JP5469583B2 - Biological electrical impedance tomography measuring device - Google Patents

Description

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

  Conventionally, an electrical impedance CT called EIT (Electrical Impedance Tomography) is known. This device obtains the electrical impedance inside the living body from the potential distribution generated on the body surface by, for example, attaching 8 electrocardiogram electrodes horizontally and at equal intervals to the living body surface and applying a weak constant current tomographic image. Is what you get.

  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.

  In recent years, an EIT for obtaining an absolute value of electrical impedance has been developed. For example, the impedance distribution in the region of interest is calculated using a mathematical model, and the least square error between the predicted boundary voltage and the actually measured boundary voltage is generated and converged by iterative processing to obtain the absolute value of the electrical impedance. Is known (see Patent Document 1).

  However, in the above conventional example, the accuracy of the absolute value of the obtained electrical impedance is the accuracy of the mathematical model used, that is, the external shape of the living body, or the position, size, and shape of the organ and / or tissue inside the living body. There was a problem that it depends on accuracy.

  FIG. 21 shows a chest CT image of a child, and FIG. 22 shows a chest CT image of an adult. The child has a clear difference such that the proportion of the heart in the lung field is larger than that of an adult. Further, from comparison of the child chest X-ray shown in FIG. 23 and the adult chest X-ray shown in FIG. 24, it can be seen that the size of the rib cage and lung of the child is clearly smaller than that of the adult. Furthermore, FIG. 25 is a chest CT image of a healthy child, and FIG. 26 is a chest CT image of a child with cardiac hypertrophy. From this, individual differences such as the position, size, and shape of the organs are similar even when the age is close. It can never be said to be small.

  FIG. 28 is an EIT image obtained by estimating the EIT of the chest using a mathematical model that matches the chest CT image for the child subject of the chest CT image shown in FIG. 21. From this, the lung field region and the heart region are in good agreement. You can see that On the other hand, FIG. 27 is an EIT image obtained by estimating the breast EIT of the child subject using the adult mathematical model generated from the adult chest CT image shown in FIG. 22, and is compared with the CT image of FIG. Thus, it can be seen that the lung field region and the heart region are clearly different. In this way, in EIT, physical differences such as differences between adults and children in the mathematical model used in the calculation greatly affect the estimation accuracy. It is very important to use a matched mathematical model.

  However, in order to create a highly accurate three-dimensional mathematical model, for example, for each of several hundred CT images of slices of several millimeters or less, each organ is extracted from each tomographic image, and upper and lower adjacent tomographic images are further extracted. It is necessary to generate a three-dimensional mesh in consideration of the region where the same organ exists, and to set typical electrical characteristic values specific to each organ in each mesh. At this time, it is necessary to generate a mesh without omission and set an electrical characteristic value in an area that is not assigned to a specific organ. However, since it is difficult to automatically extract all organs from CT images at the current technical level, the creation of a three-dimensional or higher mathematical model must be a labor-intensive operation that relies on human hands. Absent.

  To address these issues, select an approximate head model based on subject characteristics from a database based on features associated with the fictitious subject, such as the predetermined height, age, gender, etc. of the fictitious subject EIT is also known (Patent Document 2, especially column 0021). In this EIT, the current flow map acquired using the Barber-Brown linear back projection method can be changed based on the selected approximate head model.

  Using this method, the more standard models prepared in advance in the database, the more theoretically a model that is closer to the subject can be selected. Taking an example, the position, size, and shape of the heart vary considerably from person to person, and considering the case of having a disease such as cardiac hypertrophy, the necessary database becomes enormous and is not realistic.

Special table 2003-534867 gazette JP-T-2006-502809

  The present invention has been made in view of the current state of the electrical impedance tomogram measurement apparatus for living organisms as described above, and its purpose is to create a precise mathematical model that matches the patient's sex, age, body shape, and other biological feature parameters. Can be created in a short time that can be practically used in the clinical field, and once the actual measurement value is obtained, the absolute value of the electrical property value inside the living body corresponding to this can be uniquely obtained with high accuracy. An electrical impedance tomogram measuring apparatus is provided.

  The living body electrical impedance tomographic image measuring apparatus according to the present invention divides the living body cross section into a number of meshes based on the position of the organ or tissue of the living body and the electrical characteristics thereof, and sets a plurality of electrical property values of each mesh. A mathematical model creation means for creating a mathematical model of three or more dimensions that can be calculated by changing to (n), and a tomography composed of a plurality of biological cross-sections as a basis for the mathematical model created by the mathematical model creation means A tomographic model database in which multiple types of standard tomographic models with different biometric parameters including at least one of gender, age, and body type are stored, and a tomographic model corresponding to the desired biometric parameters from the tomographic model database Select and take out, modify the fault model, and supply it to the mathematical model creation means to create a mathematical model A plurality of electrodes pasted so as to surround a predetermined position on the surface of the living body, including a further means and an input pair electrode for applying a constant current and an output pair electrode for detecting a potential difference; and the input A constant current applying means for applying a constant current to the pair electrode, the first potential difference (Dmodel) calculated using the new mathematical model created by the mathematical model changing means, and the measurement obtained by actual measurement Based on the second potential difference (Dmean) generated in the output pair electrode, an optimum electrical characteristic value in each pixel is estimated and determined, and a tomographic image is displayed based on the optimum electrical characteristic value in each pixel. It is characterized by that.

  The biological electrical impedance tomographic image measurement apparatus according to the present invention is such that in each tom of the tomographic model, a plurality of different organs and / or tissues included in the tomography are in different layers with priorities. If each layer of a tomographic model is generated by combining and layering different layers and different organs and / or tissue regions overlap, the organs and / or tissues belonging to the higher priority layer become effective. The processing is performed by the mathematical model changing means.

  In the biological electrical impedance tomographic image measurement apparatus according to the present invention, the tomographic model further includes at least one of height, chest circumference, and aspect ratio of the rib cage as a characteristic parameter of the biological body, and the mathematical model changing means includes: The tomographic model selected and taken out is deformed according to the biological feature parameter.

  In the biological electrical impedance tomographic image measuring apparatus according to the present invention, the mathematical model changing unit is configured to determine a position of an external shape of an organism or an arbitrary organ and / or tissue with respect to an arbitrary tomographic model selected and extracted. And / or adjusting means for adjusting the size and / or shape.

  In the electrical impedance tomographic image measurement apparatus for living body according to the present invention, the adjusting means is linked to a change made to an arbitrary tom of the tomographic model, and the external shape or organ of another tomographic model of the tomographic model And / or changing the position and / or size and / or shape of the tissue.

  In the biological electrical impedance tomographic image measurement apparatus according to the present invention, the mathematical model creating means generates a mesh with a predetermined resolution for each region of the organ or tissue based on the provided tomographic model, The electrical characteristic value is set.

  In the electrical impedance tomogram measurement apparatus for living body according to the present invention, an electrode mathematical model simulating the shape, size, and electrical characteristic value of an electrode used for actual measurement is arranged at an arbitrary position in the mathematical model. And an electrode model generation / arrangement means.

  The apparatus for measuring electrical impedance tomograms of a living body according to the present invention is a tomographic model composed of a plurality of cross sections of a living body, which is a basis of a mathematical model, and includes a biological feature parameter including at least one of gender, age, and body type From the tomographic model database in which a plurality of types of standard tomographic models having different values are accumulated, a mathematical model changing unit selects and extracts a tomographic model corresponding to a desired biological feature parameter, changes it so as to match the subject, and applies the mathematical model Since a new mathematical model is created by supplying it to the creation means, it is possible to create a precise mathematical model that matches the subject in a short time that is practical for clinical use, and to obtain a more accurate EIT image. It is done.

  Each of the tomographic models of the tomographic model of the biological electrical impedance tomographic image measuring apparatus according to the present invention, each of the different organs and or tissues included in the tomographic area is managed in different layers with priorities, When different organs and / or tissue regions overlap in each slice generated by synthesizing the layers, the organs belonging to the higher priority layer are validated. Therefore, change of the aspect ratio of the chest circumference and / or rib cage with respect to an arbitrary fault of the fault model by the mathematical model changing means, the position and / or size and / or shape of the living body by the adjusting means, or arbitrary organs and / or tissues, When the organ and / or tissue segmentation in the tomography changes as a result of the adjustment, the position and / or size and / or shape of the living body of another tomography or organ and / or tissue can be easily linked. Therefore, it is possible to efficiently and quickly change to a fault model that is the basis of a precise mathematical model that matches the subject. Furthermore, the accuracy of the fault model can be improved by expanding or contracting each fault interval of the fault model according to the height.

  In the tomographic model of the biological electrical impedance tomographic image measurement apparatus according to the present invention, the region where the same organ is present is maintained between the upper and lower adjacent tomograms even after being changed to match the subject. Therefore, when the tomographic model is provided to a mathematical model creation means and a three-dimensional mesh is generated, the mesh generated for each organ and / or tissue may overlap another organ and / or tissue, There are no blank areas, or no state occurs. In other words, there are a plurality of electric characteristic values at the same time, or there are areas having no electric characteristic values. Problems such as EIT calculation divergence do not occur.

  In the electrical impedance tomogram measurement apparatus for living body according to the present invention, an operator can arbitrarily specify a tomographic model without considering an overlap of organs and / or tissues based on one tomographic image such as a CT image of the subject. If a desired change is made to the fault, the change is reflected in the entire fault model in conjunction with each other. Therefore, it is possible to easily create a precise mathematical model that matches the subject in a short time even if it is not an expert. Is possible.

1 is a block diagram showing a configuration of an electrical impedance tomographic image measurement apparatus according to the present invention. The figure which shows the notional structure of the model database in the electrical impedance tomogram measuring apparatus which concerns on this invention. The figure which shows the cross-sectional image which divided | segmented the structure | tissue of the process which creates a chest mathematical model based on an X-ray CT image in this invention. The flowchart for demonstrating the mathematical model extraction and adjustment by the electrical impedance tomogram measuring apparatus which concerns on this invention. The schematic diagram which shows the tomographic model and layer which the electrical impedance tomographic image measuring apparatus which concerns on this invention has employ | adopted. The schematic diagram which shows the process in a layer and a tomographic model when an organ is moved in the tomographic model which the electrical impedance tomogram measuring apparatus which concerns on this invention employ | adopts. The schematic diagram which shows the reflection process with respect to the tomographic model of the tomography adjacent to a layer, when an organ is moved in the tomographic model which the electrical impedance tomographic image measuring apparatus which concerns on this invention employ | adopts. The schematic diagram which shows the process in a layer and a tomographic model when the magnitude | size of an organ is changed in the tomographic model which the electrical impedance tomogram measuring apparatus which concerns on this invention employ | adopts. The schematic diagram which shows the reflection process with respect to the tomographic model of the tomography adjacent to a layer, when the magnitude | size of an organ is changed in the tomographic model which the electrical impedance tomographic image measuring apparatus which concerns on this invention employ | adopts. The schematic diagram which shows the process in a layer and a tomographic model when the shape of an organ is changed in the tomographic model which the electrical impedance tomogram measuring apparatus which concerns on this invention employ | adopts. The schematic diagram which shows the reflection process with respect to the tomographic model of the tomography adjacent to a layer, when the shape of an organ is changed in the tomographic model which the electrical impedance tomographic image measuring apparatus which concerns on this invention employ | adopts. The figure which shows the cross-sectional image for the electrode arrangement | positioning in the process of creating a chest mathematical model based on an X-ray CT image in the present invention. Sectional drawing which shows the chest mathematical 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 another 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 perspective view which shows the relationship between the electrode arrangement | positioning in this invention, and a slice. The flowchart which shows operation | movement of the electrical impedance tomogram measuring apparatus which concerns on this invention. 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. Child's chest CT image. Adult chest CT image. Illustration of a chest radiograph of a child. Illustration of an adult chest x-ray. Chest CT image of a healthy child. Chest CT image of a child with cardiac hypertrophy. The figure of the EIT image which estimated the child's chest EIT using the adult mathematical model. The figure of the EIT image which estimated the child's chest EIT using the child's mathematical model.

  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 a mathematical model creation means 34 for creating a mathematical model of three or more dimensions such as FEM (finite element method) and a tomographic model database 41.

  The tomographic model database 41 is a tomographic model that is the basis of the mathematical model created by the mathematical model creating means 34, and is associated with a plurality of biological feature parameters that differ in at least one of gender, age, and body type. Multiple standard fault models are accumulated. For example, as shown in FIG. 2, the tomographic model database 41 stores a plurality of tomographic models that are classified by sex (biological feature parameter) of men and women, and further classified by age (biological feature parameter). Yes. In addition, by generating and accumulating a mathematical model corresponding to the standard fault model in advance, a reference that does not require high-precision EIT or a precise mathematical model that matches the subject is generated. It can also be used.

  The biometric feature parameters shown above are only examples, and for example, the height, chest circumference, aspect ratio of the rib cage, and the like can be used as the biometric feature parameters. In the example of FIG. 2 described above, when a tomographic model is taken out, biological feature parameters including gender, age, body type, and the like are input by the input unit 33. When the biometric feature parameter is input, the main body 31 extracts a tomographic model corresponding to the biometric feature parameter from the tomographic model database 41 and displays it on the display unit 32.

  In the present embodiment, the main body 31 is provided with a mathematical model changing unit 44 and an adjusting unit 45. The adjusting means 45 is provided in the mathematical model changing means 44. The mathematical model changing means 44 transforms an arbitrary fault of the one fault model extracted above according to the aspect ratio of the chest circumference and the rib cage input to the input unit 33, and also applies to an adjacent fault of the same fault model. In turn, this deformation is reflected. Further, the mathematical model changing unit 44 expands and contracts each fault interval of the fault model according to the height input by the input unit 33.

  In this embodiment, when the position, size, and shape of the living body, organ, and / or tissue of an arbitrary tomographic model selected and extracted by the adjusting unit 45 are changed, the same tomographic model This change will be reflected in the adjacent faults one after another.

  Changes in the external shape of the living body, the position and size of the organ and / or tissue, and the shape are performed according to the following procedures.

  The deformation of the external shape of the living body is performed as follows. First, the position of the center of gravity when an arbitrary fault in the fault model is regarded as homogeneous is matched with the position of the center of gravity of the deformed shape, and a line segment is drawn radially from the center of gravity position at an equal angle of about 1 to 10 degrees. . Next, the ratio of the line segment from the center of gravity position at each angle to the outer shape of the living body is calculated, and the outer shape of the living body is changed by sequentially expanding and contracting the adjacent upper and lower faults according to the ratio. At this time, the organs and / or tissues contained in each fault are simultaneously expanded and contracted by the same method. Further, linear interpolation or spline interpolation is performed during equiangular intervals.

  Changing the position of the organ and / or tissue is performed as follows. First, a target organ or tissue is selected and moved in an arbitrary slice of the tomographic model, and a movement vector is obtained from the original center of gravity position and the moved center of gravity position of the target organ or tissue. At this time, since the movement of the target organ or tissue is performed at the layer level, the division of the organ and / or tissue in the synthesized tomographic model changes according to the movement of the target organ or tissue and the priority order of the layers. Next, the target organ or tissue is sequentially moved by the same vector also in the adjacent upper and lower tomographic sections, and the tomographic model is reconstructed.

  Changing the size of the organ and / or tissue is the following procedure. First, the target organ or tissue is selected in an arbitrary fault of the fault model, and the expansion / contraction ratio is designated. Since the expansion or contraction of the target organ or tissue is performed at the layer level, the division of the organ and / or tissue in the synthesized tomographic model changes depending on the expansion and contraction of the target organ or tissue and the priority order of the layers. Next, in the adjacent upper and lower faults, the target organ or tissue is sequentially expanded and contracted by the same ratio, and the fault model is reconstructed.

  Changing the shape of an organ and / or tissue is performed as follows. First, the target organ or tissue is selected in an arbitrary fault of the fault model, and the changed shape is designated. Next, the center of gravity position of the shape after the change of the target organ or tissue is matched with the position of the center of gravity before the change, and a line segment is drawn radially from the center of gravity position to each outer shape at an equal angle of about 1 to 10 degrees. Calculate the line segment ratio at. Since the change of the shape of the target organ or tissue is performed at the layer level, the region classification of the organ and / or tissue is changed in the synthesized tomographic model depending on the change of the shape of the target organ or tissue and the priority order of the layers. Even in the adjacent upper and lower tomograms, the outer shape of the target organ or tissue is sequentially deformed from the position of the center of gravity of the target organ according to the ratio of the radial line segments, and the tomographic model is reconstructed. Note that linear interpolation or spline interpolation is performed during equiangular intervals.

  Such a change process for the tomographic model is performed by the main body 31 according to the flowchart shown in FIG. As described above, when the biometric feature parameter is input, it is fetched (S31), the corresponding tomographic model is taken out from the tomographic model database 41 and displayed on the display unit 32 (S32).

  A tomographic model as shown in FIG. 3 and a representative cross section of the CT image of the subject are displayed in parallel or superimposed on the display unit 32 according to the operator's selection, and the operator can display the outline, organ and / or tissue position of the living body with the mouse. Perform operations to make changes. For example, changing the external shape of the living body by clicking a part of the rib cage and dragging it to the desired position and releasing it, changing the size of the selected desired organ, using the enlargement / reduction button, and dragging and dropping the position Change operation such as change of. The position and thickness of a blood vessel that is a tissue other than an organ, or the amount of fat (fat thickness) is also changed by mouse operation as necessary.

  In response to the operation by the mouse, the adjusting unit 45 displays the image of the tomographic model that has been changed and adjusted by adjusting the original tomographic model from the adjustment input detection state (S33) in the flowchart of FIG. S34).

  In the present embodiment, the adjustment by operating the mouse provided in the input unit 33 can, of course, be provided by a method using a touch panel provided on the screen of the display unit 32 or a pen input method.

  Next, a specific example of processing performed as described above by the mathematical model changing unit 44 and the adjusting unit 45 will be described. Here, in order to simplify the description, the fault model is composed of three faults, fault # 1, fault # 2, and fault # 3, as shown in FIG. , L2, and L3. In the example of FIG. 5, the fault # 2 is composed of three layers L1, L2, and L3, but the fault # 1 and the fault # 3 are similarly composed of three layers. It is configured.

  FIG. 5 shows an example in which the heart A is set in the layer L1, the right lung B and the left lung C are set in the layer L2, and the thorax D is set in the layer L3. The layers L1, L2, and L3 have priorities, and the mathematical model changing unit 44 enables the organs and / or tissues of the higher priority layers when different organs and / or tissue regions overlap. Process as follows. For the valid organs and tissues of the tomographic model thus changed, the mathematical model generation means generates meshes and sets electrical characteristic values for each mesh.

  For example, when moving the organ A, if the heart A is moved from P1 to P2 by an operator's operation in the tomography # 2, the heart A is moved from P1 to P2 by the mathematical model changing means 44 and the adjusting means 45. Then, the three layers L1, L2, and L3 are combined to create a new fault # 2a (FIG. 6). A movement vector is obtained for the heart A, and reflection processing (position change processing) is performed on the layer in which the corresponding heart A is set for the remaining slice models, the slice # 1 and the slice # 3. Are combined to create new faults # 1a and # 3a (FIG. 7).

  Further, for example, when the size of the organ A is changed, it is assumed that the size of the heart A is changed from the central elliptical shape b1 to the outer elliptical shape b2 in the tomography # 2 by the operation of the operator. The mathematical model changing means 44 and the adjusting means 45 change the heart A from the elliptical shape b1 to the elliptical shape b2, and the three layers L1, L2, and L3 are combined to create a new slice # 2b ( FIG. 8). The expansion / contraction ratio is obtained based on the change from the elliptical shape b1 to the elliptical shape b2 for the heart A, and the reflection processing to the layer in which the corresponding heart A is set for the faults # 1 and # 3 which are the remaining fault models ( Expansion / contraction processing based on the expansion / contraction ratio) is performed, and three layers are combined in each to create new faults # 1b and # 3b (FIG. 9).

  Further, for example, in the case of changing the shape of the organ A, it is assumed that the shape of the heart A is changed from the central elliptical shape c1 to the outer shape c2 in the tomography # 2 by the operation of the operator. The heart A is changed from the shape c1 to the shape c2 by the mathematical model changing means 44 and the adjusting means 45, and the new layer # 2c is created by synthesizing the three layers L1, L2, and L3 (FIG. 10). ). In this case, a line segment of about 1 to 10 is drawn at an equal angle from the center of gravity of the heart A, and the stretch ratio of the line segment length to the outline of the heart is calculated for the shapes c1 and c2. Reflection processing (expansion / contraction processing based on the expansion / contraction ratio of the line segment length) to the layer in which the corresponding heart A is set for the remaining tomographic models # 1 and # 3 is performed, and in each of the three layers Are combined to create new faults # 1b and # 3b (FIG. 11).

  The processes in steps S33 and S34 described above are repeated, and when there is an instruction input for determining a tomographic model from the input unit 33 (S35), the adjusted tomographic model is sent to the mathematical model creating means 34 (S36).

  As shown in FIG. 3, the mathematical model creation means 34 receives a tomographic model in which a region is divided for each tissue and the region is assigned a tissue number. The mathematical model creation means 34 includes a database having the contents of Table 1 indicating the correspondence between each organization, number, and resistivity, and can perform association.

  Next, the mathematical model creation means 34 creates a three-dimensional chest mathematical model from the tomographic model, and each electrode including the electrodes 11-1 to 11-8 in the electrode part 10 of FIG. 5mm) is set. Specifically, as shown in FIG. 12, eight slices l of equal angles from the center are drawn on the slice image, a 5 mm horizontal electrode is 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 described above, in the present embodiment, the electrode model generation / arrangement unit arranges, in the arbitrary position, the electrode mathematical model that simulates the shape, size, and electrical characteristic value of the electrode used for actual measurement in the mathematical model. Is provided.

  As an example, a plan view of a three-dimensional chest mathematical model having 2,660,960 elements and 527,571 nodes is shown in FIG. In FIG. 13, the back side perpendicular to the paper surface is the head, and as is apparent from the position of the spinal cord 51, the upper side of FIG. 13 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. 13, 16 electrodes are set on one slice plane. This is for the case where EIT data needs to be obtained by changing the electrode position as in a midline incision patient.

  Next, a cell wall is formed on any of the input pair electrodes (for example, 11-1 & 11-2) of the electrodes 11-1 to 11-8 using the first calculation means 35 for the constructed three-dimensional chest mathematical model. A potential difference output from an output pair electrode (a combination of electrodes 11-1 to 11-8) different from an input pair electrode when a constant current of a high frequency (for example, several MHz or more) is applied. Simulation with varying field resistivity.

  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.

  As an example of changes in the resistivity of the lung field, although there are individual differences in the lung resistivity, the normal lungs are usually 5 Ωm or more, and the pneumonia lungs are often 3 Ωm or less. A simulation of changing 1 to 8 steps (5, 5.55, 6.25, 7.14, 8.33, 10, 12.5, 16.7Ωm) between 5 and 16.7Ωm and applying a constant current of 1mA to the input pair electrodes of electrodes D1 to D8 explain. 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. 13, 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. 14 streets. Detection by the same input / output pair is inaccurate, and is set to 0. In addition, the potential difference when the output pair electrode includes one of the input pair electrodes seems to be inaccurate.

  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. 14 shows a regression curve created by a potential difference obtained from the output pair electrodes of the electrodes D3 and D4 with the electrodes D1 and D2 as input pair electrodes. Further, FIG. 16 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-mentioned regression curve, the resistivity is finely changed in multiple stages, a matrix as shown in FIG. 14 is calculated for each resistivity (in the above example, 8 stages), and the first calculation means 35 applies the target. You may comprise as the database 36 (FIG. 1) of the correspondence of the resistivity set with respect to the structure | tissue, and the electric potential difference detected from an output pair electrode.

  FIG. 17 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. 17, the reason why the current density is high in the upper left part is that 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.

  Next, the measuring means 22 (FIG. 1) 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 a surface of a required part such as the head, torso, and extremity according to the purpose, but here, the measurement of lung state change due to respiration is exemplified for the chest. . 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, and the applied constant current is preferably a high frequency (for example, several MHz or more) that goes straight through the cell wall, but is about several tens of kHz to 200 or 300 kHz. May be. The constant current applying unit 21 and the measuring unit 22 operate in synchronization with the same clock.

  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 sequentially takes the potential difference output from any one of the adjacent output pair electrodes (combination of the electrodes 11-1 to 11-8) of the electrodes 11-1 to 11-8, digitizes it, and digitizes it. Send to system 30. At this time, there are eight output pair electrodes, but detection by the output pair electrodes (11-1 & 11-2, 11-1 & 11-8, 11-2 & 11-3) including one or both of the input pair electrodes is inaccurate. So do not adopt.

  Next, the input pair electrodes are changed to different pairs (for example, 11-2 & 11-3), and the potential difference is similarly obtained. Similarly, among the electrodes 11-1 to 11-8, a preset pair is set as an input pair electrode, and the potential difference of the output pair electrode is measured by the above-described procedure. The actually measured potential difference matrix thus obtained is defined as Dmean. 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 unit 21 is not a direct application of a high frequency constant current exceeding 1 MHz, but a plurality of low frequency constant currents are applied, and the correcting unit 43 applies a high frequency constant current. It is also possible to correct the potential difference observed when a constant current is applied. The correction means 43 sweeps a plurality of low-frequency constant currents, plots the measured potential difference on a plane, and estimates the potential difference at a high frequency based on the Cole-Cole equation from the obtained curve. Is.

  The second calculating means 37 calculates Dmean from the measured potential difference, a potential difference matrix Dmodel (n) for a plurality of (n) resistivities stored in the database 36, and a sensitivity matrix based on sensitivity theory ( A plurality (n) of electrical characteristic values such as resistivity for each pixel are calculated using a weighting correction coefficient known as sensitivity matrix or Jacobian matrix. Here, the correction coefficient such as the 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, and in this example, eight types are set as shown in Table 3 and the like. However, 300 types in 0.2Ωm increments are calculated in advance, and the database 36 It is good.

  When a sensitivity matrix widely used in EIT in recent years is used, each element of Dmean and each element of Dmodel are compared by division, and a value EIT () corrected by multiplying the sensitivity matrix to weight each element is corrected. n) can be calculated for each pixel.

For each pixel, n in a state where there is no difference between Dmean and Dmodel (n), that is, n when the rate of change is zero is the resistivity to be finally obtained. When the corrected EIT (n) is n, the resistivity is finally obtained. The determination means 38 can 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. 20) 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 processing executed for obtaining the resistivity as the optimum electrical characteristic value by the second calculation means 37 and the determination means 38 described so far will be referred to as optimum electrical characteristic value determination processing.

  The tomographic image display control means 39 displays the optimal electrical characteristic value of each pixel estimated in this way in real time using a color corresponding to a preset electrical characteristic value. Here, since the optimal electrical characteristic value is an absolute value, for example, the optimal electrical characteristic value of each pixel in the lung field corresponds to the local gas amount of the corresponding lung field on a one-to-one basis. That is, the tomographic image of the same part displayed by the tomographic image display control means can objectively determine the state of the local gas amount in the lung field based on the same standard.

  The area selection means 42 includes area selection means for selecting a predetermined area from the tomographic image generated by the tomographic image display control means 39. 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 34 meshes more than n, and finally estimating and determining the optimal electrical characteristic value for each pixel from a plurality (n) or more of the electrical characteristic values, It becomes possible to estimate the electrical characteristic value in the region more accurately.

  To summarize the above description, the electrical impedance tomographic image measurement apparatus according to this embodiment operates as shown in the flowchart of FIG. That is, as described with reference to FIGS. 2 to 11, the tomographic model is selected and adjusted, a mathematical model of the living body is created (S11), electrodes are installed on the mathematical model (S12), and the target organ is selected. It is detected whether or not a region has been selected (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 (S13).

  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. 14 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.

  Subsequent to step S15, the potential difference is actually measured using the electrode unit 10 and the electrode control unit 20 to obtain a potential difference matrix Dmean (S16). Here, when the frequency of the constant current applied at the time of actual measurement is low, the electrical characteristic value obtained when applied at a frequency higher than the constant current actually used is corrected by the Cole-Cole equation (S16A). The potential difference matrix Dmodel (n) of the simulation result thus obtained is compared with the actually measured potential difference matrix Dmean and multiplied by a weighting coefficient known from the sensitivity matrix S (n) to correct each pixel. EIT (n) is calculated (S17).

Furthermore, for each pixel, the absolute value of EIT (n) or n when [EIT (n)] ² (FIG. 20) is minimum, that is, n with no difference between Dmean and Dmodel (n). Then, an absolute optimum electrical characteristic value is determined and displayed as a tomographic image in real time using a color corresponding to a preset electrical characteristic value (S19). Note that by selecting a predetermined region from the generated tomographic image, it is possible to more accurately estimate the optimum electrical characteristic value in each pixel.

  Following step S19, it is detected whether the operator has selected end (S19A). If NO, the process returns to step S19B. In step S19B, when it is detected that a region has been selected in the target organ of the generated tomographic image, the process branches to YES in S19B, and in order to measure the selected region in detail, A plurality (n) of electrical characteristic values and a plurality (n) or more of electrical characteristic values in the selected region are set (S13B), and the process proceeds to step S14 to perform subsequent processing. If the process branches to YES in step S19A, the process ends.

  In this embodiment, an absolute optimum electrical characteristic value is determined, and a tomographic image is displayed in real time using a color corresponding to a preset electrical characteristic value. As this premise, the mathematical model changing means 44 selects and extracts a standard tomographic model corresponding to a desired biological feature parameter from the tomographic model database 41 in which a plurality of types of standard tomographic models having different biological feature parameters are accumulated, The fault model is changed and supplied to the mathematical model creation means 34 to create a mathematical model. For example, in the EIT image (FIG. 28) in which the child's chest EIT is estimated using the child's mathematical model processed by the mathematical model changing means 44, the chest CT image (FIG. 21), the lung field region, and the heart region are often used. Match. On the other hand, when the conventional method of estimating a child's EIT using an adult mathematical model is used, the obtained EIT image is as shown in FIG. 27, which is compared with the CT image of FIG. It can be seen that the present embodiment using a mathematical model that matches the subject is superior because the heart region is clearly different.

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 Estimation means 36 Database 37 Calculation means 38 Determination Means 39 Tomographic image display control means 41 Fault model database 42 Area selection means 43 Correction means 44 Mathematical model change means 45 Adjustment means

Claims (7)

Three or more dimensional mathematics that can be calculated by dividing the cross section of the living body into a large number of meshes based on the position of the organ or tissue of the living body and its electrical characteristics, and changing the electrical property value of each mesh into a plurality (n) A mathematical model creation means for creating a model;
A tomographic model composed of a plurality of biological cross-sections, which is a basis of the mathematical model created by the mathematical model creating means, is a standard tomographic model having different biological feature parameters including at least one of gender, age, and body type Multiple types of accumulated fault model database,
Selecting and extracting a tomographic model corresponding to a desired biological feature parameter from the tomographic model database, applying a change to the tomographic model, and supplying the mathematical model creating unit to create a mathematical model;
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;
A constant current applying means for applying a constant current to the input pair electrodes;
Based on the first potential difference (Dmodel) calculated using the new mathematical model created by the mathematical model changing means and the second potential difference (Dmean) generated in the output pair electrode obtained by actual measurement. An apparatus for measuring an electrical impedance tomogram of a living body, wherein an optimal electrical characteristic value in each pixel is estimated and determined, and a tomographic image is displayed based on the optimal electrical characteristic value in each pixel. In each fault of the fault model, regions of different organs and / or tissues included in the fault are managed in different layers with priorities, and each fault of the fault model is synthesized by combining the layers. Is generated, and when the regions of different organs and / or tissues overlap, processing is performed by the mathematical model changing unit so that the organs / tissues belonging to the higher priority layer are valid,
The living body electrical impedance tomographic image measuring apparatus according to claim 1.   The tomographic model further includes at least one of height, chest circumference, and aspect ratio of the rib cage as a biological characteristic parameter, and the mathematical model changing means selects the tomographic model selected and extracted in accordance with the biological characteristic parameter. The living body electrical impedance tomographic image measuring apparatus according to claim 1, wherein the tomographic image measuring apparatus is configured to be deformed.   The mathematical model changing means includes an adjusting means for adjusting an external shape of a living body or a position and / or size and / or shape of an arbitrary organ and / or tissue with respect to an arbitrary slice of a tomographic model selected and extracted. The apparatus for measuring an electrical impedance tomogram of a living body according to any one of claims 1 to 3.   The adjustment means changes the position and / or the size and / or the shape of the living body of the other tomographic model of the tomographic model, or the organ and / or the tissue in conjunction with the change made to an arbitrary fault of the tomographic model. The living body electrical impedance tomographic image measuring apparatus according to claim 4. The mathematical model creating means generates a mesh with a predetermined resolution for each region of the organ or tissue based on the provided fault model, and sets a desired electrical characteristic value.
The living body electrical impedance tomographic image measuring apparatus according to any one of claims 1 to 5, wherein:   An electrode model generation / arrangement means is provided in the mathematical model, wherein an electrode mathematical model simulating the shape, size, and electrical characteristic value of an electrode used for actual measurement is arranged at an arbitrary position. Item 7. The biological electrical impedance tomographic image measurement apparatus according to any one of Items 1 to 6.