Miao Chengyu, Feng Shengchuan, Wang Fengyan, Chen Zizheng, Xu Jiaxuan, Li Xueping, Zhou Zifei, Chen Rongchang, Liang Zhenyu
Guangzhou Institute of Respiratory Health, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
J Thorac Dis. 2025 Mar 31;17(3):1736-1745. doi: 10.21037/jtd-24-1074. Epub 2025 Mar 27.
Chronic obstructive pulmonary disease (COPD) is a significant global health challenge characterized by persistent respiratory symptoms and airflow limitation. Recent advancements in computed tomography (CT) have enhanced our understanding of COPD, particularly in diagnosing extrapulmonary comorbidities. This review aims to summarize the current findings on extrapulmonary manifestations in COPD patients and the role of quantitative computed tomography (QCT) in evaluating these comorbidities.
A comprehensive literature search was conducted using PubMed and Web of Science databases, covering studies from January 1999 to May 2024. Keywords included "COPD", "chronic obstructive pulmonary disease", "muscle", "adipose tissue", "coronary artery calcification", "bone density", "extrapulmonary manifestations", and "Quantitative Computed Tomography". Inclusion criteria focused on studies involving COPD patients using QCT to identify extrapulmonary manifestations, published in peer-reviewed journals and available in English.
The review highlights significant findings, such as the reduction in muscle mass and bone density and the increase in coronary artery calcification (CAC) in COPD patients, all closely associated with disease severity and prognosis. Key metrics evaluated include mid-thigh muscle cross-sectional area, pectoralis muscle area, erector spinae muscles, and bone density. Advanced CT analysis techniques, including artificial intelligence (AI) and machine learning, are emphasized as crucial for improving assessment accuracy and efficiency. Subcutaneous fat reduction and CAC are identified as critical indicators of mortality and disease progression.
Quantitative CT evaluation is vital for understanding and managing extrapulmonary lesions in COPD. Future research should focus on establishing suitable measurement tools and methods and defining critical thresholds for treatment efficacy. The integration of advanced CT techniques and interdisciplinary approaches is essential for enhancing diagnostic accuracy and developing personalized treatment strategies for COPD patients.
慢性阻塞性肺疾病（COPD）是一项重大的全球健康挑战，其特征为持续的呼吸道症状和气流受限。计算机断层扫描（CT）的最新进展增进了我们对COPD的理解，尤其是在诊断肺外合并症方面。本综述旨在总结COPD患者肺外表现的当前研究结果以及定量计算机断层扫描（QCT）在评估这些合并症中的作用。
使用PubMed和Web of Science数据库进行全面的文献检索，涵盖1999年1月至2024年5月的研究。关键词包括“COPD”、“慢性阻塞性肺疾病”、“肌肉”、“脂肪组织”、“冠状动脉钙化”、“骨密度”、“肺外表现”和“定量计算机断层扫描”。纳入标准侧重于涉及使用QCT识别肺外表现的COPD患者的研究，这些研究发表在同行评审期刊上且为英文。
该综述突出了重要发现，例如COPD患者的肌肉质量和骨密度降低以及冠状动脉钙化（CAC）增加，所有这些都与疾病严重程度和预后密切相关。评估的关键指标包括大腿中部肌肉横截面积、胸肌面积、竖脊肌和骨密度。强调先进的CT分析技术，包括人工智能（AI）和机器学习，对于提高评估准确性和效率至关重要。皮下脂肪减少和CAC被确定为死亡率和疾病进展的关键指标。
定量CT评估对于理解和管理COPD中的肺外病变至关重要。未来的研究应侧重于建立合适的测量工具和方法，并确定治疗效果的关键阈值。先进CT技术与跨学科方法的整合对于提高诊断准确性和为COPD患者制定个性化治疗策略至关重要。
