Vascular elasticity detection and evaluation system

Abstract

The invention discloses a vascular elasticity detection and evaluation system, the system comprises a stress detection module and a control analysis module, the control analysis module is in communication connection with the stress detection module, and the stress detection module is used for determining stress data; and the control analysis module is used for evaluating the elasticity of the blood vessel according to the stress data. The artery blood vessel elasticity can be evaluated more accurately, and the health state of a user can be detected and evaluated better.

Description

Technical Field

[0001] The present invention relates to the technical field of vascular elasticity detection, and in particular to a vascular elasticity detection and evaluation system. Background Art

[0002] Vascular shear stress refers to the force exerted by blood flow on the vessel wall. It is a key parameter in the study of intravascular hemodynamics. The shear force on the vessel wall is related to blood flow and blood viscosity. Blood flow is the liquid in the blood vessels, which has characteristics such as volume, flow rate and viscosity. When blood flows through the blood vessels, it generates a certain amount of force and energy. These forces and energies can act on the vessel wall. This action can be pressure or shear force. When blood flows horizontally, it generates horizontal shear force, which is called shear stress. Shear stress is very important for maintaining normal vascular physiological function. It can affect the morphology, growth and function of blood vessels. Shear stress can also regulate cell proliferation, differentiation, adhesion and migration. Vascular endothelial cells are the cells closest to the blood flow in the vessel wall. When blood flows through the blood vessels, the shear stress between the blood flow and the endothelial cells is a direct measure of blood flow shear. Under the action of blood flow shear stress, endothelial cells release a series of signal substances, such as growth factors, hormones and inflammatory factors, which can regulate vascular physiology. Low shear stress is usually one of the characteristics of vascular pathology. Low shear stress may cause deformation and functional impairment of vascular endothelial cells, thereby triggering the occurrence of cardiovascular diseases. On the other hand, high shear stress can increase the mechanical stability and anatomical morphology of blood vessels. In the body, high shear stress is usually caused by vascular stenosis, which causes the same volume of blood to flow through a smaller channel. There is a close connection between vascular shear stress and vascular elasticity. Therefore, how to determine vascular elasticity through vascular stress and better detect and evaluate the user's health status has become an urgent problem to be solved. Summary of the invention

[0003] The present invention provides a vascular elasticity detection and evaluation system, which can more accurately evaluate the elasticity of arterial blood vessels and better detect and evaluate the health status of users.

[0004] To achieve the above object, the present invention provides the following solutions: A blood vessel elasticity detection and evaluation system includes a stress detection module and a control analysis module, wherein the control analysis module is communicatively connected to the stress detection module, the stress detection module is used to determine stress data, and the control analysis module is used to evaluate the elasticity of the blood vessel according to the stress data.

[0005] Optionally, the stress detection module includes an ultrasonic measurement unit, which is used to perform ultrasonic imaging of the blood vessel at the target position along the long-axis section or the transverse-axis section to obtain an ultrasonic image, and to stimulate the blood vessel wall through the acoustic radiation force triggered by the electrocardiogram signal so that the blood vessel wall excites a guided wave signal, and the signal is collected to obtain an ultrasonic imaging sequence.

[0006] Optionally, the stress detection module includes a data processing unit, which is used to identify the ultrasound imaging sequence to obtain the blood vessel radius and the blood vessel wall thickness, extract the space-time velocity field of the guided wave signal in the ultrasound imaging sequence, obtain the actual dispersion curve of the guided wave from the space-time velocity field, and invert the blood vessel material parameters and stress based on the blood vessel radius, the blood vessel wall thickness and the actual dispersion curve to obtain the blood vessel stress data.

[0007] Optionally, the ultrasound measurement unit includes an ultrasound probe, an ultrasound host and an ultrasound system, the ultrasound probe is used to perform ultrasound imaging of the blood vessels at the target location along the long axis section; the ultrasound host includes a radio frequency receiving end, a radio frequency transmitting end and a focused acoustic radiation force end, which are used to generate and emit acoustic radiation force, excite the blood vessel wall, and receive the excited guided wave signal; the ultrasound system is used to trigger the ultrasound host to generate acoustic radiation force with an electrocardiogram signal.

[0008] Optionally, the evaluating the elasticity of the blood vessel according to the stress data specifically includes: Acquiring a stress data set and a vascular elasticity data set of a blood vessel, wherein the vascular elasticity data set is determined by a pulse wave data set; Input the stress data set as input data and the vascular elasticity data set as output data into a neural network model for training and optimization to obtain a vascular elasticity prediction model; The stress data is input into the vascular elasticity prediction model to predict and evaluate the vascular elasticity.

[0009] Optionally, the vascular elasticity dataset is determined by a pulse wave dataset, and the specific formula is as follows: p=kh3 / h1+a Among them, p is the vascular elasticity coefficient, k is the correction coefficient, a is the correction constant, h1 is the main wave amplitude, and h3 is the pre-dicrotic wave amplitude.

[0010] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects: The present invention provides a vascular elasticity detection and evaluation system, which includes a stress detection module and a control analysis module, wherein the control analysis module is in communication connection with the stress detection module, the stress detection module is used to determine stress data, and the control analysis module is used to evaluate the elasticity of the blood vessel according to the stress data. The present invention can more accurately evaluate the elasticity of arterial blood vessels and better detect and evaluate the health status of users. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0012] Figure 1 It is a schematic diagram of the composition of the vascular elasticity detection and evaluation system of the present invention; Figure 2 is the amplitude and time value of the pulse diagram. DETAILED DESCRIPTION

[0013] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0014] The present invention provides a vascular elasticity detection and evaluation system, which can more accurately evaluate the elasticity of arterial blood vessels and better detect and evaluate the health status of users.

[0015] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0016] Figure 1 FIG. 1 is a schematic diagram of the composition of the vascular elasticity detection and evaluation system of the present invention. Figure 1 As shown, a vascular elasticity detection and evaluation system includes a stress detection module 1 and a control analysis module 2, wherein the control analysis module 2 is communicatively connected with the stress detection module 1, the stress detection module 1 is used to determine stress data, and the control analysis module 2 is used to evaluate the elasticity of the blood vessel according to the stress data.

[0017] The stress detection module 1 includes an ultrasonic measurement unit, which is used to perform ultrasonic imaging of the blood vessel at the target position along the long axis section or the transverse axis section to obtain an ultrasonic image, and to stimulate the blood vessel wall through the acoustic radiation force triggered by the electrocardiogram signal so that the blood vessel wall excites a guided wave signal, and the signal is collected to obtain an ultrasonic imaging sequence.

[0018] The stress detection module 1 includes a data processing unit, which is used to identify the ultrasound imaging sequence to obtain the blood vessel radius and the blood vessel wall thickness, extract the space-time velocity field of the guided wave signal in the ultrasound imaging sequence, obtain the actual dispersion curve of the guided wave from the space-time velocity field, and invert the blood vessel material parameters and stress based on the blood vessel radius, the blood vessel wall thickness and the actual dispersion curve to obtain the blood vessel stress data.

[0019] The ultrasonic measurement unit includes an ultrasonic probe, an ultrasonic host and an ultrasonic system. The ultrasonic probe is used to perform ultrasonic imaging of the blood vessels at the target position along the long axis section; the ultrasonic host includes a radio frequency receiving end, a radio frequency transmitting end and a focused acoustic radiation force end, which are used to generate and emit acoustic radiation force, excite the blood vessel wall, and receive the excited guided wave signal; the ultrasonic system is used to trigger the ultrasonic host to generate acoustic radiation force with an electrocardiogram signal.

[0020] The evaluating the elasticity of the blood vessel according to the stress data specifically includes: Step 101: Acquire a stress dataset and a vascular elasticity dataset of a blood vessel, wherein the vascular elasticity dataset is determined by a pulse wave dataset; Step 102: inputting the stress data set as input data and the vascular elasticity data set as output data into a neural network model for training and optimization to obtain a vascular elasticity prediction model; Step 103: Input the stress data into the vascular elasticity prediction model to predict and evaluate the vascular elasticity.

[0021] The vascular elasticity dataset is determined by the pulse wave dataset, and the specific formula is as follows: p=kh3 / h1+a Among them, p is the vascular elasticity coefficient, k is the correction coefficient, a is the correction constant, h1 is the main wave amplitude, and h3 is the pre-dicrotic wave amplitude.

[0022] The vascular characteristic parameters include: main wave amplitude, main wave gorge amplitude, pre-dicrotic wave amplitude, descending gorge amplitude, dicrotic wave amplitude, and the time value from the pulse wave starting point to each peak and trough point; the main wave amplitude and pre-dicrotic wave amplitude are selected as the main parameters of the vascular elasticity system to calculate the elasticity coefficient of the blood vessel.

[0023] Figure 2 is the amplitude and time value of the pulse diagram, Figure 2The amplitude of the pulse wave includes: The main wave amplitude h1 is the height from the main wave peak to the pulse wave baseline (when the baseline is parallel to the time axis), which reflects the ejection function of the left ventricle and the compliance of the large arteries. That is, when the left ventricle has strong contractility and the large artery has good compliance, h1 is high, otherwise it is small. The main wave gorge amplitude h2 is the amplitude of a trough between the main wave and the pre-dicrotic wave. Its physiological significance is consistent with h3. It can often be ignored in pulse chart analysis and reflects the elasticity of arterial vessels and the state of peripheral resistance. The amplitude of the pre-dicrotic wave h3 is the height from the pre-dicrotic wave peak to the pulse wave baseline, which reflects the elasticity of the arterial blood vessels and the state of peripheral resistance. If the arterial blood vessels have high wall tension, or hardening, or increased peripheral resistance, the h3 amplitude may increase. The elevation of the pre-dicrotic wave is generally accompanied by an advance in its phase, reflecting the increase in the conduction velocity of the pulse reflection wave when the arterial blood vessels are in a state of high tension and high resistance.

[0024] The amplitude of the descending gorge, h4, is the height from the bottom of the descending gorge to the baseline of the pulse wave graph, reflecting the size of the peripheral resistance of the arterial vessels. When the peripheral resistance increases, h4 increases; otherwise, it decreases.

[0025] The amplitude of the dicrotic wave h5 is the height between the base line parallel to the bottom of the descending canyon and the peak of the dicrotic wave, which reflects the elasticity of the aorta and the function of the aortic valve. When the compliance of the aorta decreases, h5 decreases, or when the aortic valve is sclerotic or incomplete, h5 can be 0 (the peak of the dicrotic wave is at the same level as the bottom of the descending canyon), or even a negative value (the peak of the dicrotic wave is lower than the bottom of the descending canyon).

[0026] Figure 2 The pulsation phase includes: The time value from the pulse graph starting point to the main wave peak point is t1; The time value t2 between the starting point of the pulse graph and the main wave gorge; The time value t3 between the starting point of the pulse graph and the pre-dicrotic wave; The time value between the starting point of the pulse chart and the descending isthmus is t4, which corresponds to the contraction period of the left ventricle; The time value t5 between Jiangzhongxia and the end point of the pulse graph corresponds to the diastole period of the left ventricle.

[0027] t is the time value from the start point to the end point of the pulse graph. It corresponds to a cardiac cycle of the left ventricle, also known as the pulsation cycle. However, when atrial fibrillation or extrasystole occurs, the cardiac cycle of the pulse graph and the electrocardiogram are not completely consistent.

[0028] With the changes of physiological factors such as peripheral vascular resistance, vascular wall elasticity and blood viscosity, the waveform characteristics of the human pulse wave will show a series of regular changes. For young healthy people with low peripheral resistance and good vascular wall elasticity, the ascending and descending branches of the pulse wave are steeper, forming a high and sharp main wave. Due to the low velocity of the reflected wave, the pre-dicrotic wave is not obvious, and the blood reflux impacts the aortic valve with a large fluctuation intensity, making the peak and trough of the dicrotic wave very obvious. With the increase of age, the peripheral resistance increases and the elasticity of the vascular wall deteriorates. The velocity of the reflected wave gradually increases, making the tidal wave from inconspicuous to obvious, and its position relative to the main wave gradually increases, approaching the main wave from back to front, and merging to varying degrees, even exceeding the main wave. At the same time, the position of the peak and trough of the dicrotic wave relative to the main wave is also gradually raised, and it is difficult to distinguish them as they are mixed together, making the entire pulse wave waveform present a steamed bun shape change. It can be seen that the pulse wave waveform is first reflected in the regular dynamic changes of the pre-dicrotic wave height with the increase of age and the deterioration of cardiovascular physiological and pathological factors. When arterial elasticity decreases, the height of the pre-dicrotic wave gradually increases from low to high and approaches the main wave. Its height is an important objective indicator reflecting the elasticity of the blood vessel wall clinically, and this has been fully confirmed by animal experiments and clinical tests.

[0029] The present invention also includes a display module 3 and a power supply module 4. The display module 3 is communicatively connected to the control and analysis module 2. The power supply module 4 is electrically connected to the control and analysis module 2, the display module 3 and the stress detection module 1 respectively. The display module 3 is used to display the measured stress to the user and to feed back the analysis and evaluation results. In addition to the above-mentioned display module 3 and power supply module, the present invention can also integrate functional modules such as human-computer interaction, posture detection, and Bluetooth communication.

[0030] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0031] The principles and implementation methods of the present invention are described in this article using specific examples. The description of the above embodiments is only used to help understand the method and core idea of ​​the present invention. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A vascular elasticity detection and evaluation system, characterized in that: The system includes a stress detection module and a control analysis module, wherein the control analysis module is in communication with the stress detection module, the stress detection module is used to determine stress data, and the control analysis module is used to evaluate the elasticity of the blood vessel according to the stress data.

2. The vascular elasticity detection and evaluation system according to claim 1, characterized in that: The stress detection module includes an ultrasonic measurement unit, which is used to perform ultrasonic imaging of the blood vessel at the target position along the long axis section or the transverse axis section to obtain an ultrasonic image, and to stimulate the blood vessel wall through the acoustic radiation force triggered by the electrocardiogram signal so that the blood vessel wall excites a guided wave signal, and the signal is collected to obtain an ultrasonic imaging sequence.

3. The vascular elasticity detection and evaluation system according to claim 2, characterized in that: The stress detection module includes a data processing unit, which is used to identify the ultrasound imaging sequence to obtain the blood vessel radius and the blood vessel wall thickness, extract the space-time velocity field of the guided wave signal in the ultrasound imaging sequence, obtain the actual dispersion curve of the guided wave from the space-time velocity field, and invert the blood vessel material parameters and stress based on the blood vessel radius, the blood vessel wall thickness and the actual dispersion curve to obtain the blood vessel stress data.

4. The vascular elasticity detection and evaluation system according to claim 3, characterized in that: The ultrasonic measurement unit includes an ultrasonic probe, an ultrasonic host and an ultrasonic system. The ultrasonic probe is used to perform ultrasonic imaging of the blood vessels at the target position along the long axis section; the ultrasonic host includes a radio frequency receiving end, a radio frequency transmitting end and a focused acoustic radiation force end, which are used to generate and emit acoustic radiation force, excite the blood vessel wall, and receive the excited guided wave signal; the ultrasonic system is used to trigger the ultrasonic host to generate acoustic radiation force with an electrocardiogram signal.

5. The vascular elasticity detection and evaluation system according to claim 1, characterized in that: The evaluating the elasticity of the blood vessel according to the stress data specifically includes: Acquiring a stress data set and a vascular elasticity data set of a blood vessel, wherein the vascular elasticity data set is determined by a pulse wave data set; Input the stress data set as input data and the vascular elasticity data set as output data into a neural network model for training and optimization to obtain a vascular elasticity prediction model; The stress data is input into the vascular elasticity prediction model to predict and evaluate the vascular elasticity.

6. The vascular elasticity detection and evaluation system according to claim 5, characterized in that: The vascular elasticity dataset is determined by the pulse wave dataset, and the specific formula is as follows: p=kh3 / h1+a Among them, p is the vascular elasticity coefficient, k is the correction coefficient, a is the correction constant, h1 is the main wave amplitude, and h3 is the pre-dicrotic wave amplitude.

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