ArticleDiagnostics (Basel, Switzerland)2020
Can Magnetic Resonance Radiomics Analysis Discriminate Parotid Gland Tumors? A Pilot Study.
Article in Diagnostics (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
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33 citing papers in PubMed, 42 citations in OpenAlex.
- Machine learning-based radiomics for histological classification of parotid tumors using morphological MRI: a comparative study.European radiology · 2022Trial
- Parotid gland tumor computed tomography image segmentation and benign-malignant differentiation diagnosis.Quantitative imaging in medicine and surgery · 2026Article
- Do MRI radiomic models truly generalize? External validation of three studies in parotid lesion characterization.European radiology · 2026Article
- An integrated clinical and imaging-based machine learning model to determine the preoperative nature of primary operable parotid tumors.BMC oral health · 2026Article
- Using Machine Learning on MRI Radiomics to Diagnose Parotid Tumours Before Comparing Performance with Radiologists: A Pilot Study.Journal of imaging informatics in medicine · 2025Article
- Classification of Parotid Tumors with Robust Radiomic Features from DCE- and DW-MRI.Journal of imaging · 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
- Distinguishing atypical parotid carcinomas and pleomorphic adenomas based on multiphasic computed tomography radiomics nomogram: a multicenter study.Frontiers in oncology · 2025Article
- The value of T1- and FST2-Weighted-based radiomics nomogram in differentiating pleomorphic adenoma and Warthin tumor.Translational oncology · 2024Article
- Article
- Prediction of malignant risk stratification model for parotid gland nodules based on clinical and conventional ultrasound features: construction and validation.Gland surgery · 2024Article
- Early prediction of long-term survival of patients with nasopharyngeal carcinoma by multi-parameter MRI radiomics.European journal of radiology open · 2024Article
- Assessment of synthetic MRI to distinguish Warthin's tumor from pleomorphic adenoma in the parotid gland: comparison of two methods of positioning the region of interest for synthetic relaxometry measurement.Frontiers in oncology · 2024Article
- Performance of radiomics in the differential diagnosis of parotid tumors: a systematic review.Frontiers in oncology · 2024Review
- Different MRI-based radiomics models for differentiating misdiagnosed or ambiguous pleomorphic adenoma and Warthin tumor of the parotid gland: a multicenter study.Frontiers in oncology · 2024Article
- Article
- 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
- The Role of an MRI-Based Radiomic Signature in Predicting Malignancy of Parotid Gland Tumors.Cancers · 2023Article
Corrections and comments
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Authors and funding
12 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Our purpose is to evaluate the performance of magnetic resonance (MR) radiomics analysis for differentiating between malignant and benign parotid neoplasms and, among the latter, between pleomorphic adenomas and Warthin tumors. We retrospectively evaluated 75 T2-weighted images of parotid gland lesions, of which 61 were benign tumors (32 pleomorphic adenomas, 23 Warthin tumors and 6 oncocytomas) and 14 were malignant tumors. A receiver operating characteristics (ROC) curve analysis was performed to find the threshold values for the most discriminative features and determine their sensitivity, specificity and area under the ROC curve (AUROC). The most discriminative features were used to train a support vector machine classifier. The best classification performance was obtained by comparing a pleomorphic adenoma with a Warthin tumor (yielding sensitivity, specificity and a diagnostic accuracy as high as 0.8695, 0.9062 and 0.8909, respectively) and a pleomorphic adenoma with malignant tumors (sensitivity, specificity and a diagnostic accuracy of 0.6666, 0.8709 and 0.8043, respectively). Radiomics analysis of parotid tumors on conventional T2-weighted MR images allows the discrimination of pleomorphic adenomas from Warthin tumors and malignant tumors with a high sensitivity, specificity and diagnostic accuracy.
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