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 (ADC), median ADC (ADC), 10th and 90th percentile of ADC (ADC and ADC), kurtosis, and skewness. The difference in ADCs between thymic carcinoma and lymphoma was compared using a test. Receiver operating characteristic analyses were conducted to determine and compare the differentiating performance of ADCs.

RESULTS

Lymphoma demonstrated significantly lower ADC, ADC, ADC, ADC, and hot-spot-ROI-based mean ADC than those found in thymic carcinoma (all values < 0.05). There were no differences found in the kurtosis ( = 0.412) and skewness ( = 0.273). The ADC demonstrated optimal differentiating performance (cut-off value, 0.403 × 10 mm/s; area under the receiver operating characteristic curve [AUC], 0.977; sensitivity, 92.3%; specificity, 93.3%), followed by the ADC, ADC, ADC, and hot-spot-ROI-based mean ADC. The AUC of ADC was significantly higher than that of the hot spot ROI based ADC (0.977 vs. 0.797, = 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.