Lung Biomechanics and Disease Progression in SPIROMICS

摘要 慢性阻塞性肺疾病(COPD)是世界各地发病率和死亡率不断增长的原因。 世界各国的经济繁荣程度各不相同。COPD是一种复杂的疾病，其特征是 永久性呼吸道fl阻塞，干扰正常呼吸。基于成像的生物标志物是 在我们寻找COPD表型的过程中变得越来越重要，建立同源性 帮助亚人群进行基因分型，指导治疗干预措施和相关结果 评估。计算机断层扫描(CT)成像可以描述疾病的空间分布， 测量COPD患者肺气肿和小气道疾病的程度，并检测伴随疾病， 如哮喘、fiBrosis和心血管疾病。 使用CT成像研究肺部的一些主要障碍与实现可靠的 扫描期间的肺容量(吸气量)，不同扫描方案的差异 测量的CT值的变化，以及站点间和制造商间的差异，从而降低了 在大型多中心试验中扫描的重复性。CT的使用受到当前的进一步限制 应用CT密度阈值判断病变部位和程度的实践。 我们假设，通过补充CT，我们对COPD的了解有可能进一步进步 密度作为以图像为基础的疾病的主要指标，通过测量局部肺力学。 我们建议在COPD研究中研究亚群和中间结果的生物力学 (SPIROMICS)队列。我们将寻找SPIROMICS疾病在机械行为方面的差异 检查肺叶解剖和fiSure完整性对肺力学和疾病的影响 分布，并通过分析确定预测COPD进展的基于图像的生物标志物 纵向的SPIROMICS数据。 该项目完成后，将建立一个描述脊柱生物力学的数据库 队列，识别用于受试者表型的COPD描述性生物标记物，并创造疾病进展 以肺生物力学为基础的模型。

Abstract Chronic obstructive pulmonary disease (COPD) is a growing cause of morbidity and mortality around the world in countries of all levels of economic prosperity. COPD is a complex disorder characterized by permanent airway flow obstruction that interferes with normal respiration. Imaging-based biomarkers are of increasing importance in our search to identify COPD phenotypes, establishing homogeneous sub-populations to aid in genotyping, and directing therapeutic interventions and associated outcomes assessment. Computed tomography (CT) imaging can describe the spatial distribution of disease, measure the extent of emphysema and small airways disease in COPD, and detect concomitant disease, such as asthma, fibrosis, and cardiovascular disease. Some of the main obstacles in using CT imaging to study the lung are associated with achieving reliable lung volumes (levels of inspiration) during scanning, variations in protocols across scans producing changes in measured CT values, and inter-site and inter-manufacturer differences which reduce the reproducibility of scanning in large multi-center trials. The use of CT is further limited by the current practice of using CT density-based thresholds to define the location and extent of disease. We hypothesize that further advances in our understanding of COPD are possible by complementing CT density as the primary image-based indicator of disease with measurements of regional lung mechanics. We propose to study the biomechanics of the Subpopulations and Intermediate Outcomes in COPD Study (SPIROMICS) cohort. We will look for differences in mechanical behavior across the SPIROMICS disease strata, examine the impact of lobar anatomy and fissure integrity on lung mechanics and disease distribution, and identify image-based biomarkers that are predictive of COPD progression by analyzing the SPIROMICS data longitudinally. When complete, this project will produce a database describing the biomechanics of the SPIROMICS cohort, identify descriptive biomarkers of COPD for subject phenotyping, and create a disease progression model based on lung biomechanics.