JP7534185B2 - Analysis device and ultrasound diagnostic device - Google Patents

Description

Embodiments of the present invention relate to an analysis device and an ultrasound diagnostic device.

In recent years, a technology called elastography has been proposed for imaging the distribution of stiffness in biological tissues in various medical imaging diagnostic devices. As an example, shear wave elastography (SWE) is used in ultrasound diagnostic devices, which displays stiffness images by measuring the propagation speed of shear waves generated by push pulses. SWE is one of the very useful quantification techniques for, for example, diffuse liver disease.

In SWE, shear waves have the tendency to be reflected at the boundary between tissues of different stiffness. These reflected shear waves are superimposed on the shear waves generated directly from the push pulse, causing a change in the contour of the displacement waveform. This change in contour adversely affects the accuracy of estimation when estimating the displacement lag (time lag), preventing stable stiffness measurement.

JP 2015-054056 A JP 2015-131097 A

The problem that the present invention aims to solve is to provide an analysis device and an ultrasound diagnostic device that can support stable measurement of the hardness of biological tissue.

The analysis device according to the embodiment includes a detection unit, a calculation unit, and an output control unit. The detection unit detects tissue movement at each of a plurality of positions within the subject by analyzing scan data collected by transmitting a first ultrasonic wave for generating shear waves and transmitting and receiving a second ultrasonic wave for observing the shear waves. The calculation unit calculates an index value related to waveform information representing a time series change in the movement of the tissue at each of the plurality of positions based on the movement of the tissue. The output control unit outputs the index value.

FIG. 1 is a block diagram showing an example of the configuration of an ultrasound diagnostic apparatus 1 according to the first embodiment. FIG. 2 is a diagram for explaining reflection of a shear wave. FIG. 3 is a diagram for explaining reflection of a shear wave. FIG. 4 is a diagram showing an example of a stiffness image according to the first embodiment. FIG. 5 is a diagram for explaining the process of the calculation function according to the first embodiment. FIG. 6 is a diagram for explaining the process of the calculation function according to the first embodiment. FIG. 7 is a diagram for explaining the process of the calculation function according to the first embodiment. FIG. 8 is a diagram for explaining the process of the calculation function according to the first embodiment. FIG. 9 is a diagram for explaining the process of the calculation function according to the first embodiment. FIG. 10 is a diagram for explaining the process of the calculation function according to the first embodiment. FIG. 11 is a diagram for explaining the process of the generation function according to the first embodiment. FIG. 12 is a diagram for explaining the process of the output control function according to the first embodiment. FIG. 13 is a flowchart showing a processing procedure performed by the ultrasound diagnostic apparatus according to the first embodiment. FIG. 14 is a diagram for explaining the process of the calculation function according to the third modification of the first embodiment. FIG. 15 is a diagram for explaining the process of the calculation function according to the fifth modification of the first embodiment. FIG. 16 is a diagram for explaining the process of the generation function according to the second embodiment. FIG. 17 is a diagram for explaining the process of the generation function according to the second embodiment. FIG. 18 is a block diagram illustrating an example of the configuration of an analysis device according to another embodiment.

Below, an analysis device and an ultrasound diagnostic device according to an embodiment will be described with reference to the drawings. In the following embodiment, an ultrasound diagnostic device will be described as an example of an analysis device, but the embodiment is not limited to this. For example, in addition to an ultrasound diagnostic device, medical information processing devices capable of processing a group of scan data collected by ultrasound scanning, such as personal computers, workstations, and PACS (Picture Archiving Communication System) viewers, can be used as the analysis device.

First Embodiment
Fig. 1 is a block diagram showing an example of the configuration of an ultrasound diagnostic apparatus 1 according to the first embodiment. As shown in Fig. 1, the ultrasound diagnostic apparatus 1 according to the first embodiment includes an apparatus main body 100, an ultrasound probe 101, an input interface 102, and a display 103. The ultrasound probe 101, the input interface 102, and the display 103 are connected to the apparatus main body 100. Note that a subject P is not included in the configuration of the ultrasound diagnostic apparatus 1.

The ultrasonic probe 101 has multiple transducers (e.g., piezoelectric transducers), which generate ultrasonic waves based on a drive signal supplied from a transmission/reception circuit 110 of the device main body 100 (described later). The multiple transducers of the ultrasonic probe 101 also receive reflected waves from the subject P and convert them into electrical signals. The ultrasonic probe 101 also has a matching layer provided on the transducers, and a backing material that prevents ultrasonic waves from propagating backward from the transducers.

When ultrasound waves are transmitted from the ultrasound probe 101 to the subject P, the transmitted ultrasound waves are reflected successively by discontinuous surfaces of acoustic impedance in the tissues of the subject P, and are received as reflected wave signals (echo signals) by multiple transducers of the ultrasound probe 101. The amplitude of the received reflected wave signal depends on the difference in acoustic impedance at the discontinuous surfaces where the ultrasound waves are reflected. When the transmitted ultrasound pulse is reflected by the surface of a moving blood flow, heart wall, etc., the reflected wave signal undergoes a frequency shift due to the Doppler effect depending on the velocity component of the moving body in the direction of ultrasound transmission.

The first embodiment can be applied to any of the following cases: the ultrasonic probe 101 shown in FIG. 1 is a one-dimensional ultrasonic probe in which multiple piezoelectric transducers are arranged in a row, a one-dimensional ultrasonic probe in which multiple piezoelectric transducers arranged in a row are mechanically oscillated, and a two-dimensional ultrasonic probe in which multiple piezoelectric transducers are arranged two-dimensionally in a lattice pattern.

The input interface 102 includes a mouse, keyboard, buttons, a panel switch, a touch command screen, a foot switch, a trackball, a joystick, etc., and accepts various setting requests from the operator of the ultrasound diagnostic device 1 and transfers the various setting requests received to the device main body 100.

The display 103 displays a GUI (Graphical User Interface) that enables the operator of the ultrasound diagnostic device 1 to input various setting requests using the input interface 102, and displays ultrasound image data generated in the device body 100, etc.

The device main body 100 is a device that generates ultrasound image data based on a reflected wave signal received by the ultrasound probe 101, and as shown in FIG. 1, has a transmission/reception circuit 110, a signal processing circuit 120, an image processing circuit 130, an image memory 140, a storage circuit 150, and a processing circuit 160. The transmission/reception circuit 110, the signal processing circuit 120, the image processing circuit 130, the image memory 140, the storage circuit 150, and the processing circuit 160 are connected so as to be able to communicate with each other.

The transmission/reception circuit 110 has a pulse generator, a transmission delay unit, a pulser, etc., and supplies a drive signal to the ultrasonic probe 101. The pulse generator repeatedly generates rate pulses for forming a transmission ultrasonic wave at a predetermined rate frequency. The transmission delay unit focuses the ultrasonic waves generated from the ultrasonic probe 101 into a beam shape and provides each rate pulse generated by the pulse generator with a delay time for each piezoelectric transducer required to determine the transmission directivity. The pulser applies a drive signal (drive pulse) to the ultrasonic probe 101 at a timing based on the rate pulse. In other words, the transmission delay unit changes the delay time provided to each rate pulse to arbitrarily adjust the transmission direction of the ultrasonic waves transmitted from the piezoelectric transducer surface.

The transmission/reception circuit 110 has the ability to instantly change the transmission frequency, transmission drive voltage, etc., in order to execute a specified scan sequence based on instructions from the processing circuit 160, which will be described later. In particular, the change in transmission drive voltage is achieved by a linear amplifier type transmission circuit that can instantly switch its value, or a mechanism that electrically switches between multiple power supply units.

The transmission/reception circuit 110 also has a preamplifier, an A/D (Analog/Digital) converter, a reception delay unit, an adder, etc., and performs various processes on the reflected wave signal received by the ultrasound probe 101 to generate reflected wave data. The preamplifier amplifies the reflected wave signal for each channel. The A/D converter A/D converts the amplified reflected wave signal. The reception delay unit provides the delay time required to determine the reception directivity. The adder performs addition processing on the reflected wave signal processed by the reception delay unit to generate reflected wave data. The addition processing by the adder emphasizes the reflected component from a direction corresponding to the reception directivity of the reflected wave signal, and a comprehensive beam for ultrasound transmission and reception is formed by the reception directivity and transmission directivity.

When scanning a two-dimensional region of the subject P, the transmission/reception circuit 110 causes the ultrasound probe 101 to transmit an ultrasound beam in two-dimensional directions. The transmission/reception circuit 110 then generates two-dimensional reflected wave data from the reflected wave signals received by the ultrasound probe 101. When scanning a three-dimensional region of the subject P, the transmission/reception circuit 110 causes the ultrasound probe 101 to transmit an ultrasound beam in three-dimensional directions. The transmission/reception circuit 110 then generates three-dimensional reflected wave data from the reflected wave signals received by the ultrasound probe 101. The transmission/reception circuit 110 is an example of a transmission/reception unit.

The signal processing circuit 120 performs, for example, logarithmic amplification, envelope detection processing, etc., on the reflected wave data received from the transmission/reception circuit 110 to generate data (B-mode data) in which the signal strength at each sample point is expressed as luminance brightness. The B-mode data generated by the signal processing circuit 120 is output to the image processing circuit 130.

The signal processing circuit 120 also generates data (Doppler data) that extracts motion information based on the Doppler effect of a moving object at each sample point in the scanning area from the reflected wave data received from the transmission/reception circuit 110. Specifically, the signal processing circuit 120 performs frequency analysis of the velocity information from the reflected wave data, extracts blood flow, tissue, and contrast agent echo components due to the Doppler effect, and generates data (Doppler data) that extracts moving object information such as average velocity, variance, and power for multiple points. Here, the moving object is, for example, blood flow, tissue such as the heart wall, and contrast agent. The motion information (blood flow information) obtained by the signal processing circuit 120 is sent to the image processing circuit 130 and displayed in color on the display 103 as an average velocity image, variance image, power image, or a combination of these images.

The signal processing circuit 120 also executes an analysis function 121 as shown in FIG. 1. Here, for example, the processing functions executed by the analysis function 121, which is a component of the signal processing circuit 120 shown in FIG. 1, are recorded in the form of a computer-executable program in a storage device (e.g., the storage circuit 150) of the ultrasound diagnostic device 1. The signal processing circuit 120 is a processor that realizes the function corresponding to each program by reading each program from the storage device and executing it. In other words, the signal processing circuit 120 in a state in which each program has been read has the functions shown in the signal processing circuit 120 in FIG. 1. The processing functions executed by the analysis function 121 will be described later. The analysis function 121 is an example of an analysis unit.

The image processing circuit 130 generates ultrasound image data from the data generated by the signal processing circuit 120. The image processing circuit 130 generates B-mode image data that represents the intensity of the reflected wave as brightness from the B-mode data generated by the signal processing circuit 120. The image processing circuit 130 also generates Doppler image data that represents moving object information from the Doppler data generated by the signal processing circuit 120. The Doppler image data is velocity image data, variance image data, power image data, or image data that is a combination of these.

Here, the image processing circuit 130 generally converts (scan converts) the scan line signal sequence of the ultrasound scan into a scan line signal sequence of a video format, such as that of a television, to generate ultrasound image data for display. Specifically, the image processing circuit 130 generates ultrasound image data for display by performing coordinate conversion according to the ultrasound scanning form of the ultrasound probe 101. In addition to scan conversion, the image processing circuit 130 also performs various image processing, such as image processing (smoothing processing) that regenerates an average brightness image using multiple image frames after scan conversion, and image processing (edge emphasis processing) that uses a differential filter within the image. In addition, the image processing circuit 130 combines supplementary information (text information of various parameters, scales, body marks, etc.) with the ultrasound image data.

That is, the B-mode data and Doppler data are ultrasound image data before scan conversion processing, and the data generated by the image processing circuit 130 is ultrasound image data for display after scan conversion processing. When the signal processing circuit 120 generates three-dimensional data (three-dimensional B-mode data and three-dimensional Doppler data), the image processing circuit 130 generates volume data by performing coordinate conversion according to the ultrasound scanning form of the ultrasound probe 101. Then, the image processing circuit 130 performs various rendering processes on the volume data to generate two-dimensional image data for display.

The image memory 140 is a memory that stores image data for display generated by the image processing circuit 130. The image memory 140 can also store data generated by the signal processing circuit 120. The B-mode data and Doppler data stored in the image memory 140 can be called up by the operator after diagnosis, for example, and becomes ultrasound image data for display via the image processing circuit 130.

The memory circuitry 150 stores various data such as control programs for transmitting and receiving ultrasound, image processing, and display processing, diagnostic information (e.g., patient ID, doctor's findings, etc.), diagnostic protocols, and various body marks. The memory circuitry 150 is also used to store image data stored in the image memory 140 as necessary. The data stored in the memory circuitry 150 can be transferred to an external device via an interface (not shown).

The processing circuitry 160 controls the overall processing of the ultrasound diagnostic device 1. Specifically, the processing circuitry 160 controls the processing of the transmission/reception circuitry 110, the signal processing circuitry 120, and the image processing circuitry 130 based on various setting requests input by the operator via the input interface 102 and various control programs and various data read from the memory circuitry 150. The processing circuitry 160 also controls the display 103 to display ultrasound image data for display stored in the image memory 140.

Furthermore, as shown in FIG. 1, the processing circuit 160 executes a calculation function 161, a generation function 162, and an output control function 163. The calculation function 161 is an example of a calculation unit. The generation function 162 is an example of a generation unit. The output control function 163 is an example of an output control unit.

Here, for example, the processing functions executed by the calculation function 161, the generation function 162, and the output control function 163, which are components of the processing circuitry 160 shown in FIG. 1, are recorded in the form of a computer-executable program in a storage device (e.g., the storage circuitry 150) of the ultrasound diagnostic device 1. The processing circuitry 160 is a processor that realizes the function corresponding to each program by reading each program from the storage device and executing it. In other words, the processing circuitry 160 in a state in which each program has been read has each function shown in the processing circuitry 160 in FIG. 1. The processing functions executed by the calculation function 161, the generation function 162, and the output control function 163 will be described later.

The term "processor (circuit)" used in the above description means, for example, a circuit such as a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), an Application Specific Integrated Circuit (ASIC), a programmable logic device (for example, a Simple Programmable Logic Device (SPLD), a Complex Programmable Logic Device (CPLD), and a Field Programmable Gate Array (FPGA)). The processor realizes its function by reading and executing a program stored in the memory circuit 150. Note that instead of storing a program in the memory circuit 150, the program may be directly built into the circuit of the processor. In this case, the processor realizes its function by reading and executing a program built into the circuit. Note that each processor in this embodiment is not limited to being configured as a single circuit for each processor, but may be configured as a single processor by combining multiple independent circuits to realize its function. Furthermore, multiple components in each figure may be integrated into a single processor to realize its function.

Here, the ultrasound diagnostic device 1 according to the first embodiment is a device capable of performing elastography, which measures the stiffness of biological tissue and visualizes the distribution of the measured stiffness. Specifically, the ultrasound diagnostic device 1 according to the first embodiment is a device capable of performing shear wave elastography (SWE) by applying an acoustic radiation force to generate a displacement in biological tissue.

In SWE, shear waves have the tendency to be reflected at the boundary between tissues with different stiffness. These reflected shear waves are superimposed on the shear waves generated directly from the push pulse, causing a change in the contour of the displacement waveform. This change in contour adversely affects the accuracy of estimating the displacement lag (time lag), preventing accurate stiffness measurement.

2 and 3 are diagrams for explaining the reflection of shear waves. In the upper diagrams of Fig. 2 and Fig. 3, the elliptical hatched area located in the center of the ROI (Region Of Interest) indicates an area (structure) whose hardness is different from other areas. In other words, the outline of the hatched area corresponds to a structural boundary surface. In addition, the lower diagrams of Fig. 2 and Fig. 3 show a displacement waveform (time-displacement curve). In other words, in the lower diagrams of Fig. 2 and Fig. 3, the horizontal axis corresponds to time (the number of tracking pulse transmissions), and the vertical axis corresponds to the amplitude of the displacement. In addition, Fig. 2 is an example of a case where a push pulse is irradiated near the boundary surface. In addition, Fig. 3 is an example of a case where a push pulse is irradiated at a position farther away from the boundary surface than in Fig. 2.

As shown in FIG. 2, when a push pulse is irradiated, a shear wave propagates from the position where the push pulse is irradiated (irradiation position). Here, shear wave A propagating from the irradiation position to the right in the figure is observed, for example, as a displacement waveform (dashed line) shown in the lower diagram of FIG. 2 at the transmission/reception position of the tracking pulse. Note that shear wave A is an example of a shear wave that propagates (directly) without reflection from the irradiation position of the push pulse to the transmission/reception position of the tracking pulse.

On the other hand, shear wave B propagating from the irradiation position to the left in the figure is reflected at the boundary surface and then propagates to the right in the figure. For this reason, shear wave B is observed, for example, as a displacement waveform (dashed line) shown in the lower diagram of Figure 2 at the transmitting and receiving position of the tracking pulse.

In other words, when a push pulse is applied near the boundary surface, the displacement waveform actually observed (solid line) has a broad shape due to the overlap of the displacement waveform generated by shear wave A (dashed line) and the displacement waveform generated by shear wave B (dash-dotted line).

Also, as shown in Figure 3, when the push pulse is irradiated at a position farther away from the boundary surface than in Figure 2, the displacement waveform actually observed (solid line) has a twin peak shape, with the displacement waveform generated by shear wave C (dashed line) and the displacement waveform generated by shear wave D (dash-dotted line) overlapping.

In this way, when the displacement waveform of the shear wave (shear wave A or shear wave C) that should be observed becomes broad or deformed into a twin peak, the amplitude and time (arrival time) of the peak differ from the displacement waveform that should be observed, which adversely affects the estimation accuracy and prevents stable hardness measurement.

Therefore, the ultrasound diagnostic device 1 according to the first embodiment has the processing functions described below to support stable measurement of the stiffness of biological tissue.

It has been explained that SWE is one of the very useful quantification techniques for, for example, diffuse liver disease, but this embodiment is not limited to diffuse liver disease. For example, this embodiment can be widely applied to sites and cases to which SWE can be applied.

The analysis function 121 executes processing for measuring the hardness of biological tissue. For example, the analysis function 121 controls the transmission/reception circuit 110 to collect scan data by transmitting push pulses and transmitting/receiving tracking pulses. Note that the push pulse is a focused ultrasonic pulse that generates transverse waves called shear waves in biological tissue based on acoustic radiation force, and is an example of ultrasonic waves for generating shear waves. Also, the tracking pulse is an ultrasonic pulse that observes shear waves, and is an example of ultrasonic waves for observing shear waves.

For example, the transmission/reception circuit 110 causes the ultrasonic probe 101 to transmit a push pulse to generate shear waves in biological tissue. The transmission/reception circuit 110 then causes the ultrasonic probe 101 to transmit a tracking pulse for observing the shear waves generated based on the push pulse. The tracking pulse is transmitted to observe the propagation speed of the shear waves generated by the push pulse at each sample point within the ROI. Typically, the tracking pulse is transmitted multiple times (e.g., 100 times) for each scanning line within the ROI. The transmission/reception circuit 110 generates reflected wave data (scan data) from the reflected wave signal of the tracking pulse transmitted for each scanning line within the ROI.

Then, the analysis function 121 analyzes the reflected wave data of the tracking pulse transmitted multiple times on each scanning line within the ROI to calculate stiffness distribution data indicating the distribution of stiffness within the ROI. Specifically, the analysis function 121 generates stiffness distribution data of the ROI by measuring the propagation speed of the shear wave generated by the push pulse at each sample point.

For example, the analysis function 121 performs frequency analysis on the reflected wave data of the tracking pulse. As a result, the analysis function 121 generates motion information (tissue Doppler data) over multiple time phases at each of the multiple sample points of each scanning line. Then, the analysis function 121 time-integrates the velocity components of the tissue Doppler data of multiple time phases obtained at each of the multiple sample points of each scanning line. As a result, the analysis function 121 calculates the displacement of each of the multiple sample points of each scanning line over multiple time phases. That is, the displacement is detected as a displacement waveform (time-displacement curve). That is, the analysis function 121 is an example of a detection unit that detects the movement (displacement) of tissue at each of multiple positions in the subject by analyzing scan data collected by transmitting push pulses and transmitting and receiving tracking pulses. Also, the displacement waveform is an example of waveform information that represents a time-series change in displacement.

Then, the analysis function 121 determines the time when the displacement is maximum at each sample point. Then, the analysis function 121 determines the time when the maximum displacement is obtained at each sample point as the arrival time when the shear wave arrives at each sample point. Next, the analysis function 121 calculates the propagation speed of the shear wave at each sample point by performing spatial differentiation of the arrival time of the shear wave at each sample point. Note that the arrival time of the shear wave is not limited to only the time when the displacement is maximum at each sample point, and for example, the time when the amount of change in displacement at each sample point is maximum may be used.

The analysis function 121 then generates information on the shear wave propagation velocity at each sample point within the ROI as stiffness distribution data. The shear wave propagation velocity is high in hard tissue and low in soft tissue. In other words, the value of the shear wave propagation velocity indicates the stiffness (elastic modulus) of the tissue. In the above case, the tracking pulse is a transmission pulse for tissue Doppler. Note that the above shear wave propagation velocity can also be calculated from the cross-correlation of tissue displacements in adjacent scan lines.

The analysis function 121 may calculate the elastic modulus (Young's modulus, shear modulus) from the shear wave propagation speed, and generate stiffness distribution data from the calculated elastic modulus. The shear wave propagation speed, Young's modulus, and shear modulus can all be used as physical quantities (index values) that represent the stiffness of biological tissue. Stiffness is an example of a parameter that represents the properties of tissue (also referred to as a "tissue property parameter").

Then, the analysis function 121 outputs the stiffness distribution data to the image processing circuit 130, which generates stiffness image data. Specifically, the image processing circuit 130 generates stiffness image data by assigning an image value according to the propagation speed of the shear wave at each sample point of the stiffness distribution data to each position within the ROI.

Figure 4 is a diagram showing an example of a stiffness image according to the first embodiment. As shown in Figure 4, stiffness image data generated by the image processing circuit 130 is superimposed, for example, on a B-mode image I10 as a stiffness image I11 and displayed on the display 103.

In this way, the analysis function 121 executes a process for measuring the stiffness of biological tissue. Note that the process for measuring the stiffness of biological tissue described above is merely an example, and is not limited to the above. For example, the analysis function 121 can apply any known technology related to elastography as long as it can detect the movement (e.g., displacement) of tissue caused by shear waves.

The calculation function 161 calculates an index value related to the tissue movement at each of the multiple positions based on the tissue movement. For example, the calculation function 161 calculates a value related to the attenuation delay of the tissue movement (displacement) as the index value.

As an example, the calculation function 161 calculates the index value using a threshold value for the magnitude of tissue movement. In other words, the calculation function 161 calculates the index value based on the displacement waveform and the threshold value. Specifically, the calculation function 161 calculates the time width during which the waveform information of the tissue movement is equal to or greater than the threshold value as the index value.

Figures 5 to 10 are diagrams for explaining the processing of the calculation function 161 according to the first embodiment. Figures 5 to 10 exemplify a displacement waveform (time displacement curve) at a certain sample point. That is, in Figures 5 to 10, the horizontal axis corresponds to time (the number of tracking pulse transmissions), and the vertical axis corresponds to the amplitude of the displacement. That is, the observation time of the displacement in the displacement waveform is determined based on the interval and number of tracking pulse transmissions and receptions. Note that in Figures 5 to 10, the threshold is a preset value (fixed value). The threshold is, for example, input in advance by the operator and stored in the memory circuit 150.

For example, the calculation function 161 calculates the time width during which the displacement waveform is equal to or greater than a threshold value as the index value. In the example shown in FIG. 5, the calculation function 161 calculates time T1 as the index value. In the example shown in FIG. 6, the calculation function 161 calculates time T2 as the index value. In the example shown in FIG. 7, the calculation function 161 calculates the sum of time T3 and time T4 as the index value. In the example shown in FIG. 8, the calculation function 161 calculates time T5 as the index value.

The example shown in FIG. 9 is an example in which the observed displacement waveform is small and there is no time when the displacement waveform is equal to or greater than the threshold. In this case, the calculation function 161 calculates "0" as the index value. The example shown in FIG. 10 is an example in which the displacement waveform that is equal to or greater than the threshold does not decay below the threshold. In this case, the calculation function 161 calculates time T6 as the index value.

In this way, the calculation function 161 calculates, for each sample point within the ROI, the time width (time interval) during which the displacement waveform is equal to or greater than the threshold value as an index value. In other words, the time width corresponds to the interval from the time the displacement value (amplitude) exceeds the threshold value to the time the displacement value falls below the threshold value, or the interval from the time the displacement value exceeds the threshold value to the time the displacement was last observed. This allows the calculation function 161 to express, as an index value, how broad the shape of the displacement waveform at each position is.

Note that the process for calculating the index value described above is merely an example, and the embodiment is not limited to this. For example, the calculation function 161 does not necessarily have to calculate the value of the time width itself as the index value. As an example, the calculation function 161 may calculate a value obtained by adding, subtracting, multiplying or dividing the value of the time width by a predetermined value, or a value obtained by inputting the value of the time width into a predetermined function. In other words, the calculation function 161 can calculate a value that increases or decreases according to an increase or decrease in the value of the time width as the index value.

For example, the calculation function 161 may use a percentage of the peak value in the waveform information of tissue movement as the threshold value, rather than a preset fixed value. For example, the calculation function 161 uses "a value that is 60% of the peak value" as the threshold value. In this case, the threshold value varies depending on the magnitude of the peak value of the displacement waveform, so that a value other than "0" is calculated even in the example shown in FIG. 9. Note that the percentage used as the threshold value is, for example, input in advance by the operator and stored in the memory circuitry 150.

In addition, the calculation function 161 may calculate the number of peaks in the range where the waveform information of the tissue movement is equal to or greater than a threshold value as the index value, instead of the time width. When calculating the number of peaks as the index value, the calculation function 161 calculates, for example, "1" for the displacement waveform in FIG. 5 and "2" for the displacement waveforms in FIG. 6 to FIG. 10. In this way, the calculation function 161 can express as an index value whether the displacement waveform at each position has a single peak, twin peaks, or three or more peaks. Examples of index values other than the time width and the number of peaks will be described later in the modified examples.

The generation function 162 generates a parametric image in which a pixel value corresponding to the index value of each of the multiple positions is assigned to each of the multiple positions. This parametric image is an example of a first index image.

Figure 11 is a diagram for explaining the processing of the generation function 162 according to the first embodiment. As shown in Figure 11, the generation function 162 generates a parametric image I12 by assigning pixel values according to the index value of each position to each position within the ROI set on the B-mode image I10. Note that the area of the parametric image I12 corresponds to the area of the stiffness image I11.

In this way, the generation function 162 generates the parametric image I12. Note that the processing of the generation function 162 can also be performed by the image processing circuit 130.

The output control function 163 outputs the index value. For example, the output control function 163 causes the parametric image I12 generated by the generation function 162 to be displayed on the display 103.

Figure 12 is a diagram for explaining the processing of the output control function 163 according to the first embodiment. As shown in Figure 12, the output control function 163 displays the parametric image I12 and the stiffness image I11 simultaneously on the display 103.

Note that the content shown in FIG. 12 is merely an example and is not limited to the content shown. For example, the parametric image I12 and the stiffness image I11 do not have to be superimposed on the B-mode image I10. Also, for example, the parametric image I12 may be superimposed on the stiffness image I11.

In addition, the output control function 163 does not necessarily have to display the parametric image I12. For example, the output control function 163 can also display the index value as a numerical value on the display 103. When displaying as a numerical value, it is preferable for the output control function 163 to display the index value at a position (sample point) specified by the operator, for example. When an area is specified by the operator, the output control function 163 may display a statistical value (average value, maximum value, minimum value, etc.) of the index value within the area, or may display the index value at a representative point within the area. In addition, when the parametric image I12 is not displayed, the processing circuit 160 may not have the generation function 162.

In addition, the destination of the information output by the output control function 163 is not limited to the display 103. For example, the output control function 163 may transmit information to an external device connected to the ultrasound diagnostic device 1 via a network. In addition, the output control function 163 may store information in the memory circuitry 150 or a portable recording medium.

Figure 13 is a flowchart showing the processing procedure by the ultrasound diagnostic device 1 according to the first embodiment. The processing procedure shown in Figure 13 is started when the operator inputs an instruction to start the elast mode, which is an imaging mode for performing elastography. Note that the detailed processing content in each processing procedure in Figure 13 is similar to the content explained as each processing function of the ultrasound diagnostic device 1, and therefore will be omitted as appropriate.

As shown in FIG. 13, when an instruction to start the elast mode is input by the operator (step S101: Yes), the ultrasound diagnostic device 1 starts the processing from step S102 onwards. Note that, until an instruction to start the elast mode is input (step S101: No), the processing from step S102 onwards is not started, and the processing in FIG. 13 is in a standby state.

When the ultrasound diagnostic device 1 is started, the analysis function 121 sets the ROI (step S102). For example, when the elastance mode is started, a B-mode image corresponding to the contact position of the ultrasound probe 101 is automatically displayed. The operator performs an input operation to place an ROI for displaying a stiffness image on the displayed B-mode image. The analysis function 121 sets the ROI at the position placed by the operator.

Then, the analysis function 121 generates a stiffness image corresponding to the ROI (step S103). For example, when the operator presses the stiffness image capture button, the analysis function 121 controls the transmission/reception circuit 110 to transmit push pulses and transmit/receive tracking pulses to collect scan data for each position within the ROI. Then, the analysis function 121 generates a stiffness image corresponding to the ROI based on the collected scan data.

Then, the calculation function 161 calculates an index value related to the attenuation of the movement based on the movement (displacement) of the tissue (step S104). For example, the calculation function 161 calculates the time width during which the displacement waveform is equal to or greater than a threshold value as the index value for each position within the ROI.

Then, the generation function 162 generates a parametric image corresponding to the ROI (step S105). For example, the generation function 162 generates a parametric image by assigning a pixel value to each position in the ROI according to the index value of each position.

Then, the output control function 163 displays the stiffness image and the parametric image (step S106). The output control function 163 displays the stiffness image and the parametric image side by side on the display 103.

Note that the content shown in FIG. 13 is merely an example, and is not limited to the content shown. For example, after a displacement is detected, the process of calculating an index value (step S104) and the process of generating a parametric image (step S105) may be executed prior to the process of generating a stiffness image (step S103), or may be executed as parallel processes.

As described above, in the ultrasound diagnostic device 1 according to the first embodiment, the transmission/reception circuit 110 collects scan data by transmitting ultrasound waves for generating shear waves and transmitting and receiving ultrasound waves for observing shear waves. Next, the analysis function 121 analyzes the scan data to detect tissue movement at each of multiple positions within the subject. Then, the calculation function 161 calculates an index value related to waveform information of the tissue movement at each of the multiple positions based on the tissue movement. Then, the output control function 163 outputs the index value. This allows the ultrasound diagnostic device 1 to support stable measurement of the stiffness of biological tissue.

For example, the ultrasound diagnostic device 1 displays, together with the stiffness image, a parametric image having pixel values corresponding to the time width during which the displacement waveform is equal to or greater than a threshold value. By viewing this parametric image, the operator can determine whether or not scan data was collected at a stable position that is unlikely to contain reflected shear waves. This enables the ultrasound diagnostic device 1 to support stable measurement of the stiffness of biological tissue, such as by re-imaging the stiffness image as necessary.

(Variation 1)
In the first embodiment, a case where "displacement" is used as the movement of tissue has been described, but the embodiment is not limited thereto. For example, the ultrasound diagnostic device 1 can use "instantaneous displacement" or "instantaneous velocity" as the movement of tissue, instead of "displacement".

For example, the velocity component of tissue Doppler data obtained in the process of measuring the stiffness of biological tissue described above corresponds to "instantaneous displacement." When the waveform information of the instantaneous displacement also contains a reflected shear wave component, a change in waveform similar to that of the waveform information of the displacement is observed. For this reason, the calculation function 161 can calculate the index value by treating the instantaneous displacement in the same way as the displacement.

Note that "instantaneous velocity" is a value obtained by differentiating instantaneous displacement. Since instantaneous velocity has the same characteristics as displacement, the calculation function 161 can calculate the index value by treating instantaneous velocity in the same way as displacement.

(Variation 2)
In the first embodiment, the fixed value and the ratio used as the threshold may be set based on the distance in the azimuth direction from the irradiation position of the push pulse.

It is known that the displacement caused by shear waves attenuates depending on the propagation distance of the shear waves. Therefore, the calculation function 161 sets the threshold value at each position based on the azimuthal distance from the push pulse irradiation position.

For example, the calculation function 161 sets the threshold value of a sample point close to the irradiation position of the push pulse to a higher value than the threshold value of a sample point far from the irradiation position of the push pulse. This allows the calculation function 161 to set a threshold value according to the propagation distance of the shear wave.

(Variation 3)
Furthermore, the "threshold value according to the propagation distance of the shear wave" described in the second modification may be set based on a reference region.

Figure 14 is a diagram for explaining the processing of the calculation function 161 according to the third modified example of the first embodiment. The upper diagram of Figure 14 illustrates a reference region R10 set on the stiffness image I11. The lower diagram of Figure 14 illustrates displacement waveforms at transmitting and receiving positions P1, P2, and P3 of the tracking pulse within the reference region R10. Note that in Figure 14, position P1 is closer to the push pulse irradiation position than position P2, and position P3 is farther from the push pulse irradiation position than position P2.

As shown in FIG. 14, the operator sets a reference region R10 on the stiffness image I11. At this time, it is preferable to set the reference region R10 in a region where the tissue (or stiffness) appears uniform.

Then, the calculation function 161 sets thresholds Th1, Th2, and Th3 (Th1>Th2>Th3) according to the propagation distance of the shear wave based on the amplitude of the displacement waveform at each position P1, P2, and P3. Here, threshold Th1 is the threshold when the propagation distance of the shear wave corresponds to position P1. Furthermore, threshold Th2 is the threshold when the propagation distance of the shear wave corresponds to position P2. Furthermore, threshold Th3 is the threshold when the propagation distance of the shear wave corresponds to position P3.

In this way, the calculation function 161 sets the threshold value at each position based on the movement of the tissue in the reference region. Note that the reference region R10 may be set on the B-mode image I10 instead of the stiffness image I11.

(Variation 4)
In addition, the index value is not limited to the time width and the number of peaks, and for example, the area can be used. However, the area of the displacement waveform reflects not only the attenuation delay of the movement of the tissue but also the magnitude of the amplitude. Therefore, when the area is used, it is preferable to calculate the area after normalizing it with the amplitude value.

For example, the calculation function 161 normalizes the amplitude of the displacement waveform at each of the multiple positions for which the index value is to be calculated. Specifically, the calculation function 161 normalizes the displacement waveform at each sample point in the ROI so that the peak amplitude value is 100%. The calculation function 161 then calculates the area of the region in which the normalized displacement waveform is equal to or greater than the threshold value. For example, when a displacement waveform such as that shown in FIG. 5 is obtained as the normalized displacement waveform, the calculation function 161 calculates the area of the region surrounded by the curve representing the displacement waveform and the threshold line (horizontal line).

In this way, the calculation function 161 calculates, as an index value, the area of the region where the waveform information of the normalized tissue movement is equal to or greater than the threshold value.

(Variation 5)
Furthermore, the index value is not limited to the time width, the number of peaks, and the area, but may also be, for example, the time it takes to reach a certain attenuation rate.

Figure 15 is a diagram for explaining the processing of the calculation function 161 according to the fifth modified example of the first embodiment. Figure 15 illustrates an example of a displacement waveform at a certain sample point. In Figure 15, the horizontal axis corresponds to time (the number of tracking pulse transmissions), and the vertical axis corresponds to the amplitude of the displacement.

In the example of FIG. 15, the attenuation rate is set to "30%". In this case, the calculation function 161 calculates, as the index value, the time T7 until the peak of the displacement waveform reaches the attenuation rate of "30%". Note that the attenuation rate is input in advance by the operator and stored in the memory circuitry 150.

In this way, the calculation function 161 calculates, as an index value, the time it takes for the peak value in the waveform information of the tissue movement to reach a predetermined attenuation rate. Note that the attenuation rate is not limited to 30% and can be set to any value.

(Variation 6)
Furthermore, as the index value, a combination of two or more values selected from the time width, the number of peaks, the area, and the time required to reach a certain attenuation rate can also be used.

For example, the calculation function 161 calculates an index value by combining a time span (time T1 in FIG. 5) and a time required to reach a certain decay rate (time T7 in FIG. 15). The combination may be a simple addition value (T1+T7), or it may be calculated by inputting the value into an arbitrary function that performs weighting, etc.

In other words, the calculation function 161 can calculate, as index values, at least one of the following: the time width during which the tissue movement waveform information is equal to or greater than the threshold, the number of peaks in the range in which the tissue movement waveform information is equal to or greater than the threshold, the area of the region in which the normalized tissue movement waveform information is equal to or greater than the threshold, and the time until the peak value in the tissue movement waveform information reaches a predetermined decay rate.

Second Embodiment
A propagation image is known as one of the techniques for displaying the reliability of the stiffness of biological tissue (Patent Document 2: JP 2015-131097 A). In the second embodiment, a case will be described in which the index value described in the first embodiment and the propagation image are combined to indicate the reliability of the stiffness of biological tissue as well as the stability of the measurement environment for the stiffness of the biological tissue.

Figures 16 and 17 are diagrams for explaining the processing of the generation function 162 according to the second embodiment. Figure 16 shows an example of a propagation image. Figure 17 shows an example of a parametric image that combines the index value and the propagation image described in the first embodiment.

As shown in FIG. 16, the generation function 162 has a function for generating a propagation image I13. Here, the propagation image I13 is an image in which a linear image (line image) is drawn in which positions where the arrival times of shear waves are approximately the same (for example, positions where the arrival times are approximately the same) are connected by a line. For example, the arrival times included within a predetermined range can be considered to be approximately the same. The propagation image I13 presents the operator with positions (lines) where shear waves arrive in approximately the same time, like contour lines drawn on a map. Note that, for example, the technology disclosed in JP 2015-131097 A (Patent Document 2) can be applied as a function for generating the propagation image I13.

For example, the generation function 162 calculates the "degree of reach" of each position based on the arrival time of each position included in the ROI. This degree of reach is a value obtained by converting the arrival time of each position, with the maximum arrival time of each position included in the ROI being 100%. The generation function 162 then generates a line image L10 by connecting positions where the degree of reach is 30%. The generation function 162 also generates a line image L11 by connecting positions where the degree of reach is 60%. The generation function 162 also generates a line image L12 by connecting positions where the degree of reach is 90%. The generation function 162 then generates an image including the three line images L10, L11, and L12 as the propagation image I13. Note that, for example, an arbitrary pixel value is assigned with a transparency of 100% to the areas of the propagation image I13 where the line images L10, L11, and L12 are not depicted.

Note that the content shown in FIG. 16 is merely an example and is not limited to this. For example, the line image may connect positions where the degree of reach is within a certain range, rather than connecting positions where the degree of reach is a constant value. For example, the generation function 162 may generate the line image L10 by connecting positions where the degree of reach is within 29% to 31%. Furthermore, the generation function 162 may use, for example, an integrated value of the time to reach, rather than using the degree of reach.

In addition, in FIG. 16, each line image is depicted with a constant width, but in reality, as a result of connecting positions where the reach is approximately the same, a line image with varying widths (an image that becomes thicker and thinner) may be generated. In such a case, the generation function 162 may use the line image with varying widths as the propagation image as is, or may process the line image so that the width is constant and use it as the propagation image.

As shown in the upper diagram of FIG. 17, the generation function 162 generates a parametric image I14 by assigning pixel values to each line image according to the index value of each position included in each line image. That is, the generation function 162 generates a line image L14 by assigning pixel values to the area of the line image L10 according to the index value of each position included in the line image L10. The generation function 162 also generates a line image L15 by assigning pixel values to the area of the line image L11 according to the index value of each position included in the line image L11. The generation function 162 also generates a line image L16 by assigning pixel values to the area of the line image L12 according to the index value of each position included in the line image L12. The generation function 162 then generates an image including the three line images L14, L15, and L16 as the parametric image I14. The parametric image I14 is an example of a second index image.

In the upper diagram of Figure 17, for convenience of illustration, each line image L14, L15, L16 is uniformly hatched, but in reality, each position (each pixel) contained in each line image L14, L15, L16 is assigned an individual pixel value according to the index value. For example, when region R11 in Figure 17 is enlarged, as shown in the lower diagram of Figure 17, the line images are assigned pixel values according to their respective index values, and are not assigned uniform pixel values.

In this way, the generation function 162 generates a parametric image I14 in which pixel values corresponding to the index values of each position included in a region where the arrival time of the shear wave falls within a predetermined range among multiple positions included in the ROI are assigned. This allows the ultrasound diagnostic device 1 according to the second embodiment to present to the operator the reliability of the stiffness of the biological tissue as well as the stability of the measurement environment for the stiffness of the biological tissue.

Note that the above is merely an example, and is not limited to the above. For example, the propagation image I13 and the parametric image I14 are described in order for convenience of explanation, and do not indicate the order in which the generation function 162 generates the images. In other words, the generation function 162 can generate the parametric image I14 without generating the propagation image I13.

In addition, in FIG. 17, a case where the parametric image I14 is superimposed on the B-mode image I10 is described, but the embodiment is not limited to this. For example, the parametric image I14 may be superimposed on the stiffness image I11, or may be displayed alone without being superimposed on any image. Furthermore, the parametric image I14 may be displayed in parallel with the stiffness image I11 and/or the parametric image I12.

The process of generating the parametric image I14 is not limited to the process described in FIG. 17. For example, the generation function 162 can generate the parametric image I14 using a mask image that masks the areas of the propagation image I13 where the line images L10, L11, and L12 are not depicted. Specifically, the generation function 162 generates a mask image in which the areas of the propagation image I13 that are included in the line images L10, L11, and L12 are set to "1" and the areas of the propagation image I13 where the line images L10, L11, and L12 are not depicted are set to "0". Then, the generation function 162 uses the generated mask image to perform mask processing on the parametric image I12 shown in FIG. 11. As a result, the generation function 162 can generate the parametric image I14.

Other Embodiments
In addition to the above-described embodiment, the present invention may be embodied in various different forms.

(Analysis Equipment)
In the above embodiment, the ultrasonic diagnostic device 1 has been described as an example of an analysis device, but the embodiment is not limited to this. For example, the analysis device may be a medical information processing device capable of processing a group of scan data collected by ultrasonic scanning, such as a personal computer, a workstation, or a PACS viewer.

Figure 18 is a block diagram showing an example of the configuration of an analysis device 200 according to another embodiment. The analysis device 200 is configured by a medical information processing device capable of processing a group of scan data collected by ultrasound scanning, such as a personal computer, a workstation, or a PACS viewer.

As shown in FIG. 18, the analysis device 200 includes an input interface 201, a display 202, a memory circuit 210, and a processing circuit 220. The input interface 201, the display 202, the memory circuit 210, and the processing circuit 220 are connected to each other so as to be able to communicate with each other.

The input interface 201 is an input device, such as a mouse, keyboard, or touch panel, for receiving various instructions and setting requests from an operator. The display 202 is a display device that displays medical images and a GUI that enables the operator to input various setting requests using the input interface 201.

The memory circuit 210 is, for example, a NAND (Not AND) type flash memory or a HDD (Hard Disk Drive), and stores various programs for displaying medical image data and GUIs, as well as information used by the programs.

The processing circuitry 220 is an electronic device (processor) that controls the overall processing in the analysis device 200. The processing circuitry 220 executes an analysis function 221, a calculation function 222, a generation function 223, and an output control function 224. The analysis function 221, the calculation function 222, the generation function 223, and the output control function 224 are recorded in the memory circuitry 210, for example, in the form of a program executable by a computer. The processing circuitry 220 reads out and executes each program to realize a function corresponding to each read program (the analysis function 221, the calculation function 222, the generation function 223, and the output control function 224).

The analysis device 200 receives scan data collected by transmitting ultrasound for generating shear waves and transmitting and receiving ultrasound for observing shear waves, for example, from an ultrasound diagnostic device capable of performing elastography.

In the analysis device 200, the analysis function 221 detects the movement of tissue at each of multiple positions within the subject by analyzing the scan data collected by transmitting ultrasound for generating shear waves and transmitting and receiving ultrasound for observing shear waves. The calculation function 222 calculates an index value related to the movement of tissue at each of the multiple positions based on the movement of tissue. The generation function 223 generates a first index image in which pixel values corresponding to the index value of each position are assigned to each of the multiple positions. The output control function 224 outputs the index value. This allows the analysis device 200 to support stable measurement of the stiffness of biological tissue.

Note that the explanation in FIG. 18 is merely an example, and is not limited to the above explanation. For example, if the analysis device 200 outputs the index value as a numerical value, it does not need to be equipped with the generation function 223.

In addition, each component of each device shown in the figure is a functional concept, and does not necessarily have to be physically configured as shown in the figure. In other words, the specific form of distribution and integration of each device is not limited to that shown in the figure, and all or part of it can be functionally or physically distributed and integrated in any unit depending on various loads, usage conditions, etc. Furthermore, each processing function performed by each device can be realized in whole or in part by a CPU and a program analyzed and executed by the CPU, or can be realized as hardware using wired logic. For example, it is possible to execute the processing functions of all of the transmission/reception circuit 110, signal processing circuit 120, image processing circuit 130, and processing circuit 160, or two or more arbitrarily selected circuits, in a single processing circuit.

Furthermore, among the processes described in the above embodiments and variations, all or part of the processes described as being performed automatically can be performed manually, or all or part of the processes described as being performed manually can be performed automatically using known methods. In addition, the information including the processing procedures, control procedures, specific names, various data, and parameters shown in the above documents and drawings can be changed as desired unless otherwise specified.

The analysis method described in the above embodiment and modified examples can be realized by executing a prepared analysis program on a computer such as a personal computer or a workstation. This analysis program can be distributed via a network such as the Internet. This ultrasound imaging method can also be recorded on a computer-readable recording medium such as a hard disk, flexible disk (FD), CD-ROM, MO, or DVD, and executed by being read from the recording medium by a computer.

At least one of the embodiments described above can assist in the stable measurement of the stiffness of biological tissue.

Although several embodiments of the present invention have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the gist of the invention. These embodiments and their modifications are within the scope of the invention and its equivalents as set forth in the claims, as well as the scope and gist of the invention.

REFERENCE SIGNS LIST 1 Ultrasound diagnostic device 120 Signal processing circuit 121 Analysis function 160 Processing circuit 161 Calculation function 162 Generation function 163 Output control function

Claims (13)

a detection unit that detects tissue movement at each of a plurality of positions within the subject by analyzing scan data collected by transmitting a first ultrasonic wave for generating a shear wave and transmitting and receiving a second ultrasonic wave for observing the shear wave;
a calculation unit that sets a threshold value for a magnitude of the tissue movement for each of the plurality of positions based on a distance from the irradiation position of the first ultrasonic wave to each of the plurality of positions in a lateral direction, and calculates an index value related to waveform information that represents a time series change of the tissue movement at each of the plurality of positions based on the tissue movement and the threshold value for each of the plurality of positions , as an index value that represents an influence of reflection at a boundary between tissues having different stiffnesses of shear waves ;
and an output control unit that outputs the index value ,
The calculation unit calculates, as the index value, a time width during which waveform information of the movement of the tissue is equal to or greater than a threshold value . The calculation unit calculates a value related to an attenuation delay of the movement of the tissue as the index value.
The analysis device according to claim 1 . The calculation unit calculates the index value based on the waveform information and the threshold value.
The analysis device according to claim 1 . The calculation unit calculates, as the index value , at least one of the number of peaks in a range where the waveform information of the tissue movement is equal to or greater than a threshold, the area of a region where the normalized waveform information of the tissue movement is equal to or greater than a threshold, and a time until a peak value in the waveform information of the tissue movement reaches a predetermined attenuation rate.
The analysis device according to claim 3 . The calculation unit uses, as the threshold value, a preset value or a ratio of the tissue movement to a peak value in the waveform information.
5. The analysis device according to claim 3 or 4 . The calculation unit sets the threshold value at each position based on a movement of the tissue in a reference region.
The analysis device according to claim 1 . The detection unit detects at least one of a displacement, an instantaneous displacement, and an instantaneous velocity of the biological tissue as the movement of the tissue.
The analysis device according to any one of claims 1 to 6 . a generating unit that generates a first index image by assigning a pixel value corresponding to the index value of each of the plurality of positions to the first index image,
The analysis device according to any one of claims 1 to 7 . The generating unit generates a second index image by allocating pixel values according to the index values of each position included in a region where the arrival time of the shear wave is included in a predetermined range among the plurality of positions.
The analysis device according to claim 8 . The observation time of the movement of the tissue in the waveform information is determined based on an interval and a number of times of transmission and reception of the second ultrasonic wave.
The analysis device according to any one of claims 1 to 9 . The time span is
the interval between the time the tissue motion value exceeds the threshold and the time the tissue motion value falls below the threshold; or
the interval between the time the tissue motion value exceeded the threshold and the time the tissue motion was last observed;
Corresponding to,
The analysis device according to claim 4 . the first ultrasonic wave is a push pulse,
The second ultrasonic wave is a tracking pulse.
The analysis device according to any one of claims 1 to 11 . a transceiver unit that collects scan data by transmitting a first ultrasonic wave for generating a shear wave and transmitting and receiving a second ultrasonic wave for observing the shear wave;
a detection unit that detects tissue movement at each of a plurality of positions within a subject by analyzing the scan data;
a calculation unit that sets a threshold value for a magnitude of the tissue movement for each of the plurality of positions based on a distance from the irradiation position of the first ultrasonic wave to each of the plurality of positions in a lateral direction, and calculates an index value related to waveform information that represents a time series change of the tissue movement at each of the plurality of positions based on the tissue movement and the threshold value for each of the plurality of positions , as an index value that represents an influence of reflection at a boundary between tissues having different stiffnesses of shear waves ;
and an output control unit that outputs the index value ,
The calculation unit calculates, as the index value, a time width during which waveform information of the movement of the tissue is equal to or greater than a threshold .

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