PET/CT及其数学预测模型对孤立性肺结节诊断价值的对比研究  

The comparative study of ^(18)F-FDG PET/CT and mathematical prediction model in diagnosis of solitary pulmonary nodule

作　　者：林洁[1] 唐坤[1] 殷薇薇[1] 郑祥武[1] 陈杨宗[1] 林信实 戴云飞[1] 

机构地区：[1]温州医科大学附属第一医院放射影像中心PET/CT室,浙江温州325015

出　　处：《温州医学院学报》2015年第5期354-358,共5页Journal of Wenzhou Medical College

摘　　要：目的:通过受试者工作特征曲线(ROC曲线)分析比较PET/CT及其数学预测模型对孤立性肺结节(SPN)的诊断价值。方法:对186例行PET/CT检查的SPN患者进行回顾性分析。PET/CT图像分析采用目视法或半定量法对结节的代谢及CT形态学特征进行综合分析判断,判断结果分为良性、良性可能大、良性可能、恶性可能、恶性可能大、恶性,并依次以0、1、2、3、4、5分进行记录。以病灶良恶性结果为应变量,对影响病灶结果的参数进行单因素和多因素分析,建立诊断SPN良、恶性的回归数学模型。分别计算PET/CT及数学预测模型诊断SPN的灵敏度、特异度、准确度、阳性预测值、阴性预测值,绘制相应ROC曲线并比较两者曲线下面积大小的差异性。结果:PET/CT诊断SPN的灵敏度、特异度、准确度、阳性预测值及阴性预测值分别为97.6%、79.4%、91.4%、90.2%及94.3%。经二元logistic回归分析建立18F-FDG PET/CT诊断SPN良、恶性的数学模型如下:p=ex/(1+ex),x=-8.111+0.091×年龄+1.351×分叶+3.565×血管集束+2.153×胸膜牵拉+0.447×SUVmax。以数学模型对SPN良恶性进行预测,其诊断SPN的灵敏度、特异度、准确度、阳性预测值及阴性预测值分别为87.8%、81.0%、85.5%、90.0%及77.3%。PET/CT及数学预测模型诊断SPN的ROC曲线下面积分别为0.951±0.015及0.927±0.019,两者间差异无统计学意义(P>0.05)。结论:数学模型作为一种实验医学其诊断SPN的效能与PET/CT相仿,且不受人为因素干扰,其优势与PET/CT互补,因此可以联合运用、相互佐证,以提高SPN诊断的准确率。Objective： To compare and analyze the value of 18F-FDG PET/CT and the mathematical prediction model in diagnosis of solitary pulmonary nodule（SPN）, using receiver operating characteristic（ROC） curves analysis. Methods： All of 186 patients confirmed with SPN and performed with PET/CT were retrospectively analyzed in this study. For PET/CT integrated images, the morphology and metabolism of lesions were semiquantitatively or visual analysed by observers. A 5-score system was used to classify the diagnostic results of PET/CT integrated images： 0, definitely benign; 1, benign more likely; 2, probably benign; 3, probably malignant; 4, malignant more likely; and 5, definitely malignant. The logistic mathematical model was established with univariate analysis and multivariate analysis. The sensitivity, specificity, accuracy, positive predictive value and negative predictive value of PET/CT and the mathematical model in diagnosis of SPN were calculated respectively. The difference of the areas under the ROC curves（AUC） between PET/CT and the mathematical model was compared. Results： The sensitivity, specificity, accuracy, positive predictive value and negative predictive value of PET/CT were 97.6%, 79.4%, 91.4%, 90.2% and 94.3%, respectively. The mathematical model established by logistic regression analysis was： p=ex/（1＋ex）, x=-8.111＋0.091×age＋1.351×lobulation＋3.565×vascular convergence＋2.153×retraction of pleural＋0.447×SUVmax. The sensitivity, specificity, accuracy, positive predictive value and negative predictive value of the model for prediction of SPN were 87.8%, 81.0%, 85.5%, 90.0% and 77.3% respectively. The AUCs of PET/CT and mathematical model were 0.951±0.015 and 0.927±0.019. There was no statistically significant in difference of AUC between PET/CT and mathematical model（P0.05）. Conclusion： The value of mathematical prediction model in diagnosis of SPN is similar to PET/CT and not affected by subjective factors. Therefore, it should be used in clinical practi

关 键 词：孤立性肺结节 体层摄影术 X线计算机 脱氧葡萄糖 体层摄影术 发射型计算机 二元LOGISTIC回归 

分 类 号：R81[医药卫生—放射医学]