Intravoxel Incoherent Motion Magnetic Resonance Imaging for Assessing Parotid Gland Tumors: Correlation and Comparison with Arterial Spin Labeling Imaging

Objective@#To compare and correlate the findings of intravoxel incoherent motion (IVIM) magnetic resonance (MR) imaging and arterial spin labeling (ASL) imaging in characterizing parotid gland tumors. @*Materials and Methods@#We retrospectively reviewed 56 patients with parotid gland tumors evaluated by MR imaging. The true diffusion coefficient (D), pseudo-diffusion coefficient (D*), and fraction of perfusion (f) values of IVIM imaging and tumor-to-parotid gland signal intensity ratio (SIR) on ASL imaging were calculated. Spearman rank correlation coefficient, chi-squared, Mann-Whitney U, and Kruskal-Wallis tests with the post-hoc Dunn-Bonferroni method and receiver operating characteristic curve assessments were used for statistical analysis. @*Results@#Malignant parotid gland tumors showed significantly lower D than benign tumors (p = 0.019). Within subgroup analyses, pleomorphic adenomas (PAs) showed significantly higher D than malignant tumors (MTs) and Warthin’s tumors (WTs) (p < 0.001). The D* of WTs was significantly higher than that of PAs (p = 0.031). The f and SIR on ASL imaging of WTs were significantly higher than those of MTs and PAs (p < 0.05). Significantly positive correlation was found between SIR on ASL imaging and f (r = 0.446, p = 0.001). In comparison with f, SIR on ASL imaging showed a higher area under curve (0.853 vs. 0.891) in discriminating MTs from WTs, although the difference was not significant (p = 0.720). @*Conclusion@#IVIM and ASL imaging could help differentiate parotid gland tumors. SIR on ASL imaging showed a significantly positive correlation with f. ASL imaging might hold potential to improve the ability to discriminate MTs from WTs.

Utility of Readout-Segmented Echo-Planar Imaging-Based Diffusion Kurtosis Imaging for Differentiating Malignant from Benign Masses in Head and Neck Region

OBJECTIVE: To compare the diagnostic performance of readout-segmented echo-planar imaging (RS-EPI)-based diffusion kurtosis imaging (DKI) and that of diffusion-weighted imaging (DWI) for differentiating malignant from benign masses in head and neck region. MATERIALS AND METHODS: Between December 2014 and April 2016, we retrospectively enrolled 72 consecutive patients with head and neck masses who had undergone RS-EPI-based DKI scan (b value of 0, 500, 1000, and 1500 s/mm2) for pretreatment evaluation. Imaging data were post-processed by using monoexponential and diffusion kurtosis (DK) model for quantitation of apparent diffusion coefficient (ADC), apparent diffusion for Gaussian distribution (Dapp), and apparent kurtosis coefficient (Kapp). Unpaired t test and Mann-Whitney U test were used to compare differences of quantitative parameters between malignant and benign groups. Receiver operating characteristic curve analyses were performed to determine and compare the diagnostic ability of quantitative parameters in predicting malignancy. RESULTS: Malignant group demonstrated significantly lower ADC (0.754 ± 0.167 vs. 1.222 ± 0.420, p < 0.001) and Dapp (1.029 ± 0.226 vs. 1.640 ± 0.445, p < 0.001) while higher Kapp (1.344 ± 0.309 vs. 0.715 ± 0.249, p < 0.001) than benign group. Using a combination of Dapp and Kapp as diagnostic index, significantly better differentiating performance was achieved than using ADC alone (area under curve: 0.956 vs. 0.876, p = 0.042). CONCLUSION: Compared to DWI, DKI could provide additional data related to tumor heterogeneity with significantly better differentiating performance. Its derived quantitative metrics could serve as a promising imaging biomarker for differentiating malignant from benign masses in head and neck region.

Diffusion Weighted Imaging for Differentiating Benign from Malignant Orbital Tumors: Diagnostic Performance of the Apparent Diffusion Coefficient Based on Region of Interest Selection Method

OBJECTIVE: To evaluate the differences in the apparent diffusion coefficient (ADC) measurements based on three different region of interest (ROI) selection methods, and compare their diagnostic performance in differentiating benign from malignant orbital tumors. MATERIALS AND METHODS: Diffusion-weighted imaging data of sixty-four patients with orbital tumors (33 benign and 31 malignant) were retrospectively analyzed. Two readers independently measured the ADC values using three different ROIs selection methods including whole-tumor (WT), single-slice (SS), and reader-defined small sample (RDSS). The differences of ADC values (ADC-ROI(WT), ADC-ROI(SS), and ADC-ROI(RDSS)) between benign and malignant group were compared using unpaired t test. Receiver operating characteristic curve was used to determine and compare their diagnostic ability. The ADC measurement time was compared using ANOVA analysis and the measurement reproducibility was assessed using Bland-Altman method and intra-class correlation coefficient (ICC). RESULTS: Malignant group showed significantly lower ADC-ROI(WT), ADC-ROI(SS), and ADC-ROI(RDSS) than benign group (all p 0.05). The ROI(SS) and ROI(RDSS) required comparable measurement time (p > 0.05), while significantly shorter than ROIWT (p < 0.05). The ROI(SS) showed the best reproducibility (mean difference ± limits of agreement between two readers were 0.022 [-0.080-0.123] × 10(-3) mm2/s; ICC, 0.997) among three ROI methods. CONCLUSION: Apparent diffusion coefficient values based on the three different ROI selection methods can help to differentiate benign from malignant orbital tumors. The results of measurement time, reproducibility and diagnostic ability suggest that the ROI(SS) method are potentially useful for clinical practice.