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Estimation of organ transport function for recirculating indicator dilution curves
G Sparacino1, R Bonadonna, H Steinberg
1Department of Electronics and Informatics, University of Padova, Italy.
Annals of Biomedical Engineering
|June 4, 1999
Summary
This study introduces a new deconvolution method to accurately measure how substances move through human leg muscle, even with recirculation. This helps calculate key physiological parameters vital for understanding diseases like diabetes.
Area of Science:
- Physiology
- Biomedical Engineering
- Pharmacokinetics
Background:
- Estimating physiological parameters from indicator transport is crucial but challenging, especially with recirculation.
- Accurate measurement of indicator transport function is vital for studying metabolic diseases.
Purpose of the Study:
- To develop and validate a novel deconvolution-based method for estimating the transport function of 3H-mannitol in human leg skeletal muscle.
- To simultaneously determine organ plasma flow, mean transit time, and distribution volume.
- To assess the reliability of the method using Monte Carlo simulations.
Main Methods:
- Administered an indicator bolus (3H-mannitol) into the femoral artery.
- Nonuniformly sampled indicator dilution curves in the femoral artery and vein to account for recirculation.
- Applied a new deconvolution technique for simultaneous estimation of transport function and plasma flow.
Main Results:
- Successfully estimated the transport function of 3H-mannitol in human leg skeletal muscle.
- Simultaneously calculated organ plasma flow, mean transit time, and extracellular distribution volume.
- Monte Carlo simulations confirmed the reliability of the developed method.
Conclusions:
- The novel deconvolution method accurately estimates indicator transport function and physiological parameters in the presence of recirculation.
- This technique provides critical insights into mean transit time and extracellular distribution volume.
- The findings are essential for advancing the study of pathophysiologic states like diabetes, insulin resistance, and hypertension.