Identifying imaging-based biomarkers of COPD development through virtual inhalation experiments

通过虚拟吸入实验识别 COPD 发展的基于成像的生物标志物

基本信息

批准号：
9144831
负责人：
Filippo Coletti
金额：
$ 22.8万
依托单位：
UNIVERSITY OF MINNESOTA
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-09-15 至 2018-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9144831
关键词：
3D Print Affect Age Air Anatomy Ancillary Study Biological Markers Breathing Bronchial Tree Caliber Cause of Death Characteristics Chronic Obstructive Airway Disease Clinical Data Data Set Deposition Detection Development Disease Disease Progression Drug Delivery Systems Early Diagnosis Environmental air flow Equation Etiology Frequencies Gender Generations Genetic Genetic Markers Geometry Goals Health Image In Vitro Incidence Individual Inherited Lead Length Liquid substance Lung Magnetic Resonance Magnetic Resonance Imaging Maps Measurement Mechanics Medical Imaging Minnesota Modeling Morphology Motion Multivariate Analysis Onset of illness Particulate Pathogenesis Patients Pattern Phase Predisposition Prevention Prevention strategy Preventive treatment Primary Health Care Property Public Health Pulmonary Emphysema Pulmonary Function Test/Forced Expiratory Volume 1 Research Resolution Resources Respiration Respiratory physiology Risk Risk Assessment Risk Factors Scanning Segmental bronchus structure Severities Smoke Smoker Smoking Smoking History Staging Stratification Structure-Activity Relationship Technology Testing Time Tobacco smoke Travel Trees United States National Institutes of Health Universities Water Work X-Ray Computed Tomography advanced disease airway inflammation base cost density fluid flow improved in vivo imaging innovation mathematical analysis molecular marker morphometry notch protein novel particle physical model pollutant productivity loss research study virtual

项目摘要

DESCRIPTION (provided by applicant): Chronic Obstructive Pulmonary Disease (COPD) is characterized by an irreversible loss of lung function, and is among the leading causes of death worldwide. While it is well established that inhaled pollutants, such as tobacco smoke, can lead to COPD, it is not understood why only 20% of the exposed individuals develop the disease. It is also unclear why some of those who develop the COPD suffer rapid and sever decline of lung function, while others remain relatively stable over time. Such poor understanding of the origin and progression of the disease is a major limitation for the development of effective strategies for both prevention and treatment. The goal of this study is to investigate whether and how innate anatomical features of the airways participate to the disease development. In particular we hypothesize that, in individuals that develop COPD, the anatomical characteristics of the bronchial tree result in air flow patterns that enhance particle deposition, a feature that makes them more susceptible to airway inflammation. To test this hypothesis we will retrospectively explore the lung structure-function relationship in 18 healthy and diseased smokers, by analyzing their airway morphology (reconstructed from CT scans), in relation to the change in lung function over five years. The data is entirely available from the large NIH COPDGene(r) study, from which this study is an Ancillary Study. We will seek two types of predictors of COPD: structural and functional. The structural predictors will be identified by analyzing the subjects' airway morphometry, including branching angle, airway lumen, and airway curvature. The functional predictors will be related to the airflow pattern and associated particle deposition. Because in vivo imaging of flow and deposition in the lungs has limited accuracy and resolution, we will perform virtual inhalation experiments. Physical models of each patient bronchial tree will be 3D printed in synthetic materials and attached to an oscillatory flow circuit. Water will be used as a working fluid, and flow rate and ventilation frequency will be adjusted to compensate for the difference in properties of water with respect to air. MRI measurements will provide the flow velocity map throughout the models at high spatial resolution, and numerical integration of the particle trajectory will provide the deposition pattern. Our innovative approach is made possible by our research team's unique combination of expertise, and by the top-notch resources available at the University of Minnesota Center for Magnetic Resonance Research. If our hypothesis is confirmed, it will pave the way towards early, pre-symptomatic detection of COPD. It will also represent a fundamental step towards an in-depth understanding of local particle deposition, which is necessary to achieve more effective and targeted inhalation drug delivery.

描述（由适用提供）：慢性阻塞性肺疾病（COPD）的特征是肺功能的不可逆转丧失，并且是全球死亡的主要原因之一。虽然众所周知，继承的污染物（例如烟草烟）可能导致COPD，但不明白为什么只有20％的暴露个人患上这种疾病。还不清楚为什么一些发展COPD的人迅速遭受肺功能的迅速下降，而另一些人则随着时间的流逝仍然相对稳定。对疾病的起源和进展的理解不足是制定预防和治疗有效策略的主要局限性。这项研究的目的是研究气道的先天解剖学特征以及如何参与疾病发展。特别是我们假设，在发展COPD的个体中，支气管树的解剖学特征会导致空气流动模式增强颗粒沉积，这一特征使它们更容易受到气道注射的影响。为了检验这一假设，我们将通过分析其气道形态（从CT扫描重建）来回顾性地探索18位健康和解散的吸烟者中的肺结构 - 功能关系，这与五年来肺功能的变化有关。数据完全可以从大型NIH Copdgene（R）研究中获得，该研究是一项辅助研究。我们将寻求COPD的两种预测指标：结构和功能。结构预测因子将通过分析受试者的气道形态计量学，包括分支角，气道管腔和气道曲率来识别。功能预测因子将与气流模式和相关粒子沉积有关。因为在肺部流量和沉积的体内成像的精度和分辨率有限，所以我们将执行虚拟吸入实验。每个患者支气管树的物理模型将将3D打印在合成材料中，并连接到振荡流动电路上。水将用作工作流体，流速和通风频率将被调整以补偿相对于空气的水性质差异。 MRI测量值将以高空间分辨率在整个模型中提供流速图，而粒子轨迹的数值整合将提供沉积模式。我们的研究团队独特的专业知识和明尼苏达大学磁共振研究中心提供的一流资源使我们的创新方法成为可能。如果我们的假设得到证实，它将为pefter的早期检测到COPD的早期检测。这也将代表对局部颗粒沉积的深入了解的基本步骤，这对于实现更有效和有针对性的吸入药物递送是必不可少的。