A magnetic resonance imaging method and system

Abstract

The present specification relates to the field of magnetic resonance imaging, and in particular to a method and system for magnetic resonance imaging. The method comprises: acquiring at least two groups of B1 image signals corresponding to each of at least two pulse flip angles based on the at least two pulse flip angles; determining relative B1 field information of the at least two pulse flip angles based on the at least two groups of B1 image signals; and determining T1 information corresponding to the at least two pulse flip angles based on at least two groups of T1 image signals corresponding to the two pulse flip angles and the relative B1 field information.

Description

Technical Field

[0001] This specification relates to the field of magnetic resonance imaging, and in particular to a magnetic resonance imaging method and system. Background Technology

[0002] Magnetic resonance imaging (MRI) systems utilize strong magnetic fields and radio frequency (RF) technology for widespread application in medical diagnosis and / or treatment. For example, MRI systems can perform various measurements on a subject, such as longitudinal relaxation time (T1) measurements, transverse relaxation time (T2) measurements, and proton density (PD) measurements, to provide a basis for disease diagnosis and / or treatment.

[0003] T1 quantification based on steady-state gradient-recalled echo (GRE) signals primarily involves acquiring signals at different flip angles to obtain steady-state GRE signals with varying T1 weighting. These signals are then fitted to obtain a preliminary T1 quantification map. This preliminary T1 quantification map includes the influence of the B1 field, often requiring additional B1 field information extraction for T1 quantification correction.

[0004] Therefore, it is desirable to provide a magnetic resonance imaging method that can obtain more accurate T1 information. Summary of the Invention

[0005] One embodiment of this specification provides a magnetic resonance imaging method, the method comprising: an image signal acquisition module, configured to acquire at least two sets of B1 image signals corresponding to each of the at least two pulse flip angles; a relative B1 field information determination module, configured to determine relative B1 field information of the at least two pulse flip angles based on the at least two sets of B1 image signals; and a T1 information determination module, configured to determine T1 information corresponding to the at least two pulse flip angles based on the at least two sets of T1 image signals corresponding to the two pulse flip angles and the relative B1 field information.

[0006] One embodiment of this specification provides a magnetic resonance imaging system, comprising: an image signal acquisition module, configured to acquire at least two sets of B1 image signals corresponding to each of the at least two pulse flip angles; a relative B1 field information determination module, configured to determine relative B1 field information of the at least two pulse flip angles based on the at least two sets of B1 image signals; and a T1 information determination module, configured to determine T1 information corresponding to the at least two pulse flip angles based on the at least two sets of T1 image signals corresponding to the two pulse flip angles and the relative B1 field information.

[0007] One embodiment of this specification provides a magnetic resonance imaging apparatus, comprising: at least one storage medium for storing computer instructions; and at least one processor for executing the computer instructions to implement the above-described magnetic resonance imaging method.

[0008] One embodiment of this specification provides a computer-readable storage medium that stores computer instructions. When a computer reads the computer instructions, the computer executes the above-described magnetic resonance imaging method. Attached Figure Description

[0009] This specification will be further described by way of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not limiting; in these embodiments, the same reference numerals denote the same structures, wherein:

[0010] Figure 1 These are schematic diagrams illustrating application scenarios of magnetic resonance imaging systems according to some embodiments of this specification;

[0011] Figure 2 This is a block diagram of an exemplary MR scanner according to some embodiments of this specification;

[0012] Figure 3 These are schematic diagrams of exemplary hardware and / or software components of a computing device according to some embodiments of this specification;

[0013] Figure 4 This is an exemplary flowchart of a magnetic resonance imaging method according to some embodiments of this specification;

[0014] Figure 5 This is a schematic diagram of signal excitation for acquiring B1 image signal scanning pulse sequence according to some embodiments of this specification;

[0015] Figure 6 This is a schematic diagram of signal excitation for acquiring T1 image signal scanning pulse sequences according to some embodiments of this specification;

[0016] Figure 7 This is a graph showing the error variation of R value versus T1 according to some embodiments of this specification;

[0017] Figure 8 This is a graph showing the error variation between the T1 value and the actual T1, based on some embodiments of this specification.

[0018] Figure 9A This is an uncorrected T1 quantification chart shown in some embodiments of this specification;

[0019] Figure 9BThis is a schematic diagram of R representing subject head data according to some embodiments of this specification;

[0020] Figure 9C This is a quantitative T1 chromatogram after R correction, as shown in some embodiments of this specification;

[0021] Figure 10 This is an exemplary block diagram of a magnetic resonance imaging system according to some embodiments of this specification. Detailed Implementation

[0022] To more clearly illustrate the technical solutions of the embodiments in this specification, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are merely some examples or embodiments of this specification. For those skilled in the art, these drawings can be applied to other similar scenarios without creative effort. Unless obvious from the context or otherwise specified, the same reference numerals in the drawings represent the same structures or operations.

[0023] It should be understood that the terms “system,” “device,” “unit,” and / or “module” used herein are one way to distinguish different components, elements, parts, sections, or assemblies at different levels. However, if other terms can achieve the same purpose, they may be replaced by other expressions.

[0024] As indicated in this specification and claims, unless the context clearly indicates otherwise, the words "a," "an," "an," and / or "the" do not specifically refer to the singular and may also include the plural. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of expressly identified steps and elements, which do not constitute an exclusive list, and the method or apparatus may also include other steps or elements.

[0025] Flowcharts are used in this specification to illustrate the operations performed by the system according to embodiments of this specification. It should be understood that the preceding or following operations are not necessarily performed in exact order. Instead, the steps can be processed in reverse order or simultaneously. Furthermore, other operations can be added to these processes, or one or more steps can be removed from them.

[0026] To determine the T1 information of a subject, a magnetization recovery pulse sequence (e.g., inversion recovery pulse sequence, saturation recovery pulse sequence) can be applied to the subject using an MR scanner to acquire echo signals. The T1 information of a physical point can be determined by correlating the signal intensity of the echo signal with the T1 relaxation effect. Another method for T1 measurement can be performed by using an MR scanner to perform multiple acquisitions on the subject with different pulse sequence parameter values ​​(e.g., different flip angles (FAs) or different repetition times). Multiple sets of MRI data can be acquired at different T1 weighting levels at the physical points during the multiple acquisitions. Because the T1 information of a physical point can affect a set of MRI data corresponding to different pulse sequence parameter values, the T1 information of the subject can be determined based on a set of MRI data. However, the implementation of the acquisition can be affected by various factors, such as the hardware limitations of the MR scanner, the wavelength of the B0 field (i.e., the main magnetic field), the wavelength of the B1 field (i.e., the radio frequency field), the dielectric and conductivity properties of the subject, etc.

[0027] Due to these factors, the actual B1 field applied to a physical point during acquisition may deviate from the preset B1 field. Furthermore, the actual B1 field exhibits a non-uniform spatial distribution (i.e., the actual B1 field can have different values ​​at different physical points on the subject), a phenomenon known as B1 inhomogeneity. B1 inhomogeneity can lead to differences between the actual FA at a physical point and the preset FA used for acquisition, which can affect the accuracy of a set of MRI data acquired during the acquisition process and the accuracy of T1 measurements based on that set of MRI data. T1 measurements may need to account for B1 inhomogeneity during acquisition.

[0028] As mentioned earlier, quantitative T1 correction typically requires additional extraction of B1 field information. However, the high coupling between B1 field information and T1 information makes separation difficult, leading to challenges in extracting B1 field spatial information. Therefore, this specification proposes a magnetic resonance imaging method that acquires at least two sets of image signals based on at least two pulse flip angles and determines the relative B1 field information of the pulse flip angles to ascertain T1 information. This method yields higher quality data, which can then be directly used to calculate and obtain quantitative T1 maps.

[0029] It should be noted that the scenarios illustrated in this specification primarily describe measurements of objects (e.g., patients, physical points of patients) within a magnetic resonance imaging (MRI) system. This should be understood as illustrative purposes only. The systems and methods described in this specification can be applied to any other type of medical imaging system. In some embodiments, the imaging system may include a single-modality imaging system and / or a multimodality imaging system. A single-modality imaging system may include, for example, an MRI system. A multimodality imaging system may include, for example, a magnetic resonance imaging-computed tomography (MRI-CT) system, a positron emission tomography-magnetic resonance imaging (PET-MRI) system, a single-photon emission computed tomography-magnetic resonance imaging (SPECT-MRI) system, a digital subtraction angiography-magnetic resonance imaging (DSA-MRI) system, etc.

[0030] Figure 1 This is a schematic diagram illustrating application scenarios of a magnetic resonance imaging system according to some embodiments of this specification.

[0031] like Figure 1 As shown, the MRI system 100 may include an MR scanner 110, a processing device 120, a storage device 130, one or more terminals 140, and a network 150. In some embodiments, the MR scanner 110, processing device 120, storage device 130, and terminals 140 may be connected to and / or communicate with each other via wireless connections, wired connections, or combinations thereof. The connections between components in the MRI system 100 may be variable. For example, the MR scanner 110 may be connected to the processing device 120 via the network 150. As another example, the MR scanner 110 may be directly connected to the processing device 120.

[0032] MR scanner (magnetic resonance scanner) 110 can be configured to scan an object (or a portion of an object) to acquire image data, such as echo signals (or MRI data) associated with the object. For example, MR scanner 110 can detect multiple sets of MRI data by applying a sequence of MR pulses to the object. In some embodiments, MR scanner 110 may include, for example, a magnetic body, gradient coils, RF coils, etc. Figure 2 In some embodiments, depending on the type of magnetic material, the MR scanner 110 may be a permanent magnet MR scanner, a superconducting magnet MR scanner, or a resistive electromagnet MR scanner, etc. In some embodiments, depending on the magnetic field strength, the MR scanner 110 may be a high-field MR scanner, a medium-field MR scanner, or a low-field MR scanner, etc.

[0033] For ease of explanation, Figure 1 It provides a coordinate system including the X-axis, Y-axis, and Z-axis. Figure 1The X and Z axes shown can be horizontal, and the Y axis can be vertical. As shown in the figure, viewed from the front of the MR scanner 110, the positive X direction along the X axis can be from the right side to the left side of the MR scanner 110; along... Figure 1 The positive Y direction of the Y-axis shown can be from the bottom to the top of the MR scanner 110; Figure 1 The positive Z-direction along the Z-axis shown can refer to the direction in which the object moves out of the scanning channel (or aperture) of the MR scanner 110. Further description of the MR scanner 110 can be found elsewhere in this specification. For example, see... Figure 2 And its description.

[0034] Processing device 120 can process data and / or information acquired from MR scanner 110, storage device 130, and / or terminal 140. For example, processing device 120 can determine target values ​​for reference coefficients by processing object-related image data (e.g., MRI data) collected by MR scanner 110, wherein the reference coefficients may be associated with B1 inhomogeneities in multiple acquisitions. As another example, processing device 120 can perform T1 measurements on the object at least in part based on the target values ​​of the reference coefficients. In some embodiments, processing device 120 may be a single server or a group of servers. The server group may be centralized or distributed. In some embodiments, processing device 120 may be local or remote. For example, processing device 120 may access information and / or data from MR scanner 110, storage device 130, and / or terminal 140 via network 150. As another example, processing device 120 may be directly connected to MR scanner 110, terminal 140, and / or storage device 130 to access information and / or data. In some embodiments, processing device 120 may be implemented on a cloud platform. For example, a cloud platform may include a private cloud, public cloud, hybrid cloud, community cloud, distributed cloud, inter-cloud cloud, multi-cloud, or a combination thereof. In some embodiments, the processing device 120 may be equipped with, for example, Figure 3 The computing device 300 with one or more of the aforementioned components is used to implement this.

[0035] Storage device 130 may store data, instructions, and / or any other information. In some embodiments, storage device 130 may store data acquired from MR scanner 110, processing device 120, and / or terminal 140. In some embodiments, storage device 130 may store data and / or instructions that can be executed by processing device 120, or that processing device 120 can use to execute the exemplary methods described herein. In some embodiments, storage device 130 may include a mass storage device, a removable storage device, a volatile read-write memory, a read-only memory (ROM), or a combination thereof. Exemplary mass storage devices may include disks, optical disks, solid-state drives, etc. Exemplary removable storage devices may include flash drives, floppy disks, optical disks, memory cards, compressed disks, magnetic tapes, etc. Exemplary volatile read-write memory may include random access memory (RAM). Exemplary RAM may include dynamic RAM (DRAM), dual data rate synchronous dynamic RAM (DDR-SDRAM), static RAM (SRAM), thyristor RAM (T-RAM), zero-capacitance RAM (Z-RAM), etc. Exemplary ROMs may include mask ROMs (MROMs), programmable ROMs (PROMs), erasable programmable ROMs (EPROMs), electrically erasable programmable ROMs (EEPROMs), optical disc ROMs (CD-ROMs), digital multifunction disk ROMs, etc. In some embodiments, storage device 130 may be implemented on a cloud platform as described elsewhere in this specification.

[0036] In some embodiments, storage device 130 may be connected to network 150 to communicate with one or more other components of MRI system 100 (e.g., MR scanner 110, processing device 120, and / or terminal 140). One or more components of MRI system 100 may access data or instructions stored in storage device 130 via network 150. In some embodiments, storage device 130 may be part of processing device 120 or terminal 140.

[0037] Terminal 140 may be configured to enable user interaction between a user and MRI system 100. For example, terminal 140 may receive instructions from the user to have MR scanner 110 scan an object. Alternatively, terminal 140 may receive processing results (e.g., values ​​of quantitative parameters related to the object or a quantitative map) from processing device 120 and display the results to the user. In some embodiments, terminal 140 may be connected to and communicate with MR scanner 110, processing device 120, and / or storage device 130. In some embodiments, terminal 140 may include mobile device 140-1, tablet computer 140-2, laptop computer 140-3, etc., or combinations thereof. For example, mobile device 140-1 may include mobile phone, personal digital assistant (PDA), gaming device, navigation device, point-of-sale (POS) device, laptop computer, tablet computer, desktop computer, etc., or combinations thereof. In some embodiments, terminal 140 may include input devices, output devices, etc. Input devices may include alphanumeric keys and other keys that can be entered via a keyboard, a touchscreen (e.g., with haptic or haptic feedback), voice input, eye-tracking input, brain monitoring system input, or any other similar input mechanism. Input information received via an input device can be transmitted to processing device 120 via, for example, a bus for further processing. Other types of input devices may include cursor control devices, such as a mouse, trackball, or arrow keys. Output devices may include a display, speakers, a printer, or combinations thereof. In some embodiments, terminal 140 may be part of processing device 120 or MR scanner 110.

[0038] Network 150 may include any suitable network that facilitates the exchange of information and / or data between the MRI system 100 and the MRI system 100. In some embodiments, one or more components of the MRI system 100 (e.g., MR scanner 110, processing device 120, storage device 130, terminal 140, etc.) may transmit information and / or data with one or more other components of the MRI system 100 via network 150. For example, processing device 120 may acquire image data (e.g., echo signals) from MR scanner 110 via network 150. As another example, processing device 120 may acquire user instructions from terminal 140 via network 150. Network 150 may include public networks (e.g., the Internet), private networks (e.g., local area networks (LANs), wide area networks (WANs)), wired networks (e.g., Ethernet), wireless networks (e.g., 802.11 networks, Wi-Fi networks, etc.), cellular networks (e.g., LTE networks), Frame Relay networks, virtual private networks (“VPNs”), satellite networks, telephone networks, routers, hubs, switches, server computers, etc., or combinations thereof. For example, network 150 may include cable networks, wired networks, fiber optic networks, telecommunications networks, intranets, wireless local area networks (WLANs), metropolitan area networks (MANs), public switched telephone networks (PSTNs), and Bluetooth. TM Network, Purple Bee TM Networks, near field communication (NFC) networks, and combinations thereof. In some embodiments, network 150 may include one or more network access points. For example, network 150 may include wired and / or wireless network access points, such as base stations and / or Internet exchange points, through which one or more components of the MRI system 100 may connect to network 150 to exchange data and / or information.

[0039] This description is intended to be illustrative, not limiting. Many alternatives, modifications, and variations will be apparent to those skilled in the art. The features, structures, methods, and characteristics of the exemplary embodiments described herein can be combined in various ways to obtain additional and / or alternative exemplary embodiments. In some embodiments, the MRI system 100 may include one or more additional components and / or one or more components described above may be omitted. Alternatively or additionally, two or more components of the MRI system 100 may be integrated into a single component. For example, processing device 120 may be integrated into MR scanner 110. As another example, a component of the MRI system 100 may be replaced by another component capable of performing the function of that component. In some embodiments, storage device 130 may be a data storage device including a cloud computing platform, such as a public cloud, private cloud, community cloud, and hybrid cloud. However, these variations and modifications do not depart from the scope of this specification.

[0040] Figure 2This is a block diagram of an exemplary MR scanner according to some embodiments of this specification. Figure 2 As shown, the MR scanner 110 may include a magnet 220, a gradient coil 230, an RF coil 240, and a pulse sequence module 250.

[0041] Magnet 220 can generate a static magnetic field during at least a portion of scanning object 210. Magnet 220 can be of various types, including, for example, permanent magnets, superconducting magnets, resistive electromagnets, etc.

[0042] Gradient coil 230 can provide a magnetic field gradient to the main magnetic field in the X, Y, and / or Z directions. As used herein, the X, Y, and Z directions can represent a coordinate system (e.g., with respect to the coordinate system). Figure 1 The X, Y, and Z axes are defined in the same or similar coordinate system described herein. For example, the Z axis may be along the axis of magnet 220, the X and Z axes may form a horizontal plane, and the X and Y axes may form a vertical plane. In some embodiments, gradient coil 230 may include an X-direction coil for providing a magnetic field gradient to the main magnetic field in the X direction, a Y-direction coil for providing a magnetic field gradient to the main magnetic field in the Y direction, and / or a Z-direction coil for providing a magnetic field gradient to the main magnetic field in the Z direction. In some embodiments, the X-direction coil, Y-direction coil, and / or Z-direction coil may have various shapes or configurations. For example, the Z-direction coil may be designed based on a Maxwell coil. As another example, the X-direction coil and Y-direction coil may be designed based on a Golay coil configuration.

[0043] RF coil 240 can transmit RF pulse signals to and / or receive echo signals from the object under inspection 210. In some embodiments, RF coil 240 may include a transmitting coil and a receiving coil. The transmitting coil can transmit a signal (e.g., an RF pulse) that excites atomic nuclei in the object 210 to provide resonance. The receiving coil can receive the echo signals transmitted from the object 210. In some embodiments, the RF transmitting coil and the RF receiving coil can be integrated into a single coil. In some embodiments, RF coil 240 can be of various types, such as quadrature detection (QD) quadrature coils, phased array coils, element-specific spectrum coils, etc. In some embodiments, RF coil 240 can be a phased array coil comprising multiple coil units, each of which can independently detect the echo signal.

[0044] In some embodiments, the RF coil 240 can be used to detect signals generated by an MR pulse sequence. MR pulse sequences can be of various types, such as spin echo (SE) pulse sequences, GRE pulse sequences, inversion recovery (IR) pulse sequences, multi-echo MR pulse sequences, T1p preparation pulse sequences, T2 preparation pulse sequences, diffusion-weighted imaging (DWI) pulse sequences, saturation recovery (SR) pulse sequences, steady-state pulse sequences, etc.

[0045] In some embodiments, the MR pulse sequence can be defined by one or more pulse sequence parameters, including, for example, the type of MR pulse sequence, the time at which the MR pulse sequence is applied, the duration of the MR pulse sequence, the flip angle of the excitation pulses in the MR pulse sequence, the count (or number) of RF pulses in the MR pulse sequence, TR, repetition count, inversion time (TI), the count (or number) acquired in the MR pulse sequence, b-value, T1ρ-preparation duration, T2 preparation duration, echo sequence length, echo interval, velocity coding (VENC) value, etc. As used herein, the FA of the excitation pulse may refer to the rotation of the excitation pulse relative to the net magnetization vector of the main magnetic field. TR may refer to the time interval between two repeating and consecutive RF pulses in the MR pulse sequence (e.g., the time interval between two consecutive excitation RF pulses in an SE pulse sequence, the time interval between two consecutive 180° inversion pulses in an IR pulse sequence). The repetition count may refer to the repetition count (or number of times) in the MR pulse sequence. TI may refer to the time span between a 180° inversion pulse and a subsequent 90° excitation pulse in an IR pulse sequence. The b-value may refer to a factor reflecting the intensity and time of the diffusion sensitization gradient in the DWI pulse sequence. The T1ρ preparation duration refers to the duration of the spin-locked pulse in the T1ρ preparation pulse sequence. The T2 preparation duration can refer to the duration of the T2 preparation pulse in the T2 preparation pulse sequence.

[0046] In some embodiments, the RF coil 240 can detect (or receive) one or more echo signals corresponding to one or more echoes excited by the MR pulse sequence. In some embodiments, the echo signal (or echo) can be defined by one or more parameters, such as echo signal type (spin echo, fast spin echo (FSE), fast recovery FSE, single-shot FSE, gradient echo, fast imaging with steady-state precession), echo time (TE), echo signal intensity, coil unit for detecting the echo signal (e.g., represented as an identifier (ID) for detecting the echo signal or a serial number of the coil unit), repetition of the echo signal detected therein (e.g., represented as a repetition sequence number), acquisition of the echo signal detected therein (e.g., represented as an acquisition sequence number), etc. TE can refer to the time between the application of the excitation RF pulse and the peak of the echo excited by the excitation RF pulse.

[0047] The pulse sequence module 250 can be configured to define parameters and arrangements associated with the MR scanner 110 before and / or during scanning the object 210. In some embodiments, parameters associated with the MR scanner 110 may include one or more parameters applied by the MR scanner 110 related to the MR pulse sequence (e.g., type of MR pulse sequence, TR, repetition count, TI, etc.), one or more parameters related to the gradient field or radio frequency field generated by the gradient coil 230 (e.g., RF center frequency, flip angle), one or more parameters related to the echo signal detected by the RF coil 240 as described elsewhere in this specification (e.g., TE, spin echo type), etc., or any combination thereof. In some embodiments, parameters associated with the MR scanner 110 may include one or more other imaging parameters, such as the count (or number) of RF channels, image contrast and / or ratio, slice thickness, imaging type (e.g., T1-weighted imaging, T2-weighted imaging, proton density-weighted imaging, etc.), field of view (FOV) of the image, eccentricity shift of the MR scanner 110, etc., or combinations thereof.

[0048] In some embodiments, the pulse sequence module 250 may be connected to and / or communicate with the processing device 120. For example, prior to MRI scan processing, the processing device 120 may design and / or determine at least a portion of the parameters and arrangements associated with the MR scanner 110 based on clinical needs or scanning protocols, and send this to the pulse sequence module 250, which may then scan the object 210 based on the parameters and arrangements defined by the pulse sequence module 250. For example, the MR scanner 110 may apply an MR pulse sequence having specific parameters associated with an MR pulse sequence defined by the pulse sequence module 250, and the RF coil 240 may receive echo signals based on specific parameters associated with echo signals defined by the pulse sequence module 250.

[0049] The above description of the MR scanner 110 is intended to be illustrative and not to limit the scope of this specification. Many alternatives, modifications, and variations will be apparent to those skilled in the art. The features, structures, methods, and characteristics of the exemplary embodiments described herein can be combined in various ways to obtain additional and / or alternative exemplary embodiments. For example, the pulse sequence module 250 may be integrated into the processing device 120. However, these variations and modifications do not depart from the scope of this specification.

[0050] Figure 3These are schematic diagrams of exemplary hardware and / or software components of a computing device according to some embodiments of this specification. In some embodiments, one or more components of the MRI system 100 may be implemented on one or more components of the computing device 300. By way of example only, the processing device 120 and / or the terminal 140 may each be implemented on one or more components of the computing device 300.

[0051] like Figure 3 As shown, computing device 300 may include processor 310, memory 320, input / output (I / O) 330, and communication port 340. Processor 310 may execute computer instructions (e.g., program code) and perform the functions of processing device 120 according to the techniques described herein. Computer instructions may include, for example, routines, programs, objects, components, data structures, procedures, modules, and functions that can perform the specific functions described herein. For example, processor 310 may process image data of an object acquired from MR scanner 110, storage device 130, terminal 140, and / or any other component of MRI system 100. In some embodiments, processor 310 may determine the T1 value of an object based on object-related MRI data acquired by MR scanner 110.

[0052] In some embodiments, processor 310 may include one or more hardware processors, such as microcontrollers, microprocessors, reduced instruction set computers (RISC), application-specific integrated circuits (ASICs), application-specific instruction set processors (ASIPs), central processing units (CPUs), graphics processing units (GPUs), physical processing units (PPUs), microcontroller units, digital signal processors (DSPs), field-programmable gate arrays (FPGAs), advanced RISC machines (ARMs), programmable logic devices (PLDs), any circuit or processor capable of performing one or more functions, or combinations thereof.

[0053] For illustrative purposes only, only one processor is described in computing device 300. However, it should be noted that computing device 300 in this specification may also include multiple processors. Therefore, the operations and / or method steps performed by one processor as described in this specification may also be performed jointly or individually by multiple processors. For example, if, in this specification, the processors of computing device 300 simultaneously execute step A and step B, it should be understood that steps A and B may also be performed jointly or individually by two or more different processors in computing device 300 (e.g., a first processor executes step A, a second processor executes step B, or the first and second processors jointly execute steps A and B).

[0054] The memory 320 can store data / information acquired from the MR scanner 110, storage device 130, terminal 140, and / or any other component of the MRI system 100. In some embodiments, the memory 320 may include a mass storage device, a removable storage device, a volatile read-write memory, a read-only memory (ROM), or similar, or combinations thereof. For example, a mass storage device may include a hard disk, an optical disk, a solid-state drive, etc. A removable storage device may include a flash drive, a floppy disk, an optical disk, a memory card, a compact disk, a magnetic tape, etc. A volatile read-write memory may include random access memory (RAM). RAM may include dynamic RAM (DRAM), dual data rate synchronous dynamic RAM (DDR-SDRAM), static RAM (SRAM), thyristor RAM (T-RAM), and zero-capacitance RAM (Z-RAM), etc. ROM may include a mask ROM (MROM), a programmable ROM (PROM), an erasable programmable ROM (EPROM), an electrically erasable programmable ROM (EEPROM), an optical disc ROM (CD-ROM), and a digital multifunction disk ROM, etc. In some embodiments, memory 320 may store one or more programs and / or instructions to perform the exemplary methods described herein. For example, memory 320 may store a program for processing device 120 to determine the T1 value of an object.

[0055] Input / output 330 can input and / or output signals, data, information, etc. In some embodiments, input / output 330 can allow user interaction with computing device 300 (e.g., processing device 120). In some embodiments, input / output 330 may include input devices and output devices. Examples of input devices may include a keyboard, mouse, touchscreen, microphone, etc., or combinations thereof. Examples of output devices may include display devices, speakers, printers, projectors, etc., or combinations thereof. Examples of display devices may include liquid crystal displays (LCDs), light-emitting diode (LED) based displays, flat panel displays, curved screens, television sets, cathode ray tubes (CRTs), touchscreens, etc., or combinations thereof.

[0056] Communication port 340 can be connected to a network (e.g., network 150) to facilitate data communication. Communication port 340 can establish a connection between computing device 300 (e.g., processing device 120) and one or more components of MRI system 100 (e.g., MR scanner 110, storage device 130, and / or terminal 140). This connection can be a wired connection, a wireless connection, any other communication connection capable of data transmission and / or reception, and / or a combination of these connections. Wired connections can include, for example, cables, optical fibers, telephone lines, or combinations thereof. Wireless connections can include, for example, Bluetooth. TM Connectivity, Wi-Fi TMLinks, WiMax TM The communication port 340 may be a link, a WLAN link, a VPN link, a mobile network link (e.g., 3G, 4G, 5G, etc.), or a combination thereof. In some embodiments, the communication port 340 may be and / or include standardized communication ports, such as RS232, RS485, etc. In some embodiments, the communication port 340 may be a specially designed communication port. For example, the communication port 340 may be designed according to the Digital Imaging and Medical Communications (DICOM) protocol.

[0057] Figure 4 This is an exemplary flowchart of a magnetic resonance imaging method according to some embodiments of this specification.

[0058] In some embodiments, one or more steps in process 400 may be performed... Figure 1 This is implemented in the MRI system 100 shown. For example, process 400 may be stored as instructions in a storage device (e.g., storage device 130 or memory 320) of the MRI system 100 and processed by a processing device 120 (e.g., such as...). Figure 3 The processor 310 of the computing device 300 shown calls and / or executes.

[0059] As used in this specification, the T1 information (also referred to as T1 information) of an object refers to the time constant of longitudinal magnetization (e.g., along the main magnetic field). For illustrative purposes, the following description uses a physical point of a patient as an exemplary object. It should be noted that the object can be a physical point of another subject, such as a part of a patient, an animal, an artificial subject (e.g., a model), etc. Furthermore, it should be understood that the determination of the T1 information of a physical point in the following description is provided as an example only, and process 400 can be used to determine the values ​​of one or more other quantitative parameters of the object (e.g., T2 value, T2* value, R2 value).

[0060] In some embodiments, process 400 may include:

[0061] Step 410: Based on at least two pulse flip angles, acquire at least two sets of B1 image signals corresponding to each pulse flip angle. In some embodiments, step 410 may be performed by the image signal acquisition module 1010.

[0062] The flip angle (FA) is actually an indicator describing the effect of a radio frequency (RF) pulse. It refers to the angle at which the RF pulse flips the macroscopic longitudinal magnetization vector to a position deviating from its original longitudinal direction. In some scenarios, it is also called the excitation angle. In some embodiments, the RF pulses can be of the same type but with different angles, or they can be of different types but with the same or different angles, etc.

[0063] The two pulse flip angles can be represented as α1 and α2 respectively. It should be noted that, for ease of description only, the description uses two pulse flip angles. In some other embodiments, the number of pulse flip angles may also include 3 or 5, etc.

[0064] B1 image signal is a type of magnetic resonance imaging signal, obtained by acquiring pulse signal intensity. The acquisition process of B1 image signal can be found in [link to relevant documentation]. Figure 5 .

[0065] Figure 5 This is a schematic diagram illustrating the signal excitation of a scanning pulse sequence for acquiring B1 image signals according to some embodiments of this specification. In some embodiments, the flip angles of the two pulses acquiring the B1 image signal can be implemented continuously or alternately. For example... Figure 5 As shown in the figure, RF represents radio frequency; TR (Time of Repetition) represents the repetition time, which determines the T1 relaxation level of the tissue; for example, in a GRE sequence, the repetition time TR refers to the time interval between the midpoints of two adjacent small-angle pulses; TE (Echo time) represents the echo time, which determines the T2 relaxation level of the tissue; S1 and S2 represent the generated signal strengths, respectively. In some embodiments, the two pulse flip angles can be implemented continuously and alternately, such as implementing pulse flip angle α1 continuously twice, and then alternately implementing pulse flip angle α2 twice.

[0066] For illustrative purposes, the following description will be combined with Figure 5 The pulse sequence is exemplified by the continuous and alternating implementation of pulse flip angles α1 and α2. TR1 and TR2 represent the first repetition time and the second repetition time, respectively. The first repetition time represents the interval between pulse flip angles α1 and α2; the second repetition time represents the interval between pulse flip angles α2 and α1. TR1 and TR2 can be the same or different. In some embodiments, since the purpose of acquiring the B1 image signal is to calculate B1 field information, TR1 and TR2 can be smaller than the actual image signal acquisition during the actual acquisition of the B1 image. It should be noted that the scheme in this specification is applicable to all steady-state GRE-type signals, such as GRE, MULTIPLEX sequences, etc. In some embodiments, the B1 image signals corresponding to the two pulse flip angles α1 and α2 are respectively:

[0067] Where M0 represents the baseline signal; This indicates the relaxation effect caused by T1, which is related to TR1; This indicates the relaxation effect caused by T1, which is related to TR2; This indicates the relaxation effect caused by T2*, which is related to TE. It should be noted that TE is not the focus of this specification.

[0068] Step 420: Determine the relative B1 field information of the at least two pulse flip angles based on the at least two sets of B1 image signals. In some embodiments, step 420 may be performed by the relative B1 field information determination module 1020.

[0069] As described above, in some embodiments, due to hardware limitations, the load on the imaging object, etc., the actual flip angle may differ from the ideal angle. To correct the T1 information, it is necessary to obtain the relative B1 field information of the flip angles of the two pulses. Simultaneously, at least two radio frequency pulses are used, ensuring that the relative B1 field distributions between the pulses are different.

[0070] In some embodiments, obtaining the relative B1 field information of the two pulse flip angles may further include: determining the intensities of at least two actual pulse signals corresponding to the at least two sets of B1 image signals respectively; and determining the relative B1 field information based on the correlation between the actual pulse signal intensities.

[0071] Continuing with the previous example, the actual angles corresponding to the two pulse flip angles α1 and α2 can be expressed as α′1 and α′2, respectively. Therefore, for formulas (1) and (2), the actual pulse signal intensities acquired at the corresponding actual angles can be expressed as follows:

[0072] In some embodiments, the correlation of actual pulse signal intensity can be the ratio of the actual pulse signal intensity. Therefore, the relative B1 field information of the actual pulse signal can be expressed as:

[0073] Where r represents the relative B1 field information of the pulse signal.

[0074] It should be noted that in some embodiments, the correlation between the actual pulse signal strength can also be the difference or the average value, etc.

[0075] In some embodiments, considering real-world scenarios, the relative B1 field information can be the ratio of the sine values ​​of at least two pulse flip angles, i.e. The ratio R is independent of T1 by definition and is highly insensitive to the relaxation characteristics of T1 in actual calculations, thus ensuring accuracy to a certain extent.

[0076] In some embodiments, it can be seen from formulas (3) and (4) combined with mathematical knowledge that when the pulse flip angle is small, such as α < 18°, the cosine value (cos(α)) is close to 1. Therefore, considering that the actual flip angle deviates from the ideal flip angle, the cosine value will not change significantly. The ideal pulse flip angles α1 and α2 can be used to replace the actual angles α′1 and α′2. Combined with formula (5), the relative B1 field information of the actual pulse signal can be expressed as:

[0077] The method of determining the relative B1 field information of the actual pulse signal by approximating the value using formula (6) avoids the process of calculating the absolute values ​​of sin(α′1) and sin(α′2). Furthermore, formula (6) is highly insensitive to the spatial non-uniformity of the pulse flip angles α1 and α2, meaning that the spatial non-uniformity of the pulse flip angles α1 and α2 will not affect the accuracy of R. It should be noted that the pulse flip angle can be in other ranges in actual use, such as α < 30° or α < 45°, and the effect of this specification can still be achieved when the pulse flip angle is other angles.

[0078] In some embodiments, assuming TR1 = TR2, then E1 = E2. In this case, the above formulas (3) to (6) can be further simplified to:

[0079] It should be noted that in some other embodiments, TR1 may not be equal to TR2. In this case, the calculation process in formulas (3) to (6) can be used directly, which will not affect the result of this solution. For ease of description, the following text will use TR1 = TR2 as an example.

[0080] Step 430: Based on at least two sets of T1 image signals corresponding to the two pulse flip angles and the relative B1 field information, determine the T1 information corresponding to the at least two pulse flip angles. In some embodiments, step 430 may be performed by the T1 information determination module 1030.

[0081] T1 image signal is a type of magnetic resonance imaging signal, similar to B1 image, and can be obtained by acquiring pulse signal intensity. The acquisition process for T1 image signal can be found in [link to relevant documentation]. Figure 6 .

[0082] Figure 6This is a schematic diagram illustrating the signal excitation of a scanning pulse sequence for acquiring T1 image signals according to some embodiments of this specification. In some embodiments, at least two sets of T1 image signals corresponding to the two pulse flip angles can be acquired independently through two separate pulse flip angles. (Reference) Figure 6 A standard GRE sequence (i.e., each sequence corresponds to a single flip angle and a single repetition time) can be used to acquire T1 images corresponding to pulse flip angles α1 and α2, respectively. In some other embodiments, the corresponding T1 images can also be acquired in other ways, which are not limited in this specification. For example, the two sets of T1 image signals can be represented as follows:

[0083] in, This represents the relaxation effect caused by T1, and is related to TR. gre Related; TR gre For the repeat time of the GRE sequence, it should be noted that TR gre TR1 and TR2 in the aforementioned formula are irrelevant and may be the same as or different from TR1 and / or TR2; TR during the acquisition process of the two sets of T1 image signals gre They can be the same or different.

[0084] In some embodiments, T1 information can be determined based on the correlation between two sets of T1 image signals and the relative B1 field information. That is, step 430 can further include: acquiring at least two sets of T1 image signals corresponding to the two pulse flip angles; determining the correlation between the at least two sets of T1 image signals; and determining the T1 information corresponding to the at least two pulse flip angles based on the correlation and the relative B1 field information.

[0085] Specifically, continuing with the example of the GRE pulse sequence in step 430, the correlation between the two sets of T1 image signals corresponding to the two pulse flip angles is obtained through formulas (11) to (12). This correlation can be the ratio of the two sets of image signals, and the correlation between the two sets of image signals can be expressed as:

[0086] It should be noted that in some embodiments, the correlation between the two sets of image signals can also be obtained through other methods (such as MDI (multi-dimensional integration) or MULTIPLEX, etc.), which will not be described in detail in this specification. Regardless of the method used, the correlation includes... That's all.

[0087] Furthermore, in some embodiments, R in formula (10) can be used instead of R in formula (13). The reason is that the two are actually equivalent, that is, they are both the combined effect of the same two actual flip angles. Therefore, formula (13) can be simplified to:

[0088] In some embodiments, the correlation R between the two sets of image signals can be used as a basis. gre The T1 information corresponding to the two pulse flip angles is determined by the relative B1 field information R. In some embodiments, the T1 information is determined by the relative B1 field information R. Substituting into formula (14), the T1 information can be expressed as:

[0089] The T1 information is calculated using formula (15), avoiding the need for indirect methods such as replacing the flip angle or directly correcting the initial T1 information. This process is simpler and achieves higher accuracy. Furthermore, the final T1 quantitative map can be calculated directly using the above method, without first calculating the initial uncorrected T1 quantitative map.

[0090] In some embodiments, it is assumed that α′1 < α′2, and the absolute value of α′1 is also relatively small (e.g., less than 5°). Therefore, in conjunction with the preceding statements, cos(α′1) can be replaced by cos(α1); and cos(α′2) can be replaced by... As an approximation, formula (15) is simplified. In some embodiments, the simplified formula (15) can be written as:

[0091] Since the pulse flip angles α1 and α2 are theoretical values, the analytical solution of T1 information can be directly obtained using formula (16) without the need for other conventional methods such as fitting, which further ensures the convenience of calculation and the accuracy of data.

[0092] For example, by simulating parameters TR1 / TR2 = 8 / 20 ms, α1 / α2 = 4° / 16°, and T1 = 1~3100 ms, the following can be obtained: Figure 7 The graph shows the error variation curve of R value versus T1; in the graph, the horizontal axis represents the value of T1, and the vertical axis represents ΔR, that is, the difference between the R value and the ideal value (i.e., T1). The difference between ). Figure 7 It can be seen that R is quite insensitive to changes in T1, with an error range of 0.51% to 0.58%. Therefore, the impact of changes in T1 can be ignored in actual processing.

[0093] For example, Figure 8For the aforementioned example, i.e., TR1 / TR2 = 8 / 20ms, α1 / α2 = 4° / 16°, T1 = 1~3100ms, the graph shows the error variation curve between the T1 value and the true T1. In the graph, the horizontal axis represents the numerical value of T1, and the vertical axis represents ΔT1, that is, the difference between the T1 value and the true T1 value. Figure 8 It can be seen that the error between the T1 information calculated by the above process 400 and the true value is less than 4% within the T1 range (i.e., 0 to 3000 ms) of normal physiological tissues.

[0094] It should be noted that the above description of process 400 is for illustrative purposes only and does not limit the scope of this specification. Those skilled in the art can make various modifications and changes to process 400 under the guidance of this specification. However, these modifications and changes remain within the scope of this specification.

[0095] Figures 9A to 9C The processing procedure for the actual collected subject head data is shown. Among other things, Figure 9A The uncorrected T1 quantification plot is shown. Figure 9B R shows the subject's head data. Figure 9C It shows Figure 9A T1 quantitative chart after Figure 9B The T1 quantification plot after R correction in the figure. As can be seen from the figure, Figure 9C The image, after further processing, has higher quality (becomes more uniform), and its values ​​are closer to those reported in the literature.

[0096] Figure 10 This is an exemplary block diagram of a magnetic resonance imaging system according to some embodiments of this specification.

[0097] like Figure 10 As shown, the magnetic resonance imaging system 1000 includes an image signal acquisition module 1010, a relative B1 field information determination module 1020, and a T1 information determination module 1030.

[0098] The image signal acquisition module 1010 can be used to acquire at least two sets of B1 image signals corresponding to each pulse flip angle, based on at least two pulse flip angles.

[0099] In some embodiments, details regarding the pulse flip angle and image signal, and further descriptions, can be found in step 410 and its related content, and will not be repeated here.

[0100] The relative B1 field information determination module 1020 can be used to determine the relative B1 field information of the at least two pulse flip angles based on the at least two sets of B1 image signals.

[0101] In some embodiments, further description of the relative B1 field information can be found in step 420 and related content, and will not be repeated here.

[0102] The T1 information determination module 1030 can be used to determine the T1 information corresponding to the at least two pulse flip angles based on at least two sets of T1 image signals corresponding to the at least two pulse flip angles and the relative B1 field information.

[0103] In some embodiments, further description of the T1 information can be found in step 430 and related content, and will not be repeated here.

[0104] It should be understood that Figure 10 The magnetic resonance imaging system 1000 and its modules shown can be implemented in various ways. For example, in some embodiments, the system and its modules can be implemented by hardware, software, or a combination of software and hardware. Exemplarily, system 1000 can be implemented by software. It should be noted that the above description of the system and its modules is for convenience only and should not limit this specification to the scope of the illustrated embodiments. It is understood that those skilled in the art, after understanding the principle of the system, may arbitrarily combine the various modules or construct subsystems connected to other modules without departing from this principle. In some embodiments, Figure 8 The image signal acquisition module 1010, the relative B1 field information determination module 1020, and the T1 information determination module 1030 disclosed herein can be different modules within a single system, or a single module can implement the functions of two or more of the aforementioned modules. For example, the modules can share a single storage module, or each module can have its own separate storage module. Such variations are all within the scope of protection of this specification.

[0105] It should be noted that different embodiments may produce different beneficial effects. In different embodiments, the beneficial effects may be any one or a combination of the above, or any other possible beneficial effects.

[0106] The basic concepts have been described above. Obviously, for those skilled in the art, the detailed disclosure above is merely illustrative and does not constitute a limitation of this specification. Although not explicitly stated herein, those skilled in the art may make various modifications, improvements, and corrections to this specification. Such modifications, improvements, and corrections are suggested in this specification and therefore remain within the spirit and scope of the exemplary embodiments described herein.

[0107] Furthermore, this specification uses specific terms to describe embodiments thereof. For example, "an embodiment," "one embodiment," and / or "some embodiments" refer to a particular feature, structure, or characteristic associated with at least one embodiment of this specification. Therefore, it should be emphasized and noted that references to "an embodiment," "one embodiment," or "an alternative embodiment" in different locations throughout this specification do not necessarily refer to the same embodiment. Moreover, certain features, structures, or characteristics in one or more embodiments of this specification can be appropriately combined.

[0108] Furthermore, unless expressly stated in the claims, the order of processing elements and sequences, the use of numbers and letters, or other names described in this specification are not intended to limit the order of the processes and methods described herein. Although various examples have been discussed in the foregoing disclosure of some embodiments of the invention that are currently considered useful, it should be understood that such details are for illustrative purposes only, and the appended claims are not limited to the disclosed embodiments; rather, the claims are intended to cover all modifications and equivalent combinations that conform to the spirit and scope of the embodiments described herein. For example, while the system components described above can be implemented using hardware devices, they can also be implemented solely using software solutions, such as installing the described system on existing servers or mobile devices.

[0109] Similarly, it should be noted that, in order to simplify the description disclosed herein and thus aid in the understanding of one or more embodiments of the invention, the foregoing description of embodiments in this specification may sometimes combine multiple features into a single embodiment, drawing, or description thereof. However, this method of disclosure does not imply that the subject matter of this specification requires more features than those mentioned in the claims. In fact, the embodiments contain fewer features than all the features of a single embodiment disclosed above.

[0110] In some embodiments, numbers describing the quantity of components and attributes are used. It should be understood that such numbers used in the description of embodiments are modified in some examples with the terms "approximately," "approximately," or "generally." Unless otherwise stated, "approximately," "approximately," or "generally" indicates that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may be changed depending on the characteristics required by individual embodiments. In some embodiments, numerical parameters should take into account specified significant digits and employ a general method of digit reservation. Although the numerical ranges and parameters used to confirm their breadth of range in some embodiments of this specification are approximate values, in specific embodiments, such values ​​are set as precisely as feasible.

[0111] For each patent, patent application, patent application publication, and other material, such as articles, books, specifications, publications, and documents, referenced in this specification, the entire contents of which are incorporated herein by reference. This excludes historical application documents that are inconsistent with or conflict with the content of this specification, as well as documents that limit the broadest scope of the claims in this specification (currently or subsequently appended to this specification). It should be noted that in the event of any inconsistency or conflict between the descriptions, definitions, and / or terminology used in the supplementary materials to this specification and the content of this specification, the descriptions, definitions, and / or terminology used in this specification shall prevail.

[0112] Finally, it should be understood that the embodiments described in this specification are merely illustrative of the principles of the embodiments described herein. Other variations may also fall within the scope of this specification. Therefore, alternative configurations of the embodiments described herein are intended to be illustrative rather than limiting, and should be considered consistent with the teachings of this specification. Accordingly, the embodiments described herein are not limited to those explicitly introduced and described herein.

Claims

1. A magnetic resonance imaging method, characterized in that, The method includes: Based on at least two pulse flip angles, at least two sets of B1 image signals corresponding to each pulse flip angle are acquired; the acquisition of the at least two pulse flip angles of the B1 image signals is carried out continuously and alternately. The relative B1 field information of the at least two pulse flip angles is determined based on the at least two sets of B1 image signals; Based on the repetition time of the steady-state gradient echo sequence, the correlation between at least two sets of T1 image signals corresponding to the two pulse flip angles, the relative B1 field information, and the actual angles of the two pulse flip angles, the T1 information corresponding to the at least two pulse flip angles is determined; the at least two sets of T1 image signals corresponding to the two pulse flip angles can be acquired independently through the two pulse flip angles.

2. The method according to claim 1, characterized in that, Determining the relative B1 field information of the at least two pulse flip angles includes: Determine the intensity of at least two actual pulse signals corresponding to the at least two sets of B1 image signals, respectively; Based on the correlation of the actual pulse signal intensity, the relative B1 field information is determined.

3. The method according to claim 2, characterized in that: The correlation is the ratio of the actual pulse signal strength.

4. The method according to claim 1, characterized in that: The relative B1 field information is the ratio of the sine values ​​of at least two pulse flip angles.

5. The method according to claim 1, characterized in that, The step of determining the T1 information corresponding to the at least two pulse flip angles based on at least two sets of T1 image signals corresponding to the two pulse flip angles and the relative B1 field information includes: Acquire at least two sets of T1 image signals corresponding to the two pulse flip angles; Determine the correlation between the at least two sets of T1 image signals; Based on the repetition time of the steady-state gradient echo sequence, the correlation between at least two sets of T1 image signals corresponding to the two pulse flip angles, the relative B1 field information, and the actual angles of the two pulse flip angles, the T1 information corresponding to the at least two pulse flip angles is determined.

6. A magnetic resonance imaging system, characterized in that, The system includes: An image signal acquisition module is used to acquire at least two sets of B1 image signals corresponding to each of the at least two pulse flip angles; the acquisition of the at least two pulse flip angles of the B1 image signals is carried out continuously and alternately. The relative B1 field information determination module is used to determine the relative B1 field information of the at least two pulse flip angles based on the at least two sets of B1 image signals; The T1 information determination module is used to determine the T1 information corresponding to the at least two pulse flip angles based on the repetition time of the steady-state gradient echo sequence, the correlation relationship of at least two sets of T1 image signals corresponding to the two pulse flip angles, the relative B1 field information, and the actual angles of the two pulse flip angles; the at least two sets of T1 image signals corresponding to the two pulse flip angles can be acquired independently through the two pulse flip angles.

7. A magnetic resonance imaging device, characterized in that, The device includes: At least one storage medium for storing computer instructions; At least one processor is configured to execute the computer instructions to implement the method of any one of claims 1 to 5.

8. A computer-readable storage medium storing computer instructions that, when read by a computer, execute the method as described in any one of claims 1 to 5.

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