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National Institute of Environmental Health Sciences

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Publication Detail

Title: A skeleton-tree-based approach to acinar morphometric analysis using microcomputed tomography with comparison of acini in young and old C57BL/6 mice.

Authors: Kizhakke Puliyakote, Abhilash S; Vasilescu, Dragoş M; Sen Sharma, Kriti; Wang, Ge; Hoffman, Eric A

Published In J Appl Physiol (1985), (2016 Jun 15)

Abstract: We seek to establish a method using interior tomographic techniques (Xradia MicroXCT-400) for acinar morphometric analysis using the pathway center lines from micro X-ray computed tomographic (Micro-CT) images as the road map. Through the application of these techniques, we present a method to extend the atlas of murine lungs to acinar levels and present a comparison between two age groups of the C57BL/6 strain. Lungs fixed via vascular perfusion were scanned using high-resolution Micro-CT protocols. Individual acini were segmented, and skeletonized paths to alveolar sacs from the entrance to the acinus were formed. Morphometric parameters, including branch lengths, diameters, and branching angles, were generated. Six mice each, at two age groups (∼20 and ∼90 wk of age), were studied. Additive Gaussian noise (0 mean and SD 1, 2, 5, and 10) was used to test the robustness of the analytical method. Noise-based variations were within ±6 μm for branch lengths and ±5 μm for diameters. At a noise level of 10, errors increased. Branch diameters were less susceptible to noise than lengths. There was >95% center line overlap across all noise levels. The measurements obtained using the center lines as a road map were not affected by added noise. Acini from younger mice had smaller branch diameters and lengths at all generations without significant differences in branching angles. The relative distribution of volume in the alveolar ducts was similar across both age groups. The method has been demonstrated to be repeatable and robust to image noise and provides a new, nondestructive technique to assess and compare acinar morphometry quantitatively.

PubMed ID: 26940656 Exiting the NIEHS site

MeSH Terms: No MeSH terms associated with this publication

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