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Related Experiment Videos

Model-free numerical deconvolution of recirculating indicator concentration curves

A V Clough1, D Cui, J H Linehan

  • 1Department of Mathematics, Statistics, and Computer Science, Marquette University, Milwaukee 53233.

Journal of Applied Physiology (Bethesda, Md. : 1985)
|March 1, 1993
PubMed
Summary

This study presents two reliable model-free deconvolution methods for analyzing indicator concentration curves. These techniques accurately estimate circulation transport functions from simulated and real patient data.

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Area of Science:

  • Biomedical Engineering
  • Pharmacokinetics
  • Physiological Modeling

Background:

  • Recirculating indicator dilution curves are crucial for assessing physiological transport functions.
  • Accurate deconvolution is essential for reliable pharmacokinetic and physiological modeling.
  • Existing deconvolution methods may lack robustness or require model assumptions.

Purpose of the Study:

  • To investigate and validate two model-free numerical deconvolution methods for recirculating indicator concentration curves.
  • To assess the reliability and accuracy of damped least squares and discrete orthogonal polynomial deconvolution.
  • To propose methods for optimizing solutions and handling artifacts in transport function estimation.

Main Methods:

  • Application of damped least squares and discrete orthogonal polynomial deconvolution to simulated indicator dilution data.

Related Experiment Videos

  • Convolution of estimated transport functions with input curves to evaluate goodness-of-fit.
  • Testing methods for optimal solution identification and artifact truncation (e.g., oscillatory tails).
  • Validation using experimental indicator dilution data from pulmonary artery and left atrium.

    • Main Results:

    • Both deconvolution methods produced smooth and accurate transport function estimates on simulated data.
    • Estimated transport functions, when convolved, yielded good fits to simulated and experimental output curves.
    • Proposed optimization and truncation techniques allowed for reasonably accurate estimation of mean transit times and variances.
    • Methods demonstrated computational stability with real patient data.

    Conclusions:

    • Model-free damped least squares and discrete orthogonal polynomial deconvolution are reliable for analyzing recirculating indicator dilution curves.
    • The proposed methods facilitate accurate estimation of circulation transport functions, including mean transit times and variances.
    • These techniques offer a robust approach for both simulation-based research and clinical applications using indicator dilution data.