目的 对比分析CT平扫和动态增 强CT检查孤立性肺结节的临床价值。方 法 根据良、恶性将60例经病理证实为SPN 的患者分为两组，采用西门子16层全身 螺旋CT扫描机对患者行平扫﹢动态增强后 不同时间点扫描，比较各组多期的动态 增强参数，CT征象，用ROC曲线分析其诊 断恶性SPN的敏感性和特异性。结果 而 良、恶性肺结节在动态增强后120s的CT 值、20min廓清值和廓清率和廓清线性斜 率分均存在统计学差异(P<0.05)，而2、3 型TDC中良、恶性SPN的差异存统计学意义 (P<0.01),而余下各型TDC比较均无统计学 意义(P>0.05)。ROC曲线下的面积(AUC） 为0.796，其敏感性为61.7%，特异性为 86.5%；运用CT征象诊断恶性SPN，则ROC 曲线下的AUC为0.964(P<0.01)，其敏感性 为98.9%，特异性为88.7%；动态增强参 数联合CT征象诊断SPN性质时，ROC曲线 下的AUC为0.975(P<0.01)，其敏感性为 99.3%，特异性为90.5%。结论 与CT平扫 相比，动态增强CT扫描可同时观察SPN的 形态学特征和强化指标，联合运用动态增 强参数和形态学特征，可有效提高恶性 SPN的诊断效率。

Objective To comparative analysis of CT scan and dynamic enhanced CT examination isolation, the clinical value of pulmonary nodules. Methods According to the benign and malignant of nodules, sixty patients confirmed by pathology of SPN patients were divided into two groups, using Siemens 16 layers spiral CT scanner body for patients with dynamic enhanced scan different times, comparison between groups of multiphase dynamic enhanced parameters, CT signs, and the results are statistically analyzed, using ROC curve analysis of the the sensitivity and specificity in the diagnosis of malignant SPN. Results There was a significant difference in the CT value, the clearance value at 20min, the clearance rate and the linear slope at the 120s after the dynamic enhancement of benign and malignant pulmonary nodules. The difference between benign and malignant SPN in type 2 and type 3 TDC was statistically significant. The remaining types of TDC were not statistically significant. The area under the ROC curve (AUC) was 0.796 with a sensitivity of 61.7% and a specificity of 86.5%. AUC of ROC curve was 0.964 (P<0.01), and the sensitivity and specificity were 98.9% and 88.7%, respectively. The CT value of AUC Was 0.975 (P<0.01), with a sensitivity of 99.3% and a specificity of 90.5%. Conclusion Compared with CT scan, dynamic contrast-enhanced CT scan can simultaneously observe the morphological features and enhancement indexes of SPN, and the combination of dynamic enhancement parameters and morphological features can effectively improve the diagnostic efficiency of SPN.