oncology (London, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Identifying predictor factors for asthma using machine learning: evidence from the English Longitudinal Study of Ageing.BMC public health · 2026Article
- Interpretable clinical-radiomics fusion model for noninvasive prediction of INI1 deficiency and prognosis in sinonasal undifferentiated carcinoma (SNUC): a two-center study.BMC medical imaging · 2026Article
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5 authors.
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Abstract
purposeThis study aimed to assess the diagnostic accuracy of combining MRI hand-crafted (HC) radiomics features with deep transfer learning (DTL) in identifying sinonasal squamous cell carcinoma (SCC), adenoid cystic carcinoma (ACC), and non-Hodgkin's lymphoma (NHL) using various machine learning (ML) models.
methodsA retrospective analysis of 132 patients (50 with SCC, 42 with NHL, 40 with ACC) was conducted. The dataset was split 80/20 into training and testing cohorts. HC radiomics and DTL features were extracted from T2-weighted, ADC, and contrast-enhanced T1-weighted MRI images. ResNet50, a pre-trained convolutional neural network, was used for DTL feature extraction. LASSO regression was applied to select features and create radiomic signatures. Seven ML models were evaluated for classification performance.
resultsThe radiomic signature included 24 hC and 8 DTL features. The support vector machine (SVM) model achieved the highest accuracy (92.6%) in the testing cohort. The SVM model's ROC analysis showed macro-average and micro-average AUC values of 0.98 and 0.99. AUCs for ACC, NHL, and SCC were 0.99, 0.97, and 1.00. K-nearest neighbors (KNN) and XGBoost also showed AUC values above 0.90.
conclusionCombining MRI-based HC radiomics and DTL features with the SVM model enhanced differentiation between sinonasal SCC, NHL, and ACC.
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