Coupling MRI-Derived Ventilation with Computational Models to Assess Inhaled Aerosol Treatment Feasibility in Severe Asthmatic Adults

哮喘是一种慢性气道疾病，影响美国2290万人，并造成巨大的经济负担。 哮喘发作（恶化）是由慢性发炎的气道和气道平滑肌的过度反应性刺激引发的，导致气道收缩和气流阻塞。降低急性发作的频率是哮喘疾病管理的主要目标。严重哮喘的治疗尤其具有挑战性， 由于该患者队列（约15%）对吸入治疗反应不佳，导致 与疾病严重程度较轻的患者相比，健康护理费用显著较高。 之一 哮喘管理的关键是早期识别哪些患者可能受益于 替代治疗策略。然而，目前还没有通过实验评估剂量测定法。 特别是在病人之间的基础上是可行的。另一方面，计算模型， 提供了一个独特的机会，揭示解剖和生理特征，导致 剂量不足。 因此，R21提案的主要目标是确定哪些患者 可能受益于替代治疗策略。 为此，从以下位置收集的现有数据集 美国国立卫生研究院资助的严重哮喘研究计划（SARP）的一部分将被纳入研究 吸入药物。本研究的一个子集包括超极化3 He通气和高通气。 分辨率CT图像，从而提供了将患者特定解剖结构和 通风分布与先进的建模技术。合并节段性-水平 通风缺陷百分比（VDP）将使准确的通风分布纳入 进入呼吸计算机模拟模型，外周给药与 不均匀通气利用现有的数据集，我们将测试我们的假设， 药物递送浓度与气道形态特征相关， 直接从CT图像中识别。 在这一建议的范围内，我们将取得关键进展， 在确定哪组患者将受益于替代治疗策略（例如， 全身性药物），因为外周气道输送不足。

Asthma is a chronic airway disorder that impacts 22.9 million people in the United States and causes a substantial economic burden. Asthma attacks (exacerbation) are triggered by stimulation of chronically inflamed airways and hyper responsive airway smooth muscle, leading to airway constriction and obstructed airflow. Reducing the frequency of exacerbations is the primary goal of asthma disease management. Severe asthma is especially challenging to treat, as this cohort of patients (~15%) does not respond well to inhaled therapeutics, resulting in significantly higher heath care costs compared to patients with milder disease severity. One of the keys to asthma management is to identify early which set of patients may benefit from alternative treatment strategies. However assessing dosimetry experimentally is not currently feasible especially on a patient-­to-­patient basis. Computational models, on the other hand, provide a unique opportunity to uncover anatomical and physiological features that lead to inadequate dosing. Thus, the main goal of this R21 proposal is to determine which set of patients may benefit from alternative treatment strategies. To do this, existing datasets collected from as part of the NIH funded Severe Asthma Research Program (SARP) will be incorporated to study inhaled medications. A subset of this study includes hyperpolarized 3He ventilation and high-­ resolution CT images, thereby providing the opportunity to couple patient-­specific anatomy and ventilation distribution with advanced modeling techniques. Incorporation of segmental-­level ventilation defects percent (VDP) will enable accurate ventilation distributions to be incorporated into the respiratory in silico models and for peripheral delivery to be correlated with the heterogeneous ventilation. With this existing dataset, we will test our hypothesis that abnormal drug delivery concentrations are correlated to airway morphometric features which may be identified directly from CT images. Within the scope of this proposal, we will make key advances in determining which set of patients would benefit from alternative treatment strategies (e.g. systemic medications) because of inadequate peripheral airway delivery.