Magnetic resonance thermography method and apparatus based on echo planar time resolved sequences

Abstract

The application discloses a magnetic resonance temperature imaging method and device based on an echo planar time resolution sequence, and the method comprises the following steps: collecting multi-echo data of a target human tissue based on a preset echo planar time resolution sequence; inputting the multi-echo data into a pre-constructed magnetic resonance water-fat signal model, iteratively processing a plurality of related parameters, and extracting water signals and fat signals of the target human tissue; and determining a phase part affected by temperature in water protons based on the water signals and the fat signals, so as to obtain an actual temperature distribution of the target human tissue. Therefore, the technical problem that, in the prior art, it is difficult to perform real-time monitoring of temperature for a scanning part with high requirements for time resolution or spatial resolution, and the scanning result has artifacts, which has a great influence on the treatment result, is solved.

Description

Technical Field

[0001] This application relates to the field of medical device technology, and in particular to a magnetic resonance temperature imaging method and apparatus based on echo plane time-resolved sequences. Background Technology

[0002] The main purpose and task of tumor ablation surgery is to inactivate tumor cells with high temperature while ensuring that the normal cells and tissues surrounding the tumor are not damaged by high temperature. Therefore, precise control of the heat source is required during the operation, with high safety and real-time requirements. Otherwise, there is a risk of incomplete tumor ablation, high recurrence rate, or damage to normal tissues and organs. Magnetic resonance thermometry, as a non-invasive spatial temperature distribution measurement technology, can monitor ablation surgery in real time. At the same time, due to its high spatial resolution and high soft tissue contrast, magnetic resonance technology can also be used for preoperative scanning to help with surgical planning, and postoperative scanning to help determine the success of the operation and the effectiveness of tumor ablation.

[0003] Since magnetic resonance thermography is based on the temperature imaging of water proton resonance frequency, it has a good temperature measurement effect on tissues with high water content such as muscle tissue and brain tissue. However, tissues and organs such as breast, bone marrow of the elderly, and fatty liver contain a lot of fat. The molecular environment inside fat is complex, and there is no obvious relationship between proton resonance frequency and temperature. Therefore, the temperature imaging method based on water proton resonance frequency cannot be used.

[0004] Meanwhile, in order to measure the temperature of tissues with a high fat content, a fat suppression operation can be performed before scanning. This operation will increase the scanning time of the sequence, which is not conducive to real-time intraoperative temperature monitoring. Moreover, fat often has 5-6 frequency peaks, and the fat suppression operation cannot suppress all fat signals. A small amount of residual fat signal can still have a significant impact on the temperature measurement results.

[0005] In related technologies, the independence of fat resonance frequency from temperature can be utilized to use the fat peak as a reference value. The frequency difference between the water peak and the fat peak can be used to calculate the temperature change. A phase signal that is only related to the water signal can be found using a multi-echo sequence. Then, a magnetic resonance signal model can be used to iteratively process the water signal and the fat signal respectively to achieve water-fat separation.

[0006] In order to separate fat signals from water signals, the relevant techniques need to complete the acquisition of multiple echo sequences simultaneously in a short period of time. Multi-echo gradient echo sequences are usually used to acquire data, which can obtain multi-echo data in a short time (about 9.5 seconds for a single-layer pelvic scan), resulting in high image accuracy and soft tissue contrast.

[0007] However, when the scanned area exhibits significant respiratory or cardiac activity, such as the liver or heart, higher temporal resolution is required. Multi-echo gradient echo sequences still require relatively long scan times, hindering real-time temperature monitoring and resulting in severe motion artifacts. This poses certain safety risks and fails to meet the real-time monitoring needs of ablation procedures. Furthermore, for scenarios requiring higher spatial resolution (such as near the spine), multi-echo gradient echo sequences will require even longer scan times, leading to greater artifacts, and require further improvement. Summary of the Invention

[0008] This application provides a magnetic resonance temperature imaging method and apparatus based on echo plane time-resolved sequence to solve the technical problems in related technologies, such as the difficulty in real-time temperature monitoring for scanning areas with high time or spatial resolution requirements, and the existence of artifacts in the scanning results, which have a significant impact on treatment outcomes.

[0009] The first aspect of this application provides a magnetic resonance temperature imaging method based on echo plane time-resolved sequences, comprising the following steps: acquiring multi-echo data of a target human tissue based on a preset echo plane time-resolved sequence; inputting the multi-echo data into a pre-constructed magnetic resonance water-fat signal model, iterating on multiple related parameters, and extracting water and fat signals of the target human tissue; and determining the temperature-affected phase portion of water protons based on the water and fat signals to obtain the actual temperature distribution of the target human tissue.

[0010] Optionally, in one embodiment of this application, the step of acquiring multi-echo data of the target human tissue based on a preset echo plane time-resolved sequence includes: determining the data trajectory of the echo plane time-resolved sequence data; performing data convolution on the echo plane time-resolved sequence data based on the data trajectory to reconstruct multiple magnetic resonance images with different echo times.

[0011] Optionally, in one embodiment of this application, the process of restoring multiple magnetic resonance images with different echo times includes: acquiring full-sample data from the acquisition portion; training a W matrix using the full-sample data; and performing data convolution based on the W matrix to restore the magnetic resonance images.

[0012] Optionally, in one embodiment of this application, the preset echo plane time-resolved sequence includes pulse rows, layer-selected gradient rows, phase-coded rows, and frequency-coded rows to acquire sawtooth-shaped multi-echo data.

[0013] Optionally, in one embodiment of this application, the step of inputting the multi-echo data into a pre-constructed magnetic resonance water-lipid signal model, iterating over multiple related parameters, and extracting the water and fat signals of the target human tissue includes: obtaining the current water-lipid chemical shifts of the water peak and the fat peak, and calculating the water-lipid separation result; applying a magnetic resonance thermometry method based on the water proton resonance frequency to the water signal and fitting and smoothing it to obtain a smoothed temperature result; inputting the smoothed temperature result into the pre-constructed magnetic resonance water-lipid model, iterating over multiple related parameters, and outputting the water signal phase and the fat signal phase.

[0014] A second aspect of this application provides a magnetic resonance temperature imaging device based on an echo plane time-resolved sequence, comprising: an acquisition module for acquiring multi-echo data of a target human tissue based on a preset echo plane time-resolved sequence; an extraction module for inputting the multi-echo data into a pre-constructed magnetic resonance water-fat signal model, iterating on multiple related parameters, and extracting water and fat signals from the target human tissue; and an acquisition module for determining the temperature-affected phase portion of water protons based on the water and fat signals to obtain the actual temperature distribution of the target human tissue.

[0015] Optionally, in one embodiment of this application, the acquisition module includes: a determination unit, used to determine the data trajectory of the echo plane time-resolved sequence data; and a convolution unit, used to perform data convolution on the echo plane time-resolved sequence data based on the data trajectory to reconstruct multiple magnetic resonance images with different echo times.

[0016] Optionally, in one embodiment of this application, the convolution unit includes: an acquisition subunit for acquiring a portion of the full-acquired data; a training subunit for training a W matrix using the full-acquired data; and a reconstruction subunit for performing data convolution based on the W matrix to reconstruct the magnetic resonance image.

[0017] Optionally, in one embodiment of this application, the preset echo plane time-resolved sequence includes pulse rows, layer-selected gradient rows, phase-coded rows, and frequency-coded rows to acquire sawtooth-shaped multi-echo data.

[0018] Optionally, in one embodiment of this application, the extraction module includes: a first calculation unit, used to acquire the current water-lipid chemical shifts of the water peak and the fat peak, and calculate the water-lipid separation result; a data processing unit, used to apply a magnetic resonance thermometry method based on the water proton resonance frequency to the water signal and fit and smooth it to obtain a smoothed temperature result; and a second calculation unit, used to input a pre-constructed magnetic resonance water-lipid model according to the smoothed temperature result, iterate on multiple related parameters, and output the phase of the water signal and the phase of the fat signal.

[0019] A third aspect of this application provides an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the magnetic resonance temperature imaging method based on echo plane time-resolved sequence as described in the above embodiments.

[0020] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described magnetic resonance temperature imaging method based on echo-plane time-resolved sequences.

[0021] This application combines echo-plane time-resolved sequences with a water-lipid thermometry algorithm. Based on a preset echo-plane time-resolved sequence, it acquires multi-echo data of the target human tissue and inputs it into a pre-constructed magnetic resonance water-lipid signal model. Multiple relevant parameters are iterated to extract water and fat signals from the target human tissue, determine the temperature-affected phase portion of water protons, and obtain the actual temperature distribution of the target human tissue. This improves scanning speed, meets the requirements of real-time imaging, and overcomes the image distortion phenomenon of echo-plane sequences. It yields real-time magnetic resonance temperature measurement results with higher robustness, higher accuracy, higher temporal resolution, and wider applicability. Therefore, it solves the technical problems in related technologies where real-time temperature monitoring is difficult for scanning areas requiring high temporal or spatial resolution, and where artifacts in the scanning results significantly impact treatment outcomes.

[0022] Additional aspects and advantages of this application 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 this application. Attached Figure Description

[0023] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0024] Figure 1 This is a flowchart of a magnetic resonance thermal imaging method based on echo plane time-resolved sequences provided in an embodiment of this application;

[0025] Figure 2 This is a schematic diagram of an EPTI (echo planar time-resolved imaging) sequence for a magnetic resonance temperature imaging method based on an echo planar time-resolved sequence according to an embodiment of this application.

[0026] Figure 3This is a schematic diagram of the EPTI sequence k-space data acquisition trajectory of a magnetic resonance temperature imaging method based on echo plane time-resolved sequences according to an embodiment of this application;

[0027] Figure 4 This is a schematic diagram illustrating the principle of GRAPPA reconstruction of EPTI data using a magnetic resonance temperature imaging method based on echo plane time-resolved sequences according to an embodiment of this application.

[0028] Figure 5 This is a flowchart of a magnetic resonance thermal imaging method based on echo plane time-resolved sequences according to an embodiment of this application;

[0029] Figure 6 This is a schematic diagram of a magnetic resonance thermal imaging device based on echo plane time-resolved sequences according to an embodiment of this application.

[0030] Figure 7 This is a schematic diagram of the structure of an electronic device provided according to an embodiment of this application. Detailed Implementation

[0031] The embodiments of this application are described in detail below. Examples of these embodiments are shown 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 this application, and should not be construed as limiting this application.

[0032] The following describes a magnetic resonance temperature imaging method and apparatus based on echo-plane time-resolved sequences according to embodiments of this application, with reference to the accompanying drawings. Addressing the technical problems mentioned in the background section of the related technologies, such as the difficulty in real-time temperature monitoring for scanning areas requiring high temporal or spatial resolution, and the presence of artifacts in the scanning results that significantly impact treatment outcomes, this application provides a magnetic resonance temperature imaging method based on echo-plane time-resolved sequences. This method combines echo-plane time-resolved sequences with a water-lipid thermometry algorithm. Multi-echo data of the target human tissue is acquired based on a preset echo-plane time-resolved sequence and input into a pre-constructed magnetic resonance water-lipid signal model. Multiple relevant parameters are iterated to extract water and fat signals from the target human tissue, determine the temperature-affected phase portion of water protons, and obtain the actual temperature distribution of the target human tissue. This improves scanning speed, meets the requirements for real-time imaging, overcomes the image distortion phenomenon of the echo-plane sequence family, and yields real-time magnetic resonance temperature measurement results with higher robustness, higher accuracy, higher temporal resolution, and wider applicability. This solves the technical problem in related technologies where it is difficult to monitor the temperature in real time for scanning areas with high temporal or spatial resolution requirements, and where scanning results contain artifacts that significantly affect treatment outcomes.

[0033] Specifically, Figure 1 This is a schematic flowchart of a magnetic resonance temperature imaging method based on echo plane time-resolved sequence provided in an embodiment of this application.

[0034] like Figure 1 As shown, the magnetic resonance temperature imaging method based on echo-plane time-resolved sequences includes the following steps:

[0035] In step S101, multi-echo data of the target human tissue are acquired based on a preset echo plane time-resolved sequence.

[0036] Understandably, unlike traditional surgical treatments, chemotherapy, and radiotherapy, tumor hyperthermia surgery has advantages such as fewer side effects, faster postoperative recovery, and less damage to the human body, earning it the title of "green therapy." Depending on the temperature range during treatment, tumor hyperthermia surgery is divided into cryogenic hyperthermia and tumor ablation. Cryogenic hyperthermia primarily utilizes the tumor's sensitivity to temperature changes, heating the tumor area to 43°C to 50°C. Within this temperature range, normal human cells and tissues are not damaged, but tumor cells become more sensitive to drugs and radiation, or are induced to undergo apoptosis, ultimately killing tumor cells and protecting normal tissue. Tumor ablation methods reach temperatures of 50°C to 60°C, or even higher, directly causing tumor cells to die, become inactivated, and coagulate, ultimately eliminating tumor cells more thoroughly. Compared to cryogenic hyperthermia, tumor ablation has a higher temperature range, resulting in a higher tumor inactivation rate and efficiency, a higher surgical success rate, and a lower recurrence rate, showing promising development prospects and gaining favor among doctors.

[0037] Magnetic resonance thermometry, as a non-invasive spatial temperature distribution measurement technology, can monitor ablation surgery in real time. At the same time, due to its high spatial resolution and high soft tissue contrast, magnetic resonance technology can also be used for preoperative scanning to help with surgical planning and postoperative scanning to help determine the success of the surgery and the effect of tumor ablation.

[0038] To achieve high-precision, robust, and more widely applicable magnetic resonance temperature imaging, it is necessary to separate fat and water signals using multi-echo gradient echo sequences. However, the scanning time of multi-echo gradient echo sequences in related technologies is directly proportional to the spatial resolution. The more detailed the image, the longer the scanning time required, resulting in greater temperature errors and artifacts. EPTI has the potential for downsampling. To obtain higher spatial resolution, it is only necessary to increase the downsampling factor, change the scanning trajectory, and modify the reconstruction algorithm. Within a certain downsampling factor range, higher spatial resolution images can be obtained using the same sequence scanning time.

[0039] Therefore, to solve the above problems, embodiments of this application can use a preset EPTI to acquire multi-echo data of the target human tissue at a faster sequence scanning speed.

[0040] Optionally, in one embodiment of this application, the preset echo plane time-resolved sequence includes pulse lines, layer-selected gradient lines, phase-coded lines, and frequency-coded lines to acquire sawtooth-shaped multi-echo data.

[0041] Specifically, such as Figure 2The image shown is an EPTI sequence diagram, where the first row is pulses, and the second to fourth rows are the layer selection gradient, phase encoding, and frequency encoding, respectively. In this embodiment, the sawtooth data acquisition can be completed by adjusting the size of the phase encoding.

[0042] Compared to the EPI acquisition trajectory in related technologies, the EPTI sequence sawtooth acquisition data, where each pulse excitation only covers a portion of the phase-encoded data in the k-space, can cover the entire k-space through multiple pulse excitations, forming a parallel-line acquisition trajectory. The distance between the "parallel lines" of this acquisition trajectory has two possible scenarios, for example, such as... Figure 3 The upper and lower parallelogram boxes are shown, where the horizontal axis is the echo time and the vertical axis is the magnetic resonance phase coding direction. Each point in the trajectory represents one frequency coding, that is, a line parallel to the kx axis.

[0043] in, Figure 3 For illustrative purposes only, each excitation in this case can cover approximately 15-50 pixels in the phase encoding direction of the k-space, and it takes approximately 4-11 excitations to cover the entire k-space (the specific situation needs to be analyzed, for example, when the frequency encoding direction resolution is 256, using 6 excitations, each excitation covers approximately 44 k-space points).

[0044] Optionally, in one embodiment of this application, acquiring multi-echo data of a target human tissue based on a preset echo plane time-resolved sequence includes: determining the data trajectory of the echo plane time-resolved sequence data; performing data convolution on the echo plane time-resolved sequence data based on the data trajectory to reconstruct multiple magnetic resonance images with different echo times.

[0045] As one possible approach, embodiments of this application can select a reconstruction mode based on EPTI data trajectories, convolve the EPTI data, and then reconstruct multiple magnetic resonance images with different echo times to achieve magnetic resonance image reconstruction.

[0046] The embodiments of this application can combine the EPTI sequence with the water-lipid temperature measurement algorithm. Compared with the traditional multi-echo gradient echo sequence, the EPTI sequence has a faster scanning speed, achieving the requirements of near real-time imaging, thereby getting rid of the image distortion phenomenon of the planar echo sequence family.

[0047] Optionally, in one embodiment of this application, multiple magnetic resonance images with different echo times are reconstructed, including: acquiring full-sample data of the acquisition portion; training a W matrix using the full-sample data; and performing data convolution based on the W matrix to reconstruct the magnetic resonance images.

[0048] Specifically, the reconstruction principle can be as follows: Figure 4As shown, embodiments of this application can select a reconstruction mode (such as...) based on EPTI data trajectories. Figure 4 As shown in (c), the upper and lower parallelogram boxes represent the two modes required for reconstruction (predicting unknown data points based on known data points). A small portion of the full-sample data is collected, and the W matrix is ​​obtained by training the GRAPPA kernel using the full-sample data. The EPTI data is then convolved to finally reconstruct complete, distortion-free magnetic resonance images with different echo times, as shown. Figure 4 As shown in (d), each vertical line represents the frequency domain of a complete image, and the number of vertical lines represents the number of echo times, i.e., the number of images obtained in a single scan. Ultimately, a single EPTI scan is reconstructed using GRAPPA to obtain multiple magnetic resonance images with different echo times.

[0049] The training formula for the W matrix can be shown below:

[0050]

[0051] In this embodiment, EPTI can employ CAIPI trajectory scanning, obtaining highly downsampled and uniformly distributed data through multiple pulse excitations. Parallel image reconstruction is performed using the GRAPPA algorithm to obtain images without phase accumulation and signal attenuation. Due to its high downsampling factor, the echo plane time-resolved sequence has high temporal resolution, making it highly valuable for clinical applications. In this embodiment, it can be combined with the magnetic resonance water-lipid signal model to solve the problems of slow scanning speed and large artifacts in traditional temperature measurement methods.

[0052] In step S102, the multi-echo data is input into the pre-constructed magnetic resonance water-fat signal model, and multiple related parameters are iterated to extract the water and fat signals of the target human tissue.

[0053] In some embodiments, multi-echo data can be input into a pre-constructed magnetic resonance water-fat signal model for processing, and multiple relevant parameters can be iterated to extract water and fat signals from the target human tissue.

[0054] Among them, the magnetic resonance water-fat signal model can be a model that includes magnetic resonance water signals, magnetic resonance fat signals, and the influence of magnetic field drift.

[0055] Optionally, in one embodiment of this application, multi-echo data is input into a pre-constructed magnetic resonance water-lipid signal model, and multiple related parameters are iterated to extract water and fat signals from the target human tissue. This includes: obtaining the current water-lipid chemical shifts of the water peak and fat peak, and calculating the water-lipid separation result; applying a magnetic resonance thermometry method based on the water proton resonance frequency to the water signal and fitting and smoothing it to obtain a smoothed temperature result; inputting the smoothed temperature result into the pre-constructed magnetic resonance water-lipid model, iterating multiple related parameters, and outputting the water signal phase and fat signal phase.

[0056] In actual implementation, the solution iteration process of this application embodiment can be as follows:

[0057] S1: The embodiments of this application can initialize the temperature distribution, such as assuming the initial human body temperature is 37°C and assuming the temperature change ΔT = 0, at which time the number of measurements m = 1.

[0058] S2: For the m-th measurement, the embodiments of this application can update the chemical shifts of the water peak and the fat peak according to the current temperature change ΔT.

[0059] S3: In this embodiment of the application, the IDEAL (Iterative Decomposition of Water and Fat With Echo Asymmetry and Least-Squares Estimation) water-fat separation operation can be performed based on the updated water-fat chemical shift to obtain the initial water term, fat term, and magnetic field drift term.

[0060] S4: In this embodiment of the application, the temperature can be obtained by using the PRF magnetic resonance temperature measurement method (i.e., the magnetic resonance temperature measurement method in the related art) when the fat content of the pixel is ≤5% based on the result of water-fat separation; otherwise, proceed to step 5.

[0061] S5: The embodiments of this application can perform low-order fitting and smoothing on discrete temperature points to obtain a coarse global temperature distribution.

[0062] S6: In this embodiment of the application, the smoothed temperature result obtained in step S5 can be used to input into the magnetic resonance water-fat model to iterate on other parameters (water signal, fat signal, magnetic field drift, water relaxation time, fat relaxation time). During the iteration process, the phase of the water signal and the phase of the fat signal are constrained to be in the range of [-π, π], the water relaxation time is constrained to be in the range of [0ms, 2000ms], and the fat relaxation time is constrained to be in the range of [0ms, 200ms].

[0063] S7: In this embodiment of the application, it can be assumed that the field drift within the field of view is sufficiently smooth and small, and the field drift term is low-pass filtered.

[0064] S8: In this embodiment of the application, the field drift term after low-pass filtering and the phase of the water signal and the phase of the fat signal calculated in step S6 can be substituted into the magnetic resonance water-fat model to calculate other parameters (amplitude of water signal, replication of fat signal, temperature).

[0065] S9: In this embodiment of the application, after obtaining the current temperature distribution, the next frame can be entered, and step S202 can be skipped to continue the iteration.

[0066] In step S103, the phase portion of water protons affected by temperature is determined based on water and fat signals to obtain the actual temperature distribution of the target human tissue.

[0067] Furthermore, in the embodiments of this application, the water signal and the fat signal can be processed separately during the process of solving the model based on the multi-echo signal, thereby extracting the phase part of the water proton that is affected by temperature, improving the robustness and applicability of the algorithm.

[0068] Combination Figures 2 to 5 As shown, an embodiment is used to illustrate in detail the working principle of the magnetic resonance temperature imaging method based on echo plane time-resolved sequence of this application.

[0069] like Figure 5 As shown, embodiments of this application may include the following steps:

[0070] Step S501: Data Acquisition. In this embodiment, EPTI can be used for data acquisition to obtain multi-echo data, such as... Figure 2 The image shown is an EPTI sequence diagram, where the first row is pulses, and the second to fourth rows are the layer selection gradient, phase encoding, and frequency encoding, respectively. In this embodiment, the sawtooth data acquisition can be completed by adjusting the size of the phase encoding.

[0071] Compared to the EPI acquisition trajectory in related technologies, the EPTI sequence sawtooth acquisition data, where each pulse excitation only covers a portion of the phase-encoded data in the k-space, can cover the entire k-space through multiple pulse excitations, forming a parallel-line acquisition trajectory. The distance between the "parallel lines" of this acquisition trajectory has two possible scenarios, for example, such as... Figure 3 The upper and lower parallelogram boxes are shown, where the horizontal axis is the echo time and the vertical axis is the magnetic resonance phase coding direction. Each point in the trajectory represents one frequency coding, that is, a line parallel to the kx axis.

[0072] in, Figure 3For illustrative purposes only, each excitation in this case can cover approximately 15-50 pixels in the phase encoding direction of the k-space, and it takes approximately 4-11 excitations to cover the entire k-space (the specific situation needs to be analyzed, for example, when the frequency encoding direction resolution is 256, using 6 excitations, each excitation covers approximately 44 k-space points).

[0073] Step S502: Image reconstruction. Specifically, the reconstruction principle can be as follows: Figure 4 As shown, embodiments of this application can select a reconstruction mode (such as...) based on EPTI data trajectories. Figure 4 As shown in (c), the upper and lower parallelogram boxes represent the two modes required for reconstruction (predicting unknown data points based on known data points). A small portion of the full-sample data is collected, and the W matrix is ​​obtained by training the GRAPPA kernel using the full-sample data. The EPTI data is then convolved to finally reconstruct complete, distortion-free magnetic resonance images with different echo times, as shown. Figure 4 As shown in (d), each vertical line represents the frequency domain of a complete image, and the number of vertical lines represents the number of echo times, i.e., the number of images obtained in a single scan. Ultimately, a single EPTI scan is reconstructed using GRAPPA to obtain multiple magnetic resonance images with different echo times.

[0074] The training formula for the W matrix can be shown below:

[0075]

[0076] Step S503: Obtain the actual temperature distribution of the target human tissue. In some embodiments, multi-echo data can be input into a pre-constructed magnetic resonance water-fat signal model for processing, iterating on multiple relevant parameters to extract water and fat signals from the target human tissue.

[0077] Among them, the magnetic resonance water-fat signal model can be a model that includes magnetic resonance water signals, magnetic resonance fat signals, and the influence of magnetic field drift.

[0078] Furthermore, in the embodiments of this application, the water signal and the fat signal can be processed separately during the process of solving the model based on the multi-echo signal, thereby extracting the phase part of the water proton that is affected by temperature, improving the robustness and applicability of the algorithm.

[0079] In actual implementation, the solution iteration process of this application embodiment can be as follows:

[0080] S1: The embodiments of this application can initialize the temperature distribution, such as assuming the initial human body temperature is 37°C and assuming the temperature change ΔT = 0, at which time the number of measurements m = 1.

[0081] S2: For the m-th measurement, the embodiments of this application can update the chemical shifts of the water peak and the fat peak according to the current temperature change ΔT.

[0082] S3: In this embodiment of the application, the IDEAL water-lipid separation operation can be performed based on the updated water-lipid chemical shift to obtain the initial water term, fat term, and magnetic field drift term.

[0083] S4: In this embodiment of the application, the temperature can be obtained by using the PRF magnetic resonance temperature measurement method (i.e., the magnetic resonance temperature measurement method in the related art) when the fat content of the pixel is ≤5% based on the result of water-fat separation; otherwise, proceed to step 5.

[0084] S5: The embodiments of this application can perform low-order fitting and smoothing on discrete temperature points to obtain a coarse global temperature distribution.

[0085] S6: In this embodiment of the application, the smoothed temperature result obtained in step S5 can be used to input into the magnetic resonance water-fat model to iterate on other parameters (water signal, fat signal, magnetic field drift, water relaxation time, fat relaxation time). During the iteration process, the phase of the water signal and the phase of the fat signal are constrained to be in the range of [-π, π], the water relaxation time is constrained to be in the range of [0ms, 2000ms], and the fat relaxation time is constrained to be in the range of [0ms, 200ms].

[0086] S7: In this embodiment of the application, it can be assumed that the field drift within the field of view is sufficiently smooth and small, and the field drift term is low-pass filtered.

[0087] S8: In this embodiment of the application, the field drift term after low-pass filtering and the phase of the water signal and the phase of the fat signal calculated in step S6 can be substituted into the magnetic resonance water-fat model to calculate other parameters (amplitude of water signal, replication of fat signal, temperature).

[0088] S9: In this embodiment of the application, after obtaining the current temperature distribution, the next frame can be entered, and step S202 can be skipped to continue the iteration.

[0089] The magnetic resonance temperature imaging method based on echo-plane time-resolved sequences proposed in this application combines echo-plane time-resolved sequences with a water-lipid thermometry algorithm. It acquires multi-echo data of the target human tissue based on a preset echo-plane time-resolved sequence, inputs it into a pre-constructed magnetic resonance water-lipid signal model, and iterates on multiple relevant parameters to extract water and fat signals from the target human tissue. This determines the temperature-affected phase portion of water protons, thereby obtaining the actual temperature distribution of the target human tissue. This improves scanning speed, meets the requirements of real-time imaging, and overcomes the image distortion phenomenon of echo-plane sequences. It yields real-time magnetic resonance temperature measurement results with higher robustness, higher accuracy, higher temporal resolution, and wider applicability. Therefore, it solves the technical problems in related technologies where real-time temperature monitoring is difficult for scanning areas requiring high temporal or spatial resolution, and where artifacts in the scanning results significantly impact treatment outcomes.

[0090] Next, referring to the accompanying drawings, a magnetic resonance temperature imaging device based on echo plane time-resolved sequences according to an embodiment of this application is described.

[0091] Figure 6 This is a block diagram of a magnetic resonance temperature imaging device based on echo plane time-resolved sequence according to an embodiment of this application.

[0092] like Figure 6 As shown, the magnetic resonance temperature imaging device 10 based on echo plane time-resolved sequence includes: acquisition module 100, extraction module 200 and acquisition module 300.

[0093] Specifically, the acquisition module 100 is used to acquire multi-echo data of the target human tissue based on a preset echo plane time-resolved sequence.

[0094] The extraction module 200 is used to input multi-echo data into a pre-constructed magnetic resonance water-fat signal model, iterate on multiple relevant parameters, and extract water and fat signals from the target human tissue.

[0095] The acquisition module 300 is used to determine the temperature-affected phase portion of water protons based on water and fat signals in order to obtain the actual temperature distribution of the target human tissue.

[0096] Optionally, in one embodiment of this application, the acquisition module 100 includes: a determination unit and a convolution unit.

[0097] The determining unit is used to determine the data trajectory of the echo plane time-resolved sequence data.

[0098] The convolutional unit is used to perform data convolution on the echo plane time-resolved sequence data based on the data trajectory, and to restore multiple magnetic resonance images with different echo times.

[0099] Optionally, in one embodiment of this application, the convolutional unit includes: a acquisition subunit and a reconstruction subunit.

[0100] The acquisition subunit is used to acquire a portion of the full-collection data; the training subunit is used to train the W matrix using the full-collection data.

[0101] The reconstruction subunit is used to perform data convolution based on the W matrix to reconstruct the magnetic resonance image.

[0102] Optionally, in one embodiment of this application, the preset echo plane time-resolved sequence includes pulse lines, layer-selected gradient lines, phase-coded lines, and frequency-coded lines to acquire sawtooth-shaped multi-echo data.

[0103] Optionally, in one embodiment of this application, the extraction module 200 includes: a first calculation unit, a data processing unit, and a second calculation unit.

[0104] The first calculation unit is used to obtain the current water-lipid chemical shifts of the water peak and the fat peak, and to calculate the water-lipid separation results.

[0105] The data processing unit is used to apply a magnetic resonance thermometry method based on the water proton resonance frequency to the water signal and to fit and smooth it to obtain a smoothed temperature result.

[0106] The second calculation unit is used to input a pre-built magnetic resonance water-lipid model based on the smoothed temperature result, iterate on multiple related parameters, and output the phase of the water signal and the phase of the fat signal.

[0107] It should be noted that the foregoing explanation of the embodiment of the magnetic resonance thermal imaging method based on echo plane time-resolved sequence also applies to the magnetic resonance thermal imaging device based on echo plane time-resolved sequence in this embodiment, and will not be repeated here.

[0108] The magnetic resonance temperature imaging device based on echo-plane time-resolved sequences proposed in this application combines echo-plane time-resolved sequences with a water-lipid temperature measurement algorithm. It acquires multi-echo data of the target human tissue based on a preset echo-plane time-resolved sequence, inputs it into a pre-constructed magnetic resonance water-lipid signal model, iterates on multiple relevant parameters, and extracts water and fat signals from the target human tissue. This determines the temperature-affected phase portion of water protons, thereby obtaining the actual temperature distribution of the target human tissue. This improves scanning speed, meets the requirements of real-time imaging, and overcomes the image distortion phenomenon of echo-plane sequences, resulting in more robust, accurate, temporally resolved, and widely applicable real-time magnetic resonance temperature measurement results. Therefore, it solves the technical problems in related technologies where real-time temperature monitoring is difficult for scanning areas requiring high temporal or spatial resolution, and where artifacts in the scanning results significantly affect treatment outcomes.

[0109] Figure 7 A schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device may include:

[0110] The memory 701, the processor 702, and the computer program stored on the memory 701 and executable on the processor 702.

[0111] When the processor 702 executes the program, it implements the magnetic resonance temperature imaging method based on echo plane time-resolved sequence provided in the above embodiments.

[0112] Furthermore, electronic devices also include:

[0113] Communication interface 703 is used for communication between memory 701 and processor 702.

[0114] The memory 701 is used to store computer programs that can run on the processor 702.

[0115] The memory 701 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0116] If the memory 701, processor 702, and communication interface 703 are implemented independently, then the communication interface 703, memory 701, and processor 702 can be interconnected via a bus to complete communication between them. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, 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.

[0117] Optionally, in a specific implementation, if the memory 701, processor 702, and communication interface 703 are integrated on a single chip, then the memory 701, processor 702, and communication interface 703 can communicate with each other through an internal interface.

[0118] The processor 702 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0119] This embodiment also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the magnetic resonance temperature imaging method based on echo plane time-resolved sequences as described above.

[0120] In the description of this specification, the 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 this application. 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. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0121] 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 application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0122] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0123] 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 programmable read-only memory (EPROM or flash memory), fiber optic devices, and...

[0124] Portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium could even be paper or other suitable media on which the programs described above can be printed, since the programs can be obtained electronically by optically scanning the paper or other media, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0125] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above-described embodiments...

[0126] In this implementation, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, the following techniques known in the art can be used.

[0127] Any one or a combination thereof can be used to implement the following: discrete logic circuits with logic gates for implementing logic functions on data signals, application-specific integrated circuits with suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0128] Those skilled in the art will understand that all or part of the steps of the methods described in the above embodiments can be implemented by a program instructing related hardware, and the program can be stored in a computer-readable storage medium.

[0129] When executed, the program includes one or a combination of steps from the method embodiments.

[0130] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing module, or each unit can exist physically separately, or two or more units can be integrated into one module. The integrated module described above...

[0131] It can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored on a computer-readable storage device.

[0132] Take it from the storage medium.

[0133] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A magnetic resonance temperature imaging method based on echo-plane time-resolved sequences, characterized in that, Includes the following steps: Multi-echo data of target human tissue were acquired based on a preset echo plane time-resolved sequence. The multi-echo data is input into a pre-constructed magnetic resonance water-fat signal model, and multiple related parameters are iterated to extract the water and fat signals of the target human tissue. as well as Based on the water signal and the fat signal, the phase portion of the water protons affected by temperature is determined to obtain the actual temperature distribution of the target human tissue; The step of inputting the multi-echo data into a pre-constructed magnetic resonance water-fat signal model, iterating on multiple relevant parameters, and extracting the water and fat signals of the target human tissue includes: Obtain the current water-lipid chemical shifts of the water peak and the lipid peak, and calculate the water-lipid separation results; A magnetic resonance thermometry method based on the water proton resonance frequency was used to fit and smooth the water signal to obtain a smoothed temperature result. Based on the smoothed temperature result, a pre-constructed magnetic resonance water-lipid model is input, and multiple related parameters are iterated to output the phase of the water signal and the phase of the fat signal. Among them, the multiple related parameters include at least water signal, fat signal, magnetic field drift, water relaxation time, and fat relaxation time; The iterative process constrains the phases of the water signal and the fat signal within a first preset phase range, constrains the relaxation time of the water signal within a first preset time range, and constrains the relaxation time of the fat signal within a second preset time range. The method further includes: The fat percentage is determined based on the water-fat separation results. In response to the fat percentage being less than or equal to a preset threshold, the temperature is obtained using a preset temperature measurement strategy as the smoothed temperature result.

2. The method according to claim 1, characterized in that, The acquisition of multi-echo data of target human tissue based on a preset echo plane time-resolved sequence includes: Determine the data trajectory of the echo plane time-resolved sequence data; Based on the data trajectory, the echo plane time-resolved sequence data is convolved to reconstruct multiple magnetic resonance images with different echo times.

3. The method according to claim 2, characterized in that, The reconstruction yields multiple magnetic resonance images with different echo times, including: The data collected in the acquisition section is all collected; The W matrix is ​​obtained by training using the fully collected data; The magnetic resonance image is reconstructed by performing data convolution based on the W matrix.

4. The method according to claim 1, characterized in that, The preset echo plane time-resolved sequence includes pulse rows, layer-selected gradient rows, phase-coded rows, and frequency-coded rows to acquire sawtooth-shaped multi-echo data.

5. A magnetic resonance temperature imaging device based on echo-plane time-resolved sequences, characterized in that, include: The acquisition module is used to acquire multi-echo data of target human tissue based on a preset echo plane time-resolved sequence; The extraction module is used to input the multi-echo data into a pre-constructed magnetic resonance water-fat signal model, iterate on multiple related parameters, and extract the water and fat signals of the target human tissue. as well as The acquisition module is used to determine the temperature-affected phase portion of water protons based on the water signal and the fat signal, so as to obtain the actual temperature distribution of the target human tissue; The extraction module inputs the multi-echo data into a pre-constructed magnetic resonance water-fat signal model, iterates on multiple relevant parameters, and extracts the water and fat signals of the target human tissue. It is also used for: Obtain the current water-lipid chemical shifts of the water peak and the lipid peak, and calculate the water-lipid separation results; A magnetic resonance thermometry method based on the water proton resonance frequency was used to fit and smooth the water signal to obtain a smoothed temperature result. Based on the smoothed temperature result, a pre-constructed magnetic resonance water-lipid model is input, and multiple related parameters are iterated to output the phase of the water signal and the phase of the fat signal. The extraction module determines that the multiple related parameters include at least water signal, fat signal, magnetic field drift, water relaxation time, and fat relaxation time. The extraction module determines that the phases of the constrained water signal and the fat signal during the iterative process are within a first preset phase range, the constrained water relaxation time is within a first preset time range, and the constrained fat relaxation time is within a second preset time range. The extraction module is also used for: The fat percentage is determined based on the water-fat separation results. In response to the fat percentage being less than or equal to a preset threshold, the temperature is obtained using a preset temperature measurement strategy as the smoothed temperature result.

6. The apparatus according to claim 5, characterized in that, The acquisition module includes: A determining unit is used to determine the data trajectory of echo plane time-resolved sequence data; The convolution unit is used to perform data convolution on the echo plane time-resolved sequence data based on the data trajectory to reconstruct multiple magnetic resonance images with different echo times.

7. The apparatus according to claim 6, characterized in that, The convolutional unit includes: The acquisition subunit is used to acquire a portion of the full-data collection. A training subunit is used to train the W matrix using the full-sampled data; The reconstruction subunit is used to perform data convolution based on the W matrix to reconstruct the magnetic resonance image.

8. The apparatus according to claim 5, characterized in that, The preset echo plane time-resolved sequence includes pulse rows, layer-selected gradient rows, phase-coded rows, and frequency-coded rows to acquire sawtooth-shaped multi-echo data.

9. The apparatus according to claim 5, characterized in that, The extraction module includes: The first calculation unit is used to obtain the current water-lipid chemical shifts of the water peak and the fat peak, and to calculate the water-lipid separation results. The data processing unit is used to apply a magnetic resonance thermometry method based on the water proton resonance frequency to the water signal and to fit and smooth it to obtain a smoothed temperature result. The second calculation unit is used to input a pre-built magnetic resonance water-lipid model based on the smoothed temperature result, iterate on multiple related parameters, and output the phase of the water signal and the phase of the fat signal.

10. An electronic device, characterized in that, include: The memory, the processor, and the computer program stored in the memory and executable on the processor, the processor executing the program to implement the magnetic resonance temperature imaging method based on echo plane time-resolved sequences as described in any one of claims 1-4.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that, The program is executed by a processor to implement the magnetic resonance temperature imaging method based on echo plane time-resolved sequences as described in any one of claims 1-4.

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