Contribution of Apparent Diffusion Coefficient Histogram Analysis Findings in Differential Diagnosis of Parotid Gland Masses

Introduction: In this retrospective study, our purpose was to research the usefulness of apparent diffusion coefficient (ADC) histogram graphics for the preoperative diagnosis of parotis tumors with heterogeneous signal distribution. Methods: Our patient group included 50 patients with total 52 parotid gland masses who had diffusion-weighted imaging and ADC maps before operation or biopsy, which were archived in our instutional Picture Archiving and Communications System. Freehand region of interest-based ADC histogram parameters were minimum (ADC min), maximum (ADC max), mean (ADC mean) and standard deviation (SD) (ADC SD). Statistical analyses were performed with the SPSS 17.0 using Kruskal-Wallis, Mann-Whitney U tests, Spearmans' rho correlation and receiver operating characteristic (ROC) curve. Results: ADC min, ADC max and especially the ADC mean were statistically significant in differentiating pleomorphic adenoma (PA) from Warthin tumor (WT). ADC min and ADC max values were also significant in differentiating PA from malignant tumor (MT) (p<0.05). In PA-WT differentiation ADC mean value with 1465.50 cut-off level, sensitivity was 94.1% and specificity was 88.6%. For PA-MT differentiation, ADC min value with 962.00 cut-off level, sensitivity was 82.4% and specificity was 94.3%. Whereas, ADC histogram values for WT-MT differentiation were statistically insignificant (p>0.05). Conclusion: Our results support the assumption that ADC histogram parameters can help discriminate PA from WT and PA from MTs preoperatively. However, they are unhelpful in the differential diagnosis of malignant masses from WT.