Ultrasound diagnostic device and fat percentage estimation method

Abstract

In an ultrasound diagnostic device, a fat rate is estimated or a value approximate to MRI-PDFF is calculated. A two-dimensional region of interest is set in the liver of a subject (S12). On the basis of first reception information obtained from a two-dimensional region of interest, a first parameter group including a first attenuation coefficient is calculated (S16). On the basis of second reception information obtained from the two-dimensional region of interest, a second parameter group including a second attenuation coefficient is calculated (S20). A parameter set including the first parameter set and the second parameter set is given to the mathematical model, and an estimated value of the fat rate is calculated (S22).

Description

Technical Field

[0001] The present invention relates to an ultrasonic diagnostic apparatus and a fat percentage estimation method, and particularly to a technique for estimating the fat percentage of the liver. Background Art

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

[0003] An ultrasonic diagnostic apparatus has a function of measuring the attenuation coefficient (attenuation rate) in the liver. In such an ultrasonic diagnostic apparatus, ultrasonic waves are transmitted to the liver and reflected waves from the liver are received. Then, based on the obtained reception information, the attenuation coefficient is calculated. The attenuation coefficient is a parameter that varies according to the characteristics of liver tissue. A certain correlation has been confirmed between the attenuation coefficient and the fat percentage, but the attenuation coefficient does not directly represent the fat percentage.

[0004] The MRI-PDFF (Proton density fat fraction) of the liver measured by an MRI (Magnetic resonance imaging) apparatus (hereinafter simply referred to as PDFF) represents the ratio of the amount of protons contained in water molecules to the amount of protons contained in fat molecules. That is, PDFF directly represents the fat percentage of the liver. However, an MRI apparatus is an expensive and large device. There is a need to develop a technique that can more easily measure the fat percentage of the liver.

[0005] Patent Document 1: International Publication No. 2017 / 0688892

[0006] Patent Document 2: Japanese Unexamined Patent Application Publication No. 2020-354

[0007] Non-Patent Document 1: Hidekatsu Kuroda et al., Multivariable Quantitative US Parameters for Assessing Hepatic Steatosis, Radiology, Volume 309, Number 1, 2023.

[0008] There is a desire to estimate the fat percentage or calculate a value approximating PDFF using an ultrasonic diagnostic apparatus.

[0009] In Patent Document 1, an ultrasonic diagnostic apparatus for measuring an attenuation coefficient is disclosed. In this ultrasonic diagnostic apparatus, an attenuation coefficient is calculated based on a first reception signal obtained by forming a first ultrasonic beam and a second reception signal obtained by forming a second ultrasonic beam. However, a technique for estimating a fat percentage is not disclosed in Patent Document 1, especially a technique for estimating a fat percentage based on a plurality of attenuation coefficients.

[0010] In Patent Document 2, an ultrasonic diagnostic apparatus for measuring an attenuation coefficient is also disclosed. However, a technique for estimating a fat percentage is not disclosed in Patent Document 2 either.

[0011] In Non-Patent Document 1, the relationship between the attenuation coefficient measured by an ultrasonic diagnostic apparatus and the PDFF measured by an MRI apparatus is described. However, a technique for estimating a fat percentage based on a plurality of attenuation coefficients is not disclosed in Non-Patent Document 1 either. Summary of the Invention

[0012] An object of the present invention is to estimate a fat percentage or calculate a value approximating PDFF in an ultrasonic diagnostic apparatus.

[0013] The ultrasonic diagnostic apparatus according to the present invention is characterized in that it includes: a first calculation unit that calculates a plurality of attenuation coefficients based on a plurality of reception information having different frequency characteristics obtained from the liver in a subject; and a second calculation unit that calculates an estimated value of the fat percentage based on a parameter set including the plurality of attenuation coefficients.

[0014] The fat percentage estimation method according to the present invention is characterized by including the following steps: calculating a plurality of attenuation coefficients based on a plurality of reception information having different frequency characteristics obtained from the liver in a subject; and calculating an estimated value of the fat percentage based on a parameter set including the plurality of attenuation coefficients.

[0015] Advantages of the Invention

[0016] According to the present invention, in an ultrasonic diagnostic apparatus, it is possible to estimate a fat percentage or calculate a value approximating PDFF. Brief Description of the Drawings

[0017] Figure 1 It is a block diagram showing a structural example of the ultrasonic diagnostic apparatus according to the embodiment.

[0018] Figure 2 It shows Figure 1 a block diagram showing a structural example of the operation module shown.

[0019] Figure 3 It is a diagram showing a region of interest.

[0020] Figure 4It is a diagram showing the reception intensity matrix.

[0021] Figure 5 It is a diagram showing the method for estimating the fat percentage.

[0022] Figure 6 It is a diagram showing the method for creating a mathematical model.

[0023] Figure 7 It is a diagram showing a display example.

[0024] Figure 8 It is a diagram showing Figure 1 a flowchart of the operation of the ultrasonic diagnostic apparatus shown.

[0025] Figure 9 It is a flowchart of the operation of the ultrasonic diagnostic apparatus according to the modified example.

[0026] Symbol Explanation

[0027] 10 - Ultrasonic diagnostic apparatus, 12 - Ultrasonic probe, 24 - Information processing unit, 28 - Arithmetic module, 30 - Parameter arithmetic unit (first arithmetic unit), 32 - Estimated value arithmetic unit (second arithmetic unit). Detailed Embodiment

[0028] Hereinafter, the embodiments will be described with reference to the drawings.

[0029] (1) Outline of the Embodiment

[0030] The ultrasonic diagnostic apparatus according to the embodiment includes a first arithmetic unit and a second arithmetic unit. The first arithmetic unit calculates a plurality of attenuation coefficients based on a plurality of reception information having mutually different frequency characteristics obtained from the liver within the subject. The second arithmetic unit calculates an estimated value of the fat percentage based on a parameter set including the plurality of attenuation coefficients.

[0031] The acoustic characteristics of a living tissue depend on the frequency of the ultrasonic wave propagating through the living tissue. The plurality of reception information are all information reflecting the characteristics of the liver tissue, but have mutually different frequency characteristics. Based on such a plurality of reception information, a plurality of attenuation coefficients are calculated. By calculating the estimated value of the fat percentage based on the plurality of attenuation coefficients, the reliability of the estimated value can be improved.

[0032] In an embodiment, the parameter set includes a plurality of parameters other than a plurality of attenuation coefficients and a plurality of parameters calculated based on 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 the parameters obtained by ultrasonic diagnosis. In order to obtain the plurality of received signals, a plurality of transmission signals having a plurality of different center frequencies from each other may be used, or a plurality of reception filters having a plurality of different frequency characteristics from each other may be used. The frequency characteristic refers to a frequency band.

[0033] In an embodiment, the second calculation unit has a model created in such a way that the estimated value of the fat percentage approximates the MRI-PDFF. By assigning the parameter set to the model, the estimated value of the fat percentage is calculated. 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.

[0034] In an embodiment, the plurality of received information includes first received information having a first frequency characteristic and second received information having a second frequency characteristic. The plurality of attenuation coefficients includes a first attenuation coefficient calculated based on the first received information and a second attenuation coefficient calculated based on the second received information. The plurality of received information may be composed of three or more received information, and the plurality of attenuation coefficients may also be composed of three or more attenuation coefficients.

[0035] The ultrasonic diagnostic apparatus according to the embodiment includes an ultrasonic probe. The ultrasonic probe obtains the first received information by transmitting a first ultrasonic wave having a first center frequency into a subject. Further, the ultrasonic probe obtains the second received information by transmitting a second ultrasonic wave having a second center frequency different from the first center frequency into the subject.

[0036] In an embodiment, transmission and reception for forming a tomographic image, transmission and reception for obtaining the first received information, and transmission and reception for obtaining the second received information are performed. All or part of these transmissions and receptions may be combined.

[0037] The ultrasonic diagnostic apparatus according to the embodiment includes a generator. The generator generates first reference information for comparison with the first received information and second reference information for comparison with the second received information. The first calculation unit calculates the first attenuation coefficient based on the first received information and the first reference information. Further, the first calculation unit calculates the second attenuation coefficient based on the second received information and the second reference information.

[0038] In an embodiment, the first reference information and the second reference information are defined by a prescribed calculation formula, respectively. In this case, the information generator is constituted by an arithmetic unit. The first reference information and the second reference information may be respectively constituted as prescribed numerical sequences. In this case, the above-mentioned generator may be constituted by a memory.

[0039] In an embodiment, the first received information and the second received information are information respectively obtained from a two-dimensional region within the subject. The first arithmetic unit calculates a first attenuation matrix based on the first received information and the first reference information, and calculates a first parameter set including a first attenuation coefficient, a first attenuation average, and a first attenuation deviation based on the first attenuation matrix. Further, the first arithmetic unit calculates a second attenuation matrix based on the second received information and the second reference information, and calculates a second parameter set including a second attenuation coefficient, a second attenuation average, and a second attenuation deviation based on the second attenuation matrix. The parameter set includes the first parameter set and the second parameter set.

[0040] The first attenuation matrix and the second attenuation matrix are matrices respectively constituted by a plurality of elements corresponding to a plurality of two-dimensional coordinates. For example, each element is relative attenuation (relative attenuation amount). Each element may be absolute attenuation (absolute attenuation amount). The first attenuation average and the second attenuation average are respectively two-dimensional averages of relative attenuation (or absolute attenuation). The first attenuation average and the second attenuation average may be respectively two-dimensional averages of attenuation coefficients. On the other hand, the first attenuation deviation and the second attenuation deviation are respectively two-dimensional deviations of relative attenuation (or absolute attenuation). Specifically, the deviation is a standard deviation, a variance, or the like. The first attenuation deviation and the second attenuation deviation may be respectively two-dimensional deviations of attenuation coefficients.

[0041] In an embodiment, the two-dimensional region corresponds to a plurality of reception beams arranged in the electronic scanning direction. The first arithmetic unit calculates the first attenuation coefficient based on a specific attenuation column selected from the first attenuation matrix, and calculates the first attenuation average and the first attenuation deviation based on a plurality of attenuation columns in the first attenuation matrix. Further, the first arithmetic unit calculates the second attenuation coefficient based on a specific attenuation column selected from the second attenuation matrix, and calculates the second attenuation average and the second attenuation deviation based on a plurality of attenuation columns in the second attenuation matrix.

[0042] In an embodiment, the parameter set further includes one or more parameters obtained from the subject by an examination other than ultrasonic examination. Examples of such one or more parameters include the height, weight, BMI, blood test values, etc. of the subject. The parameter set may include the result of tomographic image analysis.

[0043] The ultrasonic diagnostic apparatus according to the embodiment includes a former and a display. The former forms an ultrasonic image based on received information different from the plurality of received information. The display displays the ultrasonic image, at least one of the plurality of attenuation coefficients, and an estimated value of the fat percentage.

[0044] The fat percentage estimation method according to the embodiment includes a first step and a second step. In the first step, based on a plurality of received information having a plurality of different frequency characteristics obtained from the liver in the subject, a plurality of attenuation coefficients are calculated. In the second step, based on a parameter set including the plurality of attenuation coefficients, an estimated value of the fat percentage is calculated.

[0045] The above fat percentage estimation method can be implemented as a function of a program. In this case, the program is installed in the information processing device via a network or a portable memory. The information processing device is an ultrasonic diagnostic device, a computer, or the like. The information processing device has a non-temporary storage medium storing the above program.

[0046] (2) Details of the embodiment

[0047] In Figure 1 FIG. shows an ultrasonic diagnostic device 10 according to the embodiment. The ultrasonic diagnostic device 10 is a medical device used in ultrasonic examinations of a subject (living body) installed in a medical institution such as a hospital. The ultrasonic diagnostic device 10 according to the embodiment has an operation mode (hereinafter referred to as the fat percentage estimation mode) for estimating the fat percentage of the liver in addition to the B mode for displaying tomographic images.

[0048] In Figure 1 FIG., an ultrasonic probe 12 is a portable device that transmits and receives ultrasonic waves to obtain received information. The ultrasonic probe 12 has an oscillator array composed of a plurality of oscillators arranged linearly or curvilinearly. An ultrasonic beam is formed by the oscillator array. The ultrasonic beam is electronically scanned. As the electronic scanning method, an electronic linear scanning method, an electronic sector scanning method, etc. are known. A two-dimensional oscillator array may be provided in the ultrasonic probe 12.

[0049] The transmission circuit 13 is an electronic circuit that functions as a transmission beam former. At the time of transmission, the transmission circuit 13 supplies a plurality of transmission signals to the oscillator array in parallel. Thereby, a transmission beam is formed by the oscillator array.

[0050] The reception circuit 14 is an electronic circuit that functions as a reception beam former. At the time of reception, if a reflected wave from inside the living body is received by the oscillator array, a plurality of received signals are output in parallel from the oscillator array. The reception circuit 14 applies in-phase addition to the plurality of received signals, thereby generating reception beam data. The reception circuit 14 has a plurality of amplifiers, a plurality of A / D converters, an in-phase addition circuit, etc.

[0051] When performing the B mode, the ultrasonic beam is electronically scanned over the entire range of the electronic scan. Thereby, received frame data is obtained. The received frame data is composed of a plurality of received beam data arranged along the electronic scan direction. Each received beam data is composed of a plurality of echo data arranged along the depth direction. The received frame data is B mode reception information. As the electronic scanning of the ultrasonic beam is repeatedly performed, a plurality of received frame data are sequentially output from the receiving circuit 14.

[0052] When performing the fat percentage estimation mode, the first transmission / reception and the second transmission / reception different from those for the B mode are sequentially performed. Specifically, the first transmission / reception and the second transmission / reception are sequentially performed on a two-dimensional region of interest set in the liver as the object to be examined.

[0053] In the first transmission / reception, a first ultrasonic wave having a first center frequency is transmitted into the subject to be examined, and the first reception information is obtained by receiving the first reflected wave from within the subject to be examined. The first reception information is composed of a plurality of first received beam data (first received beam data set) corresponding to a plurality of first received beams passing through the region of interest. More specifically, the first received beam data set is composed of a plurality of echo data corresponding to a plurality of observation points (sampling points) two-dimensionally diffused within the region of interest.

[0054] In the second transmission / reception, a second ultrasonic wave having a second center frequency different from the first center frequency is transmitted into the subject to be examined, and the second reception information is obtained by receiving the second reflected wave from within the subject to be examined. The second reception information is composed of a plurality of second received beam data (second received beam data set) corresponding to a plurality of second received beams passing through the region of interest. More specifically, the second received beam data set is composed of a plurality of echo data corresponding to a plurality of observation points (sampling points) two-dimensionally diffused within the region of interest. In addition, 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.

[0055] The data processing unit 16 is an electronic circuit that applies the necessary processing to each received beam data. The data processing unit 16 includes an envelope detection circuit, a smoothing circuit, a logarithmic compression circuit, etc. When performing the B mode, a plurality of received frame data are sequentially transmitted from the data processing unit 16 to the image forming unit 18. When performing the fat percentage estimation mode, the first received beam data set and the second received beam data set are sequentially transmitted from the data processing unit 16 to the information processing unit 24.

[0056] The image forming unit 18 sequentially generates a plurality of tomographic image data based on the plurality of received frame data. The image forming unit 18 has a digital scan converter (DSC), and the digital scan converter (DSC) has functions such as a coordinate transformation function and a pixel interpolation function.

[0057] A plurality of tomographic image data are sent to the display 22 via the display processing unit 20. In the display 22, a plurality of tomographic images are displayed as a moving image. If a freeze operation is performed, the tomographic image corresponding to a specific time is displayed as a still image. The display 22 is composed of an organic electroluminescence (EL) display or the like. When the fat percentage estimation mode is executed, in addition to the tomographic image as a still image, the attenuation coefficient, the estimated value of the fat percentage (PDFF estimated value), etc. are also displayed on the display 22.

[0058] The information processing unit 24 is composed of a CPU that executes a program. The information processing unit 24 has a function of controlling the operations of the respective components constituting the ultrasonic diagnostic apparatus 10. In Figure 1 this, the multiple main functions exerted by the information processing unit 24 are represented by multiple functional blocks. The information processing unit 24 has a transceiver controller 26 and an arithmetic module 28. The arithmetic module 28 has a parameter arithmetic unit (first arithmetic unit) 30 and an estimated value arithmetic unit (second arithmetic unit) 32.

[0059] The transceiver controller 26 controls the transmission and reception of ultrasonic waves. Specifically, it controls the operations of the transmission circuit 13 and the reception circuit 14. As will be described later, the parameter arithmetic unit 30 has a function of calculating a first parameter set based on the first received information and a function of calculating a second parameter set based on the second received information. The estimated value arithmetic unit 32 has a function of calculating an estimated value of the fat percentage based on a parameter set including the first parameter set and the second parameter set.

[0060] 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.

[0061] The memory 36 is composed of, for example, a semiconductor memory. Information or programs required for the ultrasonic diagnostic apparatus 10 to operate are stored in the memory 36. 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 inspection value data from an external device are input to the information processing unit 24. The inspection value data includes, for example, BMI data, blood test data, etc. In addition, Figure 1 each of the components shown is composed of an electronic circuit, a processor, a device, etc.

[0062] In Figure 2 this, a structural example of the parameter arithmetic unit 30 and the estimated value arithmetic unit 32 shown Figure 1 is shown. They function in the fat percentage estimation mode.

[0063] The parameter operation unit 30 includes a first matrix operation unit 40, a second matrix operation unit 42, a first information generator 43, a second information generator 44, a first coefficient operation unit 46, a first average operation unit 48, a first deviation operation unit 50, a second coefficient operation unit 52, a second average operation unit 54, and a second deviation operation unit 56.

[0064] The first matrix operation unit 40 calculates a first attenuation matrix based on the first received information. The first attenuation matrix can also be referred to as a first attenuation amount matrix. Specifically, the first matrix operation unit 40 calculates the first attenuation matrix, which is a two-dimensional matrix, based on the two-dimensional first received intensity matrix obtained from within the region of interest and the one-dimensional first reference intensity column output from the first information generator 43.

[0065] The second matrix operation unit 42 calculates a second attenuation matrix based on the second received information. The second attenuation matrix can also be referred to as a second attenuation amount matrix. Specifically, the second matrix operation unit 42 calculates the second attenuation matrix, which is a two-dimensional matrix, based on the two-dimensional second received intensity matrix obtained from within the region of interest and the one-dimensional second reference intensity column output from the second information generator 44.

[0066] The first information generator 43 generates a first reference intensity column according to the first reference intensity function. The second information generator 44 generates a second reference intensity column according to the second reference intensity function. The first reference intensity column and the second reference intensity column that have been calculated or measured can be stored in a memory in advance (refer to Figure 1 ).

[0067] The first coefficient operation unit 46 calculates a first attenuation coefficient (first attenuation rate) based on a specific first attenuation column selected from the first attenuation matrix. In the embodiment, the specific first attenuation column corresponds to the received beam passing through the center of the region of interest.

[0068] The first average operation unit 48 calculates a first attenuation average based on the multiple first attenuation columns that make up the first attenuation matrix. The first attenuation average can also be referred to as a first attenuation amount average. The first attenuation average can be calculated based on a part of the first attenuation matrix.

[0069] The first deviation operation unit 50 calculates a first attenuation deviation based on the multiple first attenuation columns that make up the first attenuation matrix. The first attenuation deviation can also be referred to as a first attenuation amount deviation. The first attenuation deviation can also be calculated based on a part of the first attenuation matrix. Specifically, the first attenuation deviation is the standard deviation (SD). As the first attenuation deviation, variance, etc. can be calculated.

[0070] The second coefficient calculator 52 calculates a second attenuation coefficient (second attenuation rate) based on a specific second attenuation column selected from the second attenuation matrix. In the embodiment, the specific second attenuation column corresponds to the reception beam passing through the center of the region of interest.

[0071] 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 can also be said to be the second attenuation amount average. The second attenuation average can also be calculated based on a part of the second attenuation matrix.

[0072] The second deviation calculator 56 calculates a second attenuation deviation based on a plurality of second attenuation columns constituting the second attenuation matrix. The second attenuation deviation can also be said to be the second attenuation amount deviation. The second attenuation deviation can be calculated based on a part of the second attenuation matrix. Specifically, the second attenuation deviation is the standard deviation (SD). As the second attenuation deviation, variance or the like can be calculated.

[0073] The first parameter group is composed of the above-mentioned first attenuation coefficient, first attenuation average, and first attenuation deviation. The second parameter group is composed of the above-mentioned second attenuation coefficient, second attenuation average, and second attenuation deviation. The first parameter group and the second parameter group are included in the parameter set. In the embodiment, the parameter set further includes examination values obtained from the subject through examinations other than ultrasonic examinations. Specifically, it includes BMI (Body Mass Index). The parameter set can include examination values in place of BMI, or can also include BMI and other examination values.

[0074] The estimated value calculation unit 32 has a mathematical model 58. The mathematical model 58 is composed of one or more mathematical expressions for calculating the estimated value of the fat percentage based on the parameter set. A machine learning completed model can also be used instead of the mathematical model 58. The machine learning completed model is composed of a neural network or the like, inputs the parameter set, and outputs the estimated value of the fat percentage.

[0075] The estimated value calculation unit 32 according to the embodiment has 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, when a blood vessel or an artifact is included in the region of interest, the error determiner 60 determines an error. An error can also be determined based on one or both of the first attenuation deviation and the second attenuation deviation. When an error is determined, an error message is provided to the user. Then, based on the user changing the position of the region of interest, the above-mentioned first transceiver and second transceiver are executed again.

[0076] In Figure 3 is shown the region of interest 64 set on the beam scanning plane 62. In Figure 3In this case, the x-direction is the depth direction, and the θ-direction is the electronic scanning direction. The beam scanning plane 62 is formed by electronically scanning the ultrasonic beam 65.

[0077] The region of interest 64 is a two-dimensional region. Specifically, the region of interest 64 extends in the depth direction over a range from depth x1 to depth x2. The region of interest 64 corresponds to an arrangement of N received beams in the electronic scanning direction. N is, for example, 9, 11, 13, etc. In the embodiment, the depths x1 and x2 are fixed values. The depths x1 and x2 can be specified by the user. The azimuth θ1 is the azimuth corresponding to the center of the region of interest 64. The user can change the azimuth θ1. For example, the region of interest 64 is set so that the large blood vessel does not enter the region of interest 64. In fact, the region of interest 64 is specified on the tomographic image.

[0078] In Figure 4 FIG. shows N received beams 66 passing through the region of interest 64. Each received beam 66 includes M received intensities (amplitude values) 68 arranged in the depth direction. The first received intensity matrix obtained by the first transceiver is composed of M×N received intensities arranged in the depth direction and the electronic scanning direction. Similarly, the second received intensity matrix obtained by the second transceiver is composed of M×N received intensities arranged in the depth direction and the electronic scanning direction. The symbol 70 represents the column of received intensities located at the center of the region of interest. In the depth direction, the observation point pitch is represented by Δx.

[0079] Next, the fat percentage estimation method according to the embodiment will be described. First, the operations of the attenuation matrix, attenuation coefficient, attenuation average, and attenuation deviation will be described, and then the operation of the estimated value approximating the PDFF will be described. The entity of each attenuation constituting the attenuation matrix is the attenuation amount.

[0080] 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).

[0081] [Equation 1]

[0082]

[0083] Here, f is the frequency of the ultrasonic wave (typically the center frequency), and x is the depth (the coordinate in the depth direction). The received intensity matrix P(x) is composed of a plurality of received intensities obtained from a plurality of observation points constituting the two-dimensional region of interest.

[0084] In the above equation (1), the attenuation matrix A aEach attenuation is equivalent to an absolute attenuation. The absolute attenuation varies significantly depending on the operating conditions of the ultrasonic diagnostic device, etc. Therefore, generally, according to the following equation (2), the attenuation matrix A is obtained by comparing the received intensity matrix P(x) with the reference intensity column (reference signal) P ref (x). r . In addition, the common reference intensity column P ref (x) is applied to multiple received intensity columns arranged in the electronic scanning direction.

[0085] [Equation 2]

[0086]

[0087] The attenuation matrix A r is composed of multiple attenuations arranged in the depth direction and the electronic scanning direction. Each attenuation is a relative attenuation. By adding a known attenuation corresponding to the reference intensity column P ref (x) to each attenuation, the final attenuation (absolute attenuation) is obtained.

[0088] Incidentally, the reference intensity column P ref (x) is defined by the following equation (3), for example. Here, γ is a coefficient.

[0089] [Equation 3]

[0090]

[0091] The reference intensity column P ref (x) can also be defined by other functions. The reference intensity column can be given as a numerical column.

[0092] [[ID=,38]]The attenuation coefficient column α r is calculated according to the following equation (4).

[0093] [Equation 4]

[0094]

[0095] Here, i represents the depth number. A rc (x i ) represents the central attenuation column in the attenuation matrix. Δx is defined by the following equation (5).

[0096] [Equation 5]

[0097]

[0098] Each attenuation constituting the attenuation coefficient column α r is a relative attenuation coefficient. The attenuation coefficient (absolute attenuation coefficient) α at each depth is calculated according to the following equation (6).

[0099] [Equation 6]

[0100]

[0101] Here, k2 is a known attenuation coefficient corresponding to the reference intensity column P ref (x). k1 and k3 are adjustment coefficients respectively.

[0102] On the other hand, the attenuation average μ is calculated according to the following formula (7).

[0103] [Equation 7]

[0104]

[0105] 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 electron scanning direction in the region of interest. i represents the coordinate in the depth direction, and j represents the coordinate in the electron scanning direction. A r i，j represents the attenuation corresponding to the observation point (i, j). As the attenuation average μ, the average of the attenuation coefficients can be calculated.

[0106] As the attenuation deviation, the attenuation standard deviation (attenuation SD) σ is calculated according to the following formula (8).

[0107] [Equation 8]

[0108]

[0109] The variance can be calculated instead of the attenuation SD σ, and other indices representing the deviation of the attenuation can also be calculated.

[0110] In the embodiment, before calculating the estimated value E of the fat percentage, the intermediate value Y is calculated according to the following formula (9).

[0111] [Equation 9]

[0112]

[0113] Here, a, b, c, d, e, f, g, h are coefficients respectively, which are determined in advance by the multiple regression analysis described later. Among these coefficients, h is equivalent to the offset. α1 is the first attenuation coefficient obtained from the first received information, μ1 is the first attenuation average obtained from the first received information, and σ1 is the first attenuation standard deviation obtained from the first received information. α2 is the second attenuation coefficient obtained from the second received information, μ2 is the second attenuation average obtained from the second received information, and σ2 is the second attenuation standard deviation obtained from the second received information. BMI is the BMI value of the subject.

[0114] According to the intermediate value Y, the estimated value E is calculated according to the following formula (10).

[0115] [Equation 10]

[0116]

[0117] Here, B, C, and A are coefficients respectively.

[0118] There is a non-linear relationship (specifically, a logarithmic relationship) expressed by the following equation (11) between the intermediate value Y and the PDFF.

[0119] [Equation 11]

[0120]

[0121] On the premise of multiple regression analysis, in order to correspond to the above non-linear relationship, the intermediate value Y is obtained in the embodiment. It is also possible to directly calculate the estimated value E from the combination of α1, μ1, σ1, α2, μ2, σ2, and BMI without going through the calculation of the intermediate value Y. In this case, a machine learning completed estimation model can be used.

[0122] In Figure 5 shows the process of calculating the estimated value. The entity of the first received information is the first received intensity matrix P1(x), and the entity of the second received information is the second received intensity matrix P2(x). The entity of the first reference information is the first reference intensity column P ref1 (x), and the entity of the second reference information is the second reference intensity column P ref2 (x).

[0123] Calculate the first attenuation matrix A ref1 according to the first received intensity matrix P1(x) and the first reference intensity column P r1 . Calculate the second attenuation matrix A ref2 according to the second received intensity matrix P2(x) and the second reference intensity column P r2 . Apply the first reference intensity column P ref1 (x) that is common to multiple first received intensity columns constituting the first received intensity matrix P1(x). Similarly, apply the second reference intensity column P ref2 (x) that is common to multiple second received intensity columns constituting the second received intensity matrix P2(x).

[0124] By comparing the central attenuation column A r1 in the first attenuation matrix A rc1 with the first reference intensity column P ref1 (x), calculate the first attenuation coefficient α1. According to the first attenuation matrix A r1To calculate the first decay average μ1 and the first decay SD σ1. The first parameter set consists of the first decay coefficient α1, the first decay average μ1, and the first standard deviation σ1.

[0125] By multiplying the second decay matrix A r2 with the central decay column A rc2 in it and comparing it with the second reference intensity column P ref2 (x), the second decay coefficient α2 is calculated. Based on the second decay matrix A r2 the second decay average μ2 and the second decay SD σ2 are calculated. The second parameter set consists of the second decay coefficient α2, the second decay average μ2, and the second decay SD σ2. The parameter set consists of the first parameter set, the second parameter set, and the BMI.

[0126] Based on the parameter set, the estimated value E of the fat percentage is calculated. As will be described later, this estimated value E is based on the PDFF obtained through the actual measurements of multiple examinees, and thus becomes a value approximated to the PDFF.

[0127] In Figure 6 the generation method of the mathematical model is shown. By performing MRI examinations, ultrasonic examinations, and other examinations on multiple examinees, a PDFF group 74, a parameter group 76, and a BMI group 78 (reference sign 72) are obtained. According to the above formula (11), the PDFF group 74 is converted into an intermediate value group 80. In addition, the coefficients A, B, and C in the formula (11) are determined in advance. The coefficients a to h and the coefficients A, B, and C can be determined simultaneously by an optimal solution search method or the like.

[0128] By performing multiple regression analysis 82 based on the intermediate value group 80, the parameter group 76, and the BMI group 78, the coefficient group (a to h) 84 is determined. Thus, the above formula (9) is defined as the mathematical model 86. In addition, the estimation model can also be generated by machine learning using the PDFF group 74, the parameter group 76, and the BMI group 78.

[0129] In Figure 7 a display example is shown. On the screen 88 of the display, a tomographic image 90 as an ultrasonic image is displayed. The tomographic image 90 represents the cross-section of the liver of the examinee. In the tomographic image 90, a first marker 94 and a second marker 96 indicating both ends of the region of interest in the depth direction are included. In addition, the line 92 represents the center line of the region of interest.

[0130] As a result of executing the fat percentage estimation mode, the decay 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 decay coefficient 98 is the first decay coefficient or the second decay coefficient. These average values can be displayed as the decay coefficient 98. In the case of being determined as an error, an error message is displayed on the screen 88.

[0131] Next, according toFigure 8 , an operation example of the ultrasonic diagnostic apparatus shown in Figure 1 will be described. In S10, B-mode transmission and reception is performed. As a result, a tomographic image representing 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.

[0132] In S14, first transmission and reception is performed. Specifically, a first ultrasonic wave having a first center frequency is transmitted from the ultrasonic probe to the region of interest. Then, the first reflected wave from the region of interest is received by the ultrasonic probe. As a result, first reception information is obtained. In S16, a first parameter set including a first attenuation coefficient is calculated based on the first reception information.

[0133] In S18, second transmission and reception is performed. Specifically, a second ultrasonic wave having a second center frequency is transmitted from the ultrasonic probe to the region of interest. Then, the second reflected wave from the region of interest is received by the ultrasonic probe. As a result, second reception information is obtained. In S20, a second parameter set including a second attenuation coefficient is calculated based on the second reception information. In practice, S18 is performed immediately after S14 ends, and S20 is performed immediately after S16 ends.

[0134] In S22, an estimated value of the fat percentage is calculated based on the parameter set including the first parameter set and the second parameter set. In S24, the estimated value and the attenuation coefficient are displayed together. At this time, the entire parameter set can be displayed.

[0135] In Figure 9 , an operation example of the ultrasonic diagnostic apparatus according to the modified example is shown. B-mode transmission and reception is performed in S10, and a region of interest is set in S12. In S30, transmission and reception for fat percentage estimation is performed. For example, an ultrasonic wave including a first frequency component and a second frequency component is transmitted to the region of interest, and the reflected wave from the region of interest is received. As a result, reception information is obtained.

[0136] In S32, the first frequency component included in the reception information is extracted by a first reception filter, and a first parameter set is calculated based on the first frequency component. In S34, the second frequency component included in the reception information is extracted by a second reception filter, and a second parameter set is calculated based on the second frequency component. The first reception filter has a first frequency characteristic for extracting the first frequency component, and the second reception filter has a second frequency characteristic for extracting the second frequency component. In S36, an estimated value of the fat percentage is calculated based on the parameter set including the first parameter set and the second parameter set. In S38, the estimated value is displayed.

[0137] According to this modified example, the estimated value is obtained by one-time transmission and reception. When giving priority to estimation accuracy, it is preferable to adopt the operation shown in Figure 8 .

[0138] According to the above-described embodiment, in the ultrasonic diagnostic apparatus, it is possible to calculate an estimated value of the fat percentage based on the first attenuation coefficient and the second attenuation coefficient obtained under different transmission and reception conditions. In particular, it is possible to calculate an estimated value approximate to PDFF. Since the parameter set has a plurality of parameters other than the first attenuation coefficient and the second attenuation coefficient, the estimation accuracy of the fat percentage can be improved. Instead of or in addition to the attenuation average and the attenuation deviation, other parameters obtained from the received information can also be used. BMI can be excluded from the parameter set, or an examination value substituting for BMI can be used.

Claims

1. An ultrasonic diagnostic apparatus, characterized in that, Comprising: A first arithmetic unit that calculates a plurality of attenuation coefficients based on a plurality of received information having mutually different frequency characteristics obtained from the liver within the subject. And A second arithmetic unit that calculates an estimated value of the fat ratio based on a parameter set including the plurality of attenuation coefficients.

2. The ultrasonic diagnostic apparatus according to claim 1, wherein The second arithmetic unit has a model created in such a way that the estimated value approximates MRI-PDFF, And calculates the estimated value by assigning the parameter set to the model.

3. The ultrasonic diagnostic apparatus according to claim 1, wherein The plurality of received information includes first received information having a first frequency characteristic and second received information having a second frequency characteristic, The plurality of attenuation coefficients includes a first attenuation coefficient calculated based on the first received information and a second attenuation coefficient calculated based on the second received information.

4. The ultrasonic diagnostic apparatus according to claim 3, wherein Comprising: An ultrasonic probe that obtains the first received information by transmitting a first ultrasonic wave having a first center frequency into the subject, and obtains the second received information by transmitting a second ultrasonic wave having a second center frequency different from the first center frequency into the subject.

5. The ultrasonic diagnostic apparatus according to claim 3, characterized in that, Comprising: A generator that generates first reference information for comparison with the first received information and second reference information for comparison with the second received information, The first arithmetic unit performs the following processing: Calculates the first attenuation coefficient based on the first received information and the first reference information; and Calculates the second attenuation coefficient based on the second received information and the second reference information.

6. The ultrasonic diagnostic apparatus according to claim 5, wherein The first received information and the second received information are respectively information obtained from a two-dimensional region within the subject, The first arithmetic unit performs the following processing: Calculates a first attenuation matrix based on the first received information and the first reference information, Calculates a first parameter group including the first attenuation coefficient, the first attenuation average, and the first attenuation deviation based on the first attenuation matrix, Calculates a second attenuation matrix based on the second received information and the second reference information, Calculates a second parameter group including the second attenuation coefficient, the second attenuation average, and the second attenuation deviation based on the second attenuation matrix, The parameter set includes the first parameter group and the second parameter group.

7. The ultrasonic diagnostic apparatus according to claim 6, wherein The two-dimensional region corresponds to a plurality of received beams arranged in the electronic scanning direction, The first arithmetic unit performs the following processing: Calculates the first attenuation coefficient based on a specific attenuation column selected from the first attenuation matrix, Calculates the first attenuation average and the first attenuation deviation based on a plurality of attenuation columns in the first attenuation matrix, Calculates the second attenuation coefficient based on a specific attenuation column selected from the second attenuation matrix, Calculates the second attenuation average and the second attenuation deviation based on a plurality of attenuation columns in the second attenuation matrix.

8. The ultrasonic diagnostic apparatus according to claim 6, wherein: the parameter set further includes one or more parameters obtained from the subject through examinations other than ultrasonic examinations.

9. The ultrasonic diagnostic apparatus according to claim 1, wherein comprising: a former that forms an ultrasonic image based on received information different from the plurality of received information; and a display that displays the ultrasonic image, at least one of the plurality of attenuation coefficients, and an estimated value of the fat percentage.

10. A method for estimating fat percentage, characterized in that, including the following steps: calculating a plurality of attenuation coefficients based on a plurality of received information having different frequency characteristics obtained from the liver within the subject; and calculating an estimated value of the fat percentage based on a parameter set including the plurality of attenuation coefficients.

11. A storage medium stores a program, characterized in that, The program is for executing a fat percentage estimation method in an information processing apparatus, and the program includes the following functions: calculating a plurality of attenuation coefficients based on a plurality of received information having different frequency characteristics obtained from the liver within the subject; and calculating an estimated value of the fat percentage based on a parameter set including the plurality of attenuation coefficients.

12. A program product, comprising a program, characterized in that, The program is for executing a fat percentage estimation method in an information processing apparatus, and the program includes the following functions: calculating a plurality of attenuation coefficients based on a plurality of received information having different frequency characteristics obtained from the liver within the subject; and calculating an estimated value of the fat percentage based on a parameter set including the plurality of attenuation coefficients.

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