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: 9768482
• 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/9768482
• 关键词: 3-Dimensional; 4D Imaging; Aerosols; Affect; Air Pollution; Algorithms; Asthma; Biological; Breathing; Caliber; Cause of Death; Chemicals; Chronic Obstructive Airway Disease; Computer Simulation; Coupled; Coupling; Data; Databases; Deposition; Development; Dimensions; Disease; Dose; Drug Delivery Systems; Dust; Environmental Health; Environmental air flow; 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; 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; Workplace; X-Ray Computed Tomography; base; cigarette smoke; cohort; data submission; dosimetry; environmental toxicology; improved; model development; multi-scale modeling; multimodality; novel; novel strategies; particle; pathogen exposure; physical property; predictive modeling; respiratory; 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.

摘要 这项提案的总体目标是开发多尺度计算模型，可以预测沉积 健康或患病个体呼吸系统所有区域的吸入气溶胶 呼吸系统疾病，如COPD（慢性阻塞性肺病）。COPD通常与 暴露于有毒/刺激性气溶胶（如香烟烟雾、职业粉尘/烟雾、环境PM2.5 空气污染等）并对数百万易感个体的生活质量产生不利影响。沿着 哮喘、COPD是美国第三大基于疾病的死亡原因。 已经被开发作为用于COPD的治疗性气雾剂的局部和全身递送的潜在途径， 哮喘或其它疾病，其中药物通过其它给药途径可能不那么有效。结果导致 预测性气溶胶剂量测定模型的开发一直是环境毒理学的主要焦点， 几十年来的医药卫生研究。到目前为止，预测吸入的沉积物的挑战 疾病条件下的气溶胶在很大程度上没有得到满足。我们建议利用我们现有的先进技术， 一组研究人员和其他人在成像、气溶胶暴露和测量方面取得了进展， 计算建模，以开发，实验评估和完善多尺度模型，预测网站， 和区域特定的沉积气溶胶在整个呼吸系统，并研究如何沉积， 受疾病影响。我们提出的模型将通过逐步的，模块化的3D集成开发 计算流体动力学（CFD）气流和气溶胶跟踪模型，从鼻子和嘴延伸 其中每个3D肺气道与下气道双向耦合 三维气流，气溶胶运输和组织力学模型来描述气溶胶运输和 在整个呼吸系统和整个呼吸循环中的沉积（目标1）。车型将 最初开发用于健康个体（目标2），然后是疾病（目标3），使用公开的气道， 组织力学数据，并且在不存在人类数据的情况下，从我们的4D成像和气溶胶提取 健康和患病大鼠的沉积数据。我们的多尺度链接模块化方法将允许用户 随着新技术的进步，替换单个模型组件。将对多尺度模型进行评估 并使用多模态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群组的人类志愿者。我们工作的预期成果将是 一套模块化、多尺度模型和标准化方法，用于新模型开发， 由研究人员、风险评估人员或临床医生预测人类呼吸系统中的气溶胶沉积 在健康和疾病的条件下，除了基本的算法和框架， 今后将用户定义的个性化气溶胶剂量测定模型连接起来。