title: Modeling Plasma-to-Interstitium Glucose Kinetics from Multitracer Plasma and Microdialysis Data.
abstract: 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.
  
  
  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 11.0 min (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.
authors: 1 Department of Information Engineering, University of Padova , Padova, Italy .
authors: Michele
authors: M
authors: Schiavon
authors: 1 Department of Information Engineering, University of Padova , Padova, Italy .
authors: Chiara
authors: C
authors: Dalla Man
authors: 2 Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Department of Internal Medicine, Mayo Clinic and Foundation , Rochester, Minnesota.
authors: Simmi
authors: S
authors: Dube
authors: 2 Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Department of Internal Medicine, Mayo Clinic and Foundation , Rochester, Minnesota.
authors: Michael
authors: M
authors: Slama
authors: 2 Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Department of Internal Medicine, Mayo Clinic and Foundation , Rochester, Minnesota.
authors: Yogish C
authors: YC
authors: Kudva
authors: 3 IDDM Consulting , San Diego, California.
authors: Thomas
authors: T
authors: Peyser
authors: 2 Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Department of Internal Medicine, Mayo Clinic and Foundation , Rochester, Minnesota.
authors: Ananda
authors: A
authors: Basu
authors: 2 Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Department of Internal Medicine, Mayo Clinic and Foundation , Rochester, Minnesota.
authors: Rita
authors: R
authors: Basu
authors: 1 Department of Information Engineering, University of Padova , Padova, Italy .
authors: Claudio
authors: C
authors: Cobelli
mesh_terms: D000328:Adult; D001786:Blood Glucose / Q000032:analysis / Q000378:metabolism*; D015190:Blood Glucose Self-Monitoring / Q000379:methods; D003922:Diabetes Mellitus, Type 1 / Q000097:blood*; D045604:Extracellular Fluid / Q000378:metabolism*; D005215:Fasting / Q000378:metabolism; D005260:Female; D064368:Healthy Volunteers; D006801:Humans; D007700:Kinetics; D016014:Linear Models; D008297:Male; D017551:Microdialysis / Q000706:statistics & numerical data*; D008875:Middle Aged
chemical_list: D001786:Blood Glucose