Modeling the relative impact of capsular tissue effects on implanted glucose sensor time lag and signal attenuation.

Anal Bioanal Chem

Department of Biomedical Engineering, Duke University, 136 Hudson Hall, Box 90281, Durham, NC 27708, USA.

Published: October 2010

AI Article Synopsis

  • A mathematical model was developed to understand why implanted glucose sensors lag behind actual blood glucose levels in terms of response time and peak readings.
  • The model used physiological data regarding tissue properties, such as capsule thickness and vessel density, to simulate how glucose moves from the blood to the sensor.
  • Results showed that capsule thickness significantly impacts the time lag of the sensor, while vessel density and capsule porosity most affect the concentration of glucose detected by the sensor.

Article Abstract

Little is known mechanistically about why implanted glucose sensors lag behind blood glucose levels in both the time to peak sensor response and the magnitude of peak sensor response. A mathematical model of glucose transport from capillaries through surrounding tissue to the sensor surface was constructed to address how different aspects of the tissue affect glucose transport to an implanted sensor. Physiologically relevant values of capsule diffusion coefficient, capsule porosity, cellular glucose consumption, capsule thickness, and subcutaneous vessel density were used as inputs to create simulated sensor traces that mimic experimental instances of time lag and concentration attenuation relative to a given blood glucose profile. Using logarithmic sensitivity analysis, each parameter was analyzed to study the effect of these variables on both lag and attenuation. Results identify capsule thickness as the strongest determinant of sensor time lag, while subcutaneous vessel density and capsule porosity had the largest effects on attenuation of glucose that reaches the sensor surface. These findings provide mechanistic insight for the rational design of sensor modifications that may alleviate the deleterious consequences of tissue effects on implanted sensor performance.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2966551PMC
http://dx.doi.org/10.1007/s00216-010-4097-6DOI Listing

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