Multiscale Modeling of Lung Disease-Influenced Aerosol Dosimetry

肺部疾病影响的气溶胶剂量测定的多尺度建模

• 批准号: 10200811
• 负责人: CHANTAL DARQUENNE
• 金额: $ 65万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2023-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10200811
• 关键词: 3-Dimensional; 4D Imaging; Aerosols; Affect; Air Movements; Air Pollution; Algorithms; Asthma; Biological; Breathing; Caliber; Cause of Death; Chemicals; Chronic Obstructive Airway Disease; Computer Models; Coupled; Coupling; Data; Databases; Deposition; Development; Dimensions; Disease; Dose; Drug Delivery Systems; Dust; Environmental Exposure; Environmental Health; Exposure to; Future; Goals; Health; Heterogeneity; Human; Human Volunteers; Image; Individual; Indoor Air Pollution; Inhalation; Irritants; Link; Liquid substance; Lung; Lung diseases; Measurement; Mechanics; Methods; Modeling; Nose; Occupational; Occupational Exposure; Oral cavity; Outcome; Performance; Pharmaceutical Preparations; Pharmacologic Substance; Property; Published Database; Publishing; Quality of life; Rattus; Research; Research Personnel; Resolution; Respiratory System; Risk; Risk Assessment; Route; Site; Standardization; Therapeutic; Therapeutic Intervention; Three-Dimensional Imaging; Tissues; Work; X-Ray Computed Tomography; base; cigarette smoke; cohort; data submission; dosimetry; environmental toxicology; fine particles; improved; model development; multi-scale modeling; multimodality; novel; novel strategies; particle; pathogen exposure; physical property; predictive modeling; respiratory; ventilation; volunteer

Abstract The overall goal of this proposal is to develop multiscale computational models that can predict the deposition of inhaled aerosols in all regions of the respiratory system of individuals that are either healthy or suffering from respiratory diseases such as COPD (chronic obstructive pulmonary disease). COPD is generally associated with exposure to toxic/irritant aerosols (e.g. cigarette smoke, occupational dusts/fumes, environmental PM2.5 air pollution, etc.) and adversely affects the quality of life for millions of susceptible individuals. Along with asthma, COPD is the third leading disease-based cause of death in the U.S. In addition, the respiratory system has been exploited as a potential route for local and systemic delivery of therapeutic aerosols for COPD, asthma, or other diseases where drugs may not be as effective by other routes of administration. As a result, the development of predictive aerosol dosimetry models has been a major focus of environmental toxicology and pharmaceutical health research for decades. To date, the challenge of predicting the deposition of inhaled aerosols under disease conditions has been largely unmet. We propose to utilize advancements our established team of investigators and others have made in imaging, aerosol exposure and measurement, and computational modeling to develop, experimentally evaluate, and refine multiscale models that predict site- and region-specific deposition of aerosols throughout the respiratory system and to study how deposition is influenced by disease. Our proposed models will be developed by a step-wise, modular integration of 3D computational fluid dynamic (CFD) airflow and aerosol tracking models that extend from the nose and mouth to the conducting airways of the lung with each 3D pulmonary airway bi-directionally coupled with lower dimensional airflow, aerosol transport, and tissue mechanics models to describe aerosol transport and deposition over the full respiratory system and throughout the complete breathing cycle (Aim 1). Models will initially be developed for healthy individuals (Aim 2) followed by disease (Aim 3) using published airway and tissue mechanics data and, where data do not exist for humans, extracted from our 4D imaging and aerosol deposition data in healthy and diseased rats. Our modular approach to multiscale linkages will allow users to substitute individual model components as new advances are made. The multiscale models will be evaluated and further refined using a rich database of multi-modal 3D imaging and aerosol deposition measurements in human volunteers that include both healthy and COPD cohorts. The expected outcome of our work will be a suite of modular, multiscale models and standardized approaches for new model development that can be used by researchers, risk assessors, or clinicians to predict aerosol deposition in the respiratory systems of humans under healthy and disease conditions in addition to the underlying algorithms and framework for effective linking of user-defined, personalized aerosol dosimetry models in the future.

抽象的 该提案的总体目标是开发可以预测沉积的多尺度计算模型 在健康或遭受痛苦的个体呼吸系统的所有区域的吸入气雾剂 来自呼吸道疾病，例如COPD（慢性阻塞性肺部疾病）。 COPD通常关联 暴露于有毒/刺激性气溶胶（例如香烟，烟雾/烟雾，环境PM2.5） 空气污染等）并对数百万易感人群的生活质量产生不利影响。以及 哮喘，COPD是美国第三大主要疾病死因，此外，呼吸系统 已被利用为局部和全身输送COPD治疗气溶胶的潜在途径， 哮喘或其他药物可能不会有效的哮喘或其他疾病。结果， 预测性气溶胶剂量测定模型的开发一直是环境毒理学和 药物健康研究数十年。迄今为止，预测吸入沉积的挑战 在疾病条件下的气溶胶在很大程度上没有得到满足。我们建议利用我们已建立的进步 调查人员和其他人在成像，气溶胶暴露和测量方面都做出了 计算建模以开发，实验评估和完善多尺度模型，以预测站点 整个呼吸系统的气溶胶的区域特异性沉积，并研究沉积 受疾病的影响。我们提出的模型将通过3D的逐步模块化整合开发 计算流体动态（CFD）气流和气溶胶跟踪模型，从鼻子和嘴巴延伸 每3D肺气道与较低 尺寸气流，气溶胶运输和组织力学模型，以描述气溶胶传输和 在整个呼吸系统以及整个完整的呼吸周期中沉积（AIM 1）。模型将 最初是针对健康个体开发的（AIM 2），然后使用已发表的气道和 组织力学数据以及人类不存在的数据，从我们的4D成像和气溶胶中提取 健康和患病大鼠的沉积数据。我们的模块化链接方法将使用户能够 随着新的进步，替代单个模型组件。将评估多尺度模型 并使用丰富的多模式3D成像和气溶胶沉积测量的丰富数据库进一步完善 包括健康和COPD队列的人类志愿者。我们工作的预期结果将是 可以使用的模块化，多尺度模型和标准化方法 研究人员，风险评估者或临床医生可以预测人类呼吸系统中的气溶胶沉积 在健康和疾病条件下，除了基础算法和有效的框架 将来链接用户定义的个性化气溶胶剂量计模型。