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Multiscale modeling of metabolism, flows, and exchanges in heterogeneous organs
Author(s) -
Bassingthwaighte James B.,
Raymond Gary M.,
Butterworth Erik,
Alessio Adam,
Caldwell James H.
Publication year - 2010
Publication title -
annals of the new york academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.712
H-Index - 248
eISSN - 1749-6632
pISSN - 0077-8923
DOI - 10.1111/j.1749-6632.2009.05090.x
Subject(s) - modular design , computer science , computation , region of interest , image resolution , positron emission tomography , biological system , blood flow , image (mathematics) , algorithm , biomedical engineering , computer vision , nuclear medicine , radiology , biology , medicine , operating system
Large‐scale models accounting for the processes supporting metabolism and function in an organ or tissue with a marked heterogeneity of flows and metabolic rates are computationally complex and tedious to compute. Their use in the analysis of data from positron emission tomography (PET) and magnetic resonance imaging (MRI) requires model reduction since the data are composed of concentration–time curves from hundreds of regions of interest (ROI) within the organ. Within each ROI, one must account for blood flow, intracapillary gradients in concentrations, transmembrane transport, and intracellular reactions. Using modular design, we configured a whole organ model, GENTEX, to allow adaptive usage for multiple reacting molecular species while omitting computation of unused components. The temporal and spatial resolution and the number of species are adaptable and the numerical accuracy and computational speed is adjustable during optimization runs, which increases accuracy and spatial resolution as convergence approaches. An application to the interpretation of PET image sequences after intravenous injection of 13 NH 3 provides functional image maps of regional myocardial blood flows.