Water-fat separation detection method based on SAR value quality control

Abstract

The present invention discloses a water-fat separation detection method based on SAR value quality control, and relates to the field of nuclear magnetic resonance imaging technology. It includes: S1 imaging sequence design stage to collect data for calculating specific absorption rate SAR value; S2 pre-scan sequence data collection includes: emission field map, water-fat separation parameters; S3 emission field map determines the electromagnetic field conditions corresponding to each voxel position, and the T1 weighted image of water-fat separation is used to perform individual-specific modeling of the anatomical structure of the brain, and finally the specific absorption rate SAR value is calculated by Sim4Life software; S4 calculates the specific absorption rate SAR value of other scanning sequences; based on the obtained specific absorption rate SAR value, the heat accumulation of the scanning process is judged, and the order of the current scanning sequence is optimized. The present invention improves the safety of children undergoing nuclear magnetic resonance sequence scanning, the accuracy of image acquisition, and provides medical image support for the diagnosis of ASD.

Description

Technical Field

[0001] The invention relates to the technical field of nuclear magnetic resonance imaging, and in particular to a water-fat separation detection method based on SAR value quality control. Background Art

[0002] In medical magnetic resonance imaging (MRI), chemical shift imaging (also known as spectral imaging) is more conducive to the clear display of lesions and surrounding tissues than conventional selective fat magnetization saturation, water selective excitation and short TI recovery (STIR) fat suppression imaging techniques. It has no special requirements for the uniformity of the radio frequency field B1 and the magnetic field strength, and does not lose the image signal-to-noise ratio. It can also measure the relative proportion of fat and water in the tissue. The names of the water-fat separation imaging scanning sequences of different brands of nuclear magnetic resonance equipment are different. For example, Dixon water-fat separation imaging technology has gradually replaced early fat suppression imaging technology and become an advanced magnetic resonance imaging diagnostic method that is widely used in clinical practice. It has unique value for the clear development of lesions and surrounding tissues under fat suppression conditions and the diagnosis of fat diseases. Compared with the two-point Dixon technology, the three-point Dixon technology is conducive to the accurate attribution of pixels at the water-fat boundary and the elimination of the groove edge effect. Both technologies can actually accurately calculate the initial φ of the echo on the basis of correct phase unwrapping. 0 and phase error φ to eliminate interference from hardware defects and field inhomogeneity effects. However, to date, water-fat separation imaging technology has not been clinically applied to T1-weighted enhanced scanning because the scanning time is difficult to control within 10 seconds, and it is also impossible to avoid the interference of motion artifacts in the imaging process of infants and ADHD patients through ultra-fast scanning, so that the advantages of this technology over other fat suppression technologies cannot be fully utilized in clinical practice. In fact, the excitation and acquisition method of long echo trains is conducive to speeding up the scanning speed. It has been applied in fast spin echo (FSE) and echo planar imaging (EPI) decades ago, but the phase error associated with this excitation and acquisition method will cause a variety of image artifacts. This was once a difficulty faced by the routine application of FSE and EPI and was only solved after a long period of research and development efforts.

[0003] For specific sequences, there are some systematic difficulties in monitoring SAR values. For example, the weight M needs to be entered in the patient information registered before scanning, but this data is often inaccurate for children, a specific scanning group. At the same time, children are in a critical period of brain development and are more sensitive to local hot spots caused by high SAR value sequences than adults. Therefore, it is necessary to determine whether the sequence combination proposed in this consensus is safe and reliable from the perspective of local SAR values.

[0004] Therefore, it is an urgent problem for those skilled in the art to propose a water-fat separation detection method based on SAR value quality control to solve the difficulties existing in the prior art. Summary of the invention

[0005] In view of this, the present invention provides a water-fat separation detection method based on SAR value quality control, which improves the safety of children undergoing nuclear magnetic resonance sequence scanning, the accuracy of image acquisition, and provides medical image support for the diagnosis of ASD.

[0006] In order to achieve the above object, the present invention adopts the following technical solution:

[0007] The water-fat separation detection method based on SAR value quality control includes a magnetic resonance imaging system necessary for the execution of a two-dimensional / three-dimensional imaging sequence and a data processing algorithm. The magnetic resonance imaging system is composed of a magnet that generates a uniform magnetic field, a gradient system that generates a spatial encoding gradient, a radio frequency system that transmits radio frequency pulses and receives magnetic resonance signals, and clinical operation software, and includes the following steps:

[0008] S1, data collection for calculating specific absorption rate SAR value in the imaging sequence design stage;

[0009] S2, pre-scan sequence data acquisition includes: emission field map, water-fat separation parameters;

[0010] S3, the emission field map determines the electromagnetic field conditions corresponding to each voxel position, and the water-fat separated T1-weighted image is used to perform individual-specific modeling of the brain's anatomical structure, and finally the specific absorption rate SAR value is calculated by Sim4Life software;

[0011] S4, calculating the specific absorption rate SAR values ​​of other scanning sequences;

[0012] S5. Determine the heat accumulation in the scanning process based on the obtained specific absorption rate SAR value, and optimize the current scanning sequence order.

[0013] In the above method, optionally, the specific absorption rate SAR value in S1 includes: an overall specific absorption rate SAR value and a local specific absorption rate SAR value.

[0014] In the above method, optionally, the overall specific absorption rate SAR value is automatically monitored by the magnetic resonance device through software and hardware two-layer integration.

[0015] The above method is optional. In the integrated automatic scanning, the calculation formula of the overall specific absorption rate SAR value is as follows:

[0016]

[0017] Where FA is the flip angle, M is the input subject weight, C is a constant related to the coil, machine and sequence, and TR refers to the time interval between two adjacent executions of the pulse sequence.

[0018] In the above method, the pre-scan sequence design in S2, that is, the real-time local SAR value calculation process of the clinical pre-scan is as follows:

[0019] 1) Emission field image acquisition: two FSPGR sequences were used, FOV 24.0 cm × 24.0 cm, 1 mm isotropic resolution 1 mm × 1 mm × 1 mm, matrix 240 × 240, TR 8.5 / 17 ms, TE 3.2 ms, inversion time 450 ms, bandwidth 31.25 Hz, flip angle 12°, and 156 layers;

[0020] 2) Water-fat separation R uses one IDEAL sequence or two FLAIR sequences instead FOV 24.0 cm × 24.0 cm, 2 mm isotropic resolution 2 mm × 2 mm × 2 mm, matrix 120 × 120S layers 120 layers.

[0021] In the above method, optionally, the conventional scanning sequence in S4 includes: axial T2, T1, and diffusion tensor imaging (SDTI).

[0022] In the above method, optionally, the special scanning sequence in S4 includes:

[0023] Three-Dimensional Fast Spoiled Gradient-Recalled, 3D FSPGR;

[0024] Resting-State functional MRIS, rs-fMRI;

[0025] Oxygenation-dependent level imaging BOLD under visual-auditory stimulation;

[0026] Diffusion tensor imaging acquired using a single-shot EPI sequence;

[0027] Inhomogeneous Magnetization Transfer Imaging, ihMTI;

[0028] Arterial Spin Labeling (ASL).

[0029] In the above method, optionally, the monitoring standard in S4 is:

[0030] During the entire scanning process, the maximum value of the overall specific absorption rate SAR must be lower than the overall SAR value limit of 2W / kg specified by the International Electrotechnical Commission (IEC).

[0031] It can be seen from the above technical solution that, compared with the prior art, the present invention provides a water-fat separation detection method based on SAR value quality control, which has the following beneficial effects:

[0032] 1) Analyze the quality control of the serial SAR values ​​to provide a reference for the safe scanning of ASD magnetic resonance imaging in clinical work, so as to obtain high signal-to-noise ratio and high-resolution images;

[0033] 2) It improves the safety of children undergoing MRI sequence scanning, the accuracy of image acquisition, and provides medical image support for the diagnosis of ASD. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0035] Figure 1 The present invention discloses a flow chart of the water-fat separation detection method based on SAR value quality control. DETAILED DESCRIPTION

[0036] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0037] In this application, relational terms such as first and second, etc. are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. The terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of more restrictions, the elements defined by the sentence "comprise one..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0038] Reference Figure 1 As shown, the water-fat separation detection method based on SAR value quality control includes a magnetic resonance imaging system necessary for the execution of a two-dimensional / three-dimensional imaging sequence and a data processing algorithm. The magnetic resonance imaging system is composed of a magnet that generates a uniform magnetic field, a gradient system that generates a spatial encoding gradient, a radio frequency system that transmits radio frequency pulses and receives magnetic resonance signals, and clinical operation software, and includes the following steps:

[0039] S1, data collection for calculating specific absorption rate SAR value in the imaging sequence design stage;

[0040] S2, pre-scan sequence data acquisition includes: emission field map, water-fat separation parameters;

[0041] S3, the emission field map determines the electromagnetic field conditions corresponding to each voxel position, and the water-fat separated T1-weighted image is used to perform individual-specific modeling of the brain's anatomical structure, and finally the specific absorption rate SAR value is calculated by Sim4Life software;

[0042] S4, calculating the specific absorption rate SAR values ​​of other scanning sequences;

[0043] S5. Determine the heat accumulation in the scanning process based on the obtained specific absorption rate SAR value, and optimize the current scanning sequence order.

[0044] Furthermore, the specific absorption rate SAR value in S1 includes: an overall specific absorption rate SAR value and a local specific absorption rate SAR value.

[0045] Furthermore, the overall SAR value is automatically monitored by the MRI device through software and hardware integration.

[0046] Furthermore, in the integrated automatic scan, the overall specific absorption rate SAR value is calculated as follows:

[0047]

[0048] Where FA is the flip angle, M is the input subject weight, C is a constant related to the coil, machine and sequence, and TR refers to the time interval between two adjacent executions of the pulse sequence.

[0049] Furthermore, the pre-scan sequence design in S2, that is, the real-time local SAR value calculation process of the clinical pre-scan is as follows:

[0050] 1) Emission field image acquisition: two FSPGR sequences were used, FOV 24.0 cm × 24.0 cm, 1 mm isotropic resolution 1 mm × 1 mm × 1 mm, matrix 240 × 240, TR 8.5 / 17 ms, TE 3.2 ms, inversion time 450 ms, bandwidth 31.25 Hz, flip angle 12°, and 156 layers;

[0051] 2) Water-fat separation R uses one IDEAL sequence or two FLAIR sequences instead FOV 24.0 cm × 24.0 cm, 2 mm isotropic resolution 2 mm × 2 mm × 2 mm, matrix 120 × 120S layers 120 layers.

[0052] Furthermore, the routine scanning sequences in S4 include: axial T2, T1, Diffusion Tensor Imaging SDTI, the scanning baseline is parallel to the anterior-posterior joint line (AC-PC line), the scanning range covers the foramen magnum to the top of the skull, the coronal T2 FLAIRR is perpendicular to the longitudinal fissure of the brain and parallel to the brainstem, enhanced scanning is performed when necessary, and the positioning is the same as the T1W or T2W sequence. The MRI images obtained by routine scanning can be used to diagnose whether ASD patients suffer from other types of congenital brain diseases or secondary brain function reduction caused by trauma, such as childhood spasms, ADHD, ketoacidosis, multiple sclerosis, adrenal white matter dysplasia, etc.

[0053] Furthermore, the special scanning sequences in S4 have different names for different brands of MRI equipment, as shown below:

[0054] Three-Dimensional Fast Spoiled Gradient-Recalled, 3D FSPGR: Set sagittal imaging in the cross section so that the imaging plane is parallel to the median sagittal fissure of the brain, and parallel to the median sagittal fissure of the brain, brainstem and medulla oblongata in the coronal positioning image, and the scanning range covers the foramen magnum to the top of the skull; use small angle excitation, short TR, short TE parameters, fast scanning speed, high spatial resolution, can clearly display the anatomical structure of the brain, and has good gray matter and white matter contrast, which is very suitable for high-definition structural image scanning; recommended scanning parameters RFOV 24.0cm×24.0cm, 1mm isotropic resolution (1mm×1mm×1mm), matrix 240×240, TR 8.5ms, TE 3.2ms, inversion time 450ms, bandwidth 31.25Hz, flip angle 12°, number of layers 156. By calculating the thickness of the cerebral cortex, gray and white matter, and cerebrospinal fluid volume of the 3D structural image, we conduct research on individual brain structure differences and provide an anatomical position registration template for functional magnetic resonance imaging.

[0055] Resting-State functional MRIS, rs-fMRI: Take the axial imaging orientation, set the transverse plane scanning layer on the sagittal positioning image, make the transverse plane scanning layer parallel to the AC-PC line, and make the transverse plane scanning layer parallel to the line connecting the bases of the temporal lobes on both sides on the coronal positioning image, and the scanning range covers the foramen magnum to the top of the skull. It uses gradient echo, GRE-Echo Planar Imaging, and EPI sequence acquisition, which are very sensitive to changes in magnetic susceptibility, have high temporal resolution, and small motion artifacts. A scan can be completed within a few minutes, and a high spatial resolution is obtained. The recommended scanning parameters are RFOV 19.2cm×19.2cm, layer thickness 3.0mm, 48 layers, matrix 64×64, TR 3000ms, TE 30ms, bandwidth 250Hz, flip angle 85°, interlayer sampling time frame number 120 frames. During the scan, the subjects keep their eyes closed and relaxed. By analyzing the resting state data, the distribution of cerebral cortical functional areas is obtained, and the evaluation of individual brain function is completed, providing targets for clinical precision surgical positioning and rehabilitation intervention.

[0056] Oxygenation-dependent horizontal imaging BOLD under visual-auditory stimulation: take the axial imaging orientation, set the transverse plane scanning layer on the sagittal positioning image, make the transverse plane scanning layer parallel to the AC-PC line, and make the transverse plane scanning layer parallel to the connecting line of the base of the temporal lobe on both sides on the coronal positioning image. The scanning range covers the foramen magnum to the top of the skull. The recommended scanning parameters are RFOV 19.2cm×19.2cm, layer thickness 3.9mm, 36 layers, matrix 64×64, TR 2000ms, TE 30ms, bandwidth 250Hz, flip angle 85°, interleaved slice ordering, frame number 120 frames, and induce changes in oxygenation levels in local functional areas of the brain through visual-auditory stimulation to obtain the distribution of brain activation areas. Event-related stimulation research on cases and normal control children is carried out to provide a basis for assisting clinical early diagnosis of brain function.

[0057] Diffusion tensor imaging acquired using a single-shot EPI sequence: the standard axial imaging orientation is drawn, and the scanning range covers the foramen magnum to the upper edge of the skin on the top of the skull. The single-shot EPI sequence is used for acquisition, which has a fast scanning speed and can quantitatively analyze the fractional anisotropy SFA of brain tissue in different parts; the recommended scanning parameters are RFOV 22.4cm×22.4cm, 2mm isotropic spatial resolution, matrix 112×112, TR 6000ms, minimum TE, 2 T2s, 32 diffusion gradient field directions, diffusion weighted gradient value b=800s / mm2, 2 excitations, and a flip angle of 90°. By quantitatively analyzing the diffusion tensor parameters, the direction and connection characteristics of the brain or cortical fiber bundles can be obtained, the functional analysis between brain regions can be completed, and the distribution of white matter fiber bundles in the corticospinal tract, motor area, and sensorimotor area can be provided for clinical surgical navigation.

[0058] Inhomogeneous Magnetization Transfer Imaging (ihMTI): The sagittal imaging orientation is taken, the imaging plane is parallel to the median sagittal fissure of the brain, and the scanning range covers the foramen magnum to the top of the skull; the ihMTI sequence assumes that the magnetization transfer (MT) effect of the white matter is uneven, which can better reflect the real structure of the white matter and generate quantitative parameters such as magnetization transfer ratio (MTR), quantitative magnetization transfer ratio, inhomogeneous magnetization transfer ratio, and inhomogeneous quantitative magnetization transfer ratio, which can accurately reflect the changes in the myelin content of the white matter. The sagittal ihMTI is acquired using a 3D FSPGR sequence, with TR 14.4ms, minimum TE, FOV 23cm×23cm, matrix 96×96S, layer thickness 3.2mm, flip angle 8°, and a total of 22 phases; by calculating the inhomogeneous magnetization transfer imaging parameters, the characteristic values ​​of the brain area of ​​interest are obtained, and the difference analysis between white matter diseases and normal control subjects is completed, providing auxiliary support for the early diagnosis of clinical diseases.

[0059] Arterial Spin Labeling (ASL): Arterial Spin Labeling (ASL) imaging scans take the standard axial imaging orientation, and the scanning range covers the foramen magnum to the top of the skull. The hydrogen protons in the arterial blood are labeled as endogenous tracers, and then delayed imaging is performed to acquire an image with ASL (labeled image) and an image without ASL (control image) once each. The control image and the labeled image are then subtracted to obtain a blood flow perfusion image. ASL is an absolutely quantitative perfusion technique that can not only qualitatively but also quantitatively calculate the characteristic parameter of cerebral blood flow (SCBF) perfusion, and has no side effects of exogenous contrast agents, making it particularly suitable for children's examinations. All perfusion and reference images are obtained through three-dimensional spiral stacking rapid acquisition and refocusing echo imaging sequences. The recommended scanning parameters are RFOV 24.0 cm×24.0 cm, layer thickness 4.0 mm, 36 layers with 3 excitation times; TR 4632 ms, PLD 1500ms, TE10.5ms, bandwidth6250Hz, flip angle90°.

[0060] Furthermore, arterial spin labeling (ASL) allows CBF measurement and functional connectivity analysis on perfusion image series, detecting regional CBF changes in ASD individuals by minimizing the potential contribution of blood oxygenation level dependence and further exploring the correlation between ASD features and CBF changes.

[0061] Furthermore, the monitoring standards in S4 are:

[0062] During the entire scanning process, the maximum value of the overall specific absorption rate SAR must be lower than the overall SAR value limit of 2W / kg specified by the International Electrotechnical Commission (IEC).

[0063] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can refer to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system or system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can refer to the partial description of the method embodiment. The system and system embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without creative work.

[0064] In order to clearly illustrate the interchangeability of hardware and software, the above description has generally described the components and steps of each example according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0065] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A water-fat separation detection method based on SAR value quality control is implemented based on a magnetic resonance imaging system necessary for the execution of a two-dimensional / three-dimensional imaging sequence and a data processing algorithm. The magnetic resonance imaging system consists of a magnet that generates a uniform magnetic field, a gradient system that generates a spatial encoding gradient, a radio frequency system that transmits radio frequency pulses and receives magnetic resonance signals, and clinical operation software, and is characterized in that: The following steps are involved: S1. Data collection for calculating specific absorption rate (SAR) values ​​during the imaging sequence design phase; S2, pre-scan sequence data acquisition includes: emission field map, water-fat separation parameters; S3, the emission field map determines the electromagnetic field conditions corresponding to each voxel position, and the water-fat separated T1-weighted image is used to perform individual-specific modeling of the brain's anatomical structure, and finally the specific absorption rate SAR value is calculated by Sim4Life software; S4, calculating the specific absorption rate SAR values ​​of other scanning sequences; S5. Determine the heat accumulation in the scanning process based on the obtained specific absorption rate SAR value, and optimize the current scanning sequence order; The specific absorption rate SAR value in S1 includes: overall specific absorption rate SAR value and local specific absorption rate SAR value; The overall specific absorption rate SAR value is automatically monitored by the magnetic resonance device through two levels of integration, software and hardware; In integrated automatic scanning, the overall SAR value is calculated as follows: Where FA is the flip angle, M is the input subject weight, C is a constant related to the coil, machine and sequence, and TR refers to the time interval between two adjacent executions of the pulse sequence; The pre-scan sequence design in S2, that is, the real-time local SAR value calculation process of clinical pre-scan is as follows: 1) Emission field image acquisition: two FSPGR sequences were used, FOV 24.0 cm×24.0 cm, 1 mm isotropic resolution 1 mm×1 mm×1 mm, matrix 240×240, TR 8.5 / 17 ms, TE 3.2 ms, inversion time 450 ms, bandwidth 31.25 Hz, flip angle 12°, and 156 layers; 2) Water-fat separation: use one IDEAL sequence or replace it with two FLAIR sequences, FOV 24.0 cm × 24.0 cm, 2 mm isotropic resolution 2 mm × 2 mm × 2 mm, matrix 120 × 120, and 120 layers.

2. The water-fat separation detection method based on SAR value quality control according to claim 1 is characterized in that: The conventional scanning sequences in S4 include: axial T2, T1, and diffusion tensor imaging SDTI.

3. The water-fat separation detection method based on SAR value quality control according to claim 1 is characterized in that: Special scan sequences in S4 include: Three-Dimensional Fast Spoiled Gradient-Recalled, 3D FSPGR; Resting-State functional MRIS, rs-fMRI; Oxygenation-dependent level imaging BOLD under visual-auditory stimulation; Diffusion tensor imaging acquired using a single-shot EPI sequence; Inhomogeneous Magnetization Transfer Imaging, ihMTI; Arterial Spin Labeling (ASL).

4. The water-fat separation detection method based on SAR value quality control according to claim 1, characterized in that: The monitoring standards in S4 are: During the entire scanning process, the maximum value of the overall specific absorption rate SAR must be lower than the overall SAR value limit of 2W / kg specified by the International Electrotechnical Commission (IEC).

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