Dynamic contrast-enhanced MRI to differentiate parotid neoplasms using golden-angle radial sparse parallel imaging

Abstract

BACKGROUND AND PURPOSE: Conventional imaging frequently shows overlapping features between benign and malignant parotid neoplasms. We investigated dynamic contrast-enhanced MR imaging using golden-angle radial sparse parallel imaging in differentiating parotid neoplasms. MATERIALS AND METHODS: For this retrospective study, 41 consecutive parotid neoplasms were imaged with dynamic contrast-enhanced MR imaging with golden-angle radial sparse parallel imaging using 1-mm in-plane resolution. The temporal resolution was 3.4 seconds for 78.2 seconds and 8.8 seconds for the remaining acquisition. Three readers retrospectively and independently created and classified time-intensity curves as follows: 1) continuous wash-in; 2) rapid wash-in, subsequent plateau; and 3) rapid wash-in with washout. Additionally, time-intensity curve–derived semiquantitative metrics normalized to the ipsilateral common carotid artery were recorded. Diagnostic performance for the prediction of neoplasm type and malignancy was assessed. Subset multivariate analysis (n 32) combined semiquantitative time-intensity curve metrics with ADC values. RESULTS: Independent time-intensity curve classification of the 41 neoplasms produced moderate-to-substantial interreader agreement ( 0.50 – 0.79). The time-intensity curve classification threshold of 2 predicted malignancy with a positive predictive value of 56.0%–66.7%, and a negative predictive value of 92.0%–100%. The time-intensity curve classification threshold of 2 predicted pleomorphic adenoma with a positive predictive value of 87.0%–95.0% and a negative predictive value of 76.0%–95.0%. For all readers, type 2 and 3 curves were associated with malignant neoplasms (P .001), and type 1 curves, with pleomorphic adenomas (P .001). Semiquantitative analysis for malignancy prediction yielded an area under the receiver operating characteristic curve of 0.85 (95% CI, 0.73–0.99). Combining time-to-maximum and ADC predicts pleomorphic adenoma better than either metric alone (P .001). CONCLUSIONS: Golden-angle radial sparse parallel MR imaging allows high spatial and temporal resolution permeability characterization of parotid neoplasms, with a high negative predictive value for malignancy prediction. Combining time-to-maximum and ADC improves pleomorphic adenoma prediction compared with either metric alone.