Usefulness of MRI-based radiomic features for distinguishing Warthin tumor from pleomorphic adenoma: performance assessment using T2-weighted and post-contrast T1-weighted MR images

被引:7
|
作者
Faggioni, Lorenzo [1 ]
Gabelloni, Michela [1 ]
De Vietro, Fabrizio [1 ]
Frey, Jessica [1 ]
Mendola, Vincenzo [1 ]
Cavallero, Diletta [1 ]
Borgheresi, Rita [1 ]
Tumminello, Lorenzo [1 ]
Shortrede, Jorge [1 ]
Morganti, Riccardo [2 ]
Seccia, Veronica [3 ]
Coppola, Francesca [4 ,5 ]
Cioni, Dania [1 ,5 ]
Neri, Emanuele [1 ,5 ]
机构
[1] Univ Pisa, Acad Radiol, Dept Translat Res, Via Roma 67, I-56126 Pisa, Italy
[2] Univ Pisa, Dept Clin & Expt Med, Sect Stat, Via Roma 67, I-56126 Pisa, Italy
[3] Univ Pisa, Azienda Osped Univ Pisana, Dept Surg Med Mol Pathol & Crit Care Med, Otolaryngol Audiol & Phoniatr Operat Unit, I-56124 Pisa, Italy
[4] IRCCS Azienda Osped Univ Bologna, Dept Radiol, I-40138 Bologna, Italy
[5] SIRM Fdn, Italian Soc Med & Intervent Radiol, Via Signora 2, I-20122 Milan, Italy
关键词
Warthin tumor; Pleomorphic adenoma; Head and neck cancer; Parotid neoplasm; Radiomics; Magnetic resonance imaging;
D O I
10.1016/j.ejro.2022.100429
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Purpose:Differentiating Warthin tumor (WT) from pleomorphic adenoma (PA) is of primary importance due to differences in patient management, treatment and outcome. We sought to evaluate the performance of MRIbased radiomic features in discriminating PA from WT in the preoperative setting. Methods:We retrospectively evaluated 81 parotid gland lesions (48 PA and 33 WT) on T2-weighted (T2w) images and 52 of them on post-contrast fat-suppressed T1-weighted (pcfsT1w) images. All MRI examinations were carried out on a 1.5-Tesla MRI scanner, and images were segmented manually using the software ITK-SNAP (www.itk-snap.org). Results:The most discriminative feature on pcfsT1w images was GLCM_InverseVariance, yielding area under the curve (AUC), sensitivity and specificity of 0.9, 86 % and 87 %, respectively. Skewness was the feature extracted from T2w images with the highest specificity (88 %) in discriminating WT from PA. Conclusion:Radiomic analysis could be an important tool to improve diagnostic accuracy in differentiating PA from WT.
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页数:6
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