Cheng Nianlan, Wu Shuo, Luo Xianli, Xu Chunyan, Lou Qin, Zhu Jin, You Lu, Li Bangguo
Department of Radiology, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou Province, People's Republic of China.
Infect Drug Resist. 2021 Mar 18;14:1115-1128. doi: 10.2147/IDR.S300754. eCollection 2021.
To investigate the CT features of drug-resistant pulmonary tuberculosis (DR-PTB) and the diagnostic value of CT in DR-PTB diagnosis to provide imaging evidence for the timely detection of drug-resistant .
A total of 1546 cases of pulmonary tuberculosis (PTB) with complete clinical data, chest CT images and defined drug sensitivity testing results were consecutively enrolled; 516 cases of DR-PTB were included in the drug-resistant group, and 1030 cases of drug-sensitive pulmonary tuberculosis (DS-PTB) were included in the drug-sensitivity group. Comparative analyses of clinical symptoms and imaging findings were conducted. Univariate and logistic regression analyses were performed, a regression equation model was developed, and the receiver operating characteristic (ROC) curve was constructed.
In the univariate analysis, some features, including whole-lung involvement, multiple cavities, thick-walled cavities, collapsed lung, disseminated lesions along the bronchi, bronchiectasis, emphysema, atelectasis, calcification, proliferative lesions, encapsulated effusion, etc., were observed more frequently in the DR-PTB group than in the DS-PTB group, and the differences were statistically significant (0.05). Exudative lesions and pneumoconiosis were observed more frequently in the drug-sensitivity group than in the drug-resistant group (0.05). Logistic regression analysis indicated that whole-lung involvement, multiple cavities, thick-walled cavities, disseminated lesions along the bronchi, bronchiectasis, and emphysema were independent risk factors for DR-PTB, and exudative diseases were protective factors. The total prediction accuracy of the regression model was 80.6%, and the area under the ROC curve (AUC) was 82.6%.
Chest CT manifestations of DR-PTB had certain characteristics that significantly indicated the possibility of drug resistance in tuberculosis patients, specifically when multifarious imaging findings, including multiple cavities, thick-walled cavities, disseminated lesions along the bronchi, whole-lung involvement, etc., coexisted simultaneously. These results may provide imaging evidence for timely drug resistance detection in suspected drug-resistant cases and contribute to the early diagnosis of DR-PTB.
探讨耐多药肺结核（DR-PTB）的CT特征及CT在DR-PTB诊断中的价值，为及时发现耐药情况提供影像学依据。
连续纳入1546例具有完整临床资料、胸部CT图像及明确药敏试验结果的肺结核（PTB）患者；耐药组纳入516例DR-PTB患者，药敏组纳入1030例药物敏感肺结核（DS-PTB）患者。对临床症状和影像学表现进行对比分析。进行单因素和逻辑回归分析，建立回归方程模型，并构建受试者操作特征（ROC）曲线。
单因素分析显示，全肺受累、多发空洞、厚壁空洞、肺不张、沿支气管播散性病变、支气管扩张、肺气肿、肺不张、钙化、增殖性病变、包裹性积液等特征在DR-PTB组中比DS-PTB组更常见，差异有统计学意义（P<0.05）。渗出性病变和尘肺病在药敏组中比耐药组更常见（P<0.05）。逻辑回归分析表明，全肺受累、多发空洞、厚壁空洞、沿支气管播散性病变、支气管扩张和肺气肿是DR-PTB的独立危险因素，渗出性疾病是保护因素。回归模型的总预测准确率为80.6%，ROC曲线下面积（AUC）为82.6%。
DR-PTB的胸部CT表现具有一定特征，显著提示肺结核患者耐药的可能性，特别是当多种影像学表现如多发空洞、厚壁空洞、沿支气管播散性病变、全肺受累等同时存在时。这些结果可为疑似耐药病例的及时耐药检测提供影像学依据，有助于DR-PTB的早期诊断。
