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Structural identifiability analysis of a cardiovascular system model.

Antoine Pironet1, Pierre C Dauby1, J Geoffrey Chase2

  • 1University of Liège (ULg), GIGA-In Silico Medicine, Liège, Belgium.

Medical Engineering & Physics
|March 14, 2016
PubMed
Summary
This summary is machine-generated.

The six-chamber cardiovascular system model is identifiable using mixed pressure and volume data. This ensures unique parameter identification from limited datasets, making the model suitable for clinical diagnosis.

Keywords:
IdentifiabilityLumped-parameter modelParameter identificationPhysiological model

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Area of Science:

  • Cardiovascular Physiology
  • Mathematical Modeling
  • Systems Biology

Background:

  • The Burkhoff and Tyberg six-chamber cardiovascular system model is widely used.
  • Previous studies indicated issues with model identifiability from output data.

Purpose of the Study:

  • To address structural non-identifiability in the six-chamber cardiovascular model.
  • To demonstrate global structural identifiability using a mixed pressure-volume dataset.

Main Methods:

  • Presented cases of structural non-identifiability with single-output data (pressure or volume).
  • Utilized a mixed pressure and volume output dataset with limited clinical measurements.
  • Manipulated model equations to prove global structural identifiability.

Main Results:

  • Established global structural identifiability for the six-chamber cardiovascular model.
  • Demonstrated identifiability even with simplified assumptions (known cardiac valve resistances).
  • Confirmed parameter values are theoretically unique from well-chosen datasets.

Conclusions:

  • The six-chamber cardiovascular model is identifiable with specific, limited datasets.
  • Parameter identification is reliable, supporting the model's use in diagnosis.
  • The model's suitability for diagnostic applications is enhanced.