JP5469574B2 - Electrical impedance tomography measuring device. - Google Patents

Description

  The present invention relates to a living body electrical impedance tomographic image measuring apparatus that measures and displays electrical characteristic values related to a tissue in a cross section of a living body.

  Conventionally, an electrical impedance CT called EIT (Electrical Impedance Tomography) is known. This device, for example, applies eight electrocardiogram electrodes horizontally and at equal intervals to the surface of a living body of the chest, for example. By applying a weak constant current, the volume of ventilation due to respiration inside the body is determined from the potential distribution generated on the body surface. The electrical impedance resulting from the change is estimated and a tomographic image is obtained.

  This EIT is only non-invasive because it only sticks electrodes, the device is small, the device is small, portable, no special techniques are required for measurement, and real-time images can be obtained. There is an advantage that measurement can be performed for a long time.

  Furthermore, as an application using EIT, attempts have been widely made to measure, for example, pulmonary blood flow non-invasively and in real time by measuring changes in blood-derived electrical impedance.

  However, for example, when an electrical impedance change derived from blood flow in the trunk is to be measured, the electrical impedance change derived from blood flow is as small as about 1/10 of the electrical impedance change derived from respiration. It is not easy to measure.

  As a method of measuring changes in electrical impedance derived from blood flow using EIT, by extracting a component synchronized with the heartbeat from the impedance measured by EIT or reducing the noise of the device, electrical impedance derived from blood flow A method for improving the measurement accuracy (see Patent Document 1) is known, but accuracy sufficient for practical use has not been obtained.

  A method of injecting physiological saline into blood vessels to extremely reduce impedance and measuring blood flow has also been proposed, but not only is it time-consuming, but the effect is extremely short. Is not suitable.

  When measuring electrical impedance derived from blood flow in trunk organs such as the lung using EIT, changes in body shape such as thorax due to breathing directly affect changes in electrical impedance. Although it is possible to improve the measurement accuracy of electrical impedance derived from a minute blood flow, it is difficult to always continuously monitor the absolute value of the gas amount of the entire lung field with a conventional device.

  On the other hand, in recent years, EIT has been developed to obtain the absolute value of the electrical impedance, and it is now possible to continuously monitor the absolute value of the gas amount of the entire lung field continuously.

  For example, it is known that an impedance distribution in a region of interest is generated by generating a least square error between a predicted boundary voltage and an actually measured boundary voltage, and converged by an iterative process to obtain an absolute value of electrical impedance. (See Patent Document 2). However, EIT by the above method requires calibration using another device, and the obtained electrical impedance cannot uniquely obtain the absolute value of the electrical impedance from the actually measured value. That is, there is a problem in accuracy that the absolute value of the electrical impedance obtained above is only one of several correct answers, and the electrical impedance of the blood flow calculated by removing the influence of respiration by this method Cannot be practically accurate.

  In addition, EIT is also known in which absolute electrical impedance is estimated as an average value of an entire predetermined organ, and this is added to local relative impedance as a reference value to calculate local absolute impedance. Since the local reference value of the organ is largely different from the average value for the whole organ, the reliability of the obtained local absolute impedance is low, and the blood flow calculated by removing the influence of respiration by this method Also, the electrical impedance cannot be practically accurate.

JP 05-507864 A Special table 2003-534867 gazette

  The present invention has been made in view of the current state of the living body electrical impedance tomogram measuring apparatus as described above, and its purpose is to accurately remove the influence of respiration and to obtain a local absolute derived from highly accurate blood flow. It is an object to provide a biological electrical impedance tomogram measuring apparatus capable of obtaining an electrical impedance.

The electrical impedance tomographic image measuring apparatus according to the present invention divides the biological section based on the position of the organ or tissue of the living body and the electrical characteristics thereof, and changes the electrical characteristic value of each mesh to a plurality (n). A predetermined position on the surface of the living body, including a mathematical model creation means for creating a mathematical model of three or more dimensions that can be calculated in advance, and an input pair electrode for applying a constant current and an output pair electrode for detecting a potential difference A plurality of electrodes attached so as to surround, a constant current applying means for applying a constant current to the input pair electrodes, and changing the electrical characteristic value of an arbitrary mesh to a plurality (n) using the mathematical model Dmodel calculating means for calculating a plurality (n) of first potential differences (Dmodel) generated in the output pair electrodes when a constant current is applied to the input pair electrodes; Measuring means for measuring a second potential difference (Dmean (t)) generated at the output pair electrode when a constant current is applied to the output pair, and separating the second potential difference into a respiratory-derived component and a heartbeat-derived component , Respiratory heart rate separation means, respiratory state detection means for detecting a predetermined respiratory state from the respiratory-derived component of the second potential difference separated by the respiratory heart rate separation means, and heart rate state detection means for detecting a predetermined heart rate state A first extraction means for extracting a plurality of second potential differences in a predetermined respiratory state detected by the respiratory state detection means from the heartbeat-derived component; and a predetermined heartbeat detected by the heartbeat state detection means A second extraction means for synchronously adding a plurality of second potential differences extracted by the first extraction means based on the state to extract a second potential difference from which a respiratory-derived component has been removed; and the call EIT (n) calculating means for calculating a plurality (n) blood flow-derived electrical characteristic values corresponding to each pixel using the second potential difference from which the derived component is removed, and the plurality (n) of blood A determination means for determining an electrical characteristic value derived from an optimal blood flow in each pixel from an electrical characteristic value derived from the flow, and a blood flow for displaying a tomographic image based on the electrical characteristic value derived from the optimal blood flow in each pixel And a tomographic image display control means.

  In the electrical impedance tomographic image measuring apparatus according to the present invention, the electrical characteristic value derived from the blood flow is one or more of resistivity, conductivity, dielectric constant, and permeability. And

  In the electrical impedance tomographic image measuring apparatus according to the present invention, the optimum electrical characteristics are obtained by squaring a plurality of (n) electrical characteristic values corresponding to the respective pixels calculated by the Dmodel calculating means, or having the smallest absolute value. Characteristic value is determined.

  In the electrical impedance tomographic image measuring apparatus according to the present invention, the respiratory state detecting means detects a predetermined respiratory state using a respiratory-derived component separated by the respiratory heartbeat separating means from the second potential difference. To do.

  The electrical impedance tomographic image measuring apparatus according to the present invention has an electrocardiogram detection means for detecting electrocardiogram data, and detecting the predetermined heartbeat state detects an R wave from the electrocardiogram data.

  In the electrical impedance tomographic image measuring apparatus according to the present invention, detecting the predetermined respiratory state detects a predetermined gas amount.

  The electrical impedance tomographic image measuring apparatus according to the present invention has electrocardiogram detection means for detecting electrocardiogram data, and the second extraction means performs synchronous addition at the timing of the R wave of the electrocardiogram data.

  In the electrical impedance tomographic image measuring apparatus according to the present invention, the Dmodel calculating means calculates the first potential difference using a predetermined electrical characteristic value of the tissue in the living body.

  According to the electrical impedance tomographic image measuring apparatus according to the present invention, a predetermined respiratory state and a predetermined heartbeat state are detected, and synchronous addition is performed, thereby accurately removing the influence of respiration and the blood-derived electrical characteristics. The local absolute value of the value can be obtained with high accuracy. In particular, fluid such as blood flow can be continuously monitored with high accuracy without being affected by changes in the body shape such as the thorax due to respiration.

  According to the electrical impedance tomography measurement apparatus of the present invention, for example, by monitoring the ventilation of the lung field and the change in the absolute value of the blood flow at the same time, the ventilation is bad or the blood flow is bad when oxygenation is bad. It becomes clear at a glance and it becomes possible to select an appropriate treatment policy.

Conventionally, in patients with pulmonary embolism, although it has been known that SpO ₂ has rapidly decreased, it has been difficult to specify that the cause is pulmonary embolism. With the device, pulmonary embolism can also be quickly identified, and treatments such as suction with a catheter and administration of a thrombolytic agent can be performed quickly.

  In addition, blood flow in organs such as the kidney and heart can be monitored, so that the efficacy of medication can be confirmed in real time, and parameters such as cardiac output can be measured non-invasively from the absolute value of electrical characteristics. It is also possible to do.

1 is a block diagram showing a configuration of an electrical impedance tomographic image measurement apparatus according to the present invention. The perspective view which shows the electrode arrangement | positioning in EIT in this invention, and the relationship of a slice. The figure which shows the cross-sectional image which divided | segmented the structure | tissue in the process which creates a chest FEM model based on an X-ray CT image in this invention. The figure which shows the cross-sectional image for electrode arrangement | positioning in the process of producing a chest FEM model based on an X-ray CT image in the present invention. Sectional drawing which shows the chest FEM model created based on the X-ray CT image in this invention. The figure which shows the result of the electrical potential difference obtained by simulation of the healthy subject model in this invention. The figure which shows an example of the regression curve created using the result of the electrical potential difference obtained by simulation of the healthy subject model in this invention. The figure which shows an example of the regression curve created using the result of the electrical potential difference obtained by simulation of the healthy subject model in this invention. The figure which shows the result of the current density distribution obtained by simulation of the healthy subject model in this invention. The figure for demonstrating the process of removing the influence of respiration by the electrical impedance tomogram measuring device which concerns on embodiment of this invention. It is a figure which shows the time-dependent change of the lung resistance of a healthy person, (a) is a figure which shows the thing of a natural breath state, (b) is a figure which shows the thing of an apnea state. (A) shows the several 2nd potential difference derived from the heartbeat extracted by the 1st extraction means from the potential difference obtained from each output pair electrode by the electrical impedance tomogram measuring device which concerns on embodiment of this invention. It is a figure, (b) is a figure which shows the result of having synchronously added the potential difference of (a). The figure which shows the curve which calculates | requires the resistivity as an optimal electrical property value for every pixel of a lung field by this invention. The flowchart which shows operation | movement of the electrical impedance tomogram measuring apparatus which concerns on this invention. The flowchart which shows operation | movement of the electrical impedance tomogram measuring apparatus which concerns on this invention. It is a figure which shows the waveform processed by the electrical impedance tomogram measuring apparatus which concerns on this invention, (a) is electrocardiogram data DECG (t), (b) is a process of differentiation etc. to (a). (C) is a potential difference matrix Dmean (t) measured by a certain input electrode pair and output electrode pair, and (d) shows a respiratory heartbeat separation from the potential difference matrix Dmean (t). The heartbeat-derived component separated by the means 38 is shown, and the respiratory-derived component is shown in (e). The figure which shows the image which displayed the optimal electrical characteristic value of the blood flow, and its time-dependent change in real time using the color previously set according to the electrical characteristic value by the electrical impedance tomogram measuring apparatus which concerns on this invention. .

  Embodiments of a bioelectrical impedance tomographic image measurement apparatus according to the present invention will be described below with reference to the accompanying drawings. In each figure, the same components are denoted by the same reference numerals, and redundant description is omitted. FIG. 1 is a configuration diagram showing an embodiment of a biological electrical impedance tomogram measuring apparatus according to the present invention. This apparatus includes an electrode unit 10 and an electrode control unit 20 that constitute a potential difference detection unit, and the electrode control unit 20 is connected to a computer system 30.

  The computer system 30 includes a main unit 31 including a CPU, a main storage unit, an external storage unit, and the like, a display unit 32 including LEDs connected to the main unit 31, and an input unit 33 including a keyboard and a mouse. And. The main body 31 is provided with software as mathematical model creation means 34 for creating a mathematical model of three or more dimensions such as FEM (finite element method).

  Taking a three-dimensional chest FEM model as an example, referring to an X-ray CT image of one healthy male, the CT image is divided into regions for each tissue as shown in FIG. The model creating means 34 holds the model. A database having the contents of Table 1 showing the correspondence between each organization, number, and resistivity is provided so that the association can be performed. The region dividing process is performed on, for example, 234 CT images having a 1.3 mm slice width (from the clavicle to the upper kidney).

  Next, each electrode (for example, 6.5 mm in length and 5 mm in width) including the electrodes 11-1 to 11-8 in the electrode unit 10 of FIG. 1 is set for the three-dimensional chest FEM model. Specifically, as shown in FIG. 4, eight slices l of equal angles from the center are drawn on the slice image, 5 mm wide electrodes are plotted on the surface of the living body, and for example, a predetermined number of 1.3 mm slice width CT images are overlaid. It corresponds to the vertical dimension of the electrode.

  As an example, FIG. 5 shows a plan view of a three-dimensional chest FEM model having 2,660960 elements and 527,571 nodes. In FIG. 5, the back side perpendicular to the paper surface is the head, and as is clear from the position of the spinal cord 51, the upper side of FIG. 5 is the abdomen side and the lower side is the back side. A heart 52, right lung 53, and left lung 54 are shown as main organs. In FIG. 5, 16 electrodes D are set on one slice plane. However, this is for the case where it is necessary to obtain EIT data by changing the electrode position as in a midline incision patient. .

  Next, with respect to the constructed three-dimensional chest FEM model, the input pair electrodes (for example, 11-1 & 11-2) of the electrodes 11-1 to 11-8 have a predetermined frequency using the Dmodel calculation means 35. When the constant current is applied, the (first) potential difference output from the output pair electrode (the combination of electrodes 11-1 to 11-8) different from the input pair electrode is changed, and the lung field resistivity is changed. And simulate.

  Next, the input pair electrode is changed to another pair (for example, 11-2 & 11-3), and the potential difference is similarly simulated. Similarly, the potential difference is similarly simulated for all the pairs of the electrodes 11-1 to 11-8 as input pair electrodes sequentially. In the case where electrodes other than the electrodes 11-1 to 11-8 are arranged in other slices, the potential difference is similarly simulated.

  Although there are individual differences in lung resistance, the normal lungs are usually 5 Ωm or more, and in lungs with pneumonia, it is often 3 Ωm or less. For example, the lung resistivity is between 5 and 16.7 Ωm. A simulation in which a constant current of 1 mA is applied to the input pair electrodes of the electrodes D1 to D8 will be described with reference to Fig. 5 in 8 steps (5, 5.55, 6.25, 7.14, 8.33, 10, 12.5, 16.7 Ωm). In addition, in order to use electrical conductivity in actual simulation, the conversion table of the said resistivity and electrical conductivity is shown in Table 2.

  In the electrodes D1 to D8 in FIG. 5, the input pair electrodes are taken in the vertical direction, the output pair electrodes are taken in the horizontal direction, and the potential difference obtained from the output pair electrodes is shown in a table with the lung resistivity being 16.7 Ωm. It becomes 6 streets. Detection with the same input / output pair is inaccurate, so it was set to zero. In addition, the potential difference when the output pair electrode includes one of the input pair electrodes seems to be inaccurate. This matrix shown in FIG. 6 can be obtained by calculating for each resistivity (in the above example, 8 levels), and is detected from the resistivity set for the target tissue by the Dmodel calculation means 35 and the output pair electrode. Correspondence database 36 (FIG. 1) of potential differences to be performed is configured.

  Since there are 40 potential difference data excluding cases that seem to be inappropriate as described above, a regression curve is calculated from 8 potential differences with respect to 8 resistivity (conductivity) set for each, and the resistivity is substantially multi-stepped. It is possible to simulate the potential difference when changing.

As an example, FIG. 7 shows a regression curve created by the potential difference obtained from the output pair electrodes of the electrodes D3 and D4, with the electrodes D1 and D2 as input pair electrodes. FIG. 8 shows a regression curve created by the potential difference obtained from the output pair electrodes of the electrodes D4 and D5, with the electrodes D2 and D3 as input pair electrodes. Each figure shows the contribution ratio R ² , which was 0.99 or more, and a high correlation was obtained. Instead of calculating the above regression curve, the resistivity may be finely changed in multiple stages.

  FIG. 9 shows an example of the current distribution obtained in the above simulation. A portion with high luminance is a portion with high current density, which indicates that a large amount of current flows. In FIG. 9, the current density is high in the upper left part because the electrodes D1 and D2 are input pair electrodes. Further, it can be seen that since the lung has high resistance, a large amount of current does not flow, and a large amount of current concentrates on the low resistance heart, blood vessels and fats existing around the lung, and the like.

  Here, the size and electrical characteristic value of the heart are periodically changed due to contraction and expansion, and the change amount of the electrical characteristic value is larger than the change due to the amount of gas in the lung field due to respiration. Therefore, for example, when the heart is relatively large compared to the lung, such as in children, or when higher accuracy is required, a mathematical model that can periodically change the size and electrical characteristics of the heart is used. By calculating a more precise Dmodel having time information, it is possible to estimate a more accurate electrical characteristic value derived from blood flow.

  Next, the measuring means 22 will be described. The electrode unit 10 includes, for example, eight electrodes 11-1 to 11-8 and is attached so as to surround the surface of the living body. Here, the surface of the living body can be the surface of a required part such as the head, torso, limbs, etc., but here the subject is the chest and there is a change in the amount of gas in the lungs and the body shape such as the rib cage due to breathing 2 illustrates measurement of pulmonary blood flow. The electrodes 11-1 to 11-8 are attached to the living body at equal intervals. The electrodes 11-1 to 11-8 may be arranged in a plurality of slices as shown in FIG.

  Each electrode including the electrodes 11-1 to 11-8 is connected to the electrode control unit 20 via a lead wire. The electrode control unit may be arranged directly on each electrode without using a lead wire. The electrode control unit 20 includes a constant current applying unit 21 and a measuring unit 22. The constant current applying unit 21 and the measuring unit 22 operate in synchronization with the same clock.

  Depending on the purpose, the frequency of the constant current applied to the constant current applying means 21 is several tens of kHz to several hundred kHz, and one or more of high frequencies (for example, several MHz or more) that go straight through the cell wall. Use in combination. For example, the constant current applying unit 21 may be any one of the input pair electrodes (for example, 11) of the electrodes 11-1 to 11-8, taking the slice plane including the electrodes 11-1 to 11-8 shown in the example of FIG. -1 & 11-2).

  At this time, the measuring means 22 takes in the (second) potential difference observed at the output pair electrode obtained by combining two of the electrodes 11-1 to 11-8, digitizes it, and sends it to the computer system 30. At this time, if the output pair electrodes are limited to two adjacent ones, there are eight output pair electrodes, but output pair electrodes (11-1 & 11-2, 11-1 & 11-8) including one or both of the input pair electrodes. , 11-2 & 11-3) are not adopted because they are inaccurate.

  Next, the input pair electrodes are changed to different pairs (for example, 11-2 & 11-3), and the potential difference is similarly obtained. Similarly, in one sequence, among the electrodes 11-1 to 11-8, a preset pair is sequentially switched as an input pair electrode, and the potential difference of the output pair electrode is measured based on the above-described procedure. The measured potential difference matrix thus obtained in one sequence is defined as Dmean (t). The potential difference measurement is similarly performed on slices measured by electrodes other than the electrodes 11-1 to 11-8.

  Here, the frequency of the constant current applied to the constant current applying means 21 is not directly applied with a high frequency constant current exceeding 1 MHz, but a plurality of low frequency constant currents are applied, and the correcting means 46 of FIG. It is also possible to correct the potential difference observed when a higher frequency constant current is applied. Based on the Cole-Cole equation, the correction means 46 sweeps the frequency and plots it on a plane, and estimates the potential difference at a high frequency using curves measured at a plurality of low frequencies.

Further, the respiratory heartbeat separation means 38 provided in the main body 31 separates the respiratory-derived component Dmean (t) _R and the heartbeat-derived component Dmean (t) _C from the potential difference matrix Dmean (t). Specifically, a method of setting a cutoff frequency of about 0.5 to 1 Hz, and extracting a respiratory-derived component Dmean (t) _R by a low-pass filter and a heartbeat-derived component Dmean (t) _C by a high-pass filter, respectively. Etc. Note that the cut-off frequency can be automatically changed by actually measuring respiration with EIT. FIG. 16 (c) shows a potential difference matrix Dmean (t) measured by a certain input electrode pair and output electrode pair. FIG. 16 (d) shows a heartbeat-derived component separated therefrom by the respiratory heartbeat separating means 38, and FIG. As shown in FIG.

FIG. 11A shows the change in electrical impedance obtained during natural breathing, and it can be seen that the electrical impedance change derived from heartbeat is superimposed on the electrical impedance change derived from respiration. FIG. 11 (b) shows a similar change in electrical impedance in the apnea state. Since there is no change in the amount of gas in the lungs due to breathing and no change in the rib cage shape, It can be seen that the influence is removed, and only the change in the electrical impedance derived from the heartbeat is extracted. On the contrary, when the gas amount of the entire lung field is the same, the body shape of the trunk such as the thorax is considered to be almost the same shape. Therefore, the respiratory state detection means 39 uses the respiratory component Dmean (t) _R. A state in which the lung gas amount is within a predetermined range is detected by estimating a change in the gas amount of the entire lung field.

The EIT (n) calculating means 37 of the main body 31 includes a potential difference matrix Dmean (t) _R obtained by extracting a respiratory component from the measured potential difference, and a plurality of (n) resistivity values that are simulation results stored in the database 36. A potential difference matrix Dmodel (n) for a pixel and a weighting correction coefficient known as a sensitivity matrix based on sensitivity theory or a Jacobian matrix, and a plurality of electrical characteristic values such as resistivity for each pixel (n )calculate. Here, correction coefficients such as a sensitivity matrix can be calculated by a known method and stored as the database 36. In addition, n is the number of the set lung resistivity. In this example, eight types are used as shown in Table 2, but 300 types are calculated in advance in increments of 0.2 Ωm. It is good.

When using a sensitivity matrix that has been widely adopted in recent years in EIT, each element of Dmean (t) _R and each element of Dmodel (n) are compared by division, and the sensitivity matrix is multiplied to weight each element. Thus, the corrected value EIT (n) can be calculated for each pixel.

For each pixel, n in a state where there is no difference between Dmean (t) _R and Dmodel (n), that is, n at which the rate of change is zero is the resistivity to be finally obtained. When the EIT (n) corrected by multiplying by n is n, the resistivity to be finally obtained is obtained. The determining means 43 can also determine the resistivity to be finally obtained when EIT (n) converges to zero by iterative calculation, or set n discretely to determine the absolute value of EIT (n), or It is also possible to determine the resistivity (the optimum value in FIG. 13) to be finally obtained when [EIT (n)] ² that changes as shown in FIG. If there are other slices, the same processing is performed for the other slices. The process executed to estimate the resistivity as the optimum electrical characteristic value by the EIT (n) calculation means 37 and the determination means 43 described so far is referred to as the optimum electrical characteristic value estimation process. .

Since the optimal electrical characteristic value estimated in this way is an absolute value, the optimal electrical characteristic value of each pixel corresponds to the local gas amount of the corresponding lung field on a one-to-one basis. The total amount of gas is the total lung field. Respiratory state detection means 39 performs the same procedure on Dmean (t) buffered within a predetermined time (t _{1 to} t ₂ ), and calculates the gas amount of the entire lung field as shown by F in FIG. The time change is calculated, and the amount of gas as indicated by L in FIG. 10 from time t ₁ to t ₂ is within a predetermined value or range, that is, the amount of gas in the lung that changes with breathing And the chest and the like are detected as a predetermined respiratory state. Note that the respiratory condition detection means is pseudo in the state where there is no significant change in the pathological condition and the functional residual capacity (FRC), residual capacity (RV), and total lung capacity (TLC) are hardly changed. It is also possible to substitute a set value of a parameter relating to respiration such as a ventilator and an instantaneous value such as a flow sensor, or a device such as a flow sensor alone.

The first extraction means 41 provided in the main body 31 extracts a plurality of second potential differences derived from the heartbeat in the predetermined respiratory state detected by the respiratory state detection means. First, the first extraction unit 41 extracts data when the predetermined respiratory state is detected by the respiratory state detection unit 39 from the potential difference matrix Dmean (t) _C, and the body shape such as the lung gas amount and the thorax is extracted. It is assumed that the potential difference matrix Dmean (t) _{C_RSSync} is the same, that is, without the influence of respiration. Here, an example of the predetermined breathing state is that the gas amount including the ventilation amount is within a predetermined range.

The heartbeat state detection means 40 provided in the main body 31 is separately measured by two of the electrodes of the electrode group provided in the electrode unit 10 and the GND electrode, and buffered in the computer system 30 as shown in FIG. ) Heartbeat synchronization information within a predetermined time (t _{1 to} t ₂ ) is detected from the electrocardiogram data DECG (t) as shown in FIG. Specifically, the ECG data DECG (t) in FIG. 16A is subjected to processing such as differentiation, a plurality of R waves indicated by circles in FIG. 16B are detected, and the time t _R at each R wave is detected. Is converted from t to T so that T = 0 and the RR interval until the next R wave becomes T _RR . the average value _{T RR_mean} of t ₁ ~t ₂ of RR intervals, may be treated to convert equal time interval data.

As long as the electrocardiogram data DECG (t) can be synchronized with the actually measured potential difference matrix Dmean (t) _C , various sensors such as an electrocardiogram signal from an external ECG and a pulse oximeter may be used. Dmean (t) A potential difference signal measured from a predetermined input & main power pair electrode from _C is extracted by a filtering process or the like, or is measured separately for each Dmean (t) measurement sequence using a specific input & main power pair electrode But you can.

The second extraction means 42 _converts the time t of Dmean (t) _{C_RSSync} to T, synchronously adds a plurality of Dmean (T) _{C_RSSync} shown in FIG. A second potential difference based on the heartbeat timing is extracted. That is, the second extraction means 42 performs addition processing on a plurality of Dmean (T) _{C_RSSync} shown in FIG. 12A obtained by converting the time t of Dmean (t) _{C_RSSync} to T, and FIG. The potential difference matrix Dmean (T) _{C_Sync} for one heartbeat cycle shown in b) is extracted. The Dmean (T) _{C_RSsync} to be added may be data from a time T = 0 to a predetermined time such as _{TRR_mean} , or instead of performing processing for the predetermined time t _{1 to} t ₂ , breathing or A method of detecting a heartbeat a predetermined number of times may be used. Moreover, the detection of the predetermined respiratory state in the first extraction means 41 and the detection of the predetermined heartbeat timing in the second extraction means 42 may be mutually replaced. Here, it is desirable to perform synchronous addition at the timing of the R wave.

The above addition processing includes simple addition processing, addition averaging processing, weighted addition processing, and the like. In addition, in order to obtain the potential difference matrix Dmean (T) _{C_Sync} for one cycle of the heart rate with less addition at high speed, template matching or spline interpolation processing may be performed.

The EIT (n) calculating means 37 is a potential difference matrix Dmodel (n) for the potential difference matrix Dmean (t) _{C_Sync} from which the respiratory-derived component has been removed and a plurality of (n) resistivities stored in the database 36. ) And a weighting correction coefficient known as sensitivity matrix based on sensitivity theory or Jacobian matrix, a plurality (n) of electrical characteristic values such as resistivity of each pixel are calculated. Here, correction coefficients such as a sensitivity matrix can be calculated by a known method and stored as the database 36. In addition, n is the number of the set lung resistivity. In this example, eight types are used as shown in Table 2 and the like, but actually, about 300 types in 0.2Ωm increments are obtained as the database 36. Also good.

When a sensitivity matrix widely used in EIT in recent years is used, each element of Dmean (t) _{C_Sync} is divided and compared by each element of Dmodel, and further, the sensitivity matrix is multiplied to weight each element. The corrected value EIT (n) can be calculated for each pixel.

For each pixel, n is a state in which there is no difference between Dmean (t) _{C_Sync} and Dmodel (n), that is, the resistivity to be finally obtained when the change rate is n. When the EIT (n) corrected by multiplying by n is n, the resistivity to be finally obtained is obtained. The determining means 43 can also determine the resistivity to be finally obtained when EIT (n) converges to zero by iterative calculation, or set n discretely to determine the absolute value of EIT (n), or It is also possible to determine the resistivity (the optimum value in FIG. 13) to be finally obtained when [EIT (n)] ² that changes as shown in FIG. If there are other slices, the same processing is performed for the other slices. The process executed to determine the resistivity as the optimum electrical characteristic value by the EIT (n) calculation means 37 and the determination means 43 described so far is referred to as the determination process of the optimum electrical characteristic value of the blood flow. And

  The blood flow tomographic image display control means 44 of the main body 31 uses the color set in advance according to the electrical characteristic value for the optimal electrical characteristic value of the blood flow estimated in this way for each pixel in real time. Is displayed. FIG. 17 shows an example, and the optimal electrical characteristic value of the blood flow is an absolute value. For example, the optimal electrical characteristic value of the blood flow measured for the lung field is the lung field corresponding to each pixel. One-to-one correspondence with local blood flow. That is, the tomographic image of the same part displayed by the blood flow tomographic image display control means 44 can objectively determine the state of the local blood flow in the lung field based on the same reference. In particular, the left figure of FIG. 17 shows the change of the tomographic image every 1/25 seconds over time. With the image in FIG. 17, it is possible to grasp that the blood flow flowing in the lung field flows from the side close to the heart without being affected by changes in the rib cage or the like.

  The region selecting unit 45 of the main body 31 selects a predetermined region such as a site suspected of a pathological condition from the tomographic image generated by the blood flow tomographic image display control unit 44, and more accurate optimal electrical characteristics of the blood flow. Estimate the value. That is, when the lung is the target tissue, a desired model region is selected as appropriate, such as the entire lung, right lung, left lung, right front, right rear, left front, left rear, pixel unit, etc., and a mathematical model creation means corresponding to the selected region By changing the electrical characteristic value of the mesh of the mathematical model created by step 34 more than n, it becomes possible to estimate the electrical characteristic value of the blood flow in a predetermined region more accurately.

  To summarize the above description, the electrical impedance tomographic image measurement apparatus according to the present embodiment operates as shown in the flowcharts of FIGS. That is, as described with reference to FIG. 3, a mathematical model of a living body is created (S11), electrodes are placed on the mathematical model (S12), and it is detected whether a region is selected in the target organ ( (S19B) Since it is not initially selected, the process branches to NO, and the electrical characteristic value of the target organ is set in n ways (S13A).

  Next, for n electrical characteristic values, a simulation is performed in which an input pair electrode is determined, a potential difference is detected from the output pair electrode, and the input pair electrode is sequentially shifted so that all adjacent electrode pairs are input pair electrodes. Execute (S14). Using the simulation result, a potential difference matrix Dmodel (n) as shown in FIG. 6 showing the relationship between the potential difference between the electrodes and the change in the electrical characteristic value is obtained (S15). This may be stored in the database 36 as described above.

Next, the potential difference is measured using the electrode unit 10 and the electrode control unit 20 to obtain a potential difference matrix Dmean (t) (S16). Here, when the frequency of the constant current applied at the time of actual measurement is low, the potential difference Dmean (t) obtained when applied at a frequency higher than the constant current actually used is corrected by the Cole-Cole equation (S16A). . Further, Dmean (t) is separated into a respiratory component (Dmean (t) _R ) and a heartbeat component (Dmean (t) _C ) (S17).

Based on the potential difference matrix Dmean (t) _R obtained in this way, and the weighting coefficients such as the potential difference matrix Dmodel and the sensitivity matrix S of the simulation result, EIT (n) in each pixel is calculated (S18).

For each pixel, the absolute value of EIT (n) or the resistance at n when [EIT (n)] ² is minimum, that is, there is no difference between Dmean (t) _{C_Sync} and Dmodel (n). The rate is obtained, and the absolute optimum electrical characteristic value derived from respiration is determined (S19).

From the absolute optimum electrical characteristic value derived from respiration, a predetermined respiration state where the ventilation volume is in a certain range is detected (S20), and Dmean (t) _{C_RSSync} in the predetermined respiration state is extracted (S21).

On the other hand, ECG data is collected in step S22, or one heartbeat period (from R wave to next R wave etc.) is sequentially detected from Dmean (t) _C obtained in step S17 (S23).
Step S21 receives the processing of a step _S23, extracts the components synchronizing from _{Dmean (t) C_RSync} in each period of the heartbeat, determine the synchronous addition to _{Dmean (t) C_Sync (S24)} .

Furthermore, EIT (n) in each pixel is calculated based on Dmean (t) _{C_Sync} and weighting coefficients such as the potential difference matrix Dmodel and the sensitivity matrix S of the simulation result (S25). The absolute value or square value of EIT (n) is compared, and the electrical characteristic value in the case of n, which is the minimum value, is finally determined as the optimum electrical characteristic value for the pixel unit (S26). Are converted into luminance and displayed as a tomographic image (S27). Thereafter, the process returns to step S19B to perform the process. However, when the selection is detected, the process branches to YES in S19B. In order to measure the selected region in detail, a plurality of (n) The electrical characteristic value of the selected region is set to a plurality (n) or more (S13B), and the process proceeds to step S14 to perform the subsequent processing.

  According to the electrical impedance tomographic image measuring apparatus according to the present invention, a predetermined respiratory state and a predetermined heart rate state are detected and extracted, thereby accurately removing the influence of respiration and the blood-derived electrical characteristic value. The local absolute value can be obtained and displayed as a tomographic image, so that the state of blood flow inside the living body can be intuitively grasped in real time.

  According to the electrical impedance tomography measurement apparatus of the present invention, for example, by monitoring the ventilation of the lung field and the change in the absolute value of the blood flow at the same time, the ventilation is bad or the blood flow is bad when oxygenation is bad. It becomes clear at a glance and it becomes possible to select an appropriate treatment policy.

Conventionally, in patients with pulmonary embolism, although it has been known that SpO ₂ has rapidly decreased, it has been difficult to specify that the cause is pulmonary embolism. With the device, pulmonary embolism can also be quickly identified, and treatments such as suction with a catheter and administration of a thrombolytic agent can be performed quickly.

  In addition, blood flow in organs such as the kidney and heart can be monitored, so that the efficacy of medication can be confirmed in real time, and parameters such as cardiac output can be measured non-invasively from the absolute value of electrical characteristics. It is also possible to do.

DESCRIPTION OF SYMBOLS 10 Electrode part 11-1 to 11-8 Electrode 20 Electrode control part 21 Constant current application means 22 Measurement means 30 Computer system 31 Main body part 32 Display part 33 Input part 34 Mathematical model creation means 35 Dmodel calculation means 36 Database 37 EIT (n ) Calculation means 38 Respiration heart rate separation means 40 Heart rate state detection means 41 First extraction means 42 Second extraction means 43 Determination means 44 Blood flow tomographic image display control means 45 Correction means

Claims (8)

Based on the position of the organ or tissue of the living body and its electrical characteristics, the biological cross-section is divided, and a mathematical model that can be calculated by changing the electrical characteristic value of each mesh into a plurality (n) is created. Mathematical model creation means;
A plurality of electrodes attached to surround a predetermined position on the surface of the living body, including an input pair electrode for applying a constant current and an output pair electrode for detecting a potential difference;
Constant current applying means for applying a constant current to the input pair electrodes;
When the electrical characteristic value of an arbitrary mesh is changed to a plurality (n) using the mathematical model, and a constant current is applied to the input pair electrodes, a plurality (n) of second (n) occurrences are generated in the output pair electrodes, respectively. Dmodel calculation means for calculating one potential difference (Dmodel);
Measuring means for measuring a second potential difference (Dmean (t)) generated in the output pair electrode when a constant current is applied to the input pair electrode;
A respiratory heartbeat separating means for separating the second potential difference into a respiratory-derived component and a heartbeat-derived component;
A respiratory state detecting means for detecting a predetermined respiratory state from the respiratory-derived component of the second potential difference separated by the respiratory heartbeat separating means;
A heartbeat state detecting means for detecting a predetermined heartbeat state;
First extraction means for extracting a plurality of second potential differences in a predetermined respiratory state detected by the respiratory state detection means from the heartbeat-derived component;
Based on a predetermined heartbeat state detected by the heartbeat state detection means, a plurality of second potential differences extracted by the first extraction means are synchronously added to obtain a second potential difference from which a respiratory-derived component has been removed, A second extraction means for extracting;
EIT (n) calculating means for calculating a plurality of (n) blood flow-derived electrical characteristic values corresponding to each pixel using the second potential difference from which the respiratory-derived component has been removed;
Determination means for determining an optimal blood flow-derived electrical characteristic value in each pixel from the plurality (n) blood flow-derived electrical characteristic values;
An electrical impedance tomographic image measuring apparatus comprising: a blood flow tomographic image display control unit that displays a tomographic image based on an electrical characteristic value derived from an optimal blood flow in each pixel. The electrical impedance tomogram according to claim 1, wherein the electrical characteristic value derived from the blood flow is one or more of resistivity, conductivity, dielectric constant, and magnetic permeability. measuring device. The determining means determines the square of a plurality of (n) electrical characteristic values corresponding to each pixel calculated by the Dmodel calculating means, or the one having the smallest absolute value as the optimal electrical characteristic value. The electrical impedance tomogram measuring apparatus according to claim 1 or 2, characterized in that   The electrical condition according to any one of claims 1 to 3, wherein the respiratory state detecting means detects a predetermined respiratory state using a respiratory-derived component separated by the respiratory heartbeat separating means from the second potential difference. Impedance tomography measuring device.   5. The electrical impedance tomography according to claim 1, further comprising electrocardiogram detection means for detecting electrocardiogram data, wherein the predetermined heartbeat state is detected by detecting an R wave from the electrocardiogram data. Image measuring device.   6. The electrical impedance tomographic image measurement apparatus according to claim 1, wherein detecting the predetermined breathing state detects a predetermined gas amount.   7. The electrical impedance tomogram according to claim 1, further comprising electrocardiogram detection means for detecting electrocardiogram data, wherein the second extraction means performs synchronous addition at the timing of the R wave of the electrocardiogram data. measuring device. The Dmodel calculation means includes
The electrical impedance tomogram measurement apparatus according to any one of claims 1 to 7, wherein the first potential difference is calculated using a predetermined electrical characteristic value of the tissue in the living body.