Abstract
The knowledge of the time course of endogenous glucose production (EGP) after a glucose perturbation is crucially important for understanding the glucose regulation system in both healthy and disease (e.g. diabetes) states. EGP is not directly accessible, and thus an indirect measurement approach is required. The estimation of EGP during an intravenous glucose tolerance test (IVGTT) can be posed as an input estimation problem solvable as a Fredholm integral equation of the first kind (A. Caumo and C. Cobelli, Am. J. Physiol., 264 (1993) E829-E841). The time-varying model of the kernel of the glucose system was identified from a concomitant tracer experiment, and EGP was reconstructed by employing the Phillips-Tikhonov regularization (deconvolution) algorithm. However, the proposed deconvolution approach left some issues open, e.g. how to choose the amount of regularization and how to deal with nonuniform/infrequent sampling. Here, a solution to these problems is provided by resorting to a new deconvolution algorithm. Thanks to the stochastic embedding into which the new deconvolution method is stated, the amount of regularization is determined in a statistically sound manner. In addition, in face of infrequent sampling, a time continuous profile of EGP is obtained. The method is shown to work reliably for reconstructing EGP in different IVGTT experimental protocols, both in normal and disease states.
| Original language | English |
|---|---|
| Pages (from-to) | 147-156 |
| Number of pages | 10 |
| Journal | Computer Methods and Programs in Biomedicine |
| Volume | 52 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - Mar 1997 |
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Keywords
- input estimation
- intravenous glucose tolerance test
- mathematical model
- regularization
ASJC Scopus subject areas
- Software
Cite this
Estimation of endogenous glucose production after a glucose perturbation by nonparametric stochastic deconvolution. / Vicini, Paolo; Sparacino, Giovanni; Caumo, Andrea; Cobelli, Claudio.
In: Computer Methods and Programs in Biomedicine, Vol. 52, No. 3, 03.1997, p. 147-156.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Estimation of endogenous glucose production after a glucose perturbation by nonparametric stochastic deconvolution
AU - Vicini, Paolo
AU - Sparacino, Giovanni
AU - Caumo, Andrea
AU - Cobelli, Claudio
PY - 1997/3
Y1 - 1997/3
N2 - The knowledge of the time course of endogenous glucose production (EGP) after a glucose perturbation is crucially important for understanding the glucose regulation system in both healthy and disease (e.g. diabetes) states. EGP is not directly accessible, and thus an indirect measurement approach is required. The estimation of EGP during an intravenous glucose tolerance test (IVGTT) can be posed as an input estimation problem solvable as a Fredholm integral equation of the first kind (A. Caumo and C. Cobelli, Am. J. Physiol., 264 (1993) E829-E841). The time-varying model of the kernel of the glucose system was identified from a concomitant tracer experiment, and EGP was reconstructed by employing the Phillips-Tikhonov regularization (deconvolution) algorithm. However, the proposed deconvolution approach left some issues open, e.g. how to choose the amount of regularization and how to deal with nonuniform/infrequent sampling. Here, a solution to these problems is provided by resorting to a new deconvolution algorithm. Thanks to the stochastic embedding into which the new deconvolution method is stated, the amount of regularization is determined in a statistically sound manner. In addition, in face of infrequent sampling, a time continuous profile of EGP is obtained. The method is shown to work reliably for reconstructing EGP in different IVGTT experimental protocols, both in normal and disease states.
AB - The knowledge of the time course of endogenous glucose production (EGP) after a glucose perturbation is crucially important for understanding the glucose regulation system in both healthy and disease (e.g. diabetes) states. EGP is not directly accessible, and thus an indirect measurement approach is required. The estimation of EGP during an intravenous glucose tolerance test (IVGTT) can be posed as an input estimation problem solvable as a Fredholm integral equation of the first kind (A. Caumo and C. Cobelli, Am. J. Physiol., 264 (1993) E829-E841). The time-varying model of the kernel of the glucose system was identified from a concomitant tracer experiment, and EGP was reconstructed by employing the Phillips-Tikhonov regularization (deconvolution) algorithm. However, the proposed deconvolution approach left some issues open, e.g. how to choose the amount of regularization and how to deal with nonuniform/infrequent sampling. Here, a solution to these problems is provided by resorting to a new deconvolution algorithm. Thanks to the stochastic embedding into which the new deconvolution method is stated, the amount of regularization is determined in a statistically sound manner. In addition, in face of infrequent sampling, a time continuous profile of EGP is obtained. The method is shown to work reliably for reconstructing EGP in different IVGTT experimental protocols, both in normal and disease states.
KW - input estimation
KW - intravenous glucose tolerance test
KW - mathematical model
KW - regularization
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UR - http://www.scopus.com/inward/citedby.url?scp=0031106701&partnerID=8YFLogxK
U2 - 10.1016/S0169-2607(96)01784-1
DO - 10.1016/S0169-2607(96)01784-1
M3 - Article
C2 - 9051338
AN - SCOPUS:0031106701
VL - 52
SP - 147
EP - 156
JO - Computer Methods and Programs in Biomedicine
JF - Computer Methods and Programs in Biomedicine
SN - 0169-2607
IS - 3
ER -