非结核分枝杆菌（non-tuberculous Mycobacteria， NTM）是一类广泛存在于环境中的条件致病菌，其引起的感染性疾病在全球范围内的发病率、耐药发生率日益攀升。尽管缺乏统一的全球监测数据，但多个国家基于全国性监测或大规模数据库的研究均一致报道了NTM感染的发病率呈显著上升趋势。日本在2013年至2017年间NTM感染导致的肺病发病率从每10万人15.8例增至19.2例，增幅达17.7%；而丹麦的一项覆盖1991年至2022年的国家登记数据显示，NTM相关肺病发病率在30年间持续上升，年均增长率为2.3%。NTM肺病的临床表现缺乏特异性，且与肺结核高度相似，但治疗策略截然不同。此外，不同NTM菌种的治疗方案也大相径庭。因此，开展快速、准确的实验室鉴定和菌种区分至关重要。传统的诊断方法如涂片镜检和培养，存在灵敏度有限、耗时漫长等技术瓶颈，难以满足临床早期精准诊疗的需求。以实时荧光聚合酶链反应（quantitative real-time polymerase chain reaction， qPCR）为代表的分子诊断技术极大缩短了检测时间，实现了对NTM的快速初筛与鉴别。以二代测序和纳米孔测序为代表的基因组学技术，可针对临床直接标本一体化精确鉴定菌种至亚种水平、检测耐药基因，以早期指导临床用药。人工智能技术在联合影像学特征、临床数据乃至基因组信息方面展现出强大潜力，可协助辅助诊断、优化治疗方案及预后预测。新型NTM实验室诊断技术的发展，正推动NTM诊疗从经验模式向高效、精准的个体化模式转变。

Non-tuberculous mycobacteria (NTM) are a group of opportunistic pathogens widely present in the environment. The global incidence of NTM infections and associated drug resistance rates are increasing. Although unified global surveillance data are lacking, studies based on national surveillance or large-scale databases from multiple countries have consistently reported a significant increasing trend in the incidence of NTM infections. In Japan, the incidence of pulmonary disease caused by NTM infections increased from 15.8 to 19.2 cases per 100 000 population between 2013 and 2017, representing an increase of 17.7%. In Denmark, a national registry study covering 1991 to 2022 shows that the incidence of NTM-related pulmonary diseases has continuously increased over the 30-year period, with an average annual growth rate of 2.3%. The clinical manifestations of non-tuberculous mycobacterial pulmonary disease are non-specific and highly similar to those of pulmonary tuberculosis, but the treatment strategies are markedly different. Moreover, treatment schemes vary greatly among different NTM species. Therefore, rapid and accurate laboratory identification and species differentiation are essential. Conventional diagnostic methods such as smear microscopy and culture have technical limitations including low sensitivity and long turnaround time, making it difficult to meet the requirements of early and precise clinical diagnosis and treatment. Molecular diagnostic techniques, represented by real-time fluorescent PCR, have greatly shorte-ned detection duration and enabled rapid screening and differentiation of NTM. Genomic technologies, represented by next-generation sequencing and nanopore sequencing, can achieve integrated and precise identification of bacterial species to the subspecies level and detect drug resistance genes directly from clinical specimens, thereby guiding early clinical medication. Artificial intelligence technology demonstrates strong potential in integrating imaging features, clinical data, and even genomic information, and can assist in auxiliary diagnosis, optimize treatment schemes, and predict prognosis. The development of these novel NTM laboratory diagnostic techniques is driving the transformation of NTM diagnosis and treatment from an empirical model to an efficient, precise, and individualized model.