Automated computer-assisted quantitative analysis of intact murine lungs at the alveolar scale

Lovric, Goran; Vogiatzis Oikonomidis, Ioannis; Mokso, Rajmund; Stampanoni, Marco; Roth-Kleiner, Matthias; Schittny, Johannes (2017). Automated computer-assisted quantitative analysis of intact murine lungs at the alveolar scale. PLoS ONE, 12(9), e0183979. Public Library of Science 10.1371/journal.pone.0183979

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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.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Pre-clinic Human Medicine > Institute of Anatomy
04 Faculty of Medicine > Pre-clinic Human Medicine > Institute of Anatomy > Topographical and Clinical Anatomy

Graduate School:

Graduate School for Cellular and Biomedical Sciences (GCB)

UniBE Contributor:

Vogiatzis Oikonomidis, Ioannis and Schittny, Johannes

Subjects:

500 Science > 570 Life sciences; biology
600 Technology > 610 Medicine & health

ISSN:

1932-6203

Publisher:

Public Library of Science

Language:

English

Submitter:

Johannes Schittny

Date Deposited:

14 Dec 2017 09:19

Last Modified:

25 Oct 2019 07:17

Publisher DOI:

10.1371/journal.pone.0183979

PubMed ID:

28934236

BORIS DOI:

10.7892/boris.107421

URI:

https://boris.unibe.ch/id/eprint/107421

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