JP4791797B2 - Biomagnetic field measurement device - Google Patents

Description

  The present invention relates to a biomagnetic field measurement apparatus using a SQUID (Superconducting Quantum Interference Device) magnetic flux meter that measures a weak magnetic field generated by a living body.

  In recent years, a magnetocardiograph has been developed as a device for non-invasively visualizing electrical activity in the myocardium (see, for example, Non-Patent Documents 1 and 2). The magnetocardiograph is a device that measures a weak magnetic field generated from the heart at multiple points in a non-invasive and non-contact manner, and estimates electrical activity in the myocardium based on the measured magnetic field data.

  As one method for estimating the electrical activity in the myocardium by the magnetocardiograph, there is a method for estimating the two-dimensional and three-dimensional current distribution in the myocardium from the magnetic field data. As described above, the method of analyzing the current distribution from the magnetic field data is generally called a biomagnetic field inverse problem, and is compared with the forward problem of measuring the magnetic field generated from the current source in the living body.

  Currently, typical analysis methods applied to the inverse biomagnetic field include the Levenberg-Marquardt method (see, for example, Non-Patent Document 3), the least square method (see, for example, Non-Patent Documents 4 and 5), the Wiener filter ( For example, see Non-Patent Document 6). However, these analysis methods include improperness inherent to the inverse problem, in which the current distribution that is the solution of the inverse problem cannot be uniquely estimated.

  Therefore, in order to overcome the inappropriateness of the inverse problem, an inverse problem analysis method combining the Tikhonov regularization method has been proposed. The Tikhonov regularization method is a method for improving the inadequacy of the inverse problem by adding a stabilization term (regularization term) to the residual term used in the inverse problem analysis.

  On the other hand, a current arrow map (hereinafter referred to as “CAM”) has been developed as another method for estimating the electrical activity in the myocardium by a magnetocardiograph (see, for example, Non-Patent Document 7). CAM is a method of visualizing electrical activity in the myocardium by approximating a vector on a two-dimensional plane obtained from the spatial differentiation of the normal component magnetic field to an in-vivo current distribution.

Therefore, the use of CAM can be expected to improve the understanding level of doctors and laboratory technicians for the analysis results of the magnetocardiograph. Also, by using CAM, the test results can be provided to the patient in an easy-to-understand manner. For example, by applying CAM to cardiac disease analysis, abnormal atrial excitement of atrial flutter (for example, see Non-Patent Document 8) and abnormal ventricular excitement of QT prolongation syndrome (for example, see Non-Patent Document 9) can be visualized. ing.
K. Tsukada, et.al., "Multichanel SQUID system detecting tangential components of the cardiac magnetic field", Rev. Sci. Instruments, vol. 66, pp. 5085-5091, 1995. K. Tsukada, et.al., "A simplified superconducting interference device system to analyze vector components of a cardiac magnetic field", Proc. 20th Int. Conf. IEEE / EMBS (Hong Kong), pp. 524-527, 1998. K. Pesola, et.al., "The effect of geometric and topologic differences in boundary element models on magnetocardiographic localization accuracy", IEEE Trans.Biomed.Eng., Vol.47, pp.1237-1246,2000. J. Sarvas, "Basic mathematical and electromagnetic concepts of the biomagnetic inverse problem", Phys. Med. Biol., Vol. 32, pp. 11-22, 1987. J.Nenonen, et.al., "Current-density estimation of excise-induced ischemia in patients with multivessel coronary artery disease", J. Electrocardiol., Vol. 34 (suppl.), Pp. 37-42, 2001. WESmith, "Estimation of the spatio-temporal correlations of biological electrical sources from their magnetic fields", IEEE Trans.Biomed.Eng., Vol. 39, pp.997-1004, 1992. T.Miyashita, et.al., "Construction of tangential vectors from normal cardiac magnetic field components", Proc. 20th Int. Conf. IEEE / EMBS (Hong Kong), pp. 520-523, 1998. S. Yamada, et.al., "Noninvasive, direct visualization of macro-reentrant circuits by using magnetocardiograms: initiation and persistence of atrial flutter", Europace, vol.5, pp.343-350, 2003. A. Kandori, et.al., "Detection of spatial repolarization abnormalities in patients with LQT1 and LQT2 forms of congenital long-QT syndrome", Physiol. Meas., Vol. 23, pp. 603-614, 2002.

  Here, when the electrical activity in the myocardium is estimated using the CAM, the value calculated by the CAM is a value that approximates the current. In addition, even when the Tikhonov regularization method is applied in order to analyze the inverse problem and estimate the electrical activity in the myocardium, the method for determining the optimal regularization parameter has not yet been established. was there.

  Therefore, an object of the present invention is to provide a biomagnetic field measurement apparatus capable of obtaining the current distribution in the myocardium as an appropriate current value based on the measured magnetic field data.

In order to solve the above-described problems, the present invention provides a temporal change of a magnetic field component in the z direction perpendicular to the xy plane along a substantially body surface of a biomagnetic field generated from a living body, or along a substantially body surface of the biomagnetic field. A plurality of time-dependent changes in the magnetic field component in the x direction parallel to the xy plane and the magnetic field component in the y direction are arranged two-dimensionally at coordinate positions of (x, y) coordinates parallel to the body surface of the living body. A biomagnetic field measurement apparatus comprising a magnetometer, a computing device that computes the output signals of the plurality of magnetometers, and a display device that displays the results of the computation, wherein the computing device is: ) And (2) at least one of the biomagnetic field measurement devices.
(1) Calculation means for obtaining a change amount in the x direction and a change amount in the y direction of the magnetic field component in the z direction at an arbitrary time point, and a current source in the living body from the plurality of two-dimensional magnetometers determining the current distribution by multiplying arithmetic means for obtaining the conversion factor is determined in accordance with field current converted straight line that corresponds to the current source depth, the conversion factor to the amount of change in the x direction of the change amount and the y direction to the Arithmetic means (2) Arithmetic means for obtaining a conversion coefficient determined according to a magnetic field current conversion line corresponding to a current source depth from the plurality of magnetometers arranged in two dimensions to the current source in the living body, and an arbitrary time point It said computing means determining the current distribution by multiplying the conversion factor to a magnetic field component of the magnetic field component and the y direction of the x-direction regarding the other invention will become apparent herein in.

  According to the present invention, the approximate current distribution estimated by the CAM can be converted into a current value by comparing the estimation results of the CAM and the biomagnetic field inverse problem analysis.

  Hereinafter, the best mode for carrying out the present invention (hereinafter referred to as “embodiment”) will be described in detail with reference to the drawings as appropriate.

In the present embodiment, a biomagnetic field measurement apparatus capable of obtaining a current distribution in the myocardium as an appropriate current value based on measured magnetic field data is provided.
In other words, in this embodiment, from the viewpoint of estimating the current distribution using the CAM, the value approximated to the current is converted into a physical current value, and the inverse magnetic field problem is solved using the Tikhonov regularization method. From the viewpoint of analysis, the present invention provides a biomagnetic field measurement apparatus capable of obtaining a current distribution by determining an optimal regularization parameter.

FIG. 1 is a schematic diagram showing the overall configuration of the biomagnetic field measurement apparatus of the present embodiment. As shown in FIG. 1, the constituent elements of the biomagnetic field measurement apparatus 1 are arranged separately inside and outside the magnetic shield room 2.
Inside the magnetic shield room 2 are a cryostat 3 in which a plurality of SQUID magnetometers are arranged and kept at a cryogenic temperature, a gantry 4 that supports the cryostat 3, and a bed 5 on which a subject (not shown) lies. Is arranged. The bed 5 moves in the short axis (A direction, y direction) of the bed 5, moves in the long axis (C direction, x direction) of the bed 5, and in the vertical direction (B direction, z direction) of the bed 5. The measurement part can be easily aligned.

  Outside the magnetic shield room 2, a drive circuit 6 for driving a plurality of SQUID magnetometers arranged in the cryostat 3, an amplifier filter unit 7 for amplifying and filtering the output from the drive circuit 6, and an amplifier filter unit The output signal from 7 is collected, the collected data (hereinafter referred to as “magnetic field data”) is subjected to analysis processing, and the arithmetic device 8 that controls each part of the biomagnetic field measurement device 1 is analyzed. A display device 9 for displaying the analyzed results is mainly arranged.

  The biomagnetic field measurement apparatus 1 of the present embodiment is an apparatus that measures a magnetic field emitted from a living body, and is particularly characterized by an arithmetic unit 8 that performs an analysis process on the measured magnetic field data. Therefore, the configuration and operation of the apparatus related to other measurement and the like are appropriately applied according to the measurement site of the subject, for example, the configuration and operation of a conventional biomagnetic field measurement apparatus such as a magnetocardiograph, a magnetoencephalograph, a pulmonary magnetometer, or a magnetomyograph can do. And in this embodiment, the biomagnetic field measuring apparatus 1 of the structure which measures a cardiac magnetic field especially is demonstrated.

FIG. 2 is a diagram for explaining an example of an arrangement of a plurality of SQUID magnetometers and an arrangement with respect to a subject. The plurality of SQUID magnetometers are suspended along the z direction on the inner wall of the bottom of the cryostat (see FIG. 1) 3 and measure the magnetic field component B _z in the z direction perpendicular to the chest wall 10 over time. . The plurality of SQUID magnetometers are arranged at equal intervals in the x and y directions so that the amount of change in magnetic distance can be accurately grasped. That is, the measurement region 11 by a plurality of SQUID magnetometers can be expressed as a plane that is partitioned in a square lattice shape and arranged in parallel to the chest wall 10 of the subject as shown in FIG.

  In this embodiment, as an example, the distance between SQUID magnetometers is 0.025 m, the measurement area 11 is 0.175 m × 0.175 m, and the number of SQUID magnetometers is 8 × 8. The case of 64 channels will be described. In the coordinate system of the measurement region 11 shown in FIG. 2, for example, the SQUID magnetometer corresponding to the seventh row and the third column indicated by reference numeral 12 is positioned right above the sword-like projection 13 of the chest. Perform alignment. At this time, the SQUID magnetometer in the first row and the eighth column is set as the origin O of the coordinate system.

FIG. 3 is a block diagram showing a functional configuration of the arithmetic device 8. As shown in FIG. 3, the arithmetic device 8 includes a data processing unit 81 that analyzes collected magnetic field data, and a control unit 82 that controls each part of the biomagnetic field measurement apparatus 1. Further, the data processing unit 81 includes a CAM analysis unit (first calculation unit) 811, a current source depth estimation unit (third and ninth calculation units) 812, a magnetic field current conversion straight line generation unit 813, and a current value. A calculation unit (seventh, thirteenth, fifteenth, and seventeenth calculation means) 814 and a current distribution image generation unit 815 are included. The detailed configuration of the magnetic field current conversion straight line generation unit 813 will be described later.
The arithmetic device 8 includes a CPU and a storage device (not shown), and the function of each unit can be realized by the CPU executing a program stored in the storage device.

  Here, in the magnetic field data analysis process, the data processing unit 81 of the present embodiment performs a calculation process on the assumption that the current distribution and the magnetic field generated with the myocardial excitation satisfy the current dipole model assumed below.

FIG. 4 is a diagram for explaining the current dipole model used in the present embodiment. As shown in FIG. 4, measurement points 15 are arranged in an 8 × 8 grid on the xy plane 14 with z = 0 m.
Then, the current distribution at the time of myocardial excitation is expressed as a current dipole J (r ′) (J (r) present at a coordinate r ′ on the xy plane 17 (plane A ′) of z = z _{d in} the semi-infinite plane conductor 16. ′) = [J _x (r ′) J _y (r ′) J _z (r ′)] ^T )

When the volume current in the semi-infinite plane conductor 16 is not taken into consideration, the magnetic field B _i ( _i ) measured at the i (i = 1, 2,..., M) -th measurement point r outside the semi-infinite plane conductor 16. r) (B _i (r) = [B _{x, i} (r) B _{y, i} (r) B _{z, i} (r)] ^T ) uses the following equation (1) according to Biot-Savart's law: Can be calculated.

B _i (r) = ∫L _i (r ′) · J (r ′) dv ′ (1)

In the equation (1), L _i (r ′) is a lead field (magnetic field derivation) matrix related to the current dipole J (r ′) and the magnetic field B _i (r) measured at the i-th measurement point. The integral in the equation (1) is the area of the plane A ′. When the equation (1) is applied to all measurement points M and the plane A ′ where the current dipole exists is discretized into N regions, the matrix equation shown in the following equation (2) is obtained.

B = LJ (2)

In Equation (2), B represents a 3M × 1 magnetic field column vector, L represents a 3M × 3N lead field matrix, and J represents a 3N × 1 current dipole column vector. In the present embodiment, all the measurement points M correspond to 64, which is the number of SQUID magnetometers, but can be changed according to the configuration of the measuring apparatus including the SQUID magnetometer.
Turning now to the normal component B _z of the measurement magnetic field, it can be converted (2) is the following equation (3).

B _z = L _z J (3)

In equation (3), B _z represents an M × 1 column vector, and L _z represents an M × 3N lead field matrix. Normally, the lead field matrix L _z is determined by the detection sensitivity of each SQUID magnetometer, and is stored in advance in the storage device and is appropriately read out from the storage device during the arithmetic processing. That is, according to the equation (3), the relationship between the assumed current dipole J (r ′) corresponding to the current distribution and the normal component B _{z of the} magnetic field is defined.

[CAM analysis section]
The CAM analysis unit 811 shown in FIG. 3 estimates an approximate current distribution based on the measured magnetic field data without particularly analyzing the inverse problem. Specifically, approximate current distribution, the vector on a two-dimensional plane obtained from the spatial derivative of the normal component B _z of the magnetic field, by treating the approximate current distribution vector J ^CAM, which is expressed It is.
A current distribution image generated based on ^JCAM is referred to as a CAM image.

Here, a procedure in which the CAM analysis unit 811 calculates an approximate current distribution vector ^JCAM based on the measured magnetic field data will be described.
In the CAM analysis unit 811 of the present embodiment, it is obtained from the spatial differentiation of the normal component B _{z, i} (r) of the magnetic field at the i (i = 1, 2,..., M) th measurement point r. The magnetic field tangential component B ^CAM _{x, i} (r), B ^CAM _{y, i} (r) is treated as an approximate current distribution vector J ^CAM _i (r) in the myocardium.
^{Thus, J} _CAM i (r) constituting the x component ^J _{CAM x,} i (r) and y components ^J _{CAM y,} i (r), respectively, the following equation (4) and (5) be calculated from the equation Can do.

J ^CAM _{x, i} (r) = B ^CAM _{y, i} (r) = dB _{z, i} (r) / dy (4)
J ^CAM _{y, i} (r) = B ^CAM _{x, i} (r) = − dB _{z, i} (r) / dx (5)

Also, the approximate magnitude | J ^CAM _i (r) | of the current distribution vector is derived from the following equation (6) using the equations (4) and (5).

| ^JCAM _i (r) | = √ (( ^JCAM _{x, i} (r)) ² + ( ^JCAM _{y, i} (r)) ² ) (6)

As apparent from the equations (4) and (5), the unit of the approximate current distribution vector J ^CAM obtained by the CAM analysis unit 811 is T / m, and does not indicate a physical quantity of the current value. Absent.
Then, J ^CAM calculated by the CAM analysis unit 811 is output to the magnetic field current conversion straight line generation unit 813 and the current value calculation unit 814.

[Current source depth estimation section]
The current source depth estimation unit 812 estimates the current source depth z _d from the measurement surface of the SQUID magnetometer to the current source. As an example of a means for estimating a current source depth z _d, in this embodiment, by applying the dipole estimation method.

In the dipole estimation method, electrophysiological activity in a living body is represented by one dipole (corresponding to a current source), and its dipole coordinates (x _d , y _d , z _d ), direction θ and moment Q are estimated. This method results in an optimization problem that minimizes the following equation (7).

F ₁ (x _d , y _d , z _d , θ, Q) =
Σ (B _{z, i} −QL _i (x _d , y _d , z _d , θ)) ² / Σ (B _{z, i} ) ² (7)

In the equation (7), B _{z, i} (i = 1, 2,..., M) is a normal component of the magnetic field at a predetermined time t ₂ measured by each SQUID magnetometer of the biomagnetic field measurement apparatus 1, L _i represents the coefficients derived by the law of Biot-Savart. Further, Σ of the numerator and denominator represents addition of i = 1 to M corresponding to a plurality of SQUID magnetometers. In particular, the predetermined time t ₂ for use in the dipole, the electrical activity in the heart muscle is local, it is preferred that the initial time of the p-wave or Q waves. Thus, by using the dipole estimation method, the local myocardial excitation site in the vicinity of the sinus node, which is the current source, can be estimated relatively accurately based on the measured magnetic field data.
Then, the current source depth z _d estimated by the current source depth estimation unit 812 is output to the current value calculation unit 814.

[Magnetic current conversion straight line generator]
Field current conversion line generating unit 813, approximate the current distribution vector J ^CAM calculated by CAM analysis unit 811, to the current distribution vector (hereinafter estimated by analysis biomagnetic inverse problem in field current conversion line generating unit 813 ^And a magnetic field current conversion straight line for converting J ^CAM into a current value.
Here, the magnetic field current conversion line generating unit 813, and inverse analysis unit 813a, and the current distribution comparing unit ^813b, J ^{CAM -J MNMTR} correlation diagram generating section 813c (second, fifth, sixth, eighth and 11th and 12th calculation means) 813c and a current source depth-conversion coefficient correlation diagram generation unit 813d (14th and 16th calculation means) 813d. A combination of the inverse problem analysis unit 813a and the current distribution comparison unit 813b corresponds to the fourth and tenth arithmetic means.

(Inverse Problem Analysis Department)
The inverse problem analysis unit 813a obtains the current distribution in the living body by performing a biomagnetic field inverse problem analysis based on the measured magnetic field data.
Specifically, the current distribution estimated by the inverse problem analysis unit ^813a is expressed as a current distribution vector ^JMNMTR .
A current distribution image generated based on ^JMNMTR is referred to as an MNMTR image. A detailed description of J ^MNMTR will be given later.

The method for analyzing the inverse biomagnetic field problem by the inverse problem analysis unit 813a is not particularly limited. First, a case where analysis is performed by applying a least square method (hereinafter referred to as “MNM” for short) will be described. . MNM is one of the typical methods for inverse problem analysis, and is a method for estimating the current distribution in the myocardium by minimizing the square error between the measured value and the calculated value of the magnetic field.
That is, in the MNM, the current distribution in the myocardium is determined so as to minimize the evaluation function F shown in the following equation (8).

F = || B _z −B _z ^mes || ² (8)

In equation (8), B _z corresponds to the calculated value of the normal component magnetic field, and B _z ^mes corresponds to the measured value of the normal component magnetic field. || · || represents the Euclidean norm. Here, when the expression (3) is used, the two-dimensional current distribution vector ^JMNM that minimizes F in the expression (8) is estimated by the following expression (9).

J ^MNM = (L _z ^T L _z ) ^-1 L _z B _z ^mes (9)

However, it is difficult to uniquely find the solution of ^JMNM in equation (9). This is because the condition number of the matrix L _z ^T L _z used in the equation (9) is large, and thus noise and numerical errors of the measurement magnetic field are mixed in the current distribution vector J ^MNM obtained from the inverse matrix. To do. As described above, a problem in which a solution cannot be uniquely determined is a characteristic inherent to the inverse problem, and is called inappropriateness of the inverse problem.

Therefore, in the present embodiment, in order to improve such problems in the inverse problem analysis, the inverse problem is analyzed by combining the MNM with the Tikhonov regularization method. The Tikhonov regularization method is a method for improving the inadequacy of the inverse problem by adding a stabilization term (regularization term) to the residual term used in the inverse problem analysis. In the following, the MNM that combines the Tikhonov regularization method is described as MNMTR, and the two-dimensional current distribution vector obtained by the ^MNMTR is described as ^JMNMTR .
That is, in MNMTR, current distribution vector ^{J MNMTR} in the myocardium is estimated so as to minimize an evaluation function F in the following equation (10).

F = || B _z (J ^MNMTR ) −B _z ^mes || ² + α || RJ ^MNMTR || (10)

In Expression (10), α is a coefficient (positive constant) called a regularization parameter, and R is a 3N × 3N matrix called a stabilization matrix. Here, when the expression (3) is used, the two-dimensional current distribution vector J ^MNMTR that minimizes F in the expression (10) is estimated by the following expression (11).

^{_{J MNMTR = (L z T L}} z + αR T R) -1 L z B z mes ··· (11)

In the equation (11), for the stabilization matrix R, for example, the unit matrix I can be used. Further, as a method for obtaining the regularization parameter α, a general cross validation method, an L-curve method, and the like have been proposed.
In this embodiment, MNMTR is used as an inverse problem analysis method. However, when other analysis methods (for example, the above-described Levenberg-Marqrtdt method, Wiener filter method, etc.) are used, the same results as MNMTR are obtained. Obtainable.
Then, the current distribution vector J ^MNMTR estimated by the inverse problem analysis unit 813a is output to the current distribution comparison unit 813b.

(Current distribution comparison part)
As described above, the J ^MNMTR is estimated by analyzing the biomagnetic field inverse problem in the inverse problem analysis unit 813a. However, even when such an inverse problem analysis method is used, the regularization parameter α cannot be obtained stably. Therefore, an appropriate value is not always estimated for ^JMNMTR .

Therefore, current distribution comparing unit ^813b, by comparing the distribution pattern of ^{J CAM} and ^{J MNMTR,} to determine the appropriate ^{J MNMTR.} In addition, by determining an appropriate J ^MMNTR , an appropriate regularization parameter α is also determined.
^Here, to compare the distribution pattern of ^{J CAM} and ^{J MNMTR,} a discrete number N of ^{J MNMTR,} coordinate points M of ^{J CAM} is the same.
At this time, the current distribution comparison unit 813b determines ^JMNMTR so as to reduce the evaluation function RE _mcg shown in the following equation (12).

RE _mcg = || J ^CAM _x -J ^MNMTR _x || ² / || J ^MNMTR _x || ²
+ || J ^CAM _y −J ^MNMTR _y || ² / || J ^MMNTR _y || ² (12)

In equation (12), J ^CAM _x and J ^CAM _y are the distributions of the x component and y component of the approximate current distribution vector J ^CAM , and J ^MNMTR _x and J ^MNMTR _y are the x component and y of the current distribution vector J ^MNMTR. Represents the distribution of components. J ^CAM _x , J ^CAM _y , J ^MNMTR _x, and J ^MNMTR _y are all M × 1 column vectors. Here, J ^CAM _x , J ^CAM _y , J ^MNMTR _x and J ^MNMTR _y are values normalized by the maximum intensity of each distribution.

Note that J ^CAM and J ^MNMTR for comparing current distribution patterns are not necessarily calculated based on the measured magnetic field data. For example, in a numerical simulation, a numerical value is set for an assumed current dipole J (r ′), and distribution patterns of J ^CAM and J ^MNMTR calculated from the set current dipole J (r ′) are respectively set to the current dipoles set. It can also be evaluated by comparing with a distribution pattern of J (r ′).
Specifically, in the numerical ^simulation, the distribution pattern of ^{J CAM} and ^{J MNMTR,} and the distribution pattern of the set current dipole J (r '), is compared according to the following equation (13).

RE _sim = (|| J ^CAL _x -J ^TRUE _x || ² / || J ^TRUE _x || ²
+ || J ^CAL _y -J ^TRUE _y || ² / || J ^TRUE _y || ² ) (13)

In equation (13), J ^TRUE _x and J ^TRUE _y are the distributions of the x and y components of the current dipole J (r ′) set in the numerical simulation, and J ^CAL _x and J ^CAL _y are the current distribution vector J ^CAM or J represents the distribution of the x and y components of ^MMNTR . J ^TRUE _x, J ^TRUE _y, J ^CAL _x, and J ^CAL _x are all M × 1 column vectors. Here, J ^TRUE _x , J ^TRUE _y , J ^CAL _x and J ^CAL _y are values normalized by the maximum intensity of each distribution.

That is, in the numerical simulation, using equation (13) calculates a comparison of the distribution pattern of the current dipole J (r ') and ^{J CAM} as _{RE sim,} similarly, using the equation (13), a current dipole J and (r ') a comparison of the distribution pattern of ^{J MNMTR} calculated as _{RE sim,} compared by comparing the value of each _{RE sim,} the distribution pattern of indirectly ^{J CAM,} and a distribution pattern of ^{J MNMTR} can do. Comparison of current distribution patterns using this numerical simulation will be described in more detail in Example 1 described later.

Moreover, although the case where the comparison of the current distribution pattern is performed using the expressions (12) and (13) has been described, the current distribution pattern is approximated by comparing the brightness and the contour in the generated current distribution image. It can also be evaluated. In this ^{case, J MNMTR} to form a distribution pattern which approximates the ^{J CAM} is employed as a suitable ^{J MNMTR.}

The appropriate ^{J MNMTR} determined by the current distribution comparing unit 813b ^is output to the J ^{CAM -J MNMTR} correlation diagram generating section 813c.

^(J CAM ^{-J MNMTR} correlation diagram generation unit)
J ^CAM -J ^MNMTR correlation diagram generation unit 813c includes, at a plurality of time points _{t ^n,} extracts the maximum value of ^{J CAM} and ^{J MNMTR} generates correlation diagram, further, is to generate the regression line.

^Here, J ^{CAM -J MNMTR} correlation diagram generation unit 813c will be described a procedure for generating a regression line.
First, the J ^CAM -J ^MNMTR correlation diagram generation unit 813c determines a plurality of analysis times (time points t _n ). As the time _{t n,} p wave, QRS wave, it is preferable to use each of about 10 points of the T-wave.
^Next, J ^{CAM -J MNMTR} correlation diagram generation unit 813c extracts the maximum value of the current distribution vector ^{J CAM} and ^{J MNMTR} size at multiple time points _{t n.} This maximum value corresponds to, for example, the size of the longest vector among the 64 vectors drawn in the CAM image or the MNMTR image.

^Then, J ^{CAM -J MNMTR} correlation diagram generation unit 813c generates a correlation diagram of the magnitude maximum value of ^{J CAM} and ^{J MNMTR} at multiple time points _{t n.} In this ^case, the maximum value of the magnitude of ^{J CAM} and ^{J MNMTR} show strong positive correlation.
^Therefore, J ^{CAM -J MNMTR} correlation diagram generation unit 813c, in ^J CAM ^{-J MNMTR} correlation diagram generated, to generate a regression line. Here, the slope of this regression line is referred to as a “conversion coefficient”. The unit of the slope value of the regression line is (A · m) / (T / m).

Thus, the conversion factor calculated based on the maximum value of the magnitudes of J ^CAM and J ^MNMTR in the same measurement target (constant current source depth) is the J ^CAM (T / This can be applied when converting m) into a current value (A · m).

^Thus, by using the conversion coefficient calculated by J ^{CAM -J MNMTR} correlation diagram generating section 813c, it is possible to convert the ^{J CAM} indicating an approximate current distribution to the current value. However, the conversion coefficient generated from the measurement data of the same measurement object is applied only to that measurement object, and cannot be applied to other measurement objects.

Therefore, in order to generalize the application of such a conversion ^factor, J ^{CAM -J MNMTR} correlation diagram generation unit 813c, based on the measurement data from a plurality of measurement target (a plurality of current sources depth _{z d),} generating a plurality of ^J CAM ^{-J MNMTR} correlation diagram, it calculates a plurality of magnetic field electric conversion factor (slope of the regression line) in each of the correlation diagram. The J ^CAM -J ^MNMTR correlation diagram generation unit 813c outputs the plurality of conversion coefficients to the current source depth-conversion coefficient correlation diagram generation unit 813d.

(Current source depth-conversion coefficient correlation diagram generator)
Current source depth - Conversion factor correlation diagram generating section 813d generates a correlation diagram and a plurality of current source depth z _d, a conversion factor corresponding to each of the current source depth z _d, furthermore, to generate a regression line Is.

Here, a procedure in which the current source depth-conversion coefficient correlation diagram generation unit 813d generates a regression line will be described.
First, the current source depth-conversion coefficient correlation diagram generation unit 813d generates a correlation diagram between a plurality of current source depths z _d and conversion coefficients corresponding to the respective current source depths z _d . At this time, the current source depth z _d a conversion factor, shows a strong negative correlation.
Therefore, the current source depth-conversion coefficient correlation diagram generating unit 813d generates a regression line in the generated current source depth-conversion coefficient correlation diagram. Here, this regression line is referred to as a “magnetic field current conversion line”.

In this way, the magnetic field current conversion line generated based on the plurality of measurement objects (the plurality of current source depths z _d ) and the conversion coefficient corresponding to each current source depth z _d is the current source depth z Even if it is a measuring object of _d , it can apply when converting from ^JCAM (T / m) to an electric current value (A * m).

The magnetic field current conversion straight line generated by the current source depth-conversion coefficient correlation diagram generation unit 813d is stored in a storage unit (not shown) of the arithmetic device 8, and is read by the current value calculation unit 814 as appropriate. This storage means (not shown) can be realized by a commonly used memory or hard disk device. Further, this storage means, not only to store the magnetic field current conversion linearity, J ^CAM -J ^MNMTR and stores a correlation diagram and the regression line generated by the correlation diagram generation unit 813c, also specific measurement object ( A conversion coefficient or the like corresponding to a specific current source depth z _d ) can be extracted and stored in advance, and can be appropriately read out and used for arithmetic processing.

[Current value calculation unit]
Current calculation unit 814, based on the field current converted straight line, extracts the conversion coefficient corresponding to the current source depth z _d, and calculates the current value by multiplying the conversion factor J ^CAM.

Here, a procedure in which the current value calculation unit 814 calculates a current value will be described with reference to the drawings. FIG. 5 is a diagram illustrating an example of a magnetic field current conversion straight line.
First, the current value calculation unit 814 reads the magnetic field current conversion straight line 100 from the storage unit.
Then, the current value calculation unit 814 extracts a conversion coefficient corresponding to the current source depth z _d estimated by the current source depth estimation unit 812 based on the magnetic field current conversion straight line 100. For example, in FIG. 5, when the current source depth z _d is −0.10 m, the conversion factor is approximately 1200 (A · m / T / m).
Then, the current value calculation section 814, by multiplying the conversion factor extracted in correspondence to the current source depth z _d, the J ^CAM calculated by CAM analysis unit 811 calculates the current value. The unit of the current value calculated at this time is (A · m) and indicates the physical quantity of the current value.
Then, the current value calculation unit 814 outputs the current value converted from ^JCAM to the current distribution image generation unit 815.

[Current distribution image generator]
The current distribution image generation unit 815 generates a CAM image based on the current value converted from J ^CAM and displays it on the display device 9.
The format of the CAM image generated by the current distribution image generation unit 815 is preferably drawn by a vector on a two-dimensional plane, like a CAM image generated by a conventional CAM. The current distribution image generating unit 815 ^not only generates a CAM image based on the current value converted from ^{J CAM,} the ^{J CAM} and before it is converted into a current ^value, based on ^{J MNMTR} current distribution An arithmetic process for generating an image can also be performed.

<Current distribution calculation method>
Next, a method for calculating a current distribution by converting ^JCAM into a current value using the biomagnetic field measurement apparatus 1 of the present embodiment will be described with reference to FIGS.

FIG. 6 is a flowchart showing the overall operation of the biomagnetic field measurement apparatus 1 when calculating the current distribution by converting ^JCAM into a current value.
First, SQUID magnetometer biomagnetic field measuring apparatus 1 measures the cardiac magnetic field _{B z} of the normal component (step S10).
Next, the arithmetic unit 8 of the biomagnetic field measuring apparatus 1, the CAM analysis unit 811, ^{(corresponding} to ^{J CAM)} tangential variation from the magnetic field _{B z} of the normal component at any point in time _{t 1} to calculate the ( Step S20).
Then, the arithmetic unit 8 of the biomagnetic field measurement apparatus 1 calculates the dipole coordinates at the predetermined time t ₂ by the current source depth estimation unit 812, and obtains the current source depth z _d from the measurement surface of the SQUID magnetometer to the current source. (Step S30). Further, as described above, the predetermined time t ₂ is preferably the initial time of the p-wave or Q waves.
Then, the arithmetic unit 8 of the biomagnetic field measurement apparatus 1 generates (stores) the magnetic field current conversion straight line 100 by the magnetic field current conversion straight line generation unit 813 (step S40).
Then, the computing device 8 of the biomagnetic field measurement apparatus 1 extracts the conversion coefficient corresponding to the current source depth z _d from the magnetic field current conversion straight line 100 by the current value calculation unit 814 (step S50).
And the arithmetic unit 8 of the biomagnetic field measurement apparatus 1 calculates a current value by multiplying ^JCAM by the conversion coefficient by the current value calculation unit 814 (step S60).
Then, the arithmetic unit 8 of the biomagnetic field measuring apparatus 1, the current distribution image generating unit ^815, based on the current value converted from ^{J CAM,} and generates a CAM image (step S70).
Then, the computing device 8 of the biomagnetic field measurement apparatus 1 outputs the generated CAM image to the display device 9 by the current distribution image generation unit 815 (step S80).

Hereinafter, the generation process of the magnetic field current conversion straight line 100 in step S40 will be described in detail.
FIG. 7 is a flowchart for explaining in detail the generation process (step S40) of the magnetic field current conversion straight line 100.
First, the magnetic field current conversion straight line generation unit 813 performs an inverse problem analysis process based on the magnetic field data measured by the inverse problem analysis unit 813a, and estimates the current distribution vector ^JMNMTR (step S41).
Next, the magnetic field current conversion line generating unit 813, by the current distribution comparing unit ^813b, and compare the distribution pattern of ^{J CAM} and ^{J MNMTR,} calculates the appropriate ^{J MNMTR} (step S42).
Then, the magnetic field current conversion straight line generation unit 813 determines a plurality of analysis times (time points t _n ) by the J ^CAM -J ^MNMTR correlation diagram generation unit 813c (step S43). Incidentally, as a plurality of time points _{t n,} P wave, QRS wave, it is preferable to use each of about 10 points of the T-wave.
Then, the magnetic field current conversion straight line generation unit 813 extracts the maximum values of the sizes of J ^CAM and J ^MNMTR at a plurality of time points t _n ^using the J ^CAM -J ^MNMTR correlation diagram generation unit 813c (step S44).
Then, the magnetic field current conversion straight line generation unit 813 generates a correlation diagram of the maximum values of J ^CAM and J ^MNMTR by the J ^CAM -J ^MNMTR correlation diagram generation unit 813c, and generates a regression line (step S45). . As described above, the slope of this regression line is referred to as a “conversion coefficient”.
Then, the magnetic field current conversion straight line generation unit 813 uses the current source depth-conversion coefficient correlation diagram generation unit 813d to generate a correlation diagram between the plurality of current source depths z _d and the conversion coefficients corresponding to the respective current source depths z _d . To generate a regression line (step S46). As described above, this regression line is referred to as a “magnetic field current conversion line”.
Then, the magnetic field current conversion straight line generation unit 813 causes the current source depth-conversion coefficient correlation diagram generation unit 813d to store the generated magnetic field current conversion straight line 100 in the storage unit (step S47). Further, as described above, storing means field current converted straight line 100 that is stored in the current value calculating unit 814 is appropriately read when calculating the current value from J ^CAM, is utilized for arithmetic processing.

<Example of display screen>
FIG. 8 is a diagram illustrating an example of a display screen displayed on the display device 9 of the biomagnetic field measurement apparatus 1.
On the display screen 48 of the display device 9, a ^CAM display for displaying a magnetic field waveform display column 49 for displaying magnetic field waveforms with time measured by a plurality of SQUID magnetometers and a CAM image 68 generated based on JCAM. And a column 50 are displayed. The display screen 48 also relates to a magnetic field waveform display condition input field 51 for inputting the display conditions of the magnetic field waveform displayed in the magnetic field waveform display field 49 and a CAM image 68 displayed in the CAM display field 50 hereinafter. , A CAM calculation condition input field 52 for inputting a calculation condition for calculating J ^CAM , a CAM display condition input field 53 for inputting a display condition of the CAM image 68, and a calculation condition for converting J ^CAM into a current value And a current value calculation condition input field 54 for inputting.

  In the magnetic field waveform display column 49, a cardiac magnetic field waveform 60, a bar 61 displayed corresponding to the input in the magnetic field waveform display condition input column 51, and a scroll bar 62 corresponding to the display time width of the cardiac magnetic field waveform 60 are displayed. Is done.

In the CAM display column 50, a CAM image 68, a color bar 69 corresponding to an approximate current intensity value (J ^CAM size) of the displayed CAM image 68, a maximum value display 70 of the color bar 69, A minimum value display 71 of the color bar 69 is displayed.

  The magnetic field waveform display condition input field 51 has an input field 55 for setting the time width of the displayed magnetic field waveform, an input field 56 for setting the time width offset, and an input for setting the width of the amplitude of the displayed magnetic field waveform. A field 57, an input field 58 for setting an amplitude width offset, and an execution button 59 for reflecting the settings of these input fields 55 to 58 to the magnetic field waveform display column 49 are provided.

The CAM calculation condition input field 52 includes an input field 63 for setting the number of CAM images 68 to be calculated (number of maps), an input field 64 for setting the start time of the CAM image 68 to be calculated, and the time of the CAM image 68 to be calculated. An input field 65 for setting the interval, an execution button 66 for calculating J ^CAM according to the setting values of these input fields 63 to 65 and displaying the CAM image 68 on the CAM display column 50, and setting values of the input fields 63 to 65 The clear button 67 for clearing is provided.

  The CAM display condition input field 53 includes an input field 72 for setting a color map maximum value display 70 for the CAM image 68, an input field 73 for setting a color map minimum value display 71 for the CAM image 68, and these input fields. An execution button 74 for reflecting the settings 72 and 73 in the CAM display field 50 is provided.

The current value calculation condition input field 54 has an input field 75 for setting the depth of the heart from the measurement surface, that is, the current source depth z _d from the measurement surface of the SQUID magnetometer to the heart, and J ^CAM is converted into a current value. Radio buttons (calculation selection buttons) 76, 77 for selecting conversion straight lines (standard straight lines, individual straight lines) to be used for the calculation, and a display button 78 for calculating and displaying the conversion straight lines selected by the radio buttons 76, 77; In accordance with the settings of the input field 75 and radio buttons 76 and 77, an execution button 79 for converting ^JCAM into a current value and a cancel button 80 for canceling the settings of the input field 75 and radio buttons 76 and 77 are provided.
Note that the standard straight line indicated by the radio button 76 in the figure corresponds to a field current converted straight line 100, and individual line representing a radio button 77, a predetermined current source depth _{z d} ^J CAM ^{-J MNMTR} produced in It corresponds to the regression line of the correlation diagram. Moreover, although the selected conversion straight line (standard straight line, individual straight line) is not shown in FIG. 8, it is assumed that it is displayed as appropriate.

FIG. 9 shows a display screen 48 when a CAM image 68 converted into a current value is displayed in the CAM display field 50. As shown in FIG. 9, after the execution button 79 in the current value calculation condition input field 54 is pressed, the CAM image 68 converted into the current value is displayed in the CAM display field 50. Further, the maximum value display 70 of the color bar 69 and the minimum value display 71 of the color bar are changed to display of the maximum value and the minimum value of the current value, respectively. At this time, the unit of the color bar is also changed from the T / m in FIG. 8 to the display of the unit of physical current (A · m).
Further, when the CAM image 68 converted into the current value is displayed in the CAM display field 50, when the cancel button 80 in the current value calculation condition input field 54 is pressed, the CAM image 68 before conversion into the current value is displayed again. Is displayed.

  8 and 9, the CAM image before conversion into the current value and the CAM image after conversion are sequentially displayed according to the input, but the screen configuration may be such that both are displayed in the same screen. Good.

According to the above, the following effects can be obtained in the present embodiment.
A current distribution can be calculated as a current value by multiplying J ^CAM representing an approximate current distribution by a conversion coefficient. Furthermore, since the means for calculating the conversion coefficient is provided, even if the conversion coefficient is not stored in advance, a new conversion coefficient can be calculated based on the measurement data and J ^CAM can be converted into a current value. it can.
Further, by using the magnetic field current conversion straight line 100, J ^CAM (T / m) can be converted into a current value (A · m) from any current source depth z _d to be measured. . Furthermore, since a structure in which a means for generating a conversion factor and a field current converted straight line 100 that associates a current source depth z _d (field current conversion line generating unit 813), field current converted straight line 100 is stored in advance even if not newly generate a field current converted linearly 100 based on the measured data, it is possible to extract a conversion factor corresponding to the current source depth z _d.
That is, once if the generated magnetic field current conversion straight line 100 may use a biomagnetic field measuring apparatus 1 of the present embodiment, it converts the plurality of measurement target J ^CAM having different current source depth z _d in current value .

  In addition, this embodiment is not limited to the said embodiment, A various change implementation can be performed in the range which the technical idea covers.

In the present ^embodiment, J ^{CAM -J MNMTR} correlation diagram generation unit 813c is, but to generate a correlation diagram based on the size the maximum value of ^{J CAM} and ^{J MNMTR} at multiple time points _{t n,} the technique of the present invention The range of the philosophy is to obtain an appropriate current distribution by comparing the approximate current distribution estimated by CAM and the current distribution estimated by inverse biomagnetic field analysis, and the above-mentioned conversion is not necessarily required. The method is not limited to the method for generating the coefficient / magnetic field current conversion straight line. For example, the correlation diagram can be generated based on the average value of the magnitudes of J ^{CAM and} J ^MNMTR at a plurality of ^times t _n .

<Modified Example of Approximate Current Distribution Vector Calculation Processing>
In the present embodiment, by measuring the magnetic field component B _z of the z direction perpendicular to the xy plane, by spatial differentiation magnetic field component of the magnetic field components B _x and y direction parallel x-direction in the xy direction B _y preparative it is configured to calculate the, as approximate current distribution vector J ^CAM, if it is possible to determine the magnetic field component B _y of the magnetic field components B _x and y direction of the x-direction, the method is not particularly limited.

Here, a method of calculating the J ^CAM when using SQUID magnetometers for detecting a time variation of the magnetic field component B _y of the magnetic field components B _x and _y directions parallel x-direction in the xy plane of the biomagnetic field. When the magnetic field line B _{x, i} (r) in the x direction and the magnetic field component B _{y, i} (r) in the y direction at the i (i = 1, 2,..., M) th measurement point r are used. , ^JCAM can be calculated from the following equations (14) and (15).

J ^CAM _{x, i} (r) = B _{y, i} (r) (14)
J ^CAM _{y, i} (r) = − B _{x, i} (r) (15)

Note that the magnitude of the approximate current distribution vector | J ^CAM _i (r) | can be obtained from the same calculation as in the equation (6).

<Modification regarding current source depth estimation unit>
In the present embodiment, the current source depth z _d is estimated by providing the current source depth estimation unit 812 in the data processing unit 81 and performing dipole estimation based on the measured magnetic field data. However, the current source depth z _d Can be obtained, the biomagnetic field measurement apparatus 1 may have any configuration. Instead of the current source depth estimation unit 812, for example, conventional nuclear magnetic resonance imaging apparatus, X-rays CT device, or by features an ultrasonic imaging apparatus, it easy to estimate the current source depth z _d it can.

When obtaining the current source depth z _d from the measurement result of the nuclear magnetic resonance imaging apparatus, X-ray CT apparatus or ultrasonic imaging apparatus, first, the measurement of the nuclear magnetic resonance imaging apparatus, X-ray CT apparatus or ultrasonic imaging apparatus is performed. The result is used to calculate the distance from the body surface to the heart. Next, add the distance from the measurement surface of the magnetocardiograph measured during magnetocardiography to the body surface and the distance from the body surface to the heart, and the distance from the meter side of the magnetocardiograph to the heart (current source depth). z _d ) is obtained.

Although not shown, when measured actually a current source depth _{z d} along this modification, the current value of the maximum QRS wave was 6.85 × ^{10 -10} A · m. On the other hand, when the current source depth z _d is estimated based on the dipole estimation of the present embodiment, the maximum current value of the QRS wave is 6.66 × 10 ⁻¹⁰ A · m, which is almost the same value. showed that.
According to the biomagnetic field measurement apparatus of the present invention, regardless of the method of estimating the current source depth z _d, it is possible to obtain the appropriate current value.

<Modification of current distribution calculation method>
In this embodiment, the current distribution is calculated by converting ^JCAM representing an approximate current distribution into a current value. However, the scope of the technical idea of the present invention is an approximate current estimated by the CAM. An appropriate current distribution is obtained by comparing the distribution and the current distribution estimated by the biomagnetic field inverse problem analysis, and is not necessarily limited to the above-described current distribution calculation method.
Here, with reference to FIG. 10, a method of calculating a current distribution as ^JMNMTR using the biomagnetic field measurement apparatus 1 of the present embodiment will be described.

FIG. 10 is a flowchart showing the overall operation of the biomagnetic field measurement apparatus 1 when calculating the current distribution as ^JMNMTR .
First, SQUID magnetometer biomagnetic field measuring apparatus 1 measures the cardiac magnetic field _{B z} of the normal component (step S110).
Next, the arithmetic unit 8 of the biomagnetic field measuring apparatus 1, the CAM analysis unit 811, ^{(corresponding} to ^{J CAM)} tangential variation from the magnetic field _{B z} of the normal component at any point in time _{t 1} to calculate the ( Step S120).
Then, the arithmetic unit 8 of the biomagnetic field measurement apparatus 1 calculates the dipole coordinates at the predetermined time t ₂ by the current source depth estimation unit 812, and obtains the current source depth z _d from the measurement surface of the SQUID magnetometer to the current source. (Step S130). Further, as described above, the predetermined time t ₂ is preferably the initial time of the p-wave or Q waves.
Then, the arithmetic unit 8 of the biomagnetic field measuring apparatus 1, the inverse analysis unit 813a, performs the inverse problem analysis in the current source depth _{z ^d,} estimates the ^{J MNMTR} (step S140). Note that a value of about 10 ^{−1 is} usually adopted as the initial value α ₀ of the regularization parameter α used for the inverse problem analysis processing.
Then, the arithmetic unit 8 of the biomagnetic field measuring apparatus 1, the current distribution comparing unit ^813b, with reference to the ^{J MNMTR} and ^{J CAM,} calculate the optimal regularization parameter alpha _opt that minimizes the equation (12) (step S150). Note that it is preferable to use the downhill simplex method for the function minimization of the equation (12).
Then, the arithmetic unit 8 of the biomagnetic field measurement apparatus 1 calculates the optimum J ^MNMTR using the optimum regularization parameter α _opt by the inverse problem analysis unit 813a (step S160).
Then, the arithmetic unit 8 of the biomagnetic field measurement apparatus 1 generates an MNMTR image based on the optimum ^JMNMTR by the current distribution image generation unit 815 (step S170).
Then, the arithmetic device 8 of the biomagnetic field measurement apparatus 1 outputs the generated MNMTR image to the display device 9 by the current value calculation unit 814 (step S180).

As described above, according to the modification of the current distribution calculation method, in the biomagnetic field inverse problem analysis combined with the Tikhonov regularization method, the optimal regularization parameter α _opt is estimated by the CAM and biomagnetic field inverse problem analysis. The evaluation function defined by the difference between the current distributions to be minimized can be determined. As a result, the optimal J ^MNMTR can be calculated.
It should be noted that the optimal regularization parameter α _opt and the optimal J ^MNMTR calculated in this modification of the current distribution calculation method are used as the magnetic field current conversion straight line 100 described in the present embodiment, and the J ^CAM -J ^MNMTR correlation diagram. Needless to say, it can be used to generate regression lines.

<Display screen example according to a modification of the current distribution calculation method>
FIG. 11 is a diagram illustrating an example of a display screen that displays a current distribution (hereinafter, referred to as an MNMTR image) generated based on the optimum ^JMNMTR using the biomagnetic field measurement apparatus 1 of the present embodiment.
In the display screen example shown in FIG. 11, compared to the display screen example of the present embodiment described with reference to FIG. 8, the MNMTR display field 150 for displaying the MNMTR image 168 and the in-vivo current distribution calculation condition input field. 152 is different from the MNMTR display condition input field 154. Therefore, description about the overlapping part is omitted, and the characteristic part in this example will be described in detail.

The MNMTR display field 150 includes an MNMTR image 168, a color bar 169 corresponding to the current intensity value (the size of J ^MNMTR ) of the displayed MNMTR image 168, a maximum value display 170 of the color bar 169, and a color bar 169 A minimum value display 171 is displayed.

The in-vivo current distribution calculation condition input field 152 has an input field 163 for setting the number of CAM images 68 and MNMTR images 168 to be calculated (the number of maps), and an input for setting the start times of the CAM images 68 and MNMTR images 168 to be calculated. From the field 164, an input field 165 for setting the time interval between the CAM image 68 and the MNMTR image 168 to be calculated, and the heart depth from the measurement plane used to calculate the MNMTR image 168, that is, from the measurement plane of the SQUID magnetometer An input field 175 for setting the current source depth z _d to the heart, and a current distribution vector (J ^CAM and J ^MNMTR ) are calculated according to the set values of the input fields 163, 164, 165, 175, and the CAM image 68 and MNMTR Images 168 are displayed in CAM display field 50 and M, respectively. An execution button 166 to be displayed in the NMTR display field 150 and a clear button 167 for clearing the set values in the input fields 163, 164, 165, and 175 are provided.

  The MNMTR display condition input field 154 includes an input field 172 for setting a color map maximum value display 170 of the MNMTR image 168 displayed in the MNMTR display field 150, and a color map of the MNMTR image 168 displayed in the MNMTR display field 150. An input field 173 for setting the minimum value display 171 and an execution button 179 for reflecting the settings of the input fields 172 and 173 to the MNMTR display field 150 are provided.

  Hereinafter, the biomagnetic field measurement apparatus of the present invention described in the above-described embodiment will be described using examples.

<Example 1>
The first embodiment is an embodiment in which an appropriate regularization parameter α is determined by numerical simulation.
Specifically, a numerical value is set for the current dipole J (r ′) (see FIG. 4) assumed in the above-described embodiment, and J ^CAM and J ^MNMTR calculated based on the set current dipole J (r ′). The appropriate regularization parameter α was determined by comparing the distribution patterns of.

  In the numerical simulation of Example 1, first, as shown in FIG. 4, the measurement points 15 were arranged in an 8 × 8 grid on the xy plane 14 with z = 0 m. The interval between the measurement points 15 is 0.025 m and has a measurement area of 0.175 m × 0.175 m.

And in the numerical simulation of Example 1, three simulation models are examined. In the three simulation models, the current dipole J (r ′) is set on the xy plane 17 (plane A ′) of z = z _{d in} the semi-infinite plane conductor 16 in common.
In each of the three simulation models, the current source depth z _d from the measurement surface of the SQUID magnetometer to the current dipole J (r ′) is set to z _d = −0.08 m, −0.10 m, and −0.12 m. did.

FIG. 12 is a layout diagram of the set current dipole J (r ′) on the xy plane 17 where z = z _d in the three simulation models. 12, (a) is a simulation model (model 1) in which four current dipoles 18 are arranged in a square region, and (b) is a simulation model (model) in which twelve current dipoles 19 are arranged in an L-shaped region. 2) and (c) are simulation models (model 3) in which twelve current dipoles 20 that continuously rotate are arranged in a square region. In any simulation model, the moment of the current dipole J (r ′) is 5.0 μT · m.
The angle of the current dipole J (r ′) is (a) in one direction (45 °), (b) in two directions (0 ° and 90 °), and (c) in four directions (0 ° , 90 °, 180 ° and 270 °). Note that these current direction angles conform to the angle definition 21 shown in FIG.

And about three simulation models, the magnetic field _{Bz, i} (r) of the normal direction was calculated from (3) Formula. Further, J ^CAM and J ^MNMTR were calculated based on the magnetic field B _{z, i} (r) of the normal component. J ^MNMTR obtained values corresponding to the regularization parameters α while changing the regularization parameters α in the range of 10 ⁻¹ to 10 ⁻¹⁶ .

Then, was calculated according to the distribution pattern, the matching degree _{RE sim} the distribution pattern of the calculated ^{J CAM} (13) equation of the set current dipole J (r '). Similarly, the degree of coincidence RE _sim between the set distribution pattern of the current dipole J (r ′) and the calculated distribution pattern of ^JMMNTR was calculated according to the equation (13).

13-15, 'a degree of coincidence _{RE sim} distribution pattern of the ^{J _CAM,} current dipole J (r current dipole J (r)' was plotted and coincidence degree _{RE sim} distribution pattern of ^{J MNMTR} a) simultaneously Figure 13 to 15 correspond to models 1 to 3 shown in FIGS. 12A, 12B, and 12C, respectively. 13 to 15, the horizontal axis represents a method (CAM and MNMTR) compared with the set distribution pattern of the current dipole J (r ′), and the vertical axis represents the current dipole J (r ′). It is the degree of agreement RE _sim of the distribution pattern with the compared method. In FIGS. 13 to 15, circles (●) 22, triangles (▲) 23, and squares (■) 24 have current source depths z _d of −0.08 m, −0.10 m, and −0.12 m, respectively. It is RE _sim at the time.

Here, as shown in FIG. 13, the distribution pattern of the current dipole J (r ′) and J ^CAM at each depth (z _d = −0.08 m, −0.10 m and −0.12 m) of the model 1. The coincidence degree RE _sim is 2.43, 3.20, and 4.07, respectively.
As shown in FIG. 14, the degree of coincidence between the distribution patterns of the current dipole J (r ′) and J ^CAM at each depth (z _d = −0.08 m, −0.10 m and −0.12 m) of the model 2 RE _sim is 0.96, 1.22 and 1.48, respectively.
As shown in FIG. 15, the depth of the model 3 in the _(z d = _{-0.08m, -0.10m} and -0.12M), current dipole J (r ') and matching of the distribution pattern of ^{J CAM} RE _sim is 1.86, 2.60 and 3.12.

As shown in FIGS. 13 to 15, in each simulation model and each depth, the degree of coincidence RE _sim ^between the distribution patterns of the current dipole J (r ′) and J ^MNMTR has a regularization parameter α of 10 ^−. When the regularization parameter α is 10 ⁻⁹ to 10 ⁻¹⁵ , the value of RE _sim is greatly decreased while the value is hardly changed when it is ¹ to 10 ⁻⁸ .

Then, 'the matching degree _{RE sim} distribution pattern of the ^{J CAM,} current dipole J (r current dipole J (r)' is compared with the coincidence of _{RE sim} distribution pattern of ^{J MNMTR} with), in 13 to 15 In each simulation model and each depth shown, the matching degree RE _sim of the distribution pattern of the current dipole J (r ′) and J ^CAM and the matching degree RE of the distribution pattern of the current dipole J (r ′) and J ^MNMTR It matched with _sim when the regularization parameter (alpha) was 10 ^<-9> to 10 ^{<-10 >} . This ^is to reflect a higher degree of matching distribution pattern of ^{J CAM} and ^{J MNMTR.}
Therefore, as a result of the numerical simulation of Example 1, an appropriate regularization parameter α was determined as 10 ⁻¹⁰ .

Here, with reference to FIGS. 16 to 18, the degree of coincidence of the current distribution patterns in the simulation model of Example 1 is visually evaluated.
Figure 16 is a current distribution image generated on the basis of the ^{J CAM} and ^{J MNMTR} calculated in the model 1, (a) is ^{J CAM, (b) ~ (} d) is generated based on ^{J MNMTR} It is an electric current distribution image. Also, (b), (c), and (d) differ in the value of the regularization parameter α when calculating ^JMMNTR . In FIG. 16, the current source depth z _d shows a case where z _d = −0.10 m as an example.

  In FIGS. 16A to 16D, an arrow 25 represents a current distribution vector. In FIGS. 16A to 16D, a black region 26 indicates a region where the current distribution vector has a large size, and a gray region 27 indicates a region where the current distribution vector has a medium size. The region 28 indicates a region where the magnitude of the current distribution vector is small.

Here, the current distribution image based on ^{J MNMTR} upon the current distribution image based on ^{J CAM} shown in FIG. 16 (a), and ^{10 -10} of the regularization parameter α shown in FIG. 16 (c), in good agreement It was shown that. And when not shown, other current source depth _{z d (z d = -0.08m,} -0.12m) ^even, that the current distribution image based on ^{J CAM,} the regularization parameter α was set to ^{10 -10} The current distribution images based on ^JMNMTR were in good agreement. On the other hand, when the regularization parameter α was set to 10 ⁻¹ and 10 ⁻¹⁵ , no coincidence was observed.

FIGS. 17 and 18 are diagrams showing current distribution images generated based on J ^CAM and J ^MNMTR calculated in models 2 and 3, respectively. As shown in FIGS. 17 and 18, also in Models 2 and ^3, the current distribution image based on ^{J CAM,} current distribution image based on ^{J MNMTR} when the regularization parameter α is ^{10 -10,} good one I did it.

According to the results of Example 1, in the numerical ^simulation, the distribution pattern of ^{J CAM} and ^{J MNMTR,} (in this example ^{10 -10)} a predetermined regularization parameter was shown to coincide at. This is by using a predetermined conversion factor, the J ^CAM indicating an approximate current distribution means that can be converted into a current value in units of J ^MNMTR.

<Example 2>
Example 2 is an example in which an appropriate regularization parameter α is determined based on measured magnetic field data.
Specifically, to determine the appropriate regularization parameter α by comparing the actually measured J ^CAM and J ^MNMTR distribution pattern calculated based on the magnetic field data.

  The measurement conditions of the cardiac magnetic field in Example 2 were the same as those exemplified in the above-described embodiment, and an apparatus having 64 SQUID magnetometers and measuring the cardiac magnetic field in the normal direction was used. The SQUID magnetometers are arranged in an 8 × 8 grid, and the distance between each sensor is 0.025 m.

FIG. 19 is a diagram in which the magnetocardiogram waveform of a healthy person A measured over time by 64 SQUID magnetometers is superimposed on one trace. As shown in FIG. 19, the magnetocardiogram waveform 29 is composed of three waves, a p wave, a QRS wave, and a T wave.
In Example 2, J ^CAM and J ^MNMTR were calculated at three points: p wave maximum time 30, QRS wave maximum time 31, and T wave maximum time 32.

J ^MNMTR was calculated and evaluated when the regularization parameter α was set to 10 ⁻¹ , 10 ⁻¹⁰ , and 10 ⁻¹⁶ . In addition, the current source depth z _d for calculating J ^{MMNTR used} dipole coordinates (x _d , y _d , z _d ) obtained from the dipole estimation result at the beginning of the p-wave. According to the dipole results for p-wave initial, current source depth _{z d} was -0.112M.

Here, with reference to FIGS. 20 to 22, the degree of coincidence of the current distribution patterns calculated based on the measurement data of Example 2 is visually evaluated.
FIG. 20 is a current distribution image generated based on the J ^CAM and J ^MNMTR calculated at the p-wave maximum time (see FIG. 19) 30, where (a) is J ^CAM and (b) to (d) are It is the electric current distribution image produced ^| generated based on ^JMNMTR . Also, (b), (c), and (d) differ in the value of the regularization parameter α when calculating ^JMMNTR .

  20A to 20D, an arrow 33 represents a current distribution vector. 20A to 20D, a black region 34 indicates a region where the current distribution vector is large, and a gray region 35 indicates a region where the current distribution vector is large. The region 36 indicates a region where the magnitude of the current distribution vector is small.

Here, FIG. 20 (a) and the current distribution image based on ^{J CAM} shown in current distribution image based on ^{J MNMTR} when formed into a ^{10 -10} regularization parameter α shown in FIG. 20 (c), in good agreement It was shown that. On the other hand, when the regularization parameter α was set to 10 ⁻¹ and 10 ⁻¹⁵ , no coincidence was observed.

21 and 22 are current distribution images generated based on J ^CAM and J ^MNMTR calculated at QRS wave maximum time (see FIG. 19) 31 and T wave maximum time (see FIG. 19) 32, respectively. is there. As shown in FIGS. 21 and 22, also in the QRS wave maximum time (see FIG. 19) 31 and the T wave maximum time (see FIG. 19) 32, the current distribution image based on ^JCAM and the regularization parameter α are set to 10 ^{−. The} current distribution images based on ^JMNMTR when the ^value was ¹⁰ matched well.

According to the results of Example 2, in the case of using the actual measured magnetic field data, the distribution pattern of J ^CAM and J ^MNMTR, to match (10 ^-10 in the present ^embodiment) given regularization parameter It has been shown. This is by using a predetermined conversion factor, the J ^CAM indicating an approximate current distribution means that can be converted into a current value in units of J ^MNMTR.
Further, since the appropriate regularization parameter ^10-10 determined in the second embodiment matches the regularization parameter ^10-10 determined in the numerical simulation of the first embodiment, an appropriate regularization parameter is also obtained by the numerical simulation. It was shown that α can be determined.

<Example 3>
Example 3, based on the field data of one person in healthy subjects A heart ^generates J ^{CAM -J MNMTR} correlation diagram, further, an embodiment in which to generate the regression line.
First, at the 33 time points of the magnetic field data of the heart (when a predetermined time width is extracted from the initial time of the p wave, QRS wave, and T wave and each time width is divided into 10 equal parts), J ^CAM and J ^MNMTR (α = 10 ⁻¹⁰ ) was calculated, and the maximum value of J ^CAM and J ^MNMTR (α = 10 ⁻¹⁰ ) at each time point was extracted.
Then, based on the maximum value extracted ^to produce a J ^{CAM -J MNMTR} correlation diagram. The current source depth z _d for estimating J ^MNMTR used the dipole coordinates (x _d , y _d , z _d ) obtained from the dipole estimation result of the healthy person A in the early ^stage of the p-wave.

Figure 23 is a ^J CAM ^{-J MNMTR} correlation diagram healthy person A (regularization parameter α = 10 ^-10). 23, the horizontal axis (x-axis) is a maximum value of the magnitude of ^{J CAM,} the vertical axis (y-axis) indicates the maximum value of the magnitude of ^{J MNMTR.} The circles (●) 37 ^is a plot which corresponds the maximum size of the ^{J CAM} and ^{J MNMTR.} In the generated ^J CAM ^{-J MNMTR} correlation ^diagram, the correlation coefficient magnitude maximum value of ^{J CAM} and ^{J MNMTR (α = 10 -10)} was 0.9 or more.

Subsequently, in the ^J CAM ^{-J MNMTR} correlation diagram, to produce a regression line 38. At this time, the regression line 38 was y = 1101x. It can be seen that the current value (A · m) can be converted by multiplying the CAM value (T / m) by using the slope of the regression line 38 as a conversion coefficient.
According to the results of Example 3, the same subject J ^CAM and J ^MNMTR calculated based on the magnetic field data of the heart ^(α = 10 ^-10) has a very strong correlation was shown to be converted to each other .

<Example 4>
Example 4 is an example in which a current source depth-conversion coefficient correlation diagram is generated based on magnetic field data of 10 adult hearts, and a regression line is generated.
First, for 10 adult subjects, J ^CAM and J ^MNMTR (α = 10 ⁻¹⁰ ) were calculated at 33 time points from the total time width of the ^{magnetocardiographic} data, and J ^CAM and J ^MNMTR ( The maximum value of the size of α = 10 ⁻¹⁰ ) was extracted. Then, based on the maximum value extracted ^to produce a J ^{CAM -J MNMTR} correlation diagram.
As the current source depth z _d for estimating J ^MNMTR , dipole coordinates (x _d , y _d , z _d ) obtained from the dipole estimation results at the initial ^stage of the p wave for each subject were used.

Figure 24 is a ^J CAM ^{-J MNMTR} correlation diagram for subjects 10 adults (regularization parameter alpha ^{= 10 -10).} In Figure 24, the horizontal axis (x-axis) is a maximum value of the magnitude of ^{J CAM,} the vertical axis (y-axis) indicates the maximum value of the magnitude of ^{J MNMTR.} The code 39 ^is a plot which corresponds the maximum size of the ^{J CAM} and ^{J MNMTR.} Moreover, in the code | symbol 39, the plot derived from the same test subject is shown with the same symbol. In ^J CAM ^{-J MNMTR} correlation diagram generated, the correlation coefficient magnitude maximum value of ^{J CAM} and ^{J MNMTR} in the same subject (α ^{= 10 -10)} was 0.9 or more. On the other hand, the correlation coefficient of the plot between different subjects showed a relatively weak correlation.

Subsequently, in the ^J CAM ^{-J MNMTR} correlation diagram, as shown in FIG. 25, to generate a regression line 40. The regression line 40 was generated for each identical subject (same reference numeral 39 in FIG. 24).
At this time, the slope of the regression line varied from subject to subject. This is considered to be because the current source depth z _d from the magnetocardiogram measurement surface to the current source in the living body differs for each subject.

Therefore, as shown in FIG. 26, a current source depth-conversion coefficient correlation diagram is generated in which the current source depth z _d from the side of the magnetocardiograph to the current source in the living body is associated with the conversion coefficient for each subject.
In FIG. 26, the horizontal axis (x-axis) is the current source depth z _d from the measurement surface to the current source in the living body, and the vertical axis (y-axis) indicates the conversion factor. A circle (●) 41 is a plot that associates the current source depth z _d with the conversion coefficient. In the generated current source depth-conversion coefficient correlation diagram, the current source depth z _d and the conversion coefficient showed a strong correlation.

Further, a regression line 42 was generated in this current source depth-conversion coefficient correlation diagram. At this time, the regression line 42 was y = -11773x-158. By substituting the current source depth z _d from the measurement surface to the current source in the living body into this regression line 42 and multiplying the extracted conversion coefficient by J ^CAM (T / m), the current value (A · m ) Can be obtained.
According to the result of Example 4, it was shown that the current source depth z _d from the measurement surface to the current source in the living body and the conversion coefficient of 10 subjects had a strong correlation.

<Example 5>
In the fifth embodiment, a conversion coefficient is calculated based on the magnetic field data of the heart of a child with a small heart, and the correspondence relationship with the current source depth z _d is verified.
First, the subject of four children (age 9 from 5 years), at 33 time points from the total duration of the magnetocardiogram measurement ^data, calculate the ^{J CAM} and ^{J MNMTR (α = 10 -10)} , each time point and it extracts the maximum value of the magnitude of ^{J CAM} and ^{J MNMTR (α = 10 -10)} in. Then, based on the maximum value extracted ^to produce a J ^{CAM -J MNMTR} correlation diagram (not shown).
As the current source depth z _d for estimating J ^MNMTR , dipole coordinates (x _d , y _d , z _d ) obtained from the dipole estimation results at the initial ^stage of the p wave for each subject were used.
^Then, the J ^{CAM -J MNMTR} correlation diagram, generate a regression line, by calculating the slope of the regression line was obtained a conversion factor.

Then, a current source depth z _d until the current source in the living body from magnetocardiograph side, to correspond to conversion coefficients for each subject, a current source depth - to generate a conversion factor correlation diagram.
FIG. 27 is a diagram in which the child current source depth-conversion coefficient correlation diagram generated in Example 5 is superimposed on the adult current source depth-conversion coefficient correlation diagram shown in FIG. Therefore, the description about the part which overlaps with FIG. 26 is abbreviate | omitted.
In FIG. 27, a white circle (◯) 43 is a plot that associates the current source depth z _d of a child with a conversion factor. As shown in FIG. 27, this white circle (◯) 43 was located on a regression straight line (magnetic field current conversion straight line) 42 obtained from an adult. That is, even in children with small hearts, the current source depth z _d and the conversion factor showed a strong correlation.
According to the result of Example 5, it was shown that the conversion factor is uniquely determined by the current source depth z _d , as in the case of an adult, even in a child with a small heart.

<Example 6>
Example 6 is an example for explaining in detail a modification of the current distribution calculation method.
Specifically, the optimal regularization parameter α _opt was calculated based on the actually measured magnetic field data, and the optimal J ^MNMTR was calculated based on the calculated optimal regularization parameter α _opt . And the current distribution image was produced ^| generated based on ^JMNMTR .

FIG. 28 is a current distribution image generated based on J ^MNMTR (regularization parameter α _opt ) and J ^{CAM of} healthy person A, (a) p-wave maximum time, (b) QRS wave maximum time, (C) is a current distribution at the T-wave maximum time. Further, in FIG. 28 (a) ~ (c) , the left column Figure is a current distribution image based on ^{J MNMTR (α} _opt), the right column drawing a current distribution image based on the ^{J CAM.}

  In FIGS. 28A to 28C, an arrow 44 represents a current distribution vector. In FIGS. 28A to 28C, the black region 45 is a region where the current distribution vector is large, and the gray region 46 is a region where the current distribution vector is medium. A region 47 indicates a region where the magnitude of the current distribution vector is small.

Here, at each time of FIGS. ^{28A to 28C} , the current distribution image generated based on J ^MNMTR (α _opt ) matches the current distribution image generated based on J ^CAM . It was shown that.

According to the results of Example 6, distribution pattern of J ^MNMTR calculated using the optimal regularization parameter alpha _opt, at each measurement time, it was shown that equal distribution pattern of J ^CAM.

It is the schematic which shows the whole structure of the biomagnetic field measuring apparatus of this embodiment. It is a figure for demonstrating an example of arrangement | positioning with respect to a test subject of a several SQUID magnetometer. It is a block diagram which shows the function structure of a calculating device. It is a figure for demonstrating the current dipole model used by this embodiment. It is a figure which shows an example of a magnetic field current conversion straight line. It is a flowchart which shows the whole operation | movement of the biomagnetic field measuring apparatus in the case of calculating current distribution by converting ^JCAM into an electric current value. It is a flowchart for demonstrating in detail the production | generation process of a magnetic field current conversion straight line. It is a figure which shows an example of the display screen displayed on the display apparatus of a biomagnetic field measuring device. It is a display screen when a CAM image after conversion into a current value is displayed in the CAM display column. It is a flowchart which shows the whole operation ^{| movement} of the biomagnetic field measuring apparatus in the case of calculating electric current distribution as ^JMNMTR . It is a figure which shows an example of the display screen which displays the electric current distribution produced ^| generated based on optimal ^JMNMTR using the biomagnetic field measuring apparatus of this embodiment. In three of the simulation model is a layout view on the xy plane is a z = z _d of the set current dipole J (r '). 'And matching degree _{RE sim} distribution pattern of the ^{J _CAM,} current dipole J (r current dipole J (r)' is a plot simultaneously the coincidence degree _{RE sim} distribution pattern of ^{J MNMTR} with). 'And matching degree _{RE sim} distribution pattern of the ^{J _CAM,} current dipole J (r current dipole J (r)' is a plot simultaneously the coincidence degree _{RE sim} distribution pattern of ^{J MNMTR} with). 'And matching degree _{RE sim} distribution pattern of the ^{J _CAM,} current dipole J (r current dipole J (r)' is a plot simultaneously the coincidence degree _{RE sim} distribution pattern of ^{J MNMTR} with). A current distribution image generated on the basis of the ^{J CAM} and ^{J MNMTR} calculated in model 1. A current distribution image generated on the basis of the ^{J CAM} and ^{J MNMTR} calculated in model 2. A current distribution image generated on the basis of the ^{J CAM} and ^{J MNMTR} calculated in model 3. It is the figure which superimposed the magnetocardiogram waveform of the healthy subject A measured with time by 64 SQUID magnetometers on one trace. a current distribution image generated on the basis of the ^{J CAM} and ^{J MNMTR} calculated in p-wave maximum time. A current distribution image generated on the basis of the ^{J CAM} and ^{J MNMTR} calculated in QRS wave maximum time. A current distribution image generated on the basis of the ^{J CAM} and ^{J MNMTR} calculated in T-wave up time. A ^J CAM ^{-J MNMTR} correlation diagram healthy person A (regularization parameter α = 10 ^-10). A ^J CAM ^{-J MNMTR} correlation diagram for subjects 10 adults (regularization parameter alpha = 10 ^-10). In ^J CAM ^{-J MNMTR} correlation diagram shown in FIG. 24 is a diagram that generated the regression line. It is an adult current source depth-conversion coefficient correlation diagram. FIG. 27 is a diagram in which an infant current source depth-conversion coefficient correlation diagram is superimposed on the adult current source depth-conversion coefficient correlation diagram shown in FIG. 26. A current distribution image generated based ^{J MNMTR} healthy individuals A and (regularization parameter alpha _opt) to the ^{J CAM.}

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Biomagnetic field measuring device 2 Magnetic shield room 3 Cryostat 4 Gantry 5 Bed 6 Drive circuit 7 Amplifier filter unit 8 Arithmetic device 9 Display device 10 Chest wall 11 Measurement area 12 7th row 3rd column corresponding SQUID magnetometer 13 Sacral projection 14 xy plane at z = 0 m 15 measurement point 16 semi-infinite plane conductor 17 xy plane at z = z _d 18, 19, 20 Current dipole 21 Angle definition 25, 33, 44 Current distribution vector 26, 34, 45 Size of current distribution vector Area where the magnitude of current distribution vector is medium 28, 36, 47 area where the magnitude of current distribution vector is small 29 magnetocardiogram waveform 30 p wave maximum time 31 QRS wave maximum time 32 T-wave maximum time 38 regression line 39 J ^CAM paired magnitude maximum value of ^{J MNMTR} It is to plot 40 the regression line 41 current source depth _{z d} a conversion factor and the corresponding is thereby plotted 42 regression line 43 pediatric current source depth _{z d} a conversion factor and the corresponding is thereby plotted 48 display screen 49 a magnetic field waveform display column 50 CAM display field of the 51 Magnetic field waveform display condition input field 52 CAM calculation condition input field 53 CAM display condition input field 54 Current value calculation condition input field 55 Input field for setting time width of displayed magnetic field waveform 56 Input field for setting time width offset 57 Input field for setting amplitude width of displayed magnetic field waveform 58 Input field for setting offset of amplitude width 59 Execute button 60 Cardiac magnetic field waveform 61 Bar 62 Scroll bar 63 Number of CAM images to be calculated (number of maps) Input field to set 64 CAM image to be calculated Input field for setting start time 65 Input field for setting time interval of CAM image to be calculated 66 Execution button 67 Clear button 68 CAM image 69 Approximate current intensity value (J ^CAM size) of displayed CAM image Corresponding color bar 70 Maximum value display of color bar 71 Minimum value display of color bar 72 Input field for setting maximum value display of color map of CAM image 73 Input field for setting minimum value display of color map of CAM image 74 Execution Button 75 Input field for setting the current source depth z _d from the measurement surface of the SQUID magnetometer to the heart 76,77 J Radio for selecting a conversion straight line (standard straight line, individual straight line) used when converting J ^CAM into a current value Button (Calculation selection button)
78 Display button for calculating and displaying the conversion straight line selected by the radio button 79 Execution button 80 Cancel button 81 Data processing unit 82 Control unit 100 Magnetic field current conversion straight line 150 MNMTR display field 152 In vivo current distribution calculation condition input field 154 MNMTR Display condition input field 163 Input field for setting the number of CAM images and MNMTR images to be calculated (number of maps) 164 Input field for setting the start time of CAM images and MNMTR images to be calculated 165 Time interval between CAM images and MNMTR images to be calculated Input field for setting 166 Execute button 167 Clear button 168 MNMTR image 169 Color bar corresponding to current intensity value (J ^MNMTR size) of displayed MNMTR image 168 170 Maximum color bar Value display 171 Minimum value display of color bar 172 Input field for setting maximum value display of color map of MNMTR image 173 Input field for setting minimum value display of color map of MNMTR image 175 From measurement surface of SQUID magnetometer to heart Input field for setting the current source depth z _d 179 Execution button 811 CAM analysis unit (first calculation means)
812 Current source depth estimation unit (third and ninth calculation means)
813 Magnetic field current conversion straight line generation unit 813a Inverse problem analysis unit (fourth and tenth calculation means)
813b Current distribution comparison unit (fourth and tenth calculation means)
813c J ^CAM -J ^MNMTR correlation diagram generating section (second, fifth, sixth, eighth, eleventh, twelfth calculation means)
813d Current source depth-conversion coefficient correlation diagram generation unit (fourteenth and sixteenth calculation means)
814 Current value calculation unit (seventh, thirteenth, fifteenth and seventeenth arithmetic means)
815 Current distribution image generator

Claims (12)

A time variation of a magnetic field component in the z direction perpendicular to the xy plane along the substantially body surface of the biomagnetic field generated from the living body, or a magnetic field component in the x direction parallel to the xy plane along the approximately body surface of the biomagnetic field and measuring a time change of a magnetic field component in the y direction, and a plurality of magnetometers arranged two-dimensionally at coordinate positions of (x, y) coordinates parallel to the body surface of the living body;
A biomagnetic field measurement apparatus comprising: an arithmetic device that calculates the output signals of the plurality of magnetometers; and a display device that displays a result of the calculation,
The said arithmetic unit has at least one of following (1) and (2), The biomagnetic field measuring device characterized by the above-mentioned.
(1) Calculation means for obtaining a change amount in the x direction and a change amount in the y direction of the magnetic field component in the z direction at an arbitrary time point, and a current source in the living body from the plurality of two-dimensional magnetometers determining the current distribution by multiplying arithmetic means for obtaining the conversion factor is determined in accordance with field current converted straight line that corresponds to the current source depth, the conversion factor to the amount of change in the x direction of the change amount and the y direction to the Arithmetic means (2) Arithmetic means for obtaining a conversion coefficient determined according to a magnetic field current conversion line corresponding to a current source depth from the plurality of magnetometers arranged in two dimensions to the current source in the living body, and an arbitrary time point calculating means for calculating the current distribution by multiplying the conversion factor to a magnetic field component and the y-direction of the magnetic field component in the x direction at The following (1) and biomagnetic field measurement apparatus according to claim 1, characterized in that it comprises at least one calculating means out of (2).
(1) The assumed one current source so that a difference between the z-direction magnetic field component at a predetermined time point and a calculated value of the z-direction magnetic field component generated by the assumed one current source is minimized. Means for calculating the current source depth based on the calculation result for estimating the magnitude, direction and position of the current source. (2) Assuming the magnetic field component in the x direction and the magnetic field component in the y direction at a predetermined time point. The size, direction and position of the assumed one current source are estimated so that the difference between the calculated value of the magnetic field component in the x direction and the calculated value of the magnetic field component in the y direction generated by two current sources is minimized. Means for calculating the current source depth based on the calculation result Nuclear magnetic resonance imaging apparatus, or, X-rays CT device, or depth information obtained using the ultrasonic imaging apparatus, according to claim 1, characterized in that it comprises a means for calculating as the current source depth Biomagnetic field measurement device. On the display device, operation selection button for selecting the operation of obtaining the conversion factor is displayed, biomagnetic field measurement according to claim 1, characterized in that the operation corresponding to the operation selection button selected is executed apparatus. The display device in biomagnetic field measurement apparatus according to claim 1, wherein the magnetic field current conversion lines and said conversion factor is characterized in that it is displayed. On the display device, the amount of change in the x direction and the amount of change in the y direction of the magnetic field component in the z direction and the current distribution in the living body, or the magnetic field component in the x direction and the direction of the y direction The biomagnetic field measurement apparatus according to claim 1 , wherein the magnetic field component and the current distribution in the living body are displayed on the same screen. The biomagnetic field measurement apparatus according to claim 2 , wherein a p-wave initial time is used as the predetermined time point. The biomagnetic field measurement apparatus according to claim 2 , wherein a Q wave initial time is used as the predetermined time point. A time variation of a magnetic field component in the z direction perpendicular to the xy plane along the substantially body surface of the biomagnetic field generated from the living body, or a magnetic field component in the x direction parallel to the xy plane along the approximately body surface of the biomagnetic field and measuring a time change of a magnetic field component in the y direction, and a plurality of magnetometers arranged two-dimensionally at coordinate positions of (x, y) coordinates parallel to the body surface of the living body;
A computing device for computing the output signals of the plurality of magnetometers;
A biomagnetic field measurement apparatus comprising a display device for displaying the result of the calculation,
The said arithmetic unit has at least one of following (1) and (2), The biomagnetic field measuring device characterized by the above-mentioned.
(1) first calculation means for obtaining a change amount in the x direction and a change amount in the y direction of the magnetic field component in the z direction at an arbitrary time point;
Second computing means for obtaining a maximum value of the magnitude distribution of the change amount in the x direction and the change amount in the y direction at the arbitrary time point;
As the current source depth from the plurality of magnetometers arranged in two dimensions to the current source in the living body, the magnetic field component in the z direction at a predetermined time and the magnetic field in the z direction generated by one assumed current source. Third calculation means for calculating the current source depth based on a calculation result for estimating the size, direction and position of the assumed one current source so that a difference from the calculated value of the component is minimized; ,
The magnetic field component in the z direction at the arbitrary time point, and the magnetometer position formed by the x component distribution and the y component distribution of the plurality of magnetic field sources at the arbitrary time point assumed on the current source depth. Distribution of the x component and y component of the plurality of assumed magnetic field sources so that the sum of the difference between the calculated value of the magnetic field component in the z direction and the additional term multiplied by the regularization parameter is minimized. A fourth computing means for estimating the distribution;
Fifth arithmetic means for obtaining a maximum value of the distribution of the x component distribution and the y component distribution of the magnetic field source at the arbitrary time point;
The calculation by the first to fifth calculation means is performed at a plurality of time points included in the arbitrary time point, and the maximum value estimated by the second calculation means and the fifth calculation means are estimated. A sixth calculating means for calculating the slope of the regression line obtained from the maximum value;
Seventh computing means for obtaining a current distribution by multiplying the amount of change in the x direction and the amount of change in the y direction by the conversion factor, using the slope of the regression line as a conversion factor. (2) The x at any point in time An eighth computing means for obtaining a maximum value of the magnitude distribution of the magnetic field component in the direction and the magnitude of the magnetic field component in the y direction;
As the current source depth from the plurality of magnetometers arranged in two dimensions to the current source in the living body, the x-direction magnetic field component and the y-direction magnetic field component at a predetermined time point and one assumed current An operation for estimating the size, direction and position of the assumed one current source so that the difference between the calculated value of the magnetic field component in the x direction and the calculated value of the magnetic field component in the y direction generated by the source is minimized. Ninth calculation means for calculating the current source depth based on the result;
The x-direction magnetic field component and the y-direction magnetic field component at the arbitrary time point, and the x component distribution and the y component distribution of the plurality of magnetic field sources at the arbitrary time point assumed on the current source depth. The sum of the difference between the calculated value of the magnetic field component in the x direction and the calculated value of the magnetic field component in the y direction at the magnetometer position and the additional term multiplied by the regularization parameter is minimized. A tenth computing means for estimating a distribution of x components and a distribution of y components of the plurality of assumed magnetic field sources;
Eleventh computing means for obtaining a maximum value of the distribution of the x-component distribution and the y-component distribution of the magnetic field source at the arbitrary time point;
The calculation by the eighth to eleventh calculation means is performed at a plurality of time points included in the arbitrary time point, and the maximum value estimated by the eighth calculation means and the eleventh calculation means are estimated. A twelfth computing means for calculating the slope of the regression line obtained from the maximum value;
A thirteenth calculation means for obtaining a current distribution by multiplying the magnetic field component in the x direction and the magnetic field component in the y direction by the conversion coefficient, using the slope of the regression line as the conversion coefficient. The biomagnetic field measurement apparatus according to claim 9 , further comprising at least one computing means of the following (1) and (2).
(1) Fourteenth calculation for performing calculation by the sixth calculation means for a plurality of subjects, and calculating a regression line obtained from the current source depth and the slope of the regression line for each subject as a magnetic field current conversion line Means,
Fifteenth calculation means for determining a current distribution by determining a conversion coefficient from the magnetic field current conversion line and multiplying the change amount in the x direction and the change amount in the y direction by the conversion coefficient (2) The twelfth calculation Sixteenth calculation means for performing calculation by means for a plurality of subjects, and calculating a regression line obtained from the current source depth for each subject and the slope of the regression line as a magnetic field current conversion line;
Seventeenth calculating means for determining a current coefficient by determining a conversion coefficient from the magnetic field current conversion coefficient and multiplying the magnetic field component in the x direction and the magnetic field component in the y direction by the conversion coefficient A time variation of a magnetic field component in the z direction perpendicular to the xy plane along the substantially body surface of the biomagnetic field generated from the living body, or a magnetic field component in the x direction parallel to the xy plane along the approximately body surface of the biomagnetic field and measuring a time change of a magnetic field component in the y direction, and a plurality of magnetometers arranged two-dimensionally at coordinate positions of (x, y) coordinates parallel to the body surface of the living body;
A computing device for computing the output signals of the plurality of magnetometers;
A biomagnetic field measurement apparatus comprising a display device for displaying the result of the calculation,
The said arithmetic unit has at least one of following (1) and (2), The biomagnetic field measuring device characterized by the above-mentioned.
(1) Calculation means for obtaining a change amount in the x direction and a change amount in the y direction of the magnetic field component in the z direction at an arbitrary time point;
The sum of the difference between the z-direction magnetic field component and the calculated value of the z-direction magnetic field component generated by a plurality of assumed magnetic field source distributions and the additional term multiplied by the regularization parameter is minimized. A calculation means for the inverse biomagnetic field problem for estimating the size and direction of the plurality of assumed magnetic field sources;
Means for calculating, as the regularization parameter, a regularization parameter that minimizes the difference between the amount of change in the x direction and the amount of change in the y direction and the distributions of the plurality of assumed magnetic field sources as the regularization parameter (2 ) Calculated values of the x-direction magnetic field component and the y-direction magnetic field component generated by the distribution of a plurality of assumed magnetic field sources and the x-direction magnetic field component and the y-direction magnetic field component at arbitrary points in time. And a biomagnetic field inverse problem computing means for estimating the sizes and directions of the plurality of assumed magnetic field sources so that the sum of the difference between and the additional term multiplied by the regularization parameter is minimized,
Means for calculating, as the regularization parameter, a regularization parameter that minimizes a difference between the magnetic field component in the x direction and the magnetic field component in the y direction and the distribution of the plurality of assumed magnetic field sources as the regularization parameter. In the display device, the change amount in the x direction and the change amount in the y direction at the arbitrary time point, or the magnetic field component in the x direction and the magnetic field component in the y direction, and the distribution of the plurality of magnetic field sources The biomagnetic field measurement apparatus according to claim 11 , wherein is displayed on the same screen.

Images