Detection method, detection system, and recording medium

Abstract

A detection method for detecting a detection target magnetic particle using an alternating excitation magnetic field includes: a step (S1) of acquiring, for a candidate magnetic particle, a Néel relaxation curve representing a relationship between a Néel relaxation time and a particle diameter; a step (S2) of acquiring, for the candidate magnetic particle, a Brownian relaxation curve representing a relationship between a Brownian relaxation time and the particle diameter; a step (S3) of determining, as an intersection point particle diameter, a particle diameter corresponding to an intersection point of the Néel relaxation curve and the Brownian relaxation curve; and a step (S4) of selecting, as the detection target magnetic particle, the candidate magnetic particle having a particle diameter larger than the intersection point particle diameter.

Description

Technical Field

[0001] This disclosure relates to detection methods, detection systems, procedures, and recording media for detecting magnetic particles. Background Technology

[0002] In recent years, there has been ongoing development of magnetic immunoassay using magnetic particles as a novel immunoserological test. Magnetic immunoassay offers advantages such as eliminating the need for the cleaning process required by traditional immunoassays, including fluorescence-based methods, and high sensitivity. Furthermore, based on the transparency of magnetic signals to the human body, it is hoped that magnetic immunoassay can be applied to in vivo diagnostics without removing the patient.

[0003] In magnetic immunoassay, by pre-attaching substances such as proteins that bind to the target substance in the antigen-antibody reaction to magnetic particles, the amount and location of the target substance can be determined based on the magnetic signal from the magnetic particles.

[0004] Japanese Patent Application Publication No. 2013-228280 (Patent Document 1) discloses a magnetic immunoassay method and apparatus using an alternating magnetic field. In the method described in Patent Document 1, magnetic particles bound to a target substance (hereinafter referred to as "bound particles") are precipitated using a permanent magnet. Only the unbound magnetic particles (hereinafter referred to as "unbound particles") present in the clarified portion are energized to obtain a magnetic signal from the unbound particles. The amount of bound particles is indirectly detected by calculating the difference between the obtained magnetic signal and the magnetic signal from magnetic particles in a sample completely free of target substance.

[0005] Existing technical documents

[0006] Patent documents

[0007] Patent Document 1: Japanese Patent Application Publication No. 2013-228280

[0008] Non-patent literature

[0009] Non-Patent Literature 1: R. Matthew Ferguson, 2 others, “Optimization of nanoparticle core size for magnetic particle imaging”, J. Magn. Magn. Mater., 321 (2009), pp. 1548-1551 Summary of the Invention

[0010] The technical problem that the invention aims to solve

[0011] According to the technology described in Patent Document 1, the detection accuracy is lower than that of direct quantitative examination because it is an indirect quantitative examination. Furthermore, a permanent magnet is required to separate bound particles from unbound particles, making it unsuitable for in vivo examinations where the subject is not removed from the body.

[0012] This disclosure is made to solve the above-mentioned technical problems, and its purpose is to provide a detection method, detection system, program and recording medium that can be applied to in vivo examination and can detect bound particles with high precision.

[0013] Technical solutions for solving technical problems

[0014] In one aspect of the detection method disclosed herein, an alternating current excitation magnetic field is used to detect target magnetic particles. The detection method includes the following steps: obtaining a first curve representing the relationship between Niehr relaxation time and particle diameter for candidate magnetic particles; obtaining a second curve representing the relationship between Brownian relaxation time and particle diameter for candidate magnetic particles; determining the particle diameter corresponding to the intersection point of the first and second curves as the intersection particle diameter; and selecting candidate magnetic particles with a particle diameter larger than the intersection particle diameter as the target magnetic particles for detection.

[0015] One aspect of the detection system disclosed herein uses an excitation magnetic field to detect target magnetic particles. The detection system includes a processor that performs information processing for selecting target magnetic particles from candidate magnetic particles. The processor acquires a first curve representing the relationship between Niehr relaxation time and particle diameter for each candidate magnetic particle, and a second curve representing the relationship between Brownian relaxation time and particle diameter for each candidate magnetic particle. Furthermore, the processor determines the particle diameter corresponding to the intersection point of the first and second curves as the intersection particle diameter, and selects candidate magnetic particles with a particle diameter larger than the intersection particle diameter as target magnetic particles.

[0016] One aspect of this disclosure is a computer program that supports a detection system for detecting target magnetic particles using an excitation magnetic field. The computer program causes a computer to perform the following steps: obtaining a first curve representing the relationship between Niehr relaxation time and particle diameter for candidate magnetic particles; obtaining a second curve representing the relationship between Brownian relaxation time and particle diameter for candidate magnetic particles; determining the particle diameter corresponding to the intersection of the first and second curves as the intersection particle diameter; and selecting candidate magnetic particles with particle diameters larger than the intersection particle diameter as the target magnetic particles for detection.

[0017] One aspect of this disclosure is that a computer-readable recording medium records the aforementioned computer program.

[0018] Invention Effects

[0019] According to this disclosure, the phase of the magnetic signal from a target magnetic particle with a diameter larger than that of the intersection particle primarily corresponds to the Brownian relaxation time. The Brownian relaxation time varies depending on whether the target magnetic particle is bound to the target material. Therefore, when an excitation magnetic field is applied to an object containing both bound and unbound particles, bound particles can be detected with high precision based on the difference in Brownian relaxation time. Furthermore, since there is no need to separate bound and unbound particles, it can also be applied to in vivo examinations. Attached Figure Description

[0020] Figure 1 This is a diagram illustrating an example of the overall structure of the detection system according to Embodiment 1.

[0021] Figure 2 This is a three-dimensional view showing a part of the detection system.

[0022] Figure 3 This is a diagram illustrating an example of the hardware structure of an information processing device.

[0023] Figure 4 This is a flowchart illustrating the process of the magnetic particle detection method according to Embodiment 1.

[0024] Figure 5 This is a diagram showing an example of a Niehl relaxation curve and a Brownian relaxation curve.

[0025] Figure 6 This is a graph showing an example of the effective relaxation curves for bound and unbound particles.

[0026] Figure 7 This is a graph showing other examples of effective relaxation curves for bound and unbound particles.

[0027] Figure 8 It is shown Figure 4 The flowchart of the subroutine of step S8 is shown.

[0028] Figure 9 This is a diagram showing the processing content of steps S83 and S84.

[0029] Figure 10 It is shown Figure 4 The flowchart of the subroutine of step S10 is shown.

[0030] Figure 11 This is a diagram illustrating an example of the overall structure of the detection system according to Embodiment 2.

[0031] Figure 12 This illustrates embodiment 2. Figure 4 The flowchart of the subroutine of step S8.

[0032] Figure 13 This is a flowchart illustrating the processing flow of the detection method of Embodiment 3.

[0033] Figure 14 This is a diagram showing an example of a device for performing step S11.

[0034] Figure Labels

[0035] 1: Excitation magnetic field applicator; 2: Zero magnetic field generator; 2a, 2b: Electromagnet; 3: Magnetic sensor; 4: Zero magnetic field region; 5: Signal amplifier; 6: Subject under inspection; 7: First power supply; 8a: Second power supply; 8b: Third power supply; 9, 9A: Information processing device; 10: Detection program; 11: Optical recording medium; 12: Processor; 13: RAM; 14: Reading unit; 15: Internal storage unit; 16: Display unit; 17: Operation unit; 18: Communication interface; 19: Server device; 20: Lock-in amplifier; 21: NieR relaxation curve; 22: Brownian relaxation curve; 23, 23a, 23b: Effective relaxation curve; 40: Permanent magnet; 41: Candidate magnetic particle; 42: Detection target magnetic particle; 43: Non-target magnetic particle; 45: Column; 100, 100A: Detection system. Detailed Implementation

[0036] The embodiments of this disclosure will now be described in detail with reference to the accompanying drawings. Furthermore, the same or equivalent parts will be labeled with the same reference numerals in the drawings, and their descriptions will generally not be repeated. In the following drawings, the size relationships of the constituent parts may sometimes differ from the actual figures.

[0037] Implementation method 1.

[0038] (Overall structure of the detection system)

[0039] Figure 1 This is a diagram illustrating an example of the overall structure of the detection system according to Embodiment 1. Figure 1 The detection system 100 shown includes an excitation magnetic field applicator 1, a zero magnetic field generator 2, a magnetic sensor 3, a signal amplifier 5, a first power supply 7, a second power supply 8a, a third power supply 8b, and an information processing device 9.

[0040] The excitation magnetic field applicator 1 applies an alternating excitation magnetic field to the area where the subject 6 is placed. Specifically, the excitation magnetic field applicator 1 is composed of a coil connected to a first power supply 7. By having current flow from the first power supply 7 to the excitation magnetic field applicator 1, an excitation magnetic field is applied to the area where the subject 6 is placed.

[0041] By applying an excitation magnetic field to the object under inspection 6, the magnetic particles contained in the object under inspection 6 generate a magnetic signal with a fundamental frequency f0 and a magnetic signal with higher harmonics (n×f0) of the same frequency as the excitation magnetic field (higher harmonic signal).

[0042] During the antigen-antibody reaction, substances such as proteins that bind to the target substances contained in the subject 6 attach to the magnetic particles.

[0043] The zero magnetic field generator 2 creates a zero magnetic field region in the area where the object under inspection 6 is placed. Specifically, the zero magnetic field generator 2 includes a pair of electromagnets 2a and 2b arranged opposite each other in opposite magnetization directions. Electromagnets 2a and 2b are connected to a second power supply 8a and a third power supply 8b, respectively. The zero magnetic field region is generated by current flowing from the second power supply 8a and the third power supply 8b to the electromagnets 2a and 2b, respectively.

[0044] In this embodiment, the zero magnetic field generator 2 is described as including electromagnets 2a and 2b. However, as the zero magnetic field generator 2, electromagnets 2a and 2b may not be used, and two opposing permanent magnets or a combination of permanent magnets and electromagnets may be used instead. When the zero magnetic field region is formed using two permanent magnets, the second power supply 8a and the third power supply 8b are omitted.

[0045] Magnetic sensor 3 detects the magnetic signal from magnetic particles contained in the inspected object 6, which is subjected to an applied excitation magnetic field. The magnetic signal represents the change in the magnetic moment of the magnetic particles. Signal amplifier 5 amplifies the magnetic signal output from magnetic sensor 3.

[0046] The information processing device 9 is connected to various parts of the detection system 100 via a bus. The information processing device 9 performs various information processing operations to control the operation of the detection system 100. The information processing device 9 performs a process of selecting magnetic particles that can be applied to in vivo examinations and can be detected with high precision when bound to a target substance as the target magnetic particles for detection. Furthermore, the information processing device 9 acquires a magnetic signal from the signal amplifier 5 and a reference signal with the same frequency and phase as the excitation magnetic field from the first power supply. The information processing device 9 performs a process of using the magnetic signal and the reference signal to detect the target magnetic particles bound to the target substance.

[0047] (Zero magnetic field region)

[0048] Figure 2 This is a three-dimensional view showing a portion of the detection system. Figure 2 In the example shown, a linear zero-magnetic-field region (Field Free Line (FFL)) 4 is generated using a pair of electromagnets 2a and 2b included in the zero-magnetic-field generator 2. However, in this embodiment, the shape of the zero-magnetic-field region 4 is not limited to a linear shape. For example, the zero-magnetic-field region 4 can be a point-shaped zero-magnetic-field region (Field Free Point (FFP)) or a surface, etc.

[0049] The position and orientation of the linear zero magnetic field region 4 are scanned by changing the current balance of electromagnets 2a and 2b. Specifically, the distance between the origin of the coordinate system determined by the positions of electromagnets 2a and 2b and the linear zero magnetic field region 4 (hereinafter referred to as "translation position r"), and the angle between the axis set in this coordinate system and the linear zero magnetic field region 4 (hereinafter referred to as "angle θ"), vary according to the current balance of electromagnets 2a and 2b. Furthermore, the method of scanning the zero magnetic field region 4 is not limited to this. For example, the zero magnetic field region 4 can also be scanned by physically moving electromagnets 2a and 2b. Alternatively, the zero magnetic field region 4 can be scanned relative to the inspected object 6 by fixing the position of the zero magnetic field region 4 and moving the inspected object 6.

[0050] (Hardware structure of information processing device)

[0051] Figure 3 This is a diagram illustrating an example of the hardware structure of an information processing device. (See diagram for example.) Figure 3 As shown, the information processing device 9 includes a processor 12, RAM (Random Access Memory) 13, a reading unit 14, an internal storage unit 15, a display unit 16, an operation unit 17, and a communication interface 18.

[0052] The processor 12 is, for example, a CPU (Central Processing Unit) that performs arithmetic operations. The RAM 13 stores temporary information generated during the arithmetic operations of the processor 12. The processor 12 reads the program (including the detection program 10) stored in the internal storage unit 15 and executes it in the RAM 13.

[0053] The reading unit 14 reads information recorded on optical recording media 11, such as CD-ROM (Compact Disk Read Only Memory).

[0054] The internal storage unit 15 contains, for example, a hard disk drive, a storage detection program 10, and various programs and data.

[0055] The display unit 16 is, for example, a liquid crystal display (LCD) that displays images generated based on the calculations performed by the processor 12. The operation unit 17 includes, for example, a keyboard and a mouse, for input by the operator.

[0056] Communication interface 18 communicates with external devices (e.g., server device 19) via a network.

[0057] The detection program 10 includes a group of commands related to the detection of magnetic particles. The detection program 10 is recorded on, for example, an optical recording medium 11, read by the reading unit 14, and saved to the internal storage unit 15. Alternatively, the detection program 10 can also be downloaded from the server device 19 via the communication interface 18 and saved to the internal storage unit 15.

[0058] (Flowchart of the method for detecting magnetic particles)

[0059] Figure 4 This is a flowchart illustrating the process of the magnetic particle detection method according to Embodiment 1. The detection program 10, which is expanded in RAM 13, is executed by the processor 12. Figure 4 The process is shown below.

[0060] First, in step S1, the processor 12 of the information processing device 9 calculates and obtains a NieR relaxation curve representing the relationship between NieR relaxation time and particle diameter for the candidate magnetic particles. Then, in step S2, the processor 12 calculates and obtains a Brownian relaxation curve representing the relationship between Brownian relaxation time and particle diameter for the candidate magnetic particles. Next, in step S3, the processor 12 determines the particle diameter corresponding to the intersection of the NieR relaxation curve and the Brownian relaxation curve as the intersection particle diameter. In step S4, the processor 12 selects candidate magnetic particles with particle diameters larger than the intersection particle diameter as the detection target magnetic particles.

[0061] Candidate magnetic particles are candidates for the magnetic particles provided to the subject 6. Candidate magnetic particles are particles that are capable of binding with the target material contained in the subject 6, and are pre-designed according to the target material.

[0062] When magnetic particles are small in size, their magnetic properties are easily affected by heat. As a result of thermal influence, Nilleney relaxation and Brownian relaxation are known. Nilleney relaxation refers to the phenomenon where the magnetic moment within the magnetic particle rotates randomly due to heat, resulting in a decrease in magnetization. Brownian relaxation refers to the phenomenon where magnetization decreases due to the rotation of the magnetic particle itself.

[0063] Processor 12 uses the following equations (1) and (2) to calculate the radius r representing the core particle. n With NieR relaxation time τ n The relationship is represented by the Niehr relaxation curve. Furthermore, τ0 is the relaxation time constant (s), and K is the anisotropic energy of the magnetic particle (J / m²). 3 ), k B is the Boltzmann constant (J / K), and T is the temperature of the magnetic particle (K). The processor 12 calculates the Niehr relaxation curve by inputting the values ​​provided by the operator based on the candidate magnetic particle and the object under inspection 6 as parameters.

[0064] [Formula 1]

[0065]

[0066] [Equation 2]

[0067]

[0068] Processor 12 uses the following equations (3) and (4) to calculate the hydrodynamic radius r. f With Brownian relaxation time τ b The Brownian relaxation curve of the relationship. Hydrodynamic radius r f It is the radius of the particle, including the outer coating of the magnetic particle's nucleus, modifying groups (proteins that react with the target substance to produce antigen-antibody reactions), and the target substance itself. Therefore, when the hydrodynamic radius changes due to the structure outside the nucleus, the offset and slope of the Brownian relaxation curve change. Furthermore, η is the viscosity (Js / m³) of the medium in which the magnetic particles exist. 3 The processor 12 calculates the Brownian relaxation curve by inputting the values ​​provided by the operator based on the candidate magnetic particles and the inspected object 6 as parameters.

[0069] [Formula 3]

[0070]

[0071] [Formula 4]

[0072]

[0073] Figure 5 This is a graph showing an example of a Niehr relaxation curve and a Brownian relaxation curve. Among them, Figure 5 The horizontal axis represents the nucleus diameter, which is determined by the nucleus radius r. n and the hydrodynamic radius r f The converted particle diameter. Processor 12 will calculate the nuclear particle radius r of the Niehr relaxation curve according to equations (1) and (2). n This can be converted to the nucleus particle size. Similarly, processor 12 will calculate the hydrodynamic radius r of the Brownian relaxation curve according to equations (3) and (4). f You can convert it to nucleus size.

[0074] like Figure 5 As shown, the slope of the Niehr relaxation curve 21 is greater than the slope of the Brownian relaxation curve 22. When the nucleus size is small, the Niehr relaxation time is shorter than the Brownian relaxation time. Therefore, the Niehr relaxation curve 21 and the Brownian relaxation curve 22 intersect. The processor 12 determines the nucleus size corresponding to the intersection point of the Niehr relaxation curve 21 and the Brownian relaxation curve 22 as the intersection particle diameter.

[0075] The effective relaxation time of magnetized magnetic particles depends on the shorter of the Niehr relaxation time and the Brownian relaxation time. Figure 5 In the diagram, effective relaxation curve 23 represents the relationship between the nucleus size of the candidate magnetic particle and the effective relaxation time. As shown in effective relaxation curve 23, for candidate magnetic particles with a nucleus size smaller than the diameter of the intersection particle, magnetization relaxes according to the Niehr relaxation time; for candidate magnetic particles with a nucleus size larger than the diameter of the intersection particle, magnetization relaxes according to the Brownian relaxation time.

[0076] Figure 6 This is a graph showing an example of the effective relaxation curves for bound and unbound particles. Figure 7 These are other examples of effective relaxation curves for bound and unbound particles. Figure 6 , 7 In the figure, reference numeral 23a represents the effective relaxation curve of candidate magnetic particles (bound particles) that have bound to the target material. Reference numeral 23b represents the effective relaxation curve of candidate magnetic particles (unbound particles) that have not bound to the target material. Figure 6 The effective relaxation curves 23a and 23b are shown when the candidate magnetic particle can still rotate after binding with the target material. Figure 7 The effective relaxation curves 23a and 23b of the candidate magnetic particles are shown when they are in non-rotational motion after binding with the target material.

[0077] like Figure 6 , 7 As shown, for nucleus sizes smaller than the intersection particle diameter, the difference between the effective relaxation curve 23a of bound particles and the effective relaxation curve 23b of unbound particles is almost imperceptible. Conversely, for nucleus sizes larger than the intersection particle diameter, the difference between the effective relaxation curve 23a of bound particles and the effective relaxation curve 23b of unbound particles becomes larger. That is, the relaxation time of candidate magnetic particles with nucleus sizes larger than the intersection particle diameter varies depending on whether they are bound to the target material. Therefore, when an excitation magnetic field is applied to candidate magnetic particles with nucleus sizes larger than the intersection particle diameter, the phase of the magnetic signal from the candidate magnetic particles varies depending on whether they are bound to the target material. That is, by using phase information, bound particles and unbound particles can be distinguished. Therefore, as... Figure 6 , 7 As shown, the processor 12 selects candidate magnetic particles with a nuclear particle diameter larger than that of the intersection particle as the detection target magnetic particles.

[0078] Return to Figure 4The following describes the processing after step S5. In step S5, the processor 12 generates instructions to control the power supply to electromagnets 2a and 2b, and outputs the generated instructions to the second power supply 8a and the third power supply 8b. As a result, the second power supply 8a and the third power supply 8b begin supplying power to the electromagnets 2a and 2b according to the instructions. Consequently, a zero magnetic field region is generated in the inspected object 6. Furthermore, candidate magnetic particles are injected into the inspected object 6.

[0079] Next, in step S6, the processor 12 generates an instruction to control the power supply to the excitation magnetic field applicator 1 and outputs the generated instruction to the first power supply 7. Thus, the first power supply 7 begins to supply power to the excitation magnetic field applicator 1 according to the instruction. As a result, an AC excitation magnetic field is applied to the object under inspection 6.

[0080] Next, in step S7, the processor 12 scans the zero magnetic field region in the inspected object 6 by adjusting the current balance from the second power supply 8a and the third power supply 8b to the electromagnets 2a and 2b. Furthermore, in step S5, when the zero magnetic field region is located at the position of the first scan, the first step S7 is omitted.

[0081] Next, in step S8, the processor 12 detects the change in the magnetic moment of the target magnetic particle caused by the excitation magnetic field and stores the detection result.

[0082] Next, in step S9, the processor 12 determines whether the scanning of the zero magnetic field region in the inspected object 6 has ended. If the scanning has not ended ("No" in step S9), the process returns to step S7. Thus, steps S7 and S8 are performed for each scanning position of the zero magnetic field region.

[0083] If the scan is completed (Yes in step S9), in step S10, the processor 12 performs a process (spatial distribution imaging) to generate an image representing the spatial distribution of the target substance in the examined body 6 using the stored detection results.

[0084] Furthermore, the order of steps S5 and S6 can also be reversed. Additionally, the order of steps S7 and S8 can also be reversed.

[0085] (Subroutine of step S8)

[0086] Figure 8 It is shown Figure 4 The flowchart shows the process of the subroutine in step S8. Figure 8As shown, in step S81, the processor 12 acquires a magnetic signal from the signal amplifier 5, representing the change in the magnetic moment of the target magnetic particle present in the zero magnetic field region, corresponding to the excitation magnetic field. Next, in step S82, the processor 12 performs a Fourier transform on the magnetic signal. Most of the fundamental signal is caused by the excitation magnetic field. Therefore, in step S82, the processor 12 preferably detects the phase of the higher harmonic signals generated in response to the change in magnetic moment.

[0087] Next, in step S83, the processor 12 uses the signal phase of the bound particles as a reference phase to perform a rotational transformation on the magnetic signal. In step S84, the processor 12 acquires the reference phase component in the rotated magnetic signal as the signal of the bound particles. That is, the processor 12 determines whether there is binding between the target magnetic particles and the target material based on the phase of the magnetic signal, and acquires the signal of the bound particles. The processor 12 stores the acquired signal of the bound particles in correspondence with the information representing the scanning position of the zero magnetic field region (the aforementioned translation position r and angle θ).

[0088] Figure 9 This is a diagram illustrating the processing steps S83 and S84. Figure 9 In the diagram, the X-axis represents the component of the change in the magnetic moment of the detected target magnetic particle that follows the AC excitation magnetic field. The Y-axis represents the delayed component of the change in the magnetic moment of the detected target magnetic particle with respect to the AC excitation magnetic field. The delayed component is offset by 90° relative to the following component.

[0089] Figure 9 The left side shows the state obtained by plotting the Fourier transform of the magnetic signal 30 on the XY plane. The signal phase 31 of the bound particles and the signal phase 32 of the unbound particles are pre-measured and registered in the information processing device 9. The information processing device 9 performs a rotational transformation on the magnetic signal 30, using the signal phase 31 of the bound particles as a reference phase. As a result, the X-axis is rotated to the X' axis, and the Y-axis is rotated to the Y' axis. Furthermore, the processor 12... Figure 6 , 7 The relaxation time of the effective relaxation curve 23a of the bound particle shown is used to calculate the signal phase 31 of the bound particle, and the rotation transformation matrix can be calculated based on the calculation result.

[0090] The processor 12 acquires the X'-axis component of the rotated magnetic signal 30 as the signal for binding particles.

[0091] (Subroutine of step S10)

[0092] Figure 10 It is shown Figure 4 The flowchart of the subroutine of step S10 is shown. Figure 10The diagram illustrates a method for generating an image representing the spatial distribution of bound particles using a well-known successive approximation image reconstruction method.

[0093] like Figure 10 As shown, in step S101, processor 12 generates a sinogram (hereinafter referred to as "measured sinogram") based on the signal of the bound particles stored in step S8 and the information representing the scan position of the zero magnetic field region. The sinogram is a signal map with the horizontal axis as the angle θ and the vertical axis as the translation position r.

[0094] Next, in step S102, processor 12 assumes a distribution of the bound particles. In step S103, processor 12 uses the assumed distribution from step S102 to generate a hypothetical sine curve. In step S104, processor 12 calculates the error between the measured sine curve generated in step S101 and the hypothetical sine curve generated in step S103. In step S105, processor 12 determines whether the error is below a predetermined convergence condition. If the error is "no" in step S105, the process returns to step S102.

[0095] The processor 12 repeats steps S102 to S104 until the error is below the convergence condition.

[0096] If "yes" is selected in step S105, in step S106, the processor 12 generates data (spatial distribution image data) representing an image that corresponds to a hypothetical sine wave satisfying the convergence condition, and outputs the generated data. For example, the processor 12 causes the display unit 16 to display an image representing the spatial distribution of the bound particles.

[0097] As described in "R. Matthew Ferguson, et al., 'Optimization of nanoparticle core size for magnetic particle imaging', J. Magn. Magn. Mater., 321 (2009), pp. 1548-1551" (Non-Patent Document 1), conventional magnetic particle imaging devices generally select the excitation frequency and the core size of the magnetic particles in a manner that minimizes the effect of relaxation delay. However, even if the signal strength is slightly reduced due to relaxation delay, it is still possible to image the spatial distribution of bound particles by distinguishing between bound and unbound particles based on the phase of the magnetic signal. This results in improved image contrast.

[0098] Furthermore, the case where the zero magnetic field region 4 is linear has been explained here. However, as mentioned above, the shape of the zero magnetic field region is not limited to linear. When the shape of the zero magnetic field region 4 is not linear, the following process can be performed: using information representing the correspondence between the scanning position of the zero magnetic field region 4 and the signal intensity at that scanning position, the hypothetical distribution is determined in a manner that makes the error between the hypothetical value obtained based on the hypothetical distribution and the measured value a convergence condition.

[0099] Implementation method 2.

[0100] Figure 11 This is a diagram illustrating an example of the overall structure of the detection system according to Embodiment 2. (See diagram for example.) Figure 11 As shown, the detection system 100A of Embodiment 2 differs from the detection system 100 of Embodiment 1 in that it includes a lock-in amplifier 20 and an information processing device 9A, which respectively replace the signal amplifier 5 and the information processing device 9.

[0101] The lock-in amplifier 20 extracts a signal with a known frequency and phase from the input signal. As the input signal, a magnetic signal measured by the magnetic sensor 3 is input to the lock-in amplifier 20. Furthermore, a reference signal with the same frequency and phase as the AC excitation magnetic field is input to the lock-in amplifier 20 from the first power supply 7. The lock-in amplifier 20 adjusts the phase of the reference signal according to a predetermined setting, in a manner consistent with the phase of the magnetic signal from the bound particles. By synchronously detecting the input signal and the adjusted reference signal, the lock-in amplifier 20 extracts a high-order harmonic signal with a phase specific to the bound particles from the magnetic signal measured by the magnetic sensor 3, and outputs the extracted signal to the information processing device 9A.

[0102] The information processing device 9A has the same hardware structure as the information processing device 9 of Embodiment 1. The processor 12 is configured in the same manner as in Embodiment 1. Figure 4 The flowchart shown illustrates the execution process.

[0103] Figure 12 This illustrates implementation method 2. Figure 4 The flowchart of the subroutine of step S8.

[0104] like Figure 12 As shown, in step S85, processor 12 receives the signal obtained by synchronous detection through lock-in amplifier 20. As described above, this signal is a high-order harmonic signal with a phase unique to the binding particles. Next, in step S86, processor 12 acquires the signal received in step S85 as the signal of the binding particles.

[0105] Implementation method 3.

[0106] Figure 13This is a flowchart illustrating the processing flow of the detection method of Embodiment 3. Figure 13 The flowchart shown is Figure 4 The difference between the flowchart shown is that it includes steps S11 and S12.

[0107] like Figure 13 As shown, in step S11 after step S4, in order to reduce magnetic particles with a nuclear particle size smaller than the diameter of the intersection particle, the target magnetic particles with a nuclear particle size larger than the diameter of the intersection particle are extracted from the candidate magnetic particles.

[0108] Figure 14 This is a diagram illustrating an example of a device for performing step S11. (See diagram for example.) Figure 14 As shown, the device includes a column 45 for allowing candidate magnetic particles 41 to pass through and a permanent magnet 40 disposed outside the column 45.

[0109] The candidate magnetic particles 41 include: target magnetic particles 42, having a nucleus diameter larger than that of the intersection particles; and non-target magnetic particles 43, having a nucleus diameter smaller than that of the intersection particles. Since the target magnetic particles 42 are more easily magnetized, they experience a stronger magnetic force. Therefore, when candidate magnetic particles 41 are introduced into the column 45, the target magnetic particles 42 are attracted to the magnetic field, while the non-target magnetic particles 43 pass through the column 45. Thus, the target magnetic particles 42 and the non-target magnetic particles are separated, and the target magnetic particles 42 are extracted. Alternatively, an electromagnet composed of coils and magnetic materials can be used instead of a permanent magnet. Alternatively, a mesh-like sieve can be used to physically extract the target magnetic particles 42.

[0110] like Figure 13 As shown, in step S12 following step S11, the extracted target magnetic particles 42 are injected into the object being inspected 6. After step S12, the process is carried out... Figure 4 The same steps S5 to S10 are repeated.

[0111] The signals from candidate magnetic particles with nuclei smaller than the diameter of the intersection particle are in phase regardless of whether they are bound to the target material. Therefore, they cannot be used to distinguish between bound and unbound particles. By reducing the number of candidate magnetic particles with nuclei smaller than the diameter of the intersection particle, the proportion of redundant signals that do not contribute to resolution input to the signal amplifier 5 or lock-in amplifier 20 can be reduced. As a result, the signal generated by detecting the target magnetic particle can be further amplified, and the signal-to-noise ratio (S / N) is improved.

[0112] Variations.

[0113] In the above description, the detection system is assumed to generate an image representing the spatial distribution of bound particles. However, in cases where total quantity checks are not required to image the spatial distribution, this can be omitted. Figure 4 Steps S5 and S7 to S10 are shown.

[0114] It should be understood that the embodiments disclosed herein are merely illustrative and not restrictive in all respects. The scope of this disclosure is defined not by the description of the above embodiments but by the claims, and is intended to include all modifications within the meaning and scope equivalent to the claims.

Claims

1. A detection method using an alternating current excitation magnetic field to detect target magnetic particles, wherein the detection method comprises: The steps for obtaining the first curve representing the relationship between Niehr relaxation time and particle diameter for candidate magnetic particles; The step of obtaining a second curve representing the relationship between Brownian relaxation time and particle diameter for the candidate magnetic particles; The step of determining the particle diameter corresponding to the intersection point of the first curve and the second curve as the intersection point particle diameter; and The step of selecting the candidate magnetic particles with a particle diameter larger than that of the intersection particle as the detection target magnetic particles.

2. The detection method according to claim 1, wherein, It also has: The steps of applying the excitation magnetic field to the target magnetic particles being detected; and The step of detecting the change in the magnetic moment of the target magnetic particle caused by the excitation magnetic field.

3. The detection method according to claim 2, wherein, The detected target magnetic particles can bind to the target material. The detection steps include: The step of detecting the phase of the higher harmonic signal generated in response to the change in said magnetic moment; and The step of determining whether the detected target magnetic particles are combined with the target material based on the phase.

4. The detection method according to claim 3, wherein, It also has: The step of generating a zero magnetic field region in the subject of inspection in the presence of the target magnetic particles and the target material; The step of scanning the zero magnetic field region in the object being inspected; as well as The step of generating an image representing the spatial distribution of the detected target magnetic particles determined to be bound to the target material in the subject under examination.

5. The detection method according to claim 1 or 2, wherein, It also has: The step of extracting the target magnetic particle from the candidate magnetic particles; and The step of injecting the target magnetic particles extracted through the extraction step into the subject of examination containing a target substance capable of binding with the target magnetic particles.

6. A detection system that uses an excitation magnetic field to detect target magnetic particles, wherein, It has a processor that performs information processing for selecting the target magnetic particle from candidate magnetic particles. The processor: For the candidate magnetic particles, obtain the first curve representing the relationship between Niehr relaxation time and particle diameter. For the candidate magnetic particles, a second curve representing the relationship between Brownian relaxation time and particle diameter was obtained. The particle diameter corresponding to the intersection point of the first curve and the second curve is determined as the intersection point particle diameter, and The candidate magnetic particles with a particle diameter larger than that of the intersection particle are selected as the detection target magnetic particles.

7. The detection system according to claim 6, wherein, It also has: An applicator applies the excitation magnetic field to the detected target magnetic particles; and A sensor that detects a magnetic signal representing a change in the magnetic moment of the target magnetic particle caused by the excitation magnetic field.

8. The detection system according to claim 7, wherein, The detected target magnetic particles can bind to the target material. The processor also includes: Based on the magnetic signal, the phase of the higher harmonic signal generated in response to the change in the magnetic moment is detected. Based on the phase, it is determined whether the detected target magnetic particles have combined with the target material.

9. The detection system according to claim 7, wherein, The detected target magnetic particles can bind to the target material. The detection system also includes a lock-in amplifier, which extracts high-order harmonic signals from the magnetic signal that correspond to the phase of particles in the target magnetic particles that are bound to the target material. The processor determines whether the detected target magnetic particles are combined with the target material based on the higher harmonic signals.

10. The detection system according to claim 8 or 9, wherein, It also has: A zero magnetic field generator generates a zero magnetic field region in an inspected object containing the target magnetic particles and the target material; and The scanning unit scans the zero magnetic field region in the object being inspected. The processor generates an image representing the spatial distribution of the detected target magnetic particles determined to be bound to the target substance in the inspected body, based on the scanning position of the zero magnetic field region and the determination result of whether or not the binding exists.

11. A computer-readable recording medium containing a computer program that supports a detection system for detecting target magnetic particles using an excitation magnetic field, wherein... The computer program causes the computer to execute: The steps for obtaining the first curve representing the relationship between Niehr relaxation time and particle diameter for candidate magnetic particles; The step of obtaining a second curve representing the relationship between Brownian relaxation time and particle diameter for the candidate magnetic particles; The step of determining the particle diameter corresponding to the intersection point of the first curve and the second curve as the intersection point particle diameter; and The step of selecting the candidate magnetic particles with a particle diameter larger than that of the intersection particle as the detection target magnetic particles.

12. The computer-readable recording medium according to claim 11, wherein, The detected target magnetic particles can bind to the target material. The computer program also causes the computer to perform: The step of determining whether the target magnetic particle is bonded to the target material based on the phase of the higher harmonic signal generated in response to the change in the magnetic moment of the target magnetic particle caused by the excitation magnetic field.

13. The computer-readable recording medium according to claim 12, wherein, The detection system has the following features: A zero magnetic field generator generates a zero magnetic field region in an inspected object containing the target magnetic particles and the target material; and The scanning unit scans the zero magnetic field region in the object being inspected. The computer program also causes the computer to perform: The step of generating an image representing the spatial distribution of the detected target magnetic particles determined to be bound to the target substance in the subject of examination, based on the scanning position of the zero magnetic field region and the determination result of whether or not the binding exists.

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