Method and apparatus for real-time monitoring of myocardial microperfusion using ultrafast ultrasound imaging

Abstract

The application discloses a kind of real-time monitoring myocardial microcirculation's ultrafast ultrasound imaging method and imaging equipment, and imaging method includes: step one, read ultrasonic image RF data sequence;Step two, select n frames of data and reorganize into two-dimensional array, then carry out singular value decomposition;Step three, carry out space-time filtering;Step four, carry out arithmetic average calculation;Step five, with frame as interval, again select frame image to carry out space-time filtering and average calculation, in turn repeat, obtain a group of ultrasonic image sequence;Step six, according to frame number W intercept, and carry out Hamming window weighting, then carry out arithmetic average calculation, obtain new ultrasonic image frame;Step seven, interval S frame, and also select W frame image to carry out time domain smoothing, in turn repeat, until a group of new ultrasonic image data sequence is obtained.The ultrasonic image obtained by the application has good reconstruction effect on the microcirculation target in myocardium, and real-time and clear ultrasonic image of myocardial microcirculation can be obtained.

Description

Technical Field

[0001] This invention relates to an ultrafast ultrasound imaging method and imaging device for real-time monitoring of myocardial microblood flow, belonging to the field of medical devices. Background Technology

[0002] Myocardial microcirculation function is closely related to myocardial contraction, ischemia-reperfusion injury, and clinical prognosis. Real-time monitoring of myocardial microblood flow can dynamically assess myocardial perfusion status, which is of crucial value for the precise diagnosis and treatment of various cardiovascular diseases such as coronary heart disease and heart failure. It helps to identify occult ischemia, assess treatment effectiveness, predict the risk of myocardial infarction and heart failure, and guide the development of individualized treatment plans. Precise monitoring of the dynamic changes of myocardial microblood flow in both temporal and spatial dimensions is of great significance for a comprehensive understanding of myocardial blood perfusion and cardiac function.

[0003] Currently, the medical community lacks imaging tools that can intuitively display and dynamically monitor myocardial microcirculation behavior. Traditional electrocardiogram changes, hemodynamic parameters, or postoperative images (such as MRI and PET) are insufficient to meet the temporal resolution and immediacy required for intraoperative decision-making. Intraoperative transesophageal Doppler ultrasound has limitations in low-velocity blood flow detection and spatiotemporal resolution, making it difficult to capture the subtle dynamic changes in myocardial microcirculation.

[0004] Therefore, there is a need for an imaging system capable of real-time monitoring of myocardial microflow, providing high spatiotemporal resolution images of myocardial microflow. Such a system would be of great significance for intraoperative monitoring during cardiac surgery, postoperative recovery of cardiac function, long-term prognosis, and heart transplantation. Summary of the Invention

[0005] The purpose of this invention is to provide an ultrafast ultrasound imaging method and imaging device for real-time monitoring of myocardial microblood flow, which can clearly present the distribution of microvessels in the myocardium and the blood flow therein based on ultrafast ultrasound imaging.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0007] On the one hand, the present invention provides an ultrafast ultrasound imaging method for real-time monitoring of myocardial microblood flow, comprising the following steps:

[0008] Step 1: Under the epicardial imaging window, acquire ultrasound imaging RF data of the myocardial region at a rate of no less than 512 frames per second; each acquired frame of RF data is considered a single unit. A two-dimensional array, where Number of scan lines The number of data points on each scan line;

[0009] Step 2, by frame number Extract subsequences of ultrasound image data, reassemble the subsequences into a two-dimensional matrix, and then perform singular value decomposition.

[0010] Step 3: Select the rank interval [k1, k2] within the energy-rank spectrum and set the ranks of other non-rank values ​​to zero, thereby performing spatiotemporal filtering on the two-dimensional matrix;

[0011] Step 4: Using the pixels at the same position as a reference, perform an arithmetic average on the spatiotemporally filtered ultrasound image from Step 3 to obtain a new spatiotemporally filtered ultrasound image frame.

[0012] Step 5, with Frames as intervals, select again The frame image is subjected to spatiotemporal filtering and averaging calculations as in steps three and four to obtain another new ultrasound image frame after spatiotemporal filtering; this process is repeated to obtain a set of spatiotemporally filtered ultrasound image sequences.

[0013] Step 6: Extract subsequences of the ultrasound image data sequence according to the number of frames W, and perform Hamming window weighting based on the pixels at the same position. Then, perform arithmetic average calculation based on the pixels at the same position to obtain a new frame of ultrasound image frame that has been smoothed in the time domain.

[0014] Step seven: After an interval of S frames, select W frames and perform temporal smoothing as in step six to obtain another temporally smoothed ultrasound image frame; repeat this process until a new set of temporally smoothed ultrasound image data sequences is obtained. The ultrasound images obtained in this way have a good reconstruction effect on the small and rapidly changing target of microblood flow in the myocardium, thus obtaining real-time and clear ultrasound images of myocardial microblood flow.

[0015] Furthermore, in step two, the number of frames... The preferred value range is 32-256.

[0016] Furthermore, in step two, the extracted ultrasound image data subsequences are used to form a three-dimensional matrix. Its size is Rearrange it in spatial direction to obtain a two-dimensional matrix. ,in, Then, perform SVD decomposition on the two-dimensional matrix. The result of the decomposition is expressed as follows:

[0017]

[0018] in, It is a spatial vector matrix. It is a singular value matrix. It is a time vector matrix.

[0019] Furthermore, in step three, the formula for calculating the spatiotemporal filtering of the two-dimensional matrix M is as follows:

[0020]

[0021] in, The filtered blood flow signal is represented by [k1, k2], and the selection criteria are as follows:

[0022]

[0023]

[0024] in, Indicates the preceding The proportion of the cumulative energy of each singular value component to the total energy. Representing a two-dimensional matrix After singular value decomposition, the first The energy corresponding to the singular value, i.e. the first singular value. The squares of the singular values, where r is the length of the image sequence. This is the upper limit of energy decay. This is the lower limit of energy decay. In this step... , , .

[0025] Furthermore, in step five, the number of frames... The preferred value range is 1-8 frames.

[0026] Furthermore, in step six, the preferred value range for the number of frames W is 8-16 frames.

[0027] Furthermore, in step seven, the preferred value range for the interval S is 1-4 frames.

[0028] On the other hand, the present invention also provides an imaging device, including an ultrasonic probe, a transmitting and receiving circuit, a control and processing circuit, a memory, and a display, wherein:

[0029] The ultrasonic probe is used to convert electrical signals into acoustic signals, or vice versa.

[0030] The transmitting and receiving circuit is used to control the ultrasonic probe to transmit ultrasonic waves to the target area, receive the echo of the ultrasonic waves, and convert the echo signal from an analog signal to a digital signal.

[0031] The control processing circuit is used to control the transmitting and receiving circuits and process various data, and to execute the steps of the ultrafast ultrasound imaging method for real-time monitoring of myocardial microblood flow as described above.

[0032] The memory is used to store the programs and data of the ultrasound equipment;

[0033] The display is used to present ultrafast ultrasound imaging images to the operator.

[0034] Furthermore, to quickly transmit ultrasound echo data from the transmitting and receiving circuit to the control and processing circuit, both the transmitting and receiving circuit and the control and processing circuit support PCIe transmission mode; and to efficiently execute the ultrafast ultrasound imaging method, the control and processing circuit includes at least one graphics processing unit (GPU).

[0035] The beneficial effects of this invention are as follows: Unlike contrast-enhanced ultrasound imaging that requires external reagents, or ultrasound images acquired over a long period and processed offline using specialized equipment, or magnetic resonance imaging (MRI), this invention can achieve real-time, clear ultrasound imaging of myocardial microflow using only ordinary portable ultrafast ultrasound imaging equipment. It eliminates the risks of contrast agent allergy or kidney damage, allows for continuous use during surgery, and enables precise dynamic assessment before, during, and after vascular reconstruction or transplantation. In intensive care or bedside monitoring, it provides continuous insight into myocardial microvascular function, guiding the titration of vasodilators, cardiotonics, or antithrombotic therapies. Attached Figure Description

[0036] Figure 1 This is a schematic diagram of the data processing flow of the present invention;

[0037] Figure 2 This is a system block diagram of the ultrasonic device of the present invention;

[0038] Figure 3 A schematic diagram of the experimental setup for cardiac imaging;

[0039] Figure 4 Microflow diagram of the myocardium in experimental pigs. Detailed Implementation

[0040] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments.

[0041] Example 1

[0042] This embodiment illustrates an ultrafast ultrasound imaging method for real-time monitoring of myocardial microflow. The method employs... Figure 1 The method shown describes real-time myocardial microflow detection in the heart of a live pig. The specific steps are as follows:

[0043] During the experiment, the experimental pigs were first subjected to open-chest surgery, followed by... Figure 3 The ultrasound probe was placed directly against the heart of the experimental pig for myocardial blood flow imaging. The ultrasound probe was fixed to the target myocardial imaging area by a bracket, and the ultrasound host displayed the myocardial micro-blood flow images in real time as follows:

[0044] Step 1: Under the epicardial imaging window, set an imaging depth of 15mm and acquire ultrasound imaging RF data of the target myocardial imaging area at an ultra-fast frame rate of 660fps. Each frame of RF data acquired is considered a single unit. A two-dimensional array, where =128 is the number of scan lines. =976 represents the number of data points on each scan line. RF data over a period of time forms an ultrasound image data sequence.

[0045] Step 2, by frame number =128 subsequences of ultrasound image data were extracted, and these data formed a three-dimensional matrix. Its size is Rearrange it in spatial direction to obtain a two-dimensional matrix. ,in, The matrix is ​​decomposed using SVD, and the result can be expressed as:

[0046]

[0047] in, It is a spatial vector matrix. It is a singular value matrix. It is a time vector matrix.

[0048] Step 3, in the energy-rank spectrum (i.e., the singular value matrix) Within a given interval, select the rank interval [k1, k2] and set the ranks of all other matrices not within this interval to zero. Then, perform spatiotemporal filtering on the two-dimensional matrix M. The calculation formula is as follows:

[0049]

[0050] in, The filtered blood flow signal is represented by [k1, k2], and the selection criteria are as follows:

[0051]

[0052]

[0053] in, Indicates the preceding The proportion of the cumulative energy of each singular value component to the total energy. Representing a two-dimensional matrix After singular value decomposition, the first The energy corresponding to the singular value, i.e. the first singular value. The squares of the singular values, where r is the length of the image sequence. This is the upper limit of energy decay. This is the lower limit of energy decay. In this embodiment... , , .

[0054] Step four: Using pixels at the same location as a reference, process the pixels generated in step three... The arithmetic mean of the spatiotemporally filtered ultrasound images is used to obtain a new spatiotemporally filtered ultrasound image frame.

[0055] Step 5, with Frames are the intervals, and the same selection is made. The frame image undergoes spatiotemporal filtering as described in steps three and four to obtain another spatiotemporally filtered ultrasound image frame. This process is repeated to obtain a sequence of spatiotemporally filtered ultrasound images.

[0056] Step 6: For the spatiotemporal filtered ultrasound image data sequence after steps 3 to 5, extract image data subsequences according to frame number W=12, and perform Hamming window weighting based on pixels at the same position. Then, calculate the arithmetic mean based on pixels at the same position to obtain a new frame of ultrasound image frame that has been smoothed in the time domain.

[0057] Step 7: At an interval of S=2 frames, select W=12 frames and perform temporal smoothing as in Step 6 to obtain another temporally smoothed ultrasound image frame. Repeat this process to obtain a new sequence of temporally smoothed ultrasound image data.

[0058] The real-time microflow imaging results of porcine myocardium obtained by the above method are as follows: Figure 4 As shown, the method of this invention can achieve clear and stable reconstruction results for targets such as micro-blood flow in the myocardium, which are small and rapidly changing.

[0059] Example 2

[0060] This embodiment illustrates an ultrasound imaging device that can implement the ultrafast ultrasound imaging method in Embodiment 1 above. The frame of the ultrasound imaging device is as follows: Figure 2 As shown, the system includes an ultrasound probe, a transmitting and receiving circuit, a control and processing circuit, a memory, and a display. Specifically: the ultrasound probe can convert electrical signals into acoustic signals and vice versa; the transmitting and receiving circuit controls the ultrasound probe to transmit ultrasound waves to the target area, receives the echoes of the ultrasound waves, and converts the echo signals from analog signals to digital signals; the control and processing circuit controls the transmitting and receiving circuit, processes various data, and executes the ultrafast ultrasound imaging method for real-time monitoring of myocardial microblood flow as described in Example 1; the memory stores the ultrasound equipment's programs and data; and the display presents the ultrafast ultrasound imaging images to the operator.

[0061] In this embodiment, the ultrafast ultrasound imaging system used can achieve a frame rate of 1000fps at an imaging depth of 10mm, and the imaging probe is a linear array probe with 128 elements, an element spacing of 0.1mm, and a center frequency of 18MHz.

[0062] In this embodiment, in order to quickly transmit ultrasonic echo data from the transmitting and receiving circuit to the control and processing circuit, both should support PCIe transmission mode; in order to efficiently execute the ultrafast ultrasonic imaging method, the control and processing circuit should include at least one graphics processor unit.

[0063] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the above embodiments do not limit the scope of protection of the present invention in any way, and all technical solutions obtained by equivalent substitution or other means fall within the scope of protection of the present invention. Parts not covered in this invention are the same as or can be implemented using existing technology.

Claims

1. A method of ultrafast ultrasound imaging for real-time monitoring of myocardial microperfusion, characterized in that, Includes the following steps: Step one, under the epicardial imaging window, collect the ultrasound imaging RF data of the myocardial region at a speed no less than 512 frames per second; each frame of the collected RF data is a two-dimensional array, wherein is the number of scan lines, is the number of data points on each scan line, is the number of data points on each scan line, Step 2, by frame number Extract subsequences of ultrasound image data, reassemble the subsequences into a two-dimensional matrix, and then perform singular value decomposition. Step 3: Select the rank interval [k1, k2] within the energy-rank spectrum and set the ranks of other non-rank values ​​to zero, thereby performing spatiotemporal filtering on the two-dimensional matrix; Step 4: Using the pixels at the same position as a reference, perform an arithmetic average on the spatiotemporally filtered ultrasound image from Step 3 to obtain a new spatiotemporally filtered ultrasound image frame. Step 5, with Frames as intervals, select again The frame image is subjected to spatiotemporal filtering and averaging calculations as in steps three and four to obtain another new ultrasound image frame after spatiotemporal filtering; this process is repeated to obtain a set of spatiotemporally filtered ultrasound image sequences. Step 6: Extract subsequences of the ultrasound image data sequence according to the number of frames W, and perform Hamming window weighting based on the pixels at the same position. Then, perform arithmetic average calculation based on the pixels at the same position to obtain a new frame of ultrasound image frame that has been smoothed in the time domain. Step 7: At an interval of S frames, select W frames and perform temporal smoothing as in Step 6 to obtain another temporally smoothed ultrasound image frame; repeat this process until a new set of temporally smoothed ultrasound image data sequences is obtained.

2. The ultrafast ultrasound imaging method for real-time monitoring of myocardial microflow according to claim 1, characterized in that, In step two, the number of frames The value range is 32-256.

3. The ultrafast ultrasound imaging method for real-time monitoring of myocardial microflow according to claim 1, characterized in that, In step two, the extracted ultrasound image data subsequences are arranged into a three-dimensional matrix. Its size is Rearrange it in spatial direction to obtain a two-dimensional matrix. ,in, Then, perform SVD decomposition on the two-dimensional matrix. The result of the decomposition is expressed as follows: in, It is a spatial vector matrix. It is a singular value matrix. It is a time vector matrix.

4. The ultrafast ultrasound imaging method for real-time monitoring of myocardial microflow according to claim 1, characterized in that, In step three, the formula for calculating the spatiotemporal filtering of the two-dimensional matrix M is as follows: in, The filtered blood flow signal is represented by [k1, k2], and the selection criteria are as follows: in, Indicates the preceding The proportion of the cumulative energy of each singular value component to the total energy. Representing a two-dimensional matrix After singular value decomposition, the first The energy corresponding to the singular value, i.e. the first singular value. The squares of the singular values, where r is the length of the image sequence. This is the upper limit of energy decay. This is the lower limit of energy decay.

5. The ultrafast ultrasound imaging method for real-time monitoring of myocardial microflow according to claim 1, characterized in that, In step five, the number of frames The value range is 1-8 frames.

6. The ultrafast ultrasound imaging method for real-time monitoring of myocardial microflow according to claim 1, characterized in that, In step six, the frame number W ranges from 8 to 16 frames.

7. The ultrafast ultrasound imaging method for real-time monitoring of myocardial microflow according to claim 1, characterized in that, In step seven, the value of the interval S frames ranges from 1 to 4 frames.

8. An imaging device, characterized in that, It includes an ultrasonic probe, transmitting and receiving circuits, control and processing circuits, memory, and a display, wherein: The ultrasonic probe is used to convert electrical signals into acoustic signals, or vice versa. The transmitting and receiving circuit is used to control the ultrasonic probe to transmit ultrasonic waves to the target area, receive the echo of the ultrasonic waves, and convert the echo signal from an analog signal to a digital signal. The control processing circuit is used to control the transmitting and receiving circuits and process various data, and to execute the steps of the ultrafast ultrasound imaging method for real-time monitoring of myocardial microblood flow as described in any one of claims 1 to 7. The memory is used to store the programs and data of the ultrasound equipment; The display is used to present ultrafast ultrasound imaging images to the operator.

9. The ultrasonic imaging device according to claim 8, characterized in that, Both the transmitting and receiving circuit and the control processing circuit support PCIe transmission; and the control processing circuit includes at least one graphics processor unit.

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