Imaging method based on signal spectrum analysis of magnetic particle relaxation time

Abstract

The application discloses an imaging method for magnetic particle relaxation time based on signal spectrum analysis, which comprises the following steps: generating FFP; moving FFP in the space range where the single magnetic nano-particle injected target is located, generating pulsed square wave excitation magnetic field at each FFP position and receiving the original signal generated by the magnetic nano-particle in the target; performing inverse Laplace transform on the signal and obtaining the spectrum curve of the FFP position according to the transform result; determining the magnetic particle relaxation time detection result of the FFP position according to the two peak regions in the spectrum curve and the distribution of the two corresponding peaks in the spectrum curve determined by the pre-experiment of the single magnetic nano-particle; and performing imaging based on at least one same item in the magnetic particle relaxation time detection results of all FFP positions to obtain the relaxation time imaging graph. The application can separate and detect the relaxation time, and can combine the free point scanning of the magnetic field to perform multi-color magnetic particle imaging so as to distinguish the plaque, conduit and blood vessel regions.

Description

Technical Field

[0001] This invention belongs to the field of magnetic particle biomedical detection and imaging, specifically relating to an imaging method based on signal spectrum analysis of magnetic particle relaxation time. Background Technology

[0002] Magnetic Particle Imaging (MPI) is a tracing method based on functional and tomographic imaging techniques to detect the spatial distribution of magnetic nanoparticles (SPIONs). As a functional imaging method, MPI improves imaging resolution without using radioactive materials, making it one of the most promising technologies for clinical translation in the past 20 years. Significant progress has been made in areas such as multimodal in vivo imaging, tumor detection and immunotherapy, cell therapy monitoring, vascular perfusion imaging, inflammation quantification, infectious disease research, precision magnetothermal therapy, targeted drug delivery, and nanomaterials.

[0003] The imaging principle of MPI is based on Langevin's law of magnetization and the nonlinear magnetization curve. The static gradient magnetic field of MPI, or the selective field, causes magnetic particles at different locations to generate distinct signals. The selective field has a corresponding field vector at each spatial location, with the field vector being zero at the center. This point is called the Field Free Region (FFR), where the magnetic field strength is zero; it is also known as the field-free point (FFP) or field-free line (FFL). Rapidly moving the FFR, when it passes through a region containing magnetic particles, particles farther from the FFR reach magnetic saturation and do not react to changes in the overall magnetic field; the receiving coil does not detect a signal. Conversely, particles near the FFP are not magnetically saturated, and their magnetization changes in magnitude and direction, thus detecting a voltage signal in the receiving coil. This voltage signal is distributed to each location of the FFP for reconstruction, yielding the spatial distribution information of the magnetic particles, i.e., the MPI signal, enabling the reconstruction imaging of the concentration distribution of SPIONs.

[0004] Research on magnetic nanoparticles shows that the relaxation time of the magnetization response under an excitation magnetic field is a crucial characteristic. The basic relaxation mechanisms include internal rotation (Nieren relaxation) and external physical rotation (Brown relaxation). The Nieren relaxation time is a function of temperature and the volume of the magnetic core. The Brown relaxation time depends on the fluid viscosity, temperature, and the hydrodynamic volume of the magnetic nanoparticles. Accurate measurement of each relaxation time can be used to describe the in vivo state of magnetic nanoparticles, potentially leading to various clinical applications, such as pathological detection based on viscosity and temperature predictions.

[0005] For example, viscosity within biological tissues can exhibit certain clinical characteristics. The cellular response to the viscoelasticity of the matrix surface is crucial for controlling cellular behavior, such as controlling stem cell proliferation and determining cell fate. In the tumor microenvironment, increased viscosity is caused by the overexpression of indicators such as lymphocytes, lactate, proteins, enzymes, lipids, extracellular secretions, and extracellular matrix components. Increased whole blood viscosity increases cardiovascular mortality and the likelihood of developing Alzheimer's disease. Mice with inflammation and peritonitis exhibit decreased blood viscosity, and so on.

[0006] Temperature is associated with poor prognosis in breast cancer patients. Furthermore, HSP90 is a molecular chaperone in the heat shock response, maintaining the structural and functional integrity of oncogenic proteins in pancreatic cancer cells. The anticancer effects of HSP90 inhibitors can be evaluated by inducing heat shock through magnetothermal therapy combined with temperature monitoring.

[0007] Given the clinical application potential of MPI imaging, the development of multicolor magnetic particle imaging using a specific relaxation time would undoubtedly expand the breadth and depth of MPI applications. However, current methods widely employ sinusoidal excitation to generate dynamically changing magnetic fields to excite magnetic nanoparticles. Both of these relaxation times are functions of the applied magnetic field, decreasing with increasing magnetic field amplitude, and lack a fixed Nilleney or Brownian relaxation time throughout the excitation period. Therefore, under traditional sinusoidal excitation methods, it is difficult to decouple the Nilleney and Brownian relaxation times, thus hindering research development in this area. Summary of the Invention

[0008] To address the aforementioned problems in the prior art, this invention provides an imaging method, apparatus, electronic device, and storage medium based on signal spectrum analysis of magnetic particle relaxation time. The technical problem to be solved by this invention is achieved through the following technical solution:

[0009] In a first aspect, embodiments of the present invention provide an imaging method based on signal spectrum analysis of magnetic particle relaxation time, the method comprising:

[0010] Generates a magnetic field free point (FFP);

[0011] The FFP is moved within the spatial range of the target under test, which has been injected with a single type of magnetic nanoparticle. At each FFP position, a pulsed square wave excitation magnetic field is generated, and the original signal generated by the magnetic nanoparticles in the target under test at that FFP position under the excitation of the pulsed square wave excitation magnetic field is received.

[0012] Perform an inverse Laplace transform on the original signal, and obtain the spectral curve corresponding to the FFP position based on the inverse Laplace transform result;

[0013] Based on the region of the two peaks in the spectrum curve and the distribution of the two relaxation time peaks in the spectrum curve determined by the pre-experiment of the single magnetic nanoparticle, the magnetic particle relaxation time detection result at the FFP position is determined; wherein, the magnetic particle relaxation time detection result includes the Niehr relaxation time constant, the Brown relaxation time constant, and the percentage of Niehr relaxation and Brown relaxation.

[0014] Imaging is performed based on at least one of the same terms from the magnetic particle relaxation time detection results obtained from all FFP positions to obtain a relaxation time image of the target under test.

[0015] In one embodiment of the present invention, generating a pulsed square wave excitation magnetic field at each FFP location and receiving the original signal generated by the magnetic nanoparticles within the target at that FFP location under the excitation of the pulsed square wave excitation magnetic field includes:

[0016] At each FFP location, a pulsed square wave excitation magnetic field is generated using a pre-designed pulsed square wave relaxor, and the original signal generated by the magnetic nanoparticles in the target at that FFP location under the excitation of the pulsed square wave excitation magnetic field is received.

[0017] In one embodiment of the present invention, the pulse square wave relaxor includes:

[0018] A digital acquisition card is used to generate analog signals of pulse square waves and to digitize the input raw signals.

[0019] An AC power amplifier is used to amplify the analog signal;

[0020] The transmitting coil is used to transmit amplified analog signals to generate a pulsed square wave excitation magnetic field;

[0021] A current sensor is used to monitor the emission waveform of the AC power amplifier in real time.

[0022] A receiving coil is used to receive the original signal generated by magnetic particles under the excitation of the pulsed square wave excitation magnetic field;

[0023] A low-noise preamplifier is used to amplify the original signal and provide it to the digital acquisition card.

[0024] In one embodiment of the present invention, determining the magnetic particle relaxation time detection result at the FFP position based on the region of the two peaks present in the spectrum curve and the distribution of the two relaxation time corresponding peaks in the spectrum curve determined by prior experiments on the single magnetic nanoparticle includes:

[0025] Based on the regions with two peaks in the spectrum curve, determine the first relaxation time, the second relaxation time, and their respective percentages;

[0026] Based on the distribution of the peaks corresponding to the two relaxation times in the spectral curves determined by the prior experiments on the single type of magnetic nanoparticle, the Niehr relaxation time and Brown relaxation time in the two relaxation times in the spectral curves are distinguished, and the magnetic particle relaxation time detection result at the FFP position is obtained.

[0027] In one embodiment of the present invention, determining the first relaxation time, the second relaxation time, and their respective percentages based on the regions of the two peaks present in the spectral curve includes:

[0028] The magnitudes of the first relaxation time and the second relaxation time are determined based on the peak positions of the two peaks in the spectrum curve, and the percentages of the first relaxation time and the second relaxation time are determined based on the area of ​​the two peaks.

[0029] In one embodiment of the present invention, for the single type of magnetic nanoparticle, the distribution of the peaks corresponding to the two relaxation times in the spectral curve is determined in advance by experiments, including:

[0030] To prepare single magnetic particle samples for a single type of magnetic nanoparticle, an environmental parameter sequence for the single magnetic particle sample is determined based on the difference in response of the pre-determined Niehr relaxation time or Brownian relaxation time to changes in the environmental parameters of the magnetic particles; wherein, the environmental parameters include viscosity, stiffness, temperature, and microenvironment; the environmental parameter sequence contains multiple environmental parameter values ​​and exhibits the same trend of change;

[0031] A pulsed square wave excitation magnetic field is generated, and the sample signal generated by the single magnetic particle sample corresponding to each environmental parameter value under the excitation of the pulsed square wave excitation magnetic field is received.

[0032] Perform an inverse Laplace transform on each sample signal and obtain the corresponding spectrum curve based on the results of each inverse Laplace transform;

[0033] For any given spectral curve, based on the regions containing two peaks, determine the first relaxation time, the second relaxation time, and their respective percentages under the corresponding environmental parameter values. Furthermore, based on the differences in the changing trends of the first and second relaxation times among multiple spectral curves, distinguish the Niehr relaxation time and Brown relaxation time among the two relaxation times in any given spectral curve, and determine the distribution of the peaks corresponding to the two relaxation times in the spectral curve of a single magnetic nanoparticle.

[0034] In one embodiment of the present invention, imaging is performed based on at least one term from the magnetic particle relaxation time detection results obtained from all FFP positions to obtain a relaxation time imaging map of the target under test, including:

[0035] Based on the Brownian relaxation time constants obtained from the magnetic particle relaxation time detection results at all FFP locations, an image of the Brownian relaxation time of the target under test is obtained.

[0036] Secondly, embodiments of the present invention provide an imaging device based on signal spectrum analysis of magnetic particle relaxation time, the device comprising:

[0037] The FFP generation module is used to generate magnetic field free points (FFPs).

[0038] The original signal acquisition module is used to move the FFP within the spatial range of the target under test where a single type of magnetic nanoparticle has been injected. At each FFP position, a pulsed square wave excitation magnetic field is generated, and the original signal generated by the magnetic nanoparticles in the target under test at that FFP position under the excitation of the pulsed square wave excitation magnetic field is received.

[0039] The spectrum curve acquisition module is used to perform an inverse Laplace transform on the original signal and obtain the spectrum curve corresponding to the FFP position based on the inverse Laplace transform result.

[0040] The magnetic particle relaxation time detection module is used to determine the magnetic particle relaxation time detection result at the FFP position based on the region of the two peaks in the spectrum curve and the distribution of the two relaxation time corresponding peaks in the spectrum curve determined by the pre-experiment of the single magnetic nanoparticle; wherein, the magnetic particle relaxation time detection result includes the Niehr relaxation time constant, the Brown relaxation time constant, and the percentage of Niehr relaxation and Brown relaxation.

[0041] The imaging module is used to perform imaging based on at least one of the same terms in the magnetic particle relaxation time detection results obtained from all FFP positions, so as to obtain a relaxation time imaging map of the target under test.

[0042] Thirdly, embodiments of the present invention provide an electronic device, including a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus;

[0043] The memory is used to store computer programs;

[0044] When the processor executes the program stored in the memory, it implements the steps of the imaging method based on signal spectrum analysis of magnetic particle relaxation time provided in the embodiments of the present invention.

[0045] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the imaging method based on signal spectrum analysis of magnetic particle relaxation time provided in the embodiments of the present invention.

[0046] The beneficial effects of this invention are:

[0047] In the scheme provided by this invention, a magnetic field free point (FFP) is first generated; then, the FFP is moved within the spatial range of the target object where a single type of magnetic nanoparticle has been injected, and a pulsed square wave excitation magnetic field is generated at each FFP location. The original signal generated by the magnetic nanoparticles in the target object at that FFP location under the excitation of the pulsed square wave excitation magnetic field is received; next, the original signal is subjected to an inverse Laplace transform, and the spectrum curve corresponding to the FFP location is obtained based on the inverse Laplace transform result; then, based on the region of the two peaks in the spectrum curve and the distribution of the two relaxation time corresponding peaks in the spectrum curve of the single type of magnetic nanoparticle determined in advance by experiments, the magnetic particle relaxation time detection result at the FFP location is determined; finally, imaging is performed based on at least one identical term in the magnetic particle relaxation time detection results obtained from all FFP locations to obtain a relaxation time imaging map of the target object. This invention utilizes multicolor magnetic particle imaging combined with magnetic field free point scanning. At each FFP location, the Nieer relaxation time and Brownian relaxation time of the magnetic nanoparticles are distinguished and detected using a spectral analysis-based inversion recovery method. The relaxation time imaging map obtained using the same detection results from all FFP locations can at least be used to distinguish plaques, ducts, and vascular regions. Attached Figure Description

[0048] Figure 1 The left and right figures are schematic diagrams of the signal curve and magnetization intensity curve under trapezoidal pulse excitation, respectively;

[0049] Figure 2 This is a schematic flowchart of an imaging method based on signal spectrum analysis of magnetic particle relaxation time provided in an embodiment of the present invention.

[0050] Figure 3 The left figure shows the attenuation signal of Synomag-D and 1% glycerol under trapezoidal pulse wave excitation during the flat phase of the magnetic field with different excitation field amplitudes in an embodiment of the present invention. Figure 3 The right figure shows the spectral analysis results of the attenuation signal during the flat phase of the magnetic field in an embodiment of the present invention;

[0051] The left image of Figure 4(a) shows the spectrum analysis results of the relaxation time under different viscosities when performing spectrum analysis on the attenuation signal in the flat phase of the magnetic field of Synomag-D in the embodiment of the present invention under the excitation of a pulse square wave with a magnetic field amplitude of 3mT; the right image of Figure 4(a) shows the spectrum analysis results of the relaxation time under different viscosities when performing spectrum analysis on the pulse square wave with a magnetic field amplitude of 6mT.

[0052] Figure 4(b) shows two relaxation time diagrams of Synomag-D at different viscosity levels in the embodiment of the present invention;

[0053] The left image of Figure 5(a) shows the spectral analysis results of Synomag-D with different gelatin concentrations and stiffness under a magnetic field amplitude of 3mT in the embodiment of the present invention. The right image of Figure 5(a) shows the spectral analysis results of Synomag-D with different gelatin concentrations and stiffness under a magnetic field amplitude of 6mT.

[0054] The left panel of Figure 5(b) shows the spectral analysis results of Synomag-D with different gelatin concentrations under a magnetic field amplitude of 3 mT, and the right panel of Figure 5(b) shows the spectral analysis results of Synomag-D with different gelatin concentrations under a magnetic field amplitude of 6 mT.

[0055] Figure 5(c) shows the relaxation time of the gel under different field amplitudes;

[0056] Figure 6 The left figure shows the spectral analysis results of Synomag-D at different temperatures with a 1% glycerol concentration; Figure 6 The right figure shows the spectral analysis results of Synomag-D at different temperatures with a 10% glycerol concentration;

[0057] Figure 7 This is a schematic diagram of the vascular system model used in the simulation experiment of an embodiment of the present invention;

[0058] Figure 8 This is a schematic diagram of the magnetic field environment of the vascular system model in the simulation experiment of this invention;

[0059] Figure 9 This is a schematic diagram of the signal weighting factor distribution in the simulation experiment of an embodiment of the present invention;

[0060] Figures 10(a) to 10(c) These are, respectively, digital blood vessel phantom images, baseline images, and Brownian relaxation time imaging images from the simulation experiments of this invention embodiment;

[0061] Figure 11 This is a graph showing the variation of Brownian relaxation time of plaque, duct, and vascular regions with the average signal period in a simulation experiment of an embodiment of the present invention.

[0062] Figure 12This is a schematic diagram of the structure of an imaging device based on signal spectrum analysis of magnetic particle relaxation time, provided in an embodiment of the present invention.

[0063] Figure 13 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0064] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0065] Under traditional sinusoidal excitation methods, it is difficult to decouple the Nieer relaxation time and the Brownian relaxation time. One approximation method for detecting relaxation time under sinusoidal excitation is to use the total relaxation time of the signal broadening and hysteresis. Specifically, the relaxation process of magnetic nanoparticles can be modeled as a first-order Debye process, where the convolution kernel is a single exponential decay function, and the relaxation time constant in the kernel is the so-called Debye relaxation time. This simple model has been experimentally verified to be useful for matching relaxation effects. Based on this, researchers have proposed a relaxation imaging technique called TAURUS (TAU estimation by recovering the underlying mirror symmetry), which estimates the Debye relaxation time constant by recovering the underlying mirror symmetry signal from sinusoidal excitation. Another approximation method for detecting relaxation time is to consider only Brownian relaxation while ignoring Nieer relaxation. This approach is based on the premise that Brownian relaxation dominates when the sinusoidal excitation frequency is high and the magnetic nanoparticle diameter is greater than 25 nm.

[0066] Therefore, there is currently no effective means to distinguish and detect the Nillet relaxation time and Brownian relaxation time of magnetic nanoparticles.

[0067] To facilitate understanding of this scheme, the inventive concept of pulsed square wave excitation, Debye relaxation time in the prior art, and relaxation time detection used in the imaging of this embodiment will be briefly explained first.

[0068] This invention assumes that the period of the pulsed square wave excitation is T. The following explanation uses a trapezoidal pulse as a specific example of a pulsed square wave. For a trapezoidal wave with a period of T, the rising and flat phases of the magnetic field within half a period can be represented as follows:

[0069]

[0070] Where t represents time; H0 represents the magnetic field amplitude during the flat phase; fp represents the ratio of the flat phase time to the total pulse time; and α represents the slope during the rising phase.

[0071]

[0072] In the study of this embodiment of the invention, the half-cycle of the wave is much longer than the relaxation time, which means that within each pulse cycle, the magnetic field is fully magnetized at the end of the flat phase. During the first half-cycle, the non-adiabatic magnetization of the magnetic nanoparticles can be calculated by integrating the received signal:

[0073]

[0074] Among them, M non-adiabatic (t) represents the non-adiabatic magnetization; S received (t') represents the received signal, that is, the signal generated by the received magnetic particles under the excitation of the trapezoidal pulse excitation magnetic field; M0 represents the magnetization intensity at the static excitation field H0.

[0075] See Figure 1 The black curve in the left figure represents the signal curve under trapezoidal pulse excitation, i.e., the curve corresponding to the received signal; the red curve in the right figure represents the magnetization intensity curve under trapezoidal pulse excitation, abbreviated as the M curve; the green curves in both figures represent the corresponding magnetic field intensity curves, abbreviated as the H curve. See also... Figure 1 Understanding this, the magnetization M0 at the static excitation field H0 can be estimated using half of the signal AUC (Area Under Curve, defined as the area under the ROC curve and the coordinate axes) over the entire half-cycle:

[0076]

[0077] from Figure 1 It can be seen that the MH curve under trapezoidal pulse excitation can be divided into a magnetic field rising phase and a magnetic field flat phase. The curve in the magnetic field rising phase has the same trend as the rising excitation magnetic field. However, the MH curve in the rising phase depends on the slope of the rising magnetic field and the relaxation time of the magnetic nanoparticles. Since the excitation field amplitude is constant, the MH curve in the field flat phase is basically a vertical line. The embodiments of the present invention assume that the magnetization is fully recovered at the end of the magnetic field flat phase.

[0078] Neill and Brownian relaxation times are often difficult to measure separately, and there is currently no suitable formula to calculate them separately.

[0079] This invention, through research, has found that during the flat phase of the magnetic field under pulsed square wave excitation, the relaxation time of magnetic nanoparticles can be considered constant. Pulsed excitation provides a steady-state signal, avoiding signal broadening and hysteresis caused by relaxation effects. Pulsed excitation includes two phases: a magnetic field rise phase and a magnetic field flat phase. The former generates a rapidly changing magnetic field; during this phase, the Nieer and Brownian relaxation times are not constant and cannot be decoupled, allowing only the Debye relaxation process to be evaluated. During the magnetic field flat phase, the magnetic field does not change with time; the Nieer and Brownian relaxation times are constant and may differ, thus enabling decoupling. Based on this, this invention proposes a spectral analysis relaxation theory, a theory of magnetization reversal recovery during pulsed excitation, used to describe the magnetization recovery signal in pulsed square wave excitation. Based on this theory, this invention proposes a magnetic particle relaxation time detection method, and further proposes an imaging method, device, electronic device, and storage medium based on signal spectral analysis of magnetic particle relaxation time.

[0080] Firstly, such as Figure 2 As shown in the embodiment of the present invention, an imaging method based on signal spectrum analysis of magnetic particle relaxation time may include the following steps:

[0081] S1 generates a magnetic field free point FFP;

[0082] Based on MPI imaging technology, it can be understood that the magnetic field free point (hereinafter referred to as FFP) is generated by the selected field.

[0083] This step can generate FFP using a preset static gradient magnetic field. For example, the gradient of this preset static gradient magnetic field can be along the x and y directions, and the field strength can be set as needed. Gradient fields in different directions can be achieved using gradient coil pairs with spacing in the corresponding directions. The coils used can be, for example, Maxwell coils, etc., and there are no restrictions here.

[0084] S2, move the FFP within the spatial range of the target to be tested where a single type of magnetic nanoparticle has been injected, generate a pulsed square wave excitation magnetic field at each FFP position, and receive the original signal generated by the magnetic nanoparticles in the target to be tested at that FFP position under the excitation of the pulsed square wave excitation magnetic field.

[0085] In this embodiment of the invention, the target to be tested can be a human body, animal body, etc. The target to be tested is pre-injected with a single type of magnetic nanoparticle, which means containing only one type of magnetic nanoparticle. This type of magnetic nanoparticle can be superparamagnetic iron oxide nanoparticles (Resovist), specifically various commercially available magnetic nanoparticles, such as iron carboxymethyl glycosides, Perimag, Synomag-D, and the Dongna series magnetic particles, or a self-developed and synthesized magnetic nanoparticle; no specific limitation is made here. However, in one optional embodiment, in order to achieve good relaxation time detection and imaging results, the selected magnetic nanoparticles are those that have been pre-tested and evaluated on different target samples as experimental samples, showing better response and detection effects.

[0086] The magnetic nanoparticles are in a colloidal suspension with a concentration of up to 0.5 mmol Fe / mL. The injection dosage is set according to the weight of the target. The magnetic nanoparticles are administered intravenously, either manually by a doctor or automatically by an instrument. As is well known, magnetic nanoparticles are superparamagnetic. When an external magnetic field is present, the magnetic moments of the magnetic nanoparticles in the liquid will deflect towards the direction of the applied magnetic field, generating a change in magnetic flux in the receiving coil, thereby producing a response voltage signal, which is the original signal in this embodiment of the invention.

[0087] Specifically, the spatial range of the target under test corresponds to the entire field of view (FOV). The field of view device (FFP) is moved within this range to scan the target point by point. At each FFP position, a pulsed square wave excitation magnetic field is generated and the original signal is acquired. Regarding the generation of the pulsed square wave excitation magnetic field and the acquisition of the original signal, any method or device capable of generating a pulsed square wave excitation magnetic field can be used to generate the required pulsed square wave excitation magnetic field, and any signal receiving method or device can be used to receive the signal generated by the magnetic particles under the excitation of the pulsed square wave excitation magnetic field, such as a receiving coil, etc. No specific limitations are imposed here.

[0088] In one optional implementation, generating a pulsed square wave excitation magnetic field at each FFP location and receiving the original signal generated by the magnetic nanoparticles within the target at that FFP location under the excitation of the pulsed square wave excitation magnetic field includes:

[0089] At each FFP location, a pulsed square wave excitation magnetic field is generated using a pre-designed pulsed square wave relaxor, and the original signal generated by the magnetic nanoparticles in the target at that FFP location under the excitation of the pulsed square wave excitation magnetic field is received.

[0090] The pulse square wave relaxor (TWR) of this invention integrates pulse square wave excitation magnetic field generation and raw signal reception functions. The TWR design can eliminate the need for a resonant circuit, allowing trapezoidal waveform excitation. In one optional embodiment, the pulse square wave relaxor may include:

[0091] 1) Digital acquisition card, used to generate analog signals of pulse square waves and to digitize the input raw signals;

[0092] 2) An AC power amplifier, used to amplify the analog signal;

[0093] 3) Transmitting coil, used to transmit amplified analog signals to generate pulsed square wave excitation magnetic field;

[0094] 4) A current sensor is used to monitor the emission waveform of the AC power amplifier in real time;

[0095] 5) A receiving coil, used to receive the original signal generated by the magnetic particles under the excitation of the pulsed square wave excitation magnetic field;

[0096] 6) A low-noise preamplifier is used to amplify the original signal and provide it to the digital acquisition card.

[0097] The various components of the pulse square wave relaxor can be implemented using existing commercial equipment or self-developed equipment, without specific limitations. For example, in optional embodiments, the data acquisition card can be a DAQ NI6363, the AC power amplifier can be an AE Techron 7548, the low-noise preamplifier can be an SR560, and the transmitting and receiving coils can be implemented using multilayer Litz coils, etc. Of course, the pulse square wave relaxor of this invention is not limited to the structure described above.

[0098] S3, perform an inverse Laplace transform on the original signal, and obtain the spectral curve corresponding to the FFP position based on the inverse Laplace transform result;

[0099] In this embodiment of the invention, the relaxation process of magnetization during the flat phase of the magnetic field under pulsed excitation is similar to the reverse recovery pulsed longitudinal (T1) relaxation process in magnetic resonance imaging. Reverse recovery uses an initial pulse of 180° to reverse the longitudinal magnetization intensity, which recovers with a time constant T1. This embodiment of the invention assumes that the magnetic field suddenly switches from a negative peak to a positive peak during pulsed square wave excitation, and vice versa. In this embodiment of the invention, under pulsed excitation from zero increasing magnetic field, the magnetization process is obtained by spectral analysis. Specifically, after each pulsed square wave excitation with a 180° magnetic field reversal, the original signal is acquired for spectral analysis; the magnetization intensity of the magnetic nanoparticles will be recovered through two relaxation effects. The two-step magnetization response in the Brownian state occurs after the Niehr state. The relaxation-induced decay signal during the flat phase of the magnetic field can be spectrally analyzed using the UPEN algorithm. The UPEN algorithm is characterized by a uniform smoothing penalty for sharp and widespread components.

[0100] According to the inverse Laplace transform, the attenuated signal during the flat phase of the magnetic field, i.e., the signal after performing the inverse Laplace transform on the original signal, can be expressed as:

[0101]

[0102] Where non-adiabatic represents non-adiabatic conditions; t represents time; ε(t) is the noise in the signal; τ N τ represents the Niehr relaxation time constant; B τ represents the Brownian relaxation time constant. N and τ B The values ​​of τ all represent the corresponding relaxation times; N <τ B ; a represents the percentage of Neill relaxation, b represents the percentage of Brownian relaxation, and a+b=1.

[0103] The corresponding spectral curve can be obtained from the signal after the inverse Laplace transform. This can be achieved using existing technologies, such as the PDCO algorithm. The PDCO method can be used to perform spectral analysis on the attenuated signal caused by relaxation in the flat magnetic field segment. This method is a primal-dual internal method for solving linearly constrained optimization problems with convex objective functions, implemented in MATLAB. For details, please refer to the relevant technical explanations; they will not be elaborated here. Figure 3 The left figure shows the attenuation signal of Synomag-D and 1% glycerol under trapezoidal pulse wave excitation during the flat phase of the magnetic field with different excitation field amplitudes; the right figure shows the spectral analysis results of the attenuation signal during the flat phase, i.e., the spectral curve, which contains multiple spectral curves. Figure 3 It is evident that both relaxation times decrease as the field amplitude increases.

[0104] S4. Based on the regions of the two peaks in the spectrum curve and the distribution of the two relaxation time peaks in the spectrum curve determined by the pre-experiment of the single magnetic nanoparticle, determine the magnetic particle relaxation time detection result at the FFP position.

[0105] The magnetic particle relaxation time detection results include the Niehr relaxation time constant, the Brown relaxation time constant, and the percentages of Niehr relaxation and Brown relaxation.

[0106] In one optional implementation, S4 may include:

[0107] S41, Based on the region of the two peaks present in the spectrum curve, determine the first relaxation time, the second relaxation time, and their respective percentages;

[0108] S42, based on the distribution of the peaks corresponding to the two relaxation times in the spectral curve determined by the pre-experiment of the single magnetic nanoparticle, distinguish the Niehr relaxation time and Brown relaxation time in the two relaxation times in the spectral curve, and obtain the magnetic particle relaxation time detection result at the FFP position.

[0109] In this embodiment of the invention, if there are two relaxation times, the spectrum curve will show a region with two peaks. For S41, each relaxation time and its corresponding percentage can be determined for each peak. However, at this time, it is impossible to distinguish which of the two relaxation times is the Niel relaxation time and which is the Brown relaxation time.

[0110] In one optional implementation, S41 may include:

[0111] The magnitudes of the first relaxation time and the second relaxation time are determined based on the peak positions of the two peaks in the spectrum curve, and the percentages of the first relaxation time and the second relaxation time are determined based on the area of ​​the two peaks.

[0112] Please see Figure 3 To understand any spectrum curve in the right-hand figure, the horizontal axis of the spectrum curve represents time. Determining the relaxation time based on the peak position means taking the relaxation time with the highest frequency among the peak values, which is the time value on the horizontal axis corresponding to the peak. The percentage of relaxation time is obtained by dividing the area under the curve (AUC) of the relaxation time peak by the total AUC in the relaxation time histogram. Simultaneously, the full width at half maximum (FWHM) of the relaxation time distribution can be calculated; FWHM corresponds to the particle size distribution range of the magnetic particles.

[0113] Regarding S42, in one optional implementation, for the single type of magnetic nanoparticle, pre-determining the distribution of the peaks corresponding to the two relaxation times in the spectral curve through experiments may include:

[0114] 1) For the preparation of single magnetic nanoparticle samples for a single type of magnetic nanoparticle, the environmental parameter sequence of the single magnetic nanoparticle sample is determined based on the difference in response of the pre-determined Niehr relaxation time or Brown relaxation time to changes in the environmental parameters of the magnetic particles.

[0115] A single magnetic particle sample refers to a sample containing only one type of magnetic nanoparticle. This single magnetic particle sample can be any commercially available magnetic nanoparticle, such as iron-carboxymethylglucan, Perimag, Synomag-D, or the Dongna series magnetic particles, or it can be any self-developed and synthesized magnetic nanoparticle. Synomag-D is a multinuclear magnetic nanoparticle coated with dextran, with an initial iron concentration of 6 mg / ml. The following example uses a single magnetic particle sample corresponding to this magnetic nanoparticle.

[0116] The environmental parameters include viscosity, stiffness, temperature, and microenvironment, and may also include the free or bound state of magnetic particles.

[0117] This invention's embodiments reveal that the Néel relaxation time is a function of temperature and magnetic core volume. The Brownian relaxation time, on the other hand, depends on the fluid viscosity, temperature, and the hydrodynamic volume of the magnetic nanoparticles. Both Néel and Brownian relaxation times are temperature-dependent, and temperature can serve as an environmental parameter for the magnetic particles. Accurate measurement of both relaxation times can provide precise temperature measurement methods. Therefore, the achieved temperature measurement can be further applied in fields such as medicine. For example, real-time temperature imaging is crucial in thermal ablation treatments such as magnetothermal therapy and high-intensity focused ultrasound; temperature is associated with poor prognosis in breast cancer patients; heatstroke, characterized by extreme hyperthermia, also requires accurate temperature measurement; and the anticancer effects of HSP90 inhibitors can be evaluated by inducing heat shock through magnetothermal therapy combined with temperature monitoring, etc.

[0118] One important application of bioviscous environments is in the medical field. For example, studying cellular responses to the viscoelasticity of the matrix surface is crucial for controlling cellular behavior, such as controlling stem cell proliferation. Alternatively, in the tumor microenvironment, the overexpression of indicators such as lymphocytes, lactate, proteins, enzymes, lipids, extracellular secretions, and extracellular matrix components can lead to increased viscosity. Increased whole blood viscosity can raise cardiovascular mortality and the risk of Alzheimer's disease, while blood viscosity decreases in mice with inflammation and peritonitis. Biostiffness environments can also be applied in the medical field, such as the changes in stiffness caused by the intervention of different materials like stents and catheters in biological systems. Therefore, predicting viscosity and stiffness holds promise for widespread application in medical and other fields.

[0119] The free state of magnetic particles refers to the state in which each magnetic particle is independent, unrelated to others, and in a state of free movement; the combined state of magnetic particles refers to the state in which multiple magnetic particles are tightly packed together, forming a cluster, unable to move freely, and constrained and restricted by the surrounding magnetic particles.

[0120] The microenvironment refers to the pH value and granzyme environment of the magnetic particles, such as the pH value and granzyme environment of a tumor environment. Granzymes are serine proteases that play an important role in killing virus-infected cells and tumor cells by NK cells and CTLs. Granzymes are granule-related enzymes in cytotoxic T lymphocytes. The pH value and granzymes in the tumor environment can break down bound magnetic particles, causing them to change from a bound state to a free state. This embodiment of the invention can detect the microenvironment by detecting this change.

[0121] This invention utilizes the conclusion that the response difference of a pre-determined Niehr relaxation time or Brownian relaxation time to changes in the environmental parameters of a magnetic particle to determine the environmental parameter sequence of a single magnetic particle sample; wherein the environmental parameter sequence contains multiple environmental parameter values ​​that exhibit the same trend of change.

[0122] Specifically, the environmental parameter sequence can be any one of viscosity, hardness, temperature, or microenvironment. For example, if the environmental parameter sequence is for viscosity, it includes multiple environmental parameter values ​​that are values ​​related to viscosity, and these values ​​are set according to the same trend of increasing or decreasing.

[0123] In the experiment, individual magnetic nanoparticles such as Synomag-D can be placed in a buffer solution composed of a mixture of water and glycerol. By changing the composition of the glycerol, the viscosity of the single magnetic particle sample can be altered, thereby simulating different biological viscosity environments. For example, Synomag-D with an original iron concentration of 6 mg / ml has the lowest viscosity, which increases after adding a buffer solution composed of a mixture of water and glycerol. In this embodiment of the invention, to obtain single magnetic particle samples with different viscosities, a series of water-glycerol mixtures with glycerol concentrations ranging from 1% to 70% wt can be prepared as buffer solutions for diluting the magnetic nanoparticles.

[0124] Furthermore, individual magnetic nanoparticles such as Synomag-D can be placed in a mixture of water and gelatin gel, using this mixture as an embedding matrix for the individual magnetic nanoparticles to further limit their Brownian mobility. In this invention, the hardness of the single magnetic particle sample can be altered by changing the gelatin composition, thereby simulating different biological hardness (stiffness) environments. For example, this invention can use a water-gelatin gel with a gelatin concentration of 5% to 30% wt as the embedding matrix for the magnetic nanoparticles, and so on. The preparation process can, for example, involve adding gelatin powder to ddH2O (double-distilled water) and heating it to a certain temperature, such as 65°C, until the gelatin powder is completely dissolved. The magnetic nanoparticles are then uniformly dispersed in the resulting mixture, and the sample is solidified at a set temperature, such as 4°C. The iron concentration of the single magnetic particle sample can be set to 0.5 mg / ml, etc.

[0125] In this embodiment of the invention, the obtained single magnetic particle samples can also be placed at different temperatures to study the relaxation behavior of magnetic nanoparticles at different temperatures. Specifically, for example, a digital temperature-controlled water bath can be used to heat the single magnetic particle samples to 25°C, 37°C and 52°C respectively, and relaxation time can be detected and analyzed at each temperature, etc.

[0126] In this embodiment of the invention, the obtained single magnetic particle samples can also be placed in different microenvironments to study the relaxation behavior of magnetic nanoparticles in different microenvironments. Specifically, the changes in the microenvironment can be controlled by adjusting the pH value of the tumor environment and the amount of granzyme.

[0127] The differences in response to changes in the environmental parameters of the magnetic particles regarding the predetermined Niehr relaxation time or Brown relaxation time will be explained later.

[0128] 2) Generate a pulsed square wave excitation magnetic field and receive the sample signal generated by the single magnetic particle sample corresponding to each environmental parameter value under the excitation of the pulsed square wave excitation magnetic field;

[0129] This step is the same as in S2, where a pulsed square wave excitation magnetic field is generated and the original signal generated by the magnetic nanoparticles in the target under test at an FFP location under the excitation of the pulsed square wave excitation magnetic field is received. However, the difference is that each sample signal is generated under a certain environmental parameter value.

[0130] 3) Perform an inverse Laplace transform on each sample signal and obtain the corresponding spectrum curve based on the results of each inverse Laplace transform;

[0131] This step is similar to S3, and will not be described in detail here.

[0132] 4) For any given spectral curve, based on the regions containing two peaks, determine the first relaxation time, the second relaxation time, and their respective percentages under the corresponding environmental parameter values; and based on the differences in the changing trends of the first and second relaxation times among the obtained multiple spectral curves, distinguish the Nieer relaxation time and the Brownian relaxation time among the two relaxation times in any given spectral curve, and determine the distribution of the peaks corresponding to the two relaxation times in the spectral curve corresponding to a single type of magnetic nanoparticle.

[0133] Through the above process, the corresponding relaxation time detection results can be obtained for any spectral curve, including the Niehr relaxation time constant, the Brown relaxation time constant, and the percentages of Niehr relaxation and Brown relaxation.

[0134] In this section, for any given spectral curve, the process of determining the first relaxation time, the second relaxation time, and their respective percentages under the corresponding environmental parameter values ​​based on the regions containing two peaks can be understood by referring to the corresponding section of S4 above.

[0135] To facilitate understanding of the differences in the changing trends of the first and second relaxation times in the multiple spectral curves obtained above, distinguishing the Niehr relaxation time and Brown relaxation time in any spectral curve, and determining the distribution of the peaks corresponding to the two relaxation times in the spectral curve of a single magnetic nanoparticle, the process of determining the conclusion of the pre-determined Niehr relaxation time or Brown relaxation time in response to changes in the environmental parameters of the magnetic particle mentioned in 1) is explained here.

[0136] This invention employs prior research using known sample data to investigate the relationship between two relaxation times of magnetic nanoparticles and various functional parameters. The following example uses a single magnetic particle sample of Synomag-D. The viscosity change is achieved by altering the glycerol content in a buffer solution composed of a water-glycerol mixture. For instance, a series of water-glycerol mixtures with glycerol concentrations ranging from 1% to 70% wt can be prepared as buffer solutions for diluting Synomag-D. The stiffness change is achieved by altering the gelatin concentration in a mixture composed of water and gelatin gel; for example, water-gelatin gels ranging from 5% to 30% wt can be prepared. Temperature changes can be achieved by heating Synomag-D to multiple temperatures, such as 25°C, 37°C, and 52°C, using a digitally temperature-controlled water bath.

[0137] In this embodiment of the invention, the relationship between the relaxation time of magnetic nanoparticles and environmental parameters was studied experimentally. The following describes the study of some environmental parameters.

[0138] (1) Relaxation time characteristics under different viscosities

[0139] For the spectral analysis of the attenuation signal during the flat phase of the Synomag-D magnetic field, please refer to Figure 4(a). The left side of Figure 4(a) shows the spectral analysis results of relaxation times at different viscosities under pulsed square wave excitation with a magnetic field amplitude of 3 mT, and the right side shows the spectral analysis results of relaxation times at different viscosities under pulsed square wave excitation with a magnetic field amplitude of 6 mT. Both figures contain multiple spectral curves. As can be seen from the figures, the peak with a shorter relaxation time is estimated to be Niehr relaxation because it changes slightly with increasing viscosity. Another peak with a longer relaxation time increases with increasing viscosity and is considered to be Brownian relaxation. By comparing 3 mT and 6 mT, the increase is more significant under higher excitation field amplitudes. That is, the relaxation spectra of Synomag-D samples at different viscosity levels have two relaxation time peaks. The lower peak, corresponding to a longer relaxation time, increases with increasing viscosity and is identified as the Brownian relaxation component. The higher peak value corresponds to a shorter relaxation time, which decreases slightly with increasing glycerol concentration, and is identified as the Niel relaxation component.

[0140] Please refer to Figure 4(b), which shows the two relaxation times at different viscosity levels. Within the range of 0.9–3.2 mPa·s, the Brownian relaxation time exhibits a positive linear relationship with the viscosity level. When the viscosity is greater than 3.2 mPa·s, the Brownian relaxation time reaches saturation and does not change with further viscosity increases. The Néel relaxation time decreases slightly with increasing viscosity. When the viscosity level is greater than 3.2 mPa·s, the Néel relaxation time for all field amplitudes shows a similar saturation effect.

[0141] Therefore, it can be concluded that Brownian relaxation time increases with increasing viscosity.

[0142] (2) Relaxation time characteristics under different stiffnesses

[0143] According to spectral analysis, the Brownian relaxation peak decreases and disappears with increasing gelatin concentration. The Neel relaxation time decreases and broadens with increasing stiffness and gelatin concentration. See Figure 5(a) for details. The left panel of Figure 5(a) shows the spectral analysis results of Synomag-D with different gelatin concentrations and stiffnesses under a 3 mT magnetic field amplitude, and the right panel shows the spectral analysis results of Synomag-D with different gelatin concentrations and stiffnesses under a 6 mT magnetic field amplitude. See also another example, as shown in Figure 5(b). The left panel of Figure 5(b) shows the spectral analysis results of Synomag-D with different gelatin concentrations under a 3 mT magnetic field amplitude, and the right panel shows the spectral analysis results of Synomag-D with different gelatin concentrations under a 6 mT magnetic field amplitude. It can be seen that the Synomag-D sample exhibits Neel and Brownian relaxation time peaks at low gelatin concentrations and field amplitudes. With increasing gelatin concentration, the Neel relaxation time decreases slightly. At high gelatin concentrations and high field amplitudes, the Brownian relaxation peak disappears. This can also be understood in conjunction with Figure 5(c), which shows the relaxation time of the gel in the gel at different field amplitudes, illustrating the relationship between relaxation time and gelatin concentration. It can be seen that the Niehr relaxation time generally decreases with increasing gelatin concentration. When the gelatin concentration is greater than 10 wt%, the Brownian relaxation time disappears due to the immobility of MNPs; that is, the Brownian relaxation component disappears at high gelatin concentrations.

[0144] Therefore, it can be concluded that as hardness increases, the peak amplitude corresponding to the Brownian relaxation time in the spectrum curve decreases, and its proportion also decreases. This shows that there is a certain relationship between the Brownian relaxation time and stiffness in the spectrum curve.

[0145] In clinical practice, stiffness can correspond to conditions such as liver cirrhosis and tumor masses, and the above conclusions can be used for corresponding detection.

[0146] (3) Relaxation time characteristics at different temperatures

[0147] See Figure 6 , Figure 6 The images show the spectral analysis results of Synomag-D at different temperatures. The left image corresponds to a 1% glycerol concentration, and the right image corresponds to a 10% glycerol concentration. From the signal spectrum analysis, at a 1% glycerol concentration, the Brownian relaxation time peak width narrows with increasing temperature, meaning the Brownian relaxation time decreases with increasing temperature, while the Nilsner relaxation time shows little change with increasing temperature.

[0148] Therefore, it can be concluded that the Brownian relaxation time decreases as the temperature increases.

[0149] (4) Relaxation time characteristics under different microenvironments

[0150] Experiments based on embodiments of the present invention lead to the conclusion that as the pH of the microenvironment increases or decreases, and as the amount of granzyme increases, magnetic particles change from a bound state to a free state, resulting in a shorter Brownian relaxation time, an increased peak amplitude, and a higher proportion of the peak. Further illustration is omitted here.

[0151] Therefore, Brownian relaxation time can be used to detect changes in the microenvironment and enable various applications in biology, medicine, and other fields. For example, during apoptosis, cytoplasmic viscosity increases. In this invention, magnetic particles can be incorporated into cells, and relaxation analysis can be used to study cytoplasmic / organelle viscosity. For instance, using the aforementioned conclusions, Brownian relaxation time can be used to detect changes in the intracellular microenvironment, thereby determining the number of apoptotic cells. Studies have shown that the method of this invention can detect changes in intracellular viscosity of 1-10 mPa, thus effectively achieving apoptosis monitoring / detection.

[0152] For example, drugs may be released as the microenvironment changes. Based on the relaxation time of magnetic particles and the changing patterns of the microenvironment, combined with pre-determined patterns of drug release with changes in the microenvironment, drug release efficiency can be detected. Of course, the applications of microenvironment detection are not limited to those described above.

[0153] Compared with the existing technology that uses sinusoidal excitation, the embodiments of the present invention use pulsed square wave excitation, and firstly, innovatively propose an effective means to distinguish and detect the Nieer relaxation time and Brownian relaxation time of magnetic nanoparticles.

[0154] The above research results indicate that, for any single magnetic nanoparticle, the changing trend of a certain relaxation time peak in multiple spectral curves obtained from increasing or decreasing environmental parameter values ​​can be determined in advance. This, combined with the pre-determined difference in the response of the NieR or Brownian relaxation time to changes in the environmental parameters of the magnetic particle (i.e., the response difference conclusion mentioned earlier), allows for the comparison and differentiation of the NieR and Brownian relaxation times in any spectral curve of the single magnetic nanoparticle. Based on this, the distribution of the two relaxation time peaks in the spectral curve of the single magnetic nanoparticle can be determined. Therefore, during execution S42, based on the distribution of the two relaxation time peaks in the spectral curve pre-determined for the single magnetic nanoparticle, the NieR and Brownian relaxation times in the spectral curve determined in S41 can be distinguished, thus obtaining the magnetic particle relaxation time detection result at the FFP position.

[0155] Specifically, based on the distribution of the peaks corresponding to the two relaxation times in the spectral curve determined by the prior experiments for this single type of magnetic nanoparticle, the specific method for distinguishing the Niehr relaxation time and Brown relaxation time in the spectral curve determined by S41 can be as follows: The correspondence between the two peaks in the spectral curve of this single type of magnetic nanoparticle and each relaxation time can be used as the distribution of the peaks corresponding to the two relaxation times in the spectral curve, such as the difference in position on both sides of the graph. This can be used as prior knowledge to determine the relaxation times corresponding to the two peaks in S41. Alternatively, the spectral curve of this single type of magnetic nanoparticle (carrying the relaxation time labels corresponding to each peak) can be used as the distribution of the peaks corresponding to the two relaxation times, and the relaxation times corresponding to the two peaks in S41 can be determined by comparing the similarity of the peaks in the curve, and so on.

[0156] S5. Based on at least one of the same terms in the magnetic particle relaxation time detection results obtained from all FFP positions, an imaging is performed to obtain a relaxation time image of the target under test.

[0157] This step can utilize at least one of the following for imaging: the Niehr relaxation time constant, the Brownian relaxation time constant, the percentage of Niehr relaxation, or the percentage of Brownian relaxation obtained from all FFP locations. Furthermore, depending on the scanning method of the target under test, two-dimensional imaging or three-dimensional imaging can be performed. Specific methods for imaging using point data of different dimensions can be implemented using existing technologies, which is not the focus of this embodiment. It is understood that imaging using any one of the above four items can obtain a relaxation time imaging map corresponding to the target under test. Alternatively, in an optional embodiment, at least two of these items can be combined to obtain a relaxation time imaging map corresponding to the target under test, and so on; all of these are reasonable.

[0158] This invention utilizes multicolor magnetic particle imaging combined with magnetic field free point scanning. At each FFP location, the Nieer relaxation time and Brownian relaxation time of the magnetic nanoparticles are distinguished and detected using a spectral analysis-based inversion recovery method. The relaxation time imaging map obtained using the same detection results from all FFP locations can at least be used to distinguish plaques, ducts, and vascular regions.

[0159] Specifically, in this embodiment of the invention, a digital blood vessel phantom is constructed through simulation for imaging studies.

[0160] Based on the above research conclusions, Brownian relaxation time and other methods can be used to predict functional parameters such as viscosity or stiffness. If a target to be tested, which has been pre-injected with magnetic nanoparticles, has different viscosities or stiffness in different regions near its blood vessels, it is feasible to distinguish them using Brownian relaxation time. This makes it feasible to distinguish between catheters, plaques and normal vascular tissue regions. To facilitate intuitive display, imaging can be used.

[0161] As an experimental example, this embodiment of the invention constructs a digital blood vessel phantom using simulation methods. Specifically, it is a 5×6cm² vascular system model composed of a container structure with suspended magnetic nanoparticle clusters (MNPs), representing a multicolor MPI digital phantom, such as... Figure 7 As shown, this includes catheters, plaques, and blood vessels. The vascular system model was infused with the same type of magnetic nanoparticles. The diameter of the nanoparticles around the main branches of the blood vessels was ≥3 mm, and the diameter of the catheters inserted into the vessels was 0.83 mm. Point-by-point scanning of the vascular system model using FFP is illustrated in the diagram. Figure 8 As shown.

[0162] A uniform pulsed square wave excitation magnetic field can be used as the excitation field and combined with a free-floating pressure filter (FFP) for spectral imaging. The relaxation time imaging map can be generated by moving the FFP point-by-point across the entire field of view (FOV).

[0163] Assume the gradient of the chosen field is along the x and y directions, and the excitation field is along the z direction. The formula for calculating the total magnetic field is:

[0164]

[0165] Where t represents time; x, y, and z are three spatial coordinates. It is a unit vector in three coordinate directions; G x G represents the gradient field intensity in the x-direction; y H is the gradient field intensity in the y-direction; H(t) is the magnitude of the magnetic field at time t.

[0166] Near the center of the FFP, the magnetization fully recovered along the z-direction from a single MNP (magnetic nanoparticle) can be calculated as follows:

[0167]

[0168] Where L(H) is the Langevin function; H represents the magnitude of the total magnetic field; m represents the magnetic moment of a single magnetic nanoparticle; r represents the particle size in nanometers (nm); and H0 represents the magnetic field amplitude during the flat phase of the magnetic field. In FFP(G x =G y The magnetization completely recovered from a single MNP along the z-direction at the center of (=0) is expressed as:

[0169] M z (0)=m·L(H0) (8)

[0170] In this embodiment of the invention, the signal weighting factor is assumed to be the ratio of the magnetization in the z-direction at any position to the magnetization at the center of the FFP, as shown in equation (9). See also... Figure 9 When a pixel moves away from the center of the FFP, the signal weighting factor drops rapidly to zero.

[0171]

[0172] The overall signal, or the original signal, is composed of the digital phantom signal S(r,t) (representing the actual magnetic particle distribution) and the signal weighting factor w. s (r) yielded:

[0173] S FFP (r, t) = S(r, t) * w s (r) (10)

[0174] Here, "*" indicates convolution in the FOV spatial domain. The signal weighting factor is a point spread function (PSF), which is closely related to the image resolution.

[0175] Specifically, a selective magnetic field (G) can be used. x =G y =7.0T / m / u0) forms an FFP, which moves point-by-point throughout the FOV. A total of 100 × 100 FFP positions were generated in the simulation. For each FFP position, the signal weighting factor was convolved with the curve of the digital phantom signal to calculate the curve corresponding to the original signal.

[0176] Based on the specific content of S3 to S4 above, the magnetic particle relaxation time detection results at each FFP position can be obtained, including (τ N , τ B (a, b).

[0177] For (τ) N , τ B At least one parameter from (a, b) can be used for imaging in embodiment S5 of the present invention, and the values ​​of such parameters at all FFP locations can be used.

[0178] In one alternative implementation, due to the Brownian relaxation time, i.e., τ B The correlation between the observed changes in environmental parameters such as viscosity and stiffness, and the imaging based on at least one term from the magnetic particle relaxation time detection results obtained from all FFP locations to obtain a relaxation time imaging map of the target, may include:

[0179] Based on the Brownian relaxation time constants obtained from the magnetic particle relaxation time detection results at all FFP locations, an image of the Brownian relaxation time of the target under test is obtained.

[0180] Specifically, for the digital vascular phantom image, baseline image, and Brownian relaxation time imaging at a field amplitude of 4.5 mT, please refer to [link to relevant documentation]. Figures 10(a) to 10(c) As shown; wherein, the digital blood vessel phantom image in Figure 10(a) is artificially designed; the baseline image in Figure 10(b) is reconstructed by calculating the signal area under the curve during the full excitation period at each FFP location, specifically the image of magnetization obtained by integrating the original signal, the integration is achieved using formula (4), the distribution of blood vessels can be seen on the baseline image, which can be compared with the Brownian relaxation time imaging obtained in the embodiment of the present invention; or in an optional embodiment, a colored Brownian relaxation time imaging can be superimposed on the baseline image to obtain the final imaging image, which is easier to observe, the Brownian relaxation time imaging in Figure 10(c) uses different colors to represent the Brownian relaxation time τ B Since there are no magnetic nanoparticles outside the blood vessel, this part appears black. In the normal area of ​​the blood vessel where no plaque or duct appears, the magnetic nanoparticles are uniformly distributed, so the Brownian relaxation time is the same, and the image color is consistent. However, the plaque has viscous MNPs compared to the normal blood vessel area, so the viscosity is different. The duct area has solidified MNPs compared to the normal blood vessel area, so the stiffness is different. It can be seen that the normal blood vessel area, plaque and duct can be distinguished by Brownian relaxation time imaging.

[0181] Specifically, regarding Brownian relaxation time: 34.53 μs in the plaque area, 12.61 μs in the duct area, and 30.27 μs in the vascular area. Regarding Niehr relaxation time: 8.20 μs in the plaque area, 3.43 μs in the duct area, and 8.23 ​​μs in the vascular area.

[0182] See Figure 11 , Figure 11 This diagram illustrates the variation of Brownian relaxation times of plaque, duct, and vascular regions with the average signal period in a simulation experiment according to an embodiment of the present invention. At an excitation field amplitude of 4.5 mT, the Brownian relaxation times of the plaque, duct, and vascular regions initially decrease with increasing average signal period. When the average signal period is ≥ 40, the Brownian relaxation times from different tissue regions stabilize. In other words, the Brownian relaxation times of the plaque, duct, and vascular regions decrease and stabilize with increasing average signal period. If 40 excitation periods are used for image acquisition in this embodiment of the present invention, the total scanning time of the digital phantom is approximately 200 seconds (100 × 100 pixels × 40 / 2 kHz).

[0183] Of course, the imaging methods used in the embodiments of the present invention are not limited to Brownian relaxation time. Imaging can also be performed according to the correspondence between the other three items and the changes in functional parameters. For example, the proportion of Brownian relaxation time can be used, or Brownian relaxation time can be used in conjunction with imaging, etc., for applications in fields such as biomedicine. Detailed examples will not be provided here.

[0184] This invention utilizes spectral analysis to separate and detect relaxation time, and can combine this method with magnetic field free point scanning for multicolor magnetic particle imaging to distinguish plaques, ducts, and vascular regions.

[0185] Secondly, corresponding to the above method embodiments, this invention also provides an imaging device based on signal spectrum analysis of magnetic particle relaxation time, such as... Figure 12 As shown, the device includes:

[0186] FFP generation module 1201 is used to generate magnetic field free points (FFPs).

[0187] The original signal acquisition module 1202 is used to move the FFP within the spatial range of the target under test where a single type of magnetic nanoparticle has been injected, generate a pulsed square wave excitation magnetic field at each FFP position, and receive the original signal generated by the magnetic nanoparticles in the target under test at that FFP position under the excitation of the pulsed square wave excitation magnetic field.

[0188] The spectrum curve acquisition module 1203 is used to perform an inverse Laplace transform on the original signal and obtain the spectrum curve corresponding to the FFP position based on the inverse Laplace transform result.

[0189] The magnetic particle relaxation time detection module 1204 is used to determine the magnetic particle relaxation time detection result at the FFP position based on the region of the two peaks in the spectrum curve and the distribution of the two relaxation time corresponding peaks in the spectrum curve determined by the pre-experiment of the single magnetic nanoparticle; wherein, the magnetic particle relaxation time detection result includes the Niehr relaxation time constant, the Brown relaxation time constant, and the percentage of Niehr relaxation and Brown relaxation.

[0190] The imaging module 1205 is used to perform imaging based on at least one of the same terms in the magnetic particle relaxation time detection results obtained from all FFP positions, so as to obtain a relaxation time imaging map of the target under test.

[0191] Optionally, when the raw signal acquisition module 1202 generates a pulsed square wave excitation magnetic field at each FFP location it moves to, and receives the raw signal generated by the magnetic nanoparticles within the target under test at that FFP location under the excitation of the pulsed square wave excitation magnetic field, it is specifically used for:

[0192] At each FFP location, a pulsed square wave excitation magnetic field is generated using a pre-designed pulsed square wave relaxor, and the original signal generated by the magnetic nanoparticles in the target at that FFP location under the excitation of the pulsed square wave excitation magnetic field is received.

[0193] Optionally, the pulse square wave relaxor includes:

[0194] A digital acquisition card is used to generate analog signals of pulse square waves and to digitize the input raw signals.

[0195] An AC power amplifier is used to amplify the analog signal;

[0196] The transmitting coil is used to transmit amplified analog signals to generate a pulsed square wave excitation magnetic field;

[0197] A current sensor is used to monitor the emission waveform of the AC power amplifier in real time.

[0198] A receiving coil is used to receive the original signal generated by a single magnetic particle sample under the excitation of the pulsed square wave excitation magnetic field;

[0199] A low-noise preamplifier is used to amplify the original signal and provide it to the digital acquisition card.

[0200] Optionally, when the magnetic particle relaxation time detection module 1204 determines the magnetic particle relaxation time detection result at the FFP position based on the region of two peaks in the spectrum curve and the distribution of the two relaxation time corresponding peaks in the spectrum curve determined by pre-experimentation for the single type of magnetic nanoparticle, it is specifically used for:

[0201] Based on the regions with two peaks in the spectrum curve, determine the first relaxation time, the second relaxation time, and their respective percentages;

[0202] Based on the distribution of the peaks corresponding to the two relaxation times in the spectral curves determined by the prior experiments on the single type of magnetic nanoparticle, the Niehr relaxation time and Brown relaxation time in the two relaxation times in the spectral curves are distinguished, and the magnetic particle relaxation time detection result at the FFP position is obtained.

[0203] Optionally, determining the first relaxation time, the second relaxation time, and their respective percentages based on the regions of the two peaks present in the spectral curve includes:

[0204] The magnitudes of the first relaxation time and the second relaxation time are determined based on the peak positions of the two peaks in the spectrum curve, and the percentages of the first relaxation time and the second relaxation time are determined based on the area of ​​the two peaks.

[0205] Optionally, for the single type of magnetic nanoparticle, the distribution of the peaks corresponding to the two relaxation times in the spectral curve is determined in advance through experiments, including:

[0206] To prepare single magnetic particle samples for a single type of magnetic nanoparticle, an environmental parameter sequence for the single magnetic particle sample is determined based on the difference in response of the pre-determined Niehr relaxation time or Brownian relaxation time to changes in the environmental parameters of the magnetic particles; wherein, the environmental parameters include viscosity, stiffness, temperature, and microenvironment; the environmental parameter sequence contains multiple environmental parameter values ​​and exhibits the same trend of change;

[0207] A pulsed square wave excitation magnetic field is generated, and the sample signal generated by the single magnetic particle sample corresponding to each environmental parameter value under the excitation of the pulsed square wave excitation magnetic field is received.

[0208] Perform an inverse Laplace transform on each sample signal and obtain the corresponding spectrum curve based on the results of each inverse Laplace transform;

[0209] For any given spectral curve, based on the regions containing two peaks, determine the first relaxation time, the second relaxation time, and their respective percentages under the corresponding environmental parameter values. Furthermore, based on the differences in the changing trends of the first and second relaxation times among multiple spectral curves, distinguish the Niehr relaxation time and Brown relaxation time among the two relaxation times in any given spectral curve, and determine the distribution of the peaks corresponding to the two relaxation times in the spectral curve of a single magnetic nanoparticle.

[0210] Optionally, when the imaging module 1205 performs imaging on at least one term of the magnetic particle relaxation time detection results obtained based on all FFP positions to obtain a relaxation time image of the target under test, it is specifically used for:

[0211] Based on the Brownian relaxation time constants obtained from the magnetic particle relaxation time detection results at all FFP locations, an image of the Brownian relaxation time of the target under test is obtained.

[0212] For details, please refer to the imaging method based on signal spectrum analysis of magnetic particle relaxation time described in the first aspect, which will not be repeated here.

[0213] Thirdly, embodiments of the present invention also provide an electronic device, such as... Figure 13 As shown, it includes a processor 1301, a communication interface 1302, a memory 1303, and a communication bus 1304, wherein the processor 1301, the communication interface 1302, and the memory 1303 communicate with each other through the communication bus 1304.

[0214] The memory is used to store computer programs;

[0215] When the processor executes the program stored in the memory, it implements the steps of any of the imaging methods based on signal spectrum analysis of magnetic particle relaxation time provided in the first aspect of the present invention.

[0216] The communication bus mentioned in the above electronic devices can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus can be divided into address bus, data bus, control bus, etc. For ease of illustration, only one thick line is used to represent it in the diagram, but this does not mean that there is only one bus or one type of bus.

[0217] The communication interface is used for communication between the aforementioned electronic devices and other devices.

[0218] The memory may include random access memory (RAM) or non-volatile memory (NVM), such as at least one disk storage device. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor.

[0219] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0220] The method provided in this invention can be applied to electronic devices. Specifically, the electronic device can be a desktop computer, a portable computer, a smart mobile terminal, a server, etc. No limitation is made herein; any electronic device that can implement this invention falls within the protection scope of this invention.

[0221] Fourthly, corresponding to the imaging method based on signal spectrum analysis of magnetic particle relaxation time provided in the first aspect, the present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of any of the imaging methods based on signal spectrum analysis of magnetic particle relaxation time provided in the first aspect of the present invention.

[0222] For the embodiments of the device / electronic device / storage medium, since they are basically similar to the method embodiments, the description is relatively simple, and relevant parts can be referred to in the description of the method embodiments.

[0223] It should be noted that the device, electronic device and storage medium in the embodiments of the present invention are respectively the device, electronic device and storage medium for applying the above-mentioned imaging method based on signal spectrum analysis of magnetic particle relaxation time. Therefore, all embodiments of the above-mentioned imaging method based on signal spectrum analysis of magnetic particle relaxation time are applicable to the device, electronic device and storage medium, and can achieve the same or similar beneficial effects.

[0224] The above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention are included within the scope of protection of the present invention.

Claims

1. An imaging method based on signal spectrum analysis of magnetic particle relaxation time, characterized in that, include: Generates a magnetic field free point (FFP); The FFP is moved within the spatial range of the target under test, which has been injected with a single type of magnetic nanoparticle. At each FFP position, a pulsed square wave excitation magnetic field is generated, and the original signal generated by the magnetic nanoparticles in the target under test at that FFP position under the excitation of the pulsed square wave excitation magnetic field is received. Perform an inverse Laplace transform on the original signal, and obtain the spectral curve corresponding to the FFP position based on the inverse Laplace transform result; Based on the region of the two peaks in the spectrum curve and the distribution of the two relaxation time peaks in the spectrum curve determined by the pre-experiment of the single magnetic nanoparticle, the magnetic particle relaxation time detection result at the FFP position is determined; wherein, the magnetic particle relaxation time detection result includes the Niehr relaxation time constant, the Brown relaxation time constant, and the percentage of Niehr relaxation and Brown relaxation. Imaging is performed based on at least one of the same terms from the magnetic particle relaxation time detection results obtained from all FFP positions to obtain a relaxation time image of the target under test.

2. The imaging method based on signal spectrum analysis of magnetic particle relaxation time according to claim 1, characterized in that, The process of generating a pulsed square wave excitation magnetic field at each FFP location and receiving the original signal generated by the magnetic nanoparticles within the target at that FFP location under the excitation of the pulsed square wave excitation magnetic field includes: At each FFP location, a pulsed square wave excitation magnetic field is generated using a pre-designed pulsed square wave relaxor, and the original signal generated by the magnetic nanoparticles in the target at that FFP location under the excitation of the pulsed square wave excitation magnetic field is received.

3. The imaging method based on signal spectrum analysis of magnetic particle relaxation time according to claim 2, characterized in that, The pulse square wave relaxor includes: A digital acquisition card is used to generate analog signals of pulse square waves and to digitize the input raw signals. An AC power amplifier is used to amplify the analog signal; The transmitting coil is used to transmit amplified analog signals to generate a pulsed square wave excitation magnetic field; A current sensor is used to monitor the emission waveform of the AC power amplifier in real time. A receiving coil is used to receive the original signal generated by magnetic particles under the excitation of the pulsed square wave excitation magnetic field; A low-noise preamplifier is used to amplify the original signal and provide it to the digital acquisition card.

4. The imaging method based on signal spectrum analysis of magnetic particle relaxation time according to claim 1, characterized in that, The determination of the magnetic particle relaxation time detection result at the FFP position based on the region of the two peaks in the spectrum curve and the distribution of the two relaxation time corresponding peaks in the spectrum curve determined by the pre-experiment of the single magnetic nanoparticle includes: Based on the regions with two peaks in the spectrum curve, determine the first relaxation time, the second relaxation time, and their respective percentages; Based on the distribution of the peaks corresponding to the two relaxation times in the spectral curves determined by the prior experiments on the single type of magnetic nanoparticle, the Niehr relaxation time and Brown relaxation time in the two relaxation times in the spectral curves are distinguished, and the magnetic particle relaxation time detection result at the FFP position is obtained.

5. The imaging method based on signal spectrum analysis of magnetic particle relaxation time according to claim 4, characterized in that, The step of determining the first relaxation time, the second relaxation time, and their respective percentages based on the regions with two peaks in the spectral curve includes: The magnitudes of the first relaxation time and the second relaxation time are determined based on the peak positions of the two peaks in the spectrum curve, and the percentages of the first relaxation time and the second relaxation time are determined based on the area of ​​the two peaks.

6. The imaging method based on signal spectrum analysis of magnetic particle relaxation time according to claim 1, characterized in that, For the aforementioned single type of magnetic nanoparticle, the distribution of peaks corresponding to two relaxation times in the spectral curve was determined in advance through experiments, including: To prepare single magnetic particle samples for a single type of magnetic nanoparticle, an environmental parameter sequence for the single magnetic particle sample is determined based on the difference in response of the pre-determined Niehr relaxation time or Brownian relaxation time to changes in the environmental parameters of the magnetic particles; wherein, the environmental parameters include viscosity, stiffness, temperature, and microenvironment; the environmental parameter sequence contains multiple environmental parameter values ​​and exhibits the same trend of change; A pulsed square wave excitation magnetic field is generated, and the sample signal generated by the single magnetic particle sample corresponding to each environmental parameter value under the excitation of the pulsed square wave excitation magnetic field is received. Perform an inverse Laplace transform on each sample signal and obtain the corresponding spectrum curve based on the results of each inverse Laplace transform; For any given spectral curve, based on the regions containing two peaks, determine the first relaxation time, the second relaxation time, and their respective percentages under the corresponding environmental parameter values. Furthermore, based on the differences in the changing trends of the first and second relaxation times among multiple spectral curves, distinguish the Niehr relaxation time and Brown relaxation time among the two relaxation times in any given spectral curve, and determine the distribution of the peaks corresponding to the two relaxation times in the spectral curve of a single magnetic nanoparticle.

7. The imaging method based on signal spectrum analysis of magnetic particle relaxation time according to claim 1, characterized in that, Imaging is performed on at least one of the magnetic particle relaxation time detection results obtained based on all FFP positions to obtain a relaxation time imaging map of the target under test, including: Based on the Brownian relaxation time constants obtained from the magnetic particle relaxation time detection results at all FFP locations, an image of the Brownian relaxation time of the target under test is obtained.

8. An imaging device based on signal spectrum analysis of magnetic particle relaxation time, characterized in that, include: The FFP generation module is used to generate magnetic field free points (FFPs). The original signal acquisition module is used to move the FFP within the spatial range of the target under test where a single type of magnetic nanoparticle has been injected. At each FFP position, a pulsed square wave excitation magnetic field is generated, and the original signal generated by the magnetic nanoparticles in the target under test at that FFP position under the excitation of the pulsed square wave excitation magnetic field is received. The spectrum curve acquisition module is used to perform an inverse Laplace transform on the original signal and obtain the spectrum curve corresponding to the FFP position based on the inverse Laplace transform result. The magnetic particle relaxation time detection module is used to determine the magnetic particle relaxation time detection result at the FFP position based on the region of the two peaks in the spectrum curve and the distribution of the two relaxation time corresponding peaks in the spectrum curve determined by the pre-experiment of the single magnetic nanoparticle; wherein, the magnetic particle relaxation time detection result includes the Niehr relaxation time constant, the Brown relaxation time constant, and the percentage of Niehr relaxation and Brown relaxation. The imaging module is used to perform imaging based on at least one of the same terms in the magnetic particle relaxation time detection results obtained from all FFP positions, so as to obtain a relaxation time imaging map of the target under test.

9. An electronic device, characterized in that, It includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; The memory is used to store computer programs; When the processor executes the program stored in the memory, it implements the steps of the method described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the method described in any one of claims 1-7.

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