Myocardial fibrosis analysis method, device, equipment, system and medium

Abstract

The invention belongs to the technical field of heart detection, and particularly relates to a myocardial fibrosis analysis method, device, equipment, system and medium. The method comprises the following steps: generating a radio frequency data sequence according to reflection echoes obtained after a to-be-detected area of the heart receives radiation force shear waves; performing demodulation processing on the radio frequency data sequence to obtain a complex data sequence; processing correlation between frames in the complex data sequence to obtain a myocardial tissue propagation velocity image; processing the myocardial tissue propagation velocity image by adopting a smoothing method to obtain a myocardial tissue propagation velocity smooth image and a myocardial tissue acceleration image; generating an analysis report of imaging data according to the smooth image of the propagation velocity of the myocardial tissue and the acceleration imaging of the myocardial tissue; wherein the analysis report comprises statistical characteristics and spatial distribution information of the data. The statistical characteristics and spatial distribution information of the imaging data are analyzed emphatically, and powerful data support is provided for subsequent medical research or clinical analysis.

Description

Technical Field

[0001] The present invention belongs to the technical field of cardiac detection, and in particular relates to a method, device, equipment, system and medium for analyzing myocardial fibrosis. Background Art

[0002] Myocardial fibrosis is a common pathological change in the progression of various heart diseases, such as ischemic heart disease, heart failure, dilated cardiomyopathy, hypertrophic cardiomyopathy, type II diabetes, hypertensive cardiomyopathy, severe valvular disease (especially aortic stenosis), and cardiac toxicity after chemotherapy (especially anthracycline therapy). Myocardial fibrosis can cause decreased myocardial elasticity and increased hardness, which in turn leads to ventricular diastolic dysfunction, and ultimately leads to heart failure with preserved ejection fraction (HFpEF), significantly increasing the hospitalization rate and mortality rate of patients. At the same time, myocardial fibrosis is also an important prognostic indicator for dilated and hypertrophic cardiomyopathy. From a clinical perspective, if myocardial fibrosis and changes in myocardial elasticity can be detected before irreversible changes in the heart structure occur, and early intervention treatment can be implemented in a timely manner, it is very likely to delay the progression of heart failure, which is of vital significance for improving patient symptoms and prognosis.

[0003] 1. Insufficiency of commonly used detection parameters At present, the commonly used clinical detection parameters, such as left ventricular shortening fraction (FS), left ventricular ejection fraction (LV EF) calculated by the biplane Simpson method, tissue Doppler spectrum of left ventricular free wall and ventricular septum, peak systolic velocity (s'cm / s), ventricular work index, and ventricular segment and overall strain, etc., will only be manifested after irreversible damage to the myocardium occurs, and it is impossible to gain insight into the intrinsic characteristics of the myocardium in advance. Moreover, these indicators are easily affected by the use of diuretics and changes in hypovolemia, resulting in deviations in the results, making it difficult to accurately reflect the true functional status of the myocardial tissue.

[0004] 2. Disadvantages of contrast-enhanced magnetic resonance imaging (CMR) Contrast-enhanced magnetic resonance imaging is considered the non-invasive gold standard for detecting myocardial fibrosis. It quantifies extracellular matrix proliferation by evaluating the degree of late gadolinium enhancement (LGE) and then detects tissue fibrosis. However, CMR has many problems that limit its widespread clinical application. On the one hand, its operation is complicated and costly, and it cannot be tested at the bedside, making it unsuitable for routine clinical monitoring. On the other hand, LGE mainly detects focal areas of fibrosis and requires normal myocardium as a reference area. This prerequisite greatly limits its accuracy in evaluating myocardial lesions characterized by diffuse, interstitial fibrosis. In addition, the presence of LGE is dichotomous, which is not conducive to the observation of the continuous development of fibrosis, and a relatively high concentration of fibrosis is required to detect positive results. Summary of the invention

[0005] The purpose of the present invention is to provide a method, device, equipment, system and medium for analyzing myocardial fibrosis, aiming to provide detailed data analysis based on smoothed images of myocardial tissue propagation velocity and acceleration imaging of myocardial tissue. By collecting and processing the reflected echoes of the radiation force shear wave in the area to be detected by the heart, a high-quality radio frequency data sequence is generated, and further demodulated and processed to obtain the propagation velocity and acceleration imaging of the myocardial tissue. The statistical characteristics and spatial distribution information of these imaging data are analyzed in detail to provide strong data support for subsequent medical research or clinical analysis.

[0006] In order to achieve the above object, the present invention adopts the following technical solution: In a first aspect, the present invention provides a method for analyzing myocardial fibrosis, comprising: Acquire a reflected echo, and generate a radio frequency data sequence according to the reflected echo; wherein the reflected echo is a reflected echo obtained after the heart area to be detected receives the radiation force shear wave; Demodulating the radio frequency data sequence to obtain a demodulated complex data sequence; Processing the correlation between frames in the complex data sequence to obtain myocardial tissue propagation velocity imaging; Processing the myocardial tissue propagation velocity imaging using a smoothing method to obtain a myocardial tissue propagation velocity smoothing image and a myocardial tissue acceleration imaging; An analysis report of the imaging data is generated based on the myocardial tissue propagation velocity smoothed image and the myocardial tissue acceleration imaging; wherein the analysis report includes statistical characteristics and spatial distribution information of the data.

[0007] Further, the demodulating the radio frequency data sequence includes: The radio frequency data sequence is sampled and discretized to obtain a discrete signal; Apply the Fast Fourier Transform algorithm to the discrete signal to obtain a frequency domain representation; The amplitude and phase information are extracted from the frequency domain representation to obtain a complex data sequence.

[0008] Furthermore, the processing of the correlation between frames in the complex data sequence to obtain myocardial tissue propagation velocity imaging includes: Extract frame data at different time points from the complex data sequence; Calculate the cross-correlation function between two adjacent frames of data; The time interval of shear wave propagation between two frames of data is determined by finding the maximum value of the cross-correlation function; The propagation speed of the shear wave is calculated according to the time interval of the shear wave propagation and the spatial distance between two frames of data; The shear wave propagation velocity at each position in the myocardial tissue is mapped to the corresponding spatial position to obtain myocardial tissue propagation velocity imaging.

[0009] Furthermore, a smoothing method is used to process the myocardial tissue propagation velocity imaging to obtain a myocardial tissue propagation velocity smoothing image and a myocardial tissue acceleration imaging; wherein: For each pixel in the myocardial tissue propagation velocity imaging, the pixel value within a preset range around the corresponding pixel is taken; The pixel values ​​are weighted averaged according to the weight of the Gaussian kernel to obtain the smoothed pixel value; A myocardial tissue propagation velocity smoothing image is obtained according to each smoothed pixel value.

[0010] Furthermore, a smoothing method is used to process the myocardial tissue propagation velocity imaging to obtain a myocardial tissue propagation velocity smoothing image and a myocardial tissue acceleration imaging; wherein: After obtaining the smoothed propagation velocity image, the myocardial tissue acceleration imaging is obtained by analyzing the change rate of the propagation velocity.

[0011] In a second aspect, the present invention provides a myocardial fibrosis analysis device for use in the above-mentioned myocardial fibrosis analysis method, comprising: A data conversion module is used to obtain a reflected echo and generate a radio frequency data sequence according to the reflected echo; wherein the reflected echo is a reflected echo obtained after the heart area to be detected receives a radiation force shear wave; A demodulation module, used for demodulating the radio frequency data sequence to obtain a demodulated complex data sequence; A first data processing module is used to process the correlation between frames in the complex data sequence to obtain myocardial tissue propagation velocity imaging; A second data processing module is used to process the myocardial tissue propagation velocity imaging by a smoothing method to obtain a myocardial tissue propagation velocity smoothing image and a myocardial tissue acceleration imaging; The analysis module is used to generate an analysis report of the imaging data based on the myocardial tissue propagation velocity smoothing image and the myocardial tissue acceleration imaging; wherein the analysis report includes the statistical characteristics and spatial distribution information of the data.

[0012] In a third aspect, the present invention provides a method for analyzing myocardial fibrosis, comprising the following steps: emitting radiation force shear waves to the area to be detected in the heart; Receiving reflected echo from the area to be detected in the heart; generating a radio frequency data sequence according to the reflected echo; Processing the radio frequency data sequence to obtain a demodulated complex data sequence; Processing the correlation between frames in the complex data sequence to obtain myocardial tissue propagation velocity imaging; The myocardial tissue propagation velocity imaging is processed by a smoothing method to obtain a myocardial tissue propagation velocity smoothing image and a myocardial tissue acceleration imaging; An analysis report of the imaging data is generated based on the myocardial tissue propagation velocity smoothed image and the myocardial tissue acceleration imaging; wherein the analysis report includes statistical characteristics and spatial distribution information of the data.

[0013] In a fourth aspect, the present invention provides a myocardial fibrosis analysis system, which is used to implement the myocardial fibrosis analysis method of the third aspect, comprising: An ultrasonic probe, used for emitting radiation force shear waves to the heart area to be detected, and receiving reflected echoes from the heart area to be detected; An analog-to-digital conversion module, used for generating a radio frequency data sequence according to the reflected echo; A demodulation module, used for processing the radio frequency data sequence to obtain a demodulated complex data sequence; A first data processing module is used to process the correlation between frames in the complex data sequence to obtain myocardial tissue propagation velocity imaging; The second data processing module processes the myocardial tissue propagation velocity imaging by a smoothing method to obtain a myocardial tissue propagation velocity smoothing image and a myocardial tissue acceleration imaging; The analysis module is used to generate an analysis report of the imaging data based on the myocardial tissue propagation velocity smoothing image and the myocardial tissue acceleration imaging; wherein the analysis report includes the statistical characteristics and spatial distribution information of the data.

[0014] According to a fifth aspect of the present invention, an electronic device is provided, comprising a processor and a memory, wherein the processor is used to execute a computer program stored in the memory to implement the myocardial fibrosis analysis method according to the first aspect.

[0015] In a sixth aspect, the present invention provides a computer-readable storage medium, characterized in that the computer-readable storage medium stores at least one instruction, and when the at least one instruction is executed by a processor, the myocardial fibrosis analysis method as described in the first aspect above is implemented.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: The present invention provides a method for analyzing myocardial fibrosis, which uses an ultrasonic device to emit radiation force shear waves to the heart area to be detected, and receives reflected echoes to generate a radio frequency data sequence. The radio frequency data sequence is demodulated to obtain a complex data sequence, and the correlation between frames in the complex data sequence is processed to obtain myocardial tissue propagation velocity imaging. The myocardial tissue propagation velocity imaging is processed by a smoothing method to obtain a smoothed image of the myocardial tissue propagation velocity, and the myocardial tissue acceleration imaging is calculated at the same time. Based on the smoothed image of the myocardial tissue propagation velocity and the acceleration imaging, an analysis report containing data statistical characteristics and spatial distribution information is generated. The report provides quantitative indicators of the mechanical properties of myocardial tissue, and displays the distribution and degree of myocardial fibrosis through visualization means, providing strong support for clinical decision-making.

[0017] The method of the present invention reveals the mechanical property distribution and dynamic response characteristics of myocardial tissue by analyzing the smoothed image of myocardial tissue propagation velocity and acceleration imaging. Imaging data provides valuable objective basis for medical research and helps to deeply understand the physiological and pathological processes of myocardial tissue. A myocardial fibrosis analysis device, system, electronic device and computer-readable storage medium provided by the present invention also solve the problems raised in the background technology section.

[0018] The present invention utilizes a high-speed ultrasound platform and a signal processing algorithm to improve the precision and accuracy of myocardial fibrosis detection.

[0019] The present invention realizes real-time detection and analysis by optimizing the data collection and transmission process, and provides timely information support for clinical decision-making. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The drawings constituting a part of the present application are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings: Figure 1 This is a flow chart of a method for analyzing myocardial fibrosis according to an embodiment of the present invention; Figure 2 This is a schematic diagram of an animal heart experiment of acoustic radiation force shear wave elastic imaging in an embodiment of the present invention; Figure 3 A schematic diagram of the displacement of radiation force shear waves displayed and tracked using high frame rate ultrasound in an embodiment of the present invention; Figure 4 This is a structural block diagram of a myocardial fibrosis analysis device according to an embodiment of the present invention; Figure 5 The present invention is a structural block diagram of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0021] The present invention will be described in detail below with reference to the accompanying drawings and in combination with embodiments. It should be noted that the embodiments and features in the embodiments of the present application can be combined with each other without conflict.

[0022] The following detailed description is an exemplary description, which is intended to provide further detailed description of the present invention. Unless otherwise specified, all technical terms used in the present invention have the same meaning as those generally understood by those skilled in the art to which the present application belongs. The terms used in the present invention are only for describing specific embodiments, and are not intended to limit exemplary embodiments according to the present invention.

[0023] Example 1 like Figure 1 As shown, a first aspect of an embodiment of the present invention provides a method for analyzing myocardial fibrosis, comprising the following steps: S1, obtaining a reflected echo, and generating a radio frequency data sequence according to the reflected echo; wherein the reflected echo is a reflected echo obtained after the heart area to be detected receives a radiation force shear wave; S2, demodulating the radio frequency data sequence to obtain a demodulated complex data sequence; In step S2, the demodulation processing of the RF data sequence includes: sampling and discretizing the RF data sequence to obtain a discrete signal; applying a fast Fourier transform algorithm to the discrete signal to obtain a frequency domain representation; extracting amplitude and phase information from the frequency domain representation to obtain a complex data sequence.

[0024] S3, processing the correlation between frames in the complex data sequence to obtain myocardial tissue propagation velocity imaging; In step S3, the correlation between frames in the complex data sequence is processed to obtain myocardial tissue propagation velocity imaging, including: extracting frame data at different time points from the complex data sequence; calculating the cross-correlation function between two adjacent frames of data; determining the time interval for the propagation of the shear wave between the two frames of data by finding the maximum value of the cross-correlation function; calculating the propagation velocity of the shear wave based on the time interval for the propagation of the shear wave and the spatial distance between the two frames of data; mapping the shear wave propagation velocity at each position in the myocardial tissue to the corresponding spatial position to obtain myocardial tissue propagation velocity imaging.

[0025] S4, using a smoothing method to process the myocardial tissue propagation velocity imaging to obtain a myocardial tissue propagation velocity smoothing image and a myocardial tissue acceleration imaging; In step S4, the myocardial tissue propagation velocity imaging is processed by a smoothing method to obtain a myocardial tissue propagation velocity smoothed image and a myocardial tissue acceleration imaging; wherein: for each pixel in the myocardial tissue propagation velocity imaging, a pixel value within a preset range around the corresponding pixel is taken; the taken pixel values ​​are weighted averaged according to the weight of the Gaussian kernel to obtain a smoothed pixel value; and a myocardial tissue propagation velocity smoothed image is obtained according to each smoothed pixel value. After obtaining the smoothed propagation velocity image, the myocardial tissue acceleration imaging is obtained by analyzing the rate of change of the propagation velocity.

[0026] S5. Generate an analysis report of the imaging data based on the myocardial tissue propagation velocity smoothed image and the myocardial tissue acceleration imaging; wherein the analysis report includes statistical characteristics and spatial distribution information of the data.

[0027] The myocardial fibrosis analysis method of this scheme finally realizes the judgment of myocardial fibrosis through the steps of transmitting shear waves, receiving reflected echoes, generating radio frequency data sequences, demodulation processing, calculating propagation velocity and acceleration imaging, etc.

[0028] In an optional embodiment, a method for analyzing myocardial fibrosis is also provided, comprising the following steps: S10, obtaining reflected echoes, and generating a radio frequency data sequence according to the reflected echoes; wherein the reflected echoes are reflected echoes obtained after the heart area to be detected receives the radiation force shear wave.

[0029] Specifically, the detection process is initiated by emitting radiation force shear waves to the heart area to be detected, wherein the radiation force shear waves are transverse waves that can propagate in myocardial tissue, and the propagation speed is used to reflect the elastic properties of myocardial tissue.

[0030] As an example, the present solution may use an ultrasonic device, such as an ultrasonic probe, to generate and guide shear waves to a region of the heart to be detected. The ultrasonic probe is equipped with a transducer and is capable of generating and receiving ultrasonic signals.

[0031] Optionally, this solution uses a high-performance cardiac probe (fractional bandwidth greater than 90%) connected to a chip from Texas Instruments (TI) to generate focused ultrasound energy to focus on the myocardial area to be measured, artificially inducing acoustic radiation force shear waves. This method can induce shear waves to propagate in myocardial tissue at any time during the cardiac cycle, thereby achieving the evaluation of the degree of myocardial tissue fibrosis by quantifying the shear wave velocity at different phases of the cardiac cycle, and accurately reflecting the changes in myocardial elastic hardness (such as Figure 2 The propagation velocity of the acoustic radiation force shear wave changes with the cardiac cycle, and the natural shear wave propagation velocity at the moment of mitral valve and aortic valve closing can also be measured.

[0032] Figure 2 This is an animal heart experiment of acoustic radiation force shear wave elastography. The propagation velocity of the acoustic radiation force shear wave changes with the cardiac cycle, and the natural shear wave propagation velocity (at the moment of mitral valve and aortic valve closure) is also measured. Shear wave speed, shear wave speed; MVC, mitral valve closure; AVC, aortic closure.

[0033] It should be noted that in actual use, the frequency and intensity of the shear wave are suitable for the detection of myocardial tissue and will not cause unnecessary damage to the heart. For example, the shear wave frequency range in the myocardial tissue detection of this scheme is 2-6mHz; the intensity is 0.002~0.5W / cmSPTA.

[0034] When performing heart testing, the direction and position of the shear wave can be controlled by controlling the ultrasound probe to cover all areas to be tested.

[0035] Specifically, when the shear wave propagates in the myocardial tissue, it interacts with the myocardial tissue and generates a reflected echo.

[0036] As an example, the present solution may use a receiving transducer of an ultrasonic device to capture reflected echoes.

[0037] It should be noted that, in order to capture the reflected signal, receiving transducers with different sensitivities can be selected according to actual needs.

[0038] Specifically, the received reflected echo is converted into a radio frequency (RF) signal to generate a radio frequency data sequence.

[0039] As an example, an analog-to-digital converter may be used to convert an analog signal of a receiving transducer into a digital signal and generate a radio frequency data sequence.

[0040] S20. Demodulate the radio frequency data sequence to obtain a demodulated complex data sequence.

[0041] In step S20, the demodulation processing of the RF data sequence includes: sampling and discretizing the RF data sequence to obtain a discrete signal; applying a fast Fourier transform algorithm to the discrete signal to obtain a frequency domain representation; extracting amplitude and phase information from the frequency domain representation to obtain a complex data sequence.

[0042] Specifically, the radio frequency data sequence is demodulated to extract information related to the elastic properties of the myocardial tissue and generate a complex data sequence IQ (in-phase / quadrature, IQ).

[0043] As an example, the present solution uses a digital signal processing algorithm (such as a fast Fourier transform) to demodulate the RF data sequence.

[0044] The process of fast Fourier transform is as follows: (1) The RF data sequence is sampled and discretized to obtain a discrete signal x(n) of length N, where n = 0, 1, ..., N-1.

[0045] (2) Apply the fast Fourier transform algorithm to the discrete signal x[n] to obtain its frequency domain representation X(k); where k = 0, 1, ..., N-1. The core idea of ​​the FFT algorithm is to decompose the DFT into smaller DFTs and calculate them recursively or iteratively, thereby greatly improving the computational efficiency.

[0046] The discrete Fourier transform (DFT) formula is as follows:

[0047] Where X(k) is the frequency domain representation, x[n] is the time domain signal, N is the signal length, and j is the imaginary unit.

[0048] (3) Extracting amplitude and phase information from the frequency domain representation X(k) to obtain a complex data sequence, wherein each element of the complex data sequence contains amplitude and phase information for subsequent analysis and processing.

[0049] The complex data sequence can be expressed as:

[0050] Where Z(n) is the nth element of the complex data sequence, A(n) is the amplitude, ϕ ( n ) is the phase.

[0051] Preferably, the demodulated complex data sequence is verified and calibrated.

[0052] Furthermore, the currently widely used ultrasound platform Verasonics System has a high-speed serial computer expansion bus (PCIE) upload bandwidth that is smaller than the data bandwidth of the original RF signal, and cannot achieve real-time upload while collecting data. It needs to be cached in a local memory with a small capacity (only 64MB per channel), and then read from the local memory and transmitted to the host computer through the PCIE high-speed transmission line. This process greatly limits the duration of continuous acquisition and is not conducive to obtaining sufficient detection data. This solution processes the RF data sequence in the host computer. The computer is equipped with data processing software. Among them, the system PCIE upload bandwidth is greater than the data bandwidth, and there is no transmission bottleneck for data upload. It can be directly uploaded to the host computer and written to the high-speed solid-state hard drive in real time. In this way, the continuous acquisition duration is only limited by the hard disk capacity, and the system PCIE of this solution can collect long-term data of 5-10 seconds. Extending the acquisition time helps to track more shear wave signals and provide more sufficient data support for accurate assessment of myocardial fibrosis.

[0053] S30, processing the correlation between frames in the complex data sequence to obtain myocardial tissue propagation velocity imaging.

[0054] In step S30, the correlation between frames in the complex data sequence is processed to obtain myocardial tissue propagation velocity imaging, including: extracting frame data at different time points from the complex data sequence; calculating the cross-correlation function between two adjacent frames of data; determining the time interval for the shear wave to propagate between the two frames of data by finding the maximum value of the cross-correlation function; calculating the propagation velocity of the shear wave based on the time interval for the shear wave propagation and the spatial distance between the two frames of data; mapping the shear wave propagation velocity at each position in the myocardial tissue to the corresponding spatial position to obtain myocardial tissue propagation velocity imaging.

[0055] Specifically, this solution can calculate the propagation velocity of the shear wave in the myocardial tissue and generate myocardial tissue propagation velocity imaging by analyzing the correlation between different frames in the complex data sequence.

[0056] As an example, this solution uses a correlation analysis algorithm to calculate the propagation velocity of the shear wave and generate imaging results.

[0057] In this step, the propagation velocity of the shear wave is calculated by analyzing the correlation between different frames in the complex data sequence. The complex data sequence contains the response information of the myocardial tissue to the shear wave. By comparing the data at different time points (i.e., different frames), the propagation of the shear wave in the myocardial tissue can be evaluated.

[0058] The process of calculating shear wave propagation velocity using the correlation analysis algorithm is as follows: (1) Extract frame data at different time points from the complex data sequence. Assuming there are N frames of data, each containing M sampling points, the complex data sequence is represented as an N×M matrix.

[0059] (2) For two adjacent frames of data (or two frames of data separated by a fixed time interval), calculate the correlation between them.

[0060] Correlation is achieved by calculating the cross-correlation function between two signals. The formula of the cross-correlation function is:

[0061] in, x ( n )and y ( n ) are the complex representations of the two frames of data, y ∗ ( n )yes y ( n ), τ is the time delay (or frame interval).

[0062] In practical applications, all possible τ The values ​​are calculated to find the maximum correlation value.

[0063] (3) The time required for the shear wave to propagate from one station to another is determined by finding the maximum value of the cross-correlation function. This time is the time interval between the propagation of the shear wave between two frames of data.

[0064] (4) Given the shear wave propagation time and the spatial distance between two frames of data (i.e., the position change of the ultrasound probe or the depth of the myocardial tissue), the formula v =Δ td To calculate the shear wave propagation velocity, v is the propagation speed, d is the spatial distance, Δ t is the propagation time.

[0065] (5) For each pair of adjacent frames (or frames with a fixed time interval), repeat the above steps to calculate the shear wave propagation velocity at each position in the myocardial tissue. By mapping these velocity values ​​to the corresponding spatial positions, the propagation velocity imaging of the myocardial tissue can be generated.

[0066] Through the above process, the propagation velocity distribution of shear waves in myocardial tissue is obtained, and then the elastic properties of myocardial tissue are analyzed, providing an important basis for the detection of myocardial fibrosis.

[0067] S40, using a smoothing method to process the myocardial tissue propagation velocity imaging to obtain a myocardial tissue propagation velocity smoothed image and a myocardial tissue acceleration imaging.

[0068] In step S40, the myocardial tissue propagation velocity imaging is processed by a smoothing method to obtain a myocardial tissue propagation velocity smoothed image and a myocardial tissue acceleration imaging; wherein: for each pixel in the myocardial tissue propagation velocity imaging, a pixel value within a preset range around the corresponding pixel is taken; the taken pixel values ​​are weighted averaged according to the weight of the Gaussian kernel to obtain a smoothed pixel value; and a myocardial tissue propagation velocity smoothed image is obtained according to each smoothed pixel value. After obtaining the smoothed propagation velocity image, the myocardial tissue acceleration imaging is obtained by analyzing the rate of change of the propagation velocity.

[0069] Specifically, a smoothing method is used to process the myocardial tissue propagation velocity imaging to obtain a myocardial tissue propagation velocity smoothed image and a myocardial tissue acceleration imaging TVI (Tissue Velocity imaging, TVI).

[0070] Specifically, the myocardial tissue propagation velocity imaging is smoothed to reduce the influence of noise and artifacts, and a myocardial tissue propagation velocity smoothed image is generated. By analyzing the change rate of the propagation velocity, the myocardial tissue acceleration imaging can be obtained.

[0071] Specifically, this solution uses an image smoothing algorithm (such as Gaussian smoothing) to smooth the imaging results, and generates acceleration imaging by calculating the rate of change of the propagation velocity.

[0072] The process of Gaussian smoothing to smooth the imaging results is as follows: (1) Selecting the Gaussian kernel: The core of Gaussian smoothing is the Gaussian function, which describes the spatial weight distribution of the smoothing operation. The size of the Gaussian kernel (i.e., the standard deviation σ) determines the degree of smoothing. A larger σ value will result in a stronger smoothing effect, but it may also blur out some detail information. Therefore, when selecting the Gaussian kernel, a trade-off needs to be made based on the noise level of the imaging result and the need to retain detail.

[0073] The formula for the Gaussian function is:

[0074] in, x and y are pixel coordinates; σ is the standard deviation, which determines the width of the Gaussian function.

[0075] (2) Applying Gaussian kernel: Apply the selected Gaussian kernel to each pixel of the myocardial tissue propagation velocity imaging. Specifically, for each pixel in the imaging, take the pixel values ​​within a certain range around it (determined by the size of the Gaussian kernel), and then perform weighted averaging of these pixel values ​​according to the weight of the Gaussian kernel to obtain the smoothed pixel value.

[0076] The formula for smoothing is:

[0077] in, I ( x , y ) is the pixel value of the original image, I smooth( x , y ) is the smoothed pixel value, k is the radius of the Gaussian kernel (i.e. the pixel range covered), G ( i , j , σ ) is the Gaussian kernel at position ( i , j )’s weight.

[0078] (3) Generating a smoothed image: The above-mentioned Gaussian smoothing process is applied to each pixel in the image to obtain a smoothed image of the propagation velocity of myocardial tissue.

[0079] (4) Computational acceleration imaging: After obtaining the smoothed propagation velocity image, the myocardial tissue acceleration imaging can be obtained by analyzing the rate of change of the propagation velocity (i.e., acceleration).

[0080] The formula for acceleration (in discrete form) is approximately:

[0081] Among them, a( x,y ) is the acceleration, Δ v(x,y) is the change in propagation speed between adjacent pixels, Δ t is the time interval (in the discrete case, it can be considered as the time difference between adjacent frames). x and Δ y The pixels are x and y Spacing in direction.

[0082] Through the above-mentioned Gaussian smoothing process, a smoothed image of the propagation velocity of myocardial tissue and an acceleration image can be obtained, providing clearer and more accurate data support for subsequent judgment of myocardial fibrosis.

[0083] In the above steps, high frame rate ultrasound is used to display and track the displacement of the radiation force shear wave. The B-mode ultrasound image is obtained by processing the channel data of 6 divergent waves, and the radiofrequency (RF) data sequence is processed to obtain the demodulated complex data sequence (in-phase / quadrature, IQ). By processing the correlation between the frames of the IQ data sequence, the myocardial tissue propagation velocity imaging (Tissue Velocity imaging, TVI) is obtained, and the shear wave propagation velocity is measured on the TVI image (as shown in Figure 3). Its smoothed image TVI is obtained by applying the smoothing method to TVI*, and tissue acceleration imaging (TAI) can also be obtained.

[0084] Figure 3 It uses high frame rate ultrasound to display and track the displacement of radiation force shear waves. B-mode ultrasound images are obtained by processing the channel data of 6 divergent waves, and the propagation velocity imaging (Tissue Velocity imaging, TVI) of myocardial tissue is obtained by processing the correlation of IQ data between frames (demodulated complex data sequence: in-phase / quadrature, IQ). Smoothed image TVI is obtained by applying smoothing method to TVI*, and TAI (Tissue Acceleration imaging) is tissue acceleration imaging. S50, generating an analysis report of the imaging data according to the myocardial tissue propagation velocity smoothed image and the myocardial tissue acceleration imaging; wherein the analysis report includes statistical characteristics and spatial distribution information of the data.

[0085] Specifically, statistical feature analysis includes: Statistical characteristics of propagation velocity smoothing image: Calculate the statistical indicators such as average propagation velocity, standard deviation, maximum value and minimum value in the propagation velocity smoothing image of myocardial tissue. These indicators reflect the overall and local propagation velocity characteristics of myocardial tissue.

[0086] Statistical characteristics of acceleration imaging: Similarly, statistical indicators such as the average acceleration, standard deviation, maximum value, and minimum value in myocardial tissue acceleration imaging are calculated. These indicators provide a quantitative description of the dynamic response of myocardial tissue.

[0087] Specifically, the spatial distribution information analysis includes: Spatial distribution of smoothed propagation velocity images: Visualize the smoothed propagation velocity images of myocardial tissue and observe the changes in propagation velocity in different areas.

[0088] Spatial distribution of acceleration imaging: Similarly, myocardial tissue acceleration imaging is displayed to observe the trend of acceleration changes in different regions. Abnormal distribution of acceleration reveals changes in the mechanical properties of myocardial tissue or potential pathological processes.

[0089] This report reveals the distribution of mechanical properties and dynamic response characteristics of myocardial tissue through detailed analysis of smoothed images and acceleration imaging of myocardial tissue propagation velocity. These imaging data provide valuable objective basis for medical research and are conducive to a deeper understanding of the physiological and pathological processes of myocardial tissue.

[0090] Please note that this report only provides an objective description and analysis of imaging data and does not involve specific disease diagnosis. All analyses are based on the statistical characteristics and spatial distribution information of imaging data, and are intended to support further medical research and clinical analysis. This protocol is an information processing method in which all steps are implemented by computers and other devices, with the purpose of providing data analysis reports to support clinical research.

[0091] In some other embodiments, an image analysis algorithm may be used to compare the elastic properties of myocardial tissue with normal standards to provide information on the probability of fibrosis, but the diagnosis result is not directly output. The specific process is as follows: (1) Setting normal standards Set the normal range or standard value of propagation velocity and acceleration of myocardial tissue under normal conditions. The standard can be derived based on the test data of a large number of healthy people, or can refer to medical literature or expert consensus.

[0092] (2) Feature extraction Key features are extracted from the smoothed propagation velocity image and acceleration imaging of myocardial tissue, such as the average propagation velocity, the standard deviation of the propagation velocity, the maximum acceleration, the rate of change of acceleration, etc. The features can reflect the elastic properties of myocardial tissue.

[0093] (3) Comparison and analysis The extracted feature values ​​are compared with the set normal standards. Statistical methods (such as Z-scores, t-tests, etc.) can be used to quantify the degree of difference, or machine learning algorithms (such as support vector machines, neural networks, etc.) can be used for classification judgment. According to the comparison results, if the elastic properties of myocardial tissue are significantly different from the normal standard (such as a significant slowing of propagation speed, abnormal changes in acceleration, etc.), it is judged that myocardial fibrosis may occur (probability value information).

[0094] (3.1) Z score: used to quantify the degree of difference between the characteristic value and the normal standard. The formula is:

[0095] in, X is the eigenvalue, μis the average value of normal standards. σ is the standard deviation of the normal standard.

[0096] (3.2) t-test: used to compare whether there is a significant difference between the means of two groups of data. The formula is:

[0097] in, and is the mean of the two sets of data, μ 1 and μ 2 is the theoretical mean of the two sets of data (which can be set as the normal standard here), s pooled is the pooled standard deviation, n 1 and n 2 is the sample size of the two sets of data.

[0098] (3.3) Machine learning algorithms: such as support vector machines, neural networks, etc. Automatically extract features and make classification decisions by learning from a large amount of training data.

[0099] Another aspect of the present invention provides a method for analyzing myocardial fibrosis, comprising the following steps: emitting radiation force shear waves to the area to be detected in the heart; Receiving reflected echo from the area to be detected in the heart; generating a radio frequency data sequence according to the reflected echo; Processing the radio frequency data sequence to obtain a demodulated complex data sequence; Processing the correlation between frames in the complex data sequence to obtain myocardial tissue propagation velocity imaging; The myocardial tissue propagation velocity imaging is processed by a smoothing method to obtain a myocardial tissue propagation velocity smoothing image and a myocardial tissue acceleration imaging; An analysis report of the imaging data is generated based on the myocardial tissue propagation velocity smoothed image and the myocardial tissue acceleration imaging; wherein the analysis report includes statistical characteristics and spatial distribution information of the data.

[0100] In another aspect of the embodiments of the present invention, a system for implementing the above-mentioned myocardial fibrosis analysis method is provided, comprising: An ultrasonic probe, used for emitting radiation force shear waves to the heart area to be detected, and receiving reflected echoes from the heart area to be detected; An analog-to-digital conversion module, used for generating a radio frequency data sequence according to the reflected echo; A demodulation module, used for processing the radio frequency data sequence to obtain a demodulated complex data sequence; A first data processing module is used to process the correlation between frames in the complex data sequence to obtain myocardial tissue propagation velocity imaging; The second data processing module processes the myocardial tissue propagation velocity imaging by a smoothing method to obtain a myocardial tissue propagation velocity smoothing image and a myocardial tissue acceleration imaging; The analysis module is used to generate an analysis report of the imaging data based on the myocardial tissue propagation velocity smoothing image and the myocardial tissue acceleration imaging; wherein the analysis report includes the statistical characteristics and spatial distribution information of the data.

[0101] The above-mentioned system, the steps involved in each module and the calculation formula have been introduced in the method embodiment and will not be repeated here.

[0102] Example 2 like Figure 4 As shown, based on the same inventive concept as the above embodiment, the present invention also provides a myocardial fibrosis analysis device for implementing a myocardial fibrosis analysis method, comprising: A data conversion module is used to obtain a reflected echo and generate a radio frequency data sequence according to the reflected echo; wherein the reflected echo is a reflected echo obtained after the heart area to be detected receives a radiation force shear wave; A demodulation module, used for demodulating the radio frequency data sequence to obtain a demodulated complex data sequence; A first data processing module is used to process the correlation between frames in the complex data sequence to obtain myocardial tissue propagation velocity imaging; A second data processing module is used to process the myocardial tissue propagation velocity imaging by a smoothing method to obtain a myocardial tissue propagation velocity smoothing image and a myocardial tissue acceleration imaging; The analysis module is used to generate an analysis report of the imaging data based on the myocardial tissue propagation velocity smoothing image and the myocardial tissue acceleration imaging; wherein the analysis report includes the statistical characteristics and spatial distribution information of the data.

[0103] Example 3 like Figure 5 As shown, the present invention also provides an electronic device 100 for implementing the myocardial fibrosis analysis method; The electronic device 100 includes a memory 101 , at least one processor 102 , a computer program 103 stored in the memory 101 and executable on the at least one processor 102 , and at least one communication bus 104 .

[0104] The memory 101 can be used to store a computer program 103 . The processor 102 implements the steps of a myocardial fibrosis analysis method in Example 1 by running or executing the computer program stored in the memory 101 and calling the data stored in the memory 101 .

[0105] The memory 101 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data (such as audio data) created according to the use of the electronic device 100, etc. In addition, the memory 101 may include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other non-volatile solid-state storage devices.

[0106] At least one processor 102 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The processor 102 may be a microprocessor or any conventional processor, etc. The processor 102 is the control center of the electronic device 100, and uses various interfaces and lines to connect various parts of the entire electronic device 100.

[0107] The memory 101 in the electronic device 100 stores a plurality of instructions to implement a myocardial fibrosis analysis method, and the processor 102 can execute the plurality of instructions to implement: Acquire a reflected echo, and generate a radio frequency data sequence according to the reflected echo; wherein the reflected echo is a reflected echo obtained after the heart area to be detected receives the radiation force shear wave; Demodulating the radio frequency data sequence to obtain a demodulated complex data sequence; Processing the correlation between frames in the complex data sequence to obtain myocardial tissue propagation velocity imaging; Processing the myocardial tissue propagation velocity imaging using a smoothing method to obtain a myocardial tissue propagation velocity smoothing image and a myocardial tissue acceleration imaging; An analysis report of the imaging data is generated based on the myocardial tissue propagation velocity smoothed image and the myocardial tissue acceleration imaging; wherein the analysis report includes statistical characteristics and spatial distribution information of the data.

[0108] Example 4 If the module / unit integrated in the electronic device 100 is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. Computer-readable media may include: any entity or device capable of carrying computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory and read-only memory (ROM, Read-Only Memory).

[0109] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0110] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0111] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0112] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0113] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0114] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for analyzing myocardial fibrosis, characterized in that: include: Acquire a reflected echo, and generate a radio frequency data sequence according to the reflected echo; wherein the reflected echo is a reflected echo obtained after the heart area to be detected receives the radiation force shear wave; Demodulating the radio frequency data sequence to obtain a demodulated complex data sequence; Processing the correlation between frames in the complex data sequence to obtain myocardial tissue propagation velocity imaging; Processing the myocardial tissue propagation velocity imaging using a smoothing method to obtain a myocardial tissue propagation velocity smoothing image and a myocardial tissue acceleration imaging; An analysis report of the imaging data is generated based on the myocardial tissue propagation velocity smoothed image and the myocardial tissue acceleration imaging; wherein the analysis report includes statistical characteristics and spatial distribution information of the data.

2. The method for analyzing myocardial fibrosis according to claim 1, characterized in that: The demodulating the radio frequency data sequence includes: The radio frequency data sequence is sampled and discretized to obtain a discrete signal; Apply the Fast Fourier Transform algorithm to the discrete signal to obtain a frequency domain representation; The amplitude and phase information are extracted from the frequency domain representation to obtain a complex data sequence.

3. The method for analyzing myocardial fibrosis according to claim 1, characterized in that: The processing of the correlation between frames in the complex data sequence to obtain myocardial tissue propagation velocity imaging includes: Extract frame data at different time points from the complex data sequence; Calculate the cross-correlation function between two adjacent frames of data; The time interval of shear wave propagation between two frames of data is determined by finding the maximum value of the cross-correlation function; The propagation speed of the shear wave is calculated according to the time interval of the shear wave propagation and the spatial distance between two frames of data; The shear wave propagation velocity at each position in the myocardial tissue is mapped to the corresponding spatial position to obtain myocardial tissue propagation velocity imaging.

4. The method for analyzing myocardial fibrosis according to claim 1, characterized in that: The myocardial tissue propagation velocity imaging is processed by a smoothing method to obtain a myocardial tissue propagation velocity smoothing image and a myocardial tissue acceleration imaging; wherein: For each pixel in the myocardial tissue propagation velocity imaging, the pixel value within a preset range around the corresponding pixel is taken; The pixel values ​​are weighted averaged according to the weight of the Gaussian kernel to obtain the smoothed pixel value; A myocardial tissue propagation velocity smoothing image is obtained according to each smoothed pixel value.

5. The method for analyzing myocardial fibrosis according to claim 4, characterized in that: The myocardial tissue propagation velocity imaging is processed by a smoothing method to obtain a myocardial tissue propagation velocity smoothing image and a myocardial tissue acceleration imaging; wherein: After obtaining the smoothed propagation velocity image, the myocardial tissue acceleration imaging is obtained by analyzing the change rate of the propagation velocity.

6. A myocardial fibrosis analysis device, characterized in that: A method for analyzing myocardial fibrosis according to any one of claims 1 to 5, comprising: A data conversion module is used to obtain a reflected echo and generate a radio frequency data sequence according to the reflected echo; wherein the reflected echo is a reflected echo obtained after the heart area to be detected receives the radiation force shear wave; A demodulation module, used for demodulating the radio frequency data sequence to obtain a demodulated complex data sequence; A first data processing module is used to process the correlation between frames in the complex data sequence to obtain myocardial tissue propagation velocity imaging; A second data processing module is used to process the myocardial tissue propagation velocity imaging by a smoothing method to obtain a myocardial tissue propagation velocity smoothing image and a myocardial tissue acceleration imaging; The analysis module is used to generate an analysis report of the imaging data based on the myocardial tissue propagation velocity smoothing image and the myocardial tissue acceleration imaging; wherein the analysis report includes the statistical characteristics and spatial distribution information of the data.

7. A method for analyzing myocardial fibrosis, characterized in that: The steps include: emitting radiation force shear waves to the area to be detected in the heart; Receiving reflected echo from the area to be detected in the heart; generating a radio frequency data sequence according to the reflected echo; Processing the radio frequency data sequence to obtain a demodulated complex data sequence; Processing the correlation between frames in the complex data sequence to obtain myocardial tissue propagation velocity imaging; The myocardial tissue propagation velocity imaging is processed by a smoothing method to obtain a myocardial tissue propagation velocity smoothing image and a myocardial tissue acceleration imaging; An analysis report of the imaging data is generated based on the myocardial tissue propagation velocity smoothed image and the myocardial tissue acceleration imaging; wherein the analysis report includes statistical characteristics and spatial distribution information of the data.

8. A myocardial fibrosis analysis system, used to implement the myocardial fibrosis analysis method according to claim 7, characterized in that: include: An ultrasonic probe, used for emitting radiation force shear waves to the heart area to be detected, and receiving reflected echoes from the heart area to be detected; An analog-to-digital conversion module, used for generating a radio frequency data sequence according to the reflected echo; A demodulation module, used for processing the radio frequency data sequence to obtain a demodulated complex data sequence; A first data processing module is used to process the correlation between frames in the complex data sequence to obtain myocardial tissue propagation velocity imaging; The second data processing module processes the myocardial tissue propagation velocity imaging by a smoothing method to obtain a myocardial tissue propagation velocity smoothing image and a myocardial tissue acceleration imaging; The analysis module is used to generate an analysis report of the imaging data based on the myocardial tissue propagation velocity smoothing image and the myocardial tissue acceleration imaging; wherein the analysis report includes the statistical characteristics and spatial distribution information of the data.

9. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the processor is used to execute a computer program stored in the memory to implement the myocardial fibrosis analysis method according to any one of claims 1 to 4.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores at least one instruction, and when the at least one instruction is executed by a processor, the method for analyzing myocardial fibrosis according to any one of claims 1 to 4 is implemented.

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