Yu Yixing, Wang Ximing, Shi Cen, Hu Su, Zhu Hui, Hu Chunhong
From the Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.
J Comput Assist Tomogr. 2019 Mar/Apr;43(2):338-344. doi: 10.1097/RCT.0000000000000840.
The aim of this study was to explore the value of spectral computed tomography (CT) imaging in differentiating lung cancer from inflammatory myofibroblastic tumor (IMT).
One hundred twelve patients with 96 lung cancers and 16 IMTs underwent spectral CT during arterial phase (AP) and venous phase (VP). The normalized iodine concentration in AP (NICAP) and VP (NICVP), slope of spectral Hounsfield unit curve in AP (λAP) and VP (λVP), and normalized iodine concentration difference between AP and VP (ICD) were calculated. The 2-sample t test compared quantitative parameters. Two readers qualitatively assessed lesion types according to imaging features. Receiver operating characteristic curves were generated to calculate sensitivity and specificity. Sensitivity and specificity of the qualitative and quantitative studies were compared.
The patients with IMT had significantly higher NICAP, NICVP, λAP, λVP, and ICD than did the patients with lung cancer (P < 0.05). The threshold NICVP of 0.425 would yield the highest sensitivity and specificity of 92.7% and 81.3%, respectively, for differentiating lung cancer from IMT. The logistic regression model produced from combining quantitative parameters NICAP, NICVP, λAP, and λVP provided a sensitivity and specificity of 100% and 81.3%, respectively, for differentiating lung cancer from IMT.
Spectral CT imaging with the quantitative analysis may help to increase the accuracy of differentiating lung cancer from IMT.
本研究旨在探讨光谱计算机断层扫描（CT）成像在鉴别肺癌与炎性肌纤维母细胞瘤（IMT）中的价值。
112例患者，其中96例为肺癌，16例为IMT，在动脉期（AP）和静脉期（VP）接受光谱CT检查。计算AP期（NICAP）和VP期（NICVP）的归一化碘浓度、AP期（λAP）和VP期（λVP）的光谱亨氏单位曲线斜率以及AP期和VP期之间的归一化碘浓度差（ICD）。采用两样本t检验比较定量参数。两名阅片者根据影像特征对病变类型进行定性评估。绘制受试者操作特征曲线以计算敏感性和特异性。比较定性和定量研究的敏感性和特异性。
IMT患者的NICAP、NICVP、λAP、λVP和ICD显著高于肺癌患者（P<0.05）。区分肺癌与IMT时，NICVP阈值为0.425时敏感性和特异性最高，分别为92.7%和81.3%。结合定量参数NICAP、NICVP、λAP和λVP建立的逻辑回归模型区分肺癌与IMT的敏感性和特异性分别为100%和81.3%。
光谱CT成像结合定量分析可能有助于提高鉴别肺癌与IMT的准确性。
