Multi-task myocardial tissue characteristic quantitative imaging method and device

Abstract

The invention provides a multi-task myocardial tissue characteristic quantitative imaging method and device, and relates to the technical field of images. The method comprises the following steps: determining a multi-task magnetic resonance imaging (MTT) sequence; based on the MTT sequence, by means of MTT and diaphragm navigation, an imaging plane is adjusted in real time in the scanning process, free breathing type scanning and image reconstruction are conducted on the myocardial tissue, a multi-sequence image is obtained, the multi-sequence image is used for indicating damage of the myocardial tissue, and the organism damage types indicated by all the sequence images in the multi-sequence image are different. According to the method, the myocardial tissue can be scanned through a multi-task magnetic resonance imaging technology to obtain the multi-sequence image, so that various myocardial damages can be accurately judged through the sequence image, and a clinician is assisted to make more accurate judgment.

Description

Technical Field

[0001] The present disclosure relates to the field of image technology, and in particular to a multi-task myocardial tissue feature quantitative imaging method and device. Background Art

[0002] Myocardial damage usually refers to structural and functional damage to myocardial cells or myocardial fibroblasts due to ischemia, inflammation or toxins, which may further develop into myocardial necrosis and seriously affect heart function.

[0003] Myocardial damage is obviously regional, and if the myocardium loses nutrition, it will be ischemic and hypoxic. How to determine myocardial damage is a technical problem that needs to be solved urgently in this field. Summary of the invention

[0004] In view of this, the purpose of the present invention is to propose a multi-task myocardial tissue feature quantitative imaging method and device. The present invention can solve the existing problems in a targeted manner and can generate multi-sequence images through multi-task magnetic resonance imaging technology, thereby improving the accuracy and efficiency of myocardial injury diagnosis.

[0005] Based on the above-mentioned purpose, in a first aspect, the present disclosure proposes a multi-task myocardial tissue feature quantitative imaging method, comprising: determining a multi-task magnetic resonance imaging technology MTT sequence; based on the MTT sequence, utilizing MTT and diaphragm navigation, adjusting the imaging plane in real time during the scanning process, performing free-breathing scanning and image reconstruction on the myocardial tissue, and obtaining multi-sequence images, wherein the multi-sequence images are used to indicate damage to the myocardial tissue, and each sequence image in the multi-sequence images indicates a different type of body damage.

[0006] In a second aspect, a multi-task myocardial tissue feature quantitative imaging device is also provided, comprising: a determination unit configured to determine a multi-task magnetic resonance imaging technique MTT sequence;

[0007] The scanning unit is configured to adjust the imaging plane in real time during the scanning process based on the MTT sequence, utilize MTT and diaphragm navigation, perform free-breathing scanning and image reconstruction on the myocardial tissue, and obtain multiple sequence images. The multiple sequence images are used to indicate damage to the myocardial tissue, and each sequence image in the multiple sequence images indicates a different type of body damage.

[0008] According to a third aspect, an electronic device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method described in the first aspect.

[0009] According to a fourth aspect, a computer-readable storage medium is provided, on which a computer program is stored, and the program is executed by a processor to implement any method described in the first aspect.

[0010] In general, the present disclosure has at least the following beneficial effects: various sequence images corresponding to the multi-task magnetic resonance imaging technology can accurately identify and judge various body injuries, so as to assist clinicians in making more accurate judgments. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In the accompanying drawings, unless otherwise specified, the same reference numerals throughout the multiple drawings represent the same or similar parts or elements. These drawings are not necessarily drawn to scale. It should be understood that these drawings only depict some embodiments disclosed in accordance with the present disclosure and should not be regarded as limiting the scope of the present disclosure.

[0012] Figure 1 A flowchart of a multi-task myocardial tissue feature quantitative imaging method according to an embodiment of the present disclosure is shown;

[0013] Figure 2 A schematic diagram of verifying multiple sequence images according to an embodiment of the present disclosure is shown;

[0014] Figure 3 A flow chart showing generation of a sequence of images according to an embodiment of the present disclosure is shown;

[0015] Figure 4 A schematic diagram of a multi-task myocardial tissue feature quantitative imaging device according to an embodiment of the present disclosure is shown;

[0016] Figure 5 A schematic diagram of the structure of an electronic device provided by an embodiment of the present disclosure is shown;

[0017] Figure 6 A schematic diagram of a storage medium provided by an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0018] The present disclosure is further described in detail below in conjunction with the accompanying drawings and embodiments. It is understood that the specific embodiments described herein are only used to explain the relevant invention, rather than to limit the invention. It is also necessary to explain that, for ease of description, only the parts related to the relevant invention are shown in the accompanying drawings.

[0019] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present disclosure may be combined with each other. The present disclosure will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0020] Figure 1The multi-task myocardial tissue feature quantitative imaging method disclosed in the present invention is shown. In an embodiment of the present invention, the method includes:

[0021] Step S101, determining a multi-task magnetic resonance imaging technique MTT sequence.

[0022] In this embodiment, the execution subject (any electronic device such as a terminal device) of the multi-task myocardial tissue feature quantitative imaging method may adopt a golden angle spoke-shaped readout trajectory for continuous acquisition, use flip pulses, T2 preparation pulses and T1ρ preparation pulses to generate different T1, T2 and T1ρ contrasts, and perform multi-echo acquisition containing 6 echoes in the fifth cardiac cycle when longitudinal relaxation is closest to complete recovery. The technology uses diaphragm navigation to adjust the imaging plane in real time during the scanning process, performs prospective respiratory motion correction, and realizes free breathing acquisition. After the acquisition is completed, the technology separates the data collected during the diastole of the fifth cardiac cycle based on the electrocardiogram signals recorded during the acquisition process, reconstructs the multi-echo image, and then generates the T2* parameter map and B0 map using a post-processing program.

[0023] At the same time, the technology divides each remaining cardiac cycle into 24 phases according to the ECG signal, and uses low-rank reconstruction to obtain high-quality images without undersampling artifacts. The second singular value image with the most obvious contrast between the blood pool and the myocardium is used to compose the Cine image. Images of different cardiac phases are aligned to the same phase under a non-rigid motion field, and then averaged in the cardiac phase dimension to obtain a multi-contrast image group with a high signal-to-noise ratio. In the parameter quantification stage, the technology uses the Bloch equation to simulate a dictionary library based on the B0 map and the R wave time interval and trigger delay information saved during the scan, and then generates T1, T2 and T1ρ parameter maps through dictionary library matching.

[0024] In addition to T1, T2 and T1ρ quantification, the technology also measures the B1+ factor to correct the flip angle, and adopts a variable flip angle strategy to improve the sensitivity of the B1+ factor. In order to obtain more accurate and stable quantitative results, the study will perform a series of optimizations on the sequence. The number of preparation pulses in the sequence and their position in the sequence will affect the precision and accuracy of parameter quantification. This study will first design multiple candidate sequences based on experience, and then compare the quantitative precision and accuracy through simulation experiments, phantom experiments and in vivo experiments to screen out the best performing sequence.

[0025] Step S102, based on the MTT sequence, using MTT and diaphragm navigation, adjusting the imaging plane in real time during the scanning process, performing free-breathing scanning and image reconstruction on the myocardial tissue, and obtaining multi-sequence images, wherein the multi-sequence images are used to indicate damage to the myocardial tissue, and each sequence image in the multi-sequence images indicates a different type of body damage.

[0026] In this embodiment, the above-mentioned execution subject can obtain multiple sequence images, which are used to indicate damage to myocardial tissue and are obtained based on multi-task magnetic resonance imaging technology. Each sequence image in the multiple sequence images indicates a different type of body damage.

[0027] In this embodiment, the execution subject of the multi-task myocardial tissue feature quantitative imaging method can obtain multiple sequence images from the storage space of this device or the storage space of other electronic devices.

[0028] Sequence images can be collected in the following ways: using multitasking magnetic resonance imaging technology (MR Multitasking, MTT), scanning myocardial tissue, and the imaging data obtained is an image used to indicate body damage, that is, a sequence image. Each sequence image indicates a different type of body damage. For example, the body damage type may include body bleeding.

[0029] This embodiment can accurately identify and judge various body injuries through various sequence images corresponding to the multi-task magnetic resonance imaging technology, so as to assist clinicians in making more accurate judgments.

[0030] In some optional implementations of any one of the embodiments of the present disclosure, the body injury type is a myocardial injury type; the method includes: calling an image processing algorithm to process the multi-series images to identify different types of myocardial injuries presented by the multi-series images.

[0031] In this embodiment, an image processing algorithm such as various deep neural networks can be called to process the above sequence images to obtain different types of myocardial damage identified by the image processing algorithm. Each sequence image has a corresponding type of myocardial damage.

[0032] In some optional implementations of any embodiment of the present disclosure, the method may further include: verifying the accuracy of the multi-sequence images; and determining whether the multi-sequence images serve as images indicating myocardial damage to the myocardial tissue based on a result of the accuracy verification.

[0033] In this embodiment, the execution subject may perform accuracy verification on the multiple sequence images. Accuracy verification may be used to verify whether the sequence images are accurate. For example, the execution subject may input the multiple sequence images into a preset model and obtain the verification result output by the preset model. The preset model may be used to process each sequence image and obtain the verification result corresponding to the sequence image.

[0034] The verification result may be verification passed or verification failed. If the verification is passed, it indicates that the myocardial injury area presented by the sequence images is accurate. If the verification is failed, it indicates that the myocardial injury area presented by the sequence images is inaccurate.

[0035] The execution subject may determine whether the multiple sequence images are images indicating myocardial damage of the myocardial tissue according to the result of the accuracy verification.

[0036] For example, if the result of the accuracy verification is passed, the execution subject may determine that the multi-sequence image is an image indicating myocardial damage of the myocardial tissue. That is, the myocardial damage area displayed in the multi-sequence image corresponds to the actual myocardial damage of the myocardial tissue. If the result of the accuracy verification is not passed, the execution subject may determine that the multi-sequence image is not an image indicating myocardial damage of the myocardial tissue.

[0037] In these optional implementations, the execution subject may use the multi-sequence images as images indicating myocardial damage to the myocardial tissue when the multi-sequence images pass accuracy verification.

[0038] In some optional implementations of any embodiment of the present disclosure, the use of MTT to scan and reconstruct images of myocardial tissue to obtain multi-sequence images includes: performing flip pulses, T2 preparation pulses and T1ρ preparation pulses on the magnetic resonance imaging scanner to obtain T1 contrast, T2 contrast and T1ρ contrast, respectively; and reconstructing multi-echo images through the T1 contrast, T2 contrast and T1ρ contrast to obtain the multi-sequence images.

[0039] Optionally, the method of performing flip pulses, T2 preparation pulses and T1ρ preparation pulses on the MRI scanner to obtain T1 contrast, T2 contrast and T1ρ contrast respectively includes: dividing each remaining cardiac cycle into multiple cardiac phases according to the electrocardiogram signal, and obtaining an image without under-sampling artifacts by using low-rank reconstruction; for images of different cardiac phases, aligning them to the same phase under a non-rigid motion field, averaging them in the cardiac phase dimension, and obtaining a multi-contrast image with a high signal-to-noise ratio.

[0040] Optionally, reconstructing a multi-echo image through the T1 contrast, T2 contrast and T1ρ contrast to obtain the multi-sequence image includes: simulating a dictionary library using the Bloch equation according to the BO map and the R wave time interval and trigger delay information saved during scanning, matching the multi-contrast images through the dictionary library, and generating the multi-sequence image, wherein the Cine sequence in the multi-sequence image is generated by using the second singular value image with the most obvious contrast between the blood pool and the myocardium.

[0041] In these optional implementations, the execution subject can perform various preparation pulses such as flip pulses, T2 preparation pulses and T1ρ preparation pulses on the nuclear magnetic resonance instrument. Different accurate pulses can obtain different contrasts. According to these contrasts, image reconstruction can be performed to obtain different sequence images.

[0042] After contrast is obtained, a multi-echo acquisition containing 6 echoes is performed in the fifth cardiac cycle when longitudinal relaxation is closest to full recovery. After that, the imaging plane can be adjusted in real time during the scan using diaphragm navigation, and prospective respiratory motion correction can be performed to achieve free-breathing acquisition. After the acquisition is completed, the data collected during the diastole of the fifth cardiac cycle are separated from the ECG signals recorded during the acquisition process, and the above multi-echo image is reconstructed. Then, the T2* parameter map and B0 map can be generated using a post-processing program.

[0043] The above execution subject can obtain a T1 image according to the T1 contrast, a T2 image according to the T2 contrast, and a T1ρ image according to the T1ρ contrast.

[0044] In addition, the above-mentioned execution subject can divide each remaining cardiac cycle into 24 cardiac phases according to the ECG signal, and use low-rank reconstruction to obtain high-quality images without undersampling artifacts. The second singular value image with the most obvious contrast between the blood pool and the myocardium is used to form a Cine image. Images of different cardiac phases are aligned to the same phase under a non-rigid motion field, and then averaged in the cardiac phase dimension to obtain a multi-sequence image group with a high signal-to-noise ratio. In the parameter quantification stage, the technology uses the Bloch equation to simulate a dictionary library based on the B0 map and the R wave time interval and trigger delay information saved during the scan, and then generates T1, T2 and T1ρ parameter maps through dictionary library matching.

[0045] In addition to T1, T2, and T1ρ quantification, the B1+ factor can be measured to correct for the flip angle, and a variable flip angle strategy can be used to increase the sensitivity of the B1+ factor.

[0046] like Figure 2 As shown, the myocardial tissue used here is that of a beagle dog.

[0047] In some optional implementations of any embodiment of the present disclosure, the accuracy verification of the multi-sequence images includes: obtaining the pathological detection results of the myocardial tissue; and comparing the multi-sequence images with the pathological detection results of the myocardial tissue to verify the accuracy of the multi-sequence images.

[0048] In these optional implementations, the execution subject may compare the multi-sequence images with the pathology detection results based on the pathology detection results to verify the accuracy of the multi-sequence images.

[0049] Pathological examination may include at least one of the following: TTC staining to detect myocardial infarction, hematoxylin and eosin staining to detect myocardial edema, myocardial infarction and maximum venous oxygen, Prussian blue staining (PB staining) to detect intramyocardial hemorrhage, and Masson staining to detect myocardial fibrosis.

[0050] A model of myocardial tissue injury after reperfusion can be established in beagle dogs. The open-chest ligation method was proposed to establish a model of myocardial tissue injury after ischemia-reperfusion in beagle dogs. According to the protocol approved by the Animal Care and Ethics Committee, 10 beagle dogs (20-25 kg; female) were included. Five CCS stage 4 dogs and five sham operation groups were expected. After left thoracotomy under general anesthesia, a 2-5 mm segment of the left anterior descending artery (LAD) was stripped from the surrounding tissue distal to the first diagonal branch, and a suture was passed underneath it to cause myocardial ischemia. The suture was then untied to allow myocardial reperfusion, the chest wall was closed, and the animal was allowed to recover. An electrocardiogram monitor was used throughout the operation to detect the animal's heart rate, heart rhythm, and blood oxygen saturation.

[0051] The beagle dogs with successful modeling were subjected to cardiac magnetic resonance MTT sequence examination and conventional magnetic resonance examination, both using a Siemens 3.0T whole-body magnetic resonance scanner (Skyra, Siemens Medical Solutions, Erlangen, Germany). The experimental animals were deprived of food and water for 12 hours before scanning, and anesthetized with isoflurane mixed with 20% oxygen and 80% air, and the respiratory rate was artificially controlled by a ventilator. The MTT sequence obtained Cine, T1, T2, T2* and T1ρ images through a single scan of free breathing. Conventional magnetic resonance examination sequences include: Cine, T1mapping, T2mapping, T2*mapping and T1ρmapping. MTT and all conventional magnetic resonance sequence scans were performed before gadolinium contrast agent enhancement, and MTT sequence and conventional T1mapping scans were performed after gadolinium contrast agent enhancement. The hematocrit was obtained based on venous blood sampling, and the myocardial cell extracellular volume fraction (ECV) of the area was obtained using a formula. Myocardial edema was identified by T2 mapping images, intramyocardial hemorrhage was identified by T2* mapping images, and myocardial infarction area and MVO were identified by T1 mapping, T1ρmapping and calculated ECV values.

[0052] Histopathological validation of CCS staging based on MTT. After MRI examination, the animals in each group were killed, and heart specimens were collected for pathological tissue-related tests. TTC staining was used to detect myocardial infarction, hematoxylin and eosin staining (HE staining) was used to detect myocardial edema, myocardial infarction and MVO, Perl's Prussian blue staining (PB staining) was used to detect intramyocardial hemorrhage, and Masson staining was used to detect myocardial fibrosis. With pathology as the gold standard, the MTT test results were compared with the pathological results to verify the feasibility and accuracy of the MTT technology for qualitative and quantitative histological characteristics such as myocardial edema and necrosis, and compared with the results of traditional magnetic resonance imaging sequences, in order to achieve the purpose of accurately stratifying the degree of myocardial tissue damage using MTT sequence myocardial qualitative and quantitative analysis at the animal level.

[0053] In some optional implementations of any one of the embodiments of the present disclosure, the myocardial tissue is human myocardial tissue; and the accuracy verification of the multi-sequence images includes: acquiring an image of the human myocardial tissue with an area of ​​interest marked; and comparing the multi-sequence images with an image of the human myocardial tissue to verify the accuracy of the multi-sequence images.

[0054] In these optional implementations, the execution subject may determine multiple sequence images of human myocardial tissue, and compare them with images of human myocardial tissue with regions of interest marked, so as to verify accuracy.

[0055] For example, multiple cases, such as 15 STEMI patients and 15 normal volunteers, were collected and underwent imaging examinations after obtaining written informed consent. Both patients and normal volunteers had MTT sequences and conventional mapping sequences. The conventional sequences were MOLLI 5(3)3 for obtaining T1mapping images, T2-prep bSSFP for obtaining T2 mapping images, and T1ρ-prepbSSFP for obtaining T1 rho mapping images. T2*mapping images were obtained based on T2-prep bSSFP. In addition, patients underwent late gadolinium enhancement (LGE) imaging to detect lesion enhancement. Regions of interest were manually defined in T1, T2, and T1ρ images based on the 16 segments of the American Heart Association (AHA) model. Then, the mean and standard deviation of each short-axis slice were calculated to evaluate the accuracy and precision, further verifying the feasibility of the MTT technique.

[0056] In this way, the feasibility of generating multiple sequence images for the human body can be further evaluated on the human body.

[0057] In some optional implementations of any one of the embodiments of the present disclosure, the myocardial injury types include intramyocardial hemorrhage, myocardial edema and myocardial fibrosis, and the multi-sequence images include T1 images, T2 images, T2* images and T1ρ images; calling the image processing algorithm to process the multi-sequence images to identify different types of myocardial injuries presented by the multi-sequence images includes: determining the area of ​​myocardial fibrosis of the myocardial tissue based on the T1 image and the T1ρ image; determining the area of ​​myocardial edema of the myocardial tissue based on the T2 image; and determining the area of ​​myocardial hemorrhage of the myocardial tissue based on the T2* image.

[0058] like Figure 3 As shown, the sequence diagram and post-processing flow in the present disclosure are shown in the figure. The figure shows multiple sequence images, namely T1 mapping image, T2 mapping image, T1ρmapping image, B1 mapping image and Cine image.

[0059] The embodiment of the present disclosure provides a multi-task myocardial tissue feature quantitative imaging device, which is used to perform the multi-task myocardial tissue feature quantitative imaging method described in the above embodiment, such as Figure 4 As shown, the device includes: a determination unit, configured to determine a multi-task magnetic resonance imaging technology MTT sequence; a scanning unit, configured to scan and reconstruct myocardial tissue using MTT based on the MTT sequence to obtain multiple sequence images, wherein the multiple sequence images are used to indicate damage to myocardial tissue, and each sequence image in the multiple sequence images indicates a different type of body damage.

[0060] The multi-task myocardial tissue feature quantitative imaging device provided in the above-mentioned embodiment of the present disclosure and the multi-task myocardial tissue feature quantitative imaging method provided in the embodiment of the present disclosure are based on the same inventive concept and have the same beneficial effects as the methods adopted, run or implemented by the application programs stored therein.

[0061] The embodiment of the present disclosure also provides an electronic device corresponding to the multi-task myocardial tissue feature quantitative imaging method provided in the above embodiment, so as to execute the above multi-task myocardial tissue feature quantitative imaging method. The embodiment of the present disclosure is not limited.

[0062] Please refer to Figure 5 , which shows a schematic diagram of an electronic device provided by some embodiments of the present disclosure. Figure 5As shown, the electronic device 50 includes: a processor 500, a memory 501, a bus 502 and a communication interface 503, and the processor 500, the communication interface 503 and the memory 501 are connected via the bus 502; the memory 501 stores a computer program that can be run on the processor 500, and the processor 500 executes the method provided in any of the aforementioned embodiments of the present disclosure when running the computer program.

[0063] The memory 501 may include a high-speed random access memory (RAM), and may also include a non-volatile memory, such as at least one disk storage. The communication connection between the system network element and at least one other network element is realized through at least one communication interface 503 (which may be wired or wireless), and the Internet, wide area network, local area network, metropolitan area network, etc. may be used.

[0064] The bus 502 may be an ISA bus, a PCI bus, or an EISA bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. The memory 501 is used to store programs, and the processor 500 executes the programs after receiving execution instructions. The multi-task myocardial tissue feature quantitative imaging method disclosed in any implementation of the aforementioned embodiment of the present disclosure may be applied to the processor 500, or implemented by the processor 500.

[0065] The processor 500 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit in the processor 500 or the instruction in the form of software. The above processor 500 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present disclosure can be implemented or executed. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor. The steps of the method disclosed in conjunction with the embodiments of the present disclosure can be directly embodied as a hardware decoding processor to be executed, or the hardware and software modules in the decoding processor can be executed. The software module can be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory 501, and the processor 500 reads the information in the memory 501 and completes the steps of the above method in combination with its hardware.

[0066] The electronic device provided by the embodiment of the present disclosure and the multi-task myocardial tissue feature quantitative imaging method provided by the embodiment of the present disclosure are based on the same inventive concept and have the same beneficial effects as the methods adopted, operated or implemented by them.

[0067] The present disclosure also provides a computer-readable storage medium corresponding to the multi-task myocardial tissue feature quantitative imaging method provided in the above embodiment. Figure 6 The computer-readable storage medium shown is a CD 60 on which a computer program (ie, a program product) is stored. When the computer program is run by a processor, it executes the multi-task myocardial tissue feature quantitative imaging method provided by any of the aforementioned embodiments.

[0068] It should be noted that examples of the computer-readable storage medium may also include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other optical or magnetic storage media, which are not listed here one by one.

[0069] The computer-readable storage medium provided by the above-mentioned embodiments of the present disclosure and the multi-task myocardial tissue feature quantitative imaging method provided by the embodiments of the present disclosure are based on the same inventive concept and have the same beneficial effects as the methods adopted, run or implemented by the application programs stored therein.

[0070] It should be noted that:

[0071] In the above text, the term "comprises", "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprising a ..." does not exclude the presence of other identical elements in the process, method, article or device including the element. In addition, it should be noted that the scope of the method and device in the embodiments of the present disclosure is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved, for example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0072] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present disclosure, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for enabling a terminal (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods described in each embodiment of the present disclosure.

[0073] The embodiments of the present disclosure are described above in conjunction with the accompanying drawings, which are only specific implementation modes of the present disclosure. However, the present disclosure is not limited to the above-mentioned specific implementation modes. The above-mentioned specific implementation modes are merely illustrative and not restrictive. Under the guidance of the present disclosure, ordinary technicians in this field can also make many forms without departing from the purpose of the present disclosure and the scope of protection of the claims, all of which are within the protection of the present disclosure.

Claims

1. A multi-task myocardial tissue feature quantitative imaging method, characterized in that: include: Determine the MTT sequence of multi-task magnetic resonance imaging technology; Based on the MTT sequence, using MTT and diaphragm navigation, the imaging plane is adjusted in real time during the scanning process, and the myocardial tissue is scanned and reconstructed in a free-breathing manner to obtain multi-sequence images. The multi-sequence images are used to indicate damage to the myocardial tissue, and each sequence image in the multi-sequence images indicates a different type of body damage.

2. The method according to claim 1, characterized in that The body injury type is myocardial injury type; the method further comprises: An image processing algorithm is called to process the multiple sequence images to identify different types of myocardial damage presented by the multiple sequence images.

3. The method according to claim 2, characterized in that Before calling the image processing algorithm to process the multiple sequence images, the method further includes: Verifying the accuracy of the multiple sequence images; According to the result of the accuracy verification, it is determined whether the multiple sequence images serve as images indicating myocardial damage of the myocardial tissue.

4. The method according to claim 1, characterized in that: The method uses MTT to scan and reconstruct the myocardial tissue to obtain multiple sequence images, including: Performing flip pulse, T2 preparation pulse and T1ρ preparation pulse on the MRI scanner to obtain T1 contrast, T2 contrast and T1ρ contrast respectively; The multi-echo image is reconstructed by using the T1 contrast, T2 contrast and T1ρ contrast to obtain the multi-sequence image.

5. The method according to claim 4, characterized in that The method of performing a flip pulse, a T2 preparation pulse and a T1ρ preparation pulse on the nuclear magnetic resonance scanner to obtain T1 contrast, T2 contrast and T1ρ contrast respectively includes: Each remaining cardiac cycle is divided into multiple cardiac phases according to the ECG signal, and an image without undersampling artifacts is obtained by low-rank reconstruction; Images of different cardiac phases are registered to the same phase under a non-rigid motion field and averaged in the cardiac phase dimension to obtain multi-contrast images with high signal-to-noise ratio.

6. The method according to claim 5, characterized in that The method of reconstructing a multi-echo image by using the T1 contrast, T2 contrast and T1ρ contrast to obtain the multi-sequence image comprises: According to the BO map and the R-wave time interval and trigger delay information saved during scanning, a dictionary library is simulated using the Bloch equation, and the multi-contrast images are matched through the dictionary library to generate the multi-sequence images, wherein the Cine sequence in the multi-sequence images is generated by using the second singular value image with the most obvious contrast between the blood pool and the myocardium.

7. The method according to claim 3, characterized in that The accuracy verification of the multiple sequence images includes: Obtaining a pathological test result of the myocardial tissue; The multi-sequence images are compared with the pathological detection results of the myocardial tissue to verify the accuracy of the multi-sequence images.

8. The method according to claim 3, characterized in that The myocardial tissue is human myocardial tissue; and the accuracy verification of the multiple sequence images includes: Acquire an image of the human myocardial tissue with a region of interest marked thereon; The multi-sequence images are compared with the images of the human myocardial tissue to verify the accuracy of the multi-sequence images.

9. The method according to claim 2, characterized in that: The myocardial injury types include intramyocardial hemorrhage, myocardial edema and myocardial fibrosis, and the multi-series images include T1 images, T2 images, T2* images and T1ρ images; The calling of an image processing algorithm to process the multiple sequence images to identify different types of myocardial damage presented by the multiple sequence images includes: Determining a region of myocardial fibrosis in the myocardial tissue according to the T1 image and the T1ρ image; Determining the area of ​​myocardial edema of the myocardial tissue according to the T2 image; The area of ​​myocardial hemorrhage in the myocardial tissue is determined based on the T2* image.

10. A multi-task myocardial tissue feature quantitative imaging device, characterized in that: include: A determination unit configured to determine a multi-task magnetic resonance imaging technique MTT sequence; The scanning unit is configured to adjust the imaging plane in real time during the scanning process based on the MTT sequence, utilize MTT and diaphragm navigation, perform free-breathing scanning and image reconstruction on the myocardial tissue, and obtain multiple sequence images. The multiple sequence images are used to indicate damage to the myocardial tissue, and each sequence image in the multiple sequence images indicates a different type of body damage.

Images