A Whole-Tumor Histogram Analysis of Apparent Diffusion Coefficient Maps for Differentiating Thymic Carcinoma from Lymphoma

Objective To assess the performance of a whole-tumor histogram analysis of apparent diffusion coefficient (ADC) maps in differentiating thymic carcinoma from lymphoma, and compare it with that of a commonly used hot-spot region-of-interest (ROI)-based ADC measurement. Materials and Methods Diffusion weighted imaging data of 15 patients with thymic carcinoma and 13 patients with lymphoma were retrospectively collected and processed with a mono-exponential model. ADC measurements were performed by using a histogram-based and hot-spot-ROI-based approach. In the histogram-based approach, the following parameters were generated: mean ADC (ADCmean), median ADC (ADCmedian), 10th and 90th percentile of ADC (ADC10 and ADC90), kurtosis, and skewness. The difference in ADCs between thymic carcinoma and lymphoma was compared using a t test. Receiver operating characteristic analyses were conducted to determine and compare the differentiating performance of ADCs. Results Lymphoma demonstrated significantly lower ADCmean, ADCmedian, ADC10, ADC90, and hot-spot-ROI-based mean ADC than those found in thymic carcinoma (all p values < 0.05). There were no differences found in the kurtosis (p = 0.412) and skewness (p = 0.273). The ADC10 demonstrated optimal differentiating performance (cut-off value, 0.403 × 10-3 mm2/s; area under the receiver operating characteristic curve [AUC], 0.977; sensitivity, 92.3%; specificity, 93.3%), followed by the ADCmean, ADCmedian, ADC90, and hot-spot-ROI-based mean ADC. The AUC of ADC10 was significantly higher than that of the hot spot ROI based ADC (0.977 vs. 0.797, p = 0.036). Conclusion Compared with the commonly used hot spot ROI based ADC measurement, a histogram analysis of ADC maps can improve the differentiating performance between thymic carcinoma and lymphoma.