How are systemic vascular resistance (SVR) and aortic (arterial) compliance derived using LiDCO and PiCCO cardiac output monitors?

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Last updated: September 15, 2026 • View editorial policy

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How SVR and Aortic Compliance are Derived in LiDCO and PiCCO Monitors

Both LiDCO and PiCCO systems calculate systemic vascular resistance (SVR) using the standard hemodynamic formula (SVR = [MAP - CVP] / CO × 80), while aortic compliance is derived through pulse contour analysis algorithms that analyze the arterial pressure waveform characteristics.

Systemic Vascular Resistance (SVR) Calculation

Both monitoring systems derive SVR through the same fundamental approach:

  • Standard hemodynamic formula: SVR = (Mean Arterial Pressure - Central Venous Pressure) / Cardiac Output × 80
  • The constant 80 converts units to dynes·sec·cm⁻⁵
  • Requires three measured/calculated inputs:
    • Mean arterial pressure (MAP) from the arterial catheter
    • Central venous pressure (CVP) from central line
    • Cardiac output (CO) from their respective measurement techniques

The key difference lies in how each system measures cardiac output 1:

  • PiCCO: Uses transpulmonary thermodilution as the primary method, injecting cold fluid centrally and measuring temperature changes via a thermistor in the arterial catheter (typically femoral) 2, 1
  • LiDCO: Uses lithium dilution or pulse power analysis to calibrate its pulse contour algorithm 3

Aortic (Arterial) Compliance Derivation

Compliance estimation is more complex and differs between systems:

Pulse Contour Analysis Method

Both systems analyze the arterial pressure waveform to estimate compliance through mathematical modeling:

  • Windkessel model application: The systems use variations of the Windkessel model (typically 2- or 3-element) that represents the arterial system as characteristic impedance, arterial compliance, and systemic vascular resistance 4, 5
  • Dynamic time constant: Compliance is derived from the relationship between systemic vascular resistance and the arterial pressure decay during diastole 4
  • Pressure-area relationships: Algorithms incorporate age-dependent aortic pressure-area relationships to estimate compliance from the arterial waveform characteristics 5

PiCCO-Specific Approach

  • Integrates compliance estimation with its pulse contour analysis algorithm
  • Uses the calibrated thermodilution cardiac output to improve accuracy of derived parameters 1
  • Recalibration through repeated thermodilution measurements adjusts for changes in arterial tone 1

LiDCO-Specific Approach

  • Analyzes pulse power (area under the systolic portion of the arterial waveform) 3
  • The system interprets the arterial wave morphology to estimate vascular properties including compliance 3

Important Clinical Caveats

Reliability concerns with changing arterial tone: Both systems' pulse contour-derived parameters become less reliable when arterial tone changes significantly, particularly during vasoactive drug administration 6. This is why:

  • PiCCO requires recalibration via repeated thermodilution when hemodynamic conditions change substantially 1
  • LiDCO requires recalibration via lithium dilution or may use uncalibrated algorithms with reduced accuracy 6

Compliance is an estimated, not directly measured parameter: Unlike cardiac output (which can be directly measured via thermodilution in PiCCO), compliance is always a calculated/modeled value based on arterial waveform analysis and mathematical assumptions about the arterial system 4, 5.

The 2025 ESICM guidelines note that while transpulmonary thermodilution (PiCCO) and pulse wave analysis systems provide valuable hemodynamic data, their derived parameters should be interpreted within the context of their limitations, particularly during states of changing vascular tone 6.

References

1
Research

The PiCCO monitor: a review.

Anaesthesia and intensive care, 2012

2
Research

[Hemodynamic monitoring: PiCCO system].

Enfermeria intensiva, 2008

4
Research

Dynamic Estimation of Cardiovascular State From Arterial Blood Pressure Recordings.

IEEE transactions on bio-medical engineering, 2024

5
Research

Computation of aortic flow from pressure in humans using a nonlinear, three-element model.

Journal of applied physiology (Bethesda, Md. : 1985), 1993

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