Multi-center Structural & Functional Quantitative CT Pulmonary Phenotyping

多中心结构

基本信息

批准号：
8990993
负责人：
ERIC Alfred HOFFMAN
金额：
$ 113.76万
依托单位：
UNIVERSITY OF IOWA
依托单位国家：
美国
项目类别：
财政年份：
2012
资助国家：
美国
起止时间：
2012-08-01 至 2019-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8990993
关键词：
Accounting Adherence Air Algorithms Anatomy Asthma Back Biological Markers Biomedical Engineering Blood Vessels Blood Volume Blood flow Calibration Chronic Obstructive Airway Disease Cluster Analysis Computer software Contrast Media Coupled Data Collection Development Disease Dose Environmental air flow Equipment Etiology Evaluation Functional Imaging Gases Genotype Health Heterogeneity Image Image Analysis Imaging Techniques Inflammation Injection of therapeutic agent Intervention Journals Link Liquid substance Lung Lung CAT Scan Lung diseases Manufacturer Name Measurement Measures Medicine Methodology Methods Modeling Multicenter Studies Multicenter Trials New England Noise Pathologic Processes Pathology Perfusion Peripheral Phenotype Population Process Protocols documentation Pulmonary Emphysema Radiation Reporting Research Respiratory physiology Scanning Science Smoking Staging Structure Structure-Activity Relationship Subgroup Techniques Technology Testing Time Trees Venous X-Ray Computed Tomography Xenon airway remodeling base computerized tools detector disease phenotype disorder subtype endothelial dysfunction feeding imaging Segmentation imaging biomarker indexing inflammatory lung disease insight interest lung imaging lung volume new technology novel novel strategies novel therapeutics outcome prediction physiologic stressor reconstruction response tool

项目摘要

DESCRIPTION (provided by applicant): Biomarkers of regional lung function, coupled with validated low dose methods of assessing anatomic features of the lung are critical to promote discovery and testing of new interventions in COPD and asthma. This proposed bioengineering research partnership seeks to take advantage of the emerging acquisition technique of multi-spectral computed tomography (currently dual energy CT: DECT), careful evaluation of dose lowering methods, and novel approaches to statistical cluster anlaysis to expand the biomarkers used in multi-center studies to identify sub-populations of lung disease. Current CT methods have focused largely on parenchymal destruction, air trapping and airway remodeling. With our recent findings reported in the Proceedings of the National Acedemy of Sciences and the New England Journal of Medicine, there is growing evidence that the etiology of emphysema may be correlated with abnormal vascular responses to inflammation in COPD. To further validate these findings, we focus on multi-spectral CT to simplify the current dynamic CT approach in its assessment of ventilation and perfusion. With DECT we can simplify to a single breath of xenon gas or a slow peripheral injection of iodinated contrast agent to assess regional ventilation or perfused blood volume (PBV). Our approach consists of 5 tightly integrated aims seeking to: 1) establish the minimum dose required to achieve the measurements of importance in defining COPD and asthma sub-populations; 2) use our well characterized CT assessment of pulmonary perfusion and ventilation using dynamic axial imaging to validate metrics from DECT, providing indices of ventilation and perfusion via single breath hold / single lung volume techniques; 3) expand image segmentation of the lung to the pulmonary arterial and venous trees to further link structure to function as well as to reliabily provide a framework for dividing the lung into sublobar segments as the standard region of interest; 4) test the application of a novel statistica approach to cluster analysis such that the measures from quantitative CT fully account for specific phenotypes for disease subgroups and link to a computational fluid dynamics model such that a putative phenotype can be better understood; and finally 5) provide a framework whereby newly developed protocols are harmonized across manufacturers and scanner models, allowing for cross institutional data collection and a means whereby technology is allowed to progress within the context of longitudial studies.

描述（由申请人提供）：区域肺功能的生物标志物，加上评估肺部解剖特征的经过验证的低剂量方法，对于促进慢性阻塞性肺病和哮喘新干预措施的发现和测试至关重要。这项拟议的生物工程研究合作伙伴关系旨在利用新兴的多光谱计算机断层扫描采集技术（目前为双能 CT：DECT）、仔细评估剂量降低方法以及统计聚类分析的新方法，以扩展多光谱中使用的生物标志物。 - 确定肺部疾病亚群的中心研究。目前的 CT 方法主要集中于实质破坏、空气滞留和气道重塑。我们最近在《美国国家科学院院刊》和《新英格兰医学杂志》上发表的研究结果表明，越来越多的证据表明，肺气肿的病因可能与慢性阻塞性肺病中血管对炎症的异常反应有关。为了进一步验证这些发现，我们重点关注多光谱 CT，以简化当前通气和灌注评估中的动态 CT 方法。通过 DECT，我们可以简化为一次氙气呼吸或缓慢外周注射碘造影剂来评估局部通气或灌注血量 (PBV)。我们的方法由 5 个紧密结合的目标组成，旨在：1）确定实现定义 COPD 和哮喘亚群的重要性测量所需的最小剂量； 2) 使用我们通过动态轴向成像对肺灌注和通气进行充分表征的 CT 评估来验证 DECT 的指标，通过单次屏气/单次肺容量技术提供通气和灌注指数； 3）将肺部的图像分割扩展到肺动脉和静脉树，以进一步将结构与功能联系起来，并可靠地提供将肺部划分为亚肺叶段作为标准感兴趣区域的框架； 4) 测试一种新的统计方法在聚类分析中的应用，以便定量 CT 的测量充分考虑疾病亚组的特定表型，并与计算流体动力学模型联系起来，以便更好地理解假定的表型；最后5）提供一个框架，使新开发的协议能够在制造商和扫描仪模型之间协调一致，从而允许跨机构的数据收集以及允许技术在纵向研究的背景下取得进展的手段。