Aim: To differentiate Warthin tumors (WTs) and pleomorphic adenomas (PAs) measuring heterogeneity of intravoxel incoherent motion (IVIM) and dynamic-contrast enhanced-magnetic resonance imaging biomarkers. Methods: Volumes of interest were traced on 18 WT and 18 PA in 25 patients. For each IVIM and dynamic-contrast enhanced biomarker, histogram parameters were calculated and then compared using the Wilcoxon-signed-rank test. Receiver operating characteristic curves and multivariate analysis were employed to identify the parameters and their pairs with the best accuracy. Results: Most of the biomarkers exhibited significant difference (p < 0.05) between PA and WT for histogram parameters. Time to peak median and skewness, and D∗ median and entropy showed the highest area under the curve. No meaningful improvement of accuracy was obtained using two features. Conclusion: IVIM and dynamic-contrast enhanced histogram descriptors may help in the classification of WT and PA.

Quantification of heterogeneity to classify benign parotid tumors : a feasibility study on most frequent histotypes / F. Patella, M. Sansone, G. Franceschelli, L. Tofanelli, M. Petrillo, M. Fusco, G.M. Nicolino, G. Buccimazza, R. Fusco, V. Gopalakrishnan, F. Pesapane, F. Biglioli, M. Cariati. - In: FUTURE ONCOLOGY. - ISSN 1479-6694. - 16:12(2020 Apr), pp. 763-778. [10.2217/fon-2019-0736]

Quantification of heterogeneity to classify benign parotid tumors : a feasibility study on most frequent histotypes

F. Patella
;
L. Tofanelli;G.M. Nicolino;G. Buccimazza;F. Pesapane;F. Biglioli;
2020

Abstract

Aim: To differentiate Warthin tumors (WTs) and pleomorphic adenomas (PAs) measuring heterogeneity of intravoxel incoherent motion (IVIM) and dynamic-contrast enhanced-magnetic resonance imaging biomarkers. Methods: Volumes of interest were traced on 18 WT and 18 PA in 25 patients. For each IVIM and dynamic-contrast enhanced biomarker, histogram parameters were calculated and then compared using the Wilcoxon-signed-rank test. Receiver operating characteristic curves and multivariate analysis were employed to identify the parameters and their pairs with the best accuracy. Results: Most of the biomarkers exhibited significant difference (p < 0.05) between PA and WT for histogram parameters. Time to peak median and skewness, and D∗ median and entropy showed the highest area under the curve. No meaningful improvement of accuracy was obtained using two features. Conclusion: IVIM and dynamic-contrast enhanced histogram descriptors may help in the classification of WT and PA.
DCE-MRI; DW-MRI; histogram; intravoxel incoherent motion; magnetic resonance; parotid tumors; pleomorphic adenoma; volume of interest; Warthin tumor; Adolescent; Adult; Aged; Aged, 80 and over; Algorithms; Biological Variation, Population; Feasibility Studies; Female; Histocytochemistry; Humans; Image Processing, Computer-Assisted; Magnetic Resonance Imaging; Male; Middle Aged; Models, Theoretical; Neoplasm Grading; Neoplasm Staging; Parotid Neoplasms; ROC Curve; Retrospective Studies; Young Adult
Settore MED/29 - Chirurgia Maxillofacciale
Settore MED/36 - Diagnostica per Immagini e Radioterapia
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/813615
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