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Breath Hold Facilitates Targeted Deposition of Aerosolized Droplets in a 3D Printed Bifurcating Airway Tree.
Annals of Biomedical Engineering ( IF 3.0 ) Pub Date : 2020-09-21 , DOI: 10.1007/s10439-020-02623-9
Adam H Sonnenberg 1, 2 , Edward Taylor 1 , Jarred R Mondoñedo 1 , Samer Bou Jawde 1 , Samir D Amin 1 , Jiaxi Song 1 , Mark W Grinstaff 1, 3 , Béla Suki 1
Affiliation  

The lungs have long been considered a desired route for drug delivery but, there is still a lack of strategies to rationally target delivery sites especially in the presence of heterogeneous airway disease. Furthermore, no standardized system has been proposed to rapidly test different ventilation strategies and how they alter the overall and regional deposition pattern in the airways. In this study, a 3D printed symmetric bifurcating tree model mimicking part of the human airway tree was developed that can be used to quantify the regional deposition patterns of different delivery methodologies. The model is constructed in a novel way that allows for repeated measurements of regional deposition using reusable parts. During ventilation, nebulized ~3-micron-sized fluid droplets were delivered into the model. Regional delivery, quantified by precision weighing individual airways, was highly reproducible. A successful strategy to control regional deposition was achieved by combining an inspiratory wave form with a “breath hold” pause after each inspiration. Specifically, the second generation of the tree was successfully targeted, and deposition was increased by up to four times in generation 2 when compared to a ventilation without the breath hold (p < 0.0001). Breath hold was also demonstrated to facilitate deposition into blocked regions of the model, which mimic airway closure during an asthma that receive no flow during inhalation. Additionally, visualization experiments demonstrated that in the absence of fluid flow, the deposition of 3-micron water droplets is dominated by gravity, which, to our knowledge, has not been confirmed under standard laboratory conditions.



中文翻译:

屏气促进气雾化液滴在 3D 打印分叉气道树中的目标沉积。

长期以来,肺部一直被认为是药物递送的理想途径,但仍然缺乏合理靶向递送部位的策略,尤其是在存在异质气道疾病的情况下。此外,还没有提出标准化系统来快速测试不同的通气策略以及它们如何改变气道中的整体和区域沉积模式。在这项研究中,开发了一种 3D 打印的对称分叉树模型,模仿了人类呼吸道树的一部分,可用于量化不同递送方法的区域沉积模式。该模型以一种新颖的方式构建,允许使用可重复使用的部件重复测量区域沉积。在通气期间,雾化的约 3 微米大小的液滴被输送到模型中。区域配送,通过精确称重单个气道进行量化,具有高度可重复性。通过将吸气波形与每次吸气后的“屏气”暂停相结合,实现了控制区域沉积的成功策略。具体来说,树的第二代被成功定位,与没有屏气的通风相比,第二代的沉积物增加了四倍。p < 0.0001)。还证明屏气有助于沉积到模型的阻塞区域,模拟哮喘期间气道闭合,吸入期间没有气流。此外,可视化实验表明,在没有流体流动的情况下,3 微米水滴的沉积主要受重力影响,据我们所知,这在标准实验室条件下尚未得到证实。

更新日期:2020-09-22
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