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ObjectiveTo 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 MethodsDiffusion-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-ROIWT, ADC-ROISS, and ADC-ROIRDSS) 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).ResultsMalignant group showed significantly lower ADC-ROIWT, ADC-ROISS, and ADC-ROIRDSS than benign group (all p < 0.05). The areas under the curve showed no significant difference when using ADC-ROIWT, ADC-ROISS, and ADC-ROIRDSS as differentiating index, respectively (all p > 0.05). The ROISS and ROIRDSS required comparable measurement time (p > 0.05), while significantly shorter than ROIWT (p < 0.05). The ROISS 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.ConclusionApparent 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 ROISS method are potentially useful for clinical practice.

ObjectiveTo 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 MethodsBetween 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.ResultsMalignant 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).ConclusionCompared 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.