WO2023092319A1 - Magnetic resonance multi contrast-ratio parameter imaging method based on wave-type gradient - Google Patents

Abstract

A magnetic resonance multi contrast-ratio parameter imaging method based on a wave-type gradient. The method comprises: collecting a magnetic resonance imaging sequence, wherein the sequence includes two times of repetition (TR1, TR2) and two flip angles (α1, α2), and each time of repetition (TR1, TR2) includes a plurality of echoes; when a readout gradient is applied to the magnetic resonance imaging sequence, applying a cosine wave gradient (CO) sequence in the direction of a selected layer by using a magnetic resonance gradient field coil, and applying a sine wave gradient (SI) sequence in the direction of a phase, or applying the cosine wave gradient (CO) sequence in the direction of the phase, and applying the sine wave gradient (SI) sequence in the direction of the selected layer; and applying a wave-type gradient sequence to a gradient recalled echo imaging (GRE) sequence, performing under-sampling on a signal to obtain a multi-layer image, and then obtaining, on the basis of the multi-layer image, a parameter image having a plurality of contrast ratios. By means of the method, a parameter image having a plurality of contrast ratios is obtained by means of a single scan, thereby significantly shortening the scan time, and improving the definition of the generated image.

Description

An MRI Multi-contrast Parametric Imaging Method Based on Wave Gradient technical field

The invention relates to the technical field of medical image analysis, and more particularly, to a wave-like gradient-based magnetic resonance multi-contrast parameter imaging method.

Background technique

Magnetic resonance imaging (Magnetic Resonance Imaging, MRI) is to apply a specific frequency radio frequency pulse to the target in the static magnetic field, so that the hydrogen protons in the target are excited and magnetic resonance phenomenon occurs. After the application of radio frequency pulses is stopped, the protons in the target generate magnetic resonance MR signals during the relaxation process, and the usable MR signals can be obtained through the processing of the MR signal reception, spatial encoding and image reconstruction. Since each signal contains full-layer information during the magnetic resonance process, it is necessary to perform spatial positioning encoding on the magnetic resonance signal, namely frequency encoding and phase encoding. Specifically, because the MR signal collected by the receiving coil is actually a radio wave with space-encoded information, which is an analog signal, it needs to be transformed into digital information through analog-to-digital conversion, and then the digital information is filled into the k-space, and finally the corresponding Digital dot matrix. Among them, k-space is closely related to the spatial positioning of magnetic resonance signals. This k-space is also called Fourier space, which is the filling space of the original digital information of MR signals with spatial positioning coding information. Each MR image has its corresponding k-space data lattice. By Fourier transforming the k-space data, the spatial positioning coding information in the original digital data can be decoded, and different frequencies, phases and For the MR signal of the amplitude, different frequencies and phases represent different spatial positions, and the amplitude represents the MR signal intensity. The MR digital signals of different frequencies, phases and signal strengths are allocated to the corresponding pixels to obtain MR image data, that is, to reconstruct the MR image. Fourier transform is the process of transforming the original data lattice of k-space into MR image lattice.

In recent years, multi-contrast parametric MRI techniques have been extensively developed and explored. In principle, almost any signal preparation and acquisition strategy, such as longitudinal recovery, helical trajectory imaging, echo planar imaging (EPI), steady state free precession imaging (SSFP), gradient refocusing echo imaging (GRE), etc. Potentially used as a basis for developing multiparametric imaging methods. Specifically, GRE acquisition using a transverse signal destruction mechanism to collect incoherent steady-state (ISS) signals may have certain advantages, such as three-dimensional high-resolution imaging capabilities, high data acquisition efficiency, easy construction of signal models, and compatibility with Various imaging sequences and acceleration techniques.

On the other hand, the imaging speed of magnetic resonance imaging is slow, and the long scanning time will cause discomfort to the patient, and at the same time, it is easy to introduce motion artifacts in the image, thereby affecting the image quality. Magnetic resonance parallel imaging method is a kind of method to accelerate the scanning speed of MRI, such as simultaneous acquisition of spatial harmonics technology (SMASH, simultaneous acquisition of spatial harmonics), sensitivity encoding technology (SENSE, sensitivity encoding) and overall automatic calibration partial parallel acquisition technology ( GRAPPA, generalized autocalibrating partially parallel acquisitions), etc. This type of method achieves the purpose of fast scanning by reducing the amount of collected data and using the redundant information contained in the multi-channel coil to reconstruct the under-sampled data. In the prior art, parallel imaging has been used to speed up various MRI sequences with multiple receive coils, and some improvements exist to achieve higher acceleration factors, for example, simultaneous multislice (SMS) imaging, controlled Hybrid acceleration technology (CAIPIRINHA), beam spotting phase encoding technology (BPE), controlled aliasing technology in volume parallel imaging (2D CAIPIRINHA), controlled mixing acceleration technology in wave-like gradient in volume parallel imaging (Wave- CAIPI) and so on. These strategies have been successfully applied in echo-planar imaging, high-resolution functional and diffusion-weighted imaging, arterial spin labeling imaging (ASL), dynamic susceptibility contrast imaging and other applications.

However, in current clinical applications, in order to obtain multiple magnetic resonance images with different contrasts, multiple pulse sequences corresponding to multiple contrasts need to be applied, so the multi-contrast magnetic resonance parametric imaging technology in the prior art total scan Long time, high risk of patient discomfort and movement during scanning, multiple scans in multiple scan sequences are required, data acquisition efficiency is low, signal model building is complicated, and the geometric factor (g-factor) and artifacts are too large at high acceleration .

Contents of the invention

The purpose of the present invention is to overcome the above-mentioned defective of prior art, provide a kind of magnetic resonance multi-contrast parameter imaging method based on wave type gradient, to reduce the total scan time of the magnetic resonance parameter imaging of multi-contrast in clinical application, improve scanning process. Patient discomfort and risk of exercise.

The technical solution of the present invention is to provide a wave-like gradient-based magnetic resonance multi-contrast parameter imaging method, comprising the following steps: acquiring a magnetic resonance imaging sequence, the sequence includes double repetition time, double flip angle, and each repetition time includes A plurality of echoes; when applying a readout gradient to the magnetic resonance imaging sequence, the magnetic resonance gradient field coil is used to apply a cosine wave gradient sequence in the layer selection direction, and a sine wave gradient sequence is applied in the phase direction; or a cosine wave is applied in the phase direction A wave gradient sequence, applying a sinusoidal wave gradient sequence in the layer selection direction; applying the wave gradient sequence to a gradient refocusing echo imaging sequence, and under-sampling the signal to obtain a multi-layer image, and then based on the multi-layer image , to obtain parametric images of various contrasts.

Compared with the prior art, the present invention has the advantage that it can realize high-magnification accelerated scanning while reducing the geometric factor g-factor and avoiding the generation of artifacts; compared with the existing Wave-CAIPI technology, the imaging proposed by the present invention The method solves the problem that one scan of Wave-CAIPI technology can only produce a single contrast image, and can obtain multiple contrast parameter images in a single scan, and significantly shortens the scanning time of contrast parameter imaging.

Other features of the present invention and advantages thereof will become apparent from the following detailed description of exemplary embodiments of the present invention with reference to the accompanying drawings.

Description of drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention.

FIG. 1 is a schematic diagram of an MRI sequence acquisition scheme according to an embodiment of the present invention;

Fig. 2 is a schematic diagram of readout gradient RO, cosine wave gradient CO, sine wave gradient SI and sampling template in k-space in a magnetic resonance imaging sequence according to an embodiment of the present invention;

Fig. 3 is a schematic diagram of an image processing pipeline of a magnetic resonance imaging sequence according to an embodiment of the present invention;

Fig. 4 is a schematic diagram of a parametric image of a 4-fold accelerated multi-contrast obtained by one magnetic resonance imaging sequence scan according to an embodiment of the present invention.

Detailed ways

Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that the relative arrangements of components and steps, numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present invention unless specifically stated otherwise.

The following description of at least one exemplary embodiment is merely illustrative in nature and in no way taken as limiting the invention, its application or uses.

Techniques, methods and devices known to those of ordinary skill in the relevant art may not be discussed in detail, but where appropriate, such techniques, methods and devices should be considered part of the description.

In all examples shown and discussed herein, any specific values should be construed as exemplary only, and not as limitations. Therefore, other instances of the exemplary embodiment may have different values.

It should be noted that like numerals and letters denote like items in the following figures, therefore, once an item is defined in one figure, it does not require further discussion in subsequent figures.

The invention provides a magnetic resonance fast imaging method based on wave-like gradient and gradient refocusing echo imaging (GRE) sequence, the sequence adopts wave-like gradient, double TR (repetition time), double flip angle (FA) and multiple The wave design can be used for three-dimensional high-resolution multi-contrast MRI rapid parametric imaging, also known as WAMP imaging (Wave-CAIPI MULTIPLEX, WAMP for short).

The present invention is based on Wave-CAIPI technology (“Wave-CAIPI for highly accelerated 3D imaging”, Magn Reson Med, June 2015; 73(6):2152-62; Bilgic B, et al.) and MULTIPLEX (“MULTI- parametric MR imaging with fLEXible design (MULTIPLEX)", Magn Reson Med, 2021 August 31. doi:10.1002/mrm.28999; Ye Y, et al.) technology to achieve ultra-fast imaging method with multiple contrast parameters, which can realize a A solution for multi-contrast parametric images acquired in a single scan. In short, the technical solution of the present invention includes:

1) While acquiring signals in a three-dimensional magnetic resonance imaging sequence (while applying a readout gradient), the magnetic resonance gradient field coil is used to apply a cosine wave gradient sequence in the layer selection direction (or phase direction). At the same time, apply a sinusoidal wave gradient sequence in the phase direction (or layer selection direction);

2) Apply the above-mentioned wave-like gradient sequence to the GRE sequence, and perform under-sampling acceleration on the signal. Among them, the sampling template sampled in k-space along the phase encoding direction adopts regular undersampling;

3), applying the technical method described in step (1) and (2) to the three-dimensional WAMP sequence, and by constructing a signal model and image processing technology, obtaining parameter images of multiple contrasts, including B _1t image, T ₁ image, T ₂ image, T ₁ weighted (T ₁ W) image, enhanced T ₁ weighted T ₁ W (aT ₁ W) image, T ₂ weighted (T ₂ W) image, enhanced T ₂ weighted T ₂ W (aT ₂ W) images, T2* (T2*) images, proton density (PD) images, proton density-weighted (PDW) images, susceptibility-weighted imaging (SWI) images, and quantitative susceptibility mapping (QSM) images, and magnetic resonance angiography (MRA ) and other images.

1) Regarding MRI sequence design

Referring to Fig. 1, the WAMP imaging sequence has double repetition time (TR), double flip angle (FA) (including α ₁ and α ₂ ) and multi-echo design. The dual TR (comprising TR ₁ and TR ₂ ) features are derived from the actual flip angle imaging (AFI) technique for B ₁ t mapping. Acq ₁ (corresponding to the upper part of the acquisition process module in Figure 1, or called the first acquisition module) and Acq ₂ (corresponding to the lower part of the acquisition process module in Figure 1, or called the second acquisition module) each contain a (AFI) Technology similar dual TR unit. Within each TR (ie TR ₁ and TR ₂ ), a certain number (ie N ₁ and N ₂ ) of gradient echoes are acquired. Additionally, Flow Modulation (FM) blocks can be inserted flexibly. Each acquisition module (Acq) uses a different flip angle (eg α ₁ /α ₂ ), each TR module has a different number of echoes and/or a different FM function (including on/off status). Among them, there is a corresponding readout gradient RO in the frequency encoding direction at each echo (RO and Acq are triggered simultaneously), a cosine wave gradient CO is applied in the layer selection encoding direction (or phase direction), and a cosine wave gradient CO is applied in the phase encoding direction ( Or select layer encoding direction) apply sinusoidal wave gradient SI. In one embodiment, the gradient pulses of RO, CO, and SI in the WAMP imaging sequence, and the template sampled in k-space are under-sampled using the rule of every row and every column, as shown in Figure 2, where Figure 2(a) is the gradient Waveforms, Figure 2(b) is a sampling example, and Figure 2(c) is a k-space trajectory. For simplicity, the following discussion assumes α ₁ <α ₂ , N ₁ <N ₂ and TR ₁ <TR ₂ .

Still combined with what is shown in FIG. 1 , a WAMP sequence scan can generate 2 (N ₁ +N ₂ ) echo image sets. Additionally, a Flow Modulation (FM) block can be optionally inserted after each excitation pulse. The processing pipeline of the data image scanned by WAMP sequence is shown in Figure 3. For simplicity, take WAMP data images as an example divided into four layers (Tier-0, Tier-1, Tier-2, and Tier-3), depending on their calculation order and relationship in the processing pipeline, and adopt multi-dimensional integration (MDI) concept for high signal-to-noise ratio (SNR), high fidelity and efficient complex image processing. The Tire-0 layer image is collected data from each k-space through the Wave-CAIPI signal, using the linear equation of the SENSE model to solve, and obtains 2 (N ₁ +N ₂ ) groups of "original" echo images; the Tire-1 layer image is the 2(N ₁ +N ₂ ) sets of “raw” echo images reconstructed using Tire-0, and its complex signal is modeled. Magnitude images present various blends of PD images, _T1 and _T2 * weights, while phase images contain background field and susceptibility effects mainly as a function of TE; Tire-2 images are calculated based on Tire-1 images Composite PDW/T ₁ W/T ₂ *W (cPDW/cT ₁ W/cT ₂ W) image, B ₁ t image, T ₁ image, enhanced T ₁ W (aT ₁ W) image, T ₂ */R ₂ * images, PD images, SWI images, QSM images, MRA images, etc.; Tier-3 images are mainly calculated based on Tier-2 images, such as using advanced post-processing or virtual signal generation using the Bloch model. For example, cPDW image, cT1W image and QSM image can be used to calculate the real SWI (tSWI) image, with the help of T ₁ image, PD image and R ₂ * (or T ₂ *) image, can be used for inversion recovery (IR), Saturation Recovery (SR), Dual IR (DIR) or stabilized signal models to simulate images with virtual weighting effects, etc. With the design based on double TR, double FA and multi-echo GRE, and a dedicated image processing program combined with MDI and other advanced algorithms, WAMP provides multiple groups of qualitative images and multi-contrast parameter maps with high signal-to-noise ratio, quantitative accuracy and Acquisition/reconstruction efficiency. In addition, the WAMP signal acquisition design is also very flexible, and some additional comparison mechanisms can be added to meet wider application requirements.

2), image reconstruction model

Combined with Figure 3, the principle of WAMP is described in detail below, and the signal model of its k-space is expressed as:

The point spread function PSF satisfies:

Among them, m[x,y,z] is the image to be solved, t is the time, γ is the gyromagnetic ratio, k _x , _ky and k _z are the k-space coordinates, τ is the integration time variable, g _y (t) and _gz (t) are a pair of wave gradient fields out of phase by π/2 during readout. It can be known from the above formula that the effect of the wave-like gradient field can be expressed by Psf(t,y,z), which is a three-dimensional phase diagram that changes sinusoidally with time and changes linearly in the y and z directions respectively. The time t is linearly corresponding to the code k _x of the readout direction of k space, and Psf(t, y, z) can also be written as Psf[k _x , y, z] in discrete form. Perform Fourier transform of Psf[k _x ,y,z] in the y and z directions, that is, transform it into Psf[k _x , _ky ,k _z ], which can describe the offset of the wave trajectory relative to the Cartesian trajectory . The inverse Fourier transform of Psf[k _x ,y,z] in the readout direction is transformed into Psf[x,y,z], which can describe the diffusion effect of the wave gradient field in the readout direction.

Based on formula (1), it is extended to parallel acquisition of multi-channel coils, and the k-space undersampling in the phase encoding direction is considered, and the inverse Fourier transform is performed on both sides of the formula, and the signal encoding formula expressed in a matrix is written in discrete form:

wave[x,y,z]=Em[x,y,z](3)

Where E is the encoding matrix, and the E matrix needs to satisfy:

where S represents the coil sensitivity encoding, F _x represents the Fourier transform in the readout direction, and M represents the offset aliasing caused by the regular undersampling mode of every row and every column (as shown in Figure 2) in the phase coding direction. In fact, formulas (3) and (4) can be equivalently written as:

The above formula (5) is also equivalent to a convolution operation:

where Psf[x,y,z] is the inverse Fourier transform of Psf[k _x ,y,z] in the readout direction,

is the convolution operation in the readout direction. Equation (6) shows that the coding model is an extended SENSE model, and the image of the echo signal can be reconstructed by using a solution method similar to the SENSE model.

3), image signal processing process

After image reconstruction, for the image of multi-echo signal, image processing and generation will be carried out according to the physical effect of its magnetic resonance imaging. Assume that under flip angle α _i (i∈[1,2])), echo time TE _j (j∈[1, N ₁ ]) and TE(k∈[1, N ₂ ]), TR ₁ (ie The image signals of S ₁ ) and TR ₂ (ie S ₂ ) are respectively:

where _M0 is the baseline signal related to the proton density, Δω represents the off-resonance effect (both global and local), W _p and

are the modulus weight and phase components of the sensitivity curve _Cp of _the pth coil channel, respectively,

is a constant baseline phase. E ₁ and E ₂ represent

and

In the computational process of images, the concept of multidimensional integration (MDI) has been proposed for high signal-to-noise ratio (SNR), high fidelity, and efficient complex image processing. The working principle of MDI is: when defining a ratio or division operation, for example, calculating R≡B/A, the corresponding value can be obtained as

where L ₁ , L ₂ ... is the length of each feasible signal dimension, and a and b are single complex signal points from datasets A and B, as shown in equations (6) and (7). Using the MDI concept in the WAMP signal dimension, including FA(α), echo time (time of echo, referred to as TE), repetition time (time of repetition, referred to as TR) and receiver coil channel (coil, referred to as C ). On 2(N ₁ +N ₂ ) groups of directly collected and reconstructed images, the following results can be obtained through corresponding image processing methods:

1) Synthesized PDW and T ₁ W images (cPDW and cT ₁ W), for example, for cPDW, use the weighted average of all Acq ₁ images, and for cT ₁ W, use the weighted average of all Acq ₂ images .

2), B _1t mapped image: AFI is applied on the image of Acq ₂ 's TR ₁ and the first N ₁ echo of TR ₂ . The Acq ₁ image is not used because α ₁ is too small (set to PDW) for AFI to work properly.

3), the mapping image of T ₁ : assuming that both TR ₁ and TR ₂ << T ₁ , let k=TR ₁ /T ₁ and nk=TR ₂ /T ₁ , the analysis of k can be obtained from formulas (6) and (7 ), the form is ak ² +bk+c=0, so T ₁ =TR ₁ /k. With the B _1t map in step 2, a modified T ₁ map can be obtained.

4), T ₂ */R ₂ * image: apply the MDI method on the 2N ₂ echo images of the two Acq modules. In principle, any mapping method of T ₂ */R ₂ * can be used.

5) PD image: Putting the B _1t , T ₁ and T ₂ * maps into formulas (6) and (7), a separate PD image can be extracted from each echo and then averaged. The averaged PD map can then be spatially normalized to reduce spatial variation related to coil sensitivity.

6), Enhanced T ₁ W (aT ₁ W) map: defined as the signal ratio between T ₁ W and PDW signal, namely

to eliminate non- _T1 factors of pure _T1 weighting.

7) SWI image: generated by using the multi-echo SWI image method based on 2N ₂ sets of echo images of two Acq modules. In principle, any multi-echo SWI image method can be used.

8), QSM image: generated using the L ₂ -norm optimization method, regularized with dynamic streak artifacts. In principle, any QSM method can be used.

9), MRA image: Optionally insert a frequency modulation module to create dark blood (with flow blanking) and bright blood (with flow compensation) images, and generate high-contrast MRA images by subtraction.

10) Virtual image: Using the respective Block signal models and the calculated T ₁ /T ₂ */PD/QSM image, an image with any virtual contrast can be generated, such as inversion recovery (IR), dual IR, PSIR, True SWI (tSWI), etc.

In order to further verify the effect of the present invention, experiments were carried out. It has been verified that the present invention can realize rapid single-scan imaging, obtain three-dimensional high-resolution multi-contrast magnetic resonance parameter imaging under 4-9 times acceleration, and the voxel resolution can reach ≤1mm ³ , and the scan time can reach 1.1- 2.5 minutes. Figure 4 is a WAMP imaging sequence scan to obtain a 4 times accelerated multi-contrast parametric image, where Figure 4(A) is the Tier-2 layer image, including qualitative images and parameter maps, and Figure 4(B) is the Tier-3 layer Example images, including virtual IR and tSWI images. where the tSWI image is calculated using susceptibility generated from the QSM map, and also utilizes cPDW+cT ₁ W as its magnitude image.

In summary, the present invention combines Wave-CAIPI (a 3D imaging method that utilizes multi-channel coils and k-space helical trajectory sampling to accelerate magnetic resonance imaging) technology and MULTIPLEX technology for three-dimensional multi-contrast magnetic resonance parameter imaging sequences . MULTIPLEX technology can use the signal destruction mechanism to collect incoherent steady-state (ISS) signals, and can obtain three-dimensional high-resolution (for example, voxel size <1mm ³ ) imaging capabilities, improve data acquisition efficiency, easily build signal models, and can Compatible with various types of imaging sequences. The Wave-CAIPI technology can be used for high-acceleration three-dimensional imaging, and the loss of geometric factor (g-factor) and artifacts can be ignored at high acceleration. The method proposed by the invention is used for realizing three-dimensional multi-contrast magnetic resonance rapid parameter imaging with a single scan with high resolution, high signal-to-noise ratio, high accuracy, high efficiency and flexible acquisition. In the technical solution provided by the present invention, not only B _1t and T ₁ images can be generated simultaneously through a sequence of scans, but also T ₁ W images, proton density weighted (PDW) images, computationally enhanced T ₁ W (aT ₁ W ) images, susceptibility-weighted imaging (SWI) images, and optional qualitative MR angiography (MRA) images, as well as _T2 * ( _R2 *) images, PD (proton density) images, and quantitative susceptibility mapping (QSM) images etc.

The present invention can be a system, method and/or computer program product. A computer program product may include a computer readable storage medium having computer readable program instructions thereon for causing a processor to implement various aspects of the present invention.

A computer readable storage medium may be a tangible device that can retain and store instructions for use by an instruction execution device. A computer readable storage medium may be, for example, but is not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer diskettes, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), or flash memory), static random access memory (SRAM), compact disc read only memory (CD-ROM), digital versatile disc (DVD), memory stick, floppy disk, mechanically encoded device, such as a printer with instructions stored thereon A hole card or a raised structure in a groove, and any suitable combination of the above. As used herein, computer-readable storage media are not to be construed as transient signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., pulses of light through fiber optic cables), or transmitted electrical signals.

Computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to a respective computing/processing device, or downloaded to an external computer or external storage device over a network, such as the Internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and/or edge servers. A network adapter card or a network interface in each computing/processing device receives computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in each computing/processing device .

Computer program instructions for carrying out operations of the present invention may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or Source or object code written in any combination, including object-oriented programming languages—such as C++, Python, JAVE, Smalltalk, etc., and conventional procedural programming languages—such as the “C” language, Fortran language, or similar Programming language. Computer readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer, or entirely on the remote computer or server implement. In cases involving a remote computer, the remote computer can be connected to the user computer through any kind of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (such as via the Internet using an Internet service provider). connect). In some embodiments, an electronic circuit, such as a programmable logic circuit, field programmable gate array (FPGA), or programmable logic array (PLA), can be customized by utilizing state information of computer-readable program instructions, which can Various aspects of the invention are implemented by executing computer readable program instructions.

Aspects of the present invention are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It should be understood that each block of the flowcharts and/or block diagrams, and combinations of blocks in the flowcharts and/or block diagrams, can be implemented by computer-readable program instructions.

These computer-readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine such that when executed by the processor of the computer or other programmable data processing apparatus , producing an apparatus for realizing the functions/actions specified in one or more blocks in the flowchart and/or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium, and these instructions cause computers, programmable data processing devices and/or other devices to work in a specific way, so that the computer-readable medium storing instructions includes An article of manufacture comprising instructions for implementing various aspects of the functions/acts specified in one or more blocks in flowcharts and/or block diagrams.

It is also possible to load computer-readable program instructions into a computer, other programmable data processing device, or other equipment, so that a series of operational steps are performed on the computer, other programmable data processing device, or other equipment to produce a computer-implemented process , so that instructions executed on computers, other programmable data processing devices, or other devices implement the functions/actions specified in one or more blocks in the flowcharts and/or block diagrams.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, a portion of a program segment, or an instruction that includes one or more Executable instructions. In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks in succession may, in fact, be executed substantially concurrently, or they may sometimes be executed in the reverse order, depending upon the functionality involved. It should also be noted that each block of the block diagrams and/or flowchart illustrations, and combinations of blocks in the block diagrams and/or flowchart illustrations, can be implemented by a dedicated hardware-based system that performs the specified function or action , or may be implemented by a combination of dedicated hardware and computer instructions. It is well known to those skilled in the art that implementation by means of hardware, implementation by means of software, and implementation by a combination of software and hardware are all equivalent.

Having described various embodiments of the present invention, the foregoing description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and alterations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principle of each embodiment, practical application or technical improvement in the market, or to enable other ordinary skilled in the art to understand each embodiment disclosed herein. The scope of the invention is defined by the appended claims.

Claims (10)

1. A magnetic resonance multi-contrast parameter imaging method based on wave-like gradients, comprising the following steps:

   Step S1: acquiring a magnetic resonance imaging sequence, the sequence includes double repetition times, double flip angles, and each repetition time includes multiple echoes;

   Step S2: When applying a readout gradient to the magnetic resonance imaging sequence, use the magnetic resonance gradient field coil to apply a cosine wave gradient sequence in the layer selection direction, and apply a sine wave gradient sequence in the phase direction; or apply a cosine wave gradient in the phase direction Sequence, applying a sine wave gradient sequence in the layer selection direction;

   Step S3: applying the wave-like gradient sequence to a gradient refocusing echo imaging sequence, and under-sampling the signal to obtain a multi-layer image, and then obtain parametric images of various contrasts based on the multi-layer image.
2. The method according to claim 1, wherein the magnetic resonance imaging sequence has a first repetition time TR ₁ and a second repetition time TR ₂ , a first flip angle and a second flip angle, wherein the first repetition time corresponds to N1 gradient echoes, the second repetition time corresponds to N2 gradient echoes, and the first repetition time and the second repetition time have different flow modulation blocks.
3. The method according to claim 1, for the magnetic resonance imaging sequence, the readout gradient RO, the cosine wave gradient CO, the sine wave gradient SI and the templates sampled in k-space are under-sampled with the rule of every row and every column.
4. The method according to claim 1, wherein the parametric images of the multiple contrasts include B _1t images, T ₁ images, T ₂ images, T ₁ weighted images, enhanced T ₁ weighted images, T ₂ weighted images, Enhance at least 5 of T2 _- weighted _T2W images, T2* images, proton density images, proton density-weighted images, susceptibility-weighted imaging images, quantitative susceptibility mapping images, and magnetic resonance angiography images.
5. The method according to claim 2, wherein, for the magnetic resonance imaging sequence, the signal model of its k-space is expressed as:

   

   The point spread function PSF satisfies:

   

   Among them, m[x,y,z] is the image to be solved, t is the time, γ is the gyromagnetic ratio, k _x , _ky and k _z are the k-space coordinates, τ is the integration time variable, g _y (t) and g _z (t) are a pair of wave gradient fields with a phase difference of π/2 during readout, and Psf(t,y,z) is a three-dimensional In the phase diagram, the time t is linearly corresponding to the code k _x of the k-space readout direction, the discrete form of Psf(t,y,z) is expressed as Psf[k _x ,y,z], and Psf[k _x ,y , z] do Fourier transform in the y and z directions, and transform it into Psf[k _x , k _y , k _z ] to describe the offset of the wave trajectory relative to the Cartesian trajectory. Psf[k _x ,y, z] is inversely Fourier transformed in the readout direction, transformed into Psf[x, y, z], which is used to describe the diffusion effect of the wave gradient field in the readout direction.
6. The method according to claim 2, wherein, corresponding to the magnetic resonance imaging sequence, the image generation process is expressed as:

   Assuming that at flip angle α _i , echo time TE _j and echo time TE _k , the image signals corresponding to the first repetition time TR1 and corresponding to the second repetition time TR2 are respectively:

   

   

   where i ∈ [1, 2], j ∈ [1, N ₁ ], k ∈ [1, N ₂ ], M ₀ is the baseline signal related to proton density, Δω represents the non-resonance effect, W _p and

   

   are the modulus weights and phase components of the sensitivity curve _Cp of _the pth coil channel,

   

   is the constant baseline phase, and _E1 and _E2 represent

   

   and

   

   T ₁ represents the longitudinal relaxation time.
7. The method according to claim 2, wherein the multi-layer image comprises four layers, and the first layer image is 2(N obtained by using the linear equation solution of the SENSE model through the Wave-CAIPI signal from each k-space acquisition data ₁ +N ₂ ) group of original echo images; the second layer image is obtained by using the first group of images to model its complex signal, and its magnitude image presents various mixed images of PD image, T ₁ and T ₂ * weights , while the phase image contains background field and magnetic susceptibility effects; the third layer image is a composite PDW/T ₁ W/T ₂ *W image calculated based on the second layer image, B ₁ t image, T ₁ image, enhanced T ₁ W image, _T2 */ _R2 * image, PD image, SWI image, QSM image, MRA image; the fourth layer image is the cPDW image, cT1W image and QSM image calculated based on the third layer image, and used to calculate the real SWI image.
8. _The method according to claim 2, characterized in that, corresponding to the magnetic resonance imaging sequence, the first acquisition module uses the first flip angle to acquire N _{1 +} N ₂ gradient echoes, the second acquisition module acquires N ₁ +N ₂ gradient echoes within the first repetition time TR ₁ and the second repetition time TR ₂ by using the second flip angle.
9. A computer-readable storage medium, on which a computer program is stored, wherein, when the program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.
10. A computer device comprising a memory and a processor, wherein a computer program capable of running on the processor is stored on the memory, wherein any one of claims 1 to 8 is implemented when the processor executes the program The steps of the method described in the item.

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