Variable saturation gradient-based three-dimensional cest or z-spectrum magnetic resonance imaging method and apparatus

Abstract

The application discloses a three-dimensional CEST or Z spectrum magnetic resonance imaging method and electronic equipment based on a variable saturation gradient, and the method comprises the following steps: opening a gradient in the r direction while applying a saturation pulse to a target object, reading an original image, and repeating the above process n times to obtain n groups of original images; filling the n groups of original images on an r-Delta omega plane; determining a target uncollected image according to the collected images in the r-Delta omega plane, and estimating the target uncollected image; performing interpolation and / or fitting based on the collected images and the estimated target uncollected image to obtain a CEST or Z spectrum image with high spatial resolution and high frequency spectrum sampling rate. The method has strong flexibility and scalability, and is convenient for parallel imaging and combined use of under-sampling technologies such as compression sensing, and the acceleration multiple can reach dozens of times or even hundreds of times, which will revolutionarily promote CEST or Z spectrum imaging of micro lesions, moving organs and dynamic enhancement of contrast agents, and realize accurate detection of CEST signals in a living body in a noninvasive manner.

Description

Technical Field

[0001] This invention relates to the field of magnetic resonance imaging technology, and in particular to a three-dimensional CEST magnetic resonance imaging method based on a variable saturation gradient and an electronic device. Background Technology

[0002] Chemical Exchange Saturation Transfer (CEST) Magnetic Resonance Imaging (MRI) is an emerging molecular imaging technique that can be used for metabolic detection and pH monitoring in diseases such as cancer, tumors, and stroke.

[0003] Because the hydrogen proton frequencies in substances such as proteins, glucose, creatine, and salicylic acid analogs in the human body differ from the resonance frequencies of hydrogen protons in water molecules, and because the magnetization vectors of hydrogen protons in these substances can exchange with those in water, a specific frequency of saturated radio frequency pulses can be applied to human tissues to saturate the hydrogen protons in these chemical substances. This exchange effect then influences the water signal intensity, and 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 under different frequency saturated pulses, followed by Z-spectrum analysis to study chemical exchange information at specific frequency shifts. By analyzing the Z-spectrum, the desired CEST signal can be extracted.

[0004] However, CEST MRI faces the problem of long scan times because it requires sequentially acquiring images of multiple saturation frequencies at the same anatomical structure, and the saturation pulses lasting several seconds need to be repeated continuously. Conventional CEST sequences typically sacrifice the number of saturation frequency points and spatial resolution to keep the scan time within a clinically acceptable range. How to simultaneously achieve rapid imaging with high spatial resolution and high spectral sampling rate has always been a research hotspot in the field of CEST MRI.

[0005] In recent years, a series of technologies have emerged to address the issues of long CEST MRI scan times and limited spatial-spectral sampling rates. Regarding acquisition sequences, fast readout modules or steady-state CEST sequences can achieve whole-brain scanning. However, each saturation frequency offset requires at least one repetition time (TR), and each TR requires 4-6 seconds to ensure sufficient saturation duration and longitudinal relaxation recovery. Therefore, it is difficult to acquire CEST data that balances spatial resolution and spectral sampling rate in practice. To further improve acquisition efficiency, a saturation gradient coding technique has been proposed. This technique achieves simultaneous acquisition of multiple saturation frequencies by simultaneously activating the slice-selective directional gradient during the application of a saturation pulse, resulting in an intra-slice-coded ultrafast Z-spectral imaging sequence. However, because this technique performs Z-spectrum 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 homogeneous tissues between sublayers. Furthermore, due to the thin layer thickness (100μm), each sublayer is limited by the signal-to-noise ratio, resulting in low intra-layer resolution (5×5mm-8mm), thus restricting its further application. Regarding reconstruction techniques, some methods, such as parallel imaging, compressed sensing, and deep learning, can recover complete CEST images from undersampled data, thereby accelerating CEST imaging. However, the drawback is that reconstruction after undersampling usually sacrifices image quality, which is detrimental to subsequent quantitative CEST analysis. Summary of the Invention

[0006] This invention aims to at least partially solve one of the technical problems in related technologies. Therefore, the objective of this invention is to propose a three-dimensional CEST or Z-spectrum magnetic resonance imaging method and electronic device 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.

[0007] To address the aforementioned technical problems, a first aspect of this invention 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 simultaneously opening a gradient in the r-direction, reading out the original image, repeating the above process n times to obtain n sets of original images, wherein the center frequency of the applied saturation pulse and the gradient value are different each time, 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 sets of original images onto the r-Δω plane, wherein Δω represents the frequency offset; determining the unacquired image of the target based on the acquired images in the r-Δω plane, and estimating the unacquired image of the target; performing interpolation and / or fitting based on the acquired images and the estimated unacquired image of the target to obtain a CEST or Z-spectrum image with high spatial resolution and high spectral sampling rate.

[0008] The three-dimensional CEST or Z-spectrum magnetic resonance imaging method based on variable saturation gradient of this invention first applies a saturation pulse to the target object while simultaneously opening the gradient in the r-direction, reads out the original image, and repeats this process n times to obtain n sets of original images. Then, the n sets of original images are filled onto the r-Δω plane. Based on the acquired images in the r-Δω plane, the unacquired images of the target are determined and estimated. Finally, interpolation and / or fitting are performed based on the acquired images and the estimated unacquired images to obtain CEST-Z-spectrum images 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, which helps improve the accuracy of CEST quantitative analysis and disease diagnosis, has significant clinical value, and is highly flexible and scalable.

[0009] In addition, the three-dimensional CEST or Z-spectrum magnetic resonance imaging method based on variable saturation gradient in the embodiments of the present invention may also have the following additional technical features:

[0010] According to an embodiment of the present invention, the n sets of original images are filled onto the r-Δω plane using the following formula:

[0011] Δω(r)=Δω0+γG offsry Δr

[0012] Where Δω(r) represents the frequency shift in the r direction, Δr represents the distance between the imaging position in the r direction and the zero point of the magnetic field, γ represents the gyromagnetic ratio, Δω0 represents the frequency shift between the saturation pulse frequency and the water hydrogen proton frequency, and G offset This represents the gradient in the r direction that is simultaneously activated during the application of the saturation pulse.

[0013] According to one embodiment of the present invention, the target unacquired image includes unacquired images in the r-Δω plane on adjacent layers of the acquired image and adjacent to the saturation frequency offset.

[0014] According to one embodiment of the present invention, the acquired image is denoted as... The corresponding target uncaptured images include The following formulas are used to respectively... Make an estimate:

[0015]

[0016]

[0017] in, These represent unsaturated images at the r1 and r2 levels, respectively. These represent the acquired images at frequency offset ω1 on the r1 plane and at frequency offset ω2 on the r2 plane, respectively. These represent the uncaptured images of the target at frequency offset ω2 on the r1 plane and at frequency offset ω1 on the r2 plane, respectively. These represent the relative saturation information at frequency offset ω2 at the r1 level and at frequency offset ω1 at the r2 level, respectively. These represent the average values ​​of the acquired images at frequency offset ω1 on the r1 plane and at frequency offset ω2 on the r2 plane, respectively. These represent the average values ​​of the unsaturated images at the r1 and r2 levels, respectively.

[0018] According to one embodiment of the present invention, interpolation and / or fitting based on acquired images and estimated target unacquired images includes: performing simulation using the multi-pool Bloch-McConnell equation, and obtaining multiple Z-spectrum sample sets with different waveforms by varying the simulation parameters of each pool; performing singular value decomposition on the Z-spectrum sample sets, 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 offset points based on the acquired images and estimated target unacquired images, and for each z0, obtaining the complete spectrum of the pixel point corresponding to z0 based on z0 and the new singular vector matrix.

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

[0020] According to one embodiment of the present invention, n sets of original images corresponding to n layers are acquired by means of fast spin echo, gradient echo, and planar echo.

[0021] According to one embodiment of the present invention, the n sets of original images corresponding to the n layers are arranged radially, parallelly, or intersectingly on the r-Δω plane.

[0022] According to an embodiment of the present invention, 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 methods include magnetization transfer rate asymmetry processing, Lorentz difference, and multi-pool Lorentz processing.

[0023] To address the aforementioned technical problems, a second aspect of the present invention provides 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, it implements the three-dimensional CEST magnetic resonance imaging method based on variable saturation gradient described in the above embodiment.

[0024] The electronic device of this invention executes the computer program corresponding to the three-dimensional CEST or Z-spectrum magnetic resonance imaging method based on the variable saturation gradient of the above embodiments stored in the memory through the processor. It can quickly obtain CEST magnetic resonance images with high spatial resolution, high spectral sampling rate and strong interpretability, 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 invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0026] Figure 1 This 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 invention;

[0027] Figure 2(a) is a schematic diagram of the acquisition sequence of an example acquisition scheme of the present invention;

[0028] Figure 2(b) shows the original image obtained 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) being filled onto the r-Δω plane;

[0030] Figure 2(d) is a schematic diagram of the frequency offset points of the original image shown in Figure 2(b);

[0031] Figure 3 This is a schematic diagram of the original image being filled onto the r-Δω plane in some examples of the present invention;

[0032] Figure 4 This is a schematic diagram of the nearest neighbor estimation process according to an embodiment of the present invention;

[0033] Figure 5 This is a schematic diagram of the fitting estimation process according to an embodiment of the present invention;

[0034] Figure 6 This is a post-processed effect diagram of one embodiment of the present invention;

[0035] Figure 7 This is a structural block diagram of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0036] Embodiments of the present invention are described in detail below. Examples of these embodiments are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

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

[0038] Figure 1 This 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 invention.

[0039] like Figure 1 As shown, three-dimensional CEST or Z-spectrum magnetic resonance imaging methods based on variable saturation gradients include:

[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. Repeat the above process n times to obtain n sets of original images. The center frequency of the applied saturation pulse and the gradient value are different each time. 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 embodiments of the present invention, the target object can be any object that can be imaged by magnetic resonance CEST, such as a patient's brain, abdominal organs, chest organs, muscles, etc.

[0042] In some examples of this invention, n is less than 10, the frequency of the saturation pulse is in the range of -15ppm to 15ppm, and the gradient value includes at least 0, for example, it can be -1G. offset ~1G offset Values ​​can be taken within a range.

[0043] Figure 2(a) illustrates a scheme for acquiring high spatial resolution CEST-MRI images based on spatial-frequency coding, in which n = 9 and the gradient value G offset The saturation pulse frequency (ppm) changed 9 times, and the frequency changed 9 times accordingly, with the specific value being 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 radio frequency pulse, Gs represents direction selection gradient, Gp represents phase encoding gradient, and Gf represents frequency encoding gradient / readout gradient. The applied saturation pulse and the gradient in the r direction can be any designed value.

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

[0046] Specifically, referring to Figure 2(a), the acquisition sequence is characterized by applying a CEST saturation frequency while simultaneously activating a variable gradient in the selected layer direction. This allows hydrogen protons in different anatomical layers along the r direction to precess at different frequencies, resulting in a frequency shift from the inherent frequency of the saturation pulse that varies with the layer position. The relationship between this frequency shift and the layer position is as follows:

[0047] Δω(r)=Δω0+γG offset Δr

[0048] Where Δω(r) represents the frequency shift in the r direction, Δr represents the distance between the imaging position in the r direction and the zero point of the magnetic field, γ represents the gyromagnetic ratio, Δω0 represents the frequency shift between the saturation pulse frequency and the water hydrogen proton frequency, and G offset This represents the gradient in the r direction that is simultaneously activated during the application of the saturation pulse.

[0049] After the aforementioned spatial-frequency encoding process, the actual saturation frequencies in different spatial directions vary linearly with the spatial location of the selected slice direction. The acquired CEST MRI data includes the full spatial location of the target object and multiple saturation frequency offsets. By adjusting the gradient G... offset By determining the magnitude and natural frequency of the saturation pulse, any straight line can be sampled on the r-Δω plane. This allows for the acquisition of high-resolution CEST data across the entire space-spectrum, which would otherwise require at least 200 samplings, in fewer than 10 samplings (e.g., 9 samplings), thus improving data acquisition efficiency.

[0050] In this embodiment, n sets of original images corresponding to n layers can be acquired using methods such as fast spin echo, gradient echo, and planar echo, but not limited to these.

[0051] Figure 2(b) shows the raw images acquired using the acquisition scheme shown in Figure 2(a), containing nine sets of whole-brain high spatial resolution CEST MRI images.

[0052] Figure 2(c) shows a schematic diagram of filling the r-Δω plane with the acquired high-resolution raw images of the whole brain shown in Figure 2(b). For the acquisition scheme shown in Figure 2(a), the acquired raw images are radially arranged on the r-Δω plane.

[0053] It should be noted that the n sets of raw CEST magnetic resonance images corresponding to the n layers acquired can appear not only radially, but also parallelly, intersectingly, etc., in the r-Δω plane, such as... Figure 3 As shown, the specific shape can be determined based on the applied saturation pulse frequency and the variable saturation gradient.

[0054] Figure 2(d) shows that in the acquired original image, each layer in the r direction actually acquired n saturation frequency offset points, corresponding to n saturation frequency offset points on the Z spectrum. For the specific acquisition scheme shown in Figure 2(a), each layer in the r direction actually acquired 9 saturation frequency offset points.

[0055] S3, determine the unacquired image of the target based on the acquired image in the r-Δω plane, and estimate the unacquired image of the target.

[0056] The unacquired target images may include unacquired images on adjacent planes and adjacent saturation frequency offsets in the r-Δω plane.

[0057] In some examples of this invention, the acquired image is denoted as... The corresponding target uncaptured images include The following formulas are used to respectively... Make an estimate:

[0058]

[0059]

[0060] in, These represent unsaturated images at the r1 and r2 levels, respectively. These represent the acquired images at frequency offset ω1 on the r1 plane and at frequency offset ω2 on the r2 plane, respectively. These represent the uncaptured images of the target at frequency offset ω2 on the r1 plane and at frequency offset ω1 on the r2 plane, respectively. These represent the relative saturation information at frequency offset ω2 at the r1 level and at frequency offset ω1 at the r2 level, respectively. These represent the average values ​​of the acquired images at frequency offset ω1 on the r1 plane and at frequency offset ω2 on the r2 plane, respectively. These represent the average values ​​of the unsaturated images at the r1 and r2 levels, respectively.

[0061] Specifically, the unacquired image of the target is estimated using the spatial-frequency offset nearest neighbor estimation method. For two CEST MRI images on adjacent slices, if they have different saturation frequency offset information, the two CEST MRI images are represented as follows:

[0062]

[0063]

[0064] in, All of these can be obtained through a single data collection. These represent the relative saturation information at frequency offset ω1 at the r1 level and at frequency offset ω2 at the r2 level, respectively. This information cannot be obtained directly and requires formulas. Calculated.

[0065] Ideally, if we want to obtain the image I at the saturation frequency offset ω2 on the r1 level... r1,ω2 It can be calculated using the following formula:

[0066]

[0067] However, in practice, a single acquisition of a traditional CEST sequence can only obtain an image at a single saturation frequency offset (such as ω1), i.e., S. r1,ω2 It is unknown. Using the gradient editing sequence proposed in this invention, although only the original image at the saturation frequency offset ω1 was acquired at level r1, the original image at the saturation frequency offset ω2 was acquired at the adjacent level r2. Due to the high spatial-spectral resolution of the proposed sequence, the anatomical and metabolic information at adjacent levels has high similarity; that is, r1 and r2, ω1 and ω2 are quite close. Therefore, the actual unacquired image... The following formula can be used to estimate:

[0068]

[0069] Similarly, the uncollected original image can also be approximately estimated at the r2 level.

[0070]

[0071] S4. Based on the acquired images and the estimated unacquired images of the target, interpolation and / or fitting are performed to obtain CEST or Z-spectrum images with high spatial resolution and high spectral sampling rate.

[0072] In some embodiments of the present invention, interpolation and / or fitting based on the acquired images and the estimated target unacquired images include: performing simulation using the multi-pool Bloch-McConnell equation, and obtaining multiple Z-spectrum sample sets with different waveforms by varying the simulation parameters of each pool; performing singular value decomposition on the Z-spectrum sample sets, 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 offset points based on the acquired images and the estimated target unacquired images, and for each z0, obtaining the complete spectrum of the pixel point corresponding to z0 based on z0 and the new singular vector matrix.

[0073] Specifically, the fitting estimate uses a partially separable model, such as... Figure 5 As shown.

[0074] See Figure 5 First, simulations were performed using the multi-pool Bloch-McConnell equation. By varying the simulation parameters of each pool, a large number of Z-spectrums with different waveforms were obtained. Each Z-spectrum was then used as a column to form a two-dimensional matrix, i.e., the Z-spectrum sample set D. Singular Value Decomposition (SVD) was then performed on this Z-spectrum sample set.

[0075] D=U·Σ·V T

[0076] In this matrix, 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, which 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.

[0077] Based on the magnitude of the singular values ​​in Σ, select the right singular vectors corresponding to the first m (e.g., 3-5) largest singular values ​​to form a new singular vector matrix V. Then, for a one-dimensional vector z0 with incomplete saturation frequency offset points, the coefficients x of each vector in V can be fitted using the following formula:

[0078] x=(V0 T V0) -1 V0 T z0

[0079] Where V0 represents the data of the main component V of the Z-spectrum information at the existing saturation frequency offset point.

[0080] See Figure 5 By fitting the coefficients x, high-resolution complete spectral information can be estimated:

[0081] z = Vx

[0082] Here, z represents the complete spectrum obtained after estimating a specific pixel. Repeating the above fitting process for all pixels in three-dimensional space yields a high-resolution CEST MRI image of the whole brain, i.e., Figure 5 Full-sampled images in the image.

[0083] In some embodiments of the present invention, the three-dimensional CEST or Z-spectrum magnetic resonance imaging method based on variable saturation gradient further includes: post-processing the obtained high spatial resolution and high spectral sampling rate CEST or Z-spectrum image, wherein the post-processing methods include magnetization transfer rate asymmetry processing, Lorentz difference, and multi-pool Lorentz processing.

[0084] Specifically, such as Figure 6 As shown, taking the whole brain as an example, post-processing was performed on the reconstructed high-resolution CEST MRI images of the whole brain, including processing for magnetization transfer ratio (MTR) asymmetry and Lorentz difference, to obtain a CEST weighted contrast map. See [link to documentation]. Figure 6 The SSE CEST image obtained using the method of this invention (after n acquisitions and processing) has comparable resolution and spectral sampling rate to the traditional CEST image obtained using traditional techniques (using independent acquisition and interpolation techniques). In other words, this invention can obtain a CEST image with high spatial resolution and high spectral sampling rate with fewer acquisitions.

[0085] In summary, the three-dimensional CEST or Z-spectrum magnetic resonance imaging method based on variable saturation gradient of the present invention has the following advantages and beneficial effects:

[0086] First, the acquisition speed is fast. By designing an rw acquisition trajectory based on a variable saturation gradient, both r-direction spatial encoding and saturation frequency offset encoding are performed simultaneously and effectively separated. This method avoids separate saturation marking and acquisition for each frequency offset, achieving an acquisition speedup of more than thirty times compared to traditional frequency offset-by-frequency CEST acquisition sequences under the same frequency offset sampling rate.

[0087] Second, it simultaneously achieves high spatial resolution and high spectral sampling rate. The solution proposed in this invention utilizes redundant information and prior knowledge in both spatial and spectral dimensions. It further combines the rw acquisition trajectory based on variable saturation gradient with the CEST Z-spectral line shape simulation model, enabling the reconstruction of metabolic scans of the whole brain, whole liver, and other organs with high spatial resolution and high Z-spectral sampling rate. This revolutionarily enhances the application scenarios and accuracy of CEST, making it less affected by motion and field inhomogeneity.

[0088] Third, it offers high flexibility. The variable saturation gradient acquisition sequence included in this invention can be designed and optimized with different rw acquisition trajectories, such as radial, parallel, and intersecting patterns, for different application scenarios and target metabolites, thereby enabling CEST magnetic resonance imaging and analysis of various metabolic components in the human body, including proteins, lipids, glucose, creatine, and salicylic acid.

[0089] Fourth, it has strong scalability. The method proposed in this invention is not limited to CEST scanning of the brain under 3T MRI, but can also be applied to various locations throughout the body, including but not limited to abdominal organs, thoracic organs, and muscles, and to MRI equipment with different field strengths (1.5T, 3T, 5T, 7T, 9.4T, 11.7T). The acquisition sequence based on variable saturation gradient coding can be used as an independent CEST marker module, combined with existing multi-channel parallel acquisition, water signal reading and reconstruction modules based on compressed sensing and deep learning, to further improve the acquisition speed, and is especially suitable for CEST metabolic imaging of musculoskeletal organs such as the heart and liver.

[0090] Figure 7 This is a structural block diagram of an electronic device according to an embodiment of the present invention.

[0091] like Figure 7 As shown, the 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, the electronic device 500 may also include a transceiver 504. It should be noted that in practical applications, the transceiver 504 is not limited to one type, and the structure of this electronic device 500 does not constitute a limitation on the embodiments of the present invention.

[0092] 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 can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this invention. Processor 501 may also be a combination that implements computational functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0093] Bus 502 may include a pathway 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, etc. Bus 502 can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 7 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0094] The memory 503 stores a computer program corresponding to the three-dimensional CEST magnetic resonance imaging method based on variable saturation gradient according to the above embodiments of the present invention. This computer program is executed under the control of the processor 501. The processor 501 executes the computer program stored in the memory 503 to implement the content shown in the aforementioned method embodiments.

[0095] Among them, electronic devices 500 include, but are not limited to: mobile terminals such as mobile phones, laptops, digital radio receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), and in-vehicle terminals (such as in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. Figure 7 The electronic device 500 shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0096] It should be noted that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which programs can be printed, because programs can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0097] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0098] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions 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 one or more embodiments or examples.

[0099] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," "counterclockwise," "axial," "radial," and "circumferential" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this invention and simplifying the description, and are not intended to indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0100] 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 indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0101] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components, unless otherwise explicitly limited. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0102] In this invention, unless otherwise explicitly specified and limited, "above" or "below" the second feature can mean that the first feature is in direct contact with the second feature, or that the first feature is in indirect contact with the second feature through an intermediate medium. Furthermore, "above," "over," and "on top" of the second feature can mean that the first feature is directly above or diagonally above the second feature, or simply that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature can mean that the first feature is directly below or diagonally below the second feature, or simply that the first feature is at a lower horizontal level than the second feature.

[0103] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A three-dimensional CEST or Z-spectrum magnetic resonance imaging method based on a variable saturation gradient, characterized in that, include: While applying a saturation pulse to the target object, the gradient in the r direction is turned on, and a set of original images is read out. The above process is repeated n times to obtain n sets of original images. The center frequency of the applied saturation pulse and the value of the gradient are different each time. r represents the spatial position, including at least one of the x, y, and z directions, and n is an integer greater than 1. Fill the n sets of original images into On a plane, among which, Indicates frequency offset; according to The acquired images in the plane determine the unacquired images of the target, and estimate the unacquired images of the target; Interpolation and / or fitting are performed based on the acquired images and the estimated unacquired images of the target to obtain CEST or Z-spectrum images with high spatial resolution and high spectral 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 sets of original images are filled into the following formula: On a plane: in, This indicates the frequency offset in the r direction. This represents the distance between the imaging position in the r direction and the zero point of the magnetic field. Indicates the gyromagnetic ratio, G represents the frequency shift of the saturation pulse relative to the frequency of the water hydrogen protons. offset This represents the gradient in the r direction that is simultaneously activated 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, characterized in that, Uncaptured images of the target include Unacquired images on adjacent planes and adjacent saturation frequency offsets of the acquired images.

4. The three-dimensional CEST or Z-spectrum magnetic resonance imaging method based on variable saturation gradient according to claim 1, characterized in that, Record the acquired images as , The corresponding uncaptured images of the target include , The following formulas are used to respectively , Make an estimate: in, , These represent unsaturated images at the r1 and r2 levels, respectively. , They represent the r1 level at the r1 level. At frequency offset, at the r2 level The acquired images at the frequency offset. , They represent the r1 level at the r1 level. At frequency offset, at the r2 level The target at the frequency offset was not captured in the image. , They represent the r1 level at the r1 level. At frequency offset, at the r2 level Relative saturation information at frequency offset , They represent the r1 level at the r1 level. At frequency offset, at the r2 level The average value of the acquired images at the frequency offset. , These represent the average values ​​of the unsaturated images at 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 claim 1, characterized in that, Interpolation and / or fitting based on acquired images and estimated unacquired images of the target include: Simulations were performed using the multi-pool Bloch-McConnell equation, and multiple Z-spectrum sample sets with different waveforms were obtained by varying the simulation parameters of each pool. 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; Based on the acquired images and the estimated unacquired images of the target, determine the vector z0 for all incomplete saturation frequency offset points, and for each z0, obtain the complete spectrum of the pixel corresponding to z0 based on 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 claim 1, characterized in that, The gradient can take values ​​of at least 0.

7. The three-dimensional CEST or Z-spectrum magnetic resonance imaging method based on variable saturation gradient according to claim 1, characterized in that, n sets of original images corresponding to n layers were acquired using fast spin echo, gradient echo, or planar echo methods.

8. 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 sets of original images corresponding to the n layers were acquired. On a plane, they can be arranged radially, parallelly, or intersectingly.

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

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