Visualization of respiratory flows from 3D reconstructed alveolar airspaces using X-ray tomographic microscopy

Sznitman, J; Sutter, R; Altorfer, D; Stampanoni, M; Rösgen, T; Schittny, J.C. (2010). Visualization of respiratory flows from 3D reconstructed alveolar airspaces using X-ray tomographic microscopy. Journal of visualization, 13(4), pp. 337-345. Berlin: Springer 10.1007/s12650-010-0043-0

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A deeper knowledge of the three-dimensional (3D) structure of the pulmonary acinus has direct applications in studies on acinar fluid dynamics and aerosol kinematics. To date, however, acinar flow simulations have been often based on geometrical models inspired by morphometrical studies; limitations in the spatial resolution of lung imaging techniques have prevented the simulation of acinar flows using 3D reconstructions of such small structures. In the present study, we use high-resolution, synchrotron radiation-based X-ray tomographic microscopy (SRXTM) images of the pulmonary acinus of a mouse to reconstruct 3D alveolar airspaces and conduct computational fluid dynamic (CFD) simulations mimicking rhythmic breathing motion. Respiratory airflows and Lagrangian (massless) particle tracking are visualized in two examples of acinar geometries with varying size and complexity, representative of terminal sacculi including their alveoli. The present CFD simulations open the path towards future acinar flow and aerosol deposition studies in complete and anatomically realistic multi-generation acinar trees using reconstructed 3D SRXTM geometries.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Pre-clinic Human Medicine > Institute of Anatomy > Functional Anatomy

UniBE Contributor:

Schittny, Johannes

ISSN:

1343-8875

Publisher:

Springer

Language:

English

Submitter:

Factscience Import

Date Deposited:

04 Oct 2013 14:11

Last Modified:

05 Dec 2022 14:01

Publisher DOI:

10.1007/s12650-010-0043-0

Web of Science ID:

000283592700014

BORIS DOI:

10.48350/2025

URI:

https://boris.unibe.ch/id/eprint/2025 (FactScience: 204173)

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