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. 2023 Aug 20;10(8):985.
doi: 10.3390/bioengineering10080985.

Study of the Relationship between Pulmonary Artery Pressure and Heart Valve Vibration Sound Based on Mock Loop

Jiachen Mi  1   2 , Zehang Zhao  1 , Hongkai Wang  1 , Hong Tang  1   3
Affiliations

Study of the Relationship between Pulmonary Artery Pressure and Heart Valve Vibration Sound Based on Mock Loop

Jiachen Mi et al. Bioengineering (Basel). .

Abstract

The vibration of the heart valves' closure is an important component of the heart sound and contains important information about the mechanical activity of a heart. Stenosis of the distal pulmonary artery can lead to pulmonary hypertension (PH). Therefore, in this paper, the relationship between the vibration sound of heart valves and the pulmonary artery blood pressure was investigated to contribute to the noninvasive detection of PH. In this paper, a lumped parameter circuit platform of pulmonary circulation was first set to guide the establishment of a mock loop of circulation. By adjusting the distal vascular resistance of the pulmonary artery, six different pulmonary arterial pressure states were achieved. In the experiment, pulmonary artery blood pressure, right ventricular blood pressure, and the vibration sound of the pulmonary valve and tricuspid valve were measured synchronously. Features of the time domain and frequency domain of two valves' vibration sound were extracted. By conducting a significance analysis of the inter-group features, it was found that the amplitude, energy and frequency features of vibration sounds changed significantly. Finally, the continuously varied pulmonary arterial blood pressure and valves' vibration sound were obtained by continuously adjusting the resistance of the distal pulmonary artery. A backward propagation neural network and deep learning model were used, respectively, to estimate the features of pulmonary arterial blood pressure, pulmonary artery systolic blood pressure, the maximum rising rate of pulmonary artery blood pressure and the maximum falling rate of pulmonary artery blood pressure by the vibration sound of the pulmonary and tricuspid valves. The results showed that the pulmonary artery pressure parameters can be well estimated by valve vibration sounds.

Keywords: backward propagation neural network; heart valve vibration sound; mock loop circulation; pulmonary artery pressure; pulmonary hypertension.

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Conflict of interest statement

The authors declare no potential conflict of interest with respect to the research, authorship and/or publication of this article.

Figures

Figure 1
Figure 1
P-V loop of right ventricle.
Figure 2
Figure 2
Simulated hemodynamics of pulmonary circulation. (a) Key pulmonary blood pressures; (b) corresponding blood flows of (a). P: blood pressure; I: blood flow; rv: right ventricle; pap: proximal pulmonary artery; pv: pulmonary veins.
Figure 3
Figure 3
P-V loops of right ventricle caused by DPAS. The different colours lines mean the progress of DPAS. The red and blue colours lines indicate normal and sever DPAS.
Figure 4
Figure 4
Pressure signal of pulmonary artery and right ventricle.
Figure 5
Figure 5
Typical waveform of pulmonary arterial pressure in 6 experiments.
Figure 6
Figure 6
Results of difference in pairs between groups of tricuspid valve vibration. Green color indicates self relationship within the group, dark blue color indicates significant differences between the two groups, and yellow color indicates no significant differences between the two groups.
Figure 7
Figure 7
Boxplot of 8 tricuspid valve vibration characteristics in 6 experiments.
Figure 8
Figure 8
Results of difference in pairs between groups of pulmonary valve vibration. Green color indicates self relationship within the group, dark blue color indicates significant differences between the two groups, and yellow color indicates no significant differences between the two groups.
Figure 9
Figure 9
Boxplot of 8 pulmonary valve vibration characteristics in 6 experiments.
Figure 10
Figure 10
Scatter plot of predicted and measured values.
Figure 11
Figure 11
Scatter plot of predicted and measured values.
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