CT定量和定性特征联合预测肺磨玻璃结节浸润程度555例的回顾性队列研究

Invasiveness assessment by CT quantitative and qualitative features of lung cancers manifesting ground-glass nodules in 555 patients:A retrospective cohort study

目的探讨CT影像学定量和定性特征和肺磨玻璃结节浸润程度的相关性,为磨玻璃结节患者术前规划提供参考价值。方法纳入2020年9月—2022年7月期间在昆明医科大学第三附属医院行手术治疗术后确诊为肺腺癌的磨玻璃结节患者的临床资料。根据病理诊断结果将其分为两组,非浸润腺癌组(包括原位腺癌和微浸润腺癌)和浸润性腺癌组。收集其影像学特征,并进行单因素logistic回归分析,将差异有统计学意义的指标纳入多因素logistic回归分析,最终确定浸润性腺癌发生风险的独立预测因素,建立预测模型。根据约登指数计算出灵敏度和特异度。使用曲线下面积(area under the curve,AUC)值、校准曲线和决策分析曲线评价模型的区分度、校准度和临床实用价值。结果555例纳入研究。非浸润腺癌组310例,其中女235例、男75例,年龄49(43,58)岁;浸润性腺癌组245例,其中女163例、男82例,年龄53(46,61)岁。二元logistic回归分析显示,肿瘤最大径[OR=4.707,95%CI(2.060,10.758)]、实性成分占比(consolidation tumor ratio,CTR)[OR=1.027,95%CI(1.011,1.043)]、最大CT值[OR=1.025,95%CI(1.004,1.047)]、平均CT值[OR=1.035,95%CI(1.008,1.063)]、毛刺征[OR=2.055,95%CI(1.148,3.679)]、血管集束征[OR=2.508,95%CI(1.345,4.676)]是浸润性腺癌发生的独立危险因素(P<0.05)。基于上述独立预测因素构建浸润性腺癌发病风险的预测模型。模型预测公式为Logit(P)=–1.293+1.549×肿瘤最大径+0.026×CTR+0.025×最大CT值+0.034×平均CT值+0.72×毛刺征+0.919×血管集束征。模型AUC值为0.910[95%CI(0.885,0.934)],说明模型预测浸润性腺癌具有良好的区分度,校准曲线显示预测模型具有良好的校准度,决策分析曲线显示模型具有良好的临床实用性。结论联合CT定量和定性特征的预测模型对磨玻璃结节侵袭性具有良好的预测能力。其预测效能高于任意单一指标。

Objective To explore the correlation between the quantitative and qualitative features of CT images and the invasiveness of pulmonary ground-glass nodules,providing reference value for preoperative planning of patients with ground-glass nodules.Methods The patients with ground-glass nodules who underwent surgical treatment and were diagnosed with pulmonary adenocarcinoma from September 2020 to July 2022 at the Third Affiliated Hospital of Kunming Medical University were collected.Based on the pathological diagnosis results,they were divided into two groups:a non-invasive adenocarcinoma group with in situ and minimally invasive adenocarcinoma,and an invasive adenocarcinoma group.Imaging features were collected,and a univariate logistic regression analysis was conducted on the clinical and imaging data of the patients.Variables with statistical difference were selected for multivariate logistic regression analysis to establish a predictive model of invasive adenocarcinoma based on independent risk factors.Finally,the sensitivity and specificity were calculated based on the Youden index.Results A total of 555 patients were collected.The were 310 patients in the non-invasive adenocarcinoma group,including 235 females and 75 males,with a meadian age of 49(43,58)years,and 245 patients in the invasive adenocarcinoma group,including 163 females and 82 males,with a meadian age of 53(46,61)years.The binary logistic regression analysis showed that the maximum diameter(OR=4.707,95%CI 2.060 to 10.758),consolidation/tumor ratio(CTR,OR=1.027,95%CI 1.011 to 1.043),maximum CT value(OR=1.025,95%CI 1.004 to 1.047),mean CT value(OR=1.035,95%CI 1.008 to 1.063),spiculation sign(OR=2.055,95%CI 1.148 to 3.679),and vascular convergence sign(OR=2.508,95%CI 1.345 to 4.676)were independent risk factors for the occurrence of invasive adenocarcinoma(P<0.05).Based on the independent predictive factors,a predictive model of invasive adenocarcinoma was constructed.The formula for the model prediction was:Logit(P)=–1.293+1.549×maximum diameter of lesion+0.026×CTR+0.025×maximum CT value+0.034×mean CT value+0.72×spiculation sign+0.919×vascular convergence sign.The area under the receiver operating characteristic curve of the model was 0.910(95%CI 0.885 to 0.934),indicating that the model had good discrimination ability.The calibration curve showed that the predictive model had good calibration,and the decision analysis curve showed that the model had good clinical utility.Conclusion The predictive model combining quantitative and qualitative features of CT has a good predictive ability for the invasiveness of ground-glass nodules.Its predictive performance is higher than any single indicator.