JP2013000136A - Medical image apparatus - Google Patents

Abstract

PROBLEM TO BE SOLVED: To appropriately diagnose an object to be diagnosed noninvasively by acquiring, on the basis of elastic information measured by a medical image apparatus, a specific diagnosis evaluation value for evaluating whether a diagnosis region is benign or malignant.SOLUTION: The medical image apparatus includes: an elastic information computing part 32 for computing the elastic image information on the basis of tomographic image information of the diagnosis region of a subject photographed through times; a hardness-ratio computing part 64 for acquiring the hardness ratio, that is a ratio between an elastic value of a first region and an elastic value of a second region set within the diagnosis region, on the basis of the elastic image information; a diagnosis-evaluation-value calculating part 65 for calculating a diagnosis evaluation value corresponding to the hardness ratio, which is acquired by the hardness-ratio computing part, on the basis of the preset correlation between the hardness ratio and the diagnosis evaluation value; and an image display part on which the elastic image formed on the basis of the elastic image information and a diagnosis evaluation value acquired by the diagnosis-evaluation-value calculating part are displayed.

Description

  The present invention relates to a medical imaging apparatus, and more particularly to a medical imaging apparatus suitable for objectively evaluating the benign / malignant nature of a diagnostic part based on elasticity information of the diagnostic part of a subject.

  In an ultrasonic imaging apparatus, a magnetic resonance imaging apparatus, or the like, which is a medical imaging apparatus, elasticity representing the hardness or softness of a living tissue based on tomographic image information of a diagnostic part of a subject imaged in time series. It is widely known to obtain image information and diagnose benign or malignant tissue of a diagnosis site based on elasticity information. For example, according to Patent Document 1, using an ultrasonic imaging apparatus, a displacement of a tissue that is displaced by a pressure applied to a diagnostic region of a subject is obtained based on two pieces of tomographic image information having different measurement times, and the obtained displacement distribution Based on the above, it is disclosed to generate and display an elasticity image representing the elasticity of the tissue at the diagnostic site. Here, various methods have been proposed as a method of applying pressure to the diagnosis site. For example, it is common to apply pressure to the diagnostic part by manually or mechanically pressing the ultrasound probe against the subject. However, mechanical shocks may be applied to the subject, the subject's breathing or pulse, etc. There are widely known methods of using the body movement of the body and applying pressure with the sound pressure of ultrasonic waves.

  Further, as the elasticity information (elastic value), the displacement amount, strain, elastic modulus and physical quantity correlated with these are known, but these elastic values include relative physical quantities. Therefore, it is difficult to objectively evaluate the benign / malignant nature of the tissue depending on the magnitude of the obtained elasticity value. Therefore, Patent Document 2 proposes setting a plurality of regions of interest in elastic image information and calculating an index value by calculating a ratio of elasticity values between the regions of interest. Thereby, for example, elastic information that can be objectively or absolutely evaluated can be obtained regardless of the pressure applied to the tissue. The elasticity information can be obtained not only by the ultrasonic imaging apparatus but also by a magnetic resonance imaging apparatus (MRI apparatus) as described in Patent Document 3 and Non-Patent Document 2.

  On the other hand, Non-Patent Document 1 reports the research results of a new diagnostic technique utilizing the ratio of elasticity information.

JP-A-5-317313 Patent No. 3991282 JP 2008-142368 A

Koizumi. Et.al, ”Liver Fibrosis in Patients with Chronic Hepatitis C: Noninvasive Diagnosis by Means of Real-time Tissue Elastography-Establishmentof the Method for Measurement” Radiology: Volume 258: Number 2-February 2011 Mikio Tsuji "Quantitative Viscoelasticity Distribution Measurement Method for Living Tissue", Biomedical Engineering Vol. 46. 181-182 (2008)

  The technique described in Patent Document 2 or Non-Patent Document 1 is a useful technique in that it proposes a method of converting a relative elasticity value into a value for performing absolute evaluation. However, correlation processing is performed on the elasticity values of different parts of the elasticity image, and the elasticity value is normalized or indexed to enable absolute evaluation.

  By the way, in the diagnosis of cirrhosis and the like, it is known that portal vein pressure increases with liver fibrosis that hardens the liver. However, the correlation between liver hardness and portal pressure obtained from blood tests and imaging tests is weak, and there is a limit to accurately estimate the portal pressure from the measured values of liver hardness.

  In addition, it is known that hypersplenic function progresses as liver fibrosis progresses and approaches cirrhosis. However, conventionally, since there is no method for non-invasively and objectively or absolutely evaluating splenic hardness, the relationship between hypersplenism and splenic hardness has not been clarified. In addition, for example, the HVPG (Hepatic Venous Pressure Gradient) method for examining the slope of hepatic venous pressure is widely recognized as being extremely useful for the progression of cirrhosis, prognosis estimation, and prediction of complications. However, since the HVPG method needs to insert a selective catheter into the hepatic vein by angiography and is invasive, there is a demand for the realization of a non-invasive method for examining the progress of cirrhosis.

  The problem to be solved by the present invention is to provide a unique diagnostic evaluation value (for example, portal vein pressure in the liver, etc.) for evaluating benign / malignant of a diagnostic site based on elasticity information measured non-invasively by a medical imaging apparatus. It is desired to realize a technique that can appropriately diagnose a diagnosis target in a non-invasive manner.

  The medical imaging apparatus of the present invention that solves the above problems is based on an elasticity information calculation unit that calculates elasticity image information based on tomographic image information of a diagnostic region of a subject that is imaged in time series, and based on the elasticity image information A hardness ratio calculation unit for obtaining a hardness ratio which is a ratio of an elasticity value of the first part and an elasticity value of the second part set as the diagnosis part, and the hardness ratio obtained by the hardness ratio calculation part A diagnostic evaluation value calculating unit that calculates a corresponding diagnostic evaluation value based on a correlation between the hardness ratio set in advance and the diagnostic evaluation value; an elastic image created based on the elastic image information; An image display unit for displaying the diagnostic evaluation value obtained by the diagnostic evaluation value calculation unit is provided.

  The inventors of the present invention have intensively studied to solve the above-mentioned problems, and as a result, have found the following and have come to configure the present invention. That is, although there is a report that there is some relationship between portal vein pressure and splenic hardness, there is no method for noninvasively and objectively evaluating splenic hardness. Therefore, for a large number of specimens, the ratio of the elasticity value of the splenic parenchyma and the elasticity value of the splenic vein is obtained as the splenic hardness ratio based on the elasticity image information obtained in real time by the medical imaging apparatus. The portal vein pressure of the specimen was measured invasively and analyzed. As a result, it was found that there is a strong correlation between the splenic hardness ratio and the portal pressure, for example, a correlation that can be expressed by a linear function. In particular, the splenic hardness ratio obtained from non-invasive elasticity information has individual differences due to age and differences between men and women, but according to the correlation between splenic hardness ratio and portal pressure, individual differences It was found that the portal pressure can be obtained with high accuracy regardless.

  From these findings, it was found that there is a specific site showing a strong correlation between the diagnostic evaluation value for evaluating benign / malignant of the diagnostic site and the hardness ratio of the two sites related to the diagnostic object. Therefore, the present invention obtains in advance a diagnostic evaluation value of a diagnostic site for a large number of individuals by an invasive examination or the like, and obtains a hardness ratio between two specific sites based on elastic image information. The correlation between the hardness ratio of the part and the diagnostic evaluation value is analyzed. If there is a strong correlation in the correlation, the correlation function is obtained by approximating the correlation function in advance, and by setting the hardness ratio between the two specific parts based on the elastic image information, the set correlation is obtained. Since a diagnostic evaluation value for evaluating benign / malignant of a diagnosis site can be objectively and accurately estimated based on a function, diagnosis of a diagnosis target can be performed appropriately or accurately.

  That is, according to the present invention, a correlation between the hardness ratio and the diagnostic evaluation value related to the diagnostic part is set in advance, and the first part and the second part corresponding to the hardness ratio are set as the diagnostic part. Then, a hardness ratio, which is a ratio between the elastic values of the first part and the second part, is obtained based on the elasticity image information, and a diagnostic evaluation value is obtained based on a correlation function between a preset hardness ratio and a diagnostic evaluation value. Is displayed on the image display unit. Thereby, an appropriate diagnosis can be performed for the diagnosis target.

  For example, the correlation function between the splenic hardness ratio obtained from the elastic image information = (splenic parenchyma / splenic portal vein) and portal pressure, which is a diagnostic evaluation value of cirrhosis, is a linear function, and is strongly established for many different individuals. I gained knowledge. Therefore, the correlation function between the splenic hardness ratio and portal pressure is called the SEP score. Based on this SEP score (Splenic Elasticity for Portal hypertension Score), the portal pressure corresponding to the splenic hardness ratio obtained from the elastic image information is calculated. By obtaining, it is possible to appropriately diagnose a diagnosis object non-invasively. That is, the first part is set to the splenic parenchyma, the second part is set to the portal vein of the spleen, and the splenic hardness ratio, which is the ratio between the splenic parenchyma and the splenic vein, is determined and set Based on the correlation function (SEP score) between the splenic hardness ratio and the portal vein pressure of the liver, the portal vein pressure of the liver corresponding to the splenic hardness ratio obtained from the elastic image information can be accurately estimated. As a result, it is possible to realize a diagnostic method that is extremely effective in diagnosing cirrhosis, prognosis of disease state, and prediction of complications.

  In the present invention, instead of the splenic parenchyma and the hilar vein, the first part can be set in the liver parenchyma and the second part can be set in the hepatic vein of the liver. The diagnostic evaluation value in this case does not change with the portal pressure of the liver, but the hardness ratio is the liver hardness ratio.

  Further, the present invention obtains both the spleen hardness ratio and the liver hardness ratio based on the elastic image information, calculates two portal vein pressures based on the correlation function between them and the portal pressure, and provides them to the examiner can do. According to this, the examiner can perform a more appropriate diagnosis for the diagnosis target in consideration of both.

  According to the present invention, since an invasive facility such as an angiographic device or a catheter is not required, it is possible to measure a diagnostic evaluation value with an ultrasonic imaging device that is relatively inexpensive.

  According to the present invention, a specific diagnostic evaluation value (for example, portal vein pressure in the liver) for evaluating benign / malignant of a diagnostic site is obtained based on elasticity information measured non-invasively by a medical imaging apparatus, and non-invasive Thus, it is possible to realize a medical image apparatus that can appropriately diagnose a diagnosis target.

1 is an overall block configuration diagram of an ultrasonic imaging apparatus according to an embodiment to which the present invention is applied. It is a block diagram which shows the detailed structure of the diagnostic evaluation value calculating part which is the characteristic part of FIG. 1 embodiment. It is a figure which shows an example of a display image. It is a figure which shows an example of a SEP score.

  An ultrasonic imaging apparatus according to an embodiment to which the present invention is applied will be described with reference to FIG. As shown in the figure, the ultrasonic imaging apparatus 1 includes an ultrasonic probe 12 that is used while being in contact with the subject 10, and an ultrasonic probe 12 that is spaced from the subject 10 via the ultrasonic probe 12 at a time interval. A transmission unit 14 that repeatedly transmits sound waves, a reception unit 16 that receives time-series reflected echo signals generated from the subject 10, a transmission / reception control unit 17 that controls the transmission unit 14 and the reception unit 16, and a reception unit 16. A phasing addition unit 18 for phasing and adding the received reflected echo is provided. Based on the RF signal frame data output from the phasing adder 18, the tomographic image forming unit 20 that forms a tomographic image of the subject, for example, a black and white tomographic image, and the output signal of the tomographic image forming unit 20 are displayed on the image display 26. And a black-and-white scan converter 22 for conversion to suit the display.

  Further, the RF signal frame data output from the phasing addition unit 18 is stored, the RF frame data selection unit 28 that selects at least two pieces of frame data, and the displacement measurement unit that measures the displacement of the living tissue of the subject 10. 30, an elastic information calculation unit 32 for obtaining elastic information (elastic value) of strain or elastic modulus from the displacement information measured by the displacement measuring unit 30, and a color elastic image based on the elastic value calculated by the elastic information calculation unit 32 And a color scan converter 36 for converting the output signal of the elastic image forming unit 34 so as to match the display on the image display 26. A display image control unit 24 that displays a black and white tomographic image and a color elastic image in parallel or generates a composite image by superimposing, and an image display unit 26 that displays an image output from the display image control unit 24. Is provided.

  In addition, an error value unit 40 that evaluates an error of the elastic image from output information of the elastic information calculation unit 32, a control unit 37 that controls the error evaluation unit 40, the elastic image forming unit 34, and the color scan converter 36, and a control A panel unit 38 as input means for giving an instruction to the unit 37 is provided.

  Next, the configuration of each part of the ultrasonic imaging apparatus 1 will be described in detail. The ultrasonic probe 12 is formed by arranging a plurality of transducers, and has a function of transmitting and receiving ultrasonic waves to and from the subject 10 via the transducers. The transmission unit 14 has a function of generating a transmission pulse for generating an ultrasonic wave by driving the ultrasonic probe 12 and setting a convergence point of the transmitted ultrasonic wave to a certain depth. Yes. The receiving unit 16 amplifies the reflected echo signal received by the ultrasonic probe 12 with a predetermined gain to generate an RF signal, that is, a received signal. The phasing adder 18 receives the RF signal amplified by the receiver 16 and performs phase control, and forms an ultrasonic beam at one point or a plurality of convergence points to generate RF signal frame data.

  The tomographic image constructing unit 20 receives the RF signal frame data from the phasing / adding unit 18 and performs signal processing such as gain correction, log compression, detection, contour emphasis, and filter processing to obtain tomographic image data. . The monochrome scan converter 22 also includes an A / D converter that converts tomographic image data from the tomographic image forming unit 20 into a digital signal, a frame memory that stores a plurality of converted tomographic image data in time series, and a control. It is configured to include a controller. This black and white scan converter 22 acquires tomographic frame data in the subject stored in the frame memory as one image, and reads the acquired tomographic frame data in accordance with display specifications such as TV synchronization.

  The RF frame data selection unit 28 stores a plurality of RF signal frame data from the phasing addition unit 18, and selects one set, that is, two RF signal frame data from the stored RF signal frame data group. For example, the RF signal frame data generated based on the time series, that is, the frame rate of the image from the phasing addition unit 18 is sequentially stored in the RF frame data selection unit 28, and the stored RF signal frame data (N) is first stored. At the same time, one RF signal frame data (X) is selected from the RF signal frame data group (N-1, N-2, N-3... NM) stored in the past in time. select. Here, N, M, and X are index numbers assigned to the RF signal frame data, and are natural numbers.

  The displacement measuring unit 30 performs one-dimensional or two-dimensional correlation processing from the selected set of data, that is, the RF signal frame data (N) and the RF signal frame data (X), and a living body corresponding to each point of the tomographic image. A one-dimensional or two-dimensional displacement distribution related to the displacement or movement vector in the tissue, that is, the direction and magnitude of the displacement is obtained. Here, a block matching method is used to detect the movement vector. The block matching method divides an image into blocks of N × N pixels, for example, pays attention to the block in the region of interest, searches the previous frame for the block that is closest to the block of interest, and refers to this Thus, predictive coding, that is, processing for determining the sample value by the difference.

  The elasticity information calculation unit 32 is a strain or elasticity of a living tissue corresponding to each point on the tomogram based on a measurement value output from the displacement measurement unit 30, for example, a movement vector, and a pressure value output from the pressure measurement unit 46. The modulus is calculated, and an elastic image signal, that is, elastic frame data is generated based on the strain and elastic modulus. Note that the pressure value output from the pressure measuring unit 46 is not necessary for strain calculation, and therefore can be omitted when the elastic value is limited to strain.

  The strain is calculated by spatially differentiating the movement amount of the living tissue, for example, the displacement. The elastic modulus data is calculated by dividing the change in pressure by the change in strain. For example, assuming that the displacement measured by the displacement measuring unit 30 is L (X) and the pressure measured by the pressure measuring unit 46 is P (X), the strain ΔS (X) spatially differentiates L (X). Therefore, it can be calculated using the equation ΔS (X) = ΔL (X) / ΔX. Further, the Young's modulus Ym (X) of the elastic modulus data is calculated by the equation Ym = (ΔP (X)) / ΔS (X). Since the elastic modulus of the living tissue corresponding to each point of the tomographic image is obtained from this Young's modulus Ym, two-dimensional elastic image data can be obtained continuously. The Young's modulus is a ratio of a simple tensile stress applied to the object and a strain generated in parallel with the tension.

  The elastic image construction unit 34 includes a frame memory and an image processing unit. The elastic image construction unit 34 secures the elastic frame data output in time series from the elastic information calculation unit 32 in the frame memory. In contrast, image processing is performed. The color scan converter 36 has a function of adding hue information to the elastic frame data from the elastic image forming unit 34. That is, the light is converted into the three primary colors of light, that is, red (R), green (G), and blue (B) based on the elastic frame data. For example, elastic data having a large strain is converted into a red code, and simultaneously elastic data having a small strain is converted into a blue code. Note that the color scan converter 36 can use a system such as YUV configured by pixel luminance and hue signals instead of the three primary colors of RGB. Furthermore, instead of using an independent scan converter, a method of reconstructing a display image by adding an identification code such as a time code to image information and writing it in a large-scale memory may be used. The same applies to black and white images. Further, a method of storing color-modulated image information in combination with original tomographic information is also possible. The large-capacity memory can also record a plurality of images as a moving image memory, and may be data of only a received beam in addition to a frame image. As a matter of course, the received beam data may be imaged data or data obtained by AD-converting an RF signal. In the latter case, an imaging processing function is provided later, but in short, it is necessary that the information of a plurality of frame images can be cited correspondingly.

  The display image control unit 24 includes a frame memory, an image processing unit, and an image selection unit. Here, the frame memory stores tomographic image data from the monochrome scan converter 22 and elastic image data from the color scan converter 36. The image processing unit synthesizes the tomographic image data and the elastic image data secured in the frame memory by changing the synthesis ratio. The luminance information and hue information of each pixel of the composite image is obtained by adding each information of the black and white tomographic image and the color elastic image at the composite ratio. Further, the image selection unit selects an image to be displayed on the image display 26 from the tomographic image data and elasticity image data in the frame memory and the composite image data of the image processing unit. Note that the frame memory is a conceptual description, and may include only sound ray data in addition to a completely developed frame image. The type of data may be data that has undergone imaging processing, or data that has just undergone AD conversion of the RF signal. Furthermore, only arguments such as addresses of received beam signals and time codes may be used. In this case, the image data is once read and reconstructed via these pieces of information.

  A detailed configuration of the diagnostic evaluation value calculation unit 57 will be described with reference to FIG. In the figure, elasticity information frame data from the elasticity information calculation unit 32 is sequentially recorded in the elasticity information storage unit 60. As described above, the stored elasticity information frame data is not limited to data of the elasticity image itself, but may be data having elasticity information constituting the elasticity information frame data. Note that elasticity information frame data corresponding to a plurality of frames may be stored in time series, and a cine memory function for reproducing a moving image after data collection may be provided. In the present embodiment, the elasticity information storage unit 60 sequentially outputs elasticity information corresponding to the frame images to the next preprocessing unit 61 corresponding to the entire processing speed during real-time imaging. It is also possible to perform a thinning process corresponding to the frame rate of the image display unit 26. Note that thinning can be performed temporally and spatially, and there is a method in which the number of data is reduced by the averaging process, but the accuracy is not statistically reduced. After freezing, it is basically possible to perform processing using all data to improve statistical accuracy, or to perform thinning or temporal and spatial averaging depending on the reproduction speed. Even if such processing is performed, time phase information such as time code is not deleted. When temporal averaging is performed, the time phase of the processed data is optimized for both real-time and cine-memory video playback. For example, when data is collected every 5 ms and data for 30 ms is averaged at the time of reproduction, a time phase corresponding to an intermediate frame between them is given as an average value.

  The pre-processing unit 61 has a function of sequentially processing elasticity information in units of frames. The pre-processing unit 61 excludes invalid data as invalid data when the elasticity information is not aligned for one frame. Also, the validity of the elasticity information is evaluated by, for example, evaluating whether or not the difference between the average elasticity value of the frame and the elasticity value of the pixel unit is larger than the set value, and using only data in a normal numerical range. I do. Also, singular points where the elasticity value of each pixel is out of the set range are removed by replacement with surrounding data or interpolation processing. When the information collected in these processes is invalid for some reason or replaced with appropriate data, warning display, warning sound output, etc. can be performed. In this case, the diagnostic evaluation value calculation control unit 69 receives the warning and instructs the display processing unit 68 to display the warning.

  The pre-processed elastic image frame data is sequentially input to the first ROI extraction unit 62 and the second ROI extraction unit 63. The first ROI and the second ROI are regions of interest for specifying two parts for obtaining the hardness ratio, and the panel unit 38 of FIG. 1 is provided via the interface (I / F) unit 70 and the diagnostic evaluation value calculation control unit 69. And input from the control unit 37. That is, as shown in FIG. 3, an elastic image and a tomographic image around the spleen are displayed on the display screen of the image display 26. In the example of FIG. 3, ROI1 is set at the position of the splenic vein inside the blood vessel and ROI2 is set at the position of the splenic parenchyma based on the command from the panel unit 38. The shape of the ROI is set in advance so as to cover an area of a size required for calculation by a template or the like, but the position can be designated by the command from the interface unit 70 and the size can be adjusted. Yes. Further, by processing the tomographic image shape to extract features, storing the first ROI and the second ROI, and creating a template, the setting operation of the ROI can be facilitated. The ROI is adjusted by manually inputting a variable by a trackball, a joystick, a keyboard input or the like installed on the panel unit 38, or by citing past examples.

  The first ROI extraction unit 62 extracts the elasticity value of each pixel included in the first ROI set in the splenic parenchyma from the elastic image frame data in response to the instruction of the diagnostic evaluation value calculation control unit 69, and calculates the average The value is output as the elasticity value of the first ROI. Similarly, the second ROI extracting unit 63 extracts the elasticity value of each pixel included in the second ROI set in the splenic vein and outputs the average value as the elasticity value of the second ROI.

The elastic values of the first ROI and the second ROI obtained in this way are output to the ratio calculation unit 64, where the spleen hardness ratio is obtained by the following equation (1).
Spleen hardness ratio = (elastic value of the first ROI) / (elastic value of the second ROI)
= (Elastic value of splenic parenchyma) / (elastic value of splenic vein) (1)
The obtained spleen hardness ratio is output to the diagnostic evaluation value calculation unit 65. In the diagnostic evaluation value calculation unit 65, a function representing a correlation between a preset hardness ratio between two specific parts and a diagnostic evaluation value for evaluating benign / malignant of the diagnostic part is stored in the form of an equation or a data table. Yes. In the case of the present embodiment, as shown in FIG. 4, a linear SEP score obtained by linearly approximating the correlation between the splenic hardness ratio and the portal vein pressure is stored. And the diagnostic evaluation value calculation part 65 calculates the portal vein pressure [mmHg] corresponding to the splenic hardness ratio output from the ratio calculation part 64 as a diagnostic evaluation value of cirrhosis based on the SEP score shown in FIG.

  The portal pressure of the diagnostic evaluation value calculated by the diagnostic evaluation value calculation unit 65 is stored in the storage unit 67 and then output to the elastic image forming unit 34 via the display processing unit 68. For example, the elastic image and the tomogram In addition to the composite image, the portal pressure is displayed numerically.

  As described above, according to the present embodiment, the portal pressure corresponding to the splenic hardness ratio obtained from the elastic image information can be accurately estimated based on the SEP score. Can be done appropriately. As a result, it is possible to realize a diagnostic method that is extremely effective in diagnosing cirrhosis, prognosis of disease state, and prediction of complications.

  In the present embodiment, the preprocessing unit 61 of FIG. 2 can be placed after the first ROI extraction unit and the second ROI extraction unit. As a result, the preprocessing needs to be performed only for a narrow ROI, so that the processing can be speeded up. The diagnostic evaluation value calculation control unit 69 controls 60 to 68 of the diagnostic evaluation value calculation unit 57. These controls are executed based on signals sent from 60 to 68. The diagnostic evaluation value calculation control unit 69 is controlled by the ultrasonic imaging apparatus 1 through the interface unit 70, and also displays information indicating the state. Control each other.

  Moreover, although the example which approximated the SEP score with the straight line was shown in this embodiment, this invention is not limited to this, It can approximate with a quadratic curve or a cubic curve. Furthermore, a certain width α may be provided in the approximate straight line or curve, and the diagnostic evaluation value may be attached with a value of ± α for output display. The inspector can also add an empirical rule as an interference term. The SEP score is preferably updated as clinical data increases.

  Although not described in the embodiment of FIG. 1, a biological signal measurement unit 47 that measures a biological signal of the subject 10 is provided, and a cardiac time phase is extracted based on an electrocardiogram waveform output from the biological signal measurement unit 47. Then, the cardiac phase can be recorded together in the elasticity information storage unit 60 of the diagnostic evaluation value calculation unit 57. As a result, when spleen and portal vein are observed with the same ultrasonic tomographic image and data of elastic image information is collected, pressurization by the heart beat can be used instead of manual compression. That is, when an elastic image moving image is recorded in the cine memory, the elapsed time from the electrocardiogram or the R wave of the electrocardiogram is added to the frame data and recorded. In recording time marks and the like, the position of the R wave is separately recorded so that the cardiac phase can be discriminated. In this case, the pre-processing unit 61 can extract only the time-phase elastic moving image suitable for diagnosis from the time-series elastic moving image. In addition, a plurality of images with different absolute times of the same cardiac time phase as candidates can be displayed in parallel so that the examiner can select them. Furthermore, by displaying the images corresponding to the cardiac time phases before and after each image together, it is possible to select the elastic image data for which the splenic hardness ratio is to be calculated for accuracy.

  In the embodiment of FIG. 1, real-time processing is shown as an example. However, the present invention is not limited to real-time processing. Elastic image data is stored in a cine memory or the like, and is processed by an information processing apparatus such as a personal computer or a workstation. Can be processed offline.

  In the above-described embodiment, one example is shown in which the ratio of the elastic values of two ROIs is obtained and the portal pressure is obtained based on the SEP score, but the present invention is not limited to this. For example, correlation data between liver stiffness ratio = (elastic value of liver parenchyma) / (elastic value of liver vein) and portal pressure, which is a diagnostic evaluation value of cirrhosis, is acquired invasively, and the correlation data Based on the above, the portal vein pressure corresponding to the liver hardness ratio obtained from the elastic image information can be obtained. However, in this case, since the correlation data between the liver hardness ratio and the portal pressure varies, it is preferable to back check the portal pressure obtained based on the SEP score. However, if a technique for correcting correlation data between the liver hardness ratio and portal pressure is developed in the future, portal pressure can be evaluated instead of the SEP score.

DESCRIPTION OF SYMBOLS 1 Ultrasonic image apparatus 10 Subject 12 Ultrasonic probe 14 Transmission part 16 Reception part 17 Transmission / reception control part 18 Phased addition part 20 Tomographic image structure part 22 Black-and-white scan converter 24 Display image control part 26 Image display device 28 RF signal Frame data selection unit 30 Displacement measurement unit 32 Elastic information calculation unit 34 Elastic image configuration unit 36 Color scan converter 37 Control unit 38 Panel unit 47 Biosignal measurement unit 57 Diagnostic evaluation value calculation unit 60 Elastic information storage unit 61 Preprocessing unit 62 First 1 ROI extraction unit 63 2nd ROI extraction unit 64 Ratio calculation unit 65 Diagnostic evaluation value calculation unit 67 Storage unit 68 Display processing unit 69 Diagnostic evaluation value calculation control unit

Claims (6)

An elastic information calculation unit that calculates elastic image information based on tomographic image information of a diagnostic region of a subject imaged in time series;
Based on the elasticity image information, a hardness ratio calculation unit for obtaining a hardness ratio that is a ratio of the elasticity value of the first part and the elasticity value of the second part set in the diagnostic part;
A diagnostic evaluation value calculation unit that calculates a diagnostic evaluation value corresponding to the hardness ratio obtained by the hardness ratio calculation unit based on a correlation between the hardness ratio set in advance and the diagnostic evaluation value;
A medical image apparatus comprising an image display unit that displays an elastic image created based on the elastic image information and the diagnostic evaluation value obtained by the diagnostic evaluation value calculation unit. The first site is set in the parenchyma of the spleen, the second site is set in the portal vein of the spleen;
The medical imaging apparatus according to claim 1, wherein the hardness ratio is a splenic hardness ratio, and the diagnostic evaluation value is a portal vein pressure of the liver. The first part is set in the parenchyma of the liver, the second part is set in the hepatic vein of the liver;
The medical image apparatus according to claim 1, wherein the hardness ratio is a liver hardness ratio, and the diagnostic evaluation value is a portal vein pressure of the liver. An elastic information calculation unit that calculates elastic image information based on tomographic image information of a diagnostic region of a subject imaged in time series;
Based on the elasticity image information, the splenic hardness ratio, which is the ratio of the elasticity value of the spleen and the portal vein of the spleen set at the diagnosis site, and the elasticity value of the liver and the liver of the liver A hardness ratio calculator for obtaining a liver hardness ratio, which is a ratio to the elasticity value of the vein,
The first diagnostic evaluation value corresponding to the splenic hardness ratio and the second diagnostic evaluation value corresponding to the liver hardness ratio obtained by the hardness ratio calculation unit are respectively set to the preset splenic hardness ratio and the first diagnostic evaluation value. A diagnostic evaluation value calculation unit that calculates the diagnostic evaluation value based on the correlation between the diagnostic evaluation value and the liver hardness ratio and the second diagnostic evaluation value;
A medical image comprising an elastic image created based on the elastic image information, and an image display unit for displaying the first diagnostic evaluation value and the second diagnostic evaluation value obtained by the diagnostic evaluation value calculation unit apparatus.   The medical image apparatus according to any one of claims 1 to 4, wherein the tomographic image information of the diagnostic region of the subject is imaged by an ultrasonic imaging apparatus.   The medical imaging apparatus according to any one of claims 1 to 4, wherein the tomographic image information of the diagnostic region of the subject is captured by a magnetic resonance imaging apparatus.

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