Multiparametric Magnetic Resonance Imaging for Assessing Thymic Epithelial Tumors: Correlation With Pathological Subtypes and Clinical Stages

Background: World Health Organization classification and Masaoka-Koga stage are widely used for thymic epithelial tumors (TETs). Reduced field-of-view (rFOV) diffusion-weighed imaging (DWI) proved to improve the image quality. Dynamic contrast-enhanced (DCE) MRI was commonly used in evaluating tumors.

Purpose: To investigate the value of multiparametric MRI in evaluating TETs.

Study type: Retrospective.

Subjects: Eighty-seven participants including 38 low risk (52.08 ± 14.19 years), 30 high risk (52.40 ± 11.35 years), and 19 thymic carcinoma patients (59.76 ± 10.78 years).

Field strength/sequence: A 3 T, turbo spin echo imaging, echo planar imaging, volumetric interpolated breath-hold examination with radial acquisition trajectory.

Assessment: DCE-MRI and apparent diffusion coefficient (ADC) variables were compared. Diagnostic performances of single significant factor and combined model were compared.

Statistical tests: Parameters were compared using one-way ANOVA or independent-samples t test. Logistic regression was employed to investigate the combined model. Receiver operating curves (ROC) and DeLong's test were used to compare the diagnostic efficiency.

Results: ADC, K^trans , and k_ep values were significantly different among low-risk, high-risk and carcinoma group (ADC, 1.279 ± 0.345 × 10^-3 mm² /sec, 0.978 ± 0.260 × 10^-3 mm² /sec, 0.661 ± 0.134 × 10^-3 mm² /sec; K^trans 0.167 ± 0.071 min^-1 , 0.254 ± 0.136 min^-1 , 0.393 ± 0.110 min^-1 ; k_ep 0.345 ± 0.113 min^-1 , 0.560 ± 0.269 min^-1 , 0.872 ± 0.149 min^-1 ). They were significantly different for early stage and advanced stage (ADC, 1.270 ± 0.356 × 10^-3 mm² /sec vs. 0.845 ± 0.251 × 10^-3 mm² /sec; K^trans 0.179 ± 0.092 min^-1 vs. 0.304 ± 0.142 min^-1 ; k_ep 0.370 ± 0.181 min^-1 vs. 0.674 ± 0.362 min^-1 ). The combination of them had highest diagnostic efficiency for WHO classification (AUC, 0.925; sensitivity, 83.7%; specificity, 89.5%), clinical stage (AUC, 0.879; sensitivity, 80.9%; specificity, 82.5%).

Data conclusion: Multiparametric MRI model may be useful for discriminating WHO classification and clinical stage of TETs.

Evidence level: 4 TECHNICAL EFFICIENCY: Stage 2.