Why the study?
While reduced-order models are recognized as effective tools for estimating cardiovascular system hemodynamic functions, practical personalized models are still lacking.
Does a personalized 0-1D coupled hemodynamic model accurately predict arterial pressure and flow velocity waveforms in healthy volunteers?
Does a personalized 0-1D coupled hemodynamic model accurately predict arterial pressure and flow velocity waveforms in healthy volunteers?
The proposed 0-1D personalized hemodynamic model efficiently and accurately predicts individualized pressure and flow waveforms, facilitating patient-specific assessment of cardiovascular function.
May support patient-specific hemodynamic assessment; leaves open prospective validation before clinical adoption.
OBJECTIVE: Personalization of hemodynamic modeling plays a crucial role in functional prediction of the cardiovascular system (CVS). While reduced-order models of one-dimensional (1D) blood vessel models with zero-dimensional (0D) blood vessel and heart models have been widely recognized to be an effective tool for reasonably estimating the hemodynamic functions of the whole CVS, practical personalized models are still lacking. In this paper, we present a novel 0-1D coupled, personalized hemodynamic model of the CVS that can predict both pressure waveforms and flow velocities in arteries. METHODS: We proposed a methodology by combining the multiscale CVS model with the Levenberg-Marquardt optimization algorithm for effectively solving an inverse problem based on measured blood pressure waveforms. Hemodynamic characteristics including brachial arterial pressure waveforms, artery diameters, stroke volumes, and flow velocities were measured noninvasively for 62 volunteers aged from 20 to 70 years for developing and validating the model. RESULTS: ; simulated blood flow velocity waveforms in carotid artery match ultrasound measurements well, achieving an average correlation coefficient of 0.911. CONCLUSION: The model is efficient, versatile, and capable of obtaining well-fitting individualized pressure waveforms while reasonably predicting flow waveforms. SIGNIFICANCE: The proposed methodology of personalized hemodynamic modeling may therefore facilitate individualized patient-specific assessment of both physiological and pathological functions of the CVS.
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Zhang et al. (2020) studied this question.
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