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Related Experiment Videos

Computation of diagnostic data from coronary sinus pressure: a comparison between two possible models.

W Schreiner1, F Neumann, J Schuster

  • 1Second Surgical Department, University of Vienna, Austria.

Journal of Biomedical Engineering
|November 1, 1989
PubMed
Summary

Two mathematical models for coronary sinus pressure (CSP) during intermittent coronary sinus occlusion (PICSO) were compared. One model excels in investigation, while another offers stability for closed-loop regulation.

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Area of Science:

  • Cardiovascular physiology
  • Mathematical modeling
  • Medical device regulation

Background:

  • Coronary sinus pressure (CSP) monitoring is crucial for cardiovascular interventions.
  • Pressure controlled intermittent coronary sinus occlusion (PICSO) requires accurate physiological modeling.
  • Evaluating mathematical models for CSP changes during PICSO is essential for clinical application.

Purpose of the Study:

  • To evaluate and compare two mathematical models describing CSP increase during PICSO.
  • To determine the suitability of each model for investigational and regulatory purposes.
  • To assess the physiological relevance of model-derived parameters.

Main Methods:

  • Non-linear least squares algorithms were used to fit two mathematical models to human and canine CSP data.

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  • Derived quantities (plateau, rise-time, mean integral) were calculated from model parameters.
  • Model performance was compared based on mean values, successful calculation rates, and species-specific features.

    • Main Results:

    • One model demonstrated superiority for investigational use.
    • The second model exhibited greater stability in critical situations, making it suitable for closed-loop PICSO regulation.
    • Physiological differences between models were negligible, with statistical significance arising from large data volumes.

    Conclusions:

    • The choice of mathematical model for CSP during PICSO depends on the intended application (investigation vs. regulation).
    • The stable model is recommended for closed-loop control systems in PICSO.
    • Model-derived physiological insights are consistent across both evaluated models.