Automated computer-assisted quantitative analysis of intact murine lungs at the alveolar scale
(2017) In PLoS ONE 12(9).- Abstract
Using state-of-the-art X-ray tomographic microscopy we can image lung tissue in three dimensions in intact animals down to a micrometer precision. The structural complexity and hierarchical branching scheme of the lung at this level of details, however, renders the extraction of biologically relevant quantities particularly challenging. We have developed a methodology for a detailed description of lung inflation patterns by measuring the size and the local curvature of the parenchymal airspaces. These quantitative tools for morphological and topological analyses were applied to high-resolution murine 3D lung image data, inflated at different pressure levels under immediate post mortem conditions. We show for the first time direct... (More)
Using state-of-the-art X-ray tomographic microscopy we can image lung tissue in three dimensions in intact animals down to a micrometer precision. The structural complexity and hierarchical branching scheme of the lung at this level of details, however, renders the extraction of biologically relevant quantities particularly challenging. We have developed a methodology for a detailed description of lung inflation patterns by measuring the size and the local curvature of the parenchymal airspaces. These quantitative tools for morphological and topological analyses were applied to high-resolution murine 3D lung image data, inflated at different pressure levels under immediate post mortem conditions. We show for the first time direct indications of heterogeneous intra-lobar and inter-lobar distension patterns at the alveolar level. Furthermore, we did not find any indication that a cyclic opening- and-collapse (recruitment) of a large number of alveoli takes place.
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- author
- Lovric, Goran ; Vogiatzis Oikonomidis, Ioannis ; Mokso, Rajmund LU ; Stampanoni, Marco ; Roth-Kleiner, Matthias and Schittny, Johannes C.
- organization
- publishing date
- 2017-09-01
- type
- Contribution to journal
- publication status
- published
- subject
- in
- PLoS ONE
- volume
- 12
- issue
- 9
- article number
- e0183979
- publisher
- Public Library of Science (PLoS)
- external identifiers
-
- pmid:28934236
- scopus:85029697455
- ISSN
- 1932-6203
- DOI
- 10.1371/journal.pone.0183979
- language
- English
- LU publication?
- yes
- id
- 83e7b3e0-4047-4615-b97f-0c95c860db4c
- date added to LUP
- 2018-01-25 08:53:01
- date last changed
- 2025-01-08 04:16:32
@article{83e7b3e0-4047-4615-b97f-0c95c860db4c,
abstract = {{<p>Using state-of-the-art X-ray tomographic microscopy we can image lung tissue in three dimensions in intact animals down to a micrometer precision. The structural complexity and hierarchical branching scheme of the lung at this level of details, however, renders the extraction of biologically relevant quantities particularly challenging. We have developed a methodology for a detailed description of lung inflation patterns by measuring the size and the local curvature of the parenchymal airspaces. These quantitative tools for morphological and topological analyses were applied to high-resolution murine 3D lung image data, inflated at different pressure levels under immediate post mortem conditions. We show for the first time direct indications of heterogeneous intra-lobar and inter-lobar distension patterns at the alveolar level. Furthermore, we did not find any indication that a cyclic opening- and-collapse (recruitment) of a large number of alveoli takes place.</p>}},
author = {{Lovric, Goran and Vogiatzis Oikonomidis, Ioannis and Mokso, Rajmund and Stampanoni, Marco and Roth-Kleiner, Matthias and Schittny, Johannes C.}},
issn = {{1932-6203}},
language = {{eng}},
month = {{09}},
number = {{9}},
publisher = {{Public Library of Science (PLoS)}},
series = {{PLoS ONE}},
title = {{Automated computer-assisted quantitative analysis of intact murine lungs at the alveolar scale}},
url = {{http://dx.doi.org/10.1371/journal.pone.0183979}},
doi = {{10.1371/journal.pone.0183979}},
volume = {{12}},
year = {{2017}},
}