摘要
目的探讨高分辨率CT定量参数在预测肺单纯性磨玻璃样结节(pGGNs)侵袭性的临床价值。方法对手术病理确诊148例患者的163个pGGNs病灶的术前CT定量参数进行回顾性分析,包括结节最大直径、最大垂直长径、最大横截面积、结节体积、质量和平均CT值等。根据手术病理类型对pGGNs病灶进行分组,包括非典型性腺瘤样增生(AAH)、原位腺癌(AIS)]和微小侵袭性腺癌(MIA)三种在内的非侵袭性癌组,以及侵袭性腺癌(IAC)单独分组,比较两组结节的CT定量参数的差异,并以受试者工作特征曲线(ROC)和logistics回归模型评估CT定量参数对pGGNs病灶侵袭程度的预测价值。结果非侵袭性癌结节的结节最大直径、最大垂直长径、最大横截面积、结节体积、质量和平均CT值等均显著低于侵袭性癌结节组(P<0.05)。CT定量参数的预测价值从高到低分别为最大横截面积(AUC=0.846)、结节质量(A U C=0. 8 3 4)、结节体积(AUC=0.811)、最大直径(AUC=0.803)、最大垂直长径(AUC=0.799)和平均CT值(AUC=0.685),均存在统计学意义(P<0.05)。logistics回归分析显示最大横截面积(OR=2.307,95%CI:1.689-3.150,P<0.001)是预测pGGNs侵袭性的独立预测因子,其预测阈值为2.224cm2。结论术前CT定量参数能够有效预测肺pGGNs的侵袭性,pGGNs的最大横截面积的预测价值最高。
Objective To investigate the predictive value of high-resolution CT quantitative parameters for the invasion of pure ground-glass nodules(pGGNs).Methods Preoperative CT quantitative parameters of 163 pGGNs lesions diagnosed by pathology in 148 patients were retrospectively analyzed,including maximum diameter,maximum vertical diameter,maximum cross-sectional area,volume,mass and mean CT value.According to the pathological classification,pGGNs were classified into two groups,the non-invasive group[including atypical adenomatous hyperplasia(AAH),adenocarcinoma in situ(AIS)and minimally invasive adenocarcinoma(MIA)],and the invasive group[only invasive adenocarcinoma(IAC)].The difference in CT quantitative parameters between the two groups of nodules was compared,the receiver operating characteristic(ROC)curve and logistic regression models were used to evaluate the predictive value of CT quantitative parameters on the degree of invasion of pGGNs.Results The maximum diameter,maximum vertical diameter,maximum cross-sectional area,volume,mass and average CT value of non-invasive group were significantly lower than those of invasive group(P<0.05).The predictive value of CT quantitative parameters from high to low were the maximum cross-sectional area(AUC=0.846),mass(AUC=0.834),volume(AUC=0.811),maximum diameter(AUC=0.803),maximum vertical diameter(AUC=0.799)and mean CT value(AUC=0.685),allwiththe statistical significance(P<0.05).The logistic regression analysis showed that the maximum cross-sectional area(OR=2.307,95%CI:1.689-3.150,P<0.001)was the only independent predictor of the invasiveness of pGGNs with a predictive threshold of 2.224 cm2.Conclusion Preoperative CT quantitative parameters can effectively predict the invasion of lung pGGNs,and the maximum cross-sectional area of pGGNs has the highest predictive value.
作者
郑旻
黄先敏
ZHENG Min;HUANG Xian-min(Department of Radiology,Fuding Hospital,Fuding 355200,Fujian Province,China)
出处
《中国CT和MRI杂志》
2019年第8期61-64,共4页
Chinese Journal of CT and MRI
