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Wave reflection quantification analysis and personalized flow wave estimation based on the central aortic pressure

Hongming Sun1, Yang Yao2, Wenyan Liu1

  • 1College of Medicine and Biological and Information Engineering, Northeastern University, Shenyang, China.

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|March 13, 2023
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Summary
This summary is machine-generated.

This study introduces a novel method to estimate aortic flow waveforms from central aortic pressure waveforms, improving cardiovascular monitoring. This personalized approach accurately calculates wave reflection indices, offering a convenient alternative to direct flow measurement.

Keywords:
arterial stiffnesspersonalized flow waveformtriangular flow waveformwave reflectionwave separation analysis

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Area of Science:

  • Cardiovascular Physiology
  • Biomedical Engineering
  • Medical Signal Processing

Background:

  • Pulse wave reflections are crucial indicators of cardiovascular status, reflecting cardiac afterload and perfusion.
  • Accurate quantification of these reflections necessitates aortic flow waveform measurement, which is often invasive and requires specialized expertise.
  • Existing methods for estimating aortic flow waveforms have limitations in accuracy and convenience.

Purpose of the Study:

  • To develop and validate a personalized method for estimating aortic flow waveforms from central aortic pressure waveforms (CAPW).
  • To assess the accuracy of this personalized method in calculating wave reflection indices (e.g., reflection index [RI], reflection magnitude [RM]) and pulse transit time (PTT).
  • To compare the performance of the personalized method against traditional triangular and lognormal flow waveform methods.

Main Methods:

  • Estimated personalized aortic flow waveforms using pressure-flow relations derived from individual CAPWs.
  • Separated forward and backward pressure waves to compute wave reflection indices and PTT.
  • Validated the method using clinical data (13 participants) and the Nektar1D Pulse Wave Database (4,374 subjects).
  • Performed statistical analyses to compare the personalized method with triangular and lognormal flow waveform methods.

Main Results:

  • The personalized flow waveform approach demonstrated a lower root mean square error compared to triangular and lognormal methods.
  • Higher correlation coefficients were observed between the personalized method's estimated flow waveform and measured flow waveforms.
  • The personalized method accurately estimated wave reflection indices, outperforming the other two methods.

Conclusions:

  • The personalized aortic flow waveform method provides a more accurate estimation of wave reflection indices than traditional methods.
  • This technique offers a convenient and potentially non-invasive alternative for measuring aortic flow waveforms.
  • The findings support the potential clinical utility of this personalized approach for cardiovascular monitoring.