Synchrotron-based micro-CT imaging of the human lung acinus

基于同步辐射的微型CT成像技术对人肺泡进行成像

阅读:1

Abstract

Structural data about the human lung fine structure are mainly based on stereological methods applied to serial sections. As these methods utilize 2D images, which are often not contiguous, they suffer from inaccuracies which are overcome by analysis of 3D micro-CT images of the never-sectioned specimen. The purpose of our study was to generate a complete data set of the intact three-dimensional architecture of the human acinus using high-resolution synchrotron-based micro-CT (synMCT). A human lung was inflation-fixed by formaldehyde ventilation and then scanned in a 64-slice CT over its apex to base extent. Lung samples (8-mm diameter, 10-mm height, N = 12) were punched out, stained with osmium tetroxide, and scanned using synMCT at (4 μm)(3) voxel size. The lung functional unit (acinus, N = 8) was segmented from the 3D tomographic image using an automated tree-analysis software program. Morphometric data of the lung were analyzed by ANOVA. Intra-acinar airways branching occurred over 11 generations. The mean acinar volume was 131.3 ± 29.2 mm(3) (range, 92.5-171.3 mm(3)) and the mean acinar surface was calculated with 1012 ± 26 cm(2). The airway internal diameter (starting from the bronchiolus terminalis) decreases distally from 0.66 ± 0.04 mm to 0.34 ± 0.06 mm (P < 0.001) and remains constant after the seventh generation (P < 0.5). The length of each generation ranges between 0.52 and 0.93 mm and did not show significant differences between the second and eleventh generation. The branching angle between daughter branches varies between 113-degree and 134-degree without significant differences between the generations (P < 0.3). This study demonstrates the feasibility of quantitating the 3D structure of the human acinus at the spatial resolution readily achievable using synMCT.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。