Department of Radiology, Jiangsu Province People's Hospital, Nanjing Medical University First Affiliated Hospital, No. 300 Guangzhou Road, Nanjing, 210029, Jiangsu, People's Republic of China.
Sci Rep. 2022 Jul 24;12(1):12629. doi: 10.1038/s41598-022-16393-y.
To evaluate the value of texture analysis based on dynamic contrast enhanced MRI (DCE-MRI) in the differential diagnosis of thymic carcinoma and thymic lymphoma. Sixty-nine patients with pathologically confirmed (thymic carcinoma, n = 32; thymic lymphoma, n = 37) were enrolled in this retrospective study. K, K and V maps were automatically generated, and texture features were extracted, including mean, median, 5th/95th percentile, skewness, kurtosis, diff-variance, diff-entropy, contrast and entropy. The differences in parameters between the two groups were compared and the diagnostic efficacy was calculated. The K-related significant features yielded an area under the curve (AUC) of 0.769 (sensitivity 90.6%, specificity 51.4%) for the differentiation between thymic carcinoma and thymic lymphoma. The K-related significant features yielded an AUC of 0.780 (sensitivity 87.5%, specificity 62.2%). The V-related significant features yielded an AUC of 0.807 (sensitivity 75.0%, specificity 78.4%). The combination of DCE-MRI textural features yielded an AUC of 0.962 (sensitivity 93.8%, specificity 89.2%). Five parameters were screened out, including age, K-entropy, K-entropy, V-entropy, and V-P95. The combination of these five parameters yielded the best discrimination efficiency (AUC of 0.943, 93.7% sensitivity, 81.1% specificity). Texture analysis of DCE-MRI may be helpful to distinguish thymic carcinoma from thymic lymphoma.
评估基于动态对比增强磁共振成像(DCE-MRI)的纹理分析在胸腺癌和胸腺瘤鉴别诊断中的价值。
回顾性分析经病理证实的 69 例胸腺癌(n=32)和胸腺瘤(n=37)患者的 DCE-MRI 资料。自动生成 K、K 和 V 图,并提取纹理特征,包括均值、中位数、5%/95%分位数、偏度、峰度、差异方差、差异熵、对比度和熵。比较两组间参数差异,并计算诊断效能。
K 相关的显著特征区分胸腺癌和胸腺瘤的曲线下面积(AUC)为 0.769(敏感度 90.6%,特异度 51.4%)。K 相关的显著特征区分胸腺癌和胸腺瘤的 AUC 为 0.780(敏感度 87.5%,特异度 62.2%)。V 相关的显著特征区分胸腺癌和胸腺瘤的 AUC 为 0.807(敏感度 75.0%,特异度 78.4%)。DCE-MRI 纹理特征联合的 AUC 为 0.962(敏感度 93.8%,特异度 89.2%)。筛选出 5 个参数,包括年龄、K 熵、K 熵、V 熵和 V-P95。这 5 个参数的组合具有最佳的鉴别效率(AUC 为 0.943,敏感度 93.7%,特异度 81.1%)。
DCE-MRI 纹理分析有助于鉴别胸腺癌和胸腺瘤。