Estimation of central pulse wave velocity from radial pulse wave analysis
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Published on: February 7, 2014
Yang Yao1, Shuran Zhou2, Jordi Alastruey3
1School of Information Science and Technology, ShanghaiTech University, Shanghai, 201210, China; College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, Liaoning 110169, China.
Insights
A new method estimates arterial stiffness using radial pulse waves, offering a practical alternative to carotid-femoral pulse wave velocity (cfPWV) measurements for cardiovascular disease risk assessment.
Area of Science:
- Cardiovascular Physiology
- Biomedical Engineering
- Medical Diagnostics
Background:
- Arterial stiffness, measured by carotid-femoral pulse wave velocity (cfPWV), is a key cardiovascular disease biomarker.
- Current cfPWV measurement is clinically impractical for routine use.
- Radial artery pulse wave analysis offers a convenient alternative for assessing arterial stiffness.
Purpose of the Study:
- To identify specific pulse wave features from a single radial pulse waveform.
- To develop accurate models for estimating cfPWV using these features.
- To establish a convenient surrogate for cfPWV measurement.
Main Methods:
- Recorded radial pulse waveforms and measured cfPWV in 140 subjects.
- Extracted time, frequency, and wave-separated features from radial waveforms.
- Utilized all-possible regressions, McHenry's select algorithm, and support vector regression for cfPWV estimation.
Main Results:
- Achieved high correlations between measured and estimated cfPWV (r=0.81, 0.81, 0.80).
- Identified physiologically interpretable features, including the diastolic peak to notch amplitude ratio (Rn,dr,P).
- Confirmed Rn,dr,P correlation with cfPWV, independent of wave reflections in simulated data (n=3,325).
Conclusions:
- The proposed radial pulse wave analysis method serves as a convenient surrogate for cfPWV.
- The feature Rn,dr,P is significantly associated with aortic pulse wave velocity.
- This association may be independent of wave reflection phenomena.
Background And Objective:
Arterial stiffness, commonly assessed by carotid-femoral pulse wave velocity (cfPWV), is an independent biomarker for cardiovascular disease. The measurement of cfPWV, however, has been considered impractical for routine clinical application. Pulse wave analysis using a single pulse wave measurement in the radial artery is a convenient alternative. This study aims to identify pulse wave features for a more accurate estimation of cfPWV from a single radial pulse wave measurement.
Methods:
From a dataset of 140 subjects, cfPWV was measured and the radial pulse waveform was recorded for 30 s twice in succession. Features were extracted from the waveforms in the time and frequency domains, as well as by wave separation analysis. All-possible regressions with bootstrapping, McHenry's select algorithm, and support vector regression were applied to compute models for cfPWV estimation.
Results:
The correlation coefficients between the measured and estimated cfPWV were r = 0.81, r = 0.81, and r = 0.8 for all-possible regressions, McHenry's select algorithm, and support vector regression, respectively. The features selected by all-possible regressions are physiologically interpretable. In particular, the amplitude ratio of the diastolic peak to the notch of the radial pulse waveform (Rn,dr,P) is shown to be correlated with cfPWV. This correlation was further evaluated and found to be independent of wave reflections using a dataset (n = 3,325) of simulated pulse waves.
Conclusions:
The proposed method may serve as a convenient surrogate for the measurement of cfPWV. Rn,dr,P is associated with aortic pulse wave velocity and this association may not be dependent on wave reflection.
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