Joint design method of variable acceleration factor k-space trajectories

Abstract

The application discloses a variable acceleration factor k-space trajectory joint design method, and belongs to the field of magnetic resonance imaging. The method is used for k-space trajectory design of a multi-frame imaging sequence with echo chain readout. Firstly, a sampling mask of a low acceleration factor frame is determined, then the trajectory of each echo chain is designed according to the mask, the number of echo chains required to be collected by a high acceleration factor frame is determined, and then the trajectory of the corresponding number of echo chains of the low acceleration factor frame is taken as the trajectory of the echo chain of the high acceleration factor frame. The application can realize trajectory design of variable acceleration factor acquisition in multi-frame magnetic resonance imaging, ensure that there is no additional T2 contrast difference between different acceleration factor image frames, and thus the reconstructed image is consistent. As an automatic trajectory design scheme, the method is especially suitable for application in three-dimensional multi-frame magnetic resonance imaging.

Description

Technical Field

[0001] This invention belongs to the field of magnetic resonance imaging and can design k-space trajectories for magnetic resonance parameter measurement sequences that require acquisition of variable acceleration factors. Background Technology

[0002] Magnetic resonance imaging (MRI) can measure tissue parameters including nuclear spin density, longitudinal relaxation time (T1), transverse relaxation time (T2), apparent diffusion coefficient (ADC), cerebral blood flow velocity, and magnetization transfer rate. These parameters can be derived from the nuclei of endogenous compounds present in the body (such as those in water). 1 H) can also originate from exogenous substances or tracers. Directly quantified MRI parameters can provide more valuable clinical information about various pathologies in neurological, musculoskeletal, hepatic, and myocardial imaging. This includes techniques such as relaxation time imaging, diffusion imaging, perfusion imaging, functional magnetic resonance imaging (fMRI), and chemical exchange saturation transfer (CEST) imaging, which generally require acquiring multi-frame image datasets with pulse sequence parameter modulation. Target parameter estimation can be achieved by fitting the signal evolution in the multi-frame image dataset to a corresponding mathematical model.

[0003] To accelerate parameter measurements in multi-frame imaging, researchers have proposed numerous methods. For example, the Keyhole method combines a low-resolution image with a high-resolution reference image to reduce the amount of data required for each acquisition, but sacrifices high-frequency information. SLAM methods can directly generate region CEST measurements from arbitrary-shaped regions of interest, achieving a much higher signal-to-noise ratio than traditional single-voxel and multi-voxel methods, but lose information about the heterogeneity of tissues within the region. Model-based methods, such as k-wROSA, can directly estimate the asymmetric Z-spectrum of interest from complete or incomplete measurements, but their acceleration capabilities are limited. The CS-CEST method based on compressed sensing can leverage the sparsity of images in the transform domain for speedup, but complete random undersampling has not yet been achieved in practical applications. These methods can improve data acquisition efficiency, reduce scanning time, and also contribute to improved image quality.

[0004] Multi-frame imaging typically involves acquiring multiple frames at the same location, ranging from a few to dozens. Full k-space sampling of all frames would be excessively time-consuming, while using the same high acceleration factor for every frame would result in severe artifacts and SNR loss. Therefore, employing a variable acceleration factor based on the importance of different frames is a reasonable approach, maximizing the balance between signal-to-noise ratio and scan speed. For example, the recently proposed Variable Speed ​​Sensitivity Coding (vSENSE) method quantifies the acceleration parameters. The vSENSE method uses a variable acceleration factor strategy to achieve high acceleration and high image quality. As an improvement on the vSENSE method, the KIPI method achieves automatic calibration, eliminates the need for acquiring additional sensitivity maps and full frame sampling, and allows for a more flexible variable acceleration strategy.

[0005] On the other hand, due to the advantages of long echo train readout sequences in terms of acquisition efficiency and signal-to-noise ratio, they are widely used in multi-frame imaging fields, such as TSE and EPI. However, due to the time dimension T2 or T2 of the signal... * Attenuation is applied in k-space with exponential attenuation filtering along the echo-encoded direction. For echo trajectories read outward from the center, this effect is equivalent to low-pass filtering in k-space. When using echo chain readout sequences for multi-frame imaging, the variable acceleration factor strategy results in different downsampling masks for image frames with different acceleration factors. Traditional methods calculate the echo chain trajectory separately for each acceleration factor's downsampling mask, leading to different T2 filtering effects across frames, introducing additional T2 contrast, and interfering with magnetic resonance parameter measurements.

[0006] Therefore, applying the variable acceleration factor strategy to multi-frame imaging sequences with long echo walks remains challenging, and high-quality practical acceleration has not yet been achieved. Thus, in the field of multi-frame imaging, proposing a method for k-space trajectory design for variable acceleration factor acquisition to achieve a consistent T2 filtering effect across all image frames is of significant importance. Summary of the Invention

[0007] The purpose of this invention is to solve the problems of additional contrast differences caused by variable acceleration factor sampling in multi-frame imaging technology and the difficulty in implementing variable acceleration factor strategies. It provides a joint design of trajectory with variable acceleration factor k-space trajectory (hereinafter referred to as JOINT method), which can automatically design the sampling trajectory of undersampled image frames with variable acceleration factor and eliminate the contrast differences between different frames caused by sampling.

[0008] The specific technical solution adopted in this invention is as follows:

[0009] A joint design method for k-space trajectory with variable acceleration factor is used to design the k-space trajectory of a multi-frame imaging sequence when acquiring undersampled image frames. The undersampled image frames include a first undersampled image frame and a second undersampled image frame with an acceleration factor of not less than 2. The acceleration factor of the first undersampled image frame is not higher than the acceleration factor of the second undersampled image frame. The readout module of the multi-frame imaging sequence is an echo chain readout.

[0010] The design method steps are as follows:

[0011] S1: For the first undersampled image frame, design a sampling mask based on the pre-set acceleration factor and echo chain length;

[0012] S2: Based on the number of sampling points in the sampling mask and the echo chain length, determine the number of first echo chains that need to be sampled in the first undersampled image frame, where the number of first echo chains is the rounded-up value of the ratio of the number of sampling points in the sampling mask to the echo chain length; then design the sampling trajectory of each echo chain in sequence, and form the first echo chain trajectory queue by the trajectories of all echo chains in the first undersampled image frame;

[0013] S3: For the second undersampled image frame, determine the number of second echo chains to be acquired, where the number of second echo chains is the rounded-up value of the product of the ratio of the acceleration factor of the first undersampled image frame to the acceleration factor of the second undersampled image frame.

[0014] S4: Select echo chain trajectories that satisfy the second number of echo chains sequentially from the first echo chain trajectory queue, and form the second echo chain trajectory queue of the second undersampled image frame, thereby completing the echo chain trajectory design.

[0015] Preferably, both the first undersampled image frame and the second undersampled image frame are two-dimensional images; the acceleration factor of the first undersampled image frame is preferably 2, and the acceleration factor of the second undersampled image frame is preferably 2 to 4.

[0016] Preferably, both the first undersampled image frame and the second undersampled image frame are three-dimensional images; the acceleration factor of the first undersampled image frame is preferably 4, and the acceleration factor of the second undersampled image frame is preferably 4 to 12.

[0017] Preferably, in S1, the sampling mask is a uniform downsampling mask or a variable-density Poisson downsampling mask.

[0018] Preferably, in S1, the center of the sampling mask retains a full sampling area.

[0019] Preferably, the density of the variable-density Poisson drop sampling mask decreases from the center to the edge.

[0020] Preferably, in S2, the acquisition trajectory of each echo chain is designed to be read outward from the center of the k-space.

[0021] Preferably, in S2, the acquisition trajectory of each echo chain should be distributed throughout the entire k-space.

[0022] Preferably, in step S2, both the first undersampled image frame and the second undersampled image frame are three-dimensional images, and the acquisition trajectory design method for each echo chain of the first undersampled image frame is as follows:

[0023] S21. Convert the coordinates of all N acquisition points in the sampling mask of the first undersampled image frame to polar coordinates (r, θ). Then, sort all acquisition points in ascending order according to the polar radius r. Then, group the sorted acquisition point sequence based on the echo chain length L and the number of first echo chains ShotNum1. The grouping rules are based on the remainder M of N divided by L and are divided into two forms:

[0024] If M=0, then the N collection points in the collection point sequence will be directly divided into L groups in order, with each group consisting of ShotNum1 collection points;

[0025] If M>0, first divide the first ShotNum1*M collection points in the collection point sequence into M groups of ShotNum1 collection points in order, and then divide the remaining collection points into LM groups of ShotNum1-1 collection points in order, for a total of L groups.

[0026] S22. Based on the grouping results and the golden angle φ, the trajectories of the ShotNum1 echo trains are designed sequentially, where:

[0027] For 1≤t≤(ShotNum1-1), when designing the trajectory of the t-th echo train, the j-th echo is sequentially assigned to the acquisition point p in the j-th group, 1≤j≤L, where the acquisition point p in the j-th group is the one whose polar angle θ is closest to the value of the unassigned acquisition point in the j-th group. The acquisition points are thus selected, and the trajectory of the t-th echo train is formed by the L acquisition points allocated.

[0028] When designing the trajectory of the final echo train t = ShotNum1, if M = 0, the j-th echo is assigned to the only remaining unassigned acquisition point in the j-th group, 1 ≤ j ≤ L; if M > 0, the j-th echo is assigned to the only remaining unassigned acquisition point in the j-th group, 1 ≤ j ≤ M.

[0029] Preferably, in step S4, the second echo chain trajectory queue is composed of the echo chain trajectories that are at the front of the first echo chain trajectory queue and satisfy the number of second echo chains.

[0030] Preferably, the second undersampled image frame has multiple frames, and different second undersampled image frames are allowed to have different acceleration factors. Each second undersampled image frame needs to design a second echo chain trajectory queue according to its own acceleration factor.

[0031] Compared with the prior art, the present invention has the following advantages:

[0032] Existing technologies design separate acquisition trajectories for undersampled image frames with different acceleration factors. These trajectory differences lead to inconsistent T2 filtering across frames, introducing additional T2 contrast and interfering with magnetic resonance parameter measurements. This invention addresses this by ensuring that the echo train trajectory of high acceleration factor frames originates entirely from the echo train trajectory queue of low acceleration factor frames. This results in consistent T2 filtering across all frames without additional T2 contrast, achieving optimal acquisition.

[0033] Compared to existing technologies, this invention allows for arbitrary changes in the acceleration factor while jointly designing the acquisition trajectory of image frames with varying acceleration factors, thus improving the quantitative effect of magnetic resonance parameters. This invention enables the practical application of a variable acceleration factor undersampling strategy to provide shorter scan times and higher image quality.

[0034] This method is applicable to any acquisition technique in magnetic resonance imaging that requires echo chain readout, including but not limited to TSE (FSE), EPI, and variable flip angle TSE sequences (also known as SPACE sequences). Multiframe imaging is any technique in magnetic resonance imaging that requires multiple acquisitions of the same imaging subject, including but not limited to relaxation time (T1, T2) imaging, functional imaging (fMRI), magnetic resonance spectroscopy (MRS) imaging, chemical exchange saturation transfer (CEST) imaging, diffusion imaging, and perfusion imaging. Attached Figure Description

[0035] Figure 1 This is a portion of the echo chain acquisition trajectory of the first undersampled image frame in the embodiment. The first row shows the result of the conventional method, and the second row shows the result of the JOINT method; each column from left to right represents the trajectory of the 1st, 3rd, 5th, and 7th echo chains, respectively. The color intensity represents the acquisition order in the echo chain, with the lightest color representing the k-space line acquired by the first echo in the echo chain, and the darkest color representing the k-space line acquired by the last echo in the echo chain.

[0036] Figure 2The acquisition trajectory consists of all echo chains designed by the conventional method and the JOINT method for the first and second undersampled image frames in the embodiment. For the first undersampled image frame, both the conventional method and the JOINT method have an acceleration factor (AF) of 2×2 (in the phase coding and layer selection coding directions, respectively), with a 15×15 full-sampling area (A, D) at the center; for the second undersampled image frame, the conventional method uses AF = 4×2 and the number of echo chains is 4 (B), while the JOINT method uses AF = 9 and the number of echo chains is 4 (E). (C), (F): the difference in echo order of the same position in the echo chain between the trajectory of the second undersampled image frame and the trajectory of the first undersampled image frame, where (C) is the conventional method and (F) is the JOINT method.

[0037] Figure 3 This is a layer from the 3.5ppm and -3.5ppm 3D-CEST source images of healthy volunteers in the example. The first column is the 3.5ppm source image, the second column is the -3.5ppm source image, and the third column is the difference between the 3.5ppm and -3.5ppm source images. The first row is the reference method, a conventional GRAPPA with AF = 2×2; the second row is the data acquired by the conventional method, with the 3.5ppm frame as the first undersampled image frame (AF = 2×2) and the -3.5ppm frame as the second undersampled image frame (AF = 4×2), and the trajectory is designed separately; the third row is the data acquired by the JOINT method, with the 3.5ppm frame as the first undersampled image frame (AF = 2×2) and the -3.5ppm frame as the second undersampled image frame (AF = 9), and the trajectory is designed jointly. Both the conventional method and the JOINT method use the KIPI method for reconstruction.

[0038] Figure 4 The images shown are APTw parameter images of healthy volunteers in this example. The first row represents the reference method (AC), using a standard GRAPPA with AF = 2 × 2. The second row represents the trajectory acquisition data (DF) designed using the conventional method, with the 3.5 ppm frame as the first undersampled image frame (AF = 2 × 2) and the other 6 frames as the second undersampled image frames (AF = 4 × 2), and the trajectory is designed separately for each frame. The third row represents the trajectory acquisition data using the JOINT method, with the 3.5 ppm frame as the first undersampled image frame (AF = 2 × 2) and the other 6 frames as the second undersampled image frames (AF = 9), and the trajectory is designed jointly for each frame. Both the conventional method and the JOINT method use KIPI for reconstruction.

[0039] Figure 5 This is a flowchart illustrating the JOINT trajectory design method of the present invention. Detailed Implementation

[0040] The present invention will be further described and illustrated below with reference to the accompanying drawings and specific embodiments. The technical features of each embodiment of the present invention can be combined accordingly, provided that there is no mutual conflict.

[0041] Multi-frame imaging requires multiple acquisitions of the same object, resulting in a long acquisition time. A variable acceleration factor strategy uses a low acceleration factor for frames with low signal-to-noise ratio (SNR) and a high acceleration factor for frames with high SNR, achieving an optimal balance between SNR and acquisition speed. On the other hand, multi-frame imaging widely uses acquisition sequences with long echo train readout modules, such as EPI, TSE (FSE), and variable flip angle TSE sequences. When using a variable acceleration factor strategy in these sequences, the difference in echo train trajectories between frames with different acceleration factors leads to significant differences in the T2 attenuation effect between frames. This introduces additional T2-related contrast, interfering with the quantification of magnetic resonance parameters.

[0042] This invention achieves the goal of ensuring that the echo chain trajectory of a high-acceleration-factor frame is entirely derived from the echo chain trajectory of a low-acceleration-factor frame by jointly designing the echo chain trajectory for frames with different acceleration factors, thus guaranteeing that the T2 filtering effect is the same for frames with different acceleration factors. The joint design method for spatial trajectories with variable acceleration factor k provided by this invention is as follows: Figure 5 As shown, the specific implementation process will be described in detail below.

[0043] This design method involves the joint design of k-space acquisition trajectories for undersampled image frames with varying acceleration factors on a magnetic resonance imaging (MRI) machine. The undersampled image frames are divided into a first undersampled image frame and a second undersampled image frame. The first undersampled image frame is undersampled with a lower acceleration factor, while the second undersampled image frame is undersampled with a higher acceleration factor (AF≥2). The acceleration factor of the second undersampled image frame is no lower than that of the first undersampled image frame. There is only one first undersampled image frame; the rest are second undersampled image frames.

[0044] It should be noted that the multi-frame image data acquired by the magnetic resonance imaging (MRI) machine can be either 2D or 3D data, and the acceleration factor is adjusted according to the actual situation. If the first undersampled image frame and the second undersampled image frame are 2D images, the acceleration factor of the first undersampled image frame is preferably 2, and the acceleration factor of the second undersampled image frame is preferably 2 to 4; if the first undersampled image frame and the second undersampled image frame are 3D images, the acceleration factor of the first undersampled image frame is preferably 4, and the acceleration factor of the second undersampled image frame is preferably 4 to 12.

[0045] It should be noted that this invention does not involve the design of acquisition in the readout direction. If it is a 2D image, this invention designs the acquisition trajectory in the phase encoding direction; if it is a 3D image, this invention designs the acquisition trajectory in the phase encoding and layer selection encoding directions.

[0046] The joint design method for the spatial trajectory of the variable acceleration factor k in this invention comprises the following steps:

[0047] S1: For the first undersampled image frame, design a sampling mask based on the pre-set acceleration factor and echo chain length.

[0048] In this invention, the sampling mask design for the first undersampled frame can employ a uniform downsampling mask or a variable-density Poisson downsampling mask. This invention recommends retaining a small full-sampling area at the center of the mask. Furthermore, if a variable-density Poisson downsampling mask is used, this invention recommends that the density of the variable-density Poisson downsampling decrease from the center to the edge.

[0049] However, it should be noted that while uniform downsampling masks or variable-density Poisson downsampling masks are recommended in this step, other downsampling masks may also be used depending on the situation, such as downsampling masks with partial Fourier transforms or random downsampling masks.

[0050] S2: Based on the number of sampling points in the sampling mask and the echo chain length, determine the number of echo chains to be acquired in the first undersampled image frame (denoted as the first echo chain number ShotNum1). The first echo chain number is the rounded-up value of the ratio of the number of sampling points in the sampling mask to the echo chain length. Where N represents the number of sampling points in the sampling mask, and L represents the echo train length. This indicates rounding up. Then, the acquisition trajectory tra for each echo train is designed sequentially. i The queue formed by the trajectories of all ShotNum1 echo chains in the first undersampled image frame is denoted as the first echo chain trajectory queue Ω1 = {tra i}, i=1...ShotNum1.

[0051] In this invention, the acquisition trajectory of each echo chain is preferably read outward from the center of the k-space, and the acquisition trajectory of each echo chain should be distributed as widely as possible throughout the k-space. However, it should be noted that although it is recommended that the acquisition trajectory of each echo chain be read outward from the center of the k-space in this step, other methods can be adopted according to the actual situation, such as random arrangement.

[0052] In addition, in the embodiments of the present invention, in order to ensure that the acquisition trajectory of each echo chain is dispersed as much as possible throughout the k-space, a design method for the echo chain acquisition trajectory of the first undersampled image frame based on the golden angle is also designed for the phase encoding ky and layer selection encoding kz directional trajectories of three-dimensional imaging.

[0053] For ease of description, we define M as the remainder when N is divided by L, and the golden angle. or Based on this definition, when both the first undersampled image frame and the second undersampled image frame are three-dimensional images, the acquisition trajectory design method for each echo chain of the first undersampled image frame is as follows:

[0054] First, for 3D imaging, the coordinates (ky, kz) of all N acquisition points in the sampling mask of the first undersampled image frame, which are all k-space points to be acquired, are converted into polar coordinates (r, θ) and sorted in ascending order according to the polar radius r. Then, the sorted acquisition point sequence is grouped based on the echo chain length L and the number of first echo chains ShotNum1. The grouping rule is based on the remainder M of N divided by L and has two forms:

[0055] For cases where N is divisible by L (M=0), the N collection points in the collection point sequence are directly grouped into groups of ShotNum1, resulting in exactly L groups.

[0056] For the case where N is not divisible by L (M>0): First, divide all N sampling points into two queues, A and B. The first ShotNum1*M sampling points are assigned to queue A, and the remaining sampling points are assigned to queue B. Within queue A, groups are formed with every ShotNum1 sampling points, resulting in M ​​groups. Within queue B, groups are formed with every ShotNum1-1 sampling points, resulting in LM groups. Therefore, this case also results in a total of L groups, with the first M groups each having ShotNum1 sampling points, and the last LM groups each having ShotNum1-1 sampling points.

[0057] Then, based on the grouping results and the golden angle φ, the trajectories of the ShotNum1 echo trains are designed sequentially, where:

[0058] First, determine the trajectory of the first echo train: assign the j-th echo (1≤j≤L) to the acquisition point p in the j-th group mentioned above. The acquisition point p in the j-th group is the acquisition point whose polar angle θ is closest to (j-1)φ among all the unassigned acquisition points in the j-th group. Thus, the trajectory of the first echo train is formed by the L assigned acquisition points. After determining the trajectory of the first echo train, mark the assigned acquisition points in each group, reducing the number of unassigned acquisition points in each group by one.

[0059] Similarly, determine the trajectory of the t-th echo train (2≤t≤(ShotNum1-1)): Assign the j-th echo (1≤j≤L) to the acquisition point p in the j-th group, where the acquisition point p in the j-th group is the one with the polar angle θ closest to the zero point among all unassigned acquisition points in the j-th group. After determining the t-th echo train trajectory, the assigned acquisition points in each group are marked, and the number of unassigned acquisition points in each group will decrease by 1.

[0060] Determining the trajectory of the last echo chain, i.e., the t = ShotNum1th echo chain, also involves two cases:

[0061] For the case where N is divisible by L (M=0), each group in L has 1 remaining acquisition point. Therefore, the j-th echo is assigned to the only remaining unassigned acquisition point in the j-th group, where 1≤j≤L.

[0062] In the case where N is not divisible by L (M>0), each of the first M groups has 1 unassigned acquisition point remaining, and each of the last LM groups has 0 acquisition points remaining. Therefore, the j-th echo is assigned to the only remaining acquisition point in the j-th group, where 1≤j≤M.

[0063] S3: For the second undersampled image frame, determine the number of echo chains to be acquired (denoted as the second echo chain number ShotNum2). The second echo chain number is the rounded-up value of the product of the ratio of the acceleration factor of the first undersampled image frame to the acceleration factor of the second undersampled image frame, i.e., the number of first echo chains. AF1 and AF2 represent the acceleration factors of the first undersampled image frame and the second undersampled image frame, respectively.

[0064] It should be noted that the echo chain lengths of the first and second undersampled image frames of this invention are the same.

[0065] S4: Select ShotNum2 echo chain trajectories sequentially from the first echo chain trajectory queue of the first undersampled image frame to form the second echo chain trajectory queue Ω2 of the second undersampled image frame. At this point, the echo chain trajectory design for all undersampled image frames is completed.

[0066] In this invention, when constructing the second echo chain trajectory queue Ω2, it is necessary to sequentially select ShotNum2 echo chain trajectories from the first echo chain trajectory queue Ω1 of the first undersampled image frame echo chain. The position selected in the queue can be adjusted according to actual needs. Preferably, the ShotNum2 echo chain trajectories at the front of the Ω1 queue are selected as the Ω2 queue. However, other methods can also be selected according to actual conditions. For example, ShotNum2 echo chain trajectories can be randomly selected from the Ω1 queue as the Ω2 queue.

[0067] It should be noted that the second undersampled image frame in this invention has multiple frames, and different second undersampled image frames can have different acceleration factors. Each second undersampled image frame needs to determine the number of second echo chains (ShotNum2) and design the second echo chain trajectory queue based on its own acceleration factor. Specifically, if the acceleration factor of a second undersampled image frame is X and the number of echo chains to be acquired is ShotNum2_X, then ShotNum2_X echo chain trajectories need to be selected from the trajectory queue of the first undersampled image frame echo chain as the Ω2 queue for this frame; when the acceleration factor of another second undersampled image frame is Y and the number of echo chains to be acquired is ShotNum2_Y, then ShotNum2_Y echo chain trajectories need to be selected from the trajectory queue of the first undersampled image frame echo chain as the Ω2 queue for this frame.

[0068] Therefore, S1 to S4 constitute the joint design method of the spatial trajectory of the variable acceleration factor k of the present invention.

[0069] The following example will further demonstrate the technical effects achievable by the aforementioned joint design method for spatial trajectories with variable acceleration factor k, so that those skilled in the art can better understand the essence of the present invention.

[0070] Example

[0071] This embodiment applies the joint design method (i.e., the JOINT method) for the spatial trajectory of the variable acceleration factor k shown in S1 to S4 above to a specific example. The specific data sources and implementation methods of each step of this method are described in detail below:

[0072] 1. Trajectory Design

[0073] All processing and analysis were performed offline using MATLAB (MathWorks, Natick, MA) software written on a PC (3.2GHz).

[0074] The acquisition matrix size for the phase coding and layer selection coding directions is preset to 80×72, the echo chain length is 142, the first undersampled image frame has AF=4, and the second undersampled image frame has only one acceleration factor, AF=9.

[0075] The trajectory design in this embodiment consists of the following steps:

[0076] 1. Design a sampling mask for the first undersampled image frame. Use a uniform downsampling mask of AF = 2×2 (in both phase coding and layer selection coding directions), retaining a 15×15 full sampling area in the center, and using 80 and 72 as the major and minor axes of an ellipse. Do not collect data outside the ellipse. The downsampling mask designed accordingly has 1276 sampling points.

[0077] 2. Based on the downsampling mask calculation, 9 echo chains are required. Note that since 1276 divided by 142 equals 8 with a remainder of 140, a total of 9 echo chains are needed, but the 9th echo chain actually collects 140 echoes. The trajectory of each echo chain is designed to be read out from the inside to the outside of k-space, and each echo chain is relatively evenly distributed throughout the k-space. The specific method is as follows:

[0078] Convert all the k-space locations (ky, kz) to polar coordinates (r, θ); sort them in ascending order of r, then group them into groups of 9, resulting in 140 groups. Finally, group the remaining 16 locations into groups of 8, resulting in 2 groups; for a total of 142 groups. Thus, the 9 locations in the first group correspond to the first echo of all 9 echo chains, and the 9 locations in the Xth group correspond to the Xth echo of all 9 echo chains (1 ≤ X ≤ 140).

[0079] The following describes how all echoes on each echo chain are distributed to their corresponding positions to ensure a relatively uniform trajectory for each echo chain: Defining the golden angle

[0080]

[0081] First, determine the trajectory of the first echo chain: fill the j-th (1≤j≤142) echo into the j-th group at the position closest to ((j-1)*φ) at the angle θ. After determining the trajectory of the first echo chain, remove the determined positions, and reduce the number of remaining positions in each group by 1.

[0082] For the trajectory of the second echo chain: fill the j-th (1≤j≤142) echo into the j-th group at the position closest to ((j-1)*φ+φ) at the angle θ. After determining the trajectory of the second echo chain, remove the determined positions. Continue to reduce the remaining positions in each group by 1.

[0083] Similarly, for the trajectory of the m-th (3≤m≤8) echo chain: select from the unassigned positions, fill the j-th (1≤j≤142) echo into the position in the j-th group whose angle θ is closest to ((j-1)*φ+m*(m-1) / 2*φ), and then remove the already determined positions.

[0084] After determining the trajectories of the 8 echo chains in sequence, there is one position remaining in each of groups 1 to 140, and no remaining positions in groups 141 and 142. Therefore, for the trajectory of the 9th echo chain, the j-th echo is filled into the only remaining position in the j-th group, where 1≤j≤140.

[0085] At this point, the design of all echo chain trajectories for the first undersampled image frame is complete.

[0086] 3. The number of echo chains in the second undersampled image frame is calculated to be 4 / 9*9 = 4. Therefore, the first to fourth echo chain trajectories in the echo chain trajectory queue of the first undersampled image frame are selected as the acquisition trajectories for the second undersampled image frame.

[0087] Thus, the echo train trajectory design for the second undersampled image frame is complete.

[0088] 2. Data Collection

[0089] The human trials were conducted on a 3T Siemens MRI scanner (MAGNETOM Prisma) using a 64-channel head receiver coil. The human trials were approved by the local institutional review board. The sequences used were CEST imaging sequences, and the MRI parameters measured were the amplitude of the amide proton transfer effect.

[0090] For the 3D human brain experiment, the SPACE-CEST sequence was used to collect data, with the following parameters: TE = 17ms, TR = 3s, FOV = 232×232×209mm. 3 Resolution = 2.9 × 2.9 × 2.9 mm 3 The acquisition matrix size was 80×80×72 (phase encoding, readout encoding, and layer selection encoding, respectively), the echo chain length was 142, and the NSA was 1.3. A total of 7 CEST saturated offset frames were acquired for amide proton transfer weighted (APTw) imaging, including (S0), ±3, ±3.5, and ±4 ppm. The +3.5 ppm frame was selected as the first undersampled image frame (AF=4), and the remaining 6 frames were selected as the second undersampled image frames (AF=9). The SPACE sequence, also known as the variable flip angle TSE sequence, was acquired using the trajectory designed by the JOINT method described above, with an acquisition time of 2.5 minutes.

[0091] For comparison, an experiment was conducted to acquire variable-speed data using traditional methods. In the +3.5ppm frame, AF = 2×2, and in other frames, AF = 4×2. The +3.5ppm frame also retained a 15×15 ACS region at its center. Meanwhile, the standard GRAPPA = 2×2 was used as a reference, with all 7 frames having AF = 2×2 and a 24×24 ACS region at its center. The acquisition time was 5 minutes.

[0092] To assess the amplitude of the amide proton transfer effect, B0-corrected data was acquired using a GRE sequence with the same field of view, azimuth, and resolution as the CEST sequence, with a TR of 30 ms. The GRE sequence was run in dual-echo mode, with TEs of 4.92 ms and 9.84 ms, respectively.

[0093] 3. Image Reconstruction

[0094] The acquisition data of the trajectory designed using the JOINT method of this invention and the acquisition data of the traditional method are both reconstructed using the KIPI method: first, the first undersampled image frame is reconstructed using the GRAPPA method, and then the coil sensitivity map and the correction factor map of the second undersampled image frame are obtained from it; the second undersampled image frame is reconstructed using CG-SENSE, and the image generated by CG-SENSE is multiplied point by point with the correction factor map to obtain the final reconstructed image.

[0095] The APTw parameter image is calculated as follows: First, the source image is registered to the first undersampled frame image at 3.5 ppm. Second, the phase difference between the two GRE images acquired by different TEs is calculated as a B0 map. Third, based on the calculated B0 map, corrected +3.5-ppm and -3.5-ppm signal values ​​are generated for each voxel. Finally, the corrected 3.5-ppm and +3.5-ppm images are subtracted to obtain the APTw parameter image.

[0096] 4. Results Analysis

[0097] Figure 1 The example shows the trajectory design for the first undersampled image frame. Traditional methods result in a more concentrated trajectory for each echo chain (AD), while the method used in this example ensures that the trajectory of each echo chain is more uniform and dispersed (EH).

[0098] Figure 2 The results of trajectory design for the first and second undersampled image frames using both the conventional method and the proposed JOINT method are presented. For the first undersampled image frame, both the conventional and proposed methods use AF = 2 × 2, with a 15 × 15 fully sampled area at the center (A, D). For the second undersampled image frame, the conventional method uses AF = 4 × 2 and 4 echo trains (B), while the JOINT method uses AF = 9 and 4 echo trains (E). The conventional method designs the trajectories for the two undersampled image frames separately, resulting in different echo ordinal numbers at the same acquisition position, with a difference of up to 20 (C). The proposed JOINT method uses a joint design, where the echo train trajectory of the second undersampled image frame is entirely derived from the first undersampled image frame. Therefore, the echo ordinal numbers at the same acquisition position in the first and second undersampled image frames are exactly the same (F), with no difference.

[0099] Figure 3This image shows a layer from 3D-CEST source images of healthy volunteers at 3.5 ppm and -3.5 ppm. The first row shows the reference method, a conventional GRAPPA (AC) with AF = 2 × 2. The second row shows the trajectory acquisition data (DF) designed using the conventional method, with the 3.5 ppm frame as the first undersampled image frame (AF = 2 × 2) and the -3.5 ppm frame as the second undersampled image frame (AF = 4 × 2), and the trajectory was designed separately. The third row shows the trajectory acquisition data (GI) designed using the JOINT method of this invention, with the 3.5 ppm frame as the first undersampled image frame (AF = 2 × 2) and the -3.5 ppm frame as the second undersampled image frame (AF = 9), and the trajectory was designed jointly. The acquisition data obtained by both the conventional method and the JOINT method were reconstructed using KIPI. As can be seen, due to the different T2 filtering effects of the first and second undersampled frames in the traditional method, the difference (F) between the two frames shows a significant T2-related signal, which is very different from the reference (C). However, the JOINT method of this invention makes the T2 filtering effect consistent in each frame through joint trajectory design, and the difference (I) between the two frames is consistent with the reference method (C), without any additional artifacts.

[0100] Figure 4 The image shows whole-brain APTw parametric images of healthy volunteers. Traditional methods result in significant artifacts (DF) due to the failure to maintain consistent T2 filtering across all frames; the 3.5ppm frame is the first undersampled image frame (AF = 2 × 2), and the other six frames are the second undersampled image frames (AF = 2 × 4), with trajectories designed separately. In contrast, the JOINT method of this invention ensures consistent T2 filtering across all frames, resulting in a high degree of consistency between the APTw image (GI) and the reference result (AC); the 3.5ppm frame is the first undersampled image frame (AF = 2 × 2), and the other six frames are the second undersampled image frames (AF = 9), with trajectories designed jointly.

[0101] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the invention. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of the invention. Therefore, all technical solutions obtained through equivalent substitution or transformation fall within the protection scope of the present invention.

Claims

1. A joint design method of variable acceleration factor k-space trajectories, for designing k-space trajectories of a multi-frame imaging sequence when acquiring undersampled image frames, characterized in that, The undersampled image frames include a first undersampled image frame and a second undersampled image frame with an acceleration factor not lower than 2, and the acceleration factor of the first undersampled image frame is not higher than the acceleration factor of the second undersampled image frame, and the readout module of the multi-frame imaging sequence is an echo train readout; The design method comprises the following steps: S1: for the first undersampled image frame, a sampling mask is designed according to the preset acceleration factor and echo train length; S2: according to the number of sampling points in the sampling mask and the echo train length, the first echo train number required by the first undersampled image frame is determined, wherein the first echo train number is the integer value of the ratio of the number of sampling points in the sampling mask to the echo train length; then the acquisition trajectory of each echo train is designed in turn, and the trajectory of all echo trains of the first undersampled image frame forms a first echo train trajectory queue; S3: for the second undersampled image frame, the second echo train number to be acquired is determined, wherein the second echo train number is the integer value of the product of the ratio of the acceleration factor of the first undersampled image frame to the acceleration factor of the second undersampled image frame and the first echo train number; S4: echo train trajectories satisfying the second echo train number are selected from the first echo train trajectory queue in turn, and a second echo train trajectory queue of the second undersampled image frame is formed, thereby completing the design of the echo train trajectory.

2. The method of joint design of variable acceleration factor k-space trajectories of claim 1, wherein, The first undersampled image frame and the second undersampled image frame are both two-dimensional images; the acceleration factor of the first undersampled image frame is preferably 2, and the acceleration factor of the second undersampled image frame is preferably 2 to 4.

3. The method of joint design of variable acceleration factor k-space trajectories of claim 1, wherein, The first undersampled image frame and the second undersampled image frame are both three-dimensional images; the acceleration factor of the first undersampled image frame is preferably 4, and the acceleration factor of the second undersampled image frame is preferably 4 to 12.

4. The method of joint design of variable acceleration factor k-space trajectories of claim 1, wherein, In S1, the sampling mask is a uniform down-sampling mask or a variable-density Poisson down-sampling mask.

5. The method of joint design of variable acceleration factor k-space trajectories of claim 1, wherein, In S1, the center of the sampling mask retains a full-sampling area.

6. The method of joint design of variable acceleration factor k-space trajectories of claim 4, wherein, The density of the variable-density Poisson down-sampling mask decreases from the center to the edge.

7. The method of joint design of variable acceleration factor k-space trajectories of claim 1, wherein, In S2, the acquisition trajectory of each echo train is designed to read out from the center of the k-space outward, and the acquisition trajectory of each echo train should be dispersed in the entire k-space.

8. The method of joint design of variable acceleration factor k-space trajectories of claim 1, wherein, In S2, the first undersampled image frame and the second undersampled image frame are both three-dimensional images, and the acquisition trajectory of each echo train of the first undersampled image frame is designed as follows: S21: the coordinates of all N sampling points in the sampling mask of the first undersampled image frame are converted into polar coordinates (r, θ) form, then all sampling points are arranged in ascending order according to the polar radius r, and then the sorted sampling point sequence is grouped based on the echo train length L and the first echo train number ShotNum1, and the grouping rule is based on the remainder M of N divided by L and divided into two forms: If M=0, N sampling points in the sampling point sequence are directly grouped into L groups in order with ShotNum1 sampling points as a group; If M>0, first, the first ShotNum1*M acquisition points in the acquisition point sequence are divided into M groups with each group having ShotNum1 acquisition points, and then the remaining acquisition points are divided into L-M groups with each group having ShotNum1-1 acquisition points, and in total, L groups are formed; S22, based on the grouping result and the golden angle φ, the trajectories of the ShotNum1 echo chains are sequentially designed, wherein: For 1≤(ShotNum1-1), when designing the trajectory of the tth echo chain, the jth echo is sequentially assigned to the acquisition point p in the jth group, 1≤L, wherein the acquisition point p in the jth group is the acquisition point with the polar angle θ closest to in all unassigned acquisition points in the jth group, so that the L acquisition points obtained by the assignment constitute the trajectory of the tth echo chain; When designing the trajectory of the last t=ShotNum1 echo chain, if M=0, the jth echo is allocated to the only remaining one unallocated acquisition point in the jth group, 1≤L; if M>0, the jth echo is allocated to the only remaining one unallocated acquisition point in the jth group, 1≤M.

9. The method of joint design of variable acceleration factor k-space trajectories of claim 1, wherein, In the S4, the second echo chain trajectory queue is composed of the first echo chain trajectory in the first echo chain trajectory queue that satisfies the second echo chain number.

10. The method of joint design of variable acceleration factor k-space trajectories of claim 1, wherein, The second undersampled image frame has multiple frames, and different second undersampled image frames allow different acceleration factors, and each second undersampled image frame needs to design a second echo chain trajectory queue according to its own acceleration factor.

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