JP4863325B2 - Hemodynamic characteristic measuring device - Google Patents

Description

The present invention relates to a hemodynamic characteristic measurement device, and in particular, by calculating a viscosity distribution representing blood properties and shear stress distribution in blood based on an ultrasonic Doppler measurement method used for diagnosis of blood flow dynamics. Measure hemodynamic properties that can be used to provide information to the surgeon for predicting the risk of atherosclerotic plaque failure, which triggers most vascular diseases, and for medical diagnostic equipment for personal daily health management Relates to the device.

Non-Patent Document 1 below uses an array of micro grooves (micro channel array) processed on the surface of a silicon single crystal substrate using a semiconductor micro processing technique (integrated circuit manufacturing technique) as a capillary model. A technique for measuring the passage time while pouring blood collected therein and observing red blood cells and plasma passing through the groove with a microscope is disclosed. This is to evaluate erythrocyte deformability, leukocyte adhesion ability, platelet aggregation ability and the like by measuring the passage time. The microchannel array used for this measurement has been commercialized (product name: MC-FAN, Micro Channel array Flow Analyzer).

Further, in Patent Document 1 below, wave information (ultrasonic waves) is input non-invasively from the surface of a living body, reflected on a body fluid flowing through the living body, and the state of blood or the like is analyzed from movement or position to obtain circulation information. An apparatus for measuring circulatory dynamics for the purpose of evaluating health status is disclosed. This apparatus includes a circulation sensor unit that transmits and receives a wave from the surface of the living body to the inside of the living body, and a processing unit that calculates the circulation dynamics from the received wave, and the circulation sensor unit further includes means for measuring blood flow and blood pressure. Means for calculating the blood viscosity information from the measured blood flow rate and blood pressure in the processing unit, or by combining with the blood viscosity value measured in advance and measured, the resistance related to the shape of the blood vessel The component is calculated.

The measurement principle of the present invention is based on obtaining circulatory information from changes in blood flow velocity, blood pressure, and blood vessel diameter over time, replacing blood vessels in a peripheral part of a living body with an electric circuit, blood flow volume Q as a current, The blood pressure value V between two different points in the blood vessel is equivalent to the voltage, and the blood vessel resistance R is considered to be the ratio of this V and Q (from Ohm's law). Vascular resistance R = blood pressure difference V / blood flow Q (formula 1) is calculated. The vascular resistance R includes a shape factor such as the thickness of the blood vessel and a factor of blood viscosity, where r is a shape factor (blood vessel shape resistance component) and ρ is a factor of blood viscosity. R = r × ρ = blood pressure difference V / blood flow rate Q (formula 2). In the same subject, since it is unlikely that r changes greatly every day, the vascular resistance R is greatly influenced by the viscosity of blood. Therefore, in a relatively short period (several days), the change in vascular resistance R can be regarded as a change in blood viscosity ρ. That is, by measuring the vascular resistance R, it is possible to know the change in the viscosity ρ of the blood. Therefore, the vascular resistance R is intended to be used as an indicator of the circulation dynamics in the peripheral region.

The measurement method of the vascular resistance R is based on (Equation 2). However, assuming that the blood flow velocity v, the blood vessel diameter d, and the blood pressure V (Equation 2), R = ρ × r = V / Q = 8V / πd ² v (Equation 3). Here, blood flow velocity v and blood vessel diameter d are measured based on transmission / reception of ultrasonic waves from a plurality of piezoelectric vibrators installed in the circulation sensor unit, and blood pressure measurement is installed in the circulation sensor unit. This is done using a blood pressure sensor.

Non-Patent Document 2 below proposes a method for noninvasively estimating blood viscosity using an ultrasonic system. In a rigid tube, the shape of the velocity profile of a Newtonian fluid in laminar flow is related to the viscosity and pressure gradient in the Navier-Stokes equation. If considered as a forward problem, the shape of the velocity distribution of the blood flow in the blood vessel is determined by the viscosity and the pressure gradient. Therefore, when considered as an inverse problem, it is conceivable that the viscosity and pressure gradient can be estimated from the shape of the velocity distribution.

The governing equation of the fluid circulating in the pipe is represented by the Stokes equation. Under the strong constraint that the flow in the cylinder is a laminar flow and an axisymmetric one-way flow, the following linear ordinary differential equation is obtained.
Here, p: pressure, x: cylinder long axis direction, ρ: density, w: velocity component (x axis direction), t: time, r: cylinder short axis radius, μ: viscosity. Since the distribution of the velocity component w can be known by ultrasonic blood flow velocity measurement, the viscosity μ and the pressure gradient dp / dx can be obtained based on the equation (4).
As described above, the following methods have been proposed for obtaining the viscosity and the pressure gradient from the velocity component distribution (velocity profile) using equation (4) as a basic equation.

(1) Linearized Method (Bensahla, 1983)
In this method, the velocity profile is frequency-resolved in the time axis direction, and the viscosity is estimated by taking the velocity ratio of two points in the tube based on the velocity profile of the pulsation component obtained as a result. However, since this method requires frequency analysis in the time axis direction, it does not satisfy the real-time property required for ultrasonic diagnostic techniques. In addition, there is a problem that the result changes depending on how to select two points having a speed ratio.

(2) Integral Method (Integral Method, Deguet, 1999)
In this method, since equation (4) can be integrated twice in the radius r direction, simultaneous equations at two different positions can be obtained by integrating the viscosity and density at spatially uniform constants at two different positions. Therefore, the viscosity is obtained by solving this. However, this method is very delicate in selecting two integration paths, and the result depends on how the integration path is selected. In this respect, there is the same problem as the linearization method.

(3) Maximum Likelihood Method (Maximum Likelihood Method, Bacrie, 1999, the method proposed in this paper)
This method is a method proposed in Non-Patent Document 2, and as described in the above (1) and (2), not only two points but also a number of points are taken and a maximum likelihood estimation method (minimum two This is a method of simultaneously estimating the viscosity and the pressure gradient by a multiplicative method. Since the calculation is performed by spatially averaging, the estimated value can be stabilized.
These methods are verified by simulation and fluid experiments, and the validity of the method is shown for the results.

In addition, in Patent Document 2 below, in order to evaluate the vascular endothelial function, information on blood vessels and / or blood flows that change according to shear stress is measured, and the amount of change is calculated. A measuring apparatus is disclosed that is normalized by a cumulative value of shear stress for a predetermined time and used as a quantitative indicator of vascular endothelial function. This measuring apparatus normalizes the shear stress calculation means for determining the shear stress generated in the blood vessel, and the amount of change in information regarding the blood vessel and / or blood flow that changes in accordance with the shear stress with the cumulative value of the shear stress for a predetermined time. It comprises index calculating means for obtaining a value as an index of vascular endothelial function.

Here, as the shear stress calculation means, the shear stress is measured by τ = 4 μQ / πr ³ (Q: blood flow volume, r: intravascular radius, μ: viscosity coefficient). That is, assuming that the viscosity coefficient is known, the blood flow volume (which can be calculated by blood flow velocity measurement) and the radius in the blood vessel are measured, and the shear stress is obtained by the above shear stress calculation formula.

JP2003-290226 JP2003-144395

Kikuchi Shinji, Monma Masato, Makino Tetsuya, Tamura Masataka: Cellular Microrheology Measurement Device MC-FAN, Cell, 30 (7), 281-284, 1998. C. C-Bacrie: “Estimation of Viscosity from Ultrasound Measurements of Velocity Profiles”, Proc. IEEE Ultrasonics Symp., Vol.2, pp.1489-1492, 1999.

According to the technique described in Non-Patent Document 1 described above, the groove of the microchannel array is used as a capillary model, blood components passing therethrough are observed with a microscope, and the passage time is measured. Since adhesive ability, platelet aggregation ability, etc. are evaluated, blood properties can be intuitively evaluated, which is an excellent technique. However, since the test is performed on the blood after blood collection, it is necessary to take measures to prevent the blood from coagulating such as adding an anticoagulant. For this reason, it is considered difficult to evaluate blood properties in the same state as in the living body.

In addition, according to the technique described in Non-Patent Document 2, the Stokes equation is used to quantitatively estimate the viscosity and pressure gradient of blood, and a one-way flow is assumed as the blood flow. Stokes equation is used. However, the actual blood flow is not always a flow in one direction, and it is considered that there is a problem that the assumption restriction is too strong. Therefore, if the one-way flow assumption is applied to a flow that has velocity components in multiple directions, the quantitativeness of the calculated viscosity and pressure gradient will be insufficient, and the reliability of the estimation results will be reduced. Conceivable. In addition, in this method, the average viscosity and pressure gradient in the blood vessel are calculated, as in the case of the above-mentioned Patent Document 1, so that the restriction is too strong. Also, with this method, the average viscosity of the entire blood flow flowing in the blood vessel is calculated, and the spatial distribution of the viscosity cannot be imaged.

Moreover, according to the technique described in Patent Document 1, the blood vessel resistance defined by the ratio between the blood flow volume and the blood pressure is used as an index related to viscosity. However, it is considered that the vascular resistance includes not only the shape factor of the blood vessel and the viscosity factor of blood but also other factors such as viscoelasticity of the blood vessel wall. Therefore, using a vascular resistance value including various factors in a complicated manner as an index relating to viscosity is not equivalent to calculating a physical quantity such as a viscosity, and is considered to lack quantitativeness. Further, since the calculation of the vascular resistance value is based on the flow measurement at two points using ultrasonic waves, it is considered that the average vascular resistance value in the two-point section is merely calculated as it is.

Further, according to the technique described in Patent Document 2, the shear stress is obtained in order to evaluate the vascular endothelial function. The equation used for shear stress estimation is τ = 4 μQ / πr ³ (Q: The derivation process of blood flow volume, r: intravascular radius, μ: viscosity coefficient) is unclear in terms of hemodynamics. Therefore, the validity of the obtained shear stress value is also unclear. In addition, the shear stress is inherently distributed such that it differs between the vascular endothelium side and the center of the axis, but the above formula can only calculate the average shear stress value in the blood vessel, and to evaluate the endothelial function Is considered insufficient.

By the way, according to a recent demographic survey of the Ministry of Health, Labor and Welfare, vascular diseases such as arteriosclerosis have the number of deaths comparable to cancer. Unstable plaque in arteriosclerosis occurs at a site with low shear stress and has a fragile structure where a large amount of lipid is covered with a thin fibrous capsule, but it suddenly fails due to large shear stress and pressure difference, resulting from thrombus formation It is known to lead to blockage. The blood flow velocity gradient and shear stress are approximately proportional to each other with the coefficient of viscosity as the coefficient, but the viscosity is associated with an increase in blood glucose level, hematocrit in the blood (polysemia), or thrombus formation (thrombosis). It is considered that the risk of unstable plaque rupture increases because the shear stress increases due to the increase, and the load on the vascular endothelium increases. That is, it can be said that shear stress and viscosity of blood are risk factors for unstable plaque failure. Currently, as a technique attracting attention for detecting unstable plaque, intravascular echo technique to coronary artery or percutaneous carotid artery echo is used to find local distortion of blood vessel wall deformed by pulsation. There is elastic imaging that diagnoses plaque instability by grasping the elasticity (hardness) of plaque. However, in order to predict the risk of plaque failure, it is necessary to know not only the tissue diagnosis but also the shear stress of blood that directly triggers the failure, or the viscosity that controls the shear stress. It is essential. Knowing the shear stress and viscosity of blood can predict the risk of plaque failure, and may be a useful index for the prevention of vascular diseases. Therefore, it is considered that meaningful diagnosis information can be provided if the shear stress and viscosity of blood can be accurately and non-invasively evaluated.

On the other hand, from the viewpoint of not only the diagnostic aspect but also the promotion of health maintenance in recent years, it is important for daily prevention of blood health to prevent vascular diseases at the individual level. For example, in smoking, thrombus formation is promoted by hematocrit, an increase in average red blood cell volume, and activation of platelets, resulting in an increase in blood viscosity. Furthermore, it is known that blood with a high blood sugar level has a high viscosity. Thus, blood properties represented by viscosity are considered useful as a daily monitoring index for lifestyle-related diseases such as arteriosclerosis and diabetes. Therefore, if the viscosity of blood can be grasped accurately and easily, it is expected that personal health management for lifestyle-related disease prevention will be promoted and, as a result, medical costs will be reduced.

For these needs, the key is to know the shear viscosity distribution and the shear stress distribution due to blood flow in addition to accurately assessing shear stress and viscosity. . As is well known, blood is a fluid mixture of blood cell components and plasma components, and the viscosity of each component is different. That is, the viscosity in blood has a distribution, and this distribution is considered to have a great influence on the failure of unstable plaque. There is a limit to discussing blood composition and evaluating blood properties from average viscosity or shear stress. Therefore, in addition to the evaluation of average viscosity and shear stress, it is considered that the above needs can be sufficiently satisfied if these distributions can be accurately known.

In view of the above problems, the object of the present invention is to divide the blood flow velocity distribution obtained by ultrasonic Doppler measurement into regions and capture the local distribution in order to capture the viscosity distribution and shear stress distribution in the blood flowing through the living body. By calculating the viscosity in each region using the 2D or 3D Navier-Stokes equation of the incompressible viscous fluid, which is assumed to be constant, and repeating this in the whole space, The purpose is to obtain a viscosity distribution.

Another object of the present invention is to calculate a shear velocity distribution from a blood flow velocity distribution obtained by ultrasonic Doppler measurement, and is Newton's law of viscosity (shear stress) = (viscosity) × (shear velocity). ) Is substituted with the calculated viscosity distribution and shear rate distribution, that is, the shear stress distribution is calculated by multiplying the viscosity distribution and shear rate distribution. The calculation of the shear stress distribution can also be obtained by multiplying the average value of the viscosity and the shear rate distribution in order to stabilize the measurement.

Another object of the present invention is not to calculate shear stress based on the Navier-Stokes equation, but to assume that the blood viscosity distribution is uniform, The purpose is to obtain a shear rate distribution and relatively grasp the shear stress distribution.

Another object of the present invention is to display an image of the obtained viscosity distribution, shear stress distribution, and shear rate distribution on the operator or examiner in real time, and at the same time, average the viscosity distribution and shear stress distribution. The value is displayed on the screen as a numerical value.

The present invention employs the following means in order to solve the above problems.
The first means percutaneously enters a wave such as an ultrasonic wave toward the blood flow in the blood vessel, receives a scattered echo from a blood cell component contained in the blood in the blood vessel, and then receives an ultrasonic Doppler. A means for measuring a blood flow velocity distribution by measurement, and using the two-dimensional or three-dimensional Navier-Stokes equation based on the measured blood flow velocity distribution, the viscosity distribution of the blood and / or the blood It is a hemodynamic characteristic measuring device characterized by comprising means for obtaining an average value of viscosity distribution of

The second means includes means for measuring the viscosity distribution of the blood in real time and displaying the image in the first means, and simultaneously displaying the average value of the viscosity distribution of the blood as a numerical value. Is a hemodynamic characteristic measuring device characterized by

The third means percutaneously enters a wave such as an ultrasonic wave toward the blood flow in the blood vessel, receives a scattered echo from a blood cell component contained in the blood in the blood vessel, and then receives an ultrasonic Doppler. Means for measuring blood flow velocity distribution by measurement, and using the two-dimensional or three-dimensional Navier-Stokes equations based on the measured blood flow velocity distribution, the viscosity distribution of the blood and / or the blood Means for calculating viscosity distribution average value, shear rate distribution calculating means for calculating shear rate distribution from the measured blood flow velocity distribution, and the calculated shear rate distribution and blood viscosity distribution or blood viscosity A hemodynamic characteristic measuring apparatus comprising: means for obtaining a shear stress distribution in blood based on a distribution average value.

According to a fourth means, in the third means, the shear stress distribution in the blood is calculated by multiplying the calculated shear rate distribution by the blood viscosity distribution or the blood viscosity distribution average value. This is a device for measuring hemodynamic characteristics.

The fifth means percutaneously enters a wave such as an ultrasonic wave toward the blood flow in the blood vessel, receives a scattered echo from a blood cell component contained in the blood in the blood vessel, and then receives an ultrasonic Doppler. Under the condition that the means for measuring the blood flow velocity distribution by measurement, the shear velocity distribution calculating means for calculating the shear velocity distribution from the measured blood flow velocity distribution, and the blood viscosity distribution is uniform, A hemodynamic characteristic measuring apparatus comprising: means for obtaining a shear stress distribution in blood from the calculated shear rate distribution.

Sixth means, in any one of the third to fifth means, the viscosity distribution of the blood and the shear stress distribution in the blood are measured and displayed in real time, A hemodynamic characteristic measuring apparatus comprising: means for displaying, as numerical values, an average value of the viscosity distribution of blood and the shear stress distribution in blood.

According to the present invention, it is possible to accurately grasp the viscosity distribution and shear stress distribution in the blood, which was difficult to capture with the conventional technology, and to display the viscosity distribution and shear stress distribution as an image. Secondary, the average value of the viscosity distribution and the shear stress distribution can be presented as numerical values to the operator or the examiner in real time.
In addition, the composition of blood such as the content ratio of blood cell component (high viscosity) and plasma component (low viscosity) can be grasped from the images of viscosity distribution and shear stress distribution. This makes it possible to accurately and easily predict the risk of plaque failure, for example, from the measurement results such as the viscosity of blood in contact with atherosclerotic plaque or the shear stress of blood flow being higher than usual. It can contribute to the prevention of vascular diseases.

It is a figure which shows the structure of the hemodynamic characteristic measuring apparatus based on invention of one Embodiment, and the flow of the whole process of this apparatus. It is a figure which shows the detailed structure of the viscosity distribution calculation part 5 shown in FIG. It is a figure which shows the specific example in the viscosity distribution calculation part 5 shown in FIG. It is a figure which shows the detailed structure of the shear stress distribution calculation part 9 shown in FIG. It is a figure which shows the specific example in the shear stress distribution calculation part 9 shown in FIG. It is a figure which shows the detailed structure of the shear rate distribution calculation part 7 in FIG. It is a figure which shows the specific example of the shear velocity distribution calculation part 7 shown in FIG. It is a figure which shows the example of a measurement of the time series data of a viscosity, shear stress, and shear rate using electrocardiogram synchronization.

  An embodiment of the present invention will be described below with reference to FIGS.

FIG. 1 is a diagram showing a configuration of a hemodynamic characteristic measuring apparatus according to the invention of the present embodiment and a flow of processing of the entire apparatus.
In the figure, reference numeral 1 denotes an ultrasonic probe used for rendering a tomographic surface of a living body and measuring a blood flow velocity distribution in a blood vessel, and is generated by generating ultrasonic waves from a one-dimensional array or a two-dimensional array on the probe surface. The incident light enters the body and receives the scattered wave from the blood cell in the blood vessel 2 to be measured and the scattered wave from the tissue surrounding the blood vessel 3 through the same element. And blood flow velocity distribution measurement.

A velocity distribution measuring unit 4 creates a tomographic image by using the ultrasonic scattered wave received via the ultrasonic probe 1 to identify the blood vessel position, and at the same time, within the two-dimensional tomographic plane or three-dimensionally. A two-dimensional velocity vector distribution or a three-dimensional velocity vector distribution in space is obtained. Here, the two-dimensional velocity vector distribution or the three-dimensional velocity vector distribution is obtained by using, for example, two ultrasonic tomographic images or two ultrasonic three-dimensional volume images that are temporally continuous at a certain time interval. The amount of movement can be obtained by a correlation method and can be obtained by dividing the amount of movement by the time interval between two images. Alternatively, if it is limited to obtaining a two-dimensional velocity vector distribution, ultrasonic doppler method is used to continuously irradiate blood cells with ultrasonic waves, and the amount of movement of adjacent scattered waves continuously received is divided by the ultrasonic irradiation time interval. Then, the velocity component in the ultrasonic irradiation direction, which is one velocity component of the two-dimensional velocity vector, is obtained, and the other velocity component orthogonal thereto is obtained using the incompressible condition in the fluid dynamics to obtain a complete two-dimensional A velocity vector distribution can also be obtained.

Reference numeral 5 denotes a viscosity distribution calculating unit that calculates the distribution of the viscosity of blood in the blood vessel 2 to be measured based on a two-dimensional or three-dimensional Navier-Stokes equation. For calculating the viscosity distribution, a velocity distribution measuring unit 4 is used. The two-dimensional velocity vector distribution or the three-dimensional velocity vector distribution obtained in (1) is used.

Reference numeral 6 denotes a viscosity distribution average value calculation unit for obtaining a spatial average value of the viscosity distribution obtained by the viscosity distribution calculation unit 5, and the viscosity distribution calculation unit 5 spatially calculates the blood viscosity. The viscosity distribution average value calculation unit 6 is a part for quantitatively grasping the blood viscosity value while it is a part for recognizing the pattern.

Reference numeral 7 denotes a shear velocity distribution calculation unit that calculates a shear velocity distribution using the two-dimensional velocity vector distribution or the three-dimensional velocity vector distribution obtained by the velocity distribution measuring unit 4. Specifically, the shear velocity distribution calculation unit 7 obtains a two-dimensional or three-dimensional strain rate tensor based on the two-dimensional velocity vector distribution or the three-dimensional velocity vector distribution, and extracts a shear component from the tensor components. To calculate the shear rate distribution. Assuming that the viscosity of blood is spatially uniform, the shear rate distribution is proportional to the shear stress distribution. Therefore, the shear rate distribution can be directly used as a relative evaluation of the shear stress distribution.

8 is a shear rate distribution average value calculating unit for obtaining a spatial average value of the shear rate distribution obtained by the shear rate distribution calculating unit 7, and the shear rate distribution calculating unit 7 spatially calculates the shear rate due to blood flow. On the other hand, the shear rate distribution average value calculation unit 8 is a part for quantitatively grasping the blood flow shear rate value.

Reference numeral 9 denotes a shear stress distribution calculation unit that calculates a shear stress distribution based on the Newtonian viscosity law formula: (shear stress) = (viscosity) × (shear rate). As the viscosity, a value obtained by the viscosity distribution calculation unit 5 or the viscosity distribution average value calculation unit 6 on the assumption that the viscosity is uniform is used. Further, as the shear rate, the shear rate distribution obtained by the shear rate distribution calculating unit 7 is used. A shear stress distribution is calculated using the viscosity distribution (or viscosity distribution average value) and the shear rate distribution thus obtained.

10 A shear stress distribution average value calculation unit for obtaining a spatial average value of the shear stress distribution obtained by the shear stress distribution calculation unit 9. The shear stress distribution calculation unit 9 is a part for recognizing a spatial pattern of shear stress due to blood flow, whereas the shear stress distribution average value calculation unit 10 quantitatively grasps the blood flow shear stress value. It is a part of.

Reference numeral 11 denotes a blood viscosity obtained by the viscosity distribution calculation unit 5 based on a two-dimensional or three-dimensional Navier-Stokes equation on a blood vessel lumen drawn by an ultrasonic tomographic image for identifying a blood vessel position. This is a display unit that superimposes each of the rate distribution, the shear rate distribution obtained by the shear rate distribution calculation unit 7, or the shear stress distribution obtained by the shear stress distribution calculation unit 9 to display an image. Each of these distribution images can be switched and displayed on the display unit 11. At the same time, the viscosity distribution average value obtained by the viscosity distribution average value calculation unit 6, the shear rate distribution average value obtained by the shear rate distribution average value calculation unit 8, or the shear stress distribution average value calculation unit 10. Can be displayed as a quantitative numerical value on the screen of the display unit 11.

Next, the operation of the hemodynamic characteristic measuring apparatus according to the present invention will be described.
First, in order to obtain non-invasive blood viscosity distribution, shear rate distribution, shear stress distribution, and viscosity distribution average value, shear rate distribution average value, and shear stress distribution average value from the body surface of the living body described above. Then, the ultrasonic probe 1 used for rendering the tomographic surface of the living body and measuring the blood flow velocity distribution in the blood vessel is placed on the body surface and brought into contact therewith. On the probe surface, an ultrasonic wave is generated from a one-dimensional array or a two-dimensional array element and is incident on a living body, and a scattered wave from a blood cell in the blood vessel 2 to be measured and a scattered wave from a tissue around the blood vessel 3 are Receive via the same element. The received scattered wave is used for tomographic plane configuration and blood flow velocity distribution measurement.

The velocity distribution measurement unit 4 creates a tomographic image by using the ultrasonic scattered wave received via the ultrasonic probe 1 in which the elements are arranged one-dimensionally or two-dimensionally and identifies the blood vessel position. A two-dimensional velocity vector distribution in a three-dimensional tomographic plane or a three-dimensional velocity vector distribution in a three-dimensional space is obtained. Two-dimensional velocity vector distribution or three-dimensional velocity vector distribution correlates the amount of movement of blood cells using, for example, two ultrasonic tomographic images or two ultrasonic three-dimensional volume images that are temporally continuous at a certain time interval. It can be obtained by the method and divided by the time interval between the two images.

Alternatively, if it is limited to obtaining a two-dimensional velocity vector distribution, ultrasonic doppler method is used to continuously irradiate blood cells with ultrasonic waves, and the amount of movement of adjacent scattered waves received continuously is measured at intervals of ultrasonic irradiation time. By dividing, a velocity component in the ultrasonic irradiation direction, which is one velocity component of the two-dimensional velocity vector, is obtained, and the other velocity component orthogonal thereto is obtained by using an incompressible condition in fluid mechanics. A dimensional velocity vector distribution can also be obtained.

Since the two-dimensional velocity vector distribution or the three-dimensional velocity vector distribution obtained here can be obtained by repeating the measurement continuously in time, the velocity distribution measuring unit 4 can obtain the two-dimensional velocity vector distribution or the three-dimensional velocity vector distribution. A time series of dimensional velocity vector distribution can be obtained.

In particular, as a method for obtaining the two-dimensional velocity vector distribution other than the application of the correlation method in the velocity distribution measuring unit 4, the non-compressive condition of fluid dynamics can be used as described above. At this time, an ultrasonic Doppler method is used as a measuring means. As described above, the velocity component obtained by this ultrasonic Doppler method is only one component of the two-dimensional velocity vector in the ultrasonic beam irradiation direction. is there. If a velocity component orthogonal to this is obtained, a two-dimensional velocity vector is obtained, but an uncompressed condition can be used to calculate this. In the present invention, since it is assumed that blood is an incompressible fluid, the following incompressible condition is satisfied for a two-dimensional velocity vector component at a place where the blood flow velocity field reaches.

Here, it is assumed that v is a velocity component measured by the ultrasonic Doppler method, and that another velocity component u orthogonal to v is calculated. If equation 1 is integrated with respect to x, the following integral equation for u can be derived.

This equation shows that if one speed component is known, the other speed component can be calculated using non-compression conditions. That is, if the distribution of the velocity component v in the ultrasonic beam irradiation direction can be obtained by the ultrasonic Doppler method, the distribution of the other velocity component u orthogonal to it can be calculated. Therefore, it is possible to calculate the two-dimensional velocity vector distribution based on the velocity measurement result by the ultrasonic Doppler method and Equation 2, but since Equation 2 includes integration, the velocity distribution region to be obtained covers a wide range. In some cases, error propagation due to noise causes insufficient calculation stability, and it is necessary to appropriately provide an initial value u (x ₀ , y) of u. In preparation for such a case, it is also possible to calculate u by an iterative method based on the uncompressed conditional expression of Expression 1. Based on Equation 1, the following iterative equation is used to calculate u based on the distribution of v measured by the ultrasonic Doppler method.

Here, v is a beam axis direction component, u is a velocity component orthogonal to the azimuth direction component, i and j are lattice points, Δx and Δy are lattice point intervals, and k is a repetition index. The initial value of u is given as follows because the angle between the beam axis direction and the tube axis is known.
In the case of a unidirectional flow, the velocity component in the azimuth direction can be estimated based on Equation 4, but it is generally difficult to approximate the blood flow in the blood vessel with the unidirectional flow. Therefore, it is effective to obtain Equation 4 while correcting u by Equation 3, using Equation 4 as an initial value in the iterative equation. The convergence of Equation 3 is confirmed by experimental data, that is, Equation 3 is effective in calculating u.

FIG. 2 is a diagram showing a detailed configuration of the viscosity distribution calculator 5 shown in FIG.
In the figure, reference numeral 12 denotes a velocity distribution sub-region dividing unit having a function of dividing the two-dimensional velocity vector distribution or the three-dimensional velocity vector distribution obtained by the velocity distribution measuring unit 4 into fine sub-regions 13. . In the present invention, the viscosity is calculated on the basis of the two-dimensional or three-dimensional Navier-Stokes equations, and since the blood is assumed to be incompressible, the viscosity is calculated as spatially unique. . However, blood is a mixed fluid such as red blood cells and platelets, and the viscosity is not unique and has a distribution. In order to obtain this distribution, the viscosity is calculated by assuming that the viscosity is uniform in the sub-region 13 within the sub-region 13. By repeating this operation for all divided sub-regions 13, a viscosity distribution is obtained.

Reference numeral 14 denotes a viscosity calculation unit, which calculates the viscosity based on a two-dimensional or three-dimensional Navier-Stokes equation, assuming that the viscosity is uniform in the sub-region 13. The viscosity calculation formula when the three-dimensional velocity vector distribution is used is based on Formula 8, 9, or 10, and the viscosity calculation formula when the two-dimensional velocity vector distribution is used is Formula 13. Based on.

Reference numeral 15 denotes a viscosity distribution component (sub-region integration), in which the viscosity in all the sub-regions 13 obtained by the viscosity-calculation unit 14 is embedded in the original sub-region position and integrated. It constitutes the distribution.

Here, the viscosity is the two-dimensional velocity vector distribution or time series of the three-dimensional velocity vector distribution calculated by the velocity distribution measuring unit 4 and the two-dimensional when the blood is assumed to be an incompressible viscous fluid. Alternatively, it is obtained based on the three-dimensional Navier-Stokes equation.

First, a viscosity calculation method based on a time series of a three-dimensional velocity vector distribution will be described. When the three orthogonal components of the time series of the three-dimensional velocity vector distribution obtained by the correlation method or the like in the velocity distribution measuring unit 4 are u, v, and w, the three-dimensional Navier-Stokes equations are as follows in the orthogonal coordinate system (xyz): Can be described as follows.
Here, t: time, ρ: density, p: pressure, ν: kinematic viscosity, the ratio of the viscosity μ and the density ρ, and ν = μ / ρ. Further, u, notation such as _x represents the partially differentiating the u at x, and so forth. That is, if the velocity vector components u, v, and w are known, the Navier-Stokes equation can be regarded as an equation including the pressure p and the kinematic viscosity ν as unknowns. From these equations, in order to obtain the kinematic viscosity ν, the differential operation is performed using two of the three equations as in the equations 5 and 6, or the equations 6 and 7, or the equations 7 and 5. Deletes the term including the pressure p.

That is, from equations 5 and 6, the kinematic viscosity ν can be obtained as equation 8 with ξ = v _{, x} -u _{, y} .
Similarly, from equations 6 and 7, the kinematic viscosity ν is obtained as equation 9 with η = w _{, y} −v _{, z} .
Similarly, from equations 7 and 5, the kinematic viscosity ν can be obtained as equation 10 with ω = u _{, z} -w _{, x} .

As described above, the kinematic viscosity ν can be calculated only from the time series of the three-dimensional velocity vector distribution by using two of the three expressions of the three-dimensional Navier-Stokes equation. The kinematic viscosity ν can be used as an alternative to viscosity calculation by obtaining the kinematic viscosity distribution and the kinematic viscosity distribution average value as physical quantities representing the viscosity of blood. That is, hereinafter, the term "viscosity" includes this kinematic viscosity calculation. Further, the viscosity can be obtained by multiplying the kinematic viscosity calculated by Expression 8, 9 or 10 by a known blood density. From the above, the basic principle of viscosity calculation in the present invention is Expression 8, Expression 9, or Expression 10.

On the other hand, since it is assumed that blood is an incompressible viscous fluid, the viscosity is obtained as a spatially single value (a value according to the average value of the viscosity distribution in the space). The viscosity distribution cannot be calculated. Therefore, in order to calculate the viscosity distribution, the three-dimensional velocity vector distribution calculated by the velocity distribution measuring unit 4 is divided into sub-regions 13 in a two-dimensional or three-dimensional space region using the velocity distribution sub-region dividing unit 12. Then, the viscosity (or kinematic viscosity is included) is calculated by applying the viscosity calculation unit 14 using Expression 8, 9, or 10 to each local sub-region 13. In this way, the viscosity in all the sub-regions 13 is obtained, and in the viscosity distribution component (sub-region integration) 15, the viscosity in the sub-region 13 is spatially rearranged and integrated. A rate distribution can be obtained. This is the basic principle of viscosity distribution calculation in the present invention.

Since Expression 8, 9 or 10 indicates that the viscosity can be calculated using the local blood flow velocity distribution, the viscosity distribution can be calculated based on the above-described concept. Further, since the viscosity distribution is obtained by using a time series of a three-dimensional velocity vector distribution, it is possible to obtain the time series of the viscosity distribution by repeating this process in terms of time. Furthermore, since Equation 8, or Equation 9, or Equation 10 is obtained from a three-dimensional velocity vector component, not only a linear blood vessel such as a carotid artery but also a subject having a three-dimensional blood flow distribution such as a heart. It can also be applied to.

The above is a description of a method for calculating a viscosity distribution using a three-dimensional velocity vector distribution. When it is difficult to obtain a three-dimensional velocity vector, a practical two-dimensional Navier-Stokes equation is used. However, it is possible to calculate the viscosity distribution of blood. As in the case of using the three-dimensional Navier-Stokes equation, it is assumed that the blood is an incompressible viscous fluid, and a two-dimensional flow, that is, a flow in which a velocity vector exists only in a cross section is handled. At this time, the two-dimensional Navier-Stokes equation for the incompressible viscous fluid can be described as follows.

Here, u and v are orthogonal components of the two-dimensional velocity vector in the same cross section, p is pressure, ρ and ν are density and kinematic viscosity (ν = μ / ρ, μ is viscosity), Since a compressible fluid is assumed, ρ and ν can be regarded as constants. If the velocity distribution measuring unit 4 obtains a time series of two-dimensional velocity vectors by the correlation method or the above-described method using the uncompressed condition, the unknown parameters are density, pressure, and kinematic viscosity. However, in order to obtain the kinematic viscosity ν, the equation 11 is differentiated by y and the equation 12 is differentiated by x, then the pressure term is eliminated, and the vorticity transport equation is derived using the incompressible condition and then ν is obtained. When solved, it is obtained as follows using ξ as the vorticity.

Where vorticity is
Is an amount obtained from a two-dimensional velocity vector component. That is, the kinematic viscosity ν of blood satisfying the two-dimensional Navier-Stokes equation is obtained by measuring the time change of the two-dimensional velocity field of the blood flow having vorticity, that is, the time series of the two-dimensional velocity vector distribution. It will be. Similar to the explanation of the viscosity using the three-dimensional Navier-Stokes equation, the kinematic viscosity calculated by the equation 13 calculates the kinematic viscosity distribution and the kinematic viscosity distribution average value as physical quantities representing the viscosity of blood. It can be used as an alternative to viscosity calculation. That is, hereinafter, the term "viscosity" includes this kinematic viscosity calculation. Further, even in the case of two dimensions, the viscosity can be calculated by multiplying the kinematic viscosity calculated by Equation 13 and a known blood density. From the above, in the present invention, the basic principle of viscosity calculation based on the two-dimensional Navier-Stokes equation is expressed by Equation 13.

On the other hand, even when the two-dimensional Navier-Stokes equation is used, it is assumed that the blood is an incompressible viscous fluid, and the viscosity is obtained as one spatial value. Cannot be calculated. Therefore, the above-described three-dimensional method can be used as a method for calculating the viscosity distribution. That is, the two-dimensional velocity vector distribution calculated in the velocity distribution measuring unit 4 is divided into sub-regions in the two-dimensional cross-sectional region using the velocity distribution sub-region dividing unit 12, and the viscosity coefficient is determined in each local sub-region. The calculation unit 14 applies Equation 13 to calculate the viscosity (or kinematic viscosity). In this way, the viscosity in all the sub-regions 13 is obtained, and in the viscosity distribution component (sub-region integration) 15, the viscosity in the sub-region 13 is spatially rearranged and integrated. A two-dimensional distribution of rates can be obtained. This is the basic principle for calculating the viscosity distribution when the two-dimensional Navier-Stokes equation is used in the present invention. Since Expression 13 indicates that the viscosity can be calculated using the local blood flow velocity distribution, the two-dimensional distribution of the viscosity can be calculated based on the above-described concept. Further, since the viscosity distribution is obtained using a time series of two-dimensional velocity vector distribution, it is possible to obtain the time series of the viscosity distribution by repeating this process in time.

As described above, the viscosity distribution calculation unit 5 based on the two-dimensional or three-dimensional Navier-Stokes equation uses the time series of the two-dimensional velocity vector distribution or the time series of the three-dimensional velocity vector distribution to calculate the viscosity. While it is possible to obtain a two-dimensional distribution or a three-dimensional distribution, the viscosity distribution average value calculation unit 6 can also obtain a spatial average value of these viscosity distributions as a numerical value. Furthermore, since the time series of the viscosity distribution can be obtained, it is naturally possible to obtain the time series of the viscosity distribution average value.

FIG. 3 is a diagram showing a specific example in the viscosity distribution calculator 5 shown in FIG.
In the figure, 16 is a cross-sectional view of a two-dimensional velocity vector distribution or a three-dimensional velocity vector distribution obtained by the velocity distribution measurement unit 4, and 17 is a viscosity coefficient in all sub-regions 13 obtained by the viscosity calculation unit 14. On the other hand, a cross-sectional view of the viscosity distribution obtained through the viscosity distribution component (sub-region integration) 15, and 18 is the viscosity distribution average value calculated by the viscosity distribution average value calculator 6.

As shown in the figure, the two-dimensional velocity vector distribution or the three-dimensional velocity vector distribution 16 calculated by the velocity distribution measuring unit 4 is divided into sub-regions 13 surrounded by broken lines in the velocity distribution sub-region dividing unit 12. Then, the viscosity is calculated by the viscosity calculator 14 in each sub-region 13. When the viscosity calculation unit 14 is based on the three-dimensional velocity vector distribution, the viscosity is obtained using the equation 8, 9, or 10, and when the viscosity is based on the two-dimensional velocity vector distribution, the equation 13 is used to determine the viscosity. The viscosity value in each sub-region 13 calculated by the viscosity calculation unit 14 is rearranged and integrated in the original sub-region 13 in the viscosity distribution component (sub-region integration) 15 to obtain the final viscosity. A rate distribution 17 is obtained. At the same time, since the viscosity value calculated from the viscosity calculation unit 14 is a local value in the blood, the viscosity distribution average value calculation unit 6 calculates the viscosity distribution average value 18.

FIG. 3 shows the calculation of the viscosity distribution and the average viscosity distribution at a certain moment, but by repeating this process in time, the time series of the viscosity distribution, And a time series of viscosity distribution average values.

Regarding the viscosity distribution calculation method, for example, the validity of Equation 13 in the two-dimensional case was examined by computer simulation. In this case, based on the kinematic viscosity of the actual blood (0.03 cm ² / s), to 0.002cm ² /s~0.04cm ² / s, the case of giving a kinematic viscosity that increases or decreases the viscosity, Navier -Flow analysis based on the Stokes equation was performed, and the kinematic viscosity was estimated using Equation 13 with reference to only the obtained two-dimensional velocity vector distribution. As a result of calculating the kinematic viscosity by finely changing the kinematic viscosity by 0.002 cm ² / s, the mean square error of the calculated viscosity value was 1.8% with respect to the true viscosity. That is, if the flow follows the Navier-Stokes equation and the two-dimensional velocity vector distribution can be obtained with high accuracy, it was confirmed that the viscosity value can be calculated with high accuracy according to the present invention.

FIG. 4 is a diagram showing a detailed configuration of the shear stress distribution calculation unit 9 shown in FIG.
As shown in the figure, in the shear rate distribution calculation unit 9, the viscosity distribution of blood calculated in the viscosity distribution calculation unit 5 or the viscosity distribution average value calculated in the viscosity distribution average value calculation unit 6; By inputting the shear rate distribution calculated in the shear rate distribution calculating unit 7, according to Newton's law of viscosity, (shear stress distribution) = (viscosity distribution) × (shear rate distribution) or (shear stress distribution) = (Viscosity distribution average value) × (shear rate distribution) is calculated to calculate a shear stress distribution.

Here, instead of the viscosity distribution, the average value of the viscosity distribution can be applied in order to stabilize the measurement. Naturally, the shear stress distribution calculation using the viscosity distribution can obtain a higher accuracy and a detailed shear stress distribution than the shear stress distribution calculation using the average viscosity distribution.
As for the shear stress distribution obtained in this way, the shear stress distribution average value calculation unit 10 can obtain the shear stress distribution average value. It is also possible to obtain a shear stress distribution time series based on the same concept as the calculation of the viscosity distribution time series.

FIG. 5 is a diagram showing a specific example in the shear stress distribution calculation unit 9 shown in FIG.
In the figure, 19 is a cross-sectional view of the shear rate distribution obtained by the shear rate distribution calculation unit 7, 20 is a cross-sectional view of the 20 shear stress distribution, and 21 is an average shear stress distribution obtained by the shear stress distribution average value calculation unit 10. A value 22 is a shear stress calculation unit that calculates shear stress for each sub-region 13 by multiplication of the viscosity obtained for each sub-region 13 and the shear rate according to Newton's viscosity law.
In typical hemodynamics, a large shear stress is generated on the vascular endothelium side. However, by appropriately calculating the shear stress distribution in the shear stress distribution calculating unit 9, it is possible to evaluate the shear stress distribution quantitatively.

For the calculation of the shear stress distribution, the viscosity distribution 17 obtained by the viscosity distribution calculation unit 5 or the viscosity distribution average value 18 obtained by the viscosity distribution average value calculation unit 6 and the shear rate distribution calculation unit 7 are used. The shear velocity distribution 19 obtained in (1) is used. The viscosity distribution 17 and the shear velocity distribution 19 are divided into sub-regions 13, and in each sub-region 13, the shear stress calculation unit 22 applies Newton's viscosity law formula to calculate viscosity × shear velocity. Thus, the shear stress is calculated for each sub-region 13. The shear stress calculated for each sub-region 13 is rearranged and integrated in the original sub-region 13 to obtain a shear stress distribution 20. Furthermore, the shear stress distribution average value 21 can be calculated by averaging the shear stress obtained for each sub-region 13 by the shear stress distribution average value calculation unit 10.

The specific example shown in FIG. 5 shows the calculation of shear stress distribution and the average calculation of shear stress distribution at a certain moment. By repeating this process repeatedly in time, the shear stress distribution is calculated. The time series of the series and the shear stress distribution average value can be obtained.

FIG. 6 is a diagram showing a detailed configuration of the shear velocity distribution calculation unit 7 in FIG.
In the figure, a two-dimensional velocity obtained by the velocity distribution measuring unit 4 is a velocity component distribution derivative calculating unit for differentiating the velocity component distribution in order to obtain a strain velocity distribution necessary for calculating the 23 shear velocity distribution. Spatial differentiation is performed on the vector distribution or the three-dimensional velocity vector distribution.

Reference numeral 24 denotes a strain rate tensor distribution calculation unit, which performs addition processing on the differentiation of the two-dimensional velocity vector or the three-dimensional velocity vector component obtained by the velocity component distribution derivative calculation unit 23 to obtain a two-dimensional or three-dimensional value. Find the strain rate tensor component of the dimension.

25, which is a shear rate distribution extraction unit, extracts only the shear rate component from the strain rate tensor distribution obtained by the strain rate tensor distribution calculation unit 25, and obtains the shear rate degree distribution.

The shear rate distribution calculation unit 7 calculates the shear rate distribution necessary for the shear stress distribution calculation unit 9, but in the case where the Navier-Stokes equation does not hold, the shear stress distribution even in such a case. It is also possible to replace the shear rate distribution proportional to the shear stress distribution when the blood viscosity distribution is uniform, as a relative shear stress distribution.

In order to calculate the shear velocity distribution in the shear velocity distribution calculation unit 7, first, a velocity component distribution differential calculation unit is applied to the two-dimensional velocity vector distribution or the three-dimensional velocity vector distribution obtained by the velocity distribution measurement unit 4. 23, the velocity vector component is spatially differentiated, and the strain rate tensor distribution calculation unit 24 calculates the strain rate tensor. The three-dimensional strain rate tensor when the three-dimensional velocity vector distribution is used is obtained as in Equations 15a to 15f.
Here, e _xx , e _yy , e _zz , e _xy , e _yz , and e _zx represent six components in a symmetric strain rate tensor. e _xx , e _yy , and e _zz indicate normal strain rate tensor components, and e _xy , e _yz , and e _zx indicate shear strain rate tensor components.

Note that the two-dimensional strain rate tensor when the two-dimensional velocity vector distribution is used is obtained as Equations 15a, 15b, and 15c.
A shear rate distribution extracting unit 25 extracts a shear component from the strain rate tensor obtained as in the formulas 15a to 15f, and the shear rate distribution in the three-dimensional case is expressed by the formulas 15d to 15f and the two-dimensional case. Equation 15d is obtained for the shear velocity distribution. That is, from being determined as the shear rate component in the case of three dimensions, e _xy, e _yz, an e _zx, being asked as shear rate component in the case of the two-dimensional is e _xy. Further, it is possible to calculate the shear rate distribution average value by applying the shear rate distribution average value calculation unit 8 to the shear rate distribution thus obtained. It is also possible to obtain the shear rate distribution time series based on the same concept as the calculation of the viscosity distribution time series.

FIG. 7 is a diagram showing a specific example of the shear velocity distribution calculation unit 7 shown in FIG.
In the figure, reference numeral 26 denotes a shear rate calculation unit for calculating a shear rate for each sub-region 13, and 27 is a shear rate distribution average value obtained by the 27 shear rate distribution average value calculation unit 8.
The two-dimensional velocity vector distribution or the three-dimensional velocity vector distribution 16 obtained by the velocity distribution measuring unit 4 is divided into sub-regions 13, and for each sub-region 13, the shear velocity calculating unit 26 Calculate the shear rate. The shear rate obtained here is calculated based on Equation 15d to Equation 15f when the three-dimensional velocity vector distribution is targeted, and based on Equation 15d when the two-dimensional velocity vector distribution is targeted. The shear rate distribution 19 can be obtained by rearranging and integrating the shear rate values calculated in all the sub-regions in the original sub-region. Further, the shear velocity distribution average value 27 can be calculated by averaging the shear velocity obtained in all the sub-regions in the shear velocity distribution average value calculating unit 8. is there.

The specific example shown in FIG. 7 shows the calculation of the shear rate distribution and the average value of the shear rate distribution at a certain moment. By repeating this process in time, the shear rate distribution is calculated. The time series of the series and the shear speed distribution average value can be obtained.

The algorithm for calculating the viscosity distribution according to the present invention can be applied unconditionally to a Newtonian fluid in which a two-dimensional or three-dimensional Navier-Stokes equation is established. A Newtonian fluid is a fluid in which shear stress and shear rate are in a linear relationship. Blood is a non-Newtonian fluid in which shear stress and shear rate are in a non-linear relationship, but even if it is in a non-linear relationship as a whole, it can be regarded as having a linear relationship if divided finely. Therefore, the viscosity distribution calculation algorithm according to the present invention can be applied to a non-Newtonian fluid such as blood in a time interval in which a small shear rate is added and shear stress and shear rate can be regarded as a linear relationship. In the measurement of peripheral blood vessels with few pulsations, it can be applied as described above, but when calculating the viscosity distribution in blood vessels with pulsation, the viscosity calculated by the time phase of pulsation It can happen that the magnitude of is periodically changed. This is shown in FIG.

FIG. 8 is a diagram illustrating a measurement example for time-series data of viscosity, shear stress, and shear rate using electrocardiographic synchronization.
Reference numeral 28 denotes a blood flow velocity waveform displaying only one component of the time series of the three-dimensional velocity vector distribution obtained by the velocity distribution measuring unit 4 or the time series of the two-dimensional velocity vector distribution.

29 is an example showing the time series of the shear rate distribution, viscosity distribution, and shear stress distribution calculated by the present invention. A portion with a symbol indicates a time phase extracted by the extraction unit 30 for shear rate, viscosity, and shear stress by electrocardiographic synchronization.

30 is an extraction unit for shear rate, viscosity, and shear stress synchronized with the electrocardiogram, which extracts the shear rate, viscosity, and shear stress in the time phase indicated by the location indicated by the symbol by taking an electrocardiogram. .

31 is a chronological arrangement of the shear rate, viscosity, and shear stress extracted by the extraction unit 30 for shear rate, viscosity, and shear stress synchronized with electrocardiogram. Since the viscosity and shear stress can be grasped almost constant, stable evaluation becomes possible.

As shown in the figure, the blood under pulsation is observed such that the viscosity changes with time due to its non-Newtonian nature, but for the time series data of viscosity, shear stress, shear rate, By applying electrocardiographic synchronization by the shear rate / viscosity / shear stress extraction unit 30, the viscosity distribution when the same shear rate is applied can be calculated. That is, even when there is a pulsation, by applying electrocardiogram synchronization, the viscosity distribution calculation algorithm according to the present invention can always calculate the viscosity distribution under the same conditions and is affected by the pulsation. It is possible to calculate the viscosity distribution of blood and its spatial average value.

As described above, the hemodynamic characteristic measurement device for viscosity distribution, shear stress distribution, and shear rate distribution according to the present invention is an existing ultrasonic diagnostic device for diagnosing and predicting the risk of atherosclerotic plaque failure. It can be installed as a new measurement function. Further, by downsizing the measuring device for viscosity distribution, shear rate distribution, and shear stress distribution, it can be used as an individual's daily health management device (home health care device).

DESCRIPTION OF SYMBOLS 1 Ultrasonic probe 2 Measurement target blood vessel 3 Vessel surrounding tissue 4 Velocity distribution measurement unit 5 Viscosity distribution calculation unit 6 Viscosity distribution average value calculation unit 7 Shear velocity distribution calculation unit 8 Shear velocity distribution average value calculation unit 9 Shear stress distribution calculation Unit 10 Shear stress distribution average value calculation unit 11 Display unit 12 Speed distribution sub-region division unit 13 Sub-region 14 Viscosity calculation unit 15 Viscosity distribution component (sub-region integration)
16 Cross-sectional diagram of two-dimensional velocity vector distribution or three-dimensional velocity vector distribution 17 Cross-sectional diagram of viscosity distribution 18 Viscosity distribution average value 19 Cross-sectional diagram of shear velocity distribution 20 Cross-sectional diagram of shear stress distribution 21 Shear stress distribution average value 22 Shear Stress calculation unit 23 Speed component distribution differentiation calculation unit 24 Strain rate tensor distribution calculation unit 25 Shear rate distribution extraction unit 26 Shear rate calculation unit 27 Shear rate distribution average value 28 Blood flow rate waveform 29 Shear rate distribution, viscosity distribution, shear stress Time series of distribution 30 Extraction unit 31 of shear rate / viscosity / shear stress by synchronization with electrocardiogram Shear rate / viscosity / shear stress extracted and arranged in time series

Claims (2)

The blood flow velocity distribution is measured by ultrasonic Doppler measurement after receiving waves such as ultrasonic waves percutaneously toward the blood flow in the blood vessel and receiving scattered echoes from blood cell components contained in the blood in the blood vessel. The calculated shear rate under the condition that the shear rate distribution calculating unit calculates the shear rate distribution from the measured blood flow rate distribution and the blood viscosity distribution is uniform. A hemodynamic characteristic measuring apparatus comprising: means for obtaining a shear stress distribution in blood from the distribution. Means for measuring the viscosity distribution of the blood and the shear stress distribution in the blood in real time and displaying the image, and simultaneously displaying the average value of the viscosity distribution of the blood and the shear stress distribution in the blood as numerical values; The hemodynamic characteristic measuring apparatus according to claim 1, comprising: