Analysis device, program, and analysis method

Abstract

To suitably present multiple types of quantified tissue properties.SOLUTION: According to an embodiment, an analysis device includes an acquisition unit and a diagram data generation unit. The acquisition unit acquires quantitative values of each of multiple types of tissue properties related to a region of interest of a subject. The diagram data generation unit generates diagram data of the region of interest on the basis of the quantitative values.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] An embodiment of the present invention relates to an analysis device and an analysis program. [Background technology]

[0002] In recent years, applications have been developed that quantify tissue properties of a subject using medical imaging diagnostic apparatuses such as ultrasound diagnostic apparatuses, MRI (Magnetic Resonance Imaging) apparatuses, and CT (Computed Tomography) apparatuses.

[0003] The quantitative values ​​calculated by such applications are presented to the user as images or numerical information and are used for diagnosis, etc.

[0004] For accurate diagnosis, quantifying one type of tissue property may not be enough. For example, it is common to quantify liver stiffness using an ultrasound diagnostic device and present images and numerical information showing liver stiffness to the user, but hepatitis and mild liver cirrhosis may measure almost the same stiffness. In other words, quantifying one type of tissue property and simply presenting it may not lead to identifying the disease. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] JP 2004-321582 A Summary of the Invention [Problem to be solved by the invention]

[0006] The problem to be solved by the present invention is to preferably present a plurality of types of quantified tissue properties. [Means for solving the problem]

[0007] According to an embodiment, an analysis apparatus includes an acquisition unit and a diagram data generation unit. The acquisition unit acquires quantitative values ​​of a plurality of types of tissue attributes related to a region of interest of a subject. The diagram data generation unit generates diagram data of the region of interest based on the quantitative values. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram showing the configuration of an ultrasonic diagnostic apparatus according to the first embodiment. [Diagram 2] FIG. 2 is a flowchart showing the operation of the control circuit when the ultrasonic diagnostic apparatus according to the first embodiment generates a diagram related to tissue characterization. [Diagram 3] FIG. 3 is a diagram illustrating workflow information displayed on a display device according to the first embodiment. [Figure 4] FIG. 4 is a flowchart showing the operation of the control circuit when the ultrasonic diagnostic apparatus according to the first embodiment acquires quantitative values ​​of tissue attributes. [Diagram 5] FIG. 5 is a diagram illustrating an updated tissue characterization diagnosis support screen displayed on the display device according to the first embodiment. [Figure 6] FIG. 6 is a flowchart showing an example of the operation of the control circuit when the ultrasound diagnostic apparatus according to the first embodiment acquires quantitative values ​​of tissue attributes. [Figure 7] FIG. 7 is a diagram illustrating an example of a radar chart displayed on a display device according to the first embodiment. [Figure 8] FIG. 8 is a diagram illustrating another example of the radar chart displayed on the display device according to the first embodiment. [Figure 9] FIG. 9 is a diagram illustrating another example of the radar chart displayed on the display device according to the first embodiment. [Figure 10] FIG. 10 is a diagram illustrating another example of the radar chart displayed on the display device according to the first embodiment. [Figure 11]FIG. 11 is a diagram illustrating an example of a diagram presenting one case displayed on a display device according to a first modified example of the first embodiment. [Figure 12] FIG. 12 is a diagram illustrating an example of workflow information displayed on a display device according to the second modified example of the first embodiment. [Figure 13] FIG. 13 is a flowchart showing an example of the operation of the control circuit when the ultrasonic diagnostic apparatus according to the second modified example generates a diagram related to tissue characterization. [Figure 14] FIG. 14 is a diagram illustrating an example of a radar chart displayed on a display device according to the second modified example. [Figure 15] FIG. 15 is a diagram illustrating an example of a radar chart displayed on a display device according to the second modified example. [Figure 16] FIG. 16 is a diagram illustrating an example of a radar chart displayed on a display device according to the second modified example. [Figure 17] FIG. 17 is a flowchart showing an example of the operation of the control circuit when calculating a statistical value for each case based on a diagnosis result by the ultrasound diagnostic apparatus according to the second modified example. [Figure 18] FIG. 18 is a diagram illustrating an example of a radar chart displayed on a display device according to the second modified example. [Figure 19] FIG. 19 is a flowchart showing an example of the operation of the control circuit 22 when switching the display of the trend map based on the empirical value. [Figure 20] FIG. 20 is a diagram illustrating an example of a radar chart displayed on a display device according to the second modified example. [Figure 21] FIG. 21 is a flow chart illustrating an example of the operation of the control circuit in generating a diagram suitable for diagnosing a suspected disease. [Figure 22] FIG. 22 is a flow chart showing the operation of the control circuit when selecting items and generating a diagram. [Diagram 23] FIG. 23 is a flowchart showing an example of the operation of the control circuit when acquiring other test result information from an external device. [Figure 24]FIG. 24 is a diagram illustrating an example of a radar chart displayed on a display device according to the second modified example. [Diagram 25] FIG. 25 is a block diagram showing the configuration of an analysis system according to the second embodiment. [Figure 26] FIG. 26 is a flowchart showing the operation of the processing circuit when the medical image processing apparatus according to the second embodiment generates a diagram related to tissue characterization. [Figure 27] FIG. 27 is a diagram illustrating a radar chart according to another embodiment. [Figure 28] FIG. 28 is a diagram showing a tissue characterization diagnosis support screen according to another embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, embodiments will be described with reference to the drawings.

[0010] [First embodiment] An ultrasonic diagnostic apparatus 1 according to the first embodiment will be described with reference to the block diagram of FIG.

[0011] 1, the ultrasound diagnostic device 1 includes an apparatus main body 10, an ultrasound probe 70, a display device 50, and an input device 60. The apparatus main body 10 is connected to an external device 40 via a network 100. The apparatus main body 10 is also connected to the display device 50 and the input device 60.

[0012] The ultrasonic probe 70 has a plurality of piezoelectric transducers, a matching layer provided on the piezoelectric transducers, and a backing material that prevents ultrasonic waves from propagating backward from the piezoelectric transducers. The ultrasonic probe 70 is detachably connected to the device body 10. The plurality of piezoelectric transducers generate ultrasonic waves based on a drive signal supplied from an ultrasonic transmission circuit 11 included in the device body 10. The ultrasonic probe 70 may also be provided with a button that is pressed for offset processing, which will be described later, freezing an ultrasonic image, and the like.

[0013] When ultrasonic waves are transmitted from the ultrasonic probe 70 to the subject P, the transmitted ultrasonic waves are successively reflected by discontinuous surfaces of acoustic impedance in the internal tissues of the subject P, and are received as reflected wave signals by the multiple piezoelectric transducers of the ultrasonic probe 70. The amplitude of the received reflected wave signal depends on the difference in acoustic impedance at the discontinuous surfaces where the ultrasonic waves are reflected. When the transmitted ultrasonic pulse is reflected by the surface of a moving blood flow or a heart wall, the reflected wave signal undergoes a frequency shift due to the Doppler effect depending on the velocity component of the moving object in the ultrasonic transmission direction. The ultrasonic probe 70 receives the reflected wave signal from the subject P and converts it into an electrical signal.

[0014] The device main body 10 shown in Fig. 1 is a device that generates an ultrasonic image based on a reflected wave signal received by an ultrasonic probe 70. As shown in Fig. 1, the device main body 10 includes an ultrasonic transmission circuit 11, an ultrasonic reception circuit 12, a B-mode processing circuit 13, a Doppler processing circuit 14, an image generation circuit 15, an internal storage circuit 17, an image memory 18 (cine memory), an image database 19, an input interface circuit 20, a communication interface circuit 21, and a control circuit 22.

[0015] The ultrasonic transmission circuit 11 is a processor that supplies a drive signal to the ultrasonic probe 70. The ultrasonic transmission circuit 11 is realized by, for example, a trigger generation circuit, a delay circuit, and a pulser circuit. The trigger generation circuit repeatedly generates a rate pulse for forming a transmission ultrasonic wave at a predetermined rate frequency under the control of the control circuit 22. The delay circuit provides each rate pulse generated by the trigger generation circuit with a delay time for each piezoelectric transducer required for focusing the ultrasonic waves generated from the ultrasonic probe 70 into a beam shape and determining the transmission directivity. The pulser circuit applies a drive signal (drive pulse) to the ultrasonic probe 70 at a timing based on the rate pulse under the control of the control circuit 22. The delay circuit changes the delay time provided to each rate pulse, thereby making it possible to arbitrarily adjust the transmission direction from the piezoelectric transducer surface.

[0016] The ultrasonic receiving circuit 12 is a processor that performs various processes on the reflected wave signal received by the ultrasonic probe 70 to generate a received signal. The ultrasonic receiving circuit 12 is realized by, for example, an amplifier circuit, an A / D converter, a reception delay circuit, an adder, and the like. The amplifier circuit amplifies the reflected wave signal received by the ultrasonic probe 70 for each channel and performs gain correction processing. The A / D converter converts the gain-corrected reflected wave signal into a digital signal. The reception delay circuit provides the digital signal with a delay time required to determine the reception directivity. The adder adds multiple digital signals to which a delay time has been provided. The addition process of the adder generates a received signal in which the reflection component from the direction corresponding to the reception directivity is emphasized.

[0017] The B-mode processing circuit 13 is a processor that generates B-mode data based on the reception signal received from the ultrasonic receiving circuit 12 under the control of the control circuit 22. The B-mode processing circuit 13 performs, for example, envelope detection processing and logarithmic amplification processing on the reception signal received from the ultrasonic receiving circuit 12, and generates data (B-mode data) in which the signal intensity is expressed by the brightness of luminance. The generated B-mode data is stored in a RAW data memory (not shown) as B-mode RAW data on a two-dimensional ultrasonic scanning line.

[0018] The Doppler processing circuit 14 is a processor that generates Doppler data based on the reception signal received from the ultrasonic receiving circuit 12. The Doppler processing circuit 14 extracts components corresponding to a moving object from the reception signal received from the ultrasonic receiving circuit 12, calculates information on the moving object for multiple points based on the extracted components, and generates Doppler data. The moving object is, for example, blood flow or tissue. The information on the moving object includes the power of the components corresponding to the moving object, the average and variance of the speed of the moving object, etc. The generated Doppler data is stored in a RAW data memory (not shown) as Doppler RAW data on a two-dimensional ultrasonic scanning line.

[0019] The image generating circuit 15 is a processor capable of generating various types of ultrasonic image data based on signals and data generated by the ultrasonic receiving circuit 12, the B-mode processing circuit 13, or the Doppler processing circuit 14. For example, the image generating circuit 15 generates B-mode image data based on the B-mode RAW data stored in the RAW data memory. The B-mode image data has pixel values ​​(luminance values) reflecting the characteristics of the ultrasonic probe, such as focusing of sound waves, and the sound field characteristics of the ultrasonic beam (for example, a transmission / reception beam). For example, in the B-mode image data, the vicinity of the focus of the ultrasonic waves in the scanned region is relatively brighter than the non-focused portion. In addition, the image generating circuit 15 generates Doppler image data relating to an image showing the distribution of the average speed of a moving object, an image showing the variance of the speed of a moving object, an image showing the power of a component corresponding to a moving object, and the like, based on the Doppler RAW data stored in the RAW data memory.

[0020] Here, the image generating circuit 15 generates ultrasonic image data for display, for example, by coordinate conversion processing, etc. The coordinate conversion processing is processing for converting a signal sequence of scanning lines of ultrasonic scanning, which is made up of B-mode data and Doppler data, into a video signal, which is a scanning line signal sequence of a general video format represented by a television, etc.

[0021] The image generating circuit 15 also generates ultrasound image data indicating information on tissue properties of the subject P. The tissue properties refer to, for example, the properties and state of the tissue. Examples of tissue property image data include elasticity image data related to an image showing the elasticity (hardness) of the tissue, viscosity image data related to an image showing the viscosity of the tissue, attenuation image data related to an image showing the degree of attenuation of ultrasonic waves in the subject tissue, and dispersion image data related to an image showing the degree of dispersion of signals reflected from inside the tissue of the subject P.

[0022] Elasticity image data is image data obtained by quantifying, for example, the hardness of tissue. When a "push pulse" having a high acoustic radiation force is transmitted from the ultrasonic probe 70, a part of the tissue is deformed, and a shear wave is generated. Elasticity image data is generated by observing the propagation of the generated shear wave by transmitting and receiving a "tracking pulse". More specifically, elasticity image data is generated by, for example, calculating the time change of displacement for each position in the imaged region by processing the received signal or Doppler data generated by transmitting and receiving the tracking pulse, and calculating the propagation velocity of the shear wave based on the time change of displacement. The quantitative value of elasticity is not limited to the elastic modulus. For example, the propagation velocity itself can be a quantitative value of elasticity. Note that elasticity image data may be generated based on the change (distortion) in the shape of the tissue to which a mechanical load is applied when a mechanical load is applied to the tissue of the subject.

[0023] The viscosity image data is image data obtained by quantifying the viscosity of tissue, for example. The viscosity image data is generated based on the frequency and propagation velocity of the shear wave, for example. The quantitative value of viscosity is not limited to the viscosity coefficient. For example, the slope of the distribution of the frequency and the propagation velocity can also be a quantitative value of viscosity. The viscosity image data is generated by processing the received signal or Doppler data generated by transmitting and receiving a tracking pulse, similar to the elasticity image data.

[0024] The attenuation image data is image data obtained by quantifying the degree of attenuation of ultrasonic waves in the tissue to be examined. The attenuation image data is generated by processing, for example, the reception signal generated by the ultrasonic receiving circuit 12, the B-mode data generated by the B-mode processing circuit 13, or the B-mode image data generated by the image generating circuit 15. More specifically, the attenuation image data is generated by, for example, transmitting and receiving narrowband ultrasonic pulses, reducing the effects of gain correction and sound field from the acquired reception signal, B-mode data, or B-mode image data, and calculating the amount of change in signal intensity along the depth direction. In addition, for example, the attenuation image data is generated by transmitting and receiving multiple ultrasonic pulses with different center frequencies, comparing the extent to which the intensity of the acquired multiple reception signals changes along the depth direction, and estimating the amount of attenuation specific to the subject.

[0025] The variance image data is image data obtained by quantifying the degree of variance of a signal reflected from inside the tissue of the subject P. The variance image data is generated by processing, for example, the received signal generated by the ultrasonic receiving circuit 12, the B-mode data generated by the B-mode processing circuit 13, or the B-mode image data generated by the image generating circuit 15. More specifically, the variance image data is generated by calculating, for each local area, the degree of deviation from a Rayleigh distribution of the signal amplitude distribution of the received signal generated by the ultrasonic receiving circuit 12.

[0026] The generated elastic image data, viscous image data, attenuation image data, and dispersion image data are associated with pixel values ​​corresponding to predetermined colors according to the quantitative values ​​(tissue attribute parameters) of the tissue attributes calculated for each pixel. The generated elastic image data, viscous image data, attenuation image data, and dispersion image data are displayed on the display device 50 as a color map.

[0027] The generated B-mode image data, Doppler image data, elasticity image data, viscous image data, attenuation image data, and dispersion image data are converted into a format that complies with the DICOM (digital imaging and communication in medicine) standard, for example, and stored in, for example, an image database 19.

[0028] As the display device 50, for example, a CRT (Cathode-Ray Tube) display, a liquid crystal display, an organic EL (Electroluminescence) display, an LED display, a plasma display, or any other display known in the art may be appropriately used. The display device 50 may be a touch panel having an input function for performing touch operations.

[0029] The internal storage circuit 17 has, for example, a magnetic or optical recording medium, or a processor-readable recording medium such as a semiconductor memory. The internal storage circuit 17 stores a control program for implementing ultrasonic transmission and reception, a control program for performing image processing, and a control program for performing display processing. The internal storage circuit 17 also stores a control program for implementing various functions according to the present embodiment. The internal storage circuit 17 also stores a group of data such as diagnostic information (for example, a patient ID, a doctor's findings, etc.), a diagnostic protocol, a body mark generation program, and a conversion table that presets the range of color data used for visualization for each diagnostic region. The internal storage circuit 17 may also store an anatomical atlas, for example, regarding the structure of organs in a living body.

[0030] The internal storage circuit 17 also stores various image data generated by the image generation circuit 15 in accordance with a storage operation input via the input interface circuit 20. The internal storage circuit 17 may also store various image data generated by the image generation circuit 15, including the operation order and operation time, in accordance with a storage operation input via the input interface circuit 20. The internal storage circuit 17 can also transfer the stored data to an external device via the communication interface circuit 21.

[0031] Moreover, the internal storage circuit 17 prestores a plurality of thresholds for each tissue attribute. The tissue attribute parameters are quantitative values ​​of tissue attributes, such as index values ​​representing the hardness of tissue, index values ​​representing the viscosity of tissue, index values ​​representing the degree of attenuation of ultrasonic waves in the test tissue, the ratio of the reflection intensity of ultrasonic waves in the liver and kidney, the degree of dispersion of signals reflected from the inside of the tissue of the subject P, and a strain ratio representing the ratio of the hardness of tissue in the region of interest to the hardness of a predetermined reference tissue. The plurality of thresholds are used to enable the user to grasp which stage each tissue attribute parameter corresponds to. The stage is, for example, an index indicating the degree of progress of a predetermined case. Note that the stage does not necessarily indicate the degree of progress only for a specific case, but may also indicate the degree of progress for multiple cases.

[0032] The index value representing the stiffness of tissue is a quantitative value used, for example, in diagnosing liver fibrosis. The index value representing the stiffness of tissue is expressed, for example, by elastic modulus. The elastic modulus becomes larger as liver fibrosis progresses. The index value representing the stiffness of tissue is acquired, for example, by analyzing elasticity image data.

[0033] The index value representing the viscosity of tissue is a quantitative value used in diagnosing cases where the viscosity is thought to increase significantly due to necrosis and inflammation, such as acute hepatitis. The index value representing the viscosity of tissue is expressed, for example, as a viscosity coefficient. The viscosity coefficient is a large value in the case of acute hepatitis, for example. The index value representing the viscosity of tissue is obtained, for example, by analyzing viscosity image data.

[0034] The index value representing the degree of attenuation of ultrasonic waves in the test tissue is a quantitative value used, for example, when diagnosing fatty liver. The index value representing the degree of attenuation of ultrasonic waves in the test tissue is expressed, for example, as an attenuation rate. The attenuation rate is large, for example, when the subject suffers from fatty liver. The index value representing the degree of attenuation of ultrasonic waves in the test tissue is acquired, for example, by analyzing attenuation image data.

[0035] The ratio of ultrasound reflection intensity in the liver and kidney is a quantitative value used, for example, when diagnosing fatty liver. The ratio of ultrasound reflection intensity in the liver and kidney is obtained as a measurement item related to liver function because the kidney is located near the liver. The ratio of ultrasound reflection intensity in the liver and kidney is expressed, for example, as a liver-kidney contrast ratio, which is the ratio of ultrasound reflection intensity of the liver based on the kidney. When the liver-kidney contrast ratio is high, that is, when the echo intensity of the liver is higher than that of the kidney, fatty liver is highly suspected. The ratio of ultrasound reflection intensity in the liver and kidney is obtained, for example, by analyzing B-mode image data.

[0036] The degree of variance of the signal reflected from the tissue of the subject P is a quantitative value used in diagnosing fatty liver, for example. The degree of variance of the intensity of the signal reflected from the tissue of the subject P is expressed, for example, by normalized local variance (NLV). The NLV indicates, for example, the degree of agreement of the probability density distribution of the brightness value of the echo signal reflected from the liver with the Rayleigh distribution. When observing from the viewpoint of fatty liver, it is considered that as the ratio of fat in the liver increases, the B-mode image becomes a uniform image like a phantom, and the probability density distribution of the amplitude value, which is the intensity of the echo signal reflected from the liver, approaches the Rayleigh distribution. At this time, the value of the NLV approaches 1. When observing from the viewpoint of liver fibrosis, it is considered that as liver fibrosis of the liver progresses, the probability density distribution of the amplitude value, which is the intensity of the echo signal reflected from the liver, begins to reflect fibrotic structures and deviates from the Rayleigh distribution. At this time, the value of the NLV becomes higher (moves away from 1). The degree of variance of the signal reflected from the tissue of the subject P is obtained, for example, by analyzing the variance image data.

[0037] The strain ratio is a quantitative value used in diagnosing liver fibrosis. The strain ratio is expressed, for example, as a ratio between the elastic modulus of a region of interest and a predetermined elastic modulus as a reference. The strain ratio becomes larger as liver fibrosis progresses. The strain ratio is obtained, for example, by analyzing elasticity image data.

[0038] The multiple thresholds may be set and changed by an operator or the like via the input interface circuit 20. The multiple thresholds may be stored for each tissue attribute as a threshold set including at least two thresholds. In this case, the operator can select an arbitrary threshold set from the multiple stored threshold sets. The tissue attribute for which the thresholds are to be set may also be set and changed by the operator or the like via the input interface circuit 20.

[0039] The image memory 18 includes, for example, a magnetic or optical recording medium, or a processor-readable recording medium such as a semiconductor memory. The image memory 18 stores image data corresponding to a plurality of frames immediately before a freeze operation input via the input interface circuit 20. The image data stored in the image memory 18 is, for example, continuously displayed (cine display).

[0040] The image database 19 stores image data transferred from the external device 40. For example, the image database 19 acquires and stores past image data related to the same patient acquired in a past examination from the external device 40. The past image data includes ultrasound image data, CT (Computed Tomography) image data, MR image data, PET (Positron Emission Tomography)-CT image data, PET-MR image data, and X-ray image data. The past image data is stored as, for example, three-dimensional volume data and rendering image data.

[0041] Note that the image database 19 may store desired image data by reading image data recorded on a recording medium such as an MO, a CD-R, or a DVD.

[0042] The input interface circuit 20 receives various instructions from an operator via the input device 60. The input device 60 is, for example, a mouse, a keyboard, a panel switch, a slider switch, a trackball, a rotary switch, a touch panel, or a touch command screen (TCS). The input interface circuit 20 is connected to the control circuit 22 via, for example, a bus, converts an operation instruction input by the operator into an electric signal, and outputs the electric signal to the control circuit 22. Note that in this specification, the input interface circuit 20 is not limited to a circuit that connects to physical operation components such as a mouse and a keyboard. For example, an example of the input interface circuit 20 also includes an electric signal processing circuit that receives an electric signal corresponding to an operation instruction input from an external input device provided separately from the ultrasound diagnostic device 1 as a wireless signal and outputs the electric signal to the control circuit 22.

[0043] The communication interface circuit 21 is connected to an external device 40 via a network 100 or the like, and performs data communication with the external device 40. The external device 40 is, for example, a database of a PACS (Picture Archiving and Communication System) which is a system for managing data of various medical images, or a database of an electronic medical record system for managing electronic medical records to which medical images are attached. The external device 40 is, for example, various medical image diagnostic devices other than the ultrasound diagnostic device 1 according to this embodiment, such as an X-ray CT device, an MRI (Magnetic Resonance Imaging) device, a nuclear medicine diagnostic device, and an X-ray diagnostic device. The standard for communication with the external device 40 may be any standard, and may be, for example, DICOM.

[0044] The control circuit 22 is, for example, a processor that functions as the core of the ultrasound diagnostic device 1. The control circuit 22 executes an operation program stored in the internal storage circuit 17, thereby realizing a function corresponding to the operation program. Specifically, the control circuit 22 has a quantitative value acquisition function 221, a diagram data generation function 223, a workflow information generation function 225, a display control function 227, and a system control function 229.

[0045] The quantitative value acquisition function 221 is a function for acquiring tissue attribute parameters of a site of interest of the subject P. When the quantitative value acquisition function 221 is executed, the control circuit 22 analyzes the B-mode image data, the elasticity image data, the viscosity image data, the attenuation image data, or the dispersion image data, and acquires predetermined tissue attribute parameters.

[0046] The diagram data generating function 223 is a function that generates a diagram for a region of interest based on a plurality of quantitative values ​​acquired by the quantitative value acquiring function 221. When the diagram data generating function 223 is executed, the control circuit 22 generates diagram data that represents the contents of a diagram that is displayed as diagnostic support information for the region of interest, using the quantitative values ​​of each of a plurality of types of tissue attributes acquired from the region of interest of the subject P and a plurality of threshold values ​​prepared for each quantitative value. The diagram includes, for example, a radar chart, a flow chart, a bar graph, a line graph, and the like.

[0047] The workflow information generation function 225 is a function that generates workflow information based on information that identifies multiple types of tissue attributes required for a specified tissue characterization diagnosis. Workflow information is information for supporting tissue characterization diagnosis. The workflow information includes an acquisition procedure for acquiring tissue characterization parameters, various setting information, and the like. When the workflow information generation function 225 is executed, the control circuit 22 reads out information that identifies multiple types of tissue attributes required for a specified tissue characterization diagnosis, for example, from the internal storage circuit 17. The control circuit 22 generates workflow information for acquiring multiple types of tissue characterization parameters based on the read information.

[0048] The display control function 227 is a function for displaying the diagram generated by the diagram data generation function 223, the workflow information generated by the workflow information generation function 225, etc. When the display control function 227 is executed, the control circuit 22 displays the workflow information on the display device 50. The control circuit 22 also displays the diagram on the display device 50. The control circuit 22 may generate a user interface (GUI: Graphical User Interface) for an operator (e.g., a surgeon) to input various instructions via the input interface circuit 20, and display the generated GUI on the display device 50.

[0049] The system control function 229 is a function that controls basic operations such as input and output of the ultrasound diagnostic apparatus 1. When the system control function 229 is executed, the control circuit 22 receives an instruction to start a report generation application and to start acquiring tissue attribute parameters, for example, via the input interface circuit 20. The input for starting the report generation application and acquiring tissue attribute parameters may be a common input.

[0050] Next, various operations of the ultrasonic diagnostic apparatus 1 according to the first embodiment will be described with reference to FIGS.

[0051] 2 is a flowchart showing an example of the operation of the control circuit 22 when the ultrasound diagnostic apparatus 1 according to the first embodiment generates a diagram related to tissue characterization. In the following description, it is assumed that before tissue characterization is performed, an ultrasound scan is performed in B mode on the target area of ​​tissue characterization to generate B mode image data. It is also assumed that the target area of ​​tissue characterization is the liver. It is also assumed that the diagram is a radar chart. It is also assumed that the tissue characterization parameters corresponding to the contents (multiple items) of the radar chart are the elastic modulus, the viscosity modulus, the attenuation rate, the normalized local variance value, and the liver-kidney contrast ratio.

[0052] When an input is made via the input interface circuit 20 to execute tissue characterization diagnosis, for example, for the liver, the control circuit 22 executes the workflow information generating function 225 to generate workflow information representing an acquisition procedure for acquiring tissue characterization parameters for each tissue characterization (step SA1). The workflow information may be stored in advance in the internal storage circuit 17 for each tissue characterization. In this case, when a diagnostic site is specified via the input interface circuit 20, the workflow information is appropriately combined according to the specified diagnostic site and read out from the internal storage circuit 17. Alternatively, the workflow information may be stored in advance in the internal storage circuit 17 in a state where workflows for acquiring various tissue characterization parameters are combined. The workflow information includes, for example, ultrasound transmission conditions, adjustment conditions after ultrasound reception, type of image data to be acquired, number of times image data is acquired per quantitative value acquisition, a calculation method for a representative value calculated for each one-shot (acquisition of image data), and a calculation method for a representative value of a tissue characterization parameter used when generating a diagram.

[0053] The ultrasonic transmission conditions are, for example, the amplitude, frequency, phase, and transmission timing of the ultrasonic waves to be transmitted. The adjustment conditions after ultrasonic reception are, for example, conditions related to image processing such as gain, STC (Sensitivity Time Control), dynamic range, frequency filter, and echo enhancement, and conditions related to a Doppler low-cut filter. The types of image data to be acquired are, for example, B-mode image data, elasticity image data, viscosity image data, attenuation image data, or dispersion image data. The number of times image data is acquired per quantitative value acquisition is, for example, five times. The calculation method of the representative value calculated for each shot is, for example, a calculation method of calculating the average value or median value of tissue attribute parameters acquired in a region of interest (ROI: Region Of Interest) of the subject P. The calculation method of the representative value of the tissue attribute parameters used when generating a diagram is a calculation method of calculating the average value or median value of the representative values ​​calculated for each shot.

[0054] Next, the control circuit 22 executes the display control function 227 to display, for example, a tissue characterization diagnosis support screen (step SA2). Fig. 3 is a diagram showing an example of workflow information displayed on the display device 50 according to the first embodiment. According to Fig. 3, a tissue characterization diagnosis support screen is displayed, which serves as a guide for allowing the operator to obtain tissue characterization parameters and display a radar chart for diagnosing tissue characteristics.

[0055] The tissue characterization diagnostic support screen shown in FIG. 3 displays a character string "Please confirm that the region of interest is displayed in the B-mode image, and press each tissue characterization parameter acquisition button in order." At this time, the user can confirm that the region of interest is displayed, for example, by visually checking the B-mode image displayed in a window or monitor other than the window in which the tissue characterization diagnostic support screen is displayed. In addition, the tissue characterization diagnostic support screen shown in FIG. 3 displays buttons B1, B2, B3, B4, and B5 that can acquire each tissue characterization parameter required for generating radar chart data for diagnosing tissue characterization. This allows the operator to acquire the quantitative values ​​of each tissue characterization in the order of elastic modulus, viscosity modulus, attenuation rate, normalized local variance value, and liver-kidney contrast ratio.

[0056] Furthermore, the tissue characterization diagnosis support screen shown in FIG. 3 displays a button B6 for displaying a radar chart based on the generated radar chart data.

[0057] Furthermore, the tissue characterization diagnosis support screen shown in Fig. 3 displays an implementation status indicating the implementation status of the acquisition of each tissue characterization parameter. According to Fig. 3, the implementation status is displayed as "not acquired" for each of the elastic modulus, viscosity coefficient, attenuation rate, normalized local variance value, and liver-kidney contrast ratio in the initial state. "Not acquired" indicates that the tissue characterization parameter has not yet been acquired. When a tissue characterization parameter with a status of "not acquired" is acquired, the implementation status is updated to "acquired". The implementation status is stored in a predetermined memory provided in the control circuit 22, for example.

[0058] After displaying the tissue characterization diagnosis support screen, the control circuit 22 accepts the selection of the tissue characterization for which quantitative values ​​are to be obtained (step SA3). At this time, it is assumed that the tissue characterization parameters are selected in the order of buttons B1, B2, B3, B4, and B5 in FIG. 3.

[0059] When button B1 is selected in step SA3, the control circuit 22 acquires the elastic modulus based on the workflow information for acquiring the elastic modulus (step SA4). Fig. 4 is a flowchart showing an example of the operation of the control circuit 22 when the ultrasound diagnostic apparatus according to the first embodiment acquires tissue attribute parameters. The case of acquiring the elastic modulus will be described below as an example.

[0060] As shown in FIG. 4, the control circuit 22 controls the ultrasonic transmission circuit 11, the ultrasonic reception circuit 12, the Doppler processing circuit 14, and the image generation circuit 15 based on the workflow information for acquiring the elastic modulus, and generates elastic image data (step SB1). For example, the ultrasonic transmission circuit 11, under the control of the control circuit 22, causes the ultrasonic probe 70 to transmit a push pulse. Then, under the control of the control circuit 22, the ultrasonic transmission circuit 11 and the ultrasonic reception circuit 12 cause the ultrasonic probe 70 to transmit and receive a tracking pulse. Then, under the control of the control circuit 22, the Doppler processing circuit 14 generates Doppler data based on the reception signal generated by the ultrasonic reception circuit 12 in response to the transmission and reception of the tracking pulse. Under the control of the control circuit 22, the image generation circuit 15 calculates the change in displacement over time for each position in the region of the image target based on the Doppler data, calculates the propagation velocity of the shear wave for each position in the region of the image target based on the change in displacement over time, and calculates the elastic modulus for each position in the region of the image target based on the propagation velocity, thereby generating elastic image data.

[0061] The control circuit 22 sets a predetermined region of interest on the color map image based on the generated elasticity image data (step SB2).

[0062] The control circuit 22 calculates a representative value, for example an average value, of the elastic modulus within the set region of interest (step SB3). The control circuit 22 determines whether the process from step SB1 to step SB3 has been performed a predetermined number of times, for example five times (step SB4).

[0063] When the control circuit 22 determines that the processes from step SB1 to step SB3 have not been performed a predetermined number of times (No in step SB4), it repeats steps SB1 to SB3 until they have been performed the predetermined number of times. When the control circuit 22 determines that the processes from step SB1 to step SB3 have been performed a predetermined number of times (Yes in step SB4), it calculates a representative value of the calculated representative values ​​for the predetermined number of times, for example, five times (step SB5). This allows the elastic modulus to be obtained. The region of interest in step SB2 may be set manually via the input interface circuit 20.

[0064] 2, when the control circuit 22 acquires the elastic modulus in step SA4 shown in Fig. 2, for example, the control circuit 22 updates the implementation status related to the elastic modulus from "not acquired" to "acquired" in a predetermined memory managed by the control circuit 22 (step SA5). Note that the tissue attribute parameters such as the elastic modulus acquired in step SA4 may be stored in the internal storage circuit 17.

[0065] The control circuit 22 determines whether there are any other tissue attributes for which quantitative values ​​need to be acquired (step SA6).

[0066] When the control circuit 22 determines that there is another tissue property for which quantitative values ​​need to be acquired (Yes in step SA6), it executes the display control function 227, reflects the updated implementation status on the tissue property diagnosis support screen shown in Fig. 3, and displays the tissue property diagnosis support screen again (step SA2). Fig. 5 is a diagram showing an example of the updated tissue property diagnosis support screen displayed on the display device 50 according to the first embodiment. According to Fig. 5, the implementation status for the elastic modulus is displayed as "Acquired" after the update.

[0067] After displaying the updated tissue characterization diagnosis support screen shown in FIG. 5, the control circuit 22 accepts the selection of the tissue characterization for which quantitative values ​​are to be obtained (step SA3).

[0068] When button B2 is selected in step SA3, control circuit 22 performs measurement based on workflow information for acquiring viscosity, and acquires viscosity (step SA4). The operation of control circuit 22 and related circuits when acquiring viscosity is similar to the operation in steps SB1 and SB2 shown in FIG. 4, although the data to be processed and the processing contents may differ.

[0069] Next, the control circuit 22 performs the processes from step SA2 to step SA6 shown in Fig. 2 in the order of attenuation rate, normalized local variance value, and liver-renal contrast ratio, on condition that buttons B3, B4, and B5 are designated. The operation of the control circuit 22 and related circuits when acquiring the attenuation rate is similar to the operation in step SB1 and step SB2 shown in Fig. 4, although the data to be processed and the processing contents may differ. The operation of the control circuit 22 and related circuits when acquiring the normalized local variance value is similar to the operation in step SB1 and step SB2 shown in Fig. 4, although the data to be processed and the processing contents may differ.

[0070] The operation of the control circuit 22 when acquiring the liver-renal contrast ratio will be described below, since it may be significantly different from the operation of the control circuit 22 etc. shown in Fig. 4. Fig. 6 is a flowchart showing an example of the operation of the control circuit 22 when the ultrasound diagnostic apparatus according to the first embodiment acquires a tissue attribute parameter. At this time, the tissue attribute parameter is assumed to be the liver-renal contrast ratio.

[0071] As shown in FIG. 6, the control circuit 22 controls the ultrasound transmission circuit 11, the ultrasound reception circuit 12, the B-mode processing circuit 13, and the image generation circuit 15 based on workflow information for acquiring the liver-renal contrast ratio, and acquires B-mode image data (step SC1).

[0072] The control circuit 22 sets regions of interest in the liver and kidneys on the B-mode image based on the acquired B-mode image data (step SC2).

[0073] The control circuit 22 calculates representative values ​​of pixel values ​​in each of the regions of interest set for the liver and kidneys (step SC3).

[0074] The control circuit 22 calculates the ratio between the representative values ​​calculated for the liver and the kidneys (step SC4).

[0075] The control circuit 22 determines whether the process from step SC1 to step SC4 has been performed a predetermined number of times, for example, five times (step SC5).

[0076] When the control circuit 22 determines that the processes from step SC1 to step SC4 have not been performed the predetermined number of times (No in step SC5), it repeats steps SC1 to SC4 until they have been performed the predetermined number of times.

[0077] When the control circuit 22 determines that the processes from step SC1 to step SC4 have been performed a predetermined number of times (Yes in step SC5), it calculates a representative value of the ratio of the liver and kidney representative values ​​for the calculated predetermined number of times, for example, five times (step SC6), thereby acquiring a liver-kidney contrast ratio.

[0078] The regions of interest for the liver and kidneys in step SC2 may be set manually via the input interface circuit 20.

[0079] 2, when the control circuit 22 determines that there are no other tissue attribute parameters that need to be acquired, i.e., when the elasticity, viscosity, attenuation rate, normalized local variance, and liver-renal contrast ratio have all been acquired (No in step SA6), it reads out multiple thresholds for each of the elasticity, viscosity, attenuation rate, normalized local variance, and liver-renal contrast ratio from the internal storage circuit 17. Then, the control circuit 22 generates radar chart data representing diagnosis support information using the multiple types of acquired tissue attribute parameters and the multiple thresholds read for each tissue attribute (step SA7).

[0080] For example, when button B6 shown in FIG. 3 is designated, the control circuit 22 executes the display control function 227 and displays a radar chart based on the generated radar chart data on the display device 50 (step SA8).

[0081] Fig. 7 is a diagram illustrating an example of a radar chart displayed on the display device 50 according to the first embodiment. The radar chart illustrated in Fig. 7 indicates which stage each of the acquired elastic modulus, viscosity coefficient, attenuation rate, normalized local variance value, and liver-renal contrast ratio corresponds to.

[0082] Specifically, in Fig. 7, the quantitative values ​​obtained, that is, the elastic modulus, the viscosity modulus, the attenuation rate, the normalized local variance value, and the liver-kidney contrast ratio, are plotted on line segments L1, L2, L3, L4, and L5, respectively, according to the obtained values. In addition, each plotted point is connected to the adjacent point by a line segment. This forms a pentagon P1.

[0083] Also, according to the radar chart shown in FIG. 7, four thresholds are set for the elastic modulus, viscosity, attenuation rate, normalized local dispersion value, and liver-kidney contrast ratio, respectively. Specifically, for the elastic modulus, four thresholds E0, E1, E2, and E3 are displayed on line segment L1. The thresholds on line segment L1 are, for example, in the relationship of E0 < E1 < E2 < E3. For the viscosity, four thresholds D0, D1, D2, and D3 are displayed on line segment L2. The thresholds on line segment L2 are, for example, in the relationship of D0 < D1 < D2 < D3. For the attenuation rate, four thresholds A0, A1, A2, and A3 are displayed on line segment L3. The thresholds on line segment L3 are, for example, in the relationship of A0 < A1 < A2 < A3. For the normalized local dispersion value, four thresholds N0, N1, N2, and N3 are displayed on line segment L5. When observed from the perspective of liver fibrosis, the thresholds on line segment L5 are, for example, in the relationship of N0 < N1 < N2 < N3. For the liver-kidney contrast ratio, four thresholds R0, R1, R2, and R3 are displayed on line segment L4. The thresholds on line segment L4 are, for example, in the relationship of R0 < R1 < R2 < R3.

[0084] According to FIG. 7, the stage of each tissue property parameter can be grasped according to the magnitude relationship between each plotted quantitative value and a plurality of thresholds set for each tissue property parameter. In FIG. 7, a level 1 stage indicating a low degree, a level 2 stage indicating a medium degree, a level 3 stage indicating a high degree, and a level 4 stage indicating a degree of level 3 or higher are displayed in the form of legends in blue, green, brown, and white, respectively. The above-described stages indicate, for example, that the cut-off values of F1 to F4 of the fibrosis stage are assigned to level 1 (E0) to level 4 (E3). Also, the number of stages is not necessarily four, and the number of stages may be changed for each tissue property. In FIG. 7 and the following examples, all parameters are described in a state of being divided into four stages.

[0085] According to Fig. 7, the regions where the elastic modulus, viscosity modulus, attenuation rate, normalized local variance value, and liver-kidney contrast ratio are equal to or less than E0, D0, A0, N0, and R0, respectively, are displayed in blue as stage level 1. For the normalized local variance value, when observing from the viewpoint of fatty liver, a threshold is set so that the value approaches 1 as it moves away from the center O on the line segment L4, for example.

[0086] According to Figure 7, the areas where the elastic modulus, viscosity modulus, attenuation rate, normalized local variance, and liver-kidney contrast ratio are “greater than E0” and “equal to E1,” “greater than D0” and “equal to D1,” “greater than A0” and “equal to A1,” “greater than N0” and “equal to N1,” and “greater than R0” and “equal to R1,” respectively, are displayed in green as level 2 stage.

[0087] Furthermore, according to Figure 7, areas where the elastic modulus, viscosity modulus, attenuation rate, normalized local variance, and liver-kidney contrast ratio are “greater than E1” and “equal to E2,” “greater than D1” and “equal to D2,” “greater than A1” and “equal to A2,” “greater than N1” and “equal to N2,” and “greater than R1” and “equal to R2,” respectively, are displayed in brown as level 3 stage.

[0088] In FIG. 7, the area outside the area indicated by the level 3 stage is displayed in white as the level 4 stage.

[0089] The control circuit 22 may highlight the points plotted according to the acquired quantitative values ​​of the tissue attributes as black dots. FIG. 8 is a diagram showing another example of a radar chart displayed on the display device 50 according to the first embodiment. According to FIG. 8, the quantitative values ​​of each tissue attribute are highlighted as black dots at positions corresponding to each quantitative value in the radar chart. Furthermore, each displayed point is connected to an adjacent point by a solid line. The lines connecting each point may be dashed lines. For example, multiple types of dashed lines may be used depending on the purpose. Furthermore, solid lines and dashed lines may be displayed together in the radar chart.

[0090] Furthermore, when the acquired tissue attribute parameter reaches or exceeds a value corresponding to the set level 4 stage, the control circuit 22 may display the radar chart in the following display mode.

[0091] For example, when the acquired tissue attribute parameter is equal to or greater than the value corresponding to the set level 4 stage, the control circuit 22 generates radar chart data with the tissue attribute parameter set to the maximum value that can be displayed on the radar chart. The control circuit 22 displays a radar chart based on the generated radar chart data on the display device 50. Fig. 9 is a diagram showing an example of a radar chart displayed on the display device 50 according to the first embodiment. According to the radar chart shown in Fig. 9, the acquired elastic modulus is equal to or greater than the value corresponding to the set level 4 stage, and therefore the control circuit 22 displays the elastic modulus at position E3.

[0092] Furthermore, for example, when the acquired tissue attribute parameter is equal to or greater than a value corresponding to the set level 4 stage, the control circuit 22 generates radar chart data in which the tissue attribute parameter is plotted outside the radar chart. The control circuit 22 displays a radar chart based on the generated radar chart data on the display device 50.

[0093] FIG. 10 is a diagram showing an example of a radar chart displayed on a display device according to the first embodiment. According to FIG. 10, the control circuit 22 generates radar chart data in which the acquired elastic modulus is plotted outside the radar chart, that is, at point V1 outside the point representing the threshold value E3. At this time, in FIG. 10, the control circuit 22 displays the part indicated by the solid line inside the radar chart of the line segment V1V2 connecting point V1 and point V2 representing the acquired viscosity as a solid line, and displays the part indicated by the dotted line outside the radar chart as a non-displayed part. Also, in FIG. 10, the control circuit 22 displays the part indicated by the solid line inside the radar chart of the line segment V1V3 connecting point V1 and point V3 representing the acquired normalized local variance value as a solid line, and displays the part indicated by the dotted line outside the radar chart as a non-displayed part.

[0094] According to the first embodiment, the control circuit 22 acquires quantitative values ​​of multiple types of tissue attributes related to a site of interest in the subject P. The control circuit 22 generates diagram data (radar chart data) related to a specified site of interest based on the acquired quantitative values.

[0095] This allows the tissue attributes of the subject to be understood from the shape, size, etc. of a figure represented by a polygon such as a pentagon. In addition, by setting multiple thresholds for each of multiple types of tissue attributes, it is possible to simultaneously understand which stage the quantitative value of each tissue attribute corresponds to. In other words, the diagnostician can make a diagnosis from multiple angles compared to when only tissue attribute parameters corresponding to one type of tissue attribute are presented.

[0096] Therefore, it becomes possible to preferably present a plurality of types of quantified tissue properties.

[0097] [First Modification] The control circuit 22 according to the first embodiment generates radar chart data representing a radar chart such as that shown in FIG. 7, but is not limited thereto. For example, the control circuit 22 may generate diagram data representing a diagram presenting one case. In the following description of the first modified example, the internal storage circuit 17 is assumed to store in advance case information associated with each of a plurality of types of tissue attributes. The case information includes a reference value to be compared with a predetermined tissue attribute parameter. In addition, the plurality of types of tissue attribute parameters are elastic modulus, viscosity modulus, attenuation rate, normalized local variance value, and liver-kidney contrast ratio, and the quantitative values ​​thereof are elastic modulus 12 [kPa], viscosity modulus 0.001 [Pa·s], normalized local variance value 1.6, attenuation rate 0.62 [dB / cm / MHz], and liver-kidney contrast ratio 1.2.

[0098] 1 reads out case information associated with the acquired multiple types of tissue attributes from the internal storage circuitry 17, for example in step SA7 shown in Fig. 2. Then, the control circuit 22 generates diagram data presenting one case based on the quantitative values ​​of the multiple types of tissue attributes and the case information associated with each of the multiple types of tissue attributes.

[0099] Specifically, the control circuit 22 compares, for example, the elastic modulus with a reference value included in case information associated with the tissue property of elasticity, and extracts related disease candidates from the case information associated with elasticity. The same applies to tissue properties other than elasticity. The control circuit 22 determines one case to be presented based on the extracted disease candidates. As a result, diagram data including information representing the determined one case and the determination process of the one case is generated.

[0100] Next, the control circuit 22 shown in Fig. 1 displays a diagram presenting one case on the display device 50 based on the generated diagram data in step SA8 shown in Fig. 2. Fig. 11 is a diagram showing an example of a diagram presenting one case displayed on the display device 50 according to the first modified example. The left column of the diagram shown in Fig. 11 displays the elastic modulus, the viscosity modulus, the normalized local variance value, the attenuation rate, and the liver-kidney contrast ratio. Specifically, the elastic modulus is displayed as 12 [kPa], the viscosity modulus as 0.001 [Pa·s], the normalized local variance value as 1.6, the attenuation rate as 0.62 [dB / cm / MHz], and the liver-kidney contrast ratio as 1.2.

[0101] Furthermore, predetermined case information is displayed in association with each tissue property in the center column of the diagram shown in Fig. 11. Specifically, for elasticity, "LC" indicating Liver Cirrhosis (LC), "NASH" indicating Nonalcoholic SteatoHepatitis (NASH), and "AH" indicating Acute Hepatitis (AH) are displayed in association with each other as disease candidates.

[0102] For the viscosity coefficient, normalized local variance value, attenuation rate, and liver-renal contrast ratio, supplementary information for identifying diseases is displayed. Specifically, "Low Viscous" indicating low viscosity is displayed in association with the viscosity coefficient. For the normalized local variance value, attenuation rate, and liver-renal contrast ratio, "Non FL" indicating non-fatty liver (FL) is displayed in association with each.

[0103] In addition, the right column of the diagram shown in FIG. 11 displays which disease is the candidate displayed in the center column of the diagram shown in FIG. 11. Specifically, "NASH" does not apply to the candidate diseases because the normalized local variance value, attenuation rate, and liver-kidney contrast ratio are "Non FL". Therefore, "X" is displayed in the right column of the diagram shown in FIG. 11. Also, "AH" does not apply because the viscosity is "Low Viscous". Therefore, "X" is displayed in the right column of the diagram shown in FIG. 11. "LC" is determined to apply because, for example, other disease candidates "NASH" and "AH" do not apply. Therefore, "◯" is displayed in the right column of the diagram shown in FIG. 11. That is, "LC" is one case presented, and the diagram shown in FIG. 11 indicates that there is a suspicion of liver cirrhosis in the area of ​​interest of the subject P.

[0104] Although "○" is displayed if the disease applies and "×" is displayed if the disease does not apply, other displays may be used as long as it is clear whether the disease applies or not. For example, "Y" may be displayed to indicate YES if the disease applies, and "N" may be displayed to indicate NO if the disease does not apply. A display in which a box is checked if the disease applies and is not checked if the disease does not apply may also be used. A display in which a box with the name of the disease that applies and a box with the name of the disease that does not apply are distinguished by coloring the background or the like, so that it is clear whether the disease applies or not.

[0105] It should be noted that the diagram shown in FIG. 11 may be displayed together with the radar chart shown in FIG.

[0106] According to the first modification, the control circuit 22 generates diagram data presenting one case based on multiple types of tissue characteristics and case information associated with the multiple types of tissue characteristics, thereby enabling a diagnostician to make a diagnosis by referring to the presented case.

[0107] [Second modified example] In the first embodiment, the control circuit 22 generates diagram data using five tissue attribute parameters, which are elastic modulus, viscosity modulus, attenuation rate, normalized local variance, and liver-kidney contrast ratio. However, the parameters used to generate the diagram data are not limited to tissue attribute parameters. The control circuit 22 may generate diagram data including categories such as the thickness of the abdominal wall of the subject and the results of the blood test of the subject in addition to categories (items) related to tissue attributes. In the following description of the second modified example, the control circuit 22 generates radar chart data based on the four tissue attribute parameters, which are elastic modulus, viscosity modulus, attenuation rate, and normalized local variance, and the thickness of the abdominal wall. In other words, the five items of the radar chart are elastic modulus, viscosity modulus, attenuation rate, normalized local variance, and the thickness of the abdominal wall.

[0108] In the first embodiment, the control circuit 22 reads out a plurality of thresholds for each tissue attribute parameter stored in the internal storage circuit 17, and displays a radar chart showing which stage the acquired tissue attribute parameter corresponds to based on the magnitude relationship between the thresholds and the acquired tissue attribute parameter. However, the display is not limited to the display of the stage based on the threshold. The control circuit 22 may read out statistical values ​​of tissue attribute parameters for each case (e.g., normal liver, fatty liver, and cirrhosis) previously acquired by the ultrasound diagnostic device 1 or other ultrasound diagnostic devices from the internal storage circuit 17, etc., and generate trend map data (diagram data showing a trend) based on the statistical values ​​for each case. In the following description of the second modified example, the control circuit 22 reads out statistical values ​​for each case of four tissue attribute parameters, namely elastic modulus, viscosity modulus, attenuation rate, and normalized local variance, and abdominal wall thickness from the internal storage circuit 17, and generates trend map data showing the statistical values ​​for each case read out.

[0109] Fig. 12 is a diagram showing an example of workflow information displayed on the display device 50 according to the second modified example. According to Fig. 12, a tissue characterization diagnosis support screen is displayed, which serves as a guide for allowing the operator to obtain the abdominal wall thickness and the above-mentioned four tissue characterization parameters and displaying a radar chart for diagnosing the tissue characterization. The tissue characterization diagnosis support screen shown in Fig. 12 displays a button B7 that can obtain the abdominal wall thickness used to generate radar chart data for diagnosing the tissue characterization, together with buttons B1, B2, B3, and B4. This allows the operator to obtain the abdominal wall thickness value and the quantitative values ​​of each tissue characterization in the order of abdominal wall thickness, elastic modulus, viscosity modulus, attenuation coefficient, and normalized local variance value.

[0110] 13 is a flowchart showing an example of the operation of the control circuit 22 when the ultrasound diagnostic device 1 according to the second modification generates a diagram related to tissue characterization. In the following, differences from the first embodiment will be mainly described, and detailed description of similarities will be omitted. In the second modification, the items corresponding to the contents of the radar chart are the thickness of the abdominal wall, the elastic modulus, the viscosity coefficient, the attenuation rate, and the normalized local variance value.

[0111] The control circuit 22 generates workflow information for each item, which indicates the procedure for acquiring the item, in the same manner as in step SA1 (step SA11). Next, the control circuit 22 displays a tissue characterization diagnosis support screen as shown in Fig. 12, in the same manner as in step SA2 (step SA12). Then, the control circuit 22 accepts the selection of an item for which a quantitative value is to be acquired (step SA13). At this time, it is assumed that the items are selected in the order of buttons B7, B1, B2, B3, and B4 in Fig. 12.

[0112] When the button B7 is designated in step SA13, the control circuit 22 acquires the abdominal wall thickness based on the workflow information for acquiring the abdominal wall thickness (step SA14). For example, the control circuit 22 can measure the abdominal wall thickness in advance on the B-mode image by using the caliper function of the control circuit 22 after the B-mode image is frozen in the B-mode image display. The measured abdominal wall thickness value may be stored in the internal storage circuit 17. In step SA14, the control circuit 22 acquires the abdominal wall thickness by reading the abdominal wall thickness value from the internal storage circuit 17. Alternatively, the control circuit 22 may acquire the abdominal wall thickness manually input by the operator using the input device 60 via the input interface circuit 20. For example, when the button B7 is designated, a screen for inputting the abdominal wall thickness is displayed, and the operator may input the abdominal wall thickness using the input device 60. The manually input abdominal wall thickness value is also the abdominal wall thickness previously measured by using the caliper function after the B-mode image is frozen in the B-mode image display.

[0113] When the control circuit 22 acquires the abdominal wall thickness in step SA14 shown in Fig. 13, it updates the implementation status regarding the abdominal wall thickness from "not acquired" to "acquired" (step SA15) in the same manner as in step SA5. Then, the control circuit 22 determines whether there are other items that need to be acquired (step SA16). The control circuit 22 repeatedly executes the processes from step SA12 to step SA16 until it is determined that there are no other items that need to be acquired.

[0114] When the control circuit 22 determines that there are no other items that need to be acquired, that is, when the abdominal wall thickness, elastic modulus, viscosity modulus, attenuation rate, and normalized local variance value have all been acquired (No in step SA16), it reads out the statistical values ​​for each case of the abdominal wall thickness, elastic modulus, viscosity modulus, attenuation rate, and normalized local variance value from the internal storage circuit 17. Then, the control circuit 22 generates diagram data representing diagnostic support information using the acquired items and the statistical values ​​for each case corresponding to the items (step SA17), and displays a diagram based on the generated diagram data on the display device 50 (step SA18).

[0115] 14 to 16 are diagrams showing examples of radar charts displayed on the display device 50 according to the second modified example. In the radar charts shown in FIG. 14 to 16, the thickness of the abdominal wall, the elastic modulus, the viscosity modulus, the damping rate, and the normalized local variance value, which are the acquired quantitative values, are plotted on the line segments L11, L12, L13, L14, and L15, respectively, and pentagons P2, P4, and P5, which connect these values ​​with solid lines, are shown in each diagram. Here, numbers representing the quantitative values ​​of each item are displayed together with the names of each item, and each line segment is marked with a scale. In addition, in each diagram, a pentagon P3, which connects values ​​corresponding to the statistical values ​​of each item in a normal liver with dashed lines, is shown as a display of a trend map based on statistical values ​​(empirical values). The lines of the pentagons P2, P3, P4, and P5 may be solid or dashed, or may be color-coded.

[0116] For example, a pentagon similar to pentagon P3 shown based on the statistical values ​​of normal liver, such as pentagon P2 in the radar chart shown in FIG. 14, represents a case of normal liver.

[0117] 14 to 16, among the five items of the radar chart, the elastic modulus and the viscosity are arranged adjacent to each other, for example, at the upper side of the radar chart. For example, the elastic modulus is arranged at the top, and the viscosity is arranged next to it. In other words, the control circuit 22 generates diagram data by using the diagram data generating function so that the elastic modulus and the viscosity are displayed adjacent to each other on the diagram.

[0118] The attenuation rate and the normalized local variance value are arranged next to each other, for example, at the lower position on the radar chart. For example, the attenuation rate and the normalized local variance value are arranged next to each other at the bottom. That is, the control circuit 22 generates diagram data by using the diagram generation function so that the attenuation rate and the normalized local variance value are displayed next to each other on the diagram. The abdominal wall thickness is arranged next to the normalized local variance value here. The abdominal wall thickness may be arranged next to the attenuation rate. For example, the viscosity rate and the abdominal wall thickness may be arranged interchangeably in the radar charts shown in Figs. 14 to 16.

[0119] It is known that fatty liver is correlated with the attenuation rate and normalized local variance value among the above-mentioned tissue attribute parameters. When the quantitative values ​​obtained for the attenuation rate and normalized local variance value are large, fatty liver tends to be diagnosed. In addition, since the thickness of the abdominal wall represents the thickness of the subcutaneous fat, fatty liver tends to be diagnosed when the value of the abdominal wall thickness is large. For this reason, the control circuit 22 generates radar chart data in which the attenuation rate, normalized local variance value, and abdominal wall thickness are arranged as a whole, for example, on the lower side, and displays a radar chart based on the generated radar chart data on the display device 50. For example, the control circuit 22 generates diagram data by using a diagram generation function so that two or more of the attenuation rate, normalized local variance value, and abdominal wall thickness value are displayed in adjacent positions on the diagram. For example, a pentagon spreading downward, such as the pentagon P4 of the radar chart shown in FIG. 15, represents a case of fatty liver.

[0120] On the other hand, it is known that liver cirrhosis is correlated with the elastic modulus and viscosity modulus among the above-mentioned tissue property parameters. If the quantitative values ​​obtained for the elastic modulus and viscosity modulus are large, liver cirrhosis tends to be diagnosed. For this reason, the control circuit 22 generates radar chart data in which the elastic modulus and viscosity modulus are grouped together and arranged, for example, on the upper side, and displays a radar chart based on the generated radar chart data on the display device 50. For example, a pentagon spreading upward, such as the pentagon P5 in the radar chart shown in FIG. 16, represents a case of liver cirrhosis.

[0121] In this way, the control circuit 22 uses the diagram generation function to generate a diagram with the quantitative values ​​of each tissue attribute arranged on the diagram based on information related to the relationship between the quantitative values ​​of each of multiple types of tissue attributes. By generating radar chart data in which correlated attribute items for each case are arranged next to each other, it becomes possible to display a radar chart that allows for more intuitive diagnosis.

[0122] FIG. 17 is a flowchart showing an example of the operation of the control circuit 22 when calculating a statistical value for each case based on the result of tissue characterization diagnosis using the ultrasound diagnostic device 1 according to the second modification. The control circuit 22 accepts an input of a diagnosis result (for example, a disease such as normal liver, fatty liver, or cirrhosis) via the input interface circuit 20, and acquires information on the diagnosis result (step SD1). The control circuit 22 links the acquired information on the diagnosis result with the quantitative value of each item of the radar chart corresponding to the diagnosis result read from the internal storage circuit 17 (step SD2). The control circuit 22 calculates a statistical value of each item of the acquired diagnosis result (step SD3). For example, the control circuit 22 reads out the statistical value of each item corresponding to the diagnosis result from the internal storage circuit 17, and calculates a new statistical value of each item from the statistical value and the quantitative value of each item linked to the diagnosis result in step SD2. The control circuit 22 updates and stores the statistical value with the calculated new statistical value (step SD4). The control circuit 22, for example, stores in the internal storage circuit 17 new statistical values ​​for each item corresponding to the diagnosis result.

[0123] By updating the statistical values ​​for each case based on the tissue characterization diagnosis results and the quantitative values ​​of each item on the radar chart corresponding to the diagnosis results, it becomes possible to generate trend map data useful for tissue characterization diagnosis and display a trend map.

[0124] FIG. 18 is a diagram showing an example of a radar chart displayed on the display device 50 according to the second modified example. According to the radar chart shown in FIG. 18, a pentagon P6 spreading downward is seen. Therefore, as described above, the liver, which is the site of interest, is suspected of having fatty liver. In such a case, the operator may perform an operation to switch the display of the pentagon P3 representing the trend of normal liver to the display of a pentagon representing the trend of fatty liver.

[0125] 19 is a flowchart showing an example of the operation of the control circuit 22 when switching the display of a diagram representing a trend. The control circuit 22 accepts an input of a case (suspected disease name) via the input interface circuit 20, and acquires case information identifying the suspected disease (step SE1). The control circuit 22 regenerates diagram data representing a trend based on the acquired case information (step SE2). The control circuit 22 reads out, for example, statistical values ​​of each item of the corresponding case from the internal storage circuit 17, and generates diagram data representing a trend based on the statistical values. The control circuit 22 redisplays the diagram representing a trend based on the generated diagram data (step SE3).

[0126] Fig. 20 is a diagram showing an example of a radar chart displayed on the display device 50 according to the second modified example. The control circuit 22 changes the display on the display device 50 by the operation of the flowchart shown in Fig. 19. For example, the diagram showing the trend on the radar chart is switched from a pentagon P3 shown in Fig. 18, which is shown based on the statistical values ​​of each item in a normal liver, to a pentagon P7 shown in Fig. 20, which is shown based on the statistical values ​​of each item in a fatty liver. Since the pentagon P6 on the radar chart shown in Fig. 20 resembles the pentagon P7 shown based on the statistical values ​​of a fatty liver, it becomes easier to understand that there is a suspicion of fatty liver.

[0127] In this way, by appropriately changing the display of the trend of each case based on the statistical values, it is possible to display the trend of each case. Also, by comparing the trend diagram of each case with the trend diagram based on the measurement results, it is possible to contribute to diagnosis.

[0128] The pentagon P3 shown in Fig. 18 and the pentagon P7 shown in Fig. 20 may be displayed simultaneously. The control circuit 22 may generate trend map data representing a plurality of cases and display a plurality of trend maps simultaneously. Alternatively, the control circuit 22 may generate trend map data representing a plurality of cases and automatically display a trend map based on trend map data that is closest to the measurement result. For example, the control circuit 22 calculates the sum of squares of the difference between the quantitative value of the tissue attribute related to the measurement result and the value of the trend map data, and displays the trend map based on the trend map data with the minimum calculated sum of squares of the difference.

[0129] So far, we have described the case where the suspected disease is unknown, but if the suspected disease is known to some extent, the control circuit 22 may generate diagram data and display a diagram more suitable for the diagnosis. For example, when the operator inputs a suspected disease using the input device 60, radar chart data is generated and a radar chart is displayed for the radar chart item suitable for diagnosing that disease.

[0130] FIG. 21 is a flow chart showing an example of the operation of the control circuit 22 when generating a diagram suitable for diagnosing a suspected disease. The control circuit 22 accepts an input of a case (suspected disease name) via the input interface circuit 20 and acquires case information for identifying the suspected disease (step SF1). The control circuit 22 generates diagram data according to the acquired case information (step SF2). For example, when the control circuit 22 acquires case information indicating that the suspected disease is "fatty liver", the control circuit 22 reads out quantitative values ​​and statistical values ​​related to the attenuation rate, normalized local variance value, and abdominal wall thickness from the internal storage circuit 17. The control circuit 22 then generates diagram data using the quantitative values ​​and statistical values. The control circuit 22 displays a diagram based on the generated diagram data on the display device 50 (step SF3).

[0131] Alternatively, the control circuit 22 may generate diagram data and display a diagram based on the selected item, thereby generating diagram data and displaying a diagram more suitable for diagnosis.

[0132] 22 is a flowchart showing an example of the operation of the control circuit 22 when selecting an item and generating a diagram. The control circuit 22 accepts the selection of an item via the input interface circuit 20 and acquires information on the selected item (step SG1). The control circuit 22 generates diagram data according to the acquired information on the item (step SG2). The control circuit 22 reads, for example, quantitative values ​​and statistical values ​​corresponding to the acquired information on the item from the internal storage circuit 17. The control circuit 22 then generates diagram data using the quantitative values ​​and statistical values. The control circuit 22 displays a diagram based on the generated diagram data on the display device 50 (step SG3).

[0133] Here, the internal storage circuit 17 may group and store the items of the radar chart. For example, the control circuit 22 groups the items of the radar chart into elastic modulus and viscosity coefficient, which are useful for diagnosing liver cirrhosis, and attenuation rate, normalized local variance value, and abdominal wall thickness, which are useful for diagnosing fatty liver, and stores them in the internal storage circuit 17. The control circuit 22 may arrange the items of the radar chart generated in the above-mentioned step SG2 so that the grouped items are adjacent to each other.

[0134] The control circuit 22 may be able to change the items of the radar chart after displaying the radar chart. For example, by making the number of acquired items for which selection is accepted greater than the number of displayed items of the radar chart in step SA13 shown in FIG. 13 , the control circuit 22 acquires in advance a greater number of quantitative values ​​than the number of displayed items of the radar chart. The acquired quantitative values ​​may be stored in the internal storage circuit 17.

[0135] Items other than the quantitative values ​​of tissue properties in the radar chart may be blood test results, for example, FIB-4 index values. The FIB-4 index is an index for estimating liver fibrosis. In this case, a button for acquiring the FIB-4 index value may be displayed in place of the button B7 for acquiring the abdominal wall thickness in the tissue property diagnosis support screen shown in FIG. 12. When the button is selected, the control circuit 22 acquires the FIB-4 index value based on the workflow information for acquiring the FIB-4 index value in step SA13 shown in FIG. 13 (step SA14). The blood test results, such as the FIB-4 index value, may be acquired from an external device 40, for example, a hospital information system (HIS), which can communicate with the ultrasound diagnostic device 1 via the network 100, and stored in the internal storage circuit 17, or may be manually input by the input device 60.

[0136] 23 is a flowchart showing an example of the operation of the control circuit 22 when acquiring other test result information from the external device 40. The control circuit 22 reads out patient identification information, for example, a patient ID, from the internal storage circuit 17, and transmits the patient identification information to the external device 40 (step SH1). The control circuit 22 acquires other test result information, for example, blood test information, corresponding to the patient identification information, from the external device 40, for example, a hospital information system (step SH2).

[0137] It is known that the value of the FIB-4 index is correlated with liver cirrhosis. A large value of the FIB-4 index indicates a suspicion of liver cirrhosis. Therefore, when the FIB-4 index is adopted as an item of the radar chart, the control circuit 22 may generate radar chart data in which the values ​​of the elastic modulus, the viscosity coefficient, and the FIB-4 index are arranged together, for example, on the upper side, and display a radar chart based on the generated radar chart data on the display device 50. In this case, a pentagon spreading upward represents a case of liver cirrhosis.

[0138] As an example of a trend map, a diagram displaying a pentagon based on the statistical values ​​of each item has been shown, but the control circuit 22 may generate diagram data for generating a vague trend map rather than a clear trend map such as a pentagon connected by lines.

[0139] FIG. 24 is a diagram showing an example of a radar chart displayed on the display device 50 according to the second modified example. According to the radar chart shown in FIG. 24, a first region A11 suspected of liver cirrhosis and a second region A12 suspected of fatty liver are shown on the radar chart. The first region A11 and the second region A12 may be regions calculated from statistical values ​​of each item based on the diagnosis result of the ultrasound diagnostic device 1, for example. In FIG. 24, the boundary line of the first region A11 and the boundary line of the second region A12 are shown by solid lines, but the boundary line may be a blurred boundary instead of a solid line. The first region A11 and the second region A12 may be expressed by a filled color with an adjustable transparency.

[0140] According to the second modification, the display of such various trend maps is useful for tissue characterization.

[0141] [Second embodiment] In the first embodiment, the ultrasound diagnostic device 1 generates diagram data (radar chart data) using quantitative values ​​of tissue characteristics acquired in real time using the ultrasound probe 70, but is not limited to this. In the second embodiment, a case will be described in which a medical image processing device such as a workstation acquires quantitative values ​​of tissue characteristics from an external device such as a medical image diagnostic device connected via a communication network, and generates diagram data using the acquired quantitative values.

[0142] Fig. 25 is a block diagram showing an example of the configuration of an analysis system according to the second embodiment. The analysis system shown in Fig. 25 includes a medical image processing device 80 and a medical image diagnostic device 90. The medical image processing device 80 and the medical image diagnostic device 90 are connected to a local network, and transmit information to a predetermined device and receive information transmitted from the predetermined device. The analysis system may be connected to an external network in addition to or instead of the local network.

[0143] The medical image processing device 80 includes an input interface circuit 81 , a display circuit 82 , a communication interface circuit 83 , a memory circuit 84 , and a processing circuit 85 .

[0144] The input interface circuitry 81 is realized by, for example, a mouse, a keyboard, a touch pad where instructions are input by touching the operation surface, etc. The input interface circuitry 81 receives, for example, an instruction to start tissue characterization from an operator.

[0145] The display circuit 82 has, for example, a CRT display, a liquid crystal display, an organic EL display, an LED display, a plasma display, etc. The display circuit 82 may be a touch panel or a TCS. The display circuit 82 is also connected to the processing circuit 85 and displays a signal supplied from the processing circuit 85 to the outside. The display circuit 82 displays, for example, a diagram based on diagram data supplied from the processing circuit 85.

[0146] The communication interface circuit 83 performs data communication with a medical image diagnostic apparatus 90 and an external device 91 connected via a network or the like shown in FIG.

[0147] The memory circuitry 84 includes, for example, a magnetic or optical recording medium, or a processor-readable recording medium such as a semiconductor memory. The memory circuitry 84 stores a control program for implementing various functions according to the present embodiment. The memory circuitry 84 also stores a plurality of thresholds for each tissue attribute in advance.

[0148] The processing circuitry 85 is, for example, a processor that functions as the core of the medical image processing device 80. The processing circuitry 85 executes an operation program stored in the memory circuitry 84, thereby realizing a function corresponding to the operation program. Specifically, the processing circuitry 85 has a quantitative value acquisition function 851, a diagram data generation function 852, and a display control function 853.

[0149] The quantitative value acquisition function 851 is a function for acquiring quantitative values ​​of tissue properties of a region of interest of a subject. When the quantitative value acquisition function 851 is executed, the processing circuitry 85 acquires ultrasound image data (including B-mode image data and tissue property image data) stored in the medical image diagnostic device 90 described later or the external device 91, for example, via the communication interface circuitry 83. The processing circuitry 85 uses the acquired ultrasound image data to set a region of interest and calculate a representative value, etc. This allows the quantitative value of tissue properties based on the acquired ultrasound image data to be acquired. Note that the processing circuitry 85 may acquire a quantitative value of a predetermined tissue property from the medical image diagnostic device 90, for example, via the communication interface circuitry 83.

[0150] The diagram data generating function 852 is a function for generating a diagram for a region of interest based on multiple types of quantitative values ​​acquired by the quantitative value acquiring function 851. When the diagram data generating function 852 is executed, the processing circuitry 85 generates diagram data as diagnosis assisting information using the quantitative values ​​of multiple types of tissue attributes acquired from the region of interest of the subject and multiple thresholds set for the multiple types of tissue attributes, respectively.

[0151] The display control function 853 is a function for displaying diagram data and the like generated by the diagram data generation function 852. When the display control function 853 is executed, the processing circuitry 85 displays a diagram based on the diagram data on the display circuitry 82. The processing circuitry 85 may generate a graphical user interface (GUI) for an operator (e.g., a diagnostician) to input various instructions via the input interface circuitry 81, and cause the display circuitry 82 to display the generated GUI.

[0152] The medical image diagnostic device 90 is a device capable of acquiring a predetermined medical image by scanning a subject. The medical image diagnostic device 90 is an ultrasound diagnostic device, an MRI device, a CT device, a nuclear medicine diagnostic device, etc. In the second embodiment, the medical image diagnostic device 90 is an ultrasound diagnostic device.

[0153] The external device 91 is, for example, a database of a PACS, which is a system for managing data of various medical images, or a database of an electronic medical record system for managing electronic medical records to which medical images are attached.

[0154] Next, the operation of the medical image processing apparatus 80 according to the second embodiment will be described with reference to the flowchart of FIG. 26. FIG. 26 is a flowchart showing an example of the operation of the processing circuit 85 when the medical image processing apparatus 80 according to the second embodiment generates a diagram related to tissue characterization diagnosis. In the following description, it is assumed that the medical image diagnostic apparatus 90 acquires ultrasound image data for acquiring quantitative values ​​of multiple types of tissue characterization in advance. It is also assumed that the acquired ultrasound image data is stored in advance in a memory circuit provided in the medical image diagnostic apparatus 90. It is also assumed that the quantitative values ​​of multiple types of tissue characterization to be acquired are elastic modulus, viscosity modulus, attenuation rate, normalized local variance value, and liver-kidney contrast ratio. It is also assumed that the target site of the tissue characterization diagnosis is the liver. It is also assumed that the diagram is a radar chart based on radar chart data. It is also assumed that the tissue characterization parameters used in generating the radar chart data are elastic modulus, viscosity modulus, attenuation rate, normalized local variance value, and liver-kidney contrast ratio. The quantitative values ​​of the multiple types of tissue characteristics thus obtained may be stored in an external storage device other than the medical image diagnostic device 90 connected to the medical image processing device 80 via a network.

[0155] When an input is made via the input interface circuit 81 to execute tissue characterization diagnosis, for example, regarding the liver, the processing circuit 85 executes a quantitative value acquisition function 851 and acquires ultrasound image data, such as B-mode image data and tissue characterization image data, stored in a memory circuit included in the medical image diagnostic device 90, via the communication interface circuit 83. Using the acquired ultrasound image data, the processing circuit 85 sets a region of interest and calculates a representative value, etc., for each of a plurality of types of tissue characterization. This allows quantitative values ​​of a plurality of types of tissue characterization based on the acquired ultrasound image data to be acquired (step SG1). Specifically, the processing circuit 85 acquires the elastic modulus, the viscosity coefficient, the attenuation rate, the normalized local variance value, and the liver-kidney contrast ratio.

[0156] Upon acquiring the elastic modulus, the viscosity modulus, the attenuation rate, the normalized local variance, and the liver-renal contrast ratio, the processing circuitry 85 executes a diagram data generating function 852 and reads out a plurality of thresholds set for the elastic modulus, the viscosity modulus, the attenuation rate, the normalized local variance, and the liver-renal contrast ratio from the memory circuitry 84. Then, the processing circuitry 85 generates radar chart data as diagnosis support information using the acquired plurality of types of tissue attribute parameters and the plurality of thresholds set for the plurality of types of tissue attributes (step SG2).

[0157] The processing circuit 85 executes the display control function 853 and displays a radar chart based on the generated radar chart data on the display circuit 82 (step SG3).

[0158] According to the second embodiment, the processing circuitry 85 acquires quantitative values ​​of multiple types of tissue attributes related to a region of interest in a subject from the medical image diagnostic device 90. This makes it possible to support diagnosticians in creating electronic medical records, etc., even if the medical image diagnostic device 90 is not nearby.

[0159] [Other embodiments] In the above embodiment, the control circuit 22 generates diagram data using quantitative values ​​of tissue properties acquired by an ultrasonic diagnostic device, but is not limited to this. For example, the control circuit 22 may generate diagram data using elastic modulus that can be acquired by MR elastography (MRE) technology using an MRI device, and X-ray attenuation rate that can be acquired by an X-ray CT device.

[0160] Also, in addition to categories (items) related to tissue properties such as elastic modulus, viscosity modulus, attenuation rate, brightness ratio, brightness variance value, and strain ratio, diagram data including other categories such as BMI, abdominal wall thickness, and blood test results (alanine aminotransferase (ALT), aspartate aminotransferase (AST), and gamma-glutamyl transpeptidase (gamma-GTP)) may be generated. In this case, the category is input, for example, by the user via an interface (by character input or by selection from among multiple candidates). Also, the cutoff value is input, for example, by the user via the input device 60 (by input or by selection from among multiple candidates). At least one of the category and the cutoff value may be preset.

[0161] In the above embodiment, the target site of tissue characterization diagnosis is the liver, but this is not limited to this. For example, tissue characterization diagnosis may be performed on the mammary gland. In this case, the control circuit 22 obtains quantitative values ​​of multiple types of tissue characteristics related to the mammary gland, and generates diagram data such as radar chart data using the obtained quantitative values.

[0162] In the above embodiment, when displaying a pentagonal radar chart, the control circuit 22 reflects all of the quantitative values ​​of the corresponding five types of tissue attributes in the pentagonal radar chart data and displays them, but this is not limited thereto. For example, when only the quantitative values ​​of four types of tissue attributes are acquired, the tissue attribute parameters for which the quantitative values ​​could not be acquired may not be displayed as points. FIG. 27 is a diagram showing an example of a radar chart according to another embodiment. FIG. 27 shows a radar chart in the case where the quantitative values ​​related to the liver-renal contrast ratio are not acquired. According to FIG. 27, the quantitative values ​​related to the liver-renal contrast ratio are not plotted as points, and the lines connecting the points on which the quantitative values ​​related to the attenuation rate are plotted and the points on which the quantitative values ​​related to the normalized local variance value are plotted are displayed as, for example, red dashed lines. On the other hand, the lines connecting the points on which the other quantitative values ​​are plotted are displayed as black solid lines. In this way, by displaying the lines crossing the line segments related to the tissue attributes for which the quantitative values ​​have not been acquired as red dashed lines rather than simply as black solid lines, it is possible to prevent the user from mistaking that there is a value for the tissue attributes for which the quantitative values ​​have not been acquired.

[0163] In the above embodiment, a pentagonal radar chart is displayed regardless of the type of quantitative values ​​of the acquired tissue attributes, but the present invention is not limited to this. For example, if quantitative values ​​of only four types of tissue attributes are acquired, a square radar chart reflecting the four types of tissue attributes may be displayed.

[0164] In the above embodiment, the order of obtaining the quantitative values ​​of the tissue attributes is predetermined, but this is not limiting. Fig. 28 is a diagram showing an example of a tissue attribute diagnosis support screen according to another embodiment. In Fig. 28, the operator specifies any one of the regions F21, F22, F23, F24, and F25, and the quantitative values ​​of the specified tissue attributes are obtained. It is also possible for the operator to perform a single operation to automatically obtain all five quantitative values ​​of the tissue attributes.

[0165] In the above embodiment, the control circuit 22 generates a diagram after acquiring all the quantitative values ​​of the five types of tissue attributes, but this is not limited to the above. For example, the control circuit 22 first generates diagram data (e.g., radar chart data) in which the quantitative values ​​of the tissue attributes are not reflected. Then, the control circuit 22 updates the diagram data generated based on the acquired quantitative value every time a quantitative value of one tissue attribute is acquired. Note that the control circuit 22 may update the diagram data generated based on the acquired quantitative value every time a quantitative value of one tissue attribute is acquired, and display a diagram based on the updated diagram data on the display device 50.

[0166] In the above embodiment, the control circuit 22 generates diagram data (radar chart data) using quantitative values ​​of multiple types of tissue attributes acquired in one quantitative value acquisition, but is not limited to this. For example, the control circuit 22 may generate diagram data using an average value of quantitative values ​​of multiple types of tissue attributes repeatedly acquired over a predetermined period in the past, and display a diagram based on the generated diagram data.

[0167] At this time, the control circuit 22 displays a diagram based on diagram data using, for example, the quantitative values ​​of multiple types of tissue characteristics acquired in the most recent quantitative value acquisition and the average value of the quantitative values ​​of multiple types of tissue characteristics acquired repeatedly in the past. The control circuit 22 generates diagram data such that, in the displayed diagram, a graph formed by the most recently acquired quantitative values ​​and a graph formed by the average value of the quantitative values ​​acquired repeatedly in the past are displayed with at least one or more different line types and colors so that they can be clearly distinguished from each other.

[0168] In the above embodiment, for example, the control circuit 22 generates diagram data based on the quantitative values ​​of multiple types of tissue attributes and displays a diagram based on the generated diagram data, but this is not limited thereto. For example, the control circuit 22 may be able to search for similar cases based on the outline of a graph formed by the quantitative values ​​of multiple types of tissue attributes and / or the tendency of the values ​​(such as which tissue attribute has a prominent value). Specifically, case data in which data representing the outline of a graph formed by quantitative values ​​(past data) of multiple types of tissue attributes previously acquired and a result of a definitive diagnosis made by a diagnostician or the like based on the quantitative values ​​are associated with each other are stored in a predetermined database in advance. At this time, a common threshold value is set for each tissue attribute when generating data representing the outline of a graph to be used as a search key and when generating data representing the outline of a graph of past data to be searched.

[0169] The control circuit 22 extracts case data having a similar outline by, for example, comparing data representing the outline of a graph generated from the quantitative values ​​of multiple types of tissue properties most recently obtained with data representing the outline of a graph generated from past data. The control circuit 22 displays the result of a definitive diagnosis contained in the extracted case data. This enables the diagnostician to make an objective diagnosis based on the past data. The data representing the outline of the graph used as a search key may be associated with the result of a definitive diagnosis finally determined by the diagnostician and stored in the database as new case data.

[0170] In the above embodiment, the diagram data (radar chart data) generated in the ultrasound diagnostic device 1 and the medical image processing device 80 are used in the ultrasound diagnostic device 1 and the medical image processing device 80, respectively, but are not limited to this. The generated diagram data may be output to an external device that creates, for example, an electronic medical record, via the communication interface circuit 21 included in the ultrasound diagnostic device 1 or the communication interface circuit 83 included in the medical image processing device 80.

[0171] In the above embodiment, the diagram data (radar chart data) generated in the ultrasound diagnostic device 1 and the medical image processing device 80 are only displayed as diagrams on the display device 50 and the display circuit 82, respectively, but the present invention is not limited to this. For example, when an area in the radar chart shown in Fig. 10 in which an item name representing a predetermined tissue attribute is displayed is specified, the control circuit 22 or the processing circuit 85 may display an image based on image data generated when obtaining a quantitative value of the tissue attribute, and / or a thumbnail image in which the image is displayed in a reduced size. This relieves the operator, for example, from the hassle of having to temporarily exit a mode related to tissue attribute diagnosis in order to check an image related to the quantitative value of the tissue attribute.

[0172] The elastic image data and the viscous image data may be generated based on a common signal or common data. In order to generate the elastic image data and the viscous image data, at least one push pulse must be transmitted and a tracking pulse must be transmitted and received multiple times, and it takes more time to generate one frame of image data than to generate other image data. As described above, when the elastic image data and the viscous image data are generated based on a common signal or common data, the diagnosis time is significantly reduced.

[0173] Also, the acquisition of tissue attribute parameters necessary for generating a diagram and the display of the diagram may be performed by one-button operation. In this case, the region of interest for acquiring the representative value of the tissue attribute parameter is set by the user referring to and specifying ultrasound image data such as B-mode image data or tissue attribute image data generated before the one-button operation. In this case, the set region of interest is fixed when acquiring the tissue attribute parameter. Alternatively, the region of interest may be automatically identified by analyzing the B-mode image data or at least one type of tissue attribute image data. For example, the region of interest is determined by calculating the variance for each local area for the brightness value of the B-mode image data, and a region with a relatively small variance is determined as the region of interest. Also, for example, the variance for each local area for the tissue attribute parameter of the tissue attribute image data is calculated, and a region with a relatively small variance is determined as the measurement region. The shape and size of the region of interest may be determined in advance, such as an ellipse or a rectangle, or the variance may be compared with a threshold value, and all regions in which a variance smaller than the threshold value is calculated may be determined as the region of interest.

[0174] The term "processor" used in the above description means a circuit such as a central processing unit (CPU), a graphics processing unit (GPU), or an application specific integrated circuit (ASIC), a programmable logic device (e.g., 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 a memory circuit. Note that each processor in this embodiment is not limited to being configured as a single circuit for each processor, and may be configured as a single processor by combining multiple independent circuits to realize its function. Furthermore, multiple components in FIG. 1 and FIG. 12 may be integrated into a single processor to realize its function.

[0175] According to at least one of the embodiments described above, it is possible to suitably present a plurality of types of quantified tissue attributes.

[0176] Although some 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 novel embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their modifications are included in the scope and spirit of the invention, and are included in the scope of the invention and its equivalents described in the claims. [Explanation of symbols]

[0177] 1...ultrasonic diagnostic device, 10...device body, 11...ultrasonic transmission circuit, 12...ultrasonic reception circuit, 13...B-mode processing circuit, 14...Doppler processing circuit, 15...image generation circuit, 17...internal memory circuit, 18...image memory, 19...image database, 20...input interface circuit, 21...communication interface circuit, 22...control circuit, 40...external device, 50...display device, 60...input device, 70...ultrasonic probe, 80...medical image processing device, 81...input interface circuit, 82...display circuit, 83...communication interface circuit, 84...memory circuit, 85...processing circuit, 90...medical image diagnostic device, 91...external device, 100...network, 221...quantitative value acquisition function, 223...diagram data generation function, 225...workflow information generation function, 227...display control function, 229...system control function, 851...quantitative value acquisition function, 852...diagram data generation function, 853...display control function.

Claims

1. an acquisition unit for acquiring quantitative values ​​of multiple types of tissue properties for a site of interest of the same subject; a diagram generating unit that generates a diagram for the subject that indicates the quantitative values ​​of the tissue properties by the type, the quantitative values ​​of the plurality of types of tissue properties include at least an elasticity quantitative value representing the elasticity of the tissue, a viscosity quantitative value representing the viscosity of the tissue, and an attenuation quantitative value representing the attenuation of ultrasonic waves in the tissue; The diagram generating unit generates the diagram in which at least two of the elastic quantitative value, the viscous quantitative value, and the damping quantitative value are arranged adjacent to each other on the diagram. Analysis device.

2. an acquisition unit for acquiring quantitative values ​​of multiple types of tissue properties for a site of interest of the same subject; a diagram generating unit configured to generate a diagram for the subject in which the quantitative values ​​of the tissue properties are arranged by the type and in which a disease can be identified based on a positional relationship between the quantitative values. Analysis device.

3. The analysis device according to claim 1 , further comprising a display control unit that displays the diagram.

4. The analysis device according to claim 1 , wherein the diagram is a radar chart.

5. 3. The analysis device according to claim 1, wherein the diagram is a bar graph.

6. The analysis device according to claim 1 , wherein the acquisition unit acquires the quantitative value corresponding to at least one of the plurality of types of tissue characteristics from an external device.

7. The analysis device according to claim 1 , wherein the diagram generating unit updates the diagram every time the quantitative value is obtained.

8. The analysis device according to claim 1 , further comprising a workflow information generating unit that generates workflow information indicating a procedure for acquiring the quantitative values ​​for each of the plurality of types of tissue attributes.

9. 3. The analysis device according to claim 1, further comprising an output unit that outputs the diagram to an external device.

10. A scanning unit that scans the region of interest is further provided, the acquisition unit acquires the quantitative value corresponding to at least one of the plurality of types of tissue attributes by analyzing a result of the scan. The analysis device according to claim 1 or 2.

11. The quantitative values ​​include at least an elasticity quantitative value representing the elasticity of a tissue, a viscosity quantitative value representing the viscosity of the tissue, and an attenuation quantitative value representing the attenuation of an ultrasonic wave in the tissue; The diagram generating unit generates the diagram in which at least two of the quantitative values ​​of the elasticity, the viscosity, and the damping are arranged adjacent to each other on the diagram. The analysis device according to claim 2 .

12. Computer, an acquisition unit that acquires quantitative values ​​of a plurality of types of tissue properties for a site of interest of the same subject; and a diagram generation unit that generates a diagram for the subject that indicates the quantitative values ​​of the tissue properties by type, the quantitative values ​​of the plurality of types of tissue properties include at least an elasticity quantitative value representing the elasticity of the tissue, a viscosity quantitative value representing the viscosity of the tissue, and an attenuation quantitative value representing the attenuation of ultrasonic waves in the tissue; The diagram generating unit generates the diagram in which at least two of the elastic quantitative value, the viscous quantitative value, and the damping quantitative value are arranged adjacent to each other on the diagram. Analysis program.

13. Computer, an acquisition unit that acquires quantitative values ​​of multiple types of tissue attributes for a site of interest of the same subject; and a diagram generation unit that generates a diagram for the subject in which the quantitative values ​​of the tissue attributes are arranged by type and in which diseases can be identified based on the relative positions of the quantitative values. Analysis program.

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