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The lung physiome: merging imaging-based measures with predictive computational models
Journal article   Open access

The lung physiome: merging imaging-based measures with predictive computational models

Merryn H Tawhai, Eric A Hoffman and Ching-Long Lin
Wiley interdisciplinary reviews. Systems biology and medicine, Vol.1(1), pp.61-72
07/2009
DOI: 10.1002/wsbm.17
PMCID: PMC2943868
PMID: 20835982
url
https://doi.org/10.1002/wsbm.17View
Published (Version of record) Open Access

Abstract

Global measurements of the lung provided by standard pulmonary function tests do not give insight into the regional basis of lung function and lung disease. Advances in imaging methodologies, computer technologies, and subject-specific simulations are creating new opportunities to study structure-function relationships in the lung through multidisciplinary research. The digital Human Lung Atlas is an image-based resource compiled from male and female subjects spanning several decades of age. The Atlas comprises both structural and functional measures, and includes computational models derived to match individual subjects for personalized prediction of function. The computational models in the Atlas form part of the Lung Physiome project, which is an international effort to develop integrative models of lung function at all levels of biological organization. The computational models provide mechanistic interpretation of imaging measures; the Atlas provides structural data on which to base model geometry, and functional data against which to test hypotheses. The example of simulating airflow on a subject-specific basis is considered. Methods for deriving multiscale models of the airway geometry for individual subjects in the Atlas are outlined, and methods for modeling turbulent flows in the airway are reviewed.
Diagnostic Imaging Animals Models, Biological Humans Computational Biology Female Male Sheep Lung - physiology Lung - anatomy & histology Models, Anatomic

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