能谱CT鉴别诊断孤立性肺结节或肿块的价值

Application of spectral CT in differential diagnosis of solitary pulmonary nodules or masses

目的:探讨能谱CT成像定量分析在鉴别诊断肺癌、肺炎性肿块和肺结核中的价值。方法:收集经能谱CT增强扫描的78例肺结节或肿块患者,其中肺癌组38例、肺结核组20例、肺炎肿块组20例,测量动、静脉期病灶的单能量CT值、碘浓度(IC)、能谱曲线斜率(λ_(HU))、标准化碘浓度(NIC)及标准化水浓度(NWC)。对3组间上述参数进行单因素方差分析或秩和检验,并进行ROC曲线分析。结果:3组病变动、静脉期单能量CT值、IC、NIC及λ_(HU)差异均有统计学意义(P<0.05)。两两比较肺炎组和结核组、肺癌组和结核组间差异有统计意义(P<0.05),而肺炎组和肺癌组间差异无统计学意义(P>0.05)。静脉期NIC>0.325及NIC>0.298时鉴别肺炎性肿块与肺结核、肺癌与肺结核的灵敏度分别为95.0%、97.4%,特异度分别为85.0%、75.0%。结论:运用宝石CT能谱成像的多参数定量分析可以鉴别肺癌和肺结核、肺炎性肿块和肺结核,但对肺炎性肿块与肺癌的鉴别诊断价值需进一步研究证实。

Objective： To explore the value of spectral CT in differential diagnosis of lung cancer, inflammatory lesions and tuberculosis. Methods： A total of 78 patients with pulmonary nodules or masses were checked by spectral CT. All patients were divided into lung cancer group（38 cases）, pulmonary tuberculosis（20 cases） and inflammatory lesions group（20 cases）. The monochromatic CT value, iodine concentration（IC）, and slope of spectral attenuation curves, normalized iodine concentration（NIC） and normalized water concentration were measured. The one-way ANOVA and Kruskal-Wallis H test were used to analyze parameters among 3 groups. ROC curves were taken to determine the threshold value of the differential diagnosis. Results： The monochromatic CT value, IC, NIC and slope rate of spectral curve among the three groups had statistically significant differences in both phases（all P〈0.05）. Pairwise comparison between lung cancer and pulmonary tuberculosis, inflammatory lesions and pulmonary tuberculosis were statistically significant（P〈0.05）, but there was no statistically significant difference between lung cancer and inflammatory lesions（P〉0.05）. When NIC（venous phase）〉0.325 and NIC〉0.298, the sensitivity of diagnosing inflammatory lesions and pulmonary tuberculosis, lung cancer and tuberculosis were respectively 95.0%, 97.4%, and the specificity of them were 85.0%, 75.0% respectively. Conclusion： The quantitative analysis of multiple parameters using spectral CT imaging has great value in the differentiation of lung cancer and pulmonary tuberculosis, and pneumonia and pulmonary tuberculosis, but it can’t be used to differentiate lung cancer and pneumonia.