[1]郑秋婷,郭琳,夏丽,等.基于CT的空洞特征在耐药肺结核的影像诊断价值[J].中国医学物理学杂志,2024,41(4):413-420.[doi:DOI:10.3969/j.issn.1005-202X.2024.04.003]
　ZHENG Qiuting,GUO Lin,XIA Li,et al.Diagnostic value of CT cavity features in drug-resistant pulmonary tuberculosis[J].Chinese Journal of Medical Physics,2024,41(4):413-420.[doi:DOI:10.3969/j.issn.1005-202X.2024.04.003]
点击复制

基于CT的空洞特征在耐药肺结核的影像诊断价值()
分享到：

《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

卷:
41卷
期数:
2024年第4期
页码:
413-420
栏目:
医学影像物理
出版日期:
2024-04-25

文章信息/Info

Title:
Diagnostic value of CT cavity features in drug-resistant pulmonary tuberculosis
文章编号:
1005-202X（2024）04-0413-08
作者:
郑秋婷1; 郭琳2; 夏丽2; 罗伟军1; 钟铖1; 邓莹莹3; 许传军4; 刘远明1; 2; 陆普选1
1.深圳市慢性病防治中心医学影像科， 广东 深圳 518020； 2.深圳市智影医疗科技有限公司， 广东 深圳 518109； 3.深圳市盐田区人民医院影像科， 广东 深圳 518081； 4.南京市第二人民医院影像科， 江苏 南京 210000
Author(s):
ZHENG Qiuting1;  GUO Lin2;  XIA Li2;  LUO Weijun1;  ZHONG Cheng1;  DENG Yingying3;  XU Chuanjun4;  LURE Y.M. Fleming1;  2;  LU Puxuan1
1. Department of Medical Imaging, Shenzhen Center for Chronic Disease Control, Shenzhen 518020, China 2. Shenzhen Zhiying Medical Imaging Co., Ltd., Shenzhen 518109, China 3. Department of Imaging, Yantian District Peoples Hospital, Shenzhen 518081, China 4. Department of Imaging, Nanjing Second Peoples Hospital, Nanjing 210000, China
关键词:
肺结核; 空洞; 鉴别诊断; 计算机体层摄影术
Keywords:
Keywords: pulmonary tuberculosis cavity differential diagnosis computed tomography
分类号:
R318；R816.4
DOI:
DOI:10.3969/j.issn.1005-202X.2024.04.003
文献标志码:
A
摘要:
分析基于CT的空洞特征对耐药肺结核（DR-PTB）及药物敏感肺结核（DS-PTB）患者影像诊断的价值，提高DR-PTB的CT诊断及鉴别诊断水平。回顾性收集明确诊断的323例DR-PTB患者和160例DS-PTB患者，对不同组别患者空洞的发生率、累及肺叶、空洞个数、结节（肿块）或实变中出现空洞、空洞的外内径大小及圆度、空洞壁的厚度进行统计学分析。结果显示，DR-PTB组的空洞发生率、空洞个数、多发空洞和累及3个及以上肺叶者的比例、肺内结节（肿块）中出现空洞的比例均明显高于DS-PTB组，且DR-PTB患者空洞分布更为广泛，DS-PTB与不同类型DR-PTB以及不同类型DR-PTB组间在空洞外径、内径和空洞壁厚度平均值方面的差异均具有统计学意义（P<0.05）。CT空洞特征对DR-PTB与DS-PTB具有鉴别诊断价值。
Abstract:
Abstract: The diagnostic value of cavity features in CT for drug-resistant pulmonary tuberculosis (DR-PTB) and drug-sensitive pulmonary tuberculosis (DS-PTB) is analyzed for improving the CT diagnosis and differential diagnosis of DR-PTB. A retrospective study is conducted on 323 DR-PTB patients and 160 DS-PTB. DR-PTB and DS-PTB groups are compared in terms of the incidence of cavities, lung involvement, the number of cavities, the appearance of cavities in nodules (masses) or consolidation, the size and roundness of the outer and inner diameters of cavities, and the thickness of cavity walls. Compared with DS-PTB group, DR-PTB group has higher incidence of cavities, more cavities. The ratio of multiple cavities and 3 or more lung lobes involved and the ratio of cavities in pulmonary nodules (mass) in DR-PTB patients are significantly higher than those in DS-PTB group. Cavities are more widely distributed in DR-PTB patients. There are significant differences in CT cavity features, including the external diameter, internal diameter, and mean cavity wall thickness for DS-PTB and different types of DR-PTB, as well as within groups of different types of DR-PTB (P<0.05). CT features based on cavitation have significant values in distinguishing DR-PTB and DS-PTB.

相似文献/References:

[1]安冬会,杨俊潇,屈亚林,等. 能谱CT在肺部磨玻璃结节良恶性鉴别中的应用价值[J].中国医学物理学杂志,2018,35(10):1160.[doi:DOI:10.3969/j.issn.1005-202X.2018.10.009]
　AN Donghui,YANG Junxiao,QU Yalin,et al. Application value of energy spectrum CT in the differential diagnosis of benign and malignant pulmonary ground-glass nodule[J].Chinese Journal of Medical Physics,2018,35(4):1160.[doi:DOI:10.3969/j.issn.1005-202X.2018.10.009]
[2]杨朝生,陈慧,孙雪皎,等.结核感染T细胞斑点试验与肺部CT表现的相关性[J].中国医学物理学杂志,2020,37(9):1155.[doi:10.3969/j.issn.1005-202X.2020.09.014]
　YANG Chaosheng,CHEN Hui,SUN Xuejiao,et al.Correlation between T-SPOT.TB assay and pulmonary CT findings in pulmonary tuberculosis[J].Chinese Journal of Medical Physics,2020,37(4):1155.[doi:10.3969/j.issn.1005-202X.2020.09.014]
[3]翟安,邓平,贝承丽,等.胸部物理治疗联合纤维支气管镜灌洗对肺结核的效果[J].中国医学物理学杂志,2021,38(8):1023.[doi:DOI:10.3969/j.issn.1005-202X.2021.08.020]
　ZHAI An,DENG Ping,BEI Chengli,et al.Therapeutic effect of chest physiotherapy combined with fiberoptic bronchoscopy lavage on pulmonary tuberculosis[J].Chinese Journal of Medical Physics,2021,38(4):1023.[doi:DOI:10.3969/j.issn.1005-202X.2021.08.020]
[4]王佳浩,王宝珠,郭志涛,等.多感受野的轻量化YOLOv4用于检测肺结核[J].中国医学物理学杂志,2022,39(9):1119.[doi:DOI:10.3969/j.issn.1005-202X.2022.09.011]
　WANG Jiahao,WANG Baozhu,GUO Zhitao,et al.Lightweight YOLOv4 with multi-receptive fields for detection of pulmonary tuberculosis[J].Chinese Journal of Medical Physics,2022,39(4):1119.[doi:DOI:10.3969/j.issn.1005-202X.2022.09.011]
[5]王京华,袁金丽,郭志涛,等.改进的YOLOv4算法在肺结核检测中的应用研究[J].中国医学物理学杂志,2023,40(1):113.[doi:DOI:10.3969/j.issn.1005-202X.2023.01.019]
　WANG Jinghua,YUAN Jinli,GUO Zhitao,et al.Application of improved YOLOv4 algorithm in the detection of pulmonary tuberculosis[J].Chinese Journal of Medical Physics,2023,40(4):113.[doi:DOI:10.3969/j.issn.1005-202X.2023.01.019]
[6]谢浩杰,鲁明丽,张陈,等.基于深度学习的肺结核检测综述[J].中国医学物理学杂志,2024,41(7):918.[doi:DOI:10.3969/j.issn.1005-202X.2024.07.020]
　XIE Haojie,LU Mingli,ZHANG Chen,et al.Review on tuberculosis detection using deep learning[J].Chinese Journal of Medical Physics,2024,41(4):918.[doi:DOI:10.3969/j.issn.1005-202X.2024.07.020]

备注/Memo

备注/Memo:
【收稿日期】2023-10-26 【基金项目】国家重点研发计划（2019YFE0121400）；深圳市科技计划（KQTD2017033110081833, JCYJ20190813153413160, JSGG20201102162802008, JCYJ20220531093817040）；广州市科技计划（2023A03J0536, 2024A03J0583） 【作者简介】郑秋婷，硕士，副主任医师，研究方向：感染与传染病影像学，E-mail: triangle525@126.com；郭琳，博士，研究方向：人工智能与医学影像，E-mail: guolin913@outlook.com（郑秋婷与郭琳为共同第一作者） 【通信作者】陆普选，主任医师，研究方向：感染与传染病影像学，E-mail: Lupuxuan@126.com；刘远明，博士，教授，研究方向：机器学习与人工智能神经网络，E-mail: f.lure@hotmail.com（陆普选与刘远明为共同通信作者）
更新日期/Last Update: 2024-04-25