Understanding lung function and disease through mathematical modeling and experiment

Wednesday, June 16 at 05:45pm (PDT)
Thursday, June 17 at 01:45am (BST)
Thursday, June 17 09:45am (KST)

SMB2021 SMB2021 Follow Wednesday (Thursday) during the "MS15" time block.
Note: this minisymposia has multiple sessions. The second session is MS14-CBBS (click here).

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Uduak George (San Diego State University, United States), Mona Eskandari (University of California Riverside, United Staes)


The COVID-19 pandemic and its impact on respiratory system has highlighted the exigent needs to research pulmonary mechanics. This mini-symposium aims to showcase some recent studies using mathematical models to examine lung development, normal lung function, diseased lung conditions and functional deterioration. These research explorations provide insights to diseases such as asthma, tuberculosis, cystic fibrosis and treatment of lung infection. They have also advanced pulmonary tissue characterization and understanding of age related alterations in lung function. Lung diseases often leads to reduced lung function and poor quality of life and mathematical models can provide excellent avenues to unravel the complex dynamics that orchestrate lung decline in various health conditions. The models employed in these works cut across different areas of mathematical and computational mathematics, including reaction-diffusion models, partial differential equation models, agent-based models, image-based analyses, mechanics, morphoelasticity etc.

Ariel Nikas

(Emory University, School of Medicine, United States)
"Using morphoelasticity to model early lung branching"
Morphoelasticity, an emerging area of continuum mechanics, can describe the large strains of organogenesis. We apply this framework modeling lung branching. Many previous models of lung branching morphogenesis were focused on the complex morphogen signaling systems and either omit explicit modeling of shape change, or model shape change by moving a surface normal to itself without explicit mechanics equations. Previous models have shown that morphogen flux distribution corresponds to the location of branching, and that this distribution is reliant on local geometry. We explicitly modeled both the morphogen signaling and the resulting growth dependent on the calculated morphogen flux distribution, in a novel application of morphoelastic shell modeling for lung growth. We concluded that local geometry affects the resulting shape change. Specifically, we observed tubule lengthening for all local geometries and shouldering for epithelium of elliptical cross-section. We also observed that the thickness of the epithelium affects the resulting shape change. This modeling approach of shell mechanics combined with morphoelasticity allowed us to test complex hypotheses on growth and can be generalized for many other organ systems.

Mona Eskandari

(University of California at Riverside, United States)
"Characterizing pulmonary mechanics using an experimental-computational framework"
COVID-19 has driven respiratory biomechanics to the forefront. Classified now as an endemic, investigative pulmonary research using computational biomechanical models is central to gaining predictive insights regarding fundamental lung physiology. The complex and hierarchical structure of the lung challenges advancements, given the bulk mechanical behavior representation is disconnected from its local tissue response. We address this knowledge gap by introducing the first structural inverse finite element model of the breathing lung using a reduced order surface representation. Using a custom-designed apparatus to imitate inflation and deflation in the ex-vivo lung, we interface the system with large deformation digital image correlation capabilities to ultimately link local strains to inflation volumes and pressures, compounding the role of the intricate bronchial network, parenchymal tissue, and visceral pleura behavior. An optimized heterogenous and hyperelastic continuum model employing adjoint methods accurately captures the experimentally observed topological lung surface strain distributions for varying pressure levels. This novel multiscale framework can facilitate in-silico explorations to improve ventilation strategies and examine how chronic disease endurance modifies the lung's load-bearing biomechanics.

Ramana Pidaparti

(University Of Georgia Athens, United States)
"Computational Models and Informatics for Lung Inflammation and Aging"
At Design Informatics and Computational Engineering (DICE) laboratory in the College of Engineering at UGA, quantitative analysis through airway lung models and informatics, computations and imaging data that correlates to inflammation, disease and aging is being conducted. A multi-scale model for cellular inflammation was developed for compliant lung geometry under mechanical ventilation by investigating respiratory mechanics at the organ, tissue and cellular levels. The cluster analysis of lung simulation data revealed that the clusters of airway strain data are correlated to airflow characteristics. The results from the inflammation model indicated that for the strain conditions considered, the model is capable of predicting the innate healing capacity of the tissue. Overall, the airway mechanical characteristics as well as lung function are compromised (about 40%-50%) due to aging. This talk provides an overview of the research at DICE lab in the College of Engineering at the University of Georgia.

Uduak George

(San Diego State University, United States)
"Mathematical modeling of fibroblast growth factor expression in developing lungs"
Fibroblast growth factor 10 (Fgf10) is a key regulator of lung development. Fgf10 is expressed at the sub-mesothelium, distal to the branching epithelial structures. Despite enormous progress in understanding the mechanisms that control lung development, the factors that determine the spatio-temporal expressions of Fgf10 are not well understood. In this study, we implemented a novel method to study Fgf10 expression at the lung mesothelium by using a system of surface reaction-diffusion equations. Numerical approximation of the equations was carried out by using the surface finite element method. Simulations of Fgf10 expression were done on murine lungs segmented from three-dimensional confocal microscopy images. Our simulation results reproduced some of the reported Fgf10 expression patterns from wet lab experiments available in the literature. The model identified the rate of reaction of Fgf10 and Fgf10 inhibitors as a possible key parameter in the regulation of Fgf10 expression. It also identified the size of the lung mesothelium, as a possible regulator of Fgf10 expression during murine lung morphogenesis.

Hosted by SMB2021 Follow
Virtual conference of the Society for Mathematical Biology, 2021.