ArticleEuropean radiology2023
Value of T2-weighted-based radiomics model in distinguishing Warthin tumor from pleomorphic adenoma of the parotid.
Article in European radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Do MRI radiomic models truly generalize? External validation of three studies in parotid lesion characterization.European radiology · 2026Article
- The study of nomogram model based on CT radiomics and clinical features for histological classification of parotid gland tumors.Scientific reports · 2026Article
- Differentiation Between Parotid Adenolymphoma and Malignant Tumor Based on Multimodal Functional MRI of Radiomics and Intratumoral Vascular ITSS Classification.Annals of surgical oncology · 2025Article
- Ultrasound-Based Deep Learning Radiomics Models for Predicting Primary and Secondary Salivary Gland Malignancies: A Multicenter Retrospective Study.Bioengineering (Basel, Switzerland) · 2025Article
- Article
- Nomogram combining dual-energy computed tomography features and radiomics for differentiating parotid warthin tumor from pleomorphic adenoma: a retrospective study.Frontiers in oncology · 2025Article
- Radiomic and Clinical Model in the Prognostic Evaluation of Adenoid Cystic Carcinoma of the Head and Neck.Cancers · 2024Article
- The value of T1- and FST2-Weighted-based radiomics nomogram in differentiating pleomorphic adenoma and Warthin tumor.Translational oncology · 2024Article
- An ultrasound-based ensemble machine learning model for the preoperative classification of pleomorphic adenoma and Warthin tumor in the parotid gland.European radiology · 2024Article
- Differentiation of salivary gland tumours using diffusion-weighted image-based virtual MR elastography: a pilot study.Dento maxillo facial radiology · 2024Article
- Performance of radiomics in the differential diagnosis of parotid tumors: a systematic review.Frontiers in oncology · 2024Review
- Risk factors and prediction model of peri-implantitis in post operative periodontitis patients.American journal of translational research · 2024Article
- Radiomics Analysis in Characterization of Salivary Gland Tumors on MRI: A Systematic Review.Cancers · 2023Review
- Semiquantitative magnetic resonance imaging parameters for differentiating parotid pleomorphic adenoma from Warthin tumor.Quantitative imaging in medicine and surgery · 2023Article
- Interpretable Deep Learning Radiomics for Differentiating Pleomorphic Adenoma and Warthin Tumor.In vivo (Athens, Greece)Article
Corrections and comments
- Erratum issued
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesThe differentiation of Warthin tumor and pleomorphic adenoma before treatment is crucial for clinical strategies. The aim of this study was to develop and test a T2-weighted-based radiomics model for differentiating pleomorphic adenoma from Warthin tumor of the parotid gland.
methodsA total of 117 patients, including 61 cases of Warthin tumor and 56 cases of pleomorphic adenoma, were retrospectively enrolled from two centers between January 2010 and June 2022. The training set included 82 cases, and the validation set included 35 cases. From T2-weighted images, 971 radiomics features were extracted. Seven radiomics features remained after a two-step selection process. We used the seven radiomics features and clinical factors through multivariable logistic regression to build radiomics and clinical models, respectively. A radiomics-clinical model was also built that combined the independent clinical predictors with the radiomics features. Through ROC curves, the three models were evaluated and compared.
resultsIn the radiomics model, AUCs were 0.826 and 0.796 in training and validation sets, respectively. In the clinical model, the AUCs were 0.923 and 0.926 in the training and validation sets, respectively. Decision curve analysis revealed that the radiomics-clinical model had the best diagnostic performance for distinguishing Warthin tumor from pleomorphic adenoma of the parotid gland (AUC = 0.962 and 0.934 for the training and validation sets, respectively).
conclusionThe radiomics-clinical model performed well in differentiating pleomorphic adenoma from Warthin tumor of the parotid gland. KEY POINTS: • The clinical model outperformed the radiomics model in distinguishing pleomorphic adenoma from Warthin tumor of the parotid gland. • The radiomics features extracted from T2-weighted images could help differentiate pleomorphic adenoma from Warthin tumor of the parotid gland. • The radiomics-clinical model was superior to the radiomics and the clinical models for differentiating pleomorphic adenoma from Warthin tumor of the parotid gland.
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