Wang R, Li J, Fang M J, Dong D, Liang P, Gao J B
Department of Radiology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China.
Department of Radiology, Affiliated Tumor Hospital of Zhengzhou University, Zhengzhou 450008, China.
Zhonghua Yi Xue Za Zhi. 2020 Jun 2;100(21):1617-1622. doi: 10.3760/cma.j.cn112137-20191113-02468.
To investigate the spectral CT-based radiomics in predicting preoperatively the lymph node metastasis (LNM) of advanced gastric cancer. From January 2014 to October 2018, the spectral CT imaging and clinical data of 196 gastric adenocarcinoma patients confirmed by pathology in the First Affiliated Hospital of Zhengzhou University were retrospectively enrolled (training set and test set were randomly divided according to the ratio of 1∶1). These 196 patients include143 males and 53 females, aged from 28 to 81 years, with an average age of (59±11) years, and were divided into nodular metastasis group and non-metastasis group according to clinicopathological data. The spectral parameters were measured and calculated, and the CT-reported lymph node (LN) status from CT images were obtained. 273 radiomics features were extracted from the dual-phases CT images in different energy level (40, 65 and 100 keV) to build the radiomics signature respectively. Univariate analysis was used to compare the differences of spectral parameters and radiomics features between two groups, and then the significant indicators were put into multivariable logistic regression analysis to construct combined prediction model and radiomics nomogram. In addition, the performance of prediction model in training and test set were measured using the receiver operating characteristics (ROC) curves and were compared using DeLong test. Both in training set and in test set, the iodine concentration (IC) of tumor in venous phase (VP) in nodular metastasis group were higher than that in non-metastasis group [training set: 22.98 (100 mg/L)>20.31 (100 mg/L), 0.086; test set: 25.14 (100 mg/L)>21.07 (100 mg/L), 0.009]. The CT-reported LN status showed significant differences between the two group (0.001, 0.001). The radiomics signatures 40 keV-arterial phase, 65 keV-venous phase, IC-VP of tumor and CT-reported LN status were independent indicators for prediction of preoperative LNM of advanced gastric cancer in combined prediction model (0.05). The radiomics nomogram predicated LNM with an area under curve (AUC) and 95% confidence interval () of 0.822 (0.739-0.906) in training set and 0.819(0.732-0.906) in test set, and there were no significant differences in AUC between two sets (0.05). The spectral CT-based radiomics can be used to quantitatively predict the LNM of advanced gastric cancer preoperatively.
探讨基于光谱CT的影像组学在术前预测进展期胃癌淋巴结转移（LNM）中的应用价值。回顾性纳入2014年1月至2018年10月在郑州大学第一附属医院经病理确诊的196例胃腺癌患者的光谱CT影像及临床资料（按1∶1随机分为训练集和测试集）。这196例患者中，男性143例，女性53例，年龄28～81岁，平均年龄（59±11）岁，根据临床病理资料分为结节转移组和无转移组。测量并计算光谱参数，获取CT图像上CT报告的淋巴结（LN）状态。从不同能量水平（40、65和100 keV）的双期CT图像中提取273个影像组学特征，分别构建影像组学特征模型。采用单因素分析比较两组光谱参数和影像组学特征的差异，将有统计学意义的指标纳入多因素logistic回归分析，构建联合预测模型和影像组学列线图。此外，采用受试者操作特征（ROC）曲线评估训练集和测试集中预测模型的性能，并采用DeLong检验进行比较。在训练集和测试集中，结节转移组肿瘤静脉期（VP）的碘浓度（IC）均高于无转移组[训练集：22.98（100 mg/L）＞20.31（100 mg/L），P = 0.086；测试集：25.14（100 mg/L）＞21.07（100 mg/L），P = 0.009]。两组CT报告的LN状态差异有统计学意义（P = 0.001，P = 0.001）。联合预测模型中，40 keV动脉期、65 keV静脉期、肿瘤IC-VP及CT报告的LN状态是预测进展期胃癌术前LNM的独立指标（P＜0.05）。影像组学列线图在训练集和测试集中预测LNM的曲线下面积（AUC）及95%置信区间分别为0.822（0.739～0.906）和0.819（0.732～0.906），两组AUC差异无统计学意义（P＞0.05）。基于光谱CT的影像组学可用于术前定量预测进展期胃癌的LNM。
