Title :
Modeling Nonsteady-State Metabolism From Arteriovenous Data
Author :
Manesso, Erica ; Toffolo, Gianna M. ; Basu, Rita ; Rizza, Robert A. ; Cobelli, Claudio
Author_Institution :
Dept. of Inf. Eng., Univ. of Padova, Padova, Italy
fDate :
5/1/2011 12:00:00 AM
Abstract :
The use of arteriovenous (AV) concentration differences to measure the production of a substance at organ/tissue level by Fick principle is limited to steady state. Out of steady state, there is the need, as originally proposed by Zierler, to account for the nonnegligible transit time of the substance through the system. Based on this theory, we propose a modeling approach that adopts a parametric description for production and transit time. Once the unknown parameters are estimated on AV data, the transition time of the substance can be assessed and production can be reconstructed. As a case study, we discuss the estimation of pancreatic insulin secretion during a meal from C-peptide concentrations measured in femoral artery and hepatic vein in 12 subjects. Results support the importance of accounting for nonnegligible transit times, even if C-peptide mean transit time across the splanchnic bed is rather limited (3.3 ± 1.3 min), it affects the estimation of pancreatic insulin secretion which shows a significantly different profile in the early portion of the postprandial period when estimated either with the novel modeling approach or with the simplified steady state equation.
Keywords :
biochemistry; blood vessels; haemodynamics; molecular biophysics; organic compounds; physiological models; C-peptide concentrations; C-peptide mean transit time; Fick principle; arteriovenous concentration differences; arteriovenous data; femoral artery; hepatic vein; nonnegligible transit time; nonsteady state metabolism modeling; pancreatic insulin secretion estimation; parametric description; postprandial period; splanchnic bed; Data models; Distribution functions; Insulin; Mathematical model; Strontium; Sugar; Arteriovenous (AV) measurements; beta cell function; insulin secretion; mean transit time; physiological model; Algorithms; Bayes Theorem; Blood Glucose; C-Peptide; Databases, Factual; Femoral Artery; Hepatic Veins; Humans; Insulin; Islets of Langerhans; Metabolic Networks and Pathways; Models, Biological;
Journal_Title :
Biomedical Engineering, IEEE Transactions on
DOI :
10.1109/TBME.2010.2096815