Predicting the risk grades of thymic epithelial tumors using T1 mapping and diffusion-weighted MRI.

Objective: To explore the value of native T1 and apparent diffusion coefficients (ADC) for predicting subtypes and stages of thymic epithelial tumors (TETs).

Methods: Sixty-seven patients with TETs confirmed by pathological analysis were retrospectively enrolled. The mean native T1 (T1mean), global native T1 (ADCtotal), relative minimum ADC (ADCmin), and global ADC (ADCtotal) values of the tumor were measured and compared for differences among low-risk thymoma (LRT), high-risk thymoma (HRT), and thymic carcinoma (TC). The differentiating efficacy was determined using receiver operating characteristic curve analysis.

Results: The native T1 values in thymoma or early stage were significantly higher than those in TC (P < 0.05/3) or advanced stage of TETs (P < 0.01). The ADC values in LRT or early stage were significantly higher than those in TC (P < 0.05/3) or advanced stage of TETs (P < 0.001). For differentiating the thymoma or HRT from TC, a combination of native T1 and ADC achieved the highest efficacy with an AUC of 0.891 and 0.851, respectively. For determining the TET stage, ADCmin achieved a relatively high diagnostic efficacy with an AUC of 0.933, and a combination of native T1 and ADC obtained an AUC of 0.876.

Conclusion: The combination of native T1 and ADC values could be helpful in clinical practice regarding evaluating TETs before treatment.

Advances in knowledge: The combination of T1 mapping and DWI can improve diagnostic accuracy and help guide clinical practice in providing the best individual treatment for TET patients.