Method for acquisition of mre imaging sequence data and device therefor

Abstract

The application relates to the technical field of magnetic resonance imaging, and discloses a method and device for collecting MRE imaging sequence data. The method comprises the following steps: combining an MRI imaging sequence with a motion encoding gradient to collect MRE imaging sequence data of a brain tissue subjected to vibration; wherein the first to Nth phase encodings are used to sequentially collect a first phase encoding line in each time sequence image of all N time sequence images, the (N+1)th to 2Nth phase encodings are used to sequentially collect a second phase encoding line in each time sequence image of all N time sequence images, the (2N+1)th to 3Nth phase encodings are used to sequentially collect a third phase encoding line in each time sequence image of all N time sequence images, and the process is continued until all phase encoding lines in each time sequence image of all N time sequence images are sequentially collected. Through the MRI sequence, the motion encoding gradient and the line scanning mode, the dynamic detection capability with millisecond-level time resolution can be realized, and the limitation of low time resolution of traditional MRE imaging is broken.

Description

Technical Field

[0001] This application relates to the field of magnetic resonance imaging technology, and in particular to a technique for acquiring MRE imaging sequence data. Background Technology

[0002] This section is intended to provide background or context for the embodiments of this application as set forth in the claims. The content in this section is for reference only and does not constitute an admission or confirmation that it is prior art that has been disclosed.

[0003] Magnetic Resonance Elastography (MRE) is a non-invasive magnetic resonance imaging technique for measuring the mechanical properties of tissues (stiffness, viscoelasticity, hardness, etc.). It has wide applications in assessing liver fibrosis and cirrhosis, and in recent years has shown advantages in researching neurodegenerative diseases (such as Alzheimer's disease), brain tumors, and brain tissue biomechanics. In simple terms, MRE imaging involves three key steps: 1) MRE generates propagating shear waves (sine waves) within the tissue by applying controlled mechanical vibrations of a certain frequency outside the tissue; 2) Motion-encoding gradients (MEGs) with the same frequency as the shear waves are used to detect the minute periodic displacements of particles within the tissue caused by the shear waves, resulting in a magnetic resonance phase map; 3) Finally, a displacement map is obtained from the phase map using a reconstruction algorithm, and a stiffness map reflecting tissue hardness is generated using an inversion algorithm. Since the displacement of particles within the tissue varies sinusoidally over time, multiple (usually 4-8) equally spaced phase offset points need to be acquired to obtain the displacement waveform; this is called phase offset. In addition, since shear waves propagate in tissues in a directional manner, tissue stiffness may be anisotropic (such as muscle and white matter fiber bundles). The unidirectional motion encoding gradient is only sensitive to displacement along that direction. Therefore, it is necessary to acquire images in multiple (usually 3 or 6) directions to accurately obtain the tissue stiffness in all directions.

[0004] Currently, the methods for detecting brain activity at the whole-brain scale in vivo still have serious shortcomings. There is a lack of safe and reliable methods that offer both high spatiotemporal resolution, which greatly restricts the development of basic neuroscience research and brain disease research. Among numerous functional brain imaging techniques, traditional blood oxygen level-dependent functional magnetic resonance imaging (BOLD-fMRI), based on neurovascular coupling effects, has long dominated in in vivo whole-brain level brain function research due to its non-invasiveness, high spatiotemporal resolution, and whole-brain visualization advantages, providing immense value for studying brain operation mechanisms and the pathogenesis of brain diseases. Although BOLD-fMRI is widely used in basic and clinical research, its signal source is neurovascular coupling signals, with a response time on the order of seconds and low signal sensitivity, which makes it impossible to study real neural activity responses and detect subtle functional changes using fMRI. On the other hand, although electroencephalography (EEG) and magnetoencephalography (EMG) can provide millisecond-level temporal resolution for studying brain functional activity, their spatial resolution is far inferior to that of magnetic resonance imaging (MRI). Furthermore, while optical imaging techniques can achieve high spatiotemporal resolution, their limited depth of detection prevents accurate measurement of deep brain regions. Although nuclear medicine molecular imaging techniques offer high sensitivity, subjects need to be exposed to ionizing radiation, and their spatial resolution is limited. Therefore, establishing and developing non-invasive methods for detecting brain functional activity with high spatiotemporal resolution is a core goal and requirement in the fields of brain imaging and neuroscience.

[0005] Furthermore, MRI technology, with its advantages of being non-invasive, highly penetrating, high-resolution, and capable of providing multi-contrast information, holds immense potential for developing high spatiotemporal resolution techniques based on MRI to study whole-brain neural activity. A comprehensive analysis of the shortcomings of current brain functional imaging methods reveals the need for breakthroughs in two key areas: "signal detection source" and "imaging temporal resolution." Therefore, to achieve the goal of non-invasive MRI-based neural activity detection, the following must be simultaneously met: 1) The detected signal source must be able to safely and accurately characterize brain neural activity. 2) Achieve millisecond temporal resolution imaging speed to dynamically capture millisecond-level representational information of neural activity. Compared to neurovascular coupling in the brain, neuromechanical coupling is much faster: nerve fibers swell within approximately 5 milliseconds of an action potential, causing physical displacement of axons; action potentials can cause transient (e.g., hundreds of milliseconds) contraction of dendritic spines. Therefore, only by developing ultrafast MRE methods with millisecond temporal resolution can these transient changes in physical and mechanical properties induced by neural activity be detected.

[0006] Therefore, there is an urgent need for an ultrafast MRE method with millisecond time resolution in order to dynamically capture representational information of brain neural activity at the millisecond level. Summary of the Invention

[0007] The purpose of this application is to provide a method for acquiring MRE imaging sequence data, which utilizes MRI sequences combined with motion-coded gradients and line scanning to achieve dynamic detection capabilities with millisecond-level temporal resolution, breaking through the limitation of low temporal resolution in traditional MRE imaging.

[0008] To address the aforementioned technical problems, this application discloses a method for acquiring MRE imaging sequence data, comprising the following steps:

[0009] Applying mechanical vibrations to the outside of brain tissue generates shear waves inside the brain tissue;

[0010] MRI imaging sequences are combined with motion-coded gradients to acquire MRE imaging sequence data of vibrated brain tissue. Specifically, the first to Nth phase encodings sequentially acquire the first phase encoding line in each of the N time-series images, the (N+1)th to 2Nth phase encodings sequentially acquire the second phase encoding line in each of the N time-series images, the (2N+1)th to 3Nth phase encodings sequentially acquire the third phase encoding line in each of the N time-series images, and so on, until all phase encoding lines in each of the N time-series images have been acquired sequentially, where N is an integer greater than 2.

[0011] In another preferred embodiment, the switching frequency of the motion-coded gradient is the same as the frequency of the shear wave.

[0012] In another preferred embodiment, the MRI imaging sequence includes: a gradient echo-based sequence and a spin echo-based sequence.

[0013] In another preferred embodiment, the step of combining the MRI imaging sequence with motion-coded gradients includes the following sub-steps:

[0014] This combines MRI imaging sequences, motion-coded gradients, and stimuli that are matched to specific phase-coded times.

[0015] In another preferred embodiment, the stimulus matched with a specific phase encoding time includes visual and tactile stimuli.

[0016] In another preferred embodiment, the acquisition method is used to acquire MRE imaging sequence data of transient mechanics dynamic signal changes induced by brain neuro-mechanical coupling.

[0017] This application also discloses an MRE imaging sequence data acquisition device, comprising:

[0018] The vibration module is used to apply mechanical vibrations to the outside of brain tissue, thereby generating shear waves inside the brain tissue;

[0019] The acquisition module is used to combine MRI imaging sequences with motion-coded gradients to acquire MRE imaging sequence data of vibrated brain tissue. Specifically, the first to Nth phase encodings sequentially acquire the first phase encoding line in each of the N time-series images, the (N+1)th to 2Nth phase encodings sequentially acquire the second phase encoding line in each of the N time-series images, the (2N+1)th to 3Nth phase encodings sequentially acquire the third phase encoding line in each of the N time-series images, and so on, until all phase encoding lines in each of the N time-series images have been acquired sequentially, where N is an integer greater than 2.

[0020] The embodiments of this application also disclose a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps in the above-described method.

[0021] This application also discloses an MRE imaging sequence data acquisition device, comprising:

[0022] Memory, used to store computer-executable instructions; and,

[0023] A processor, coupled to the memory, is configured to implement the steps of the above method when executing the computer-executable instructions.

[0024] The embodiments of this application also disclose a computer program product, including computer-executable instructions that, when executed by a processor, implement the steps in the above-described method.

[0025] The main differences and effects of the implementation method of this application compared with the prior art are as follows:

[0026] The embodiments of this application, by combining MRI sequences with motion-coded gradients and line scanning, can achieve dynamic detection capabilities with millisecond-level temporal resolution, breaking the limitation of low temporal resolution in traditional MRE imaging.

[0027] Furthermore, the embodiments of this application adopt a line scanning method, sequentially acquiring only one phase encoding line at a time point (time interval TR), and completing all phase encoding lines in all time-series images through multiple repeated acquisitions, thereby achieving the acquisition of all dynamic data sequentially with the phase encoding time interval TR as the time resolution.

[0028] Furthermore, the embodiments of this application adjust the data acquisition order and place the dynamic repetition number in the innermost loop, thereby realizing the line scan acquisition mode of MRE imaging sequence data and improving the acquisition time resolution to the millisecond level.

[0029] Furthermore, the embodiments of this application utilize a line scanning strategy to develop an ultra-fast MRE imaging sequence (e.g., TR = 10 milliseconds), and combine it with an event-related stimulus strategy to collect the transient MRE response signal induced by the stimulus, thereby achieving the acquisition of dynamic brain activity signals with a time resolution at the millisecond level.

[0030] Furthermore, embodiments of this application can be combined with existing MRI sequences to achieve high temporal resolution GRE- / SE-MRE imaging.

[0031] Furthermore, embodiments of this application are used to measure the instantaneous (millisecond level) mechanical dynamic response induced by brain neural-mechanical coupling, thereby capturing the brain neural activity process.

[0032] Furthermore, the embodiments of this application realize high temporal resolution MRE imaging technology, which can not only promote the development of medical imaging technology, but also promote the development of the field of neuroscience.

[0033] The various technical features disclosed in the above-described invention, the various technical features disclosed in the following embodiments and examples, and the various technical features disclosed in the accompanying drawings can be freely combined to form various new technical solutions (all of which should be considered as having been recorded in this specification), unless such a combination of technical features is technically infeasible. For example, in one example, feature A+B+C is disclosed, and in another example, feature A+B+D+E is disclosed. Features C and D are equivalent technical means that serve the same function, and technically only one needs to be used; it is impossible to use both simultaneously. Feature E can be technically combined with feature C. Therefore, the solution A+B+C+D should not be considered as having been recorded because it is technically infeasible, while the solution A+B+C+E should be considered as having been recorded. Attached Figure Description

[0034] Figure 1 This is a schematic diagram of a surface scanning acquisition mode for MRE sequence data in the prior art;

[0035] Figure 2 This is a schematic diagram of an MRE sequence data line scan acquisition mode according to an embodiment of this application;

[0036] Figure 3 This is a flowchart illustrating a method for acquiring MRE imaging sequence data according to the first embodiment of this application;

[0037] Figure 4 This is a schematic diagram of a GRE sequence according to the first embodiment of this application;

[0038] Figure 5This is a schematic diagram of an SE sequence according to the first embodiment of this application;

[0039] Figure 6 This is a schematic diagram of the structure of an MRE imaging sequence data acquisition device according to the second embodiment of this application. Detailed Implementation

[0040] In the following description, many technical details are presented to help the reader better understand this application. However, those skilled in the art will understand that the technical solutions claimed in this application can be implemented even without these technical details and various variations and modifications based on the following embodiments.

[0041] Explanation of some concepts:

[0042] Although both MRE (Magnetic Resonance Elastography) and MRI (Magnetic Resonance Imaging) are based on magnetic resonance technology, their principles and applications differ significantly:

[0043] MRI utilizes the resonance properties of hydrogen atoms in human tissues in a strong magnetic field. It uses radio frequency pulses to excite hydrogen atoms and receive the signals they release to generate images of anatomical structures (such as the brain, blood vessels, and organs), which are mainly used to reflect the morphology and structure of tissues.

[0044] MRE introduces mechanical shear waves on top of MRI. It quantifies the stiffness of tissue by detecting the deformation (elasticity) of the tissue under vibration. It requires special equipment to generate vibration (usually 50-1000Hz) and uses phase contrast technology to capture the propagation of the wave to generate an elasticity map (elastic modulus distribution).

[0045] MRI is a general-purpose morphological imaging tool, while MRE is a functional extension of MRI that focuses on the mechanical properties of tissues; the two can be used in a complementary manner.

[0046] Motion encoding gradient (MEG) is a key component of MRI technology, primarily used to detect and quantify microscopic tissue motion information. It is one of the core functions of the MRI gradient magnetic field system, its main role being to encode tissue motion information by applying a gradient magnetic field in a specific direction. In an MRI system, the gradient magnetic field has multiple functions, including spatial localization, signal readout, phase disturbance, flow compensation, and motion encoding.

[0047] K-space: K-images and actual MRI images are two completely equivalent but different ways of representing the same object. Essentially, it is the mathematical space (frequency domain) of the raw data, a deconstructed representation of the spatial frequencies that make up the image. It stores the raw signal information acquired during the MRI scan. MRI signals are acquired after applying phase-encoded and frequency-encoded gradients, with each acquisition filling a row or a trajectory in K-space. The final MRI image is obtained by performing a Fourier transform on the K-space data.

[0048] In a K-graph, similar to x and y coordinates in physical space, the horizontal and vertical axes are generally represented by kx and ky axes. The physical meaning of each point (kx, ky) is spatial frequencies. (kx, ky) and (x, y) are not in a one-to-one correspondence, and the spatial frequency and phase information contained in each point includes all pixel information. Simply put, it is a one-to-many relationship, and conversely, the same applies to the mapping from a point in the physical space image to the K-graph.

[0049] Neurovascular coupling refers to changes in local vascular activity caused by neural activity, including vasoconstriction and blood flow.

[0050] Neuromechanical coupling refers to the alteration of physical and mechanical properties coupled to neural activity, including properties such as viscosity, elasticity, and hardness.

[0051] A phase encoding line (PE line) is a data line acquired along the phase encoding direction in k-space. Each phase encoding line represents the signal data acquired after a specific phase encoding gradient is applied. In MRI sequences, each phase encoding line needs to be acquired individually, which is one of the main factors affecting MRI scan time. During k-space filling, each line corresponds to a different number of phase encoding steps; the center line (k-space center) usually corresponds to zero phase encoding gradient, while lines farther from the center correspond to stronger phase encoding gradients.

[0052] In existing technologies, the data acquisition sequence of MRE imaging is as follows: Figure 1 As shown, all phase-encoded lines for each surface are first acquired; this is referred to as "surface scanning." In this acquisition mode, the temporal resolution (the time required to acquire a whole-brain image or the time interval between two repetitions, defined as Volume TR, denoted by TR) is... volume (This indicates a very low number of repetitions.) Assume the number of MRE repetitions is N. repetition Phase offset number N phase The number of directions is N direction The number of phase codes collected is N pe The number of layers is N sliceThen TR volume =TR*N pe *N slice *N phase *N direction The time resolution is several minutes or even tens of minutes. The data acquisition sequence under "area scan" is shown below, with the dynamic repetition count placed in the outermost loop:

[0053]

[0054] Here, Phase Offset refers to phase compensation, and MEG polarity refers to MEG polarity.

[0055] like Figure 1 As shown, in the area scan acquisition mode, the first phase encoding acquires the first phase encoding line (PE 1) in the first time sequence image, the second phase encoding acquires the second phase encoding line (PE 2) in the first time sequence image, the third phase encoding acquires the third phase encoding line (PE 3) in the first time sequence image, and so on, until the Nth phase encoding line (PE N) in the first time sequence image is acquired, and all N phase encoding lines in the first time sequence image are acquired sequentially. pe (That is, N) phase encoding lines, thus completing the first acquisition cycle (Repetition 1), where N pe It is an integer greater than 2. Next, the second acquisition cycle continues, sequentially acquiring all N values ​​within the second time series image. pe One phase encoding line. Then, continue with the third acquisition cycle, sequentially acquiring all N in the third time series image. pe There are 1 phase encoding line. This process continues until the Nth acquisition cycle (Repetition N), sequentially acquiring all phase encoding lines within all N time-series images, where N is an integer greater than 2. The acquisition time for one phase encoding line (PE line) is TR, then the temporal resolution in this area scan acquisition mode is N. pe *TR. Additionally, in Figure 1 In the sequence shown, Motion refers to externally applied mechanical vibration.

[0056] It should be noted that, in this application, the whole-brain image is described using the example of N temporal images, and each temporal image includes N phase coding lines. Those skilled in the art will understand that in other embodiments, each temporal image may also include M phase coding lines, where N and M are integers greater than 2.

[0057] Therefore, even MRE methods based on echo planar imaging (EPI) sequences can only achieve a temporal resolution on the order of seconds. However, the mechanical properties of the nervous system change on a millisecond timescale during neural activity. Thus, existing MRE sequences cannot measure these rapidly changing (e.g., millisecond-level) tissue mechanical properties.

[0058] In this embodiment, a creative approach is proposed, such as... Figure 2 The "line scan" strategy shown involves acquiring only one phase-coded line at a time point (within a time interval of TR) according to a specific time sequence. This process is repeated multiple times to sequentially acquire all phase-coded lines within all time-series images. In this scheme, the data acquisition order is adjusted as shown below, with the dynamic repetition count placed in the innermost loop:

[0059]

[0060] This allows for a time resolution based on the time TR of acquiring a single PE line, after N... pe After several repetitions, all dynamic data are acquired according to a specific time sequence. This specific time sequence means filling the data sequentially, starting with the first line, then the second, and so on. That is, filling from -ky / 2 to ky / 2 sequentially (ky refers to the total number of phase coding steps within a time series image).

[0061] By adjusting the data acquisition order and placing the dynamic repetition count in the innermost loop, a line scan acquisition mode for MRE imaging sequence data is achieved, improving the acquisition time resolution to the millisecond level.

[0062] It should be noted that in area scan mode, N pe This refers to all phase-coded lines within a time-series image; while in online scanning mode, N pe It refers to all phase coding lines within all time-series images.

[0063] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0064] The first embodiment of this application relates to a method for acquiring MRE imaging sequence data, the process of which is as follows: Figure 3 As shown.

[0065] Specifically, such as Figure 2 and Figure 3 As shown, the method for acquiring MRE imaging sequence data includes the following steps:

[0066] In step 301, mechanical vibrations are applied outside the brain tissue to generate shear waves inside the brain tissue.

[0067] Then, proceed to step 302, where the MRI imaging sequence is combined with motion-coded gradients to acquire MRE imaging sequence data of the vibrated brain tissue. Specifically, the first (Repetition 1) to the Nth (Repetition N) phase encodings sequentially acquire the first phase encoding line (PE 1) in each of the N time-series images, the N+1 to 2Nth phase encodings sequentially acquire the second phase encoding line (PE 2) in each of the N time-series images, the 2N+1 to 3Nth phase encodings sequentially acquire the third phase encoding line (PE 3) in each of the N time-series images, and so on, until the Nth phase encoding line (PE N) in each of the N time-series images is acquired. All phase encoding lines in each of the N time-series images are acquired sequentially, where N is an integer greater than 2.

[0068] By adopting a line scanning method, one phase encoding line is acquired sequentially at one time point (time interval TR). After repeated acquisitions, all phase encoding lines in all time-series images are acquired in sequence, so that the time resolution is the time interval TR of phase encoding, and all dynamic data are acquired in sequence.

[0069] This process will then end.

[0070] This application achieves millisecond-level temporal resolution by combining MRI sequences with motion-coded gradients and line scanning, breaking the limitation of low temporal resolution in traditional MRE imaging.

[0071] In this embodiment, preferably, the switching frequency of the motion coding gradient is the same as the frequency of the shear wave.

[0072] The MRI imaging sequences include gradient echo-based sequences and spin echo-based sequences.

[0073] The core of magnetic resonance elastography (MRE) sequences is motion-coded gradients. Conventional MRI imaging sequences combined with motion-coded gradients can achieve MRE. The most commonly used is gradient echo (GRE) based sequences (such as...). Figure 4 (as shown) and sequences based on spin echo (SE) (such as...) Figure 5 (As shown). In addition, the imaging speed can be improved by combining it with echo planar imaging (EPI) acquisition technology.

[0074] The embodiments described in this application can be combined with existing conventional MRI sequences to achieve high temporal resolution GRE- / SE-MRE imaging.

[0075] In this embodiment, preferably, the step of combining the MRI imaging sequence with motion-coded gradients may further include the following sub-steps:

[0076] This involves combining MRI imaging sequences, motion-coded gradients, and stimuli matched to a specific phase-coding time. The stimuli matched to the specific phase-coding time include visual and tactile stimuli.

[0077] In the K-space filling scheme for dynamic MRE data, each MRE data signal line acquired during each phase encoding is sequentially filled into the K-space of the image at different time points according to the temporal sequence of task / stimulus matching in the experiment; this process is repeated N times. pe After each identical stimulus, the data lines fill the entire K-space of the time-series image. The acquisition time sequence corresponding to each signal line in the complete K-space of each image acquired under different tasks / stimuli is completely consistent with the sequence of stimulus occurrences (e.g., ...). Figure 2 (As shown). This allows for the effective temporal resolution of dynamic measurements of brain activity to be determined by the acquisition time (TR) of each phase encoding step. It can improve the effective temporal resolution of dynamic measurements to 10 ms (depending on TR), overcoming the limitations of existing MRE techniques in the study of dynamic neural activity. It can be combined with stimulus / task events matched to specific phase encoding times to perform millisecond-resolution dynamic studies of neural activity.

[0078] By utilizing a line-scanning strategy, an ultrafast MRE imaging sequence (e.g., TR = 10 ms) can be developed. Combined with an event-related stimulus strategy, the transient MRE response signal evoked by the stimulus can be acquired, enabling the acquisition of dynamic brain activity signals with millisecond-level temporal resolution. The stimulus duration should be less than the TR; for example, when TR = 10 ms, the stimulus duration should be less than 10 ms, such as 5 ms.

[0079] Finally, it should be noted that the MRE imaging sequence data acquisition method of this application is used to acquire MRE imaging sequence data of transient mechanical dynamic signal changes induced by brain neuro-mechanical coupling. In other words, the embodiments of this application are used to measure the transient (millisecond level) mechanical dynamic response induced by brain neuro-mechanical coupling, thereby capturing the brain neural activity process.

[0080] In summary, the embodiments of this application realize high temporal resolution MRE imaging technology, which can not only promote the development of medical imaging technology, but also promote the development of the field of neuroscience.

[0081] The second embodiment of this application relates to an acquisition device for MRE imaging sequence data, the structural schematic diagram of which is shown below. Figure 6 As shown.

[0082] Specifically, such as Figure 6 As shown, the acquisition device for the MRE imaging sequence data includes:

[0083] The vibration module is used to apply mechanical vibrations to the outside of brain tissue, thereby generating shear waves inside the brain tissue;

[0084] The acquisition module is used to combine MRI imaging sequences with motion-coded gradients to acquire MRE imaging sequence data of vibrated brain tissue. Specifically, the first to Nth phase encodings sequentially acquire the first phase encoding line in each of the N time-series images, the (N+1)th to 2Nth phase encodings sequentially acquire the second phase encoding line in each of the N time-series images, the (2N+1)th to 3Nth phase encodings sequentially acquire the third phase encoding line in each of the N time-series images, and so on, until all phase encoding lines in each of the N time-series images have been acquired sequentially, where N is an integer greater than 2.

[0085] The first embodiment is a method embodiment corresponding to this embodiment. The technical details in the first embodiment can be applied to this embodiment, and the technical details in this embodiment can also be applied to the first embodiment.

[0086] Accordingly, embodiments of this application also provide a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the various method embodiments of this application. Computer-readable storage media include permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media 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 memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device. As defined herein, computer-readable storage media does not include transient media, such as modulated data signals and carrier waves.

[0087] Furthermore, embodiments of this application also provide an MRE imaging sequence data acquisition device, including a memory for storing computer-executable instructions, and a processor; the processor is used to implement the steps in the above-described method embodiments when executing the computer-executable instructions in the memory. The processor may be a Central Processing Unit (CPU), Graphics Processing Unit (GPU), Digital Signal Processor (DSP), Microcontroller Unit (MCU), Neural Processing Unit (NPU), Application Specific Integrated Circuit (ASIC), Field Programmable Gate Array (FPGA), or other programmable logic devices. The aforementioned memory may be read-only memory (ROM), random access memory (RAM), flash memory, hard disk, or solid-state drive, etc. The steps of the methods disclosed in the embodiments of this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules in the processor.

[0088] Furthermore, embodiments of this application also provide a computer program product, including computer-executable instructions that, when executed by a processor, implement the steps in the above-described method embodiments.

[0089] It should be noted that in this application, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one" does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element. In this application, if it refers to performing an action according to an element, it means performing the action at least according to that element, including two cases: performing the action only according to that element, and performing the action according to that element and other elements. Expressions such as "multiple," "repeatedly," and "various" include two, two times, two kinds, and more than two, more than two times, and more than two kinds.

[0090] The numbering used in describing the steps of a method does not inherently limit the order of these steps. For example, a step with a higher number does not necessarily have to be executed after a step with a lower number; it can be executed first and then second, or even in parallel, as long as this execution order is reasonable to someone skilled in the art. Similarly, multiple steps with consecutively numbered sequences (e.g., step 101, step 102, step 103, etc.) do not restrict other steps from being executed between them; for example, there can be other steps between step 101 and step 102.

[0091] This specification includes combinations of various embodiments described herein. Individual references to embodiments are made (e.g., "one embodiment," "some embodiments," or "preferred embodiments"); however, these embodiments are not mutually exclusive unless indicated to be mutually exclusive or are readily apparent to those skilled in the art. It should be noted that the word "or" is used in a non-exclusive sense throughout this specification unless the context explicitly indicates or requires it.

[0092] All references to this specification are considered to be incorporated integrally into the disclosure of this application so that they can serve as the basis for modifications if necessary. Furthermore, it should be understood that the above descriptions are merely preferred embodiments of this specification and are not intended to limit the scope of protection of this specification. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of one or more embodiments of this specification should be included within the scope of protection of one or more embodiments of this specification.

[0093] In some cases, the actions or steps described in the claims can be performed in a different order than that shown in the embodiments and still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. A method of acquisition of MRE imaging sequence data, characterized in that, The acquisition method is used to acquire MRE imaging sequence data of transient mechanical dynamic signal changes induced by brain neuro-mechanical coupling, and includes the following steps: Applying mechanical vibrations to the outside of brain tissue generates shear waves inside the brain tissue; MRI imaging sequences were combined with motion-coded gradients to acquire MRE imaging sequence data of vibrating brain tissue. Specifically, the first to Nth phase encoding operations sequentially acquired the first phase-coded line in each of the N time-series images; the (N+1)th to 2Nth phase encoding operations sequentially acquired the second phase-coded line in each of the N time-series images; the (2N+1)th to 3Nth phase encoding operations sequentially acquired the third phase-coded line in each of the N time-series images, and so on, until all phase-coded lines in each of the N time-series images were acquired sequentially, where N is an integer greater than 2. During the data collection process, the data collection order is adjusted, and the dynamic repetition count is placed in the innermost loop. The step of combining the MRI imaging sequence with motion-coded gradients includes the following sub-steps: Combining MRI imaging sequences, motion-coded gradients, and stimuli matched with specific phase-coded times; The stimuli that are matched with a specific phase encoding time include visual stimuli and tactile stimuli.

2. The method of acquiring MRE imaging sequence data of claim 1, wherein, The switching frequency of the motion coding gradient is the same as the frequency of the shear wave.

3. The method of acquiring MRE imaging sequence data of claim 1, wherein, The MRI imaging sequences include gradient echo-based sequences and spin echo-based sequences.

4. An apparatus for the acquisition of MRE imaging sequence data, characterized in that The acquisition device is used to acquire MRE imaging sequence data of transient mechanical dynamic signal changes induced by brain neuro-mechanical coupling, including: The vibration module is used to apply mechanical vibrations to the outside of brain tissue, thereby generating shear waves inside the brain tissue; The acquisition module is used to combine MRI imaging sequences with motion-coded gradients to acquire MRE imaging sequence data of vibrated brain tissue. Specifically, the first to Nth phase encodings sequentially acquire the first phase encoding line in each of the N time-series images, the (N+1)th to 2Nth phase encodings sequentially acquire the second phase encoding line in each of the N time-series images, the (2N+1)th to 3Nth phase encodings sequentially acquire the third phase encoding line in each of the N time-series images, and so on, until all phase encoding lines in each of the N time-series images have been acquired sequentially, where N is an integer greater than 2. During the acquisition process, the acquisition module adjusts the data acquisition order and places the dynamic repetition count in the innermost loop. The step of combining the MRI imaging sequence with motion-coded gradients includes the following sub-steps: Combining MRI imaging sequences, motion-coded gradients, and stimuli matched with specific phase-coded times; The stimuli that are matched with a specific phase encoding time include visual stimuli and tactile stimuli.

5. A computer readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions that, when executed by a processor, implement the steps of the method as described in any one of claims 1 to 3.

6. An acquisition device of MRE imaging sequence data, characterized in that, include: Memory is used to store executable instructions for a computer; as well as, A processor, coupled to the memory, is configured to implement the steps of the method as described in any one of claims 1 to 3 when executing the computer-executable instructions.

7. A computer program product comprising computer executable instructions, characterised in that, When executed by a processor, the computer-executable instructions implement the steps of the method described in any one of claims 1 to 3.

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