
The lung physiome: merging imaging‐based measures with predictive computational models
Author(s) -
Tawhai Merryn H.,
Hoffman Eric A.,
Lin ChingLong
Publication year - 2009
Publication title -
wiley interdisciplinary reviews: systems biology and medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.087
H-Index - 51
eISSN - 1939-005X
pISSN - 1939-5094
DOI - 10.1002/wsbm.17
Subject(s) - computational model , computer science , lung function , atlas (anatomy) , machine learning , artificial intelligence , data science , medicine , lung , anatomy
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. Copyright © 2009 John Wiley & Sons, Inc. This article is categorized under: Analytical and Computational Methods > Computational Methods Models of Systems Properties and Processes > Organ, Tissue, and Physiological Models Translational, Genomic, and Systems Medicine > Translational Medicine