CN115804618B

CN115804618B - Stress measuring device, method and storage medium for human blood vessel

Info

Publication number: CN115804618B
Application number: CN202211604214.0A
Authority: CN
Inventors: 曹艳平; 江宇轩; 郑阳
Original assignee: Tsinghua University
Current assignee: Tsinghua University
Priority date: 2022-12-13
Filing date: 2022-12-13
Publication date: 2024-07-12
Anticipated expiration: 2042-12-13
Also published as: CN115804618A

Abstract

The application relates to the technical field of medical imaging, in particular to a stress measuring device, a method and a storage medium for human blood vessels, which comprise the following steps: the ultrasonic measurement module is used for carrying out ultrasonic imaging on a blood vessel at a target position along a long-axis tangential plane or a transverse-axis tangential plane, exciting the wall of the blood vessel by using acoustic radiation force triggered by electrocardiosignals to excite the blood vessel to obtain guided wave signals, and acquiring the signals to obtain an ultrasonic imaging sequence; the data processing module is used for recognizing the ultrasonic image to obtain the radius and the wall thickness of the blood vessel, extracting the space-time velocity field of the guided wave signal in the ultrasonic imaging sequence, obtaining the actual dispersion curve of the guided wave from the space-time velocity field, and inverting the parameters and the stress of the blood vessel based on the radius of the blood vessel, the wall thickness of the blood vessel and the actual dispersion curve to obtain the actual stress and the material property of the blood vessel. Therefore, the limitation caused by the fact that the system characterization of the nonlinear and viscoelastic properties of the blood vessel cannot be realized in the related technology is solved; the measuring stability of the vascular hoop stress is not high, the reliability is low, the operation is complex, and the like.

Description

Stress measuring device, method and storage medium for human blood vessel

Technical Field

The application relates to the technical field of medical imaging, in particular to a stress measuring device and method for human blood vessels and a storage medium.

Background

Related researches show that the lesions of the vascular wall and the lesions of the vascular wall develop into the direct causes of various cardiovascular complications such as myocardial infarction, apoplexy and the like, and the changes of arterial mechanical properties can be caused by the lesions of the vascular wall, so that the method has great significance in early screening and diagnosis of cardiovascular diseases in vivo measurement of the arterial mechanical properties.

Stress plays an important role in the growth and reconstruction of blood vessels because there are various forms of stress in blood vessels, including wall shear stress, hoop/axial normal stress within the wall, etc., cells in arteries (such as smooth muscle cells and endothelial cells) can experience stress, and a stress response to changes in stress by changing the homeostatic environment. Thus, non-invasive, in-vivo measurement of arterial stress is also a critical technique that is urgently needed to develop in the clinical and health arts.

In the related technology, in the aspect of characterization of mechanical properties of blood vessels, the elastic properties of arteries are mainly characterized, but the nonlinear characteristics and the viscoelastic characteristics of the blood vessels cannot be characterized, so that the analysis method has certain limitations, and the data precision of the existing analysis algorithm is low, the efficiency is low, and the clinical use is not facilitated; in the aspect of measuring vascular stress, mainly measuring vascular hoop stress, the method is limited by the limitation of measuring means and the complexity of testing conditions, so that the stability of the body side quantity of blood pressure is low, the operation is complex, and the method is not easy to widely use.

Disclosure of Invention

The application provides a stress measuring device, a method and a storage medium of a human blood vessel, which are used for solving the problem that the system characterization of the nonlinear and viscoelastic properties of the blood vessel cannot be realized in the related technology, so that the device has certain limitation; the measuring stability of the vascular hoop stress is not high, the reliability is low, the operation is complex, and the like.

An embodiment of a first aspect of the present application provides a stress measurement device for a human blood vessel, including: the ultrasonic measurement module is used for carrying out ultrasonic imaging on a blood vessel at a target position along a long-axis section or a transverse-axis section to obtain an ultrasonic image, exciting a blood vessel wall by using acoustic radiation force triggered by electrocardiosignals, so that the blood vessel wall excites a guided wave signal, and acquiring the signal to obtain an ultrasonic imaging sequence; the data processing module is used for identifying the ultrasonic image to obtain a blood vessel radius and a blood vessel wall thickness, extracting a space-time velocity field of a guided wave signal in the ultrasonic imaging sequence, acquiring an actual dispersion curve of the guided wave from the space-time velocity field, and inverting 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 actual stress and material properties of the blood vessel.

Optionally, the data processing module is further configured to: processing the ultrasonic imaging sequence by using a preset algorithm to obtain a particle velocity field; when imaging along the long axis section of the blood vessel, extracting a space-time velocity field of axial guided waves along the position of the central line of the upper wall of the blood vessel; when imaging along the transverse axis of the vessel, the space-time velocity field of the circumferential guided wave is extracted along the circular centerline position of the vessel cross section.

Optionally, the data processing module is further configured to: windowing the space-time velocity field to obtain a processed space-time velocity field; and performing two-dimensional Fourier transform on the processed space-time velocity field to obtain a spectrogram, and determining a dispersion curve of the guided wave based on extreme points of the spectrogram.

Optionally, the data processing module is further configured to: determining a vessel geometry from the vessel radius and the vessel wall thickness; determining a theoretical dispersion curve between the guided wave and the vascular geometry according to a preset mechanical model; and iteratively solving the actual dispersion curve and the theoretical dispersion curve through an optimization algorithm, taking an average value of parameters obtained by each iteration solution as an optimal vascular material parameter, and calculating the actual stress and the material property of the blood vessel based on the optimal vascular material parameter, wherein the optimization algorithm comprises a Newton iteration method, a simulated annealing method and a genetic algorithm.

Optionally, the theoretical dispersion curve includes a circumferential guided wave dispersion curve and/or an axial guided wave dispersion curve, where a calculation formula of the circumferential guided wave dispersion curve is:

c＝ω/Re(k)，

The calculation formula of the axial guided wave dispersion curve is as follows:

Wherein c represents a phase velocity, ω represents an angular frequency, k represents an angular wave number, and Re (k) represents a real part of k; c _a (ω) represents the dispersion relation of the phase velocity c _a of the axial guided wave with the change of the frequency ω, r represents the vessel radius, and n represents the circumferential wave number;

the relationship between ω and k is calculated from the following formula:

wherein s1 and s2 are solved by the following four-time equation:

Wherein, C _p ²＝κ_p/ρ^f,κ_p is the bulk modulus of water, ρ ^f is the density of water, t= (a _a+γ+α_c)/3,I represents the imaginary number of the unit,When solving the axial guided wave dispersion, alpha=alpha _a is taken, when solving the circumferential guided wave dispersion, alpha=alpha _c is taken, h=h/2 represents the half wall thickness, ρ is the blood vessel wall density, alpha _a,α_c, gamma and beta are tangential stiffness parameters of the blood vessel, and g and τ are viscoelasticity parameters of the blood vessel.

Optionally, the actual stress includes an axial stress and a hoop stress, where a calculation formula of the axial stress σ _a is:

σ_a＝α_a-γ

The calculation formula of the hoop stress sigma _c is as follows:

σ_c＝α_c-γ

Where α _a denotes the axial incremental stiffness (in Pa) of the blood vessel, α _c denotes the circumferential incremental stiffness (in Pa), and γ denotes another incremental stiffness coefficient (in Pa).

Optionally, the objective function of the optimization algorithm is:

Wherein, Representing the phase velocity measured by the experiment,The theoretical predicted phase velocity is represented by α, the incremental stiffness of the vessel (corresponding to α _a or α _c, respectively, for application to axial or circumferential guided waves), γ is another incremental stiffness parameter, g is the relaxation modulus of the viscoelasticity of the vessel, τ is the relaxation characteristic time, f _i represents the experimentally measured frequency, r represents the vessel radius, h represents the vessel wall thickness, and n represents the number of experimentally measured data points.

Optionally, the ultrasonic measurement module includes: the ultrasonic probe is used for carrying out ultrasonic imaging on the blood vessel at the target position along the long-axis section; the ultrasonic host comprises a radio frequency receiving end, a radio frequency transmitting end and a focused acoustic radiation force end, and is used for generating and transmitting acoustic radiation force, exciting the vessel wall and receiving the excited guided wave signal; and the ultrasonic system is used for triggering the ultrasonic host to generate acoustic radiation force by the electrocardiosignal.

An embodiment of the second aspect of the present application provides a stress measurement method for a human blood vessel, including the steps of: carrying out ultrasonic imaging on a blood vessel at a target position along a long-axis section or a transverse-axis section to obtain an ultrasonic image, exciting a blood vessel wall by using acoustic radiation force triggered by electrocardiosignals, so that the blood vessel wall excites a guided wave signal, and acquiring the signal to obtain an ultrasonic imaging sequence; and identifying the ultrasonic image to obtain a blood vessel radius and a blood vessel wall thickness, extracting a space-time velocity field of a guided wave signal in the ultrasonic imaging sequence, acquiring an actual dispersion curve of the guided wave from the space-time velocity field, and inverting 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 actual stress and material properties of the blood vessel.

Optionally, the extracting the space-time velocity field of the guided wave signal in the ultrasonic imaging sequence includes: processing the ultrasonic imaging sequence by using a preset algorithm to obtain a particle velocity field; when imaging along the long axis section of the blood vessel, extracting a space-time velocity field of axial guided waves along the position of the central line of the upper wall of the blood vessel; when imaging along the transverse axis of the vessel, the space-time velocity field of the circumferential guided wave is extracted along the circular centerline position of the vessel cross section.

Optionally, the acquiring an actual dispersion curve of the guided wave from the space-time velocity field includes: windowing the space-time velocity field to obtain a processed space-time velocity field; and performing two-dimensional Fourier transform on the processed space-time velocity field to obtain a spectrogram, and determining a dispersion curve of the guided wave based on extreme points of the spectrogram.

Optionally, the inverting the vessel material parameter and the stress based on the vessel radius, the vessel wall thickness and the actual dispersion curve to obtain the actual stress and the material property of the vessel comprises: determining a vessel geometry from the vessel radius and the vessel wall thickness; determining a theoretical dispersion curve between the guided wave and the vascular geometry according to a preset mechanical model; and iteratively solving the actual dispersion curve and the theoretical dispersion curve through an optimization algorithm, taking an average value of parameters obtained by each iteration solution as an optimal vascular material parameter, and calculating the actual stress and the material property of the blood vessel based on the optimal vascular material parameter, wherein the optimization algorithm comprises a Newton iteration method, a simulated annealing method and a genetic algorithm.

c＝ω/Re(k)，

the relationship between ω and k is calculated from the following formula:

wherein s1 and s2 are solved by the following four-time equation:

σ_a＝α_a-γ

The calculation formula of the hoop stress sigma _c is as follows:

σ_c＝α_c-γ

Optionally, the objective function of the optimization algorithm is:

An embodiment of the third aspect of the present application provides a computer-readable storage medium having stored thereon a computer program for execution by a processor for implementing the stress measurement method of a human blood vessel as described in the above embodiment.

Therefore, the application has at least the following beneficial effects:

the embodiment of the application designs a hardware device system for measuring the mechanical properties and stress of the blood vessel in vivo based on an ultrasonic method and a mechanical principle, develops a corresponding data processing method, can carry out noninvasive and real-time measurement on the mechanical properties and stress of the superficial artery of the human body, and has higher analysis efficiency; from the aspect of the mechanical properties of the characterized blood vessel, the mechanical properties of the artery are characterized by an arterial guided wave elastography method, so that the mechanical properties such as viscoelasticity, superelasticity, anisotropy and the like of the blood vessel can be characterized, and more quantitative guidance is hopefully provided for clinical detection; from the perspective of blood vessel stress measurement, the technical problem of blood pressure measurement is avoided, and the feasibility of measuring the axial stress of the blood vessel is higher and the operability is stronger.

Additional aspects and advantages of the application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the application.

Drawings

The foregoing and/or additional aspects and advantages of the application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings, in which:

fig. 1 is a schematic diagram of a stress measurement device for a human blood vessel according to an embodiment of the present application;

FIG. 2 is an exemplary illustration of an ultrasound test along a long-axis section of a blood vessel in accordance with an embodiment of the present application;

FIG. 3 is an exemplary diagram of an ultrasound test along a transverse axis section of a blood vessel in accordance with an embodiment of the present application;

FIG. 4 is a schematic diagram of a complete ultrasound imaging sequence in accordance with an embodiment of the present application;

FIG. 5 is an exemplary graph of extracting a spatio-temporal velocity field at a location along the centerline of the upper wall of a blood vessel when imaged along a long-axis slice of the blood vessel in accordance with an embodiment of the present application;

FIG. 6 is an exemplary graph of extracting a spatio-temporal velocity field at a location along the centerline of the upper wall of a blood vessel when imaged along a transverse axis slice of the blood vessel in accordance with an embodiment of the present application;

FIG. 7 is a schematic diagram of a windowing process for a spatio-temporal velocity field according to an embodiment of the present application;

FIG. 8 is a graph of a spectrum obtained from a two-dimensional Fourier transform in accordance with an embodiment of the present application;

fig. 9 is a graph of dispersion obtained by finding an extreme point according to an embodiment of the present application;

fig. 10 is a schematic view of measurement of a blood vessel radius by a luminance image according to an embodiment of the present application;

FIG. 11 is a schematic illustration of wall thickness measurement of a vessel's lower wall by luminance images, according to an embodiment of the present application;

FIG. 12 is a schematic diagram of an axial guided wave inversion method according to an embodiment of the application;

FIG. 13 is a schematic diagram of an inversion method of an annular guide wave according to an embodiment of the present application;

FIG. 14 is a graph of axial guided wave dispersion for carotid artery at diastolic and systolic pressures, according to an embodiment of the application;

FIG. 15 is a graph of measured axial stress at the carotid artery in accordance with an embodiment of the application;

fig. 16 is a flowchart of a stress measurement method of a human blood vessel according to an embodiment of the present application.

Detailed Description

Embodiments of the present application are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are illustrative and intended to explain the present application and should not be construed as limiting the application.

In recent years, cardiovascular system diseases become the first killer of global human health, various causes of death are first, and related researches indicate that lesions of blood vessel walls are direct causes of various cardiovascular complications such as myocardial infarction, stroke and the like, and most of lesions of the blood vessel walls can cause changes of arterial mechanical properties, so that the method has great significance in early screening and diagnosis of cardiovascular diseases in vivo measurement of the arterial mechanical properties.

Stress plays an important role in the growth and reconstruction of blood vessels because there are various forms of stress in blood vessels, including wall shear stress, hoop/axial normal stress within the wall, etc., cells in arteries (such as smooth muscle cells and endothelial cells) can experience stress, and a stress response to changes in stress by changing the homeostatic environment. The research shows that the reduction of wall shear stress has an important influence on the formation of arterial plaque, the increase of vascular hoop stress has a remarkable relation with the breakage and fracture of elastic fibers in arteries, and the change of stress is also an important factor for the occurrence of cardiovascular diseases such as plaque rupture, aortic dissection and the like. Thus, non-invasive, in-vivo measurement of arterial stress is also a critical technique that is urgently needed to develop in the clinical and health arts.

Dynamic elastography is an emerging imaging technology, which has shown some technical advantages in the field of blood vessel detection, wherein an elastography method for blood vessels, which is developed by researchers, is called an arterial guided wave elastography method, and is characterized in that an elastography method for blood vessels is developed by researchers, and an elastography wave is excited in the blood vessel wall by focused acoustic radiation force, and propagates in the blood vessel wall in a guided wave mode, and is imaged by an ultrasonic plane wave rapid imaging technology, so that wave field information is obtained, the mechanical properties of the blood vessels can be characterized by combining the wave field information, and a proper mechanical model needs to be established for obtaining the mechanical properties of the blood vessels from the wave field information analysis, wherein the square of wave velocity and the shearing modulus of materials are considered to meet a linear relation by a classical shearing wave model, but the wave field has a dispersive characteristic due to the limited thickness of the blood vessel wall and the viscoelastic material characteristic of the blood vessel wall, and on the other hand, the nonlinear behavior of the materials can also have an important influence on the wave field due to the influence of blood pressure fluctuation.

The prior art fails to consider the above problems systematically, so that the mechanical properties of the blood vessel obtained by analysis of the arterial guided wave imaging technique have errors and inaccuracy to different extents. Therefore, the embodiment of the application provides a novel data analysis method, so that the mechanical properties of the blood vessel are more accurately characterized.

On the other hand, for the measurement of vascular stress, the related technology mainly focuses on the measurement method of vascular hoop stress, is limited by the limitation of the measurement means and the complexity (in vivo and noninvasive) of the test conditions, and has not been very good at present.

Therefore, the embodiment of the application develops a set of method for simultaneously measuring the mechanical property of the blood vessel and the stress of the blood vessel (including axial stress and hoop stress) by utilizing the vascular guided wave imaging technology, so that the mechanical property of the blood vessel can be characterized on one hand, and the axial stress of the blood vessel can be measured on the other hand.

The stress measuring device, method and storage medium of human blood vessel according to the embodiments of the present application are described below with reference to the accompanying drawings. Specifically, fig. 1 is a schematic diagram of a stress measurement device for a human blood vessel according to an embodiment of the present application.

As shown in fig. 1, the stress measuring device 10 of a human blood vessel includes: an ultrasonic measurement module 100 and a data processing module 200.

The ultrasonic measurement module 100 is used for performing ultrasonic imaging on a blood vessel at a target position along a long-axis section or a transverse-axis section to obtain an ultrasonic image, exciting a blood vessel wall by using acoustic radiation force triggered by an electrocardiosignal to excite the blood vessel wall to emit a guided wave signal, and acquiring the signal to obtain an ultrasonic imaging sequence; the data processing module 200 is used for recognizing an ultrasonic image to obtain a blood vessel radius and a blood vessel wall thickness, extracting a space-time velocity field of a guided wave signal in an ultrasonic imaging sequence, acquiring an actual dispersion curve of the guided wave from the space-time velocity field, and inverting blood vessel material parameters and stress based on the blood vessel radius, the blood vessel wall thickness and the actual dispersion curve to obtain actual stress and material properties of the blood vessel.

The sound radiation force may be composed of a speaker generating a specific sound wave, and a difference in pressure density may be generated at a specific position, that is, the ultrasonic wave may change in shape under pressure, and simulate an imaginary shape and strength, which is not particularly limited herein.

It can be appreciated that the ultrasonic measurement module in the embodiment of the application is mainly responsible for programmable excitation and customized acquisition of the vascular guided wave imaging technology; the data processing module is responsible for image extraction and data analysis and is used for obtaining the mechanical property and the actual stress level of the blood vessel, and can carry out noninvasive and real-time measurement and data analysis on the mechanical property and the stress of the superficial artery of the human body, so that the feasibility is high and the operability is strong.

In an embodiment of the present application, an ultrasonic measurement module includes: an ultrasonic probe, an ultrasonic mainframe and an ultrasonic system.

The ultrasonic probe is used for carrying out ultrasonic imaging on the blood vessel at the target position along the long-axis section; the ultrasonic host comprises a radio frequency receiving end, a radio frequency transmitting end and a focused acoustic radiation force end, and is used for generating and transmitting acoustic radiation force, exciting the wall of a blood vessel and receiving guided wave signals emitted by excitation; the ultrasonic system is used for triggering the ultrasonic host to generate acoustic radiation force by the electrocardiosignal.

Wherein, the ultrasonic probe can be a common linear array probe (the center frequency of the probe is 5-15 MHz) or a lattice probe formed by a plurality of single array elements, and the ultrasonic probe is not particularly limited.

It can be understood that the ultrasonic probe in the embodiment of the application can test the long-axis section or the transverse-axis section for imaging according to different visual angles; the ultrasonic host is used for generating and transmitting acoustic radiation force, exciting the vessel wall and receiving the excited guided wave signal; the ultrasonic system is used for triggering the ultrasonic host to generate acoustic radiation force by the electrocardiosignal; thereby the ultrasonic measurement module realizes the functions of brightness mode imaging, programmable acoustic radiation force excitation and high frame rate acquisition.

In an embodiment of the present application, the data processing module is further configured to: processing the ultrasonic imaging sequence by using a preset algorithm to obtain a particle velocity field; when imaging along the long axis section of the blood vessel, extracting a space-time velocity field of axial guided waves along the position of the central line of the upper wall of the blood vessel; when imaging along the transverse axis of the vessel, the space-time velocity field of the circumferential guided wave is extracted along the circular centerline position of the vessel cross section.

The preset algorithm may be a Loupas algorithm or a Kasai algorithm, and may be selected according to the actual requirement of the user, which is not limited herein.

It can be understood that, in the embodiment of the application, an algorithm is utilized to process an ultrasonic imaging sequence to obtain a particle velocity field, and for a plane wave acquisition technology, the particle velocity field in an imaging plane can be obtained, and when imaging along a long axis section of a blood vessel, a space-time velocity field of an axial guided wave is extracted along the position of the central line of the upper wall of the blood vessel; when imaging along the transverse axis section of the blood vessel, extracting a space-time velocity field of the circumferential guided wave along the circular central line position of the cross section of the blood vessel; different extraction modes are provided for different imaging acquisitions so as to extract different space-time velocity fields, so that the actual dispersion curve of the guided wave can be obtained from the space-time velocity fields.

In an embodiment of the present application, the data processing module is further configured to: windowing is carried out on the space-time velocity field to obtain a processed space-time velocity field; and performing two-dimensional Fourier transform on the processed space-time velocity field to obtain a spectrogram, and determining a dispersion curve of the guided wave based on extreme points of the spectrogram.

The windowing process may be to intercept a signal with an infinitely long or long duration due to storage and delay problems, and select a sequence with a finite length for processing.

It can be understood that the embodiment of the application performs windowing treatment on the time-space velocity field to obtain a treated time-space velocity field, performs two-dimensional fourier transform on the treated time-space velocity field to obtain a spectrogram, determines a dispersion curve of the guided wave based on extreme points of the spectrogram, and reflects the relationship of the phase velocity along with the change of frequency, thereby obtaining the dispersion relationship of the guided wave in the time-space velocity field.

In an embodiment of the present application, the data processing module is further configured to: determining a vessel geometry from the vessel radius and the vessel wall thickness; determining a theoretical dispersion curve between the guided wave and the vascular geometry according to a preset mechanical model; and (3) iteratively solving an actual dispersion curve and a theoretical dispersion curve through an optimization algorithm, taking an average value of parameters obtained by each iteration solution as an optimal vascular material parameter, and calculating actual stress and material properties of the blood vessel based on the optimal vascular material parameter, wherein the optimization algorithm comprises but is not limited to a Newton iteration method, a simulated annealing method, a genetic algorithm, a particle swarm optimization algorithm and the like.

It should be noted that, the optimization algorithm includes newton iteration method, simulated annealing method, genetic algorithm, particle swarm optimization algorithm, etc., and it should be understood that the optimization algorithm is not limited to the above algorithm, and may be selected according to actual requirements, and is not specifically limited herein.

The preset mechanical model may be a mechanical model set in advance by a user, and may be selected according to actual requirements, which is not specifically limited herein.

The theoretical dispersion curve comprises a circumferential guided wave dispersion curve and/or an axial guided wave dispersion curve, wherein the calculation formula of the circumferential guided wave dispersion curve is as follows:

c＝ω/Re(k)，

the relationship between ω and k is calculated from the following formula:

wherein s1 and s2 are solved by the following four-time equation:

The actual stress comprises axial stress and hoop stress, wherein the calculation formula of the axial stress sigma _a is as follows:

σ_a＝α_a-γ

The calculation formula of the hoop stress sigma _c is as follows:

σ_c＝α_c-γ

Wherein, the objective function of the optimization algorithm is:

It can be understood that the embodiment of the application determines the vessel geometry according to the vessel radius and the vessel wall thickness, determines the theoretical dispersion curve between the guided wave and the vessel geometry according to the mechanical model, fits the experimental dispersion curve and the theoretical model to obtain the optimal vessel material parameter, calculates the actual stress of the vessel based on the optimal vessel material parameter, and has high accuracy, high efficiency and high stability of the data obtained by the analysis of the data processing model.

According to the stress measuring device for the human blood vessel, provided by the embodiment of the application, the ultrasonic measuring module is mainly responsible for programmable excitation and customized acquisition of a blood vessel guided wave imaging technology; the data processing module is responsible for image extraction and data analysis and is used for obtaining the mechanical property and the actual stress level of the blood vessel; from the aspect of the mechanical properties of the characterized blood vessel, the mechanical properties of the artery are characterized by an arterial guided wave elastography method, so that the mechanical properties of the blood vessel such as viscoelasticity, superelasticity and anisotropism can be characterized, and more quantitative guidance is hopefully provided for clinical detection; from the perspective of blood vessel stress measurement, the technical problem of blood pressure measurement is avoided, and the feasibility of measuring the axial stress of the blood vessel is higher and the operability is stronger. Therefore, the problem that the system characterization on the nonlinear and viscoelastic properties of the blood vessel cannot be realized in the related technology is solved, and the system characterization has certain limitation; the measuring stability of the vascular hoop stress is not high, the reliability is low, the operation is complex, and the like.

The stress measuring device of the human blood vessel will be described in detail below with reference to fig. 2 to 15, and mainly includes three aspects of a hardware system, specific implementation steps and a data post-processing method, specifically:

1. the hardware system comprises: the device comprises an ultrasonic measurement module, a data processing module and a display and output module.

The ultrasonic measuring module consists of an ultrasonic host and an ultrasonic probe. The ultrasonic host comprises an RF (Radio Frequency) receiving/transmitting end and a focused acoustic radiation force end; the ultrasonic probe can be a common linear array probe (the center frequency of the probe is 5-15 MHz) or a lattice probe formed by a plurality of single array elements; the ultrasound system may implement brightness mode imaging, programmable acoustic radiation force excitation, and high frame rate (> 5 kHz) acquisition functions. The ultrasonic equipment is provided with an electrocardio acquisition module, and the electrocardio module can realize synchronous triggering by an acoustic radiation force excitation module.

The data processing module is mainly composed of a computer and software carried on the computer and is mainly responsible for processing image data from the ultrasonic module and analyzing the data so as to obtain vascular mechanical properties and stress.

The display and output module is mainly composed of a display, and outputs measured parameters to a user in a screen display mode, and data can be output to the user in a real-time update mode for multiple measurements.

2. In the specific embodiment, the common carotid artery of the subject is taken as an example, and it is emphasized that any superficial artery (such as radial artery, brachial artery, etc.) can be measured in the embodiment of the application; the method comprises the following specific steps:

And 1, imaging the blood vessel along a long-axis section or a transverse-axis section by using an ultrasonic probe, and lightly placing the ultrasonic probe on the surface of the skin to avoid extruding the blood vessel. Care is taken to adjust the view angle of the ultrasound probe so that the blood vessel remains in the mid-position of the view. Wherein fig. 2 (a) shows the ultrasonic test along the long axis section of the blood vessel, and fig. 3 (d) shows the ultrasonic test along the transverse axis section of the blood vessel. In the testing process, the tested object is simultaneously provided with an electrocardio monitoring device, and the electrocardio signals output in real time are used for triggering the sound radiation force.

And 2, triggering an acoustic radiation force excitation module through an electrocardiosignal so as to excite guided waves in the blood vessel wall, selecting a triggering threshold value of the electrocardiosignal as a QRS peak of an electrocardiosignal waveform, and setting a specific delay time to realize ultrasonic signal acquisition at a designated cardiac cycle time (such as end systole, end diastole and the like).

The excitation modes of the acoustic radiation force include, but are not limited to, a single acoustic radiation force (as shown in fig. 2 (b), 3 (e)), a moving acoustic radiation force (a multi-point acoustic radiation force is sequentially excited, as shown in fig. 2 (c), 3 (f)), a simultaneous focusing of a multi-point acoustic radiation force, etc., the focusing position should be at or near the vessel wall so that the vessel guided wave can be excited.

And step 3, then executing an imaging acquisition mode to acquire the vascular guided wave signal.

Techniques for implementing imaging acquisition include, but are not limited to: plane wave rapid acquisition techniques, a-line echo acquisition techniques (at least two sampling points are required, i.e., two points along the path of the vessel wall), etc. Wherein the sampling range should comprise at least an upper wall and a lower wall of the blood vessel; the sampling frequency should be at least above 5kHz; the raw data acquired may be I/Q data or RF data.

In one embodiment, the plane wave imaging technique is used for imaging acquisition for a period of 4ms at a sampling frame rate of 10kHz for a total of 40 frames. A complete ultrasound imaging sequence is shown in fig. 4, including an acoustic radiation force phase, a blank phase (which may be omitted depending on the actual performance of the ultrasound device), and an imaging acquisition phase.

3. The data processing method comprises the following steps:

(1) I/Q data or RF data is acquired from the ultrasound system and raw data is processed by algorithms to obtain particle velocity fields v _x (x, z, t), specific implementations include, but are not limited to: the Loupas algorithm, the Kasai algorithm, etc.

Extraction of vessel guided wave signals from particle velocity fields there may be different extraction methods for different imaging acquisition techniques, the core being the acquisition of time-velocity curves at least at two particle locations of the vessel wall. FIGS. 5 and 6 illustrate specific embodiments in which particle velocity fields in the imaging plane can be obtained for plane wave acquisition techniques, and when imaging along a long axis slice of a vessel, the spatio-temporal velocity fields are extracted along the location of the centerline of the vessel's upper wall (shown in FIG. 5); when imaging along a transverse axis slice of a vessel, a spatio-temporal velocity field (shown in fig. 6) is extracted along a circular centerline position of the vessel cross-section.

(2) Obtaining the dispersion relation of guided waves from the space-time velocity field, wherein the implementation method comprises the following steps of: a two-dimensional fourier transform method, a wavelet transform method, and the like.

As a specific embodiment, the space-time velocity field is firstly windowed (fig. 7), then a spectrogram is obtained by two-dimensional fourier transform (fig. 8), and then a dispersion curve is obtained by searching for extreme points (fig. 9), wherein the dispersion curve reflects the relationship of the phase velocity with the change of frequency.

(3) The method comprises the steps of measuring the geometry of a blood vessel, including the radius r and the wall thickness h of the blood vessel, and ensuring that the moment of imaging the geometry of the blood vessel is basically consistent with the excitation moment of acoustic radiation force (the time difference is smaller than the magnitude of 10 ms); methods of acquiring geometric images include, but are not limited to, conventional B-mode imaging, rapid imaging techniques, and the like; image processing algorithms for measurement geometry include, but are not limited to, thresholding, bipeak fitting, edge detection, and the like.

As a specific example, one frame (the first frame in this example) of 40 frames obtained by rapid imaging is selected, and a luminance map of a blood vessel is calculated from IQ raw data, as shown in fig. 10 and 11. The vessel radius is measured by luminance image (fig. 10), and the wall thickness of the vessel lower wall is measured (fig. 11).

The characterization method for calculating the parameters and the stress of the vascular material through a specific algorithm is as follows:

1. And establishing a mechanical model to obtain theoretical relations of a vascular guided wave dispersion curve, vascular material parameters, blood pressure, geometry and the like, wherein the theoretical relations comprise the theoretical dispersion relations of axial guided waves and the theoretical dispersion relations of circumferential guided waves.

The theoretical model correlates the dispersion curve with the material parameters and geometry, thus providing theoretical guidance for characterizing the material parameters and stress levels of the blood vessel. The theoretical dispersion relationship is as follows:

And s1 and s2 are solved by the following four-time equation:

Wherein, C _p ²＝κ_p/ρ^f,κ_p is the bulk modulus of water (2.2 GPa), ρ ^f is the density of water (1000 kg/m 3), t= (α _a+γ+α_c)/3

，Where i represents the unit imaginary number,

Wherein,When solving axial guided wave dispersion, α=α _a is taken, when solving circumferential guided wave dispersion, α=α _c is taken, h=h/2 represents half wall thickness, ρ is vessel wall density (1000 kg/m3 is taken), α _a,α_c, γ and β are tangential stiffness parameters (dimension [ Pa ]) of the vessel, g and τ are viscoelasticity parameters of the vessel, and respectively represent relaxation modulus (dimension [1 ]) and relaxation characteristic time (dimension [ s ]), ω is angular frequency (=2pi f, f is frequency [ Hz ]), and k is angular wave number.

From the formulas (1) and (2), the omega-k relationship can be calculated, and then the phase velocity c can be calculated from the following formula

c＝ω/Re(k) (3)

(3) The formula is the calculated dispersion relation (i.e., the relation between the phase velocity c and the frequency f).

For calculating the axial guided wave dispersion curve of the blood vessel, the following correction formula is also needed:

Wherein c _a (ω) represents the dispersion relation of the phase velocity c _a of the axial guided wave with the change of the frequency ω, c (ω) is determined by the formula (3), r is the vessel radius, n is the circumferential wave number, where n=2.

In summary, the theoretical circumferential guided wave dispersion curve can be calculated from the equation (3), and the theoretical axial guided wave dispersion curve can be calculated from the equation (4).

2. The principle of stress measurement is given by the following theoretical relationship, and the axial stress sigma _a, the hoop stress sigma _c and the material parameters satisfy the following relationship:

σ_a＝α_a-γ (5)

σ_c＝α_c-γ (6)

3. And establishing an inversion method, and fitting the experimental dispersion curve and the theoretical model to obtain material parameters. Specifically, for axial guided waves, a material parameter set (α _a, γ, g, τ) can be obtained; for the circular guide wave, a material parameter set (alpha _c, gamma, g, tau) can be obtained, and then the stress can be calculated from the material parameter.

The inversion method includes, but is not limited to: traditional optimization algorithms (such as Newton iteration method, steepest descent method and the like), intelligent optimization algorithms (genetic algorithm, ant colony algorithm, particle swarm algorithm, simulated annealing method and the like), and machine learning methods (convolutional neural network and the like).

In particular, the embodiment of the present application needs to protect a specific inversion algorithm, i.e., a set of inversion methods based on genetic algorithm. For axial guided waves, the inversion method is shown in FIG. 12. Experimentally measured data f _i,c_i (i=1, 2, … n, n represents the number of data points of the measured dispersion data, generally taking n=40), as well as the vessel radius r and the wall thickness h. The optimal unknown parameters (alpha _a, gamma, g and tau) are obtained by iterative solution of a genetic algorithm, and in order to improve the stability of inversion parameters, the iterative solution process is repeated for M times (M=3 is taken in the embodiment), and the parameter set obtained by three solutions is averaged to obtain the final vascular material parameters. And then the axial stress sigma _a of the blood vessel can be calculated by the formula (5). For the circumferential guided wave, the inversion method is as shown in fig. 13, the material parameter set (alpha _c, gamma, g, tau) of the circumferential direction of the blood vessel is obtained through iterative solution of a genetic algorithm, and the circumferential stress sigma _c of the blood vessel is obtained through calculation of the formula (6).

It should be noted that, the vessel radius r is not required in the experimental data of the circumferential guided wave, so that only in the case of the circumferential guided wave method, the step of measuring the vessel radius may be omitted in the process of measuring the experimental data.

When the genetic algorithm is used for carrying out iterative solution, an objective function needs to be defined, and when the objective function reaches the minimum value, the optimal parameter solution is obtained. Goodness objective functionThe definition is as follows:

Wherein the method comprises the steps of Representing the phase velocity measured by the experiment,Representing a theoretical predicted phase velocity, the theoretical solution being determined by equation (4) for the axial guided wave, and α being taken as α _a; for the circular guide, the theoretical solution is determined by equation (3), and α is taken as α _c. n represents the number of experimentally measured data points (preferably n=40). The frequency band of the experimental dispersion curve is chosen between 500Hz and 1500Hz, so n=40 means that 40 equally divided frequency-phase velocity data points are acquired in this frequency band.

4. As a specific example, fig. 14 and 15 illustrate the feasibility and stability of the method. Fig. 14 is an axial guided wave dispersion curve corresponding to carotid artery at diastolic and systolic pressures, and the experimental curve and the theoretical model are fitted to obtain the material parameters, and fig. 14 also shows the fitted theoretical dispersion curve. Fig. 15 is a graph of measured axial stress at the carotid artery, where a significant change in axial stress over the cardiac cycle can be observed.

It should be noted that either of the axial guided wave imaging techniques or the circumferential guided wave techniques described above may be performed in particular embodiments without being performed simultaneously. Specifically, if an axial guided wave imaging technology is performed, measuring the mechanical property of the axial direction of the blood vessel and the axial stress of the blood vessel; if the circumferential wave guiding imaging technology is executed, measuring the circumferential mechanical property of the blood vessel and the circumferential stress of the blood vessel; if two imaging techniques are performed simultaneously, the mechanical properties and stresses of the vessel can be measured simultaneously.

Next, a stress measurement method of a human blood vessel according to an embodiment of the present application will be described with reference to the accompanying drawings.

As shown in fig. 16, the stress measurement method of the human blood vessel comprises the following steps:

In step S101, ultrasound imaging is performed on a blood vessel at a target position along a long axis section or a transverse axis section to obtain an ultrasound image, and the blood vessel wall is excited by acoustic radiation force triggered by an electrocardiosignal, so that the blood vessel wall excites a guided wave signal, and an ultrasound imaging sequence is obtained by acquiring the signal.

It can be understood that the embodiment of the application carries out ultrasonic imaging on the blood vessel at the target position along the long axis section or the transverse axis section to obtain an ultrasonic image, and excites the blood vessel wall by the electrocardio signal triggering sound radiation force, so that the blood vessel wall excites a guided wave signal, the signal is acquired to obtain an ultrasonic imaging sequence, and from the aspect of the mechanical property of the represented blood vessel, the mechanical property of the artery is represented by the artery guided wave elastography method, so that the viscoelasticity, superelasticity, anisotropy and other mechanical properties of the blood vessel can be represented, and more quantitative guidance is hopefully provided for clinical detection.

In step S102, recognizing an ultrasonic image to obtain a vessel radius and a vessel wall thickness, extracting a space-time velocity field of a guided wave signal in an ultrasonic imaging sequence, obtaining an actual dispersion curve of the guided wave from the space-time velocity field, and inverting vessel material parameters and stresses based on the vessel radius, the vessel wall thickness and the actual dispersion curve to obtain actual stresses and material properties of the vessel.

It can be understood that, in the embodiment of the application, the radius and the wall thickness of the blood vessel are obtained by identifying the ultrasonic image, the space-time velocity field of the guided wave signal in the ultrasonic imaging sequence is extracted, the actual dispersion curve of the guided wave is obtained, the inversion of the parameters and the stress of the blood vessel material is carried out based on the radius, the wall thickness and the actual dispersion curve of the blood vessel, the actual stress and the material property of the blood vessel are obtained, the technical problem of blood pressure measurement is avoided from the aspect of blood vessel stress measurement, and the measurement feasibility of the axial stress of the blood vessel is higher and the operability is stronger.

In an embodiment of the present application, extracting a spatiotemporal velocity field of a guided wave signal in an ultrasound imaging sequence includes: processing the ultrasonic imaging sequence by using a preset algorithm to obtain a particle velocity field; when imaging along the long axis section of the blood vessel, extracting a space-time velocity field of axial guided waves along the position of the central line of the upper wall of the blood vessel; when imaging along the transverse axis of the vessel, the space-time velocity field of the circumferential guided wave is extracted along the circular centerline position of the vessel cross section.

In an embodiment of the present application, obtaining an actual dispersion curve of guided waves from a space-time velocity field comprises: windowing is carried out on the space-time velocity field to obtain a processed space-time velocity field; and performing two-dimensional Fourier transform on the processed space-time velocity field to obtain a spectrogram, and determining a dispersion curve of the guided wave based on extreme points of the spectrogram.

In the embodiment of the application, inversion of blood vessel material parameters and stress is performed based on the blood vessel radius, the blood vessel wall thickness and the actual dispersion curve to obtain the actual stress and material properties of the blood vessel, and the method comprises the following steps: determining a vessel geometry from the vessel radius and the vessel wall thickness; determining a theoretical dispersion curve between the guided wave and the vascular geometry according to a preset mechanical model; and (3) iteratively solving an actual dispersion curve and a theoretical dispersion curve through an optimization algorithm, taking an average value of parameters obtained through each iteration solution as an optimal vascular material parameter, and calculating actual stress and material properties of the blood vessel based on the optimal vascular material parameter, wherein the optimization algorithm comprises a Newton iteration method, a simulated annealing method and a genetic algorithm.

In an embodiment of the application, the theoretical dispersion curve comprises a circumferential guided wave dispersion curve and/or an axial guided wave dispersion curve, wherein,

The calculation formula of the circumferential guided wave dispersion curve is as follows:

c＝ω/Re(k)，

the relationship between ω and k is calculated from the following formula:

wherein s1 and s2 are solved by the following four-time equation:

In an embodiment of the present application, the actual stresses include axial stresses and hoop stresses, wherein,

The calculation formula of the axial stress sigma _a is as follows:

σ_a＝α_a-γ

The calculation formula of the hoop stress sigma _c is as follows:

σ_c＝α_c-γ

In the embodiment of the application, the objective function of the optimization algorithm is as follows:

It should be noted that the foregoing explanation of the embodiment of the stress measurement device for a human blood vessel is also applicable to the stress measurement method for a human blood vessel of this embodiment, and will not be repeated here.

According to the stress measurement method for the human blood vessel, provided by the embodiment of the application, the blood vessel at the target position is subjected to ultrasonic imaging along the long-axis tangential plane or the transverse-axis tangential plane to obtain an ultrasonic image, the electrocardiosignal triggers the acoustic radiation force to excite the blood vessel wall, so that the blood vessel wall excites the guided wave signal, the signal is acquired to obtain an ultrasonic imaging sequence, from the aspect of the mechanical property of the represented blood vessel, the mechanical property of the artery is represented by the arterial guided wave elastic imaging method, the viscoelasticity, the superelasticity, the anisotropism and other mechanical properties of the blood vessel can be represented, and more quantitative guidance is hopefully provided for clinical detection; the method comprises the steps of obtaining the radius and the wall thickness of the blood vessel through identifying an ultrasonic image, extracting the space-time velocity field of a guided wave signal in an ultrasonic imaging sequence, obtaining the actual dispersion curve of the guided wave from the space-time velocity field, inverting the parameters and the stress of the blood vessel material based on the radius, the wall thickness and the actual dispersion curve of the blood vessel, obtaining the actual stress and the material property of the blood vessel, and avoiding the technical problem of blood pressure measurement from the angle of measuring the stress of the blood vessel, wherein the measuring feasibility of the axial stress of the blood vessel is higher and the operability is stronger. Therefore, the problem that the system characterization on the nonlinear and viscoelastic properties of the blood vessel cannot be realized in the related technology is solved, and the system characterization has certain limitation; the measuring stability of the vascular hoop stress is not high, the reliability is low, the operation is complex, and the like.

The embodiment of the application also provides a computer readable storage medium, on which a computer program is stored, which program, when being executed by a processor, implements the stress measuring method of the human blood vessel as above.

In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. In this specification, schematic representations of the above terms are not necessarily directed to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or N embodiments or examples. Furthermore, the different embodiments or examples described in this specification and the features of the different embodiments or examples may be combined and combined by those skilled in the art without contradiction.

Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In the description of the present application, "N" means at least two, for example, two, three, etc., unless specifically defined otherwise.

Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more N executable instructions for implementing specific logical functions or steps of the process, and further implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the embodiments of the present application.

It is to be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, the N steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. As with the other embodiments, if implemented in hardware, may be implemented using any one or combination of the following techniques, as is well known in the art: discrete logic circuits having logic gates for implementing logic functions on data signals, application specific integrated circuits having suitable combinational logic gates, programmable gate arrays, field programmable gate arrays, and the like.

Those of ordinary skill in the art will appreciate that all or a portion of the steps carried out in the method of the above-described embodiments may be implemented by a program to instruct related hardware, where the program may be stored in a computer readable storage medium, and where the program, when executed, includes one or a combination of the steps of the method embodiments.

While embodiments of the present application have been shown and described above, it will be understood that the above embodiments are illustrative and not to be construed as limiting the application, and that variations, modifications, alternatives and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the application.

Claims

1. A stress measurement device for a human blood vessel, comprising:

The ultrasonic measurement module is used for carrying out ultrasonic imaging on a blood vessel at a target position along a long-axis section or a transverse-axis section to obtain an ultrasonic image, exciting a blood vessel wall by using acoustic radiation force triggered by electrocardiosignals, so that the blood vessel wall excites a guided wave signal, and acquiring the signal to obtain an ultrasonic imaging sequence;

The data processing module is used for identifying the ultrasonic image to obtain a blood vessel radius and a blood vessel wall thickness, extracting a space-time velocity field of a guided wave signal in the ultrasonic imaging sequence, acquiring an actual dispersion curve of the guided wave from the space-time velocity field, and determining the blood vessel geometry according to the blood vessel radius and the blood vessel wall thickness; determining a theoretical dispersion curve between the guided wave and the vascular geometry according to a preset mechanical model; and iteratively solving the actual dispersion curve and the theoretical dispersion curve through an optimization algorithm, taking an average value of parameters obtained by each iteration solution as an optimal vascular material parameter, and calculating the actual stress and the material property of the blood vessel based on the optimal vascular material parameter, wherein the optimization algorithm comprises a Newton iteration method, a simulated annealing method and a genetic algorithm.

2. The apparatus of claim 1, wherein the data processing module is further configured to:

processing the ultrasonic imaging sequence by using a preset algorithm to obtain a particle velocity field;

when imaging along the long axis section of the blood vessel, extracting a space-time velocity field of axial guided waves along the position of the central line of the upper wall of the blood vessel; when imaging along the transverse axis of the vessel, the space-time velocity field of the circumferential guided wave is extracted along the circular centerline position of the vessel cross section.

3. The apparatus of claim 1, wherein the data processing module is further configured to:

windowing the space-time velocity field to obtain a processed space-time velocity field;

And carrying out two-dimensional Fourier transform on the processed space-time velocity field to obtain a spectrogram, and determining an actual dispersion curve of the guided wave based on extreme points of the spectrogram.

4. The apparatus of claim 1, wherein the theoretical dispersion curve comprises a circumferential guided wave dispersion curve and/or an axial guided wave dispersion curve, wherein,

c＝ω/Re(k)，

the relationship between ω and k is calculated from the following formula:

Wherein s ₁ and s ₂ are solved by the following four-time equation:

Wherein, C _p ²＝κ_p/ρ^f,κ_p is the bulk modulus of water, ρ ^f is the density of water, t= (a _a+γ+α_c)/3,I represents the imaginary number of the unit,When solving the axial guided wave dispersion, alpha=alpha _a is taken, when solving the circumferential guided wave dispersion, alpha=alpha _c is taken, h=h/2 is taken to represent the half wall thickness, ρ is the blood vessel wall density, alpha _a,α_c, gamma and beta are tangential stiffness parameters of the blood vessel, g and τ are viscoelasticity parameters of the blood vessel, and the relaxation modulus and the relaxation characteristic time are respectively represented.

5. The apparatus of claim 1, wherein the actual stresses include axial stresses and hoop stresses, wherein,

The calculation formula of the axial stress sigma _a is as follows:

σ_a＝α_a-γ

The calculation formula of the hoop stress sigma _c is as follows:

σ_c＝α_c-γ

Where α _a represents the axial incremental stiffness of the vessel, α _c represents the circumferential incremental stiffness, and γ represents another incremental stiffness coefficient.

6. The apparatus of claim 1, wherein the objective function of the optimization algorithm is:

Wherein, Representing the phase velocity measured by the experiment,The theoretical predicted phase velocity is represented by alpha, the incremental stiffness of the blood vessel is represented by alpha _a or alpha _c respectively, gamma is another incremental stiffness parameter when the theoretical predicted phase velocity is applied to axial or annular guide waves, g is the relaxation modulus of the viscoelasticity of the blood vessel, tau is relaxation characteristic time, f _i represents experimentally measured frequency, r represents the radius of the blood vessel, h represents the wall thickness of the blood vessel, and n represents the number of experimentally measured data points.

7. The apparatus of claim 1, wherein the ultrasonic measurement module comprises:

the ultrasonic probe is used for carrying out ultrasonic imaging on the blood vessel at the target position along the long-axis section;

The ultrasonic host comprises a radio frequency receiving end, a radio frequency transmitting end and a focused acoustic radiation force end, and is used for generating and transmitting acoustic radiation force, exciting the vessel wall and receiving the excited guided wave signal;

And the ultrasonic system is used for triggering the ultrasonic host to generate acoustic radiation force by the electrocardiosignal.

8. A method for measuring stress of a human blood vessel, comprising the steps of:

Carrying out ultrasonic imaging on a blood vessel at a target position along a long-axis section or a transverse-axis section to obtain an ultrasonic image, exciting a blood vessel wall by using acoustic radiation force triggered by electrocardiosignals, so that the blood vessel wall excites a guided wave signal, and acquiring the signal to obtain an ultrasonic imaging sequence;

Identifying the ultrasonic image to obtain a blood vessel radius and a blood vessel wall thickness, extracting a space-time velocity field of a guided wave signal in the ultrasonic imaging sequence, acquiring an actual dispersion curve of the guided wave from the space-time velocity field, and determining the blood vessel geometry according to the blood vessel radius and the blood vessel wall thickness; determining a theoretical dispersion curve between the guided wave and the vascular geometry according to a preset mechanical model; and iteratively solving the actual dispersion curve and the theoretical dispersion curve through an optimization algorithm, taking an average value of parameters obtained by each iteration solution as an optimal vascular material parameter, and calculating the actual stress and the material property of the blood vessel based on the optimal vascular material parameter, wherein the optimization algorithm comprises a Newton iteration method, a simulated annealing method and a genetic algorithm.

9. The method of claim 8, wherein the extracting the spatiotemporal velocity field of the guided wave signal in the ultrasound imaging sequence comprises:

10. The method of claim 8, wherein the obtaining an actual dispersion curve of guided waves from the space-time velocity field comprises:

11. The method of claim 8, wherein the theoretical dispersion curve comprises a circumferential guided wave dispersion curve and/or an axial guided wave dispersion curve, wherein,

c＝ω/Re(k)，

the relationship between ω and k is calculated from the following formula:

wherein s1 and s2 are solved by the following four-time equation:

12. The method of claim 8, wherein the actual stresses include axial stresses and hoop stresses, wherein,

The calculation formula of the axial stress sigma _a is as follows:

σ_a＝α_a-γ

The calculation formula of the hoop stress sigma _c is as follows:

σ_c＝α_c-γ

13. The method of claim 8, wherein the objective function of the optimization algorithm is:

Wherein, Representing the phase velocity measured by the experiment,The theoretical predicted phase velocity is represented by alpha, the incremental stiffness is represented by alpha _a or alpha _c respectively, gamma is a tangential stiffness parameter of a blood vessel when the theoretical predicted phase velocity is applied to axial or annular guide waves, g is a relaxation modulus of viscoelasticity of the blood vessel, tau is relaxation characteristic time, f _i represents experimentally measured frequency, r represents the radius of the blood vessel, h represents the wall thickness of the blood vessel, and n represents the number of experimentally measured data points.

14. A computer-readable storage medium, on which a computer program is stored, characterized in that the program is executed by a processor for implementing a stress measurement method of a human blood vessel according to any one of claims 8-13.