Variable saturation gradient-based three-dimensional CEST or z-spectrum magnetic resonance imaging method and device

Abstract

A variable saturation gradient-based three-dimensional CEST or Z spectrum magnetic resonance imaging method, and an electronic device (500). The method comprises: while applying a saturation pulse to a target object, turning on a gradient in an r direction, reading out an original image, and repeating this process a number n of times, to obtain n groups of original images; filling the n groups of original images onto an r-Δω plane; determining a target uncollected image based on collected images on the r-Δω plane, and estimating the target uncollected image; interpolating and / or fitting based on the collected images and the estimated target uncollected image, to obtain a CEST or Z spectrum image having high spatial resolution and a high spectrum sampling rate.

Description

Three-dimensional CEST or Z-spectrum magnetic resonance imaging method and device based on variable saturation gradient

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] The present disclosure claims priority to Chinese patent application number 202311266353.1 filed on September 27, 2023, entitled “Three-dimensional CEST or Z-spectrum magnetic resonance imaging method and device based on variable saturation gradient,” the entire contents of which are incorporated herein by reference. Technical Field

[0003] The present disclosure relates to the technical field of magnetic resonance imaging, and in particular to a three-dimensional CEST magnetic resonance imaging method based on a variable saturation gradient and an electronic device. Background Art

[0004] Chemical Exchange Saturation Transfer (CEST) Magnetic Resonance Imaging (MRI) is an emerging molecular imaging technology that can be used for metabolic detection and pH detection of diseases such as cancer, tumors, and stroke.

[0005] Because the resonant frequency of hydrogen protons in substances such as proteins, glucose, creatine, and salicylic acid analogs in the human body differs from the resonant frequency of hydrogen protons in water molecules, and the magnetization vectors of the hydrogen protons in these substances can exchange with those in water, saturation radiofrequency pulses at specific frequencies can be applied to human tissue to saturate the hydrogen protons in these chemicals. This exchange effect then affects the intensity of the water signal. By detecting changes in the water signal intensity, the exchange rate and concentration of various chemical substances in the body can be indirectly reflected. Therefore, CEST technology can serve as a signal amplifier for low-concentration biomolecules. Typically, CEST requires acquiring MR images subjected to saturation pulses of different frequencies, then generating Z spectra to study chemical exchange information at specific frequency offsets. By analyzing the Z spectra, the desired CEST signal can be extracted.

[0006] However, because CEST requires sequential acquisition of multiple saturation frequency images of the same anatomical structure, and because saturation pulses lasting several seconds must be repeated, CEST MRI technology suffers from long scan times. Conventional CEST sequences typically sacrifice the number of saturation frequency points and spatial resolution to keep scan times within clinically acceptable limits. Simultaneously achieving high spatial resolution and high spectral sampling rates for rapid imaging has been a research hotspot in the CEST MRI field.

[0007] In recent years, a series of technologies have emerged to address the problems of long CEST MRI scanning time and limited spatial-spectral sampling rate. In terms of acquisition sequence, the use of a fast readout module or a steady-state CEST sequence can achieve whole-brain scanning. However, since each saturation frequency deviation needs to be repeated for at least one repetition time (TR), and in order to ensure sufficient saturation time and longitudinal relaxation recovery, each TR requires 4-6 seconds. Therefore, in practice it is difficult to acquire CEST data that takes into account both spatial resolution and spectral sampling rate. In order to further improve the acquisition efficiency, a saturation gradient encoding technology is proposed in the related art. This technology realizes the simultaneous acquisition of multiple saturation frequencies by simultaneously turning on the layer-selective direction gradient during the application of the saturation pulse, thereby obtaining an intra-layer encoded ultrafast Z-spectrum imaging sequence. However, because this technology performs Z-spectral readings in the layer-selective direction, dividing a 10mm thick layer into dozens to hundreds of sublayers encoded with different saturation frequency offsets, it can only image relatively uniform tissue between sublayers. Furthermore, due to the thinness of each sublayer (100μm), the signal-to-noise ratio is limited, resulting in only low intra-layer resolution (5×5mm-8mm), which limits its further application. In terms of reconstruction technology, some technologies use parallel imaging, compressed sensing, deep learning, and other methods to recover complete CEST images from undersampled data, thereby accelerating CEST imaging. However, the disadvantage is that reconstruction after undersampling the data often sacrifices image quality, which is not conducive to subsequent CEST quantitative analysis.

[0008] Summary of the Invention

[0009] The present disclosure aims to at least partially address one of the technical issues in the related art. To this end, the present disclosure provides a method and electronic device for three-dimensional CEST or Z-spectrum magnetic resonance imaging based on a variable saturation gradient to rapidly obtain three-dimensional CEST or Z-spectrum magnetic resonance images with high spatial resolution and high spectral sampling rate.

[0010] To solve the above technical problems, an embodiment of the first aspect of the present disclosure proposes a three-dimensional CEST or Z-spectrum magnetic resonance imaging method based on a variable saturation gradient, comprising: applying a saturation pulse to a target object while turning on the gradient in the r direction and reading out the original image, repeating the above process n times to obtain n groups of original images, wherein the center frequency and gradient values ​​of the saturation pulse applied each time are different, r represents the spatial position, including at least one of the x, y, and z directions, and n is an integer greater than 1; filling the n groups of original images onto the r-Δω plane, wherein Δω represents the frequency offset; determining the target uncollected image based on the collected image in the r-Δω plane, and estimating the target uncollected image; performing interpolation and / or fitting based on the collected image and the estimated target uncollected image to obtain a CEST or Z-spectrum image with high spatial resolution and high spectral sampling rate.

[0011] The disclosed embodiment of the three-dimensional CEST or Z-spectrum magnetic resonance imaging method based on a variable saturation gradient first applies a saturation pulse to the target object while turning on the gradient in the r direction, reading out the original image, and repeating this process n times to obtain n sets of original images. The n sets of original images are then populated onto the r-Δω plane, and the target uncollected image is determined based on the collected image in the r-Δω plane, and the target uncollected image is estimated. Interpolation and / or fitting are then performed based on the collected image and the estimated target uncollected image to obtain a CEST-Z-spectrum image with high spatial resolution and high spectral sampling rate. This method can quickly obtain CEST magnetic resonance images with high spatial resolution, high spectral sampling rate, and strong interpretability, helping to improve the accuracy of CEST quantitative analysis and disease diagnosis. It has important clinical value and is highly flexible and scalable.

[0012] In addition, the three-dimensional CEST or Z-spectrum magnetic resonance imaging method based on a variable saturation gradient according to the embodiment of the present disclosure may also have the following additional technical features:

[0013] According to one embodiment of the present disclosure, the n groups of original images are filled onto the r-Δω plane using the following formula: Δω(r)=Δω0+γG offset Δr

[0014] Where Δω(r) represents the frequency offset corresponding to the r direction, Δr represents the distance between the imaging position corresponding to the r direction and the magnetic field zero point, γ represents the gyromagnetic ratio, Δω0 represents the frequency offset between the saturation pulse frequency and the water hydrogen proton frequency, G offset represents the gradient in the r direction that is simultaneously turned on during the application of the saturation pulse.

[0015] According to one embodiment of the present disclosure, the target uncaptured image includes an uncaptured image on an adjacent layer and adjacent saturation frequency offset to the captured image in the r-Δω plane.

[0016] According to one embodiment of the present disclosure, the captured image is recorded as The corresponding target uncollected images include Through the following formula Make an estimate:

[0017] in, Respectively represent the unsaturated images on the r1 and r2 levels, They represent the acquired images at the frequency offset ω1 on the r1 layer and at the frequency offset ω2 on the r2 layer, respectively. They represent the target images not collected at the frequency offset of ω2 on the r1 layer and at the frequency offset of ω1 on the r2 layer, respectively. They represent the relative saturation information at the ω2 frequency offset on the r1 level and at the ω1 frequency offset on the r2 level, respectively. They represent the average values ​​of the acquired images at the frequency offset ω1 on the r1 layer and at the frequency offset ω2 on the r2 layer, Represent the average values ​​of the unsaturated images on the r1 and r2 levels respectively.

[0018] According to one embodiment of the present disclosure, interpolation and / or fitting are performed based on the captured image and the estimated target uncaptured image, including: using the multi-pool Bloch-McConnell equation for simulation, and obtaining multiple Z spectrum sample sets with different waveforms by changing the simulation parameters of each pool; performing singular value decomposition on the Z spectrum sample set, and selecting the right singular vectors corresponding to the first m larger singular values ​​to form a new singular vector matrix, where m is an integer greater than 2; determining all vectors z0 with incomplete saturation frequency deviation points based on the captured image and the estimated target uncaptured image, and for each z0, obtaining the complete frequency spectrum of the pixel point corresponding to the z0 based on the z0 and the new singular vector matrix.

[0019] According to one embodiment of the present disclosure, the value of the gradient includes at least 0.

[0020] According to an embodiment of the present disclosure, n groups of original images corresponding to n layers are acquired by using fast spin echo, gradient echo, and planar echo.

[0021] According to an embodiment of the present disclosure, the n groups of original images corresponding to the n acquired layers are radial, parallel or cross-shaped on the r-Δω plane.

[0022] According to one embodiment of the present disclosure, the method further includes: post-processing the obtained CEST-Z spectrum image with high spatial resolution and high spectral sampling rate, wherein the post-processing method includes magnetization transfer rate asymmetry processing, Lorentz difference and multi-cell Lorentz processing.

[0023] To solve the above technical problems, the second embodiment of the present disclosure proposes an electronic device, including a memory, a processor and a computer program stored in the memory. When the computer program is executed by the processor, the three-dimensional CEST magnetic resonance imaging method based on variable saturation gradient of the above embodiment is implemented.

[0024] The electronic device of the embodiment of the present disclosure can quickly obtain CEST magnetic resonance images with high spatial resolution, high spectral sampling rate, and strong interpretability by executing the computer program corresponding to the three-dimensional CEST or Z-spectrum magnetic resonance imaging method based on variable saturation gradient of the above-mentioned embodiment stored in the memory through the processor, which helps to improve the accuracy of CEST quantitative analysis and disease diagnosis and has important clinical value.

[0025] Additional aspects and advantages of the present disclosure will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] FIG1 is a flow chart of a three-dimensional CEST or Z-spectrum magnetic resonance imaging method based on a variable saturation gradient according to an embodiment of the present disclosure;

[0027] FIG2( a ) is a schematic diagram of an acquisition sequence of an acquisition solution according to an example of the present disclosure;

[0028] Figure 2(b) is the original image acquired using the scheme shown in Figure 2(a);

[0029] Figure 2(c) is a schematic diagram of the original image shown in Figure 2(b) when it is filled onto the r-Δω plane;

[0030] FIG2( d ) is a schematic diagram of the frequency deviation points of the original image shown in FIG2( b );

[0031] FIG3 is a schematic diagram of an original image of some examples of the present disclosure when it is filled onto the r-Δω plane;

[0032] FIG4 is a schematic diagram of a neighbor estimation process according to an embodiment of the present disclosure;

[0033] FIG5 is a schematic diagram of a fitting estimation process according to an embodiment of the present disclosure;

[0034] FIG6 is a diagram showing the effect of post-processing according to an embodiment of the present disclosure;

[0035] FIG7 is a structural block diagram of an electronic device according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0036] The following describes in detail embodiments of the present disclosure, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present disclosure, and should not be construed as limiting the present disclosure.

[0037] The following describes a three-dimensional CEST or Z-spectrum magnetic resonance imaging method and electronic device based on a variable saturation gradient according to an embodiment of the present disclosure with reference to the accompanying drawings.

[0038] FIG1 is a flowchart of a three-dimensional CEST or Z-spectrum magnetic resonance imaging method based on a variable saturation gradient according to an embodiment of the present disclosure.

[0039] As shown in FIG1 , the three-dimensional CEST or Z-spectral magnetic resonance imaging method based on a variable saturation gradient includes:

[0040] S1: While applying a saturation pulse to the target object, turn on the gradient in the r direction and read out the original image. The above process is repeated n times to obtain n sets of original images, where the center frequency and gradient values ​​of the saturation pulse applied each time are different. r represents the spatial position, including at least one of the x, y, and z directions, and n is an integer greater than 1.

[0041] In the embodiments of the present disclosure, the target object may be any object that can be imaged by magnetic resonance imaging (CEST), such as the patient's brain, abdominal organs, chest organs, muscles, etc.

[0042] In some examples of the present disclosure, the value of n is less than 10, the frequency of the saturation pulse is within the range of -15ppm to 15ppm, and the value of the gradient includes at least 0, for example, at -1G offset ~1G offset The value is within the range.

[0043] FIG2( a ) shows a scheme for high spatial resolution CEST-MRI image acquisition based on space-frequency encoding, in which n=9 and the gradient value G offset Changes 9 times, the saturation pulse frequency ppm also changes 9 times accordingly, the specific value is: 1:1G offset +0ppm, 2:0.5G offset +0ppm,3:0.25G offset +0ppm, 4:-1G offset +0ppm, 5:-0.5G offset +0ppm, 6: -0.25G offset +0ppm, 7:0G offset +(-15ppm), 8:0G offset +3.5ppm, 9:0G offset +(-3.5ppm).

[0044] It should be noted that in Figure 2(a), RF represents the radio frequency pulse, Gs represents the direction selection gradient, Gp represents the phase encoding gradient, and Gf represents the frequency encoding gradient / readout gradient. The saturation pulse applied each time and the gradient in the r direction opened can be any designed value.

[0045] S2, fill n groups of original images onto the r-Δω plane, where Δω represents the frequency offset.

[0046] Specifically, referring to Figure 2(a), the characteristic of the acquisition sequence is that, while applying the CEST saturation frequency, a variable gradient is enabled in the slice selection direction, so that the hydrogen protons in different anatomical slices in the r direction precess at different frequencies, thereby generating a frequency offset with the natural frequency of the saturation pulse that varies with the slice position. The relationship between the frequency offset and the slice position is: Δω(r)=Δω0+γG offset Δr

[0047] Where Δω(r) represents the frequency offset corresponding to the r direction, Δr represents the distance between the imaging position corresponding to the r direction and the magnetic field zero point, γ represents the gyromagnetic ratio, Δω0 represents the frequency offset between the saturation pulse frequency and the water hydrogen proton frequency, G offset represents the gradient in the r direction that is simultaneously turned on during the application of the saturation pulse.

[0048] After the above space-frequency encoding process, the actual saturation frequency in different directions in space varies linearly with the spatial position of the selected layer direction. The collected CEST MRI data contains the full spatial position of the target object and multiple saturation frequency offsets. By adjusting the gradient G offset By knowing the size of the saturation pulse and the natural frequency of the saturation pulse, any straight line can be collected on the r-Δω plane, and then the full space-spectrum high-resolution CEST data that can only be obtained with at least 200 acquisitions can be obtained in less than 10 acquisitions (such as 9 times), thereby improving the data acquisition efficiency.

[0049] In this embodiment, n groups of original images corresponding to n slices may be acquired by using, but not limited to, fast spin echo, gradient echo, and planar echo.

[0050] FIG2( b ) shows the original images acquired using the acquisition scheme shown in FIG2( a ), including 9 sets of whole-brain high spatial resolution CEST MRI images.

[0051] Figure 2(c) shows a schematic diagram of filling the acquired high-resolution original image of the whole brain shown in Figure 2(b) onto the r-Δω plane. For the acquisition scheme shown in Figure 2(a), the acquired original image is radial on the r-Δω plane.

[0052] It should be noted that the n groups of CEST magnetic resonance original images corresponding to the n slices collected can be radial, parallel, cross, etc. on the r-Δω plane, as shown in Figure 3. The specific shape can be determined according to the applied saturation pulse frequency and variable saturation gradient.

[0053] Figure 2(d) shows that in the original image, the number of saturation frequency deviation points actually acquired on each slice in the r direction is n, corresponding to n saturation frequency deviation points on the z spectrum. For the specific acquisition scheme shown in Figure 2(a), the number of saturation frequency deviation points actually acquired on each slice in the r direction is nine.

[0054] S3, determining the target uncollected image according to the collected image in the r-Δω plane, and estimating the target uncollected image.

[0055] The target uncollected image may include an uncollected image on an adjacent layer and adjacent saturation frequency offset to the collected image in the r-Δω plane.

[0056] In some examples of the present disclosure, the captured image is recorded as The corresponding target uncollected images include Through the following formula Make an estimate:

[0057] in, Respectively represent the unsaturated images on the r1 and r2 levels, They represent the acquired images at the frequency offset ω1 on the r1 layer and at the frequency offset ω2 on the r2 layer, respectively. They represent the target images not collected at the frequency offset of ω2 on the r1 layer and at the frequency offset of ω1 on the r2 layer, respectively. They represent the relative saturation information at the ω2 frequency offset on the r1 level and at the ω1 frequency offset on the r2 level, respectively. They represent the average values ​​of the acquired images at the frequency offset ω1 on the r1 layer and at the frequency offset ω2 on the r2 layer, Represent the average values ​​of the unsaturated images on the r1 and r2 levels respectively.

[0058] Specifically, the target uncollected image is estimated by the spatial-frequency offset nearest neighbor estimation method. For two CEST MRI images on adjacent layers, if they have different saturation frequency offset information, the two CEST MRI images are expressed as:

[0059] in, All can be obtained through a single collection; They represent the relative saturation information at the ω1 frequency offset on the r1 level and at the ω2 frequency offset on the r2 level, respectively. They cannot be obtained directly and need to be obtained by the formula Calculated.

[0060] Ideally, if we want to obtain the image I at the saturation frequency offset ω2 on the r1 layer, r1,ω2 , can be calculated by the following formula:

[0061] However, in practice, a single acquisition of the traditional CEST sequence can only obtain an image at one saturation frequency offset (such as ω1), namely S r1,ω2 is unknown. Through the gradient editing sequence proposed in this disclosure, although the r1 layer still only collects the original image at the saturation frequency offset ω1, the adjacent r2 layer collects the original image at the saturation frequency offset ω2. Due to the spatial-spectral high-resolution characteristics of the proposed sequence, the anatomical information and metabolic information on adjacent layers have a relatively high similarity, that is, r1 and r2, ω1 and ω2 are relatively close, so the actual image not collected is It can be estimated by the following formula:

[0062] Similarly, the original image that was not collected can also be approximately estimated for the r2 layer

[0063] S4, performing interpolation and / or fitting based on the acquired image and the estimated target unacquired image to obtain a CEST or Z spectrum image with high spatial resolution and high spectrum sampling rate.

[0064] In some embodiments of the present disclosure, interpolation and / or fitting are performed based on the captured images and the estimated target uncaptured images, including: using the multi-pool Bloch-McConnell equation for simulation, and obtaining multiple Z spectrum sample sets with different waveforms by changing the simulation parameters of each pool; performing singular value decomposition on the Z spectrum sample set, and selecting the right singular vectors corresponding to the first m larger singular values ​​to form a new singular vector matrix, where m is an integer greater than 2; determining all vectors z0 with incomplete saturation frequency deviation points based on the captured images and the estimated target uncaptured images, and for each z0, obtaining the complete frequency spectrum of the pixel point corresponding to the z0 based on the z0 and the new singular vector matrix.

[0065] Specifically, the fitting estimation adopts a partially separable model, as shown in Figure 5.

[0066] Referring to Figure 5, we first use the multi-pool Bloch-McConnell equation to perform simulations. By varying the simulation parameters of each pool, we obtain a large number of Z spectra with different waveforms. Each Z spectrum is a column, forming a two-dimensional matrix, namely the Z spectrum sample set D. We then perform singular value decomposition (SVD) on the Z spectrum sample set: D = U Σ V T

[0067] Among them, U, Σ, and V are all two-dimensional matrices. Each row in U represents the combination coefficient of each Z spectrum in the sample set D with respect to the basis matrix V; each column in V represents a different singular vector, that is, a basis that can characterize the shape of the Z spectrum; Σ is a diagonal matrix, and the elements on the diagonal are the singular values ​​corresponding to the right singular vectors in V, in descending order.

[0068] According to the size of the singular value in Σ, the right singular vectors corresponding to the first m (such as 3-5) largest singular values ​​are selected to form a new singular vector matrix V. At this time, for the one-dimensional vector z0 with incomplete saturation frequency deviation points, the coefficients x of each vector in V can be fitted by the following formula: x=(V0 T V0) -1 V0 T z0

[0069] Wherein, V0 represents the data of the main component V of the Z spectrum information at the existing saturation frequency deviation point.

[0070] As shown in Figure 5, the coefficient x obtained by fitting can be used to estimate the complete high-resolution spectrum information: z = Vx

[0071] Here, z represents the complete spectrum estimated for a particular pixel. Repeating the above fitting process for all pixels in three-dimensional space yields a high-resolution spatial-spectral CEST MRI image of the entire brain, which is the full-acquisition image shown in Figure 5.

[0072] In some embodiments of the present disclosure, the three-dimensional CEST or Z spectrum magnetic resonance imaging method based on variable saturation gradient also includes: post-processing the obtained high spatial resolution, high spectral sampling rate CEST or Z spectrum image, wherein the post-processing method includes magnetization transfer rate asymmetry processing, Lorentz difference and multi-pool Lorentz processing.

[0073] Specifically, as shown in Figure 6, taking the whole brain as an example, the reconstructed whole-brain high-resolution CEST MRI image is post-processed, including magnetization transfer ratio (MTR) asymmetry and Lorentz difference processing, to obtain a CEST weighted contrast map. Referring to Figure 6, the SSE CEST map obtained using the method disclosed herein (n acquisitions and post-processing) is comparable to the traditional CEST map obtained using traditional technology (using independent acquisition and interpolation technology) in terms of resolution and spectral sampling rate. In other words, the present disclosure can obtain CEST maps with high spatial resolution and high spectral sampling rate with fewer acquisitions.

[0074] In summary, the three-dimensional CEST or Z-spectrum magnetic resonance imaging method based on a variable saturation gradient according to the embodiments of the present disclosure has the following advantages and beneficial effects:

[0075] First, acquisition speed is high. By designing an RW acquisition trajectory based on a variable saturation gradient, both r-direction spatial encoding and saturation frequency offset encoding are simultaneously performed and effectively separated. This method avoids separate saturation marking and acquisition for each frequency offset. Compared to traditional frequency offset-by-frequency offset CEST acquisition sequences, acquisition speed can be increased by more than 30 times at the same frequency offset sampling rate.

[0076] Second, it simultaneously achieves high spatial resolution and high spectral sampling rate. The solution proposed in this paper leverages redundant information and prior knowledge in both spatial and spectral dimensions. Combining a variable saturation gradient-based RW acquisition trajectory with a CEST Z-spectral line shape simulation model, it reconstructs metabolic scans of whole organs, such as the brain and liver, with high spatial resolution and high Z-spectral sampling rate. This revolutionizes the application scenarios and accuracy of CEST, minimizing the impact of motion and field inhomogeneity.

[0077] Third, it offers high flexibility. The variable saturation gradient acquisition sequence encompassed by this disclosure can be designed and optimized for different application scenarios and target metabolites, including radial, parallel, and cross-shaped acquisition trajectories. This enables CEST magnetic resonance imaging and analysis of various metabolic components in the human body, including proteins, lipids, glucose, creatine, and salicylic acid.

[0078] Fourth, it is highly scalable. The method proposed in this disclosure is not limited to brain CEST scanning under 3T magnetic resonance, but can also be applied to various parts of the body, including but not limited to abdominal organs, chest organs, muscles, and magnetic resonance imaging equipment of different field strengths (1.5T, 3T, 5T, 7T, 9.4T, 11.7T). The acquisition sequence based on variable saturation gradient encoding can be used as an independent CEST labeling module, combined with the existing multi-channel parallel acquisition, compressed sensing and deep learning-based water signal reading and reconstruction module to further improve the acquisition speed, which is particularly suitable for CEST metabolic imaging of motor organs such as the heart and liver.

[0079] FIG7 is a structural block diagram of an electronic device according to an embodiment of the present disclosure.

[0080] As shown in Figure 7, electronic device 500 includes: a processor 501 and a memory 503. The processor 501 and the memory 503 are connected, for example, via a bus 502. Optionally, electronic device 500 may further include a transceiver 504. It should be noted that in actual applications, the number of transceivers 504 is not limited to one, and the structure of electronic device 500 does not constitute a limitation on the embodiments of the present disclosure.

[0081] The processor 501 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It may implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the present disclosure. The processor 501 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, and the like.

[0082] Bus 502 may include a path for transmitting information between the aforementioned components. Bus 502 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, for example. Bus 502 may be divided into an address bus, a data bus, a control bus, and so on. For ease of illustration, FIG7 shows only one thick line, but this does not mean that there is only one bus or only one type of bus.

[0083] Memory 503 is used to store a computer program corresponding to the three-dimensional CEST magnetic resonance imaging method based on a variable saturation gradient according to the above-described embodiment of the present disclosure. The computer program is controlled and executed by processor 501. Processor 501 is used to execute the computer program stored in memory 503 to implement the contents of the above-described method embodiment.

[0084] The electronic device 500 includes, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), and in-vehicle terminals (e.g., in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. The electronic device 500 shown in FIG7 is merely an example and should not limit the functionality and scope of use of the embodiments of the present disclosure.

[0085] It should be noted that the logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, apparatus, or device and execute the instructions), or in conjunction with such instruction execution systems, apparatuses, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transmit a program for use by an instruction execution system, apparatus, or device, or in conjunction with such instruction execution systems, apparatuses, or devices. More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection portion having one or more wires (electronic device), a portable computer disk cartridge (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disc read-only memory (CDROM). Furthermore, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or otherwise processing it in a suitable manner if necessary, and then storing it in a computer memory.

[0086] It should be understood that various parts of the present disclosure can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used to implement: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0087] Throughout this specification, reference to terms such as "one embodiment," "some embodiments," "examples," "specific examples," or "some examples" means that a specific feature, structure, material, or characteristic described in conjunction with that embodiment or example is included in at least one embodiment or example of the present disclosure. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0088] In the description of the present disclosure, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise", "axial", "radial", "circumferential" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present disclosure and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation to the present disclosure.

[0089] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features being referred to. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. Throughout the present disclosure, "plurality" means at least two, such as two, three, etc., unless otherwise specifically defined.

[0090] In this disclosure, unless otherwise expressly specified or limited, terms such as "installed," "connected," "connect," and "fixed" should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integration; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; and internal communication between two components or interaction between two components, unless otherwise expressly limited. Those skilled in the art will understand the specific meanings of the above terms in this disclosure based on specific circumstances.

[0091] In the present disclosure, unless otherwise expressly specified or limited, when a first feature is "above" or "below" a second feature, it may mean that the first and second features are in direct contact, or the first and second features are in indirect contact through an intermediate medium. Furthermore, when a first feature is "above," "above," or "above" a second feature, it may mean that the first feature is directly above or diagonally above the second feature, or simply means that the first feature is at a higher level than the second feature. When a first feature is "below," "below," or "below" a second feature, it may mean that the first feature is directly below or diagonally below the second feature, or simply means that the first feature is at a lower level than the second feature.

[0092] Although the embodiments of the present disclosure have been shown and described above, it is understood that the above embodiments are illustrative and are not to be construed as limitations on the present disclosure. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present disclosure.

Claims

1. A three-dimensional CEST or Z-spectrum magnetic resonance imaging method based on variable saturation gradient, characterized in that: include: While applying a saturation pulse to the target object, turn on the gradient in the r direction, read out a set of original images, repeat the above process n times to obtain n sets of original images, wherein the center frequency and gradient value of the saturation pulse applied each time are different, r represents the spatial position, including at least one of the x, y, and z directions, and n is an integer greater than 1; Filling the n groups of original images onto the r-Δω plane, where Δω represents a frequency offset; Determine the target uncollected image according to the collected image in the r-Δω plane, and estimate the target uncollected image; Interpolation and / or fitting are performed based on the acquired images and the estimated target unacquired images to obtain a CEST or Z spectrum image with high spatial resolution and high spectrum sampling rate.

2. The three-dimensional CEST or Z-spectrum magnetic resonance imaging method based on variable saturation gradient according to claim 1, characterized in that: The n groups of original images are filled onto the r-Δω plane using the following formula: Δω(r)=Δω0+γG offset Δr Among them, Δω(r) represents the frequency offset corresponding to the r direction, Δr represents the distance between the imaging position corresponding to the r direction and the magnetic field zero point, γ represents the gyromagnetic ratio, Δω0 represents the frequency offset between the saturation pulse frequency and the water hydrogen proton, G offset represents the gradient in the r direction that is turned on simultaneously during the application of the saturation pulse.

3. The three-dimensional CEST or Z-spectrum magnetic resonance imaging method based on variable saturation gradient according to claim 1 or 2, characterized in that: The target uncollected images include uncollected images at adjacent layers and adjacent saturation frequency offsets to the collected images in the r-Δω plane.

4. The three-dimensional CEST or Z-spectrum magnetic resonance imaging method based on variable saturation gradient according to any one of claims 1 to 3, characterized in that: The collected image is recorded as The corresponding target uncollected images include Through the following formula Make an estimate: in, Respectively represent the unsaturated images on the r1 and r2 levels, Respectively The acquired images at the frequency offset ω1 on the r1 plane and at the frequency offset ω2 on the r2 plane, They represent that the target at the frequency offset of ω2 on the r1 level and at the frequency offset of ω1 on the r2 level has not acquired an image. They represent the relative saturation information at the ω2 frequency offset on the r1 level and at the ω1 frequency offset on the r2 level, respectively. They represent the average values ​​of the acquired images at the frequency offset ω1 on the r1 plane and at the frequency offset ω2 on the r2 plane, respectively. Represent the average values ​​of the unsaturated images on the r1 and r2 levels respectively.

5. The three-dimensional CEST or Z-spectrum magnetic resonance imaging method based on variable saturation gradient according to any one of claims 1 to 4, characterized in that: Interpolation and / or fitting are performed based on the acquired images and the estimated target unacquired images, including: The multi-cell Bloch-McConnell equation is used for simulation, and multiple Z-spectrum sample sets with different waveforms are obtained by changing the simulation parameters of each cell; Perform singular value decomposition on the Z spectrum sample set, and select the right singular vectors corresponding to the first m larger singular values ​​to form a new singular vector matrix, where m is an integer greater than 2; According to the acquired image and the estimated target unacquired image, all incomplete vectors z0 of saturation frequency deviation points are determined, and for each z0, the complete frequency spectrum of the pixel points corresponding to the z0 is obtained according to the z0 and the new singular vector matrix.

6. The three-dimensional CEST or Z-spectrum magnetic resonance imaging method based on variable saturation gradient according to any one of claims 1 to 5, characterized in that: The value of the gradient includes at least 0.

7. The three-dimensional CEST or Z-spectrum magnetic resonance imaging method based on variable saturation gradient according to any one of claims 1 to 6, characterized in that: Fast spin echo, gradient echo and planar echo are used to acquire n groups of original images corresponding to n levels.

8. The three-dimensional CEST or Z-spectrum magnetic resonance imaging method based on variable saturation gradient according to any one of claims 1 to 7, characterized in that: The n groups of original images corresponding to the n levels acquired are radial, parallel or cross-shaped on the r-Δω plane.

9. The three-dimensional CEST or Z-spectrum magnetic resonance imaging method based on variable saturation gradient according to any one of claims 1 to 8, characterized in that: The method also includes: The obtained CEST or Z spectrum images with high spatial resolution and high spectrum sampling rate are post-processed, wherein the post-processing methods include magnetization transfer rate asymmetric processing, Lorentz difference and multi-cell Lorentz processing.

10. An electronic device comprising a memory, a processor and a computer program stored in the memory, characterized in that: When the computer program is executed by a processor, the three-dimensional CEST or Z-spectrum magnetic resonance imaging method based on variable saturation gradient as described in any one of claims 1 to 9 is implemented.

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