Method and device for monitoring myocardial blood flow in quasi-periodic motion during operation

Abstract

The invention provides a method and device for monitoring quasi-periodic motion myocardial blood flow in an operation, and the method comprises the steps: determining a monitoring motion period, sequentially obtaining a laser speckle image group of a to-be-observed myocardial region in each motion period, and enabling each laser speckle image group to comprise multiple frames of laser speckle images; according to each laser speckle image group, respectively determining a plurality of blood flow index distribution images of the to-be-observed myocardial area in each motion period; the numerical gradient of each blood flow index distribution image is determined; respectively determining the standard deviation of the numerical gradient of each blood flow index distribution image; and according to the standard deviation of the numerical gradient of each blood flow index distribution image and a preset reference value, respectively determining a focused blood flow index distribution image in each motion period. According to the method and device for monitoring the myocardial blood flow in the quasi-periodic motion in the operation, the problem that the accurate evaluation of the blood flow information is interfered by the heart quasi-periodic motion can be solved, and the accuracy of monitoring the myocardial blood flow in the operation is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of biomedical imaging, and in particular to a method and a device for monitoring quasi-periodic motion myocardial blood flow during surgery. Background Art

[0002] Laser speckle contrast imaging technology has been widely used in the blood flow rate distribution monitoring of organs such as the brain, skin, retina, kidney, and heart due to its advantages of wide-field imaging, high spatiotemporal resolution, non-contact, and green and non-toxic. Laser speckle blood flow imaging technology constructs the blood flow rate distribution by analyzing the dynamic / static characteristic distribution of the coherent light field. Different from the above-mentioned organ characteristics, the heart is in quasi-periodic motion (contraction / diastole) in real time, and the use of ventilators during surgery adds a larger amplitude of periodic motion to the heart. These motion noises, on the one hand, will cause the blood flow images collected by the camera to focus and defocus repeatedly with the movement of the heart, that is, motion blur; on the other hand, it will seriously reduce or even submerge the effective information of myocardial coronary blood flow rate. Therefore, overcoming the quasi-periodic motion of the heart is the first priority for applying laser speckle blood flow imaging to in vivo myocardial blood flow monitoring in cardiac surgery. At present, there are two main technical routes to overcome motion imaging, including: shortening the single-frame imaging time-"freezing" within the exposure time, and equivalent stillness of the imaging space-"freezing" within the projection space. Using high-speed cameras to shorten the single-frame time not only collects a small number of speckle images, affecting the accuracy of the statistical characteristic values ​​of the speckle images, but also the high cost of high-speed cameras. At the same time, expensive high-speed image acquisition software and high-performance engineering machines are required to complete the high-speed acquisition, transmission and storage of speckle images, which is not conducive to product development and promotion.

[0003] In addition, laser speckle blood flow imaging technology relies on laser speckle blood flow imaging systems. In recent years, domestic and foreign scholars have made important progress in the optimization of laser speckle blood flow imaging systems. In 1996, Kingston University in the United States proposed laser speckle contrast imaging technology to achieve retinal and skin blood flow speckle imaging. In 2008, the University of Texas considered the influence of static scattering noise for the first time, established a multiple exposure speckle imaging model, and realized in vivo experimental verification of the theoretical model. In 2016, Huazhong University of Science and Technology analyzed system coherence parameters, static scattering ratio and other factors to further improve the blood flow rate assessment range and sensitivity. In 2020, Boston University systematically analyzed the multiple scattering types of red blood cells in the blood flow, and established a dynamic scattered light imaging model to improve the accuracy of cortical blood flow measurement. Subsequently, in 2023, the team systematically analyzed the influence of speckle size to pixel size ratio, polarization, exposure time and camera noise, and improved the accuracy of blood flow rate assessment and imaging resolution. The above method or device can realize real-time imaging of low blood flow rate in the surface or shallow cerebral cortex, retina, kidney and other veins in a simple and stable environment. However, multi-parameter optimization of myocardial coronary artery blood flow rate imaging devices still needs to be studied. Summary of the invention

[0004] The present invention provides a method and device for monitoring quasi-periodic motion myocardial blood flow during surgery, aiming to solve the problem that the quasi-periodic motion of the heart interferes with the accurate evaluation of blood flow information.

[0005] In order to solve the above problems, the present invention provides a method for monitoring quasi-periodic motion myocardial blood flow during surgery, comprising:

[0006] Determine a monitoring motion cycle, and sequentially obtain a laser speckle image group of the myocardial area to be observed in each motion cycle, each of the laser speckle image groups including multiple frames of laser speckle images;

[0007] Determining a plurality of blood flow index distribution images of the myocardial area to be observed in each movement cycle according to each of the laser speckle image groups;

[0008] respectively determining the numerical gradient of each of the blood flow index distribution images;

[0009] respectively determining the standard deviation of the numerical gradient of each of the blood flow index distribution images;

[0010] According to the standard deviation of the numerical gradient of each of the blood flow index distribution images and a preset reference value, a focused blood flow index distribution image in each of the motion cycles is determined respectively.

[0011] According to a method for monitoring quasi-periodic motion myocardial blood flow during surgery provided by the present invention, determining a plurality of blood flow index distribution images of the myocardial region to be observed in each motion cycle according to each laser speckle image group includes:

[0012] According to each of the laser speckle image groups, respectively determining a spatial speckle contrast matrix and a temporal speckle contrast matrix corresponding to each of the laser speckle image groups;

[0013] Get system related parameters,

[0014] Determining a dynamic scattering component ratio coefficient of the myocardial area to be observed according to the system coherence parameter, the spatial speckle contrast matrix and the temporal speckle contrast matrix;

[0015] Determining the blood flow index distribution image corresponding to each of the laser speckle image groups according to the system coherence parameter, the spatial speckle contrast matrix and the dynamic scattering component ratio coefficient;

[0016] Determine a plurality of blood flow index distribution images of the myocardial area to be observed in each movement cycle.

[0017] According to a method for monitoring quasi-periodic motion myocardial blood flow during surgery provided by the present invention, determining, according to each of the laser speckle image groups, a spatial speckle contrast matrix and a temporal speckle contrast matrix corresponding to each of the laser speckle image groups, respectively, comprises:

[0018] Using a spatial sliding window to traverse each of the laser speckle images in each of the laser speckle image groups frame by frame, and respectively determining a speckle contrast matrix of each of the laser speckle images in space, so as to determine a spatial speckle contrast matrix;

[0019] According to each of the laser speckle images, the speckle contrast of the same pixel of each of the laser speckle images in the time series is determined respectively to determine a time speckle contrast matrix.

[0020] According to a method for monitoring quasi-periodic motion myocardial blood flow during surgery provided by the present invention, the acquisition of system coherent parameters includes:

[0021] Acquire a multi-frame laser speckle image of any area of ​​a static scattering medium within a preset exposure time;

[0022] Determining the average spatial speckle contrast of the arbitrary area according to the multiple frames of the laser speckle images;

[0023] According to the average spatial speckle contrast of the area, the system coherence parameter is determined based on the following formula;

[0024] β≈K s 2

[0025] Where β is the system coherence parameter and Ks is the spatial speckle contrast.

[0026] According to a method for intraoperative monitoring of quasi-periodic motion myocardial blood flow provided by the present invention, determining the dynamic scattering component ratio coefficient of the myocardial area to be observed according to the system coherence parameter, the spatial speckle contrast matrix and the temporal speckle contrast matrix includes:

[0027] determining an average spatial speckle contrast according to the spatial speckle contrast matrix;

[0028] determining an average temporal speckle contrast according to the temporal speckle contrast matrix;

[0029] Determine a dynamic scattering component proportional coefficient based on the following formula according to the average spatial speckle contrast, the average temporal speckle contrast and the system coherence parameter;

[0030]

[0031]

[0032]

[0033]

[0034] Among them, K s is the spatial speckle contrast, β is the system coherence parameter, ρ is the dynamic scattering component ratio coefficient, x is the blood flow index, T is the exposure time, τ c is the decoherence time of the scattering medium, K t is the temporal speckle contrast.

[0035] According to a method for monitoring quasi-periodic motion myocardial blood flow during surgery provided by the present invention, determining the blood flow index distribution image corresponding to each laser speckle image group according to the system coherence parameter, the spatial speckle contrast matrix and the dynamic scattering component ratio coefficient includes:

[0036] According to the system coherence parameter, the spatial speckle contrast matrix, and the dynamic scattering component ratio coefficient, based on the following formula, a blood flow index matrix corresponding to each of the laser speckle image groups is determined;

[0037]

[0038]

[0039] According to each of the blood flow index matrices, respectively determining a blood flow index distribution image corresponding to each of the laser speckle image groups;

[0040] Among them, K s is the spatial speckle contrast, β is the system coherence parameter, ρ is the dynamic scattering component ratio coefficient, x is the blood flow index, T is the exposure time, τ c is the decoherence time of the scattering medium.

[0041] According to a method for intraoperative monitoring of quasi-periodic motion myocardial blood flow provided by the present invention, determining the focused blood flow index distribution image under each motion cycle according to the standard deviation of the numerical gradient of each blood flow index distribution image and a preset reference value includes:

[0042] Calculating a preset reference value according to a preset rule based on a standard deviation of the numerical gradient of each of the blood flow index distribution images;

[0043] The standard deviation of the numerical gradient of each of the blood flow index distribution images is compared with the preset reference value, and the blood flow index distribution image with a standard deviation greater than the preset reference value is determined as the focused blood flow index distribution image.

[0044] According to a method for monitoring quasi-periodic motion myocardial blood flow during surgery provided by the present invention, calculating a preset reference value according to a preset rule includes:

[0045] Select the standard deviation with the value in the top 10% among the standard deviations as the reference standard deviation;

[0046] determining an average of each of the reference standard deviations;

[0047] 85%-95% of the average value of each reference standard deviation is determined as the preset reference value.

[0048] According to a method for intraoperative monitoring of quasi-periodic motion myocardial blood flow provided by the present invention, sequentially acquiring multiple laser speckle image groups of a myocardial area to be observed in each motion cycle includes: sequentially acquiring multiple laser speckle image groups of a myocardial area to be observed in each motion cycle according to an electrocardiogram R wave.

[0049] The present invention also provides a device for monitoring myocardial blood flow in quasi-periodic motion during surgery, and the method for monitoring myocardial blood flow in quasi-periodic motion during surgery as described in any one of the above items comprises:

[0050] A laser illumination module, used for providing illumination to the myocardial area to be observed;

[0051] A laser speckle imaging module, used for sequentially acquiring dynamic speckle images of the myocardial area to be observed in each motion cycle according to preset parameters; and

[0052] The data processing module is used to obtain the focused blood flow index distribution image of the myocardial area to be observed according to each of the dynamic speckle images and preset rules.

[0053] According to a device for intraoperatively monitoring quasi-periodic motion myocardial blood flow provided by the present invention, the laser illumination module includes a near-infrared laser, a first reflector, a second reflector, an optical isolator, a fiber coupler, an optical fiber, a fiber collimator, an aspherical lens, and a pyramid prism arranged in sequence; or, the laser illumination module includes a near-infrared laser, a first reflector, a second reflector, an optical isolator, a fiber coupler, an optical fiber, a fiber collimator, and a scattering sheet arranged in sequence.

[0054] According to a device for monitoring quasi-periodic motion myocardial blood flow during surgery provided by the present invention, the laser speckle imaging module includes an imaging lens, and a polarizer is provided in front of the imaging lens; the acquisition frame rate of the imaging lens is greater than 200 Hz, the exposure time is 50-80 μs, and the gain is set to 8-12.

[0055] According to a device for monitoring quasi-periodic motion myocardial blood flow during surgery provided by the present invention, the ratio of the size of the dynamic speckle image to the pixel size is greater than 2 and less than 5, and the average grayscale value of the dynamic speckle image is greater than one-quarter of the saturation grayscale value and less than one-half of the saturation grayscale value.

[0056] The method for intraoperative monitoring of quasi-periodic motion myocardial blood flow provided by the present invention has the advantages of no ionizing radiation, no damage measurement, no need to inject contrast agents, etc., and can monitor in real time the temporal and spatial evolution of myocardial blood flow distribution with high blood flow rate and high blood flow rate dynamic change range characteristics. In addition, by using numerical gradient and standard deviation as characteristic quantities, the focused blood flow index distribution image can be screened to achieve self-focusing of the moving heart blood flow image, which can effectively overcome the interference of the quasi-periodic motion of the heart on the accurate evaluation of blood flow information. This method can be used to monitor the changes in myocardial blood perfusion before and after coronary artery bypass grafting, which is of great significance for the effective implementation of coronary heart disease surgery and the quantitative evaluation of postoperative effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0058] Figure 1 It is a schematic diagram of the process of the method for intraoperatively monitoring quasi-periodic motion myocardial blood flow provided by the present invention;

[0059] Figure 2 It is a blood flow index distribution image of one cardiac motion cycle in one embodiment of the method for intraoperative monitoring of quasi-periodic motion myocardial blood flow provided by the present invention;

[0060] Figure 3 It is a schematic diagram of screening a focused blood flow index distribution image in one embodiment of the method for intraoperative monitoring of quasi-periodic motion myocardial blood flow provided by the present invention;

[0061] Figure 4 It is a structural schematic diagram of a first embodiment of a laser illumination module in a device for intraoperatively monitoring quasi-periodic motion myocardial blood flow provided by the present invention;

[0062] Figure 5 It is a structural schematic diagram of a second embodiment of a laser illumination module in a device for intraoperatively monitoring quasi-periodic motion myocardial blood flow provided by the present invention;

[0063] Figure 6 It is a schematic diagram comparing test results with and without a polarizer in an embodiment of the device for intraoperative monitoring of quasi-periodic motion myocardial blood flow provided by the present invention;

[0064] Figure 7 This is a schematic diagram comparing test results at different exposure times in one embodiment of the device for monitoring quasi-periodic motion myocardial blood flow during surgery provided by the present invention;

[0065] Figure 8 This is a schematic diagram comparing test results under different camera gains in one embodiment of the device for monitoring quasi-periodic motion myocardial blood flow during surgery provided by the present invention;

[0066] Fig. 9 This is a schematic diagram comparing test results under different dynamic speckle image sizes in one embodiment of the device for monitoring quasi-periodic motion myocardial blood flow during surgery provided by the present invention;

[0067] Fig.10 The diagram is a comparison diagram of test results using a flat-top beam and a Gaussian beam in one embodiment of the device for intraoperatively monitoring quasi-periodic motion myocardial blood flow provided by the present invention. DETAILED DESCRIPTION

[0068] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0069] In the description of the embodiments of the present invention, it should be noted that the terms "center", "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the embodiments of the present invention and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore cannot be understood as limitations on the embodiments of the present invention. In addition, the terms "first", "second", and "third" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance.

[0070] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" 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 embodiment of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0071] Combine the following Figure 1-Figure 10 The present invention describes a method and a device for intraoperatively monitoring blood flow of myocardium in quasi-periodic motion.

[0072] In view of the problem that the quasi-periodic motion of the heart interferes with the accurate assessment of blood flow information in traditional technologies, please refer to Figure 1 The present invention provides a method for monitoring quasi-periodic motion myocardial blood flow during surgery, comprising:

[0073] S100, determining a monitoring motion cycle, and sequentially acquiring a laser speckle image group of a myocardial region to be observed in each motion cycle, each of the laser speckle image groups including multiple frames of laser speckle images;

[0074] S200, determining a plurality of blood flow index distribution images of the myocardial area to be observed in each movement cycle according to each of the laser speckle image groups;

[0075] S300, respectively determining the numerical gradient of each of the blood flow index distribution images;

[0076] S400, respectively determining the standard deviation of the numerical gradient of each of the blood flow index distribution images;

[0077] S500, determining a focused blood flow index distribution image in each of the motion cycles according to a standard deviation of a numerical gradient of each of the blood flow index distribution images and a preset reference value.

[0078] The precise acquisition of quasi-periodic motion heart blood flow information is the first important key step in the application of laser speckle contrast imaging technology to coronary blood flow monitoring in cardiac surgery. In the technical solution provided by the present invention, it is necessary to first determine the monitoring motion cycle. Generally, the monitoring motion cycle must be no less than 15, so that the changes in myocardial blood flow can be more comprehensively characterized. After the monitoring motion cycle is determined, it is necessary to obtain multiple laser speckle image groups of the myocardial area to be observed under each motion cycle. Each laser speckle image group includes multiple continuous frames of laser speckle images. In order to ensure the accuracy of the data, each laser speckle image group should include laser speckle images of the same number of frames. By processing the laser speckle images in each laser speckle image group, each laser speckle image group can be processed to obtain at least one blood flow index distribution image.

[0079] In the technical solution provided by the present invention, it is also necessary to obtain the standard deviation of the numerical gradient of each blood flow index distribution image to compare with the preset reference value, so as to screen out the focused blood flow index distribution image. Due to the random characteristics of speckle, it is impossible to distinguish the image sharpness and judge whether the image is focused only based on the numerical gradient. Therefore, the present invention introduces the calculation of the standard deviation. By comparing the standard deviation with the preset reference value, the focused blood flow index distribution image can be effectively screened out, so as to more accurately characterize the myocardial blood flow in each motion cycle.

[0080] Specifically, S200, determining, according to each of the laser speckle image groups, a plurality of blood flow index distribution images of the myocardial area to be observed in each of the motion cycles, respectively, includes:

[0081] S210, determining a spatial speckle contrast matrix and a temporal speckle contrast matrix corresponding to each of the laser speckle image groups according to the laser speckle image groups;

[0082] S220, obtaining system related parameters,

[0083] S230, determining a dynamic scattering component ratio coefficient of the myocardial area to be observed according to the system coherence parameter, the spatial speckle contrast matrix and the temporal speckle contrast matrix;

[0084] S240, determining the blood flow index distribution image corresponding to each of the laser speckle image groups according to the system coherence parameter, the spatial speckle contrast matrix and the dynamic scattering component ratio coefficient;

[0085] S250, determining a plurality of blood flow index distribution images of the myocardial area to be observed in each movement cycle.

[0086] Specifically, taking a laser speckle image group as an example, according to the multiple frames of laser speckle images in the laser speckle image group, the spatial speckle contrast matrix and the temporal speckle contrast matrix of the multiple frames of laser speckle images can be obtained through data processing. Then, through the spatial speckle contrast matrix, the temporal speckle contrast matrix and the system coherence parameter, the dynamic scattering component ratio coefficient of the myocardial area to be observed can be obtained through data processing, and then the blood flow index matrix of the myocardial area to be observed can be obtained through the above data, that is, the blood flow index distribution image corresponding to each laser speckle image group can be obtained, and then multiple blood flow index distribution images of the myocardial area to be observed in each motion cycle can be comprehensively obtained.

[0087] In the processing and acquisition of blood flow index distribution images, the present invention comprehensively considers the influence of system coherence parameters and dynamic scattering ratio component coefficients, and can obtain a more accurate blood flow index distribution law. At the same time, this method has the advantages of no ionizing radiation, no damage measurement, and no need to inject contrast agents. It can monitor the spatiotemporal evolution of myocardial blood flow distribution with high blood flow rate and high blood flow rate dynamic change range characteristics in real time.

[0088] Further, S210, according to each of the laser speckle image groups, respectively determining a spatial speckle contrast matrix and a temporal speckle contrast matrix corresponding to each of the laser speckle image groups includes:

[0089] S2101, using a spatial sliding window to traverse each of the laser speckle images in each of the laser speckle image groups frame by frame, and respectively determining a speckle contrast matrix of each of the laser speckle images in space to determine a spatial speckle contrast matrix;

[0090] S2102: Determine, according to each of the laser speckle images, the speckle contrast of the same pixel of each of the laser speckle images in the time series, so as to determine a time speckle contrast matrix.

[0091] The main contrast calculation methods of speckle images include spatial contrast analysis and temporal contrast analysis. The present invention combines the above two methods to obtain spatial speckle contrast matrix and temporal speckle contrast matrix respectively, which can reflect the properties of speckle images in multiple dimensions. The spatial contrast analysis is used in S2101. Taking the processing of a frame of laser speckle image as an example, it is first necessary to use a spatial sliding window to traverse the laser speckle image. In the process of sliding the spatial sliding window, the speckle contrast of each area is calculated respectively, so that the speckle contrast matrix of the processed speckle image can be obtained. After processing n laser speckle images in a laser speckle image group in sequence, n speckle contrast matrices can be obtained. Then, the corresponding elements at the same position of the n speckle contrast matrices are added to obtain the average value, and the spatial speckle contrast at the position can be obtained. The spatial speckle contrast obtained at all positions is combined to obtain the spatial speckle contrast matrix.

[0092] The method used in S2202 is time contrast analysis, which calculates the contrast value by counting the original speckle data at the same pixel position in the time series. Specifically, it is necessary to calculate the speckle contrast at the same pixel of each frame of the speckle image, and then sum and average multiple speckle contrasts to obtain the temporal speckle contrast at the pixel. Then, the temporal speckle contrast at each pixel is combined to obtain the temporal speckle contrast matrix. It should be noted that the speckle contrast is calculated according to the formula Just perform the calculation, which is the prior art and will not be elaborated in detail in the present invention.

[0093] Further, S220, the acquiring system coherent parameters includes:

[0094] S2201, acquiring a multi-frame laser speckle image of any area of ​​a static scattering medium within a preset exposure time;

[0095] S2202, determining an average spatial speckle contrast of the arbitrary area according to multiple frames of the laser speckle image;

[0096] S2203, determining a system coherence parameter according to the average spatial speckle contrast of the area based on the following formula;

[0097] β≈K s 2

[0098] Where β is the system coherence parameter and Ks is the spatial speckle contrast.

[0099] It should be noted that when acquiring speckle images and subsequent data processing, using different systems or devices may result in certain result errors. Therefore, this application needs to obtain system coherence parameters to correct the error effects of different systems or devices on the test results.

[0100] First, a comparative example needs to be selected. The present invention selects a static scattering medium as a comparative example. The static scattering medium can be selected from scattering sheets of different roughness, such as scattering sheets of 120 mesh, 220 mesh, 600 mesh, or engineering scattering sheets, or glass substrates that have been sandblasted with TiO2 powder or paint. The present invention does not limit this. Next, select any area on the static scattering medium, obtain multiple frames of laser speckle images of the area, and determine the average spatial speckle contrast based on the laser speckle images. It should be noted that the average spatial speckle contrast can be obtained via a spatial speckle contrast matrix. First, the spatial speckle contrast matrix is ​​obtained using multiple frames of laser speckle images, and then the average value of each element in the matrix is ​​added to obtain the average spatial speckle contrast. Since the static scattering medium is a uniform medium, the average spatial speckle contrast can approximately characterize the spatial speckle contrast of the entire area.

[0101] It should be noted that the spatial speckle contrast and system coherence parameters are related to the following formula:

[0102]

[0103]

[0104] It can be understood that the exposure time is much shorter than the decoherence time of the static scattering medium, so in the above formula, x approaches 0, so the above formula can be rewritten as:

[0105] β≈K s 2

[0106] The system coherence parameters can be obtained through the above steps, and the system coherence parameters can be applied to the subsequent data processing steps to correct the influence of the system on the test results. It should be noted that in the processing of each laser speckle image group, the calculated system coherence parameters are relatively small, and there are only some negligible errors. Therefore, the system coherence parameters calculated by the first laser speckle image group can be directly substituted into other laser speckle image groups for calculation to simplify the calculation process. Of course, the system coherence parameters corresponding to each speckle image group can also be calculated in sequence, and the present invention is not limited to this.

[0107] Specifically, S230, determining the dynamic scattering component ratio coefficient of the myocardial area to be observed according to the system coherence parameter, the spatial speckle contrast matrix and the temporal speckle contrast matrix includes:

[0108] S2301, determining an average spatial speckle contrast according to the spatial speckle contrast matrix;

[0109] S2302, determining an average temporal speckle contrast according to the temporal speckle contrast matrix;

[0110] S2303, determining a dynamic scattering component proportion coefficient according to the average spatial speckle contrast, the average temporal speckle contrast and the system coherence parameter based on the following formula;

[0111]

[0112]

[0113]

[0114]

[0115] Among them, K s is the spatial speckle contrast, β is the system coherence parameter, ρ is the dynamic scattering component ratio coefficient, x is the blood flow index, T is the exposure time, τ c is the decoherence time of the scattering medium, K t is the temporal speckle contrast.

[0116] When calculating the dynamic scattering component proportional coefficient, it is necessary to obtain the average spatial speckle contrast and the average temporal speckle contrast from the spatial speckle contrast matrix and the temporal speckle contrast matrix respectively. The evaluation method is to add each element in the matrix to obtain an average value. In practical applications, since the area to be observed is small, the use of the average spatial speckle contrast and the average temporal speckle contrast will not significantly affect the subsequent calculation of blood flow rate, but will simplify the calculation steps. By combining the formula of spatial speckle contrast with the formula of temporal speckle contrast, the formula of dynamic scattering component proportional coefficient, spatial speckle contrast, temporal speckle contrast and system coherence parameters can be obtained. Since the average spatial speckle contrast, the average temporal speckle contrast and the system coherence parameters have been calculated above, the dynamic scattering component proportional coefficient of the area to be observed can be obtained.

[0117] It should be noted that, since the myocardial area to be observed is generally small, the dynamic scattering component ratio coefficient calculated in each laser speckle image group is approximate. Therefore, the dynamic scattering component ratio coefficient calculated by the first laser speckle image group can be directly substituted into other laser speckle image groups for calculation to simplify the calculation process. Of course, the dynamic scattering component ratio coefficients corresponding to each speckle image group can also be calculated in sequence, and the present invention is not limited to this.

[0118] Further, S240, determining the blood flow index distribution image corresponding to each of the laser speckle image groups according to the system coherence parameter, the spatial speckle contrast matrix and the dynamic scattering component ratio coefficient includes:

[0119] S2401, determining a blood flow index matrix corresponding to each of the laser speckle image groups based on the following formula according to the system coherence parameter, the spatial speckle contrast matrix, and the dynamic scattering component ratio coefficient;

[0120]

[0121]

[0122] S2402, determining the blood flow index distribution image corresponding to each of the laser speckle image groups according to each of the blood flow index matrices;

[0123] Among them, K s is the spatial speckle contrast, β is the system coherence parameter, ρ is the dynamic scattering component ratio coefficient, x is the blood flow index, T is the exposure time, τ c is the decoherence time of the scattering medium.

[0124] In the technical solution provided by the present invention, the spatial speckle contrast matrix is ​​applied, and the value of the blood flow index can be obtained by substituting each element in the spatial speckle contrast matrix into the above formula for spatial speckle contrast, and then substituting the system coherence parameter and the dynamic scattering component proportional coefficient in sequence. When all the elements in the spatial speckle contrast matrix are substituted into the above formula in sequence for evaluation, a matrix for the blood flow index can be obtained.

[0125] It should also be noted that after the blood flow index matrix is ​​obtained, the matrix is ​​presented in the form of a two-dimensional image through software processing, that is, an image of the blood flow index distribution law can be displayed. This is a prior art and will not be described in detail in the present invention. Figure 2 By applying the method provided by the present invention, multiple blood flow index distribution maps of the myocardial area to be observed in one exercise cycle can be obtained.

[0126] Due to the high myocardial blood flow rate and equipment limitations, it is not easy to capture a clearly focused blood flow index distribution map, so it is necessary to screen the blood flow index distribution map under each motion cycle to obtain an effective and accurately characterized focused blood flow index distribution map. Specifically, S500, according to the standard deviation of the numerical gradient of each blood flow index distribution image and the preset reference value, respectively determine the focused blood flow index distribution image under each motion cycle, including:

[0127] S510, calculating a preset reference value according to a preset rule based on the standard deviation of the numerical gradient of each of the blood flow index distribution images;

[0128] S520, comparing the standard deviation of the numerical gradient of each of the blood flow index distribution images with the preset reference value, and determining that the blood flow index distribution image with a standard deviation greater than the preset reference value is a focused blood flow index distribution image.

[0129] S520, calculating a preset reference value according to a preset rule includes:

[0130] S5201, selecting the standard deviation with the value in the top 10% among the standard deviations as the reference standard deviation;

[0131] S5202, determining the average value of each reference standard deviation;

[0132] S5203. Determine 85%-95% of the average value of each reference standard deviation as a preset reference value.

[0133] As mentioned above, the random characteristics of speckle result in that only the numerical gradient is used to distinguish the image sharpness and determine whether the image is focused, which cannot effectively screen the target image. Therefore, based on the numerical gradient, the standard deviation of the statistical characteristic value is calculated, and then the preset reference value is introduced, which can effectively screen the focused blood flow index distribution image in each motion cycle. Specifically, in the calculation of the preset reference value, it is necessary to select the standard deviation with the numerical value in the top 10% as the reference standard deviation. When the number calculated as 10% is a decimal, the rounding method is adopted. For example, in a certain embodiment, 122 standard deviations are calculated, and the standard deviation with the numerical value in the top 12 will be used as the reference standard deviation; 138 standard deviations are calculated, and the standard deviation with the numerical value in the top 14 will be used as the reference standard deviation. After obtaining the reference standard deviation, the average value of the reference standard deviation is calculated, and 85%-95% of the average value is selected as the value of the preset reference value, and compared with each standard deviation. The blood flow index distribution image with a standard deviation greater than the preset reference value is a focused blood flow index distribution image. Please refer to Figure 3 In this embodiment, the monitoring motion cycle is 18. By calculation, in each motion cycle, 1-5 blood flow index distribution images have standard deviations greater than the reference standard deviation, which can be used as focused blood flow index distribution images to characterize the myocardial blood flow law. Optionally, in order to reduce the influence of parameters, the largest one to three standard deviations can be deleted, and then the first 10% standard deviations can be selected to calculate the preset reference value, which is not limited in the present invention.

[0134] Further, S100, sequentially acquiring multiple laser speckle image groups of the myocardial area to be observed in each motion cycle includes: S110, sequentially acquiring multiple laser speckle image groups of the myocardial area to be observed in each motion cycle according to the electrocardiogram R wave.

[0135] In order to ensure that the triggering conditions of the laser speckle image group acquired in each motion cycle are the same and maintain the uniformity of the samples. In the technical solution provided by the present invention, considering the characteristics of the cardiac motion cycle, the laser speckle image group is acquired in sequence according to the ECG R wave. Specifically, in each motion cycle, the laser speckle image group can be acquired immediately when the ECG R wave appears, or a delay time can be set, and the laser speckle image group can be acquired after the ECG R wave appears ts. Since the frame rate is determined, the acquisition interval time of each frame image in the laser speckle image group is the same. When the triggering conditions for acquiring each laser speckle image group are consistent, the samples of each laser speckle image group can ensure uniformity and effectively improve the accuracy of subsequent calculations. In a certain embodiment, an electrocardiogram acquisition device can be used to synchronously trigger the acquisition of laser speckle images, so that each laser speckle image group acquired is from the same state in the heartbeat / respiratory cycle. Taking the myocardial blood flow imaging of New Zealand white rabbits as an example, when the chest is opened and connected to the pneumatic anesthesia ventilator, the ventilator frequency is 40 times / minute, the heart rate is 119 times / minute, and the ECG R wave is used as a reference to set the delayed trigger time t delay ,Control the camera to collect laser speckle images, collect multiple cycles (e.g., 100 cycles) to form multiple laser speckle image groups.

[0136] On the basis of the above method, the present invention further provides a device for monitoring myocardial blood flow in quasi-periodic motion during surgery, and the method for monitoring myocardial blood flow in quasi-periodic motion during surgery as described above comprises:

[0137] A laser illumination module, used for providing illumination to the myocardial area to be observed;

[0138] A laser speckle imaging module, used for sequentially acquiring dynamic speckle images of the myocardial area to be observed in each motion cycle according to preset parameters; and

[0139] The data processing module is used to obtain the focused blood flow index distribution image of the myocardial area to be observed according to each of the dynamic speckle images and preset rules.

[0140] It should be noted that the laser speckle imaging module has an ECG R-wave synchronous triggering function, and can acquire dynamic speckle images in each motion cycle immediately according to the triggering of the ECG R-wave or acquire them after a preset delay.

[0141] Furthermore, the present invention provides several embodiments of the laser illumination module, please refer to Figure 4 In the first embodiment, the laser illumination module includes a near-infrared laser, a first reflector, a second reflector, an optical isolator, a fiber coupler, an optical fiber, a fiber collimator, an aspherical lens, and a pyramid prism, which are arranged in sequence. Figure 5In the second embodiment, the laser illumination module includes a near-infrared laser, a first reflector, a second reflector, an optical isolator, a fiber coupler, an optical fiber, a fiber collimator, and a scattering plate, which are arranged in sequence.

[0142] Furthermore, in order to ensure the quality of the speckle image, in the technical solution provided by the present invention, the laser speckle imaging module includes an imaging lens, and a polarizer is arranged in front of the imaging lens; the acquisition frame rate of the imaging lens is greater than 200Hz, the exposure time is 50-80μs, and the gain is set to 8-12. Figure 6 , by comparison, placing a polarizing plate in front of the imaging lens can suppress static scattering noise, improve the signal-to-noise ratio of the blood flow image, and is more conducive to the subsequent processing of the speckle image. Secondly, in order to avoid the influence of environmental vibration and biological vibration noise on the proportion of dynamic scattering components, it is necessary to collect speckle images at a high frame rate, that is, a frame rate greater than or equal to 200Hz. Furthermore, the exposure time is 50-80μs. In one embodiment, a flat-top beam is used to illuminate a blood flow sample covered with 0.7mm biological vascular tissue, the blood flow rate range is set to 0mm / s to 308mm / s, the exposure time is set to 50μs, 1000μs, and 2000μs, the average intensity of all speckle images is about 105, and the obtained blood flow index distribution image is as shown Figure 7 As shown. It can be observed that short exposure time is more suitable for measuring high blood flow rate, long exposure time is suitable for measuring low blood flow rate. For the characteristics of high myocardial blood flow rate, the exposure time is set to 50-80μs. Finally, in one embodiment, a flat-top beam is used to illuminate a blood flow sample covered with 0.7mm biological vascular tissue, the blood flow rate range is set to 0mm / s to 308mm / s, the exposure time is set to 1000μs, the average intensity of all speckle images is about 105, and the blood flow index distribution image obtained by changing the machine gain is as follows Figure 8 As shown, it can be observed that the signal-to-noise ratio of the blood flow image is higher when the gain is set to 8-12. In an optional embodiment, the laser speckle imaging module includes a polarizer, an imaging lens, a narrow-band filter, and a charge coupler, the pixel size of the charge coupler is not greater than 4.4 μm, the field of view size is 18 mm×14 mm, and the imaging lens magnification is 0.44.

[0143] Furthermore, no matter how the camera parameters or light source parameters are adjusted, it is necessary to ensure that the ratio of the size of the dynamic speckle image to the pixel size is greater than 2 and less than 5, and the average grayscale value of the dynamic speckle image is greater than one-fourth of the saturated grayscale value and less than one-half of the saturated grayscale value. In one embodiment, a flat-top beam is used to illuminate the sample, the camera exposure time is set to 1000 μs, and the in vivo imaging of rabbit myocardial blood flow is performed. The average intensity of the speckle image is about 105, the gain is set to 10, the imaging lens magnification is 0.44, the diffraction limit is 32 μm, Fig. 9The left side shows the blood flow image captured by an imaging lens with a pixel size of 4.4μm. Fig. 9 The right side shows a blood flow image captured by an imaging lens with a pixel size of 7μm. It can be observed that the left side has a higher imaging effect.

[0144] It should also be noted that the light beam emitted by the laser lighting module provided by the present invention is a flat-top light beam. Fig.10 ,When other parameters remain unchanged, the flat-top beam illumination scheme is adopted, the blood flow image has a higher signal-to-noise ratio and a larger dynamic range of blood flow measurement capability.

[0145] 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 aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for monitoring quasi-periodic myocardial blood flow during surgery, characterized in that: include: Determine a monitoring motion cycle, and sequentially obtain a laser speckle image group of the myocardial area to be observed in each motion cycle, each of the laser speckle image groups including multiple frames of laser speckle images; Determining a plurality of blood flow index distribution images of the myocardial area to be observed in each movement cycle according to each of the laser speckle image groups; respectively determining the numerical gradient of each of the blood flow index distribution images; respectively determining the standard deviation of the numerical gradient of each of the blood flow index distribution images; According to the standard deviation of the numerical gradient of each of the blood flow index distribution images and a preset reference value, a focused blood flow index distribution image in each of the motion cycles is determined respectively.

2. The method for monitoring quasi-periodic myocardial blood flow during surgery according to claim 1, characterized in that: Determining, according to each of the laser speckle image groups, a plurality of blood flow index distribution images of the myocardial area to be observed in each of the motion cycles comprises: According to each of the laser speckle image groups, respectively determining a spatial speckle contrast matrix and a temporal speckle contrast matrix corresponding to each of the laser speckle image groups; Get system related parameters, Determining a dynamic scattering component ratio coefficient of the myocardial area to be observed according to the system coherence parameter, the spatial speckle contrast matrix and the temporal speckle contrast matrix; Determining the blood flow index distribution image corresponding to each of the laser speckle image groups according to the system coherence parameter, the spatial speckle contrast matrix and the dynamic scattering component ratio coefficient; Determine a plurality of blood flow index distribution images of the myocardial area to be observed in each movement cycle.

3. The method for monitoring myocardial blood flow during quasi-periodic motion during surgery according to claim 2, characterized in that: According to each of the laser speckle image groups, respectively determining a spatial speckle contrast matrix and a temporal speckle contrast matrix corresponding to each of the laser speckle image groups comprises: Using a spatial sliding window to traverse each of the laser speckle images in each of the laser speckle image groups frame by frame, and respectively determining a speckle contrast matrix of each of the laser speckle images in space, so as to determine a spatial speckle contrast matrix; According to each of the laser speckle images, the speckle contrast of the same pixel of each of the laser speckle images in the time series is determined respectively to determine a time speckle contrast matrix.

4. The method for monitoring myocardial blood flow during quasi-periodic motion during surgery according to claim 2, characterized in that: The obtaining of system related parameters comprises: Acquire a multi-frame laser speckle image of any area of ​​a static scattering medium within a preset exposure time; Determining the average spatial speckle contrast of the arbitrary area according to the multiple frames of the laser speckle images; According to the average spatial speckle contrast of the area, the system coherence parameter is determined based on the following formula; β≈K s 2 Where β is the system coherence parameter, K s is the spatial speckle contrast.

5. The method for monitoring quasi-periodic motion myocardial blood flow during surgery according to claim 2, characterized in that: Determining the dynamic scattering component ratio coefficient of the myocardial area to be observed according to the system coherence parameter, the spatial speckle contrast matrix and the temporal speckle contrast matrix comprises: determining an average spatial speckle contrast according to the spatial speckle contrast matrix; determining an average temporal speckle contrast according to the temporal speckle contrast matrix; Determine a dynamic scattering component proportional coefficient based on the following formula according to the average spatial speckle contrast, the average temporal speckle contrast and the system coherence parameter; Among them, K s is the spatial speckle contrast, β is the system coherence parameter, ρ is the dynamic scattering component ratio coefficient, x is the blood flow index, T is the exposure time, τ c is the decoherence time of the scattering medium, K t is the temporal speckle contrast.

6. The method for monitoring quasi-periodic motion myocardial blood flow during surgery according to claim 5, characterized in that: Determining the blood flow index distribution image corresponding to each laser speckle image group according to the system coherence parameter, the spatial speckle contrast matrix and the dynamic scattering component ratio coefficient includes: According to the system coherence parameter, the spatial speckle contrast matrix, and the dynamic scattering component ratio coefficient, based on the following formula, a blood flow index matrix corresponding to each of the laser speckle image groups is determined; According to each of the blood flow index matrices, respectively determining a blood flow index distribution image corresponding to each of the laser speckle image groups; Among them, K s is the spatial speckle contrast, β is the system coherence parameter, ρ is the dynamic scattering component ratio coefficient, x is the blood flow index, T is the exposure time, τ c is the decoherence time of the scattering medium.

7. The method for monitoring quasi-periodic myocardial blood flow during surgery according to claim 1, characterized in that: Determining the focused blood flow index distribution image in each motion cycle according to the standard deviation of the numerical gradient of each blood flow index distribution image and a preset reference value includes: Calculating a preset reference value according to a preset rule based on a standard deviation of the numerical gradient of each of the blood flow index distribution images; The standard deviation of the numerical gradient of each of the blood flow index distribution images is compared with the preset reference value, and the blood flow index distribution image with a standard deviation greater than the preset reference value is determined as the focused blood flow index distribution image.

8. The method for monitoring myocardial blood flow during quasi-periodic motion during surgery according to claim 7, characterized in that: Calculating the preset reference value according to the preset rules includes: Select the standard deviation with the value in the top 10% among the standard deviations as the reference standard deviation; determining an average of each of the reference standard deviations; 85%-95% of the average value of each reference standard deviation is determined as the preset reference value.

9. The method for monitoring quasi-periodic motion myocardial blood flow during surgery according to claim 1, characterized in that: Sequentially acquiring a plurality of laser speckle image groups of the myocardial area to be observed in each motion cycle includes: sequentially acquiring a plurality of laser speckle image groups of the myocardial area to be observed in each motion cycle according to the electrocardiogram R wave.

10. A device for monitoring myocardial blood flow in quasi-periodic motion during surgery, using the method for monitoring myocardial blood flow in quasi-periodic motion during surgery as claimed in any one of claims 1 to 9, characterized in that: include: A laser illumination module, used for providing illumination to the myocardial area to be observed; A laser speckle imaging module, used for sequentially acquiring dynamic speckle images of the myocardial area to be observed in each motion cycle according to preset parameters; and The data processing module is used to obtain the focused blood flow index distribution image of the myocardial area to be observed according to each of the dynamic speckle images and preset rules.

11. The device for monitoring quasi-periodic myocardial blood flow during surgery according to claim 10, characterized in that: The laser illumination module comprises a near-infrared laser, a first reflector, a second reflector, an optical isolator, a fiber coupler, an optical fiber, a fiber collimator, an aspherical lens and a pyramid prism, which are arranged in sequence; or, The laser illumination module comprises a near-infrared laser, a first reflector, a second reflector, an optical isolator, a fiber coupler, an optical fiber, a fiber collimator and a scattering sheet which are arranged in sequence.

12. The device for monitoring quasi-periodic myocardial blood flow during surgery according to claim 10, characterized in that: The laser speckle imaging module comprises an imaging lens, in front of which a polarizing plate is arranged; the acquisition frame rate of the imaging lens is greater than 200 Hz, the exposure time is 50-80 μs, and the gain is set to 8-12.

13. The device for monitoring quasi-periodic myocardial blood flow during surgery according to claim 10, characterized in that: The ratio of the size of the dynamic speckle image to the pixel size is greater than 2 and less than 5, and the average grayscale value of the dynamic speckle image is greater than one quarter of the saturation grayscale value and less than one half of the saturation grayscale value.

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