非结核分枝杆菌感染的影像学研究进展  

Progress in imaging research of non-tuberculous mycobacteria infection

作　　者：陆圣威 戴琦 张景峰 郑建军[2] LU Shengwei;DAI Qi;ZHANG Jingfeng;ZHENG Jianjun(The Second Clinical Medical College,Zhejiang Chinese Medical University,Hangzhou 310000,China;Department of Radiology,Ningbo No.2 Hospital,Ningbo 315000,China)

机构地区：[1]浙江中医药大学第二临床医学院,浙江杭州310000 [2]浙江省宁波市第二医院放射科,浙江宁波315000

出　　处：《医学影像学杂志》2024年第11期140-143,共4页Journal of Medical Imaging

基　　金：浙江省基础公益科技计划项目(编号:LTGY23H180003);浙江省宁波市公益类科技计划项目(编号:2021S107);浙江省宁波市影像医学临床医学研究中心项目(编号:2021L003);浙江省宁波市省市共建医学重点学科-医学影像学项目(编号:2022-S02)。

摘　　要：非结核分枝杆菌感染多见于肺部,肺外感染亦有报道,总体发病率呈上升趋势。影像学检查是临床诊疗不可缺少的工具,对非结核分枝杆菌感染早期识别具有重要价值,同时可以直观的反应病情转归。近年来,对于人工智能技术在非结核分枝杆菌病影像学领域中的研究也在不断开展。因此,本文主要介绍非结核分枝杆菌的肺内和肺外感染的影像学进展,同时对人工智能在该疾病中的最新应用研究重点阐述。Non-tuberculous mycobacteria infection is common in the lungs,extrapulmonary infection has also been reported,and the overall incidence rate is on the rise.Imaging examination is an indispensable tool for clinical diagnosis and treatment,which is of great value for early identification of non-tuberculous mycobacteria infection and can intuitively reflect the outcome of the disease.In recent years,research on artificial intelligence technology in the field of imaging of non-tuberculous mycobacterial diseases has also been continuously carried out.Therefore,this article mainly introduces the imaging progress of pulmonary and extrapulmonary infections caused by non-tuberculous mycobacteria,and focuses on the latest application research of artificial intelligence in this disease.

关 键 词：非结核分枝杆菌肺病 肺外非结核分枝杆菌病 影像学 人工智能 

分 类 号：R516[医药卫生—内科学] R445[医药卫生—临床医学]