Electrode detection type magneto-acoustic electromagnetic particle concentration image reconstruction method

Abstract

The invention discloses an electrode detection type magneto-acoustic electromagnetic particle concentration image reconstruction method, which specifically comprises the following steps of: firstly, setting initial simulation conditions of magneto-acoustic electromagnetic particles, uniformly setting k sound source scanning excitation points, aiming at sound source excitation of rk, acquiring an electric signal of a detection electrode, discretizing and converting the electric signal into a column vector; collecting background sound field distribution, and discretizing the background sound field distribution into a sound field data matrix; solving the electric signal and the sound field matrix equation to obtain virtual fluctuation field source distribution of the magnetic particles, wherein the virtual fluctuation field source distribution has a direct corresponding relation with the concentration of the magnetic particles; magnetic particle current density distribution in the reciprocity process is obtained; and reconstructing magnetic particle concentration distribution by using the virtual fluctuation field source distribution and the current density distribution. According to the electrode detection type magneto-acoustic electromagnetic particle concentration image reconstruction method provided by the invention, discretization is carried out by utilizing a moment method, a virtual fluctuation field source matrix is solved, magnetic particle concentration information is reconstructed through electrode receiving signals and sound field data information, and the method has a good application prospect.

Description

Technical Field

[0001] The invention belongs to the field of concentration distribution image reconstruction, and in particular relates to an electrode detection type magnetic acoustic electromagnetic particle concentration image reconstruction method. Background Art

[0002] Due to their superparamagnetic properties and good biocompatibility, magnetic nanoparticles have broad application prospects in the fields of nanomedicine such as tumor diagnosis and treatment, quantitative tracking of living stem cells, and nanorobots. Magnetic nanoparticle imaging technology is a necessary imaging method for precision medicine. The current magnetic particle concentration image reconstruction technologies include classical magnetic particle imaging technology, magnetoacoustic coupling magnetic particle imaging technology, and magnetoacoustic electromagnetic particle imaging technology. Due to the relaxation effect of magnetic nanoparticles, classical magnetic particle imaging technology has a bottleneck in time and space resolution. In 2005, Gleich and Weizenecker first announced a magnetic particle imaging device with a gradient magnetic field of 3.4T / m, an AC magnetic field frequency of 25.25kHz, and an amplitude of 10mT; In 2018, Weber et al. proposed a field generator based on Halbach cylinders, which can generate a driving field with an amplitude of 30mT and a frequency of 25kHz and a focusing field with an amplitude of 100mT, with a total power consumption of about 3.4kW. It can be seen that classical magnetic particle imaging technology is still limited by the electromagnetic excitation of gradient magnetic fields and alternating magnetic fields and cannot be widely used. The magnetoacoustic coupled magnetic particle imaging method uses the coupling of electromagnetic and ultrasonic fields for imaging, and improves the imaging resolution through ultrasound, but there is still a limitation of excessive electromagnetic excitation.

[0003] Yan Xiaoheng applied for "An Electrode Detection Type Magnetoacoustic Electromagnetic Particle Imaging Device and Method" (Application No.: 202410008351.0) on January 4, 2024, which first proposed an electrode detection type magnetoacoustic electromagnetic particle concentration imaging method. It is an emerging non-invasive biomedical magnetic particle imaging method based on Langevin theory and magnetoacoustic electromechanical effect. It uses ultrasonic excitation instead of electromagnetic excitation, which can effectively solve the problem of excessive electromagnetic excitation in the existing magnetic particle imaging method, and broaden the potential for further experiments and clinical applications in nanomedicine. At present, there is no report on the magnetic nanoparticle concentration image reconstruction method based on electrode detection type magnetoacoustic electromechanical effect. Summary of the invention

[0004] Based on the above deficiencies in the prior art, the technical problem solved by the present invention is to provide an electrode detection-type magnetic acoustic electromagnetic particle concentration image reconstruction method, which uses the moment method to discretize the data, solves the virtual wave field source matrix, and reconstructs the magnetic nanoparticle concentration information through the electrode receiving signal and the acoustic field data information, and has good application prospects.

[0005] The present invention proposes an electrode detection type magnetic acoustic electromagnetic particle concentration image reconstruction method, comprising the following steps: Step 1: Set the initial conditions for the simulation of magnetic, acoustic, and electromagnetic nanoparticles. Set k sound source scanning excitation points evenly outside the imaging area. k The point sound source is excited, the electrical signal of the detection electrode is collected, and the discretized signal is converted into a column vector; Step 2: Collect r k The background sound field distribution in the area to be imaged under the excitation of a point sound source is discretized into a sound field data matrix; Step 3: Using the electrical signal and acoustic field matrix equations constructed in Steps 1 and 2, the virtual fluctuation field source distribution of the magnetic nanoparticles is solved, and there is a direct corresponding relationship between the virtual fluctuation field source distribution and the concentration distribution of the magnetic nanoparticles; Step 4: Obtain the current density distribution of the magnetic nanoparticles in the reciprocal process; Step 5: Reconstruct the concentration distribution of magnetic nanoparticles using the virtual fluctuating field source distribution and current density distribution of steps 3 and 4.

[0006] Optionally, in step 1, n excitations are selected for scanning, and r k Electrode electrical signal data u(r) under position excitation k , t), where k = 1, 2, ..., n. The continuous signal is discretized by the set sampling time to obtain the voltage column vector U.

[0007] Optionally, in step 2, in Cartesian coordinates, obtain r k Under excitation, the vibration velocity distribution of the background sound field is φ(r′, t), where r′ is any point in the xoy plane of the imaging target area, and the sound field distribution matrix V is obtained.

[0008] Optionally, in step 3, under a certain point excitation, the relationship between the sound pressure signal u(t) and the virtual wave field source H(r′) and the sound field data φ(r′, t) is: Where r′ is the magnetic nanoparticle area. Under infinite boundary conditions, The Green's function of the sound source at r is expressed as , r is the field point, f (t) is the initial ultrasonic excitation signal; Since the Green function satisfies the symmetry , according to the moment method, we can get any point r k The relationship between the voltage signal, virtual wave field source and sound field data under excitation is: Among them, Ω i is the target area, is the speed of sound. At any time t, the diameter of the integrating sphere is c0t. After a time t, the points on this sphere will reach the corresponding field point r at the same time.k . Converted into a matrix equation:

[0009] Among them, V is the sound field data U is composed of the collected voltage data H is the virtual wave field source matrix to be solved. The pixel point r′ in the solution area i The number of divisions is a×b = o, where a represents the number of divisions in the x direction and b represents the number of divisions in the y direction. Then r′ i Where i = 1, 2, 3, ..., o. Assume that the sampling time is p time points and T0 is the sampling period, then: Then V is an o×np matrix, U is a 1×np column vector, and H is a 1×o column vector. The LSQR method is used to solve the matrix equation constructed by the electric signal U and the acoustic field matrix V to obtain the virtual wave field source H of the magnetic nanoparticles.

[0010] Optionally, in step 4, the reciprocity process refers to injecting a unit current into the tissue to be imaged at the detection electrode to solve the current density distribution J2 of the magnetic nanoparticles.

[0011] Optionally, in step 5, the imaging area is the xoy plane, and the relationship between the magnetic nanoparticle concentration distribution N(x, y) and the virtual fluctuation field source distribution H(x, y) and the current density J2(x, y) is:

[0012] Where m is the magnetic moment of the magnetic nanoparticles, and ρ is the density of the magnetic nanoparticles. Solving the above equations yields the concentration distribution matrix of the magnetic nanoparticles.

[0013] From the above, the electrode detection type magnetic acoustic electromagnetic particle concentration image reconstruction method of the present invention has the following advantages: The present invention reconstructs the concentration distribution of magnetic nanoparticles based on the magnetoacoustic-electric effect of magnetic particles. A matrix equation is constructed by collecting electrode electrical signals and vibration velocity data of the magnetic nanoparticle region. The virtual wave field source is solved by the LSQR method. The concentration distribution of the magnetic nanoparticles is then calculated using the reciprocal current density distribution data. The proposed reconstruction method has flexible design and a simple solution process. The data dimension can be automatically adjusted according to actual use and segmentation conditions. The method is suitable for the reconstruction of magnetic particle concentration images with different numbers of excitations and has broad application prospects.

[0014] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the following is a detailed description in combination with the preferred embodiments and the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solution of the embodiment of the present invention, the following is a brief introduction to the drawings of the embodiment: Figure 1 is a flow chart of the present invention; Figure 2 It is a simulation model of the electrode detection type magnetic acoustic electromagnetic particle concentration image reconstruction method of the present invention; Figure 3 is a target concentration diagram in one embodiment; Figure 4 This is a reconstruction diagram of magnetic nanoparticle concentration based on this method. DETAILED DESCRIPTION

[0016] The following will further explain in detail the electrode detection type magnetic acoustic electromagnetic particle concentration image reconstruction method proposed by the present invention in conjunction with the drawings in the embodiments of the present invention.

[0017] In a preferred embodiment, if Figure 1 As shown, the simulation sampling time is set, the collected voltage signal is discretized, the area to be imaged is grid-divided according to the finite element method, the acoustic field data and the reciprocal current density data are discretized, and the matrix equation of the voltage signal, the acoustic field data and the virtual wave field source is constructed. The discrete virtual wave field source solution is obtained by the LSQR method, and the concentration distribution data is obtained by using the reciprocal current density data, and then the concentration image of the magnetic nanoparticles is reconstructed. The present invention discloses an electrode detection type magnetic acoustic electromagnetic particle concentration image reconstruction method. Figure 2 As an example, in the Cartesian coordinate system, the circle with a radius of 30 mm in the simulation model represents the biological tissue, and the circle with a radius of 8 mm represents the NMPs area, which is the area with a number concentration of 4×10 24 / mL superparamagnetic nanoparticles EMG707, using a point sound source to apply ultrasonic excitation to the tissue, the point sound source radius is 6mm. The ultrasonic excitation is a 3-cycle Hanning window modulation signal with a center frequency of 1MHz. This is achieved through the following technical solutions.

[0018] Step 1: Set the number of excitations to 36, collect the electrical signals under the scanning excitation, and discretize them into column vectors U according to the sampling time. k Electrode electrical signal data u(r) under position excitation k, t), where k = 1, 2,…,36. The sampling time is set to 0.1 μs, 701 sampling points are set, the continuous signal is discretized, and the voltage column vector U is obtained.

[0019] Step 2: Get the corresponding background sound field distribution, set 201×201 grid units, and discretize them into the sound field data matrix V. In the Cartesian coordinate system, get r k Under excitation, the vibration velocity distribution of the background sound field is φ(r′, t), where r′ is any point in the xoy plane of the imaging target area, and the sound field distribution matrix V is obtained.

[0020] Step 3: Using the matrix equations of the electrical signal U and the acoustic field V constructed in steps 1 and 2, solve the distribution of the virtual wave field source H of the magnetic nanoparticles. Under a certain point excitation, the relationship between the sound pressure signal u(t) and the virtual wave field source H(r′) and the acoustic field data φ(r′, t) is: Where r′ is the magnetic nanoparticle area. Under infinite boundary conditions, The Green's function of the sound source at r is expressed as , r is the field point, f (t) is the initial ultrasonic excitation signal; the Green function satisfies the symmetry , according to the moment method, we can get any point r k The relationship between the voltage signal, virtual wave field source and sound field data under excitation is: Among them, Ω i is the target area, is the speed of sound. At any time t, the diameter of the integrating sphere is c0t. After a time t, the points on this sphere will reach the corresponding field point r at the same time. k . Converted into a matrix equation: Among them, V is the sound field data U is composed of the collected voltage data H is the virtual wave field source matrix to be solved. The pixel point r′ in the solution area i The number is 201×201 = 40401, 201 units are divided in the x direction and 201 units are divided in the y direction, then r′ i Where i = 1, 2, 3, ..., 40401. The sampling time is 701 time points, and the sampling period T0 is 0.1 μs, then: { v k = [ v k ( r ′ 1 , 0 ) v k ( r ′ 2 , 0 ) ⋯ v k ( r ′ 40401 , 0 ) v k ( r ′ 1 , T 0 ) v k ( r ′ 2 , T 0 ) ⋯ v k ( r ′ 40401 , T 0 ) ⋮ ⋮ ⋱ ⋮ v k ( r ′ 1 , T 0 ) v k ( r ′ 2 , T 0 ) ⋯ v k ( r ′ 40401 , 700 T 0 ) ] V = [ v 1 , v 2 , ⋯ , v k , ⋯ v 36 ] T { u k = [ u ( r k , 0 ), u ( r k , T 0 ), ⋯ , u ( r k , 700 T 0 ) ] T U = [ u 1 , u 2 , ⋯ , u k , ⋯ , u 36 ] T Then V is a 40401×25236 matrix, U is a 1×25236 column vector, and H is a 1×40401 column vector. Use the LSQR method to solve the electrical signal U 1×25236 With the sound field matrix V 40401×23236 The constructed matrix equation obtains the virtual wave field source H of the magnetic nanoparticles 1×40401。

[0021] Step 4: Inject unit current into the receiving electrodes at the 36 scanning excitation positions respectively to obtain the current density distribution of the magnetic nanoparticles in the reciprocal process, divide the tissue area to be imaged into 201×201 grid units, and discretize it into a 201×201 current density matrix J2.

[0022] Step 5: Reconstruct the magnetic nanoparticle concentration distribution N using the virtual fluctuating field source distribution H and current density distribution J from steps 3 and 4. Assuming the imaging area is the xoy plane, the relationship between the magnetic nanoparticle concentration distribution N(x, y) and the virtual fluctuating field source distribution H(x, y) and current density J2(x, y) is: Where m is the magnetic moment of the magnetic nanoparticles and ρ is the density of the magnetic nanoparticles. Solving the above equations, we can obtain the concentration distribution matrix of the magnetic nanoparticles and reconstruct the concentration distribution image.

[0023] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An electrode detection type magnetic acoustic electromagnetic particle concentration image reconstruction method, characterized in that: The following steps are involved: Step 1: Set the initial conditions for the simulation of magnetic, acoustic, and electromagnetic nanoparticles. Set k sound source scanning excitation points evenly outside the imaging area. k The point sound source excitation is used to collect the electrical signal of the detection electrode and discretize it into a column vector; Step 2: Collect r k The background sound field distribution in the area to be imaged under the excitation of a point sound source is discretized into a sound field data matrix; Step 3: Using the electrical signal and acoustic field matrix equations constructed in Steps 1 and 2, the virtual fluctuation field source distribution of the magnetic nanoparticles is solved, and there is a direct corresponding relationship between the virtual fluctuation field source distribution and the concentration distribution of the magnetic nanoparticles; Step 4: Obtaining the current density distribution of the magnetic nanoparticles in the area to be imaged during the reciprocal process; Step 5: Reconstruct the concentration distribution of magnetic nanoparticles using the virtual fluctuating field source distribution and current density distribution of steps 3 and 4.

2. The electrode detection type magnetic acoustic electromagnetic particle concentration image reconstruction method according to claim 1, characterized in that: In step 1, the electrodes gradually collect data at any point r k The electrical signal data u(r k , t), set the sampling time to discretize the continuous signal and obtain the magnetic particle voltage column vector U.

3. The electrode detection type magnetic acoustic electromagnetic particle concentration image reconstruction method according to claim 1, characterized in that: In step 2, get r k The vibration velocity distribution of the background sound field under excitation is φ(r′, t), where r′ is any point in the imaging target area. The imaging target area is discretized into the sound field distribution matrix V using the moment method.

4. The electrode detection type magnetic acoustic electromagnetic particle concentration image reconstruction method according to claim 1, characterized in that: In step 3, the relationship between the sound pressure signal under a certain point excitation and the virtual wave field source and the sound field data is: Where r′ is the area of ​​magnetic nanoparticles; The Green function of the sound source at r is expressed as: Where r is the field point, f (t) is the initial ultrasonic excitation signal, ； Use the moment method to get any point r k The relationship between the voltage signal, virtual wave field source and sound field data under excitation is: Among them, Ω i is the target area, is the speed of sound, which is converted into a matrix equation: The pixel point r′ in the solution area i The number of divisions is a×b = o, where a represents the number of divisions in the x direction and b represents the number of divisions in the y direction. Then r′ i Where i = 1, 2, 3, ..., o, assuming that the sampling time is p time points, T0 is the sampling period, then: Then V is an o×np matrix, U is a 1×np column vector, and H is a 1×o column vector. The matrix equation constructed by the electric signal U and the acoustic field matrix V is solved to obtain the virtual wave field source H of the magnetic nanoparticles.

5. The electrode detection type magnetic acoustic electromagnetic particle concentration image reconstruction method according to claim 1, characterized in that: In step 4, the reciprocal process is to inject a unit current into the tissue to be imaged at the detection electrode to solve the current density distribution J2 of the magnetic nanoparticles.

6. The electrode detection type magnetic acoustic electromagnetic particle concentration image reconstruction method according to claim 1, characterized in that: In step 5, the relationship between the concentration N of magnetic nanoparticles, the virtual fluctuating field source H and the current density J2 is: Where m is the magnetic moment of the magnetic nanoparticles, and ρ is the density of the magnetic nanoparticles.

Images