Added value of slow diffusion coefficient (SDC) for the separation of benign and malignant parotid gland tumors by diffusion weighted imaging: preliminary results.

backgroundDiffusion weighted imaging (DWI) has been used to evaluate parotid gland tumors. Warthin's tumors (WTs) have very high diffusion-derived vessel 'density' (DDVD) and low ADC, while pleomorphic adenomas (PAs) have moderately high DDVD and very high apparent diffusion coefficient (ADC). These two most common benign tumors (BTs) can be largely separated by a combination of ADC and DDVD. However, most of the MTs (malignant tumors) had moderately high DDVD and low ADC, the differentiation between BT and MT remains challenging. Slow diffusion coefficient (SDC) is a novel metric being proposed to measure in vivo tissue slow diffusion. In its basic form, SDC is derived from a high b-value DWI image and a higher b-value DWI image. This study tested the application of SDC to evaluate parotid gland tumors.

methodsTwenty-four PAs, 16 WTs, and 14 MTs had DWI at 3T. ADC was calculated with b = 0 and 800 s/mm

resultsParotid gland tumors had a higher SDC than normal parotid gland tissue with SDCr > 1. SDCr was on average PAs (median: 3.075) > MTs (2.755) > WTs (2.250). Separation of BT against MT by ADCr alone, by a combination of ADCr and SDCr, and by a combination of ADCr, SDCr, and DDVDr had AUROC of 0.7393, 0.8018, 0.8054, respectively. The probability of a tumor being MT is given by: ln(p/1-p) = 0.7006*SDCr-3.198*ADCr + 1.417; or ln(p/1-p)=-0.2225*DDVDr-3.41ADCr + 0.7603*SDCr + 2.103. SDCr was positively correlated with ADCr with a Pearson r of 0.624, while SDCr was not apparently correlated with DDVDr.

conclusionThis study tested the principle of applying four b-values DWI to generate three diffusion metrics, namely, ADC, SDC, and DDVD, to evaluate parotid gland tumors. A combination of these three diffusion metrics may offer clinically useful separation of MT from BT. CLINICAL TRIAL NUMBER: Not applicable.