能谱CT诊断非小细胞肺癌纵隔淋巴结转移的应用价值

目的: 探讨能谱CT (dual energy CT, DECT) 诊断非小细胞肺癌 (non-small cell lung cancer, NSCLC) 纵隔淋巴结转移的应用价值。方法: 选择2018年4月至2019年10月在北京大学第三医院接受胸部DECT检查且经术后病理诊断证实的NSCLC患者病例资料进行回顾性分析,共收集到病例57 例,两名放射科医师共同分析患者术前CT图像,将轴位图像上所有短径 (short-axis diameter, S)≥5 mm的纵隔淋巴结纳入本研究。测量淋巴结形态学参数长径(long-axis diameter, L)、S、短径与长径比值(ratio of short-axis diameter to long-axis diameter, S/L)以及能谱参数动脉期及静脉期碘浓度 (iodine concentration, IC)、标准化碘浓度 (normalized iodine concentration, NIC)、能谱曲线斜率及有效原子序数。比较转移与非转移淋巴结形态学指标及其能谱参数的差异,将有统计学差异的参数纳入Logistic回归方程筛选出有诊断价值的参数,并生成诊断淋巴结转移的联合变量,对淋巴结S、静脉期NIC及联合变量进行受试者工作特征 (receiver operating characteristic, ROC)曲线分析。结果: 57例患者中,术后病理诊断证实转移淋巴结49 枚,非转移淋巴结938 枚。CT轴位上共检出S≥5 mm纵隔淋巴结163 枚 (转移淋巴结49 枚,非转移淋巴结114 枚)。转移淋巴结的S、L及S/L均显著大于非转移淋巴结 (P<0.05), 转移淋巴结的能谱参数均显著低于非转移性淋巴结 (P<0.05)。S是诊断淋巴结转移的最佳单一形态学指标,ROC曲线下面积 (area under curve, AUC) 为0.752,阈值8.5 mm,灵敏度67.4%,特异度73.7%,准确率71.8%。静脉期NIC为最佳单一能谱参数,AUC为0.861,阈值0.53,灵敏度95.9%,特异度70.2%,准确率77.9%。多因素分析显示S、静脉期NIC是转移淋巴结的独立预测因子。联合S、静脉期NIC诊断淋巴结转移的AUC为0.895,灵敏度 79.6%,特异度 87.7%,准确率85.3%,明显高于S (P<0.001)、静脉期NIC (P=0.037)。结论: DECT定量参数鉴别NSCLC患者纵隔淋巴结转移的价值优于形态学参数,联合S和静脉期NIC可提高术前诊断淋巴结转移的准确率。

Comparative imaging study of mediastinal lymph node from pre-surgery dual energy CT versus post-surgeron verifications in non-small cell lung cancer patients

Objective: To validate the value of dual energy CT (DECT) in the differentiation of mediastinal metastatic lymph nodes from non-metastatic lymph nodes in non-small cell lung cancer (NSCLC). Methods: In the study, 57 surgically confirmed NSCLC patients who underwent enhanced DECT scan within 2 weeks before operation were enrolled. Two radiologists analyzed the CT images before operation. All mediastinal lymph nodes with short diameter≥5 mm on axial images were included in this study. The morphological parameters [long-axis diameter (L), short-axis diameter (S) and S/L of lymph nodes] and the DECT parameters [iodine concentration (IC), normalized iodine concentration (NIC), slope of spectral hounsfield unit curve (λHU) and effective atomic number (Zeff) in arterial and venous phase] were measured. The differences of morphological parameters and DECT parameters between metastatic and non-metastatic lymph nodes were compared. The parameters with significant difference were analyzed by the Logistic regression model, then a new predictive variable was established. Receiver operator characteristic (ROC) analyses were performed for S, NIC in venous phase and the new predictive variable. Results: In 57 patients, 49 metastatic lymph nodes and 938 non-metastatic lymph nodes were confirmed by surgical pathology. A total of 163 mediastinal lymph nodes (49 metastatic, 114 non-metastatic) with S≥5 mm were detected on axial CT images. The S, L and S/L of metastatic lymph nodes were significantly higher than those of non-metastatic lymph nodes (P<0.05). The DECT parameters of metastatic lymph nodes were significantly lower than those of non-metastatic lymph nodes (P<0.05). The best single morphological parameter for differentiation between metastatic and nonmetastatic lymph nodes was S (AUC, 0.752; threshold, 8.5 mm; sensitivity, 67.4%; specificity, 73.7%; accuracy, 71.8%). The best single DECT parameter for differentiation between metastatic and nonmetastatic lymph nodes was NIC in venous phase (AUC, 0.861; threshold, 0.53; sensitivity, 95.9%; specificity, 70.2%; accuracy, 77.9%). Multivariate analysis showed that S and NIC were independent predictors of lymph node metastasis. The AUC of combined S and NIC in the venous phase was 0.895(sensitivity, 79.6%; specificity, 87.7%; accuracy, 85.3%), which were significantly higher than that of S (P<0.001) and NIC (P=0.037). Conclusion: The ability of quantitative DECT parameters to distinguish mediastinal lymph node metastasis in NSCLC patients is better than that of morphological parameters. Combined S and NIC in venous phase can be used to improve preoperative diagnostic accuracy of metastatic lymph nodes.