Literature DB >> 26592166

Modeling the Nonlinear Motion of the Rat Central Airways.

G Ibrahim, A Rona, S V Hainsworth.   

Abstract

Advances in volumetric medical imaging techniques allowed the subject-specific modeling of the bronchial flow through the first few generations of the central airways using computational fluid dynamics (CFD). However, a reliable CFD prediction of the bronchial flow requires modeling of the inhomogeneous deformation of the central airways during breathing. This paper addresses this issue by introducing two models of the central airways motion. The first model utilizes a node-to-node mapping between the discretized geometries of the central airways generated from a number of successive computed tomography (CT) images acquired dynamically (without breath hold) over the breathing cycle of two Sprague-Dawley rats. The second model uses a node-to-node mapping between only two discretized airway geometries generated from the CT images acquired at end-exhale and at end-inhale along with the ventilator measurement of the lung volume change. The advantage of this second model is that it uses just one pair of CT images, which more readily complies with the radiation dosage restrictions for humans. Three-dimensional computer aided design geometries of the central airways generated from the dynamic-CT images were used as benchmarks to validate the output from the two models at sampled time-points over the breathing cycle. The central airway geometries deformed by the first model showed good agreement to the benchmark geometries within a tolerance of 4%. The central airway geometry deformed by the second model better approximated the benchmark geometries than previous approaches that used a linear or harmonic motion model.

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Year:  2016        PMID: 26592166     DOI: 10.1115/1.4032051

Source DB:  PubMed          Journal:  J Biomech Eng        ISSN: 0148-0731            Impact factor:   2.097


  1 in total

1.  Effect of static vs. dynamic imaging on particle transport in CT-based numerical models of human central airways.

Authors:  Shinjiro Miyawaki; Eric A Hoffman; Ching-Long Lin
Journal:  J Aerosol Sci       Date:  2016-07-16       Impact factor: 3.433

  1 in total

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