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Cited by 76Pancreatic function and diabetesNumerical methods in inverse problemsControl Systems and Identification

A stochastic deconvolution method to reconstruct insulin secretion rate after a glucose stimulus

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Sparacino, G., Cobelli, C.·1996·IEEE Transactions on Biomedical Engineering
DOI 10.1109/10.488799
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Abstract

Insulin secretion rate (ISR) is not directly measurable in man but it can be reconstructed from C-peptide (CP) concentration measurements by solving an input estimation problem by deconvolution. The major difficulties posed by the estimation of ISR after a glucose stimulus, e.g., during an intravenous glucose tolerance test (IVGTT), are the ill-conditioning of the problem, the nonstationary pattern of the secretion rate, and the nonuniform/infrequent sampling schedule. In this work, a nonparametric method based on the classic Phillips-Tikhonov regularization approach is presented. The problem of nonuniform/infrequent sampling is addressed by a novel formulation of the regularization method which allows the estimation of quasi time-continuous input profiles. The input estimation problem is stated into a Bayesian context, where the a priori known nonstationary characteristics of ISR after the glucose stimulus are described by a stochastic model. Deconvolution is tackled by linear minimum variance estimation, thus allowing the derivation of new statistically based regularization criteria. Finally, a Monte-Carlo strategy is implemented to assess the uncertainty of the estimated ISR arising from CP measurement error and impulse response parameters uncertainty.

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  • Peripheral insulin concentrations do not represent insulin secretion but rather the sum of pancreatic insulin secretion, hepatic insulin extraction, and distribution into the circulating compartment.

    “However, peripheral insulin concentrations do not represent insulin secretion but rather the sum of pancreatic insulin secretion, hepatic insulin extraction, and distribution into the circulating compartment.”

    From A model of GLP-1 action on insulin secretion in nondiabetic subjects (2010) · cites this paper as [27]

    The Introduction says plasma insulin concentration reflects post-hepatic delivery into the circulation, not pancreatic secretion directly, because insulin undergoes substantial and variable liver extraction. It does not describe the concentration as a sum of secretion, extraction, and distribution, or separately explain a distribution component. (LLM, conf=0.85)

    Experimental — accuracy not yet measured

  • C-peptide and insulin are secreted in equimolar fashion and C-peptide is not extracted by the liver.

    “given that both are secreted in an equimolar fashion and C-peptide is not extracted by the liver.”

    From A model of GLP-1 action on insulin secretion in nondiabetic subjects (2010) · cites this paper as [27]

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Research works printed but not linked: 5

  1. G. De Nicolao and M. Rocchetti, "Stable and efficient techniques for the deconvolution of hormone time-series," in Computers in Endocrinology: RecentAdvances, G. Forti, V. Guardabasso, and D. Rodbard, Eds. New York: Raven, 1990, pp. 83-91. 1131
  2. G. De Nicolao, "Numerical deconvolution of physiological systems: A stochastic approach," in Proceedings of the IFAC Symposium on Modeling and Control in Biomedical Systems, Galveston, TX, B. W. Patterson, Ed.
  3. A. Pilo, E. Ferrannini, and R. Navalesi, "Measurement of glucose- induced delivery rate in man by deconvolution analysis," Am. J. Physiol., vol. 233, pp. E500-E508, 1977.
  4. G. Sparacino and C. Cobelli, "Impulse response model order affects reconstruction of insulin secretion rate by deconvolution. Influence of secretion rate spectral content, sampling frequency and impulse response input design," in Proceedings of the 3rd European Conference on Engineering and Medicine, Florence, Italy, A. Pedotti and P. Ra- bischong, Eds. Milano, Italy: Ed. Pro Juventute Don Gnocchi, 1995, p. 203.
  5. E. Van Cauter, F. Mestrez, J. Stuns, and K. S. Polonsky, "Estimation of insulin secretion rates from C-peptide levels," Diabetes, vol. 41, pp, 368-377, 1992. 1501

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Authors
Sparacino, G., & Cobelli, C.
Affiliations
University of Padua (IT)
ORCID
Venue
IEEE Transactions on Biomedical Engineering
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
1996-05
Volume
43
Issue
5
Pages
512-529
ISSN
0018-9294 (ISSN-L)
DOI
10.1109/10.488799
OpenAlex
W2062794144
Cited by
76
References
57
Citations by year
2026: 1 · 2025: 3 · 2024: 1 · 2023: 2 · 2021: 2 · 2020: 4 · 2019: 2 · 2018: 1 · 2016: 1 · 2015: 2 · 2013: 7 · 2012: 5
FWCI
4.57
Type
journal article
Language
en
Open access
Licence
Locations
  • IEEE Transactions on Biomedical Engineering (publishedVersion)
  • PubMed (publishedVersion)
  • Padua Research Archive (University of Padova) (submittedVersion, other-oa)
Funders
  • National Institutes of Health (5p41rr002176-11)
  • National Center for Research Resources (RR 02176)
Topics
  • Health Sciences › Medicine › Surgery › Pancreatic function and diabetes
  • Physical Sciences › Mathematics › Mathematical Physics › Numerical methods in inverse problems
  • Physical Sciences › Engineering › Control and Systems Engineering › Control Systems and Identification
Keywords
insulin secretion rate, C-peptide, deconvolution, input estimation, intravenous glucose tolerance test, ill-conditioned inverse problems, non-uniform sampling, Bayesian estimation, stochastic modeling, linear minimum variance estimation, Monte Carlo uncertainty analysis, measurement error
MeSH terms
Insulin Secretion, C-Peptide, Glucose, Glucose Tolerance Test, Humans, Insulin, Male, Models, Biological, Monte Carlo Method, Secretory Rate, Stimulation, Chemical, Stochastic Processes, Time Factors, Confidence Intervals, Least-Squares Analysis

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