MRI-based texture analysis to differentiate the most common parotid tumours.

AIM: To evaluate magnetic resonance imaging (MRI) features and signal characteristics of parotid masses and investigate the added role of texture analysis (TA) in the differentiation of parotid tumours.

MATERIALS AND

METHODS

Ninety-five patients (42 women, 53 men; mean age 51.67±14.15) were included in this study. The study group consisted of 40 pleomorphic adenoma, 45 Warthin's tumour, and 10 mucoepidermoid carcinomas. Two reviewers assessed the MRI sequences retrospectively. Fat-suppressed T2-weighted and contrast-enhanced T1-weighted axial images were used for TA. Receiver operating characteristic curve analyses were performed to evaluate the ability to make a diagnosis. Logistic regression analyses were conducted to explore the independent risk factors among the MRI features and to analyse the added value of TA to the qualitative analysis.

RESULTS

Significant differences were found in the tumour border (p<0.001), infiltration of the surrounding tissue (p=0.003), contrast-enhancement grading (p<0.001), perineural spread (p=0.013), and pathological lymph nodes (p<0.001) between the malignant and benign tumours. Kurtosis on contrast-enhanced T1-weighted images, and skewness and kurtosis on T2-weighted images were significantly different between the three groups (p=0.020, <0.001, 0.003; respectively). A kurtosis value on T2-weighted images <2.815 along with an ill-defined border had the highest specificity (98.8%) and positive predictive value (83.3%) in the differentiation of malignant tumours.

CONCLUSION

The addition of TA parameters to the MRI findings may contribute to distinguish benign from malignant parotid tumours.