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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

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 MRI-based radiomic features in discriminating PA from WT in the preoperative setting. METHODS:...

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Autores principales: Faggioni, Lorenzo, Gabelloni, Michela, De Vietro, Fabrizio, Frey, Jessica, Mendola, Vincenzo, Cavallero, Diletta, Borgheresi, Rita, Tumminello, Lorenzo, Shortrede, Jorge, Morganti, Riccardo, Seccia, Veronica, Coppola, Francesca, Cioni, Dania, Neri, Emanuele
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9214819/
https://www.ncbi.nlm.nih.gov/pubmed/35757232
http://dx.doi.org/10.1016/j.ejro.2022.100429
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author Faggioni, Lorenzo
Gabelloni, Michela
De Vietro, Fabrizio
Frey, Jessica
Mendola, Vincenzo
Cavallero, Diletta
Borgheresi, Rita
Tumminello, Lorenzo
Shortrede, Jorge
Morganti, Riccardo
Seccia, Veronica
Coppola, Francesca
Cioni, Dania
Neri, Emanuele
author_facet Faggioni, Lorenzo
Gabelloni, Michela
De Vietro, Fabrizio
Frey, Jessica
Mendola, Vincenzo
Cavallero, Diletta
Borgheresi, Rita
Tumminello, Lorenzo
Shortrede, Jorge
Morganti, Riccardo
Seccia, Veronica
Coppola, Francesca
Cioni, Dania
Neri, Emanuele
author_sort Faggioni, Lorenzo
collection PubMed
description 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 MRI-based 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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spelling pubmed-92148192022-06-23 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 Faggioni, Lorenzo Gabelloni, Michela De Vietro, Fabrizio Frey, Jessica Mendola, Vincenzo Cavallero, Diletta Borgheresi, Rita Tumminello, Lorenzo Shortrede, Jorge Morganti, Riccardo Seccia, Veronica Coppola, Francesca Cioni, Dania Neri, Emanuele Eur J Radiol Open Article 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 MRI-based 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. Elsevier 2022-06-18 /pmc/articles/PMC9214819/ /pubmed/35757232 http://dx.doi.org/10.1016/j.ejro.2022.100429 Text en © 2022 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Faggioni, Lorenzo
Gabelloni, Michela
De Vietro, Fabrizio
Frey, Jessica
Mendola, Vincenzo
Cavallero, Diletta
Borgheresi, Rita
Tumminello, Lorenzo
Shortrede, Jorge
Morganti, Riccardo
Seccia, Veronica
Coppola, Francesca
Cioni, Dania
Neri, Emanuele
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
title 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
title_full 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
title_fullStr 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
title_full_unstemmed 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
title_short 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
title_sort 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
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9214819/
https://www.ncbi.nlm.nih.gov/pubmed/35757232
http://dx.doi.org/10.1016/j.ejro.2022.100429
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