Abstract:

Osteoporosis is one of the primary comorbidities of chronic obstructive pulmonary disease （COPD）. Osteoporosis is mainly characterized by a reduction in bone mass and strength， leading to the occurrence of primary fragility fractures. The risk associated with decreased bone mineral density （BMD） can even surpass that of COPD itself， yet it often remains underdiagnosed and undertreated. This review summarizes the correlation between COPD and osteoporosis， and explores the cutting-edge advancements in osteoporosis screening for COPD patients through innovative imaging technologies， particularly the "CT spine bone quantification system" based on the 3D U-Net deep learning model. This article discusses current research on the pathogenesis of COPD and osteoporosis， the advantages and limitations of different BMD detection methods， and highlights the potential of the "CT spine bone quantification system" in enhancing screening efficiency and accuracy. Furthermore， the review explores future research directions， including the further optimization of imaging technologies and the development of personalized treatment strategies， to better manage the bone health of COPD patients.

Key words:chronic obstructive pulmonary disease,osteoporosis,bone mineral density,3D U-Net deep learning model,CT spine bone quantification system

摘要：

骨质疏松是慢性阻塞性肺疾病（chronic obstructive pulmonary diseases，COPD）的主要共患病之一。骨质疏松主要表现为骨量减少、骨强度下降，可导致原发性脆性骨折，骨密度（bone mineral density，BMD）下降带来的风险甚至高于COPD本身，但通常诊断和治疗方面仍存在一定的不足。本综述归纳了COPD与骨质疏松症之间的相关性，并探讨了通过影像学创新技术，特别是基于3D U-Net深度学习模型的“CT脊柱骨定量系统”，对COPD患者进行骨质疏松筛查的前沿进展，探讨目前关于COPD与骨质疏松症相关的发病机制，以及不同BMD检测方法的优势与局限，并强调了“CT脊柱骨定量系统”在提高筛查效率和准确性方面的潜力。此外，本综述还探讨了未来研究方向，包括进一步优化影像学技术和开发个性化治疗策略，以更好地管理COPD患者的骨健康。

关键词:慢性阻塞性肺疾病,骨质疏松症,骨密度,3D U-Net深度学习模型,CT脊柱骨定量系统