Application-specific approaches to MicroCT for evaluation of mouse models of pulmonary disease.
Application-specific approaches to MicroCT for evaluation of mouse models of pulmonary disease.
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DOI：
10.1371/journal.pone.0281452
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发表时间：
2023
期刊：
影响因子：
3.7
通讯作者：
中科院分区：
文献类型：
--
作者：
微型计算机断层扫描（microCT）的出现为我们在小动物模型中生成肺健康和疾病的临床相关评估的能力提供了重大进步。随着microCT在肺部临床前模型中用于生成结果分析的使用增加，图像质量和分辨率以及数据分析软件都有了实质性的改善。然而，有有限的标准化成像和自动化分析方法可供研究者使用。显微CT图像的手动定量分析因存在炎症和实质疾病而变得复杂。为了提高效率和限制用户相关的偏差，我们开发了一个自动肺空气和组织分割（PATS）任务列表，以分割肺空气体积和肺组织体积进行定量分析。我们使用四种不同的成像方法证明了PATS任务列表的有效使用，1）使用FlexiVent的体内呼吸控制扫描，2）在脂多糖、博来霉素和二氧化硅暴露引发的正在消退和未消退肺部疾病中的纵向呼吸门控体内扫描，3）死后成像，以及4）离体高分辨率扫描。将PATS任务列表的准确性与手动分割进行比较。这些成像技术和自动量化方法在肺损伤和纤维化的多个模型中的使用证明了microCT对各种肺部疾病和小动物模型的广泛适用性和适应性，并在肺部研究领域的临床前microCT成像和分析的效率和标准化方面取得了重大进展。
The advent of micro-computed tomography (microCT) has provided significant advancement in our ability to generate clinically relevant assessments of lung health and disease in small animal models. As microCT use to generate outcomes analysis in pulmonary preclinical models has increased there have been substantial improvements in image quality and resolution, and data analysis software. However, there are limited published methods for standardized imaging and automated analysis available for investigators. Manual quantitative analysis of microCT images is complicated by the presence of inflammation and parenchymal disease. To improve the efficiency and limit user-associated bias, we have developed an automated pulmonary air and tissue segmentation (PATS) task list to segment lung air volume and lung tissue volume for quantitative analysis. We demonstrate the effective use of the PATS task list using four distinct methods for imaging, 1) in vivo respiration controlled scanning using a flexiVent, 2) longitudinal breath-gated in vivo scanning in resolving and non-resolving pulmonary disease initiated by lipopolysaccharide-, bleomycin-, and silica-exposure, 3) post-mortem imaging, and 4) ex vivo high-resolution scanning. The accuracy of the PATS task list was compared to manual segmentation. The use of these imaging techniques and automated quantification methodology across multiple models of lung injury and fibrosis demonstrates the broad applicability and adaptability of microCT to various lung diseases and small animal models and presents a significant advance in efficiency and standardization of preclinical microCT imaging and analysis for the field of pulmonary research.
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影响因子：
5.2
作者：
Eisenhauer, Philip;Earle, Benjamin;Loi, Roberto;Sueblinvong, Viranuj;Goodwin, Meagan;Allen, Gilman B.;Lundblad, Lennart;Mazan, Melissa R.;Hoffman, Andrew M.;Weiss, Daniel J.
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Weiss, Daniel J.
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Herzen, Julia
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Detombe, Sarah A.;Dunmore-Buyze, Joy;Drangova, Maria
通讯作者：
Drangova, Maria
影响因子：
3.7
作者：
McDonald, Lindsay T.;Johnson, Sara D.;LaRue, Amanda C.
通讯作者：
LaRue, Amanda C.
影响因子：
3.7
作者：
De Langhe E;Vande Velde G;Hostens J;Himmelreich U;Nemery B;Luyten FP;Vanoirbeek J;Lories RJ
通讯作者：
Lories RJ