2020
Journal article  Open Access

Can Magnetic Resonance Radiomics Analysis Discriminate Parotid Gland Tumors? A Pilot Study

Gabelloni M., Faggioni L., Attanasio S., Vani V., Goddi A., Colantonio S., Germanese D., Caudai C., Bruschini L., Scarano M., Seccia V., Neri E.

Warthin tumor  adenoma  head and neck cancer  pleomorphic  Article  parotid neoplasm  Clinical Biochemistry  artificial intelligence 

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.

Source: Diagnostics (Basel) 10 (2020). doi:10.3390/diagnostics10110900

Publisher: Molecular Diversity Preservation International, Basel


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BibTeX entry
@article{oai:it.cnr:prodotti:439861,
	title = {Can Magnetic Resonance Radiomics Analysis Discriminate Parotid Gland Tumors? A Pilot Study},
	author = {Gabelloni M. and Faggioni L. and Attanasio S. and Vani V. and Goddi A. and Colantonio S. and Germanese D. and Caudai C. and Bruschini L. and Scarano M. and Seccia V. and Neri E.},
	publisher = {Molecular Diversity Preservation International, Basel  },
	doi = {10.3390/diagnostics10110900},
	journal = {Diagnostics (Basel)},
	volume = {10},
	year = {2020}
}