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Lung Biomechanics and Disease Progression in SPIROMICS

SPIROMICS 中的肺生物力学和疾病进展

基本信息

批准号：
10179453
负责人：
JOSEPH M REINHARDT
金额：
$ 51.39万
依托单位：
UNIVERSITY OF IOWA
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-08-01 至 2024-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10179453
关键词：
Age Air Algorithms Anatomy Asthma Biological Markers Biomechanics Body mass index Breathing Cardiovascular Diseases Categories Chronic Obstructive Airway Disease Clinical Trials Cohort Studies Complement Complex Country Data Databases Diagnosis Diagnostic radiologic examination Disease Disease Progression Economics Fibrosis Fissural Follow-Up Studies Gender Genotype Goals Healthcare Image Individual Intervention Lobar Lobe Location Lung Lung diseases Manufacturer Name Measurement Measures Mechanics Methods Modeling Morbidity - disease rate Multicenter Trials Obstruction Outcome Outcome Assessment Phenotype Protocols documentation Pulmonary Emphysema Reproducibility Residual volume Respiration Scanning Site Spatial Distribution Spirometry Testing Therapeutic Intervention Time Total Lung Capacity Variant Work X-Ray Computed Tomography base cohort cone-beam computed tomography density disease phenotype follow-up image processing image registration imaging biomarker indexing insight lung lobe lung volume mechanical behavior mortality predictive marker response small airways disease study population

项目摘要

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.

摘要慢性阻塞性肺疾病（COPD）是一个日益增长的发病率和死亡率的原因，世界各国经济繁荣程度各不相同。COPD是一种复杂的疾病，其特征在于干扰正常呼吸的永久性气道阻塞。基于成像的生物标志物是在我们的研究中越来越重要，以确定COPD表型，建立同质亚群有助于基因分型，并指导治疗干预和相关结果考核计算机断层扫描（CT）成像可以描述疾病的空间分布，测量COPD中肺气肿和小气道疾病的程度，并检测伴随疾病，如哮喘、纤维化和心血管疾病。使用CT成像研究肺部的一些主要障碍与实现可靠的扫描过程中的肺容量（吸气水平），扫描过程中的协议变化，测量的CT值的变化，以及降低大型多中心试验中扫描的重现性。CT的使用进一步受到当前使用基于CT密度的阈值来确定疾病的位置和程度的实践。我们假设，通过补充CT，我们对COPD的认识有可能进一步提高密度作为疾病的主要基于图像的指标，测量局部肺力学。我们建议在COPD研究中研究亚群的生物力学和中期结局（螺旋体学）队列。我们将寻找不同的机械行为在整个螺旋疾病分层，检查肺叶解剖结构和裂隙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螺旋数据。完成后，该项目将产生一个描述SPIROMICS生物力学的数据库队列，确定用于受试者表型分析的COPD描述性生物标志物，并创建疾病进展肺生物力学模型。