The respiratory system is one of the major interfaces between the body and the external environment. As a result, it can become a target for a broad range of environmental agents that can lead to increased morbidity and mortality. The medical field has also exploited the respiratory system/air interface as a way for either targeting drug delivery to specific regions of the respiratory tract or to provide rapid access to the systemic circulation for drugs that may not be effectively administered by other means. Furthermore, various diseases, such as COPD, or interstitial lung disease, can alter the structure and function of the respiratory system and dramatically affect how airborne agents or drugs are inhaled, deposited, or absorbed. Computational models that can effectively predict the dosimetry and ultimately the consequences of exposure to airborne agents under healthy or disease conditions in either animals or humans do not exist. As a result, this Bioengineering Research Partnership is developing the imaging and computational tools necessary for constructing and validating state-of-the-art, biologically based, multi-scale computational models of the respiratory system that incorporates the inherent species differences and heterogeneities in structure and functional relationships and the influence of disease on airflows and dosimetry predictions. In this way, computational predictions can be more rigorously tested and have a broader impact on human health risk assessments and therapeutic interventions. In light of increasing interest in nanomaterials for medical applications as well as concerns over potential human health risks, our model validation studies will focus on particulates utilizing our novel 3D imaging approaches.
Our specific aims are therefore organized around model development, experimental evaluation, and model refinement to predict: a) site-specific airflows in health rats (Aim 1);b) site-specific airflows in rats with interstitial lung disease and COPD (Aim 2);c) aerosol deposition in healthy and diseased rats (Aim 3);and d) aerosol deposition in healthy and diseased humans (Aim 4). Ultimately, we expect to deliver realistic, comprehensive, predictive models of the respiratory system that incorporate the inherent heterogeneities in anatomy, physiology, and disease. In addition, this effort will provide researchers and clinicians with a unique suite of imaging and computational tools for understanding species-specific pulmonary structure-function relationships and their effects on particle deposition and clearance.

Public Health Relevance

This project will impact human health through the development of realistic, computational models of the respiratory system that improves our understanding of disease-induced changes in airflow heterogeneities that impact aerosol deposition in rats and humans. Such models will improve human health risk assessments for environmental exposures and methods for drug delivery. This project will also produce novel, quantitative 3D imaging methods for respiratory anatomy, airflows, and nanoparticles in living systems and a suite of computational tools for image processing, mesh generation/refinement, and a multi-scale computational framework that includes bi-directional coupling of 3D computational fluid dynamics models with lower dimensional models of tissue properties and particle tracking.

National Institute of Health (NIH)
National Heart, Lung, and Blood Institute (NHLBI)
Research Project (R01)
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Special Emphasis Panel (ZRG1-SBIB-V (50))
Program Officer
Gan, Weiniu
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Battelle Pacific Northwest Laboratories
United States
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Jacob, Richard E; Carson, James P (2014) Automated measurement of heterogeneity in CT images of healthy and diseased rat lungs using variogram analysis of an octree decomposition. BMC Med Imaging 14:1
Kuprat, A P; Kabilan, S; Carson, J P et al. (2013) A Bidirectional Coupling Procedure Applied to Multiscale Respiratory Modeling. J Comput Phys 244:
Jacob, Richard E; Murphy, Mark K; Creim, Jeffrey A et al. (2013) Detecting radiation-induced injury using rapid 3D variogram analysis of CT images of rat lungs. Acad Radiol 20:1264-71
Freed, Alan D; Einstein, Daniel R (2013) An Implicit Elastic Theory for Lung Parenchyma. Int J Eng Sci 62:31-47
Schroeter, Jeffry D; Asgharian, Bahman; Price, Owen T et al. (2013) Computational fluid dynamics simulations of inhaled nano- and microparticle deposition in the rhesus monkey nasal passages. Inhal Toxicol 25:691-701
Einstein, Daniel R; Kuprat, Andrew P; Jiao, Xiangmin et al. (2013) An efficient algorithm for mapping imaging data to 3D unstructured grids in computational biomechanics. Int J Numer Method Biomed Eng 29:1-16
Jacob, Richard E; Carson, James P; Thomas, Mathew et al. (2013) Dynamic multiscale boundary conditions for 4D CT of healthy and emphysematous rats. PLoS One 8:e65874
Glenny, Robb W; Bauer, Christian; Hofmanninger, Johannes et al. (2013) Heterogeneity and matching of ventilation and perfusion within anatomical lung units in rats. Respir Physiol Neurobiol 189:594-606
Jacob, Richard E; Colby, Sean M; Kabilan, Senthil et al. (2013) In situ casting and imaging of the rat airway tree for accurate 3D reconstruction. Exp Lung Res 39:249-57
Neradilek, Moni B; Polissar, Nayak L; Einstein, Daniel R et al. (2012) Branch-based model for the diameters of the pulmonary airways: accounting for departures from self-consistency and registration errors. Anat Rec (Hoboken) 295:1027-44

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