Modeling Plasma-to-Interstitium Glucose Kinetics from Multitracer Plasma and Microdialysis Data

Michele Schiavon, Chiara Dalla Man, Simmi Dube, Michael Slama, Yogish C. Kudva, Thomas Peyser, Ananda Basu, Rita Basu, Claudio Cobelli

Research output: Contribution to journalArticlepeer-review

23 Scopus citations


Background: Quantitative assessment of the dynamic relationship between plasma and interstitial fluid (ISF) glucose and the estimation of the plasma-to-ISF delay are of major importance to determine the accuracy of subcutaneous glucose sensors, an essential component of open- and closed-loop therapeutic systems for type 1 diabetes mellitus (T1DM). The goal of this work is to develop a model of plasma-to-ISF glucose kinetics from multitracer plasma and interstitium data, obtained by microdialysis, in healthy and T1DM subjects, under fasting conditions. Materials and Methods: A specific experimental design, combining administration of multiple tracers with the microdialysis technique, was used to simultaneously frequently collect plasma and ISF data. Linear time-invariant compartmental modeling was used to describe glucose kinetics from the tracer data because the system is in steady state. Results: A two-compartment model was shown accurate and was identified from both plasma and ISF data. An "equilibration time" between plasma and ISF of 9.1 and 11.0min (median) in healthy and T1DM subjects, respectively, was calculated. Conclusions: We have demonstrated that, in steady-state condition, the glucose plasma-to-ISF kinetics can be modeled with a linear two-compartment model and that the "equilibration time" between the two compartments can be estimated with precision. Future studies will assess plasma-to-interstitium glucose kinetics during glucose and insulin perturbations in both healthy and T1DM subjects.

Original languageEnglish (US)
Pages (from-to)825-831
Number of pages7
JournalDiabetes Technology and Therapeutics
Issue number11
StatePublished - Nov 2015

ASJC Scopus subject areas

  • Endocrinology, Diabetes and Metabolism
  • Endocrinology
  • Medical Laboratory Technology


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