Gu Jiamei, Ren Yunyan, Chen Xiaohui, Jiang Yanping, Zhou Wenlan, Wang Lijuan, Han Yanjiang, Wang Qiaoyu, Wu Hubing
PET Center, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.
Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.
Nan Fang Yi Ke Da Xue Xue Bao. 2020 Jan 30;40(1):49-55. doi: 10.12122/j.issn.1673-4254.2020.01.08.
To investigate F-FDG PET/CT manifestations of massive type active tuberculosis and lung cancer and the differential diagnosis of the two diseases based on F-FDG PET/CT findings.
We retrospectively collected the data from 74 patients with active tuberculosis and 64 patients with lung cancer, whose lesions presented as solid masses on CT. The demographic and clinical data of the patients, F-FDG PET characteristics including SUVmax, F-FDG uptake (higher than mediastinal blood pool or not), radioactive defect within the lesion, and the CT findings including the lesion size, signs of cavity, vacuoles, lobulation, smooth border, and mediastinal/lung window ratio (M/L ratio) of the lesions were analyzed. Univariate and multivariate analyses were used to compare the variables between the two groups, and a logistic regression model was established for differentiation of the two diseases. The diagnostic efficiency was evaluated by area under the receiver-operating characteristic (ROC) curve analysis.
No significant differences were found in the quantitative index (SUV >2.5 or not) or in the qualitative index (uptake of lesion higher than mediastinal blood pool or not) in PET between massive type active tuberculosis and lung cancer (>0.05). Univariate analysis revealed that SUV, F-FDG uptake of the lesion, age, lesion size, signs of cavity, or M/L ratio were not significantly different (>0.05), but gender, signs of radioactive defect, vacuoles, smooth border and lobulation were significantly different ( < 0.05) between the two diseases. Multivariate analysis showed that gender, signs of radioactive defect, smooth border and lobulation of the lesion were independent factors for discrimination of the two diseases ( < 0.05). A risk prediction model for active tuberculosis was established based on logistic regression analysis: =1/(1+e-x), X=-0.530+1.978×gender+3.343×radioactive defect +2.846×smooth border-2.116×lobulation. For diagnosis of active tuberculosis, the sensitivity, specificity, accuracy, positive predictive value and negative predictive value of this model were 78.4%, 92.2%, 84.8%, 92.1%, and 78.7%, respectively.
The combined analysis of gender, signs of radioactive defect, smooth border and lobulation of the lesions is useful for discriminating massive type active tuberculosis from lung cancer in the majority of the patients, whereas F-FDG uptake alone has only limited value for a differential diagnosis.
探讨F-FDG PET/CT在大块型活动性肺结核与肺癌中的表现，以及基于F-FDG PET/CT表现对这两种疾病进行鉴别诊断。
回顾性收集74例活动性肺结核患者和64例肺癌患者的数据，这些患者的病变在CT上均表现为实性肿块。分析患者的人口统计学和临床数据、F-FDG PET特征（包括SUVmax、F-FDG摄取情况（是否高于纵隔血池）、病变内放射性缺损）以及CT表现（包括病变大小、空洞征象、空泡、分叶、边界光滑情况以及病变的纵隔/肺窗比值（M/L比值））。采用单因素和多因素分析比较两组之间的变量，并建立逻辑回归模型以鉴别这两种疾病。通过受试者操作特征（ROC）曲线下面积分析评估诊断效能。
大块型活动性肺结核与肺癌在PET中的定量指标（SUV是否>2.5）或定性指标（病变摄取是否高于纵隔血池）方面无显著差异（>0.05）。单因素分析显示，SUV、病变的F-FDG摄取、年龄、病变大小、空洞征象或M/L比值在两种疾病之间无显著差异（>0.05），但性别、放射性缺损征象、空泡、边界光滑情况和分叶在两种疾病之间有显著差异（<0.05）。多因素分析表明，性别、病变的放射性缺损征象、边界光滑情况和分叶是鉴别这两种疾病的独立因素（<0.05）。基于逻辑回归分析建立了活动性肺结核的风险预测模型：=1/(1+e-x)，X=-0.530+1.978×性别+3.343×放射性缺损+2.846×边界光滑情况-2.116×分叶。对于活动性肺结核的诊断，该模型的敏感性、特异性、准确性、阳性预测值和阴性预测值分别为78.4%、92.2%、84.8%、92.1%和78.7%。
综合分析病变的性别、放射性缺损征象、边界光滑情况和分叶，有助于在大多数患者中鉴别大块型活动性肺结核与肺癌，而单独的F-FDG摄取对鉴别诊断的价值有限。
