An approach for detecting hemodynamic parameters in the carotid arterial system based on the priori relationship

Jin Wang1,2, Yong-Jiang Li1,2, Yu-Yuan Zhang1,2

  • 1Institute of Cardio-Cerebrovascular Medicine, Central Hospital of Dalian University of Technology, Dalian, 116033, People's Republic of China.

Insights

This study presents a novel framework for non-invasive vascular monitoring using common carotid artery (CCA) waveforms and modeling. It enables real-time assessment of hemodynamic parameters for early cardiovascular risk detection.

Area of Science:

  • Biomedical Engineering
  • Cardiovascular Physiology
  • Medical Imaging Analysis

Background:

  • Cardio-cerebrovascular diseases are leading global causes of death, largely due to atherosclerosis.
  • The common carotid artery (CCA) is crucial for understanding disease progression, with local hemodynamics (e.g., wall shear stress) and systemic indices (e.g., peripheral resistance) being key indicators.
  • Current imaging methods for quantifying these parameters are expensive, complex, and not suitable for continuous monitoring.

Purpose of the Study:

  • To develop a non-invasive framework for continuous vascular monitoring by integrating clinical CCA waveforms with a priori modeling.
  • To enable real-time estimation of local and systemic hemodynamic indices, including wall shear stress, resistance, and compliance.
  • To support early cardiovascular risk assessment through accessible vascular health monitoring.

Main Methods:

  • Developed a framework integrating clinically acquired CCA pressure and flow velocity waveforms with a priori modeling.
  • Established a pressure-arterial radius (p-r) relationship to estimate dynamic radius changes from continuous pressure signals.
  • Utilized a distributed-lumped parameter hybrid model to compute local and systemic hemodynamic indices.

Main Results:

  • The p-r model accurately reproduced arterial radius waveforms and demonstrated temporal stability over five weeks.
  • The hybrid model provided real-time estimates of local parameters (flow rate, WSS) and systemic indices (resistance, compliance).
  • Sensitivity analysis confirmed the influence of elastic parameter variations on hemodynamic outcomes.

Conclusions:

  • The developed framework offers a promising approach for continuous, non-invasive vascular monitoring.
  • This method facilitates real-time assessment of hemodynamic parameters, aiding in early cardiovascular risk stratification.
  • The integration of waveform analysis and modeling provides a cost-effective and accessible tool for vascular health assessment.

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