Ultrasound diagnostic device and fat rate estimation method

Abstract

To estimate a fat rate or calculate a value approximate to MRI-DFF, by an ultrasound diagnostic device.SOLUTION: A two-dimensional region of interest is set within the liver of a subject (S12). Based on first reception information obtained from the two-dimensional region of interest, a first parameter group including a first attenuation coefficient is calculated (S16). Based on second reception information obtained from the two-dimensional region of interest, a second parameter group including a second attenuation coefficient is calculated (S20). By giving a parameter set including the first parameter group and the second parameter group to a mathematical model, an estimate of a fat rate is calculated (S22).SELECTED DRAWING: Figure 8

Description

[Technical Field]

[0001] The present disclosure relates to an ultrasound diagnostic apparatus and a fat percentage estimation method, and in particular to a technique for estimating a fat percentage in the liver. [Background technology]

[0002] In order to evaluate the properties of liver tissue, particularly the degree of fatty liver, it is necessary to measure the fat fraction of the liver.

[0003] Some ultrasound diagnostic devices have the function of measuring the attenuation coefficient (attenuation rate) in the liver. In such ultrasound diagnostic devices, ultrasonic waves are transmitted to the liver and reflected waves from the liver are received. The attenuation coefficient is calculated based on the received information. The attenuation coefficient is a parameter that changes depending on the properties of liver tissue. Although a certain correlation has been recognized between the attenuation coefficient and the fat percentage, the attenuation coefficient does not directly represent the fat percentage.

[0004] The MRI-PDFF (Proton Density Fat Fraction) (hereinafter simply referred to as PDFF) of the liver, measured using an MRI (Magnetic Resonance Imaging) device, indicates the ratio of the amount of protons contained in water molecules to the amount of protons contained in fat molecules. In other words, PDFF directly represents the fat percentage of the liver. However, MRI devices are expensive and large. There is a need for a technology that can more easily measure the fat percentage of the liver. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] International Publication No. 2017 / 0688892 [Patent Document 2] Japanese Patent Application Publication No. 2020-354 [Non-patent literature]

[0006] [Non-Patent Document 1] Hidekatsu Kuroda et al., Multivariable Quantitative US Parameters for Assessing Hepatic Steatosis, Radiology, Volume 309, Number 1, 2023. Summary of the Invention [Problem to be solved by the invention]

[0007] It is desirable to estimate the fat percentage or calculate a value that approximates the PDFF using an ultrasound diagnostic device.

[0008] Patent Document 1 discloses an ultrasonic diagnostic device that measures an attenuation coefficient. In this ultrasonic diagnostic device, the attenuation coefficient is calculated based on a first received signal obtained by forming a first ultrasonic beam and a second received signal obtained by forming a second ultrasonic beam. However, Patent Document 1 does not disclose a technique for estimating a fat percentage, particularly a technique for estimating a fat percentage based on multiple attenuation coefficients.

[0009] Patent Document 2 also discloses an ultrasonic diagnostic device that measures the attenuation coefficient, but Patent Document 2 does not disclose any technology for estimating the fat percentage.

[0010] Non-Patent Document 1 describes the relationship between the attenuation coefficient measured by an ultrasound diagnostic device and the PDFF measured by an MRI device. However, Non-Patent Document 1 does not disclose a technique for estimating fat percentage based on multiple attenuation coefficients.

[0011] An object of the present disclosure is to estimate a fat percentage or calculate a value approximating the PDFF in an ultrasound diagnostic device. [Means for solving the problem]

[0012] The ultrasound diagnostic device according to the present disclosure is characterized by including: a first calculation unit that calculates a plurality of attenuation coefficients based on a plurality of pieces of reception information having a plurality of different frequency characteristics acquired from the liver of a subject; and a second calculation unit that calculates an estimated value of a fat percentage based on a parameter set including the plurality of attenuation coefficients.

[0013] The fat percentage estimation method according to the present disclosure is characterized by including the steps of: calculating a plurality of attenuation coefficients based on a plurality of pieces of received information having a plurality of different frequency characteristics obtained from the liver of a subject; and calculating an estimated value of the fat percentage based on a parameter set including the plurality of attenuation coefficients. [Effects of the Invention]

[0014] According to the present invention, the ultrasonic diagnostic device can estimate the fat percentage or calculate a value approximating the PDFF. [Brief explanation of the drawings]

[0015] [Figure 1] 1 is a block diagram showing an example of the configuration of an ultrasound diagnostic apparatus according to an embodiment. [Figure 2] 2 is a block diagram showing an example of the configuration of a calculation module shown in FIG. 1. FIG. [Figure 3] FIG. [Figure 4] FIG. 10 is a diagram illustrating a reception intensity matrix. [Figure 5] FIG. 1 is a diagram illustrating a method for estimating a fat percentage. [Figure 6] FIG. 1 is a diagram illustrating a mathematical model creation method. [Figure 7] FIG. 10 is a diagram showing a display example. [Figure 8] 2 is a flowchart showing the operation of the ultrasonic diagnostic apparatus shown in FIG. [Figure 9] 10 is a flowchart showing the operation of an ultrasonic diagnostic apparatus according to a modified example. DETAILED DESCRIPTION OF THE INVENTION

[0016] Hereinafter, an embodiment will be described with reference to the drawings.

[0017] (1) Overview of the embodiment An ultrasound diagnostic apparatus according to an embodiment includes a first calculation unit and a second calculation unit. The first calculation unit calculates a plurality of attenuation coefficients based on a plurality of pieces of reception information having a plurality of different frequency characteristics acquired from the liver of a subject. The second calculation unit calculates an estimated value of a fat percentage based on a parameter set including the plurality of attenuation coefficients.

[0018] The acoustic characteristics of biological tissue depend on the frequency of the ultrasound propagating through the biological tissue. The above-mentioned multiple pieces of received information all reflect the properties of liver tissue, but each has a different frequency characteristic. Multiple attenuation coefficients are calculated based on such multiple pieces of received information. By calculating an estimated value of fat percentage based on the multiple attenuation coefficients, the reliability of the estimated value can be improved.

[0019] In an embodiment, the parameter set includes a plurality of parameters other than the plurality of attenuation coefficients, which are calculated from the plurality of received signals. By using such a parameter set, the estimation accuracy of the fat percentage can be further improved. The parameter set may include parameters other than parameters obtained by ultrasound diagnosis. To obtain the plurality of received signals, a plurality of transmitted signals having a plurality of different center frequencies may be used, or a plurality of receiving filters having a plurality of different frequency characteristics may be used. The frequency characteristics refer to a frequency band.

[0020] In an embodiment, the second calculation unit has a model created so that the estimated value of fat percentage approximates the MRI-PDFF. A parameter set is provided to the model, and the estimated value of fat percentage is calculated based on the parameter set. The model is, for example, a mathematical model generated by multiple regression analysis, or an AI model generated through a machine learning process. The mathematical model refers to one or more calculation formulas.

[0021] In an embodiment, the plurality of pieces of reception information include first reception information having a first frequency characteristic and second reception information having a second frequency characteristic. The plurality of attenuation coefficients include a first attenuation coefficient calculated based on the first reception information and a second attenuation coefficient calculated based on the second reception information. The plurality of pieces of reception information may be composed of three or more pieces of reception information, or the plurality of attenuation coefficients may be composed of three or more attenuation coefficients.

[0022] An ultrasound diagnostic device according to an embodiment includes an ultrasound probe that transmits a first ultrasound wave having a first center frequency into a subject to acquire first reception information, and transmits a second ultrasound wave having a second center frequency different from the first center frequency into the subject to acquire second reception information.

[0023] In the embodiment, transmission and reception for forming a tomographic image, transmission and reception for acquiring first reception information, and transmission and reception for acquiring second reception information are performed, and all or part of these transmission and reception may be integrated.

[0024] An ultrasound diagnostic apparatus according to an embodiment includes a generator. The generator generates first reference information to be compared with the first received information and second reference information to be compared with the second received information. A first calculation unit calculates a first attenuation coefficient based on the first received information and the first reference information. The first calculation unit also calculates a second attenuation coefficient based on the second received information and the second reference information.

[0025] In an embodiment, the first reference information and the second reference information are each defined by a predetermined calculation formula. In this case, the information generator is configured by a calculator. The first reference information and the second reference information may each be configured as a predetermined numeric sequence. In this case, the generator may be configured by a memory.

[0026] In an embodiment, the first received information and the second received information are each information acquired from a two-dimensional region within the subject. The first calculation unit calculates a first attenuation matrix based on the first received information and the first reference information, and calculates a first parameter group including a first attenuation coefficient, a first attenuation average, and a first attenuation variance based on the first attenuation matrix. The first calculation unit also calculates a second attenuation matrix based on the second received information and the second reference information, and calculates a second parameter group including a second attenuation coefficient, a second attenuation average, and a second attenuation variance based on the second attenuation matrix. The parameter set includes the first parameter group and the second parameter group.

[0027] The first attenuation matrix and the second attenuation matrix are each a matrix consisting of a plurality of elements corresponding to a plurality of two-dimensional coordinates. For example, each element is relative attenuation (amount of relative attenuation). Each element may be absolute attenuation (amount of absolute attenuation). The first attenuation average and the second attenuation average are each a two-dimensional average of relative attenuation (or absolute attenuation). The first attenuation average and the second attenuation average may each be a two-dimensional average of attenuation coefficients. Meanwhile, the first attenuation variance and the second attenuation variance are each a two-dimensional variance of relative attenuation (or absolute attenuation). Specifically, the variance is a standard deviation, a variance, or the like. The first attenuation variance and the second attenuation variance may each be a two-dimensional variance of attenuation coefficients.

[0028] In the embodiment, the two-dimensional region corresponds to a plurality of receive beams aligned in the electronic scanning direction. The first calculation unit calculates a first attenuation coefficient based on a specific attenuation column selected from the first attenuation matrix, and calculates a first attenuation average and a first attenuation variation based on the plurality of attenuation columns in the first attenuation matrix. The first calculation unit also calculates a second attenuation coefficient based on a specific attenuation column selected from the second attenuation matrix, and calculates a second attenuation average and a second attenuation variation based on the plurality of attenuation columns in the second attenuation matrix.

[0029] In an embodiment, the parameter set further includes one or more parameters obtained from the subject by an examination other than an ultrasound examination, such as the subject's height, weight, BMI, blood test values, etc. The parameter set may also include results of tomographic image analysis.

[0030] An ultrasound diagnostic device according to an embodiment includes a generator and a display. The generator generates an ultrasound image based on reception information other than the plurality of reception information. The display displays the ultrasound image, at least one of a plurality of attenuation coefficients, and an estimated value of fat percentage.

[0031] A fat percentage estimation method according to an embodiment includes a first step and a second step. In the first step, a plurality of attenuation coefficients are calculated based on a plurality of pieces of received information having a plurality of different frequency characteristics acquired from the liver of a subject. In the second step, an estimated value of the fat percentage is calculated based on a parameter set including the plurality of attenuation coefficients.

[0032] The fat percentage estimation method can be realized as a program function. In this case, the program is installed in an information processing device via a network or a portable memory. The information processing device may be an ultrasound diagnostic device, a computer, or the like. The information processing device has a non-transitory storage medium that stores the program.

[0033] (2) Details of the embodiment 1 shows an ultrasound diagnostic device 10 according to an embodiment. The ultrasound diagnostic device 10 is a medical device installed in a medical institution such as a hospital and used for ultrasound examination of a subject (living body). The ultrasound diagnostic device 10 according to the embodiment has an operation mode for estimating the fat percentage of the liver (hereinafter referred to as a fat percentage estimation mode) in addition to a B mode for displaying tomographic images.

[0034] In Fig. 1, the ultrasonic probe 12 is a portable device that transmits and receives ultrasonic waves to acquire received information. The ultrasonic probe 12 has a transducer array consisting of a plurality of transducers arranged in a linear or curved line. An ultrasonic beam is formed by the transducer array. The ultrasonic beam is electronically scanned. Known electronic scanning methods include an electronic linear scanning method and an electronic sector scanning method. A two-dimensional transducer array may be provided within the ultrasonic probe 12.

[0035] The transmission circuit 13 is an electronic circuit that functions as a transmission beam former. During transmission, the transmission circuit 13 supplies multiple transmission signals in parallel to the transducer array, causing the transducer array to form a transmission beam.

[0036] The receiving circuit 14 is an electronic circuit that functions as a receiving beamformer. During reception, when reflected waves from within the living body are received by the transducer array, multiple received signals are output in parallel from the transducer array. The receiving circuit 14 applies phasing addition to the multiple received signals, thereby generating receive beam data. The receiving circuit 14 includes multiple amplifiers, multiple A / D converters, a phasing addition circuit, etc.

[0037] When B-mode is performed, an ultrasonic beam is electronically scanned over the entire electronic scanning range. This results in received frame data. The received frame data is made up of multiple received beam data aligned in the electronic scanning direction. Each received beam data is made up of multiple echo data aligned in the depth direction. The received frame data is B-mode received information. As the electronic scanning of the ultrasonic beam is repeated, multiple received frame data are sequentially output from the receiving circuit 14.

[0038] When the fat percentage estimation mode is executed, first and second transmission and reception, which are different from the B-mode transmission and reception, are sequentially executed. Specifically, the first and second transmission and reception are sequentially executed for a two-dimensional region of interest set in the liver, which is the examination target.

[0039] In the first transmission / reception, a first ultrasonic wave having a first center frequency is transmitted into the subject, and first reflected waves from the subject are received to acquire first reception information. The first reception information is made up of a plurality of first reception beam data (first reception beam data set) corresponding to a plurality of first reception beams passing through the region of interest. More specifically, the first reception beam data set is made up of a plurality of echo data corresponding to a plurality of observation points (sampling points) spread two-dimensionally within the region of interest.

[0040] In the second transmission / reception, second ultrasonic waves having a second center frequency different from the first center frequency are transmitted into the subject, and second reflected waves from the subject are received to acquire second reception information. The second reception information consists of multiple second reception beam data (second reception beam data set) corresponding to multiple second reception beams passing through the region of interest. More specifically, the second reception beam data set consists of multiple echo data corresponding to multiple observation points (sampling points) spread two-dimensionally within the region of interest. The first center frequency is, for example, 1.5 MHz, 2 MHz, or 2.5 MHz, and the second center frequency is, for example, 3 MHz, 4 MHz, or 5 MHz.

[0041] The data processing unit 16 is an electronic circuit that applies necessary processing to each receive beam data. The data processing unit 16 includes an envelope detection circuit, a smoothing circuit, a logarithmic compression circuit, etc. When B-mode is being executed, multiple receive frame data are sequentially sent from the data processing unit 16 to the image forming unit 18. When fat percentage estimation mode is being executed, first receive beam data set and second receive beam data set are sequentially sent from the data processing unit 16 to the information processing unit 24.

[0042] The image forming unit 18 sequentially generates a plurality of tomographic image data based on a plurality of received frame data, and includes a digital scan converter (DSC) having a coordinate conversion function, a pixel interpolation function, and the like.

[0043] A plurality of tomographic image data are sent to the display 22 via the display processing unit 20. The display 22 displays a plurality of tomographic images as moving images. When a freeze operation is performed, a tomographic image corresponding to a specific time phase is displayed as a still image. The display 22 is configured with an organic EL display or the like. When the fat percentage estimation mode is executed, the display 22 displays not only the tomographic image as a still image, but also the attenuation coefficient, the estimated value of the fat percentage (the estimated PDFF value), and the like.

[0044] The information processing unit 24 is configured by a CPU that executes a program. The information processing unit 24 has a function of controlling the operation of each element that constitutes the ultrasound diagnostic apparatus 10. In FIG. 1, multiple main functions performed by the information processing unit 24 are represented by multiple blocks. The information processing unit 24 has a transmission / reception controller 26 and a calculation module 28. The calculation module 28 has a parameter calculation unit (first calculation unit) 30 and an estimated value calculation unit (second calculation unit) 32.

[0045] The transmission / reception controller 26 controls the transmission and reception of ultrasound, specifically, the operation of the transmission circuit 13 and the reception circuit 14. As will be described later, the parameter calculation unit 30 has a function of calculating a first group of parameters based on the first reception information and a function of calculating a second group of parameters based on the second reception information. The estimate value calculation unit 32 has a function of calculating an estimate of fat percentage based on a parameter set including the first group of parameters and the second group of parameters.

[0046] The operation panel 34 is an input device, and has a plurality of switches, a plurality of buttons, a trackball, etc. Through the operation panel 34, the examiner selects an operation mode and sets a region of interest.

[0047] The memory 36 is configured, for example, by a semiconductor memory. The memory 36 stores information and programs required for the operation of the ultrasound diagnostic apparatus 10. The stored information includes information for defining the first reference information and the second reference information used in the fat percentage estimation mode. One or more pieces of test value data are input to the information processing unit 24 from an external device. The test value data includes, for example, BMI data, blood test data, etc. Each component shown in FIG. 1 is configured by an electronic circuit, a processor, a device, etc.

[0048] Fig. 2 shows an example of the configuration of the parameter calculation unit 30 and the estimated value calculation unit 32 shown in Fig. 1. They function in the fat percentage estimation mode.

[0049] The parameter calculation unit 30 has a first matrix calculator 40, a second matrix calculator 42, a first information generator 43, a second information generator 44, a first coefficient calculator 46, a first average calculator 48, a first variation calculator 50, a second coefficient calculator 52, a second average calculator 54, and a second variation calculator 56.

[0050] The first matrix calculator 40 calculates a first attenuation matrix based on the first reception information. The first attenuation matrix may also be referred to as a first attenuation amount matrix. Specifically, the first matrix calculator 40 calculates the first attenuation matrix as a two-dimensional matrix based on a two-dimensional first reception intensity matrix acquired from within the region of interest and a one-dimensional first reference intensity sequence output from the first information generator 43.

[0051] The second matrix calculator 42 calculates a second attenuation matrix based on the second reception information. The second attenuation matrix may also be referred to as a second attenuation amount matrix. Specifically, the second matrix calculator 42 calculates the second attenuation matrix as a two-dimensional matrix based on a two-dimensional second reception intensity matrix acquired from within the region of interest and a one-dimensional second reference intensity sequence output from the second information generator 44.

[0052] The first information generator 43 generates a first reference intensity sequence according to a first reference intensity function. The second information generator 44 generates a second reference intensity sequence according to a second reference intensity function. The calculated or measured first and second reference intensity sequences may be pre-stored in a memory (see FIG. 1).

[0053] The first coefficient calculator 46 calculates a first attenuation coefficient (first attenuation rate) based on a specific first attenuation column selected from the first attenuation matrix. In an embodiment, the specific first attenuation column corresponds to a receive beam passing through the center of the region of interest.

[0054] The first average calculator 48 calculates a first attenuation average based on a plurality of first attenuation columns constituting the first attenuation matrix. The first attenuation average may also be referred to as a first attenuation amount average. The first attenuation average may be calculated based on a portion of the first attenuation matrix.

[0055] The first variation calculator 50 calculates the first attenuation variation based on a plurality of first attenuation columns constituting the first attenuation matrix. The first attenuation variation may also be referred to as a first attenuation amount variation. The first attenuation variation may be calculated based on a portion of the first attenuation matrix. Specifically, the first attenuation variation is a standard deviation (SD). Variance or the like may be calculated as the first attenuation variation.

[0056] The second coefficient calculator 52 calculates a second attenuation coefficient (second attenuation rate) based on a specific second attenuation sequence selected from the second attenuation matrix. In an embodiment, the specific second attenuation sequence corresponds to a receive beam passing through the center of the region of interest.

[0057] The second average calculator 54 calculates a second attenuation average based on a plurality of second attenuation columns constituting the second attenuation matrix. The second attenuation average may also be referred to as a second attenuation amount average. The second attenuation average may be calculated based on a portion of the second attenuation matrix.

[0058] The second variation calculator 56 calculates the second attenuation variation based on the plurality of second attenuation columns that make up the second attenuation matrix. The second attenuation variation may also be referred to as the second attenuation amount variation. The second attenuation variation may be calculated based on a portion of the second attenuation matrix. Specifically, the second attenuation variation is the standard deviation (SD). Variance or the like may be calculated as the second attenuation variation.

[0059] The first attenuation coefficient, the first attenuation average, and the first attenuation variance constitute a first parameter group. The second attenuation coefficient, the second attenuation average, and the second attenuation variance constitute a second parameter group. The parameter set includes the first parameter group and the second parameter group. In an embodiment, the parameter set further includes an examination value obtained from the subject by an examination other than an ultrasound examination, specifically, a BMI (Body Mass Index). The parameter set may include an examination value instead of the BMI, or may include other examination values in addition to the BMI.

[0060] The estimated value calculation unit 32 has a mathematical model 58. The mathematical model 58 is made up of one or more mathematical formulas that calculate an estimated value of the fat percentage based on a parameter set. A machine-learned model may be used instead of the mathematical model 58. The machine-learned model is configured using a neural network or the like, and receives an input of a parameter set and outputs an estimated value of the fat percentage.

[0061] The estimate value calculation unit 32 according to the embodiment includes an error determiner 60. The error determiner 60 determines an error based on the first reception information and / or the second reception information. For example, if a blood vessel, an artifact, or the like is included in the region of interest, the error determiner 60 determines an error. An error may be determined based on one or both of the first attenuation variance and the second attenuation variance. If an error is determined, error information is provided to the user. Thereafter, the position of the region of interest is changed by the user, and the above-described first transmission / reception and second transmission / reception are performed again.

[0062] 3 shows a region of interest 64 set on a beam scan plane 62. In FIG. 3, the x direction is the depth direction, and the θ direction is the electronic scan direction. The beam scan plane 62 is formed by electronically scanning an ultrasonic beam 65.

[0063] The region of interest 64 is a two-dimensional region. Specifically, the region of interest 64 ranges from a depth x1 to a depth x2 in the depth direction. The region of interest 64 corresponds to an arrangement of N receive beams in the electronic scanning direction. N is, for example, 9, 11, 13, etc. In the embodiment, the depth x1 and the depth x2 are fixed values. The depths x1 and x2 may be specified by the user. The orientation θ1 is an orientation corresponding to the center of the region of interest 64. The user may change the orientation θ1. For example, the region of interest 64 is set so that large blood vessels do not fall within the region of interest 64. The region of interest 64 is actually specified on a tomographic image.

[0064] FIG. 4 shows N receive beams 66 passing through a region of interest 64. Each receive beam 66 includes M receive intensities (amplitude values) 68 arranged in the depth direction. The first receive intensity matrix obtained by the first transmission and reception consists of M×N receive intensities arranged in the depth direction and the electronic scanning direction. Similarly, the second receive intensity matrix obtained by the second transmission and reception consists of M×N receive intensities arranged in the depth direction and the electronic scanning direction. Reference numeral 70 indicates a receive intensity sequence located at the center of the region of interest. In the depth direction, the observation point pitch is indicated by Δx.

[0065] Next, a fat percentage estimation method according to an embodiment will be described. First, the calculation of the attenuation matrix, attenuation coefficient, attenuation average, and attenuation variance will be described, and then the calculation of an estimated value approximating the PDFF will be described. The substance of each attenuation constituting the attenuation matrix is the attenuation amount.

[0066] Theoretically, based on the two-dimensional received intensity matrix P(x), the two-dimensional attenuation matrix A a is defined by the following equation (1).

number

[0067] Here, f is the frequency of the ultrasound (typically the center frequency), and x is the depth (coordinate in the depth direction). The received intensity matrix P(x) consists of multiple received intensities obtained from multiple observation points that make up a two-dimensional region of interest.

[0068] In the above equation (1), the damping matrix A a Each attenuation constituting the matrix P(x) corresponds to the absolute attenuation. The absolute attenuation varies greatly depending on the operating conditions of the ultrasound diagnostic device. For this reason, the received signal intensity matrix P(x) is usually converted into a reference signal intensity matrix P(x) according to the following equation (2): ref By comparing with (x), the damping column A r It should be noted that for multiple received intensity sequences aligned in the electronic scanning direction, a common reference intensity sequence P ref (x) applies.

number

[0069] Damping matrix A r is composed of multiple attenuations arranged in the depth direction and the electronic scanning direction. Each attenuation is a relative attenuation. For each attenuation, a reference intensity sequence P ref By adding the corresponding known attenuation to (x), the final attenuation (absolute attenuation) is found.

[0070] By the way, the reference intensity column P ref (x) is defined, for example, by the following equation (3): γ is a coefficient.

number

[0071] Reference intensity sequence P by other functions ref (x) may be defined. The reference altitude sequence may be given as a numeric sequence.

[0072] Damping coefficient sequence α ris calculated according to the following equation (4).

number

[0073] Here, i indicates the depth number. rc (x i ) represents the central damping column in the damping matrix. Δx is defined by the following equation (5).

number

[0074] Damping coefficient sequence α r Each attenuation that makes up the attenuation is a relative attenuation coefficient. The attenuation coefficient (absolute attenuation coefficient) α at each depth is calculated according to the following equation (6).

number

[0075] where k2 is the reference intensity sequence P ref are known attenuation coefficients corresponding to (x). k1 and k3 are coefficients for adjustment, respectively.

[0076] On the other hand, the damping average μ is calculated according to the following equation (7).

number

[0077] Here, M represents the number of observation points in the depth direction in the region of interest. N represents the number of observation points in the electronic scanning direction in the region of interest. i represents the coordinate in the depth direction, and j represents the coordinate in the electronic scanning direction. A r i,j denotes the attenuation corresponding to the observation point (i, j). The attenuation coefficient mean may be calculated as the attenuation mean μ.

[0078] The attenuation standard deviation (attenuation SD) σ is calculated as the attenuation variation according to the following equation (8).

number

[0079] Instead of the attenuation SDσ, the variance may be calculated, or another index representing the variation in attenuation may be calculated.

[0080] In this embodiment, prior to the calculation of the estimated value E of the fat percentage, an intermediate value Y is calculated according to the following equation (9).

number

[0081] Here, a, b, c, d, e, f, g, and h are coefficients that are determined in advance by multiple regression analysis, which will be described later. Among these coefficients, h corresponds to an offset. α1 is a first attenuation coefficient determined from the first received information, μ1 is a first attenuation average determined from the first received information, and σ1 is a first attenuation standard deviation determined from the first received information. α2 is a second attenuation coefficient determined from the second received information, μ2 is a second attenuation average determined from the second received information, and σ2 is a second attenuation standard deviation determined from the second received information. BMI is the subject's BMI value.

[0082] An estimated value E is calculated from the intermediate value Y according to the following equation (10).

number

[0083] Here, B, C, and A are coefficients.

[0084] There is a nonlinear relationship (specifically, a logarithmic relationship) between the intermediate value Y and the PDFF, which is expressed by the following equation (11).

number

[0085] In this embodiment, the intermediate value Y is calculated based on the multiple regression analysis to accommodate the nonlinear relationship. The estimated value E may be calculated directly from a combination of α1, μ1, σ1, α2, μ2, σ2, and BMI without first calculating the intermediate value Y. In this case, a machine-learned estimation model may be used.

[0086] 5 shows the process of calculating the estimated value. The substance of the first reception information is the first reception intensity matrix P1(x), and the substance of the second reception information is the second reception intensity matrix P2(x). The substance of the first reference information is the first reference intensity matrix P ref1 (x), and the substance of the second reference information is the second reference intensity sequence P ref2 (x).

[0087] The first received intensity matrix P1(x) and the first reference intensity matrix P ref1 Based on (x), the first damping matrix A r1 The second received intensity matrix P2(x) and the second reference intensity matrix P ref2 Based on (x), the second damping matrix A r2 For the plurality of first reception intensity sequences that make up the first reception intensity matrix P1(x), a first reference intensity sequence P ref1 Similarly, a second reference intensity sequence P ref2 (x) applies.

[0088] First damping matrix A r1 Attenuation column A in the center rc1 the first reference intensity column P ref1 (x) to calculate the first damping coefficient α1. r1 The first attenuation coefficient α1, the first attenuation average μ1, and the first standard deviation σ1 are calculated based on the above. A first parameter group is configured by the first attenuation coefficient α1, the first attenuation average μ1, and the first standard deviation σ1.

[0089] Second damping matrix A r2 Attenuation column A in the center rc2 the second reference intensity column P ref2(x) to calculate the second damping coefficient α2. r2 The second attenuation average μ2 and the second attenuation SDσ2 are calculated based on the above. The second parameter group is composed of the second attenuation coefficient α2, the second attenuation average μ2, and the second attenuation SDσ2. The parameter set is composed of the first parameter group, the second parameter group, and the BMI.

[0090] An estimated value E of the fat percentage is calculated based on the parameter set. As will be described later, this estimated value E is based on PDFFs obtained by actual measurements of many subjects, and therefore is a value that is close to the PDFF.

[0091] 6 shows a method for generating a mathematical model. By conducting MRI examinations, ultrasound examinations, and other examinations on a large number of subjects, a PDFF group 74, a parameter group 76, and a BMI group 78 are obtained (see reference numeral 72). Based on the above equation (11), the PDFF group 74 is converted into an intermediate value group 80. Note that the coefficients A, B, and C in equation (11) are determined in advance. The coefficients a to h and the coefficients A, B, and C may be determined simultaneously by an optimal solution search method or the like.

[0092] A coefficient set (a to h) 84 is determined by multiple regression analysis 82 based on the intermediate value group 80, the parameter group 76, and the BMI group 78. This defines the above equation (9) as a numerical model 86. Note that an estimation model may also be generated by machine learning using the PDFF group 74, the parameter group 76, and the BMI group 78.

[0093] An example display is shown in Figure 7. A cross-sectional image 90, which is an ultrasound image, is displayed on a screen 88 of a display device. The cross-sectional image 90 shows a cross section of the liver of a subject. The cross-sectional image 90 includes a first marker 94 and a second marker 96 which indicate both ends of a region of interest in the depth direction. A line 92 indicates the center line of the region of interest.

[0094] As a result of executing the fat percentage estimation mode, the attenuation coefficient 98 is displayed as a numerical value on the screen 88, and the estimated value 100 is also displayed as a numerical value. The attenuation coefficient 98 is the first attenuation coefficient or the second attenuation coefficient. The average value of these may also be displayed as the attenuation coefficient 98. If an error is determined, error information is displayed on the screen 88.

[0095] Next, an example of the operation of the ultrasound diagnostic apparatus shown in Figure 1 will be described with reference to Figure 8. In S10, B-mode transmission and reception is performed. As a result, a tomographic image showing the liver is displayed on the display. In S12, a region of interest is set on the tomographic image. Then, execution of the fat percentage estimation mode is started.

[0096] In S14, a first transmission / reception is performed. Specifically, a first ultrasonic wave having a first center frequency is transmitted from the ultrasound probe to the region of interest. Then, a first reflected wave from the region of interest is received by the ultrasound probe. This results in first reception information being acquired. In S16, a first parameter group including a first attenuation coefficient is calculated based on the first reception information.

[0097] In S18, a second transmission and reception is performed. Specifically, a second ultrasonic wave having a second center frequency is transmitted from the ultrasound probe to the region of interest. Then, a second reflected wave from the region of interest is received by the ultrasound probe. This results in second reception information being acquired. In S20, a second parameter group including a second attenuation coefficient is calculated based on the second reception information. In practice, S18 is performed immediately after the end of S14, and S20 is performed immediately after the end of S16.

[0098] In S22, an estimate of the fat percentage is calculated based on a parameter set including the first parameter group and the second parameter group. In S24, the estimate is displayed together with a damping factor. At this time, the entire parameter set may be displayed.

[0099] 9 shows an example of the operation of an ultrasound diagnostic apparatus according to a modified example. B-mode transmission and reception is performed in S10, and a region of interest is set in S12. Transmission and reception for fat percentage estimation is performed in S30. For example, ultrasound waves including a first frequency component and a second frequency component are transmitted to the region of interest, and reflected waves from the region of interest are received. As a result, reception information is acquired.

[0100] In S32, a first frequency component included in the received information is extracted by a first receiving filter, and a first set of parameters is calculated based on the first frequency component. In S34, a second frequency component included in the received information is extracted by a second receiving filter, and a second set of parameters is calculated based on the second frequency component. The first receiving filter has a first frequency characteristic for extracting the first frequency component, and the second receiving filter has a second frequency characteristic for extracting the second frequency component. In S36, an estimated value of fat percentage is calculated based on a parameter set including the first set of parameters and the second set of parameters. In S38, the estimated value is displayed.

[0101] According to this modification, an estimated value can be obtained by one transmission and reception. When priority is given to estimation accuracy, it is desirable to adopt the operation shown in FIG.

[0102] According to the above embodiment, the ultrasound diagnostic device can calculate an estimated value of fat percentage based on the first and second attenuation coefficients acquired under different transmission and reception conditions. In particular, an estimated value approximating the PDFF can be calculated. Since the parameter set includes multiple parameters other than the first and second attenuation coefficients, the accuracy of fat percentage estimation can be improved. Other parameters calculated from received information may be used instead of or in addition to the attenuation mean and attenuation variance. BMI may be excluded from the parameter set, or a test value instead of BMI may be used. [Explanation of symbols]

[0103] 10 ultrasonic diagnostic device, 12 ultrasonic probe, 24 information processing unit, 28 calculation module, 30 parameter calculation unit (first calculation unit), 32 estimated value calculation unit (second calculation unit).

Claims

1. a first calculation unit that calculates a plurality of attenuation coefficients based on a plurality of pieces of reception information having a plurality of different frequency characteristics acquired from the liver of the subject; a second calculation unit that calculates an estimated value of a fat percentage based on a parameter set including the plurality of attenuation coefficients; 1. An ultrasonic diagnostic apparatus comprising:

2. 2. The ultrasonic diagnostic apparatus according to claim 1, the second calculation unit has a model created so that the estimated value approximates MRI-PDFF; the parameter set is provided to the model, thereby computing the estimate; An ultrasonic diagnostic device characterized by:

3. 2. The ultrasonic diagnostic apparatus according to claim 1, the plurality of pieces of reception information include first reception information having a first frequency characteristic and second reception information having a second frequency characteristic; the plurality of attenuation coefficients include a first attenuation coefficient calculated based on the first reception information and a second attenuation coefficient calculated based on the second reception information; An ultrasonic diagnostic device characterized by:

4. 4. The ultrasonic diagnostic apparatus according to claim 3, an ultrasound probe that acquires the first reception information by transmitting a first ultrasound wave having a first center frequency into the subject, and acquires the second reception information by transmitting a second ultrasound wave having a second center frequency different from the first center frequency into the subject; An ultrasonic diagnostic device characterized by:

5. 4. The ultrasonic diagnostic apparatus according to claim 3, a generator that generates first reference information that is compared with the first received information and second reference information that is compared with the second received information; The first calculation unit calculating the first attenuation coefficient based on the first received information and the first reference information; calculating the second attenuation coefficient based on the second received information and the second reference information; An ultrasonic diagnostic device characterized by:

6. 6. The ultrasonic diagnostic apparatus according to claim 5, the first received information and the second received information are each information acquired from a two-dimensional region within the subject, The first calculation unit calculating a first attenuation matrix based on the first received information and the first reference information; calculating a first parameter group including the first damping coefficient, a first damping average, and a first damping variation based on the first damping matrix; calculating a second attenuation matrix based on the second received information and the second reference information; calculating a second group of parameters including the second damping coefficient, a second damping average, and a second damping variation based on the second damping matrix; the parameter set includes the first parameter group and the second parameter group; An ultrasonic diagnostic device characterized by:

7. 7. The ultrasonic diagnostic apparatus according to claim 6, the two-dimensional area corresponds to a plurality of receive beams aligned in an electronic scanning direction; The first calculation unit calculating the first damping coefficient based on a particular damping sequence selected from the first damping matrix; calculating the first attenuation average and the first attenuation variation based on a plurality of attenuation columns in the first attenuation matrix; calculating the second attenuation coefficient based on a particular attenuation column selected from the second attenuation matrix; calculating the second attenuation average and the second attenuation variation based on a plurality of attenuation columns in the second attenuation matrix; An ultrasonic diagnostic device characterized by:

8. 7. The ultrasonic diagnostic apparatus according to claim 6, The parameter set further includes one or more parameters obtained from the subject by an examination other than an ultrasound examination. An ultrasonic diagnostic device characterized by:

9. 2. The ultrasonic diagnostic apparatus according to claim 1, a generator for generating an ultrasonic image based on reception information other than the plurality of reception information; a display that displays the ultrasound image, at least one of the plurality of attenuation coefficients, and the estimated fat percentage; 1. An ultrasonic diagnostic apparatus comprising:

10. calculating a plurality of attenuation coefficients based on a plurality of pieces of received information having a plurality of different frequency characteristics acquired from the liver of the subject; calculating an estimate of percent fat based on a parameter set including the plurality of attenuation coefficients; A fat percentage estimation method comprising:

11. A program for executing a fat percentage estimation method in an information processing device, a function of calculating a plurality of attenuation coefficients based on a plurality of pieces of reception information having a plurality of different frequency characteristics acquired from the liver of the subject; a function of calculating an estimated fat percentage based on a parameter set including the plurality of attenuation coefficients; A program comprising:

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