JP4804039B2 - Blood flow dynamic analysis apparatus, X-ray CT apparatus, MRI apparatus, and blood flow dynamic analysis program - Google Patents

Description

  The present invention relates to a blood flow dynamic analysis apparatus, an X-ray CT apparatus, an MRI apparatus, and a blood flow dynamic analysis program, and in particular, it is possible to obtain biological function information depending on time changes of a subject using X-rays and electromagnetic waves. The present invention relates to a technique useful for performing image analysis such as biological function information analysis from a tomographic image provided by a computer tomographic diagnosis apparatus.

  Conventionally, there have been nuclear medicine apparatuses such as a positron emission tomography (PET) and a single photon emission CT (SPECT) as a computer tomography diagnostic apparatus for performing dynamic imaging. In the measurement of blood flow with a nuclear medicine device, radionuclide is injected into a subject, and when the radiation from the nuclide is measured with a scintillation camera, a radionuclide distribution image of the cross section can be obtained, and this radionuclide distribution image is analyzed. Therefore, the biological function information of the organ was analyzed.

  In addition, there was an X-ray CT apparatus as a computer tomography diagnosis apparatus for performing dynamic imaging. When it is difficult to diagnose the ultra-early phase of a lesion with simple X-ray CT images, dynamic imaging using an X-ray CT system mainly uses an iodine-based contrast agent. When a contrast agent is injected and a dynamic scan is performed, the contrast agent concentration and the CT value are in a proportional relationship, and thus information on the temporal change of the imaging section can be obtained. The time-concentration curve, which is the time change of the CT value of each tissue, was obtained from the time change of the imaging section, and the biological function information of the organ was analyzed by analyzing the time-concentration curve.

  In addition, there is an MR apparatus as a computer tomography diagnosis apparatus for performing another dynamic imaging. Although there is a non-contrast diagnostic method in the high magnetic field MR apparatus, a gadolinium-based contrast agent is mainly used in the case of obtaining a high-contrast image with the high magnetic field MR apparatus or in the low magnetic field MR apparatus. Also in the MR apparatus, a time-density curve which is a relative signal intensity change rate of the MR value of each tissue is obtained from the time change of the imaging cross section. By analyzing this time-concentration curve, biological function information depending on the temporal change of the organ was analyzed.

  As an algorithm for analyzing blood flow dynamics, there is a first-moment method (gamma fitting method). In the first-moment method, a first circulation component is extracted by fitting a time-concentration curve with a gamma function or the like, and blood flow information is calculated from the peak value of the fitting curve and the area under the curve.

  There was a maximum slope method (maximum slope method) as an algorithm for analyzing other blood flow dynamics. In the maximum gradient method, the blood flow rate was calculated by dividing the maximum value of the slope of the time-concentration curve in each tissue by the maximum value of the increase in CT value of the time-concentration curve in the artery.

  There was a deconvolution method as an algorithm for analyzing other blood flow dynamics. In the deconvolution method, a transfer function is obtained by deconvolution calculation of a time-concentration curve (arterial input function) in an artery and a time-concentration curve (tissue output function) in each tissue, and blood flow information is obtained from the transfer function. It was calculated. Compared to other methods, the Deconvolution method has advantages in terms of quantitativeness and contrast agent injection speed, and is the most popular algorithm in recent years.

  In the deconvolution method, the reliability of the analysis result changes depending on how the arterial input function is appropriately set. Ideally, the arterial input function should be set for each capillary network, in other words, for each pixel.

  However, it is difficult to specify the inflow route of blood flow for all capillary networks. Therefore, the main trunk artery such as the anterior cerebral artery and middle cerebral artery on the healthy side is usually analyzed as an arterial input function for all pixels. In this specification, this method is referred to as Conventional Method 1.

  As another arterial input function setting method, as disclosed in Patent Document 1, right anterior cerebral artery, left anterior cerebral artery, right middle cerebral artery, left middle cerebral artery, right posterior cerebral artery, left posterior cerebral artery, 6 main arteries are set as arterial input functions, and a pixel in each blood flow control region is selected and analyzed from the six main arteries most suitable for the blood flow control region (this specification) Then, “conventional method 2”).

Further, the blood flow dynamic analysis device of Patent Document 2 performs Fourier transform on the time-concentration curve of the inflow artery and each tissue based on the input tomographic image, and calculates an inverse filter therefrom. This inverse filter is multiplied by the Fourier transform of the time-concentration curve in each tissue to obtain the transfer function of each tissue, and the biological function information is calculated using this transfer function.
JP 2003-190148 A JP 2004-97665 A

  The present inventor has found the following problems as a result of studying the above prior art. According to Non-Patent Document 1 (INNERVISION (19.1) 2004), if all the arterial input functions are represented by one main trunk artery on the healthy side, the ischemic state on the disease side tends to be overestimated. This is representative of the arterial input function for all pixels in the main trunk artery on the healthy side, so without considering the effect of tracer arrival time (Delay) and time-density curve shape dispersion (Dispersion) It is because it is analyzing. Therefore, the conventional method 1 has a problem of overestimating the ischemic state on the disease side.

  In the conventional method 2, since the arterial input function is set for each blood flow control region, the problem of overestimating the ischemic state is improved to some extent as compared with the conventional method. However, in the conventional method 2, as compared with the conventional method 1, only the range of the region to be analyzed by being represented by one main trunk artery is reduced, and it is not set for each pixel. That is, the influence of Delay and Dispersion is not corrected for each pixel. Accordingly, although the degree of overestimation of the ischemic state is improved, there is a problem that the overestimation cannot be completely corrected. In addition, since a total of six arteries must be set for the arterial input function, there is a problem that the labor and burden on the operator is greater than in the conventional method 1 in which only one is required. In addition, since it takes a lot of time to specify six arteries, there is also a problem that it is not suitable for a test requiring quickness such as acute cerebral infarction.

  The object of the present invention is to analyze the ischemic state caused by Delay and Dispersion without increasing the burden on the operator and spending time when setting the arterial input function in the hemodynamic analysis represented by CT Perfusion and MR Perfusion. An object of the present invention is to provide a blood flow dynamic analysis device that can correct overestimation of the blood flow.

In order to solve the above problem, a blood flow dynamic analysis device according to the present invention includes a setting unit that sets an inflow artery included in a tomographic image of a subject injected with a contrast agent photographed by a medical image photographing device, Computation means for obtaining a time-concentration curve representing pixel value temporal change information for each pixel based on a tomographic image, the time-density representing time variation information of pixel values of pixels constituting the inflow artery A calculation means for obtaining an arterial input function that is a curve and an output function that is a time-concentration curve at each pixel of interest; a blood flow arrival time at the arterial input function and a blood flow arrival at each output function for each pixel of interest time difference time, and to correct at least one of shape raw Ri, of the arterial input function, and calculates a correction parameter used in the calculation of the arterial input function corresponding to each pixel of interest A positive parameter calculating means, the correcting the arterial input function using the correction parameter, and correcting means for determining an arterial input function of corrected for each of the pixel of interest, and each output function, the output function determined Based on the corrected arterial input function corresponding to the target pixel , transfer function calculating means for obtaining a transfer function for each target pixel, and functional information for calculating biological function information based on the respective transfer functions And a calculating means.

The "shape rounding of the arterial input function" occurs at the stage the operator will blood flow flows to the pixel of interest from the Arterial configured as arterial input function number (inflow artery) Time - the shape of the concentration curve It means change.

  Further, the correction parameter calculation means calculates a correction parameter based on the arterial input function, a time-concentration curve of pixels constituting the peripheral tissue of the inflow artery, and the output function. .

  The correction parameter calculation means calculates a correction parameter from various coefficients in a gamma function type fitting curve for each time-concentration curve.

  Further, the correction parameter calculation means calculates a correction parameter based on the half-value width, peak value, and blood flow arrival time of each time-concentration curve.

  The setting unit divides the tomographic image into a plurality of regions, sets an inflow artery for each region, the calculation unit obtains an arterial input function for each inflow artery, and the correction parameter unit includes: A correction parameter is calculated based on the arterial input function obtained for each region and the output function of each pixel of interest included in the region including the inflow artery corresponding to the arterial input function.

In addition, an X-ray CT apparatus according to the present invention is disposed so as to face an X-ray tube that irradiates a subject injected with a contrast agent with an X-ray, and the X-ray tube is placed opposite to the subject. An X-ray detector that detects X-rays that have passed through the specimen and outputs X-ray transmission data, a rotating means that can be rotated by mounting the X-ray source and the X-ray detector, and the X-ray transmission data An X-ray CT apparatus comprising: an image processing device that performs reconstruction calculation processing based on the image processing device to generate a tomographic image; and a display device for displaying the tomographic image. At least one inflow artery included in the tomographic image And a calculation means for obtaining a time-concentration curve representing information on a temporal change of the pixel value for each pixel based on the tomographic image, the time of the pixel value of the pixels constituting the inflow artery Arterial input function that is a time-concentration curve representing change information , The time of each pixel of interest - a calculating means for determining an output function that is a density curve for each pixel of interest, the time difference between the blood flow arrival time in bloodstream arrival time and the respective output function in the arterial input function, and the Ri raw shape of the arterial input function, in order to correct at least one of a correction parameter calculating means for calculating a correction parameter used in the calculation of the arterial input function corresponding to each pixel of interest, the correction parameter Correcting the arterial input function using a correction means for obtaining a corrected arterial input function for each pixel of interest;
Transfer function calculating means for determining a transfer function for each pixel of interest based on each output function and the corrected arterial input function corresponding to the pixel of interest for which the output function was obtained; Functional information calculation means for calculating biological function information using a function, and displaying a biological function image based on the biological function information on the display device.

The MRI apparatus according to the present invention receives a magnetic resonance signal generated from the subject by executing an imaging sequence in which a static magnetic field, a high frequency pulse, and a gradient magnetic field are applied to the subject injected with a contrast agent, An MRI apparatus for generating and displaying a tomographic image based on the received magnetic resonance signal, wherein the high-frequency pulse and the gradient magnetic field are applied based on the cross-sectional position of the subject output from the cross-sectional position output means. In an MRI apparatus for controlling and generating and displaying a tomographic image of the cross-sectional position, setting means for setting at least one inflow artery included in the tomographic image, and a pixel value for each pixel based on the tomographic image Computation means for obtaining a time-concentration curve representing time change information, wherein an arterial input function which is a time-concentration curve representing time change information of pixel values of pixels constituting the inflow artery is obtained. With time at each pixel of interest - a calculating means for determining an output function that is a density curve for each pixel of interest, the time difference between the blood flow arrival time in bloodstream arrival time and the respective output function in the arterial input function, and to correct at least one of shape raw Ri, of the arterial input function, the correction parameter calculating means for calculating a correction parameter used in the calculation of the arterial input function corresponding to each pixel of interest, the correction Correction means for correcting the arterial input function using parameters and obtaining a corrected arterial input function for each pixel of interest , the output functions, and the correction corresponding to the pixel of interest for which the output function was obtained to calculate an arterial input function, the transfer function calculating means for calculating a transfer function for each of the respective target pixel on the basis of the biological function information based on the transfer functions after A function information obtaining means, characterized by comprising display means for displaying the biological function image, the based on the biological function information.

Further, the blood flow dynamic analysis program according to the present invention includes a step of reading imaging data obtained by imaging a subject injected with a contrast agent by a medical imaging apparatus, and a tomogram generated based on the read imaging data A step of accepting a setting of an inflow artery included in an image, and a step of obtaining a time-density curve representing information on a temporal change of a pixel value for each pixel based on the tomographic image, wherein the pixels constituting the inflow artery Obtaining an arterial input function that is a time-density curve representing information on temporal change of the pixel value of each pixel, and obtaining an output function that is a time-density curve for each pixel of interest, and for each pixel of interest, the arterial input function the time difference between the blood flow arrival time in bloodstream arrival time and the respective output function in, and Ri raw shape of the arterial input function was to correct at least one of In the step of calculating a correction parameter used in the calculation of the arterial input function corresponding to each pixel of interest, the correction parameter to correct the arterial input function using the arterial input function after correction for each of the pixel of interest Determining a transfer function for each pixel of interest based on the output function and the corrected arterial input function corresponding to the pixel of interest for which the output function was determined ; And calculating the biological function information based on each transfer function.

  According to the present invention, in blood flow dynamic analysis, there is an effect that quantitative effects can be improved by removing the influence of delay and dispersion without increasing the labor and burden on the operator.

  Hereinafter, preferred embodiments of an image processing apparatus according to the present invention will be described in detail with reference to the accompanying drawings.

<First embodiment>
FIG. 1 is a schematic configuration diagram showing an X-ray CT apparatus to which a blood flow dynamic analysis apparatus according to the present invention is applied.

  The X-ray CT apparatus 1 includes a scanner 10, a bed 12, a top plate 14 of the bed 12, an image processing device (operation console) 20, a monitor 25 as a display device, and a keyboard 28 as an operation device.

  Although not shown, the scanner 10 includes an X-ray tube in which X-rays are controlled by an X-ray tube controller. X-rays radiated from the X-ray tube are converted into, for example, a pyramid-shaped X-ray beam, that is, a cone beam X-ray, by a collimator controlled by a collimator control device, and irradiated on a subject. X-rays transmitted through the subject enter the X-ray detector.

The X-ray detector includes a plurality of X-ray detection elements that are two-dimensionally arranged in a channel direction and a column direction. A data acquisition device is connected to the X-ray detector. The data collection device collects detection data of individual X-ray detection elements of the X-ray detector.
The image processing apparatus 17 is formed integrally with the console 13 of the X-ray CT apparatus, but may be an external computer.

  Next, the hardware configuration of the image processing apparatus 20 will be described with reference to FIG.

  The image processing apparatus 20 includes a central processing unit (CPU) 21, a temporary storage of an image to be displayed on the monitor 25, a temporary development of an image for calculation, and a memory 22 that is a work area at the time of program execution, A magnetic disk 23 that stores a plurality of images, and stores an operating system (OS), various software including the misregistration correction processing program, a display memory 24 that temporarily stores display image data, A monitor 25 as a display device, a mouse 26 which is one of operation means and is a position coordinate designation means, a controller 27 of the mouse 26, a keyboard 28, and a bus 29 for connecting the above components. Prepare. Instead of the CPU, a digital signal processor (DSP) or a microprocessor unit (MPU) may be provided. The monitor 25 may be integrated with the console of the X-ray CT apparatus 1 or may be configured independently.

  The image processing apparatus 20 corrects the arterial input function for each pixel to be analyzed (hereinafter referred to as “target pixel”), and corrects the arterial input function and a time-density curve (hereinafter referred to as “output function”) for each pixel. The blood flow dynamics analysis program for obtaining a biofunction information image for each target pixel based on the transfer function and generating a biofunction information image is installed.

FIG. 3 is a block diagram showing functions of the blood flow dynamic analysis program.
The CPU 21 executes an image data reading unit 21a, an artery setting unit 21b, a calculation unit 21c, a correction parameter calculation unit 21d, a correction unit 21f, a transfer function calculation unit 21g, a function information calculation unit 21h, and an image generation unit 21i which are programs. . These programs are stored in the magnetic disk 23, and are appropriately read by the CPU 21 to the memory 22 and executed.

  The image data reading unit 21a reads image data indicating a tomographic image to be subjected to blood flow dynamic analysis. The image data may be directly read from the X-ray CT apparatus 1 or a magnetic resonance imaging apparatus (hereinafter referred to as “MRI apparatus”) 80 described later, or medical images such as the X-ray CT apparatus 1 or the MRI apparatus 80 described later. You may read from the image database which stored the image data which the imaging device produced | generated.

  The arterial setting unit 21b sets the main artery (inflow artery) used as the original arterial input function, displays a tomographic image on the monitor 25, and the operator clicks the position of the main artery with the mouse 26 and designates it. Then, the main artery is set by detecting the designated position coordinates. The main trunk artery may be set automatically.

  The computing unit 21c calculates a time-density curve for each pixel. The time-density curve calculated by the calculation unit 21c based on the pixels included in the main artery region is referred to as “arterial input function”. A time-density curve calculated for each pixel included in each tissue other than the main artery is called an “output function”.

  The correction parameter calculation unit 21d calculates a parameter for correcting the original arterial input function designated by the operator. A method for calculating the correction parameter will be described later.

  The correcting unit 21f corrects the original arterial input function based on the correction parameter.

  The transfer function calculating unit 21g obtains a transfer function based on the arterial input function corrected for each pixel and the time-density curve of the pixel.

  The function information calculation unit 21h calculates biological function information from the transfer function.

The image generation unit 21i maps the biological function information generated by the function information calculation unit 21h to the coordinate position corresponding to the pixel, and generates a function image.
<Process flow>
FIG. 4 is a flowchart showing a flow of processing from data reading to display of an output image in the embodiment of the blood flow dynamic analysis apparatus according to the present invention.

  In step S401, the image data reading unit 21a reads an image to be processed and stores it in the memory 22 (S401). At this time, an image already stored in an image database connected via the magnetic disk 23 or a network (not shown) may be read, or digital image data newly collected by the X-ray CT apparatus 1 or an MRI apparatus 81 described later. May be read.

  In step S402, the image processing apparatus 21 deletes an area unnecessary for analysis of biological function information such as bones, a bed, room air, and the like reflected in the CT image and the MR image (S402). The method for deleting the unnecessary area is a method disclosed in Patent Document 2, specifically, binarization processing that separates the unnecessary area from the necessary area is performed on the original image, and the binarized image is contoured. The process can be performed by extracting a line and painting the inside of the outline with 1 to generate a mask image. Although step S402 can be omitted, it is desirable to execute step S402 in order to shorten the calculation time.

  In step S403, the image processing apparatus 21 performs noise removal processing using an image filter (S403). A known smoothing filter may be used as the image filter, but a filter capable of removing noise maintaining the resolution as disclosed by the inventors in Japanese Patent Application No. 2004-148690 and RSNA2004 (infoRad 9414). It is desirable to use it. Although step S403 can be omitted, it is desirable to execute step S403 in order to improve the analysis accuracy.

  In step S404, a time-density curve for each pixel is calculated (step S404). The computing unit 21c calculates a time-density curve for each pixel. The time-density curve is obtained by extracting the pixel value in each time phase for each pixel.

  In step S405, the image processing device 21 extracts the first circulation component from the time-density curve (step S405). The method for extracting the first circulation component may be a known method such as fitting by a gamma function or extrapolation by an exponential function.

  In step S406, the artery used for the artery input function is set using the artery setting unit 21b (step S406). At this time, it is desirable to set a vein used for correction of the Partial Volume Averaging (PVA) effect. As a method for setting an artery or vein, a manual setting method such as setting an ROI (region of interest) on an image using the input unit 11 may be used, as disclosed in JP-A-2004-97665. A method of automatic setting, specifically, calculating the central pixel of the inflow artery and inflow vein, and separating the pixels whose peak value is greater than or equal to the threshold from the pixels around the central pixel and the peak value A method of automatically determining an inflow artery and an outflow artery by extracting a connected pixel including a center pixel among pixels having a threshold value equal to or greater than a threshold value may be used. Note that the timing of executing step S406 is not limited to the position shown in FIG. 1, and may be executed at any time as long as it is a position after step S401 and before step S407.

In step S407, the PVA effect is corrected (step S407). The correction method for the PVA effect is a technique disclosed in Japanese Patent Application Laid-Open No. 2004-97665. Specifically, the peak value of the inflow artery is Pa, the peak value of the outflow vein is Pv, and the time-concentration curve of the inflow artery. May be used to correct the PVA effect in the inflow artery by multiplying Pv / Pa. Although step S407 can be omitted, it is desirable to execute step S407 in order to improve quantitativeness. Further, the timing of executing step S407 is not limited to the position shown in FIG. 1, and may be executed at any time as long as it is a position after step 206 and before step S411.

  In step S408, the parameters for correcting the delay and dispersion of the arterial input function are calculated using the correction parameter calculation unit 21d (step S408).

  In step S409, the arterial input function is corrected using the correction unit 21f (step S409). The correction parameter calculation method and correction method will be described later.

  In step S410, the transfer function calculation unit 21g calculates a transfer function from the corrected arterial input function obtained in step S409 and the time-concentration curve in each tissue after the first circulation component extraction obtained in step S405. (Step S410). As a method of calculating the transfer function, a method of performing a deconvolution operation on the time-concentration curve in the inflow artery and the time-concentration curve in the tissue disclosed in JP-A-2004-97665 may be used.

  In step S411, the function information calculation unit 21h calculates blood flow information such as blood flow volume, blood volume, and average transit time from the transfer function calculated in step S410, that is, a biological function information value (step S411). A method for calculating blood flow information from a transfer function is a method disclosed in Japanese Patent Application Laid-Open No. 2004-97665. Specifically, the blood flow is obtained from the maximum value of the transfer function, and the blood volume is obtained from the area under the curve of the transfer function. The average transit time may be obtained from a transfer function width, or a known method may be used.

  The processing from step S408 to step S411 is executed for each pixel with respect to all the pixels in the organ to be analyzed.

  In step S412, the function information value in each pixel calculated by the image generation unit 21i is mapped to obtain a function image (step S412). Each process from step S403 to step S412 may be executed for all the pixels in the image. However, in order to shorten the calculation time, the unnecessary area removed in step S402 is excluded and the analysis target organ area is excluded. It is desirable to execute each process only on the pixels within.

  In step S413, the function image created in step S412 is displayed on the monitor 25 (step S413).

  In step S414, a functional image is stored in the magnetic disk 23 as necessary (step S414). If it is not necessary to save the functional image, step S414 may be omitted. Further, step S414 may be executed before step S413.

<First Correction Parameter Calculation Method and Correction Method>
Next, a correction parameter calculation method and correction method will be described. FIG. 5 is a schematic diagram showing a correction parameter calculation method and a correction method 1.
A tomographic image 500 for which a functional image is to be created is displayed on the monitor 25. The operator designates one place in the tomographic image 500 as a place for creating the original arterial input function. In FIG. 5, it is assumed that the operator designates a point 501 on the tomographic image 500 by using an input means such as a mouse 27 or a trackball.

  The computing unit 21c calculates a time-concentration curve at the point 501 and generates an arterial input function AIForg (t). 510 in FIG. 5 shows a graph and an expression of the arterial input function AIForg (t). Further, the calculation unit 21c generates a time-density curve TDC1 (t) for the pixels around the artery and a time-density curve TDC2 (t) for the pixel of interest. Reference numerals 520 and 530 in FIG. 5 show a time-density curve TDC1 (t) for a pixel around an artery and a time-density curve TDC2 (t) for a pixel of interest and a formula. The time-concentration curve can be approximated by a gamma function as follows:

  Here, the correction parameter calculation unit 21d calculates the correction parameter 540 by comparing each coefficient in TDC1 and TDC2. Then, the correction unit 21f corrects the arterial input function AIForg (t) using the correction parameter 540 as follows, and determines the arterial input function AIFcor (t) for the target pixel. Reference numeral 550 in FIG. 5 represents a graph and an expression of the arterial input function AIFcor (t) for the pixel of interest.

数２式に従って1画素ごとに決定したAIFcor(t)を用いて伝達関数の算出を行うことにより、操作者の手間や負担を増やすことなくDelayおよびDispersionの影響を補正可能である。

By calculating the transfer function using AIFcor (t) determined for each pixel according to Equation 2, the influence of Delay and Dispersion can be corrected without increasing the labor and burden on the operator.

<Second Correction Parameter Calculation Method and Correction Method>
FIG. 6 is a schematic diagram showing a second correction parameter calculation method and correction method.

  Similar to FIG. 5, FIG. 6 shows a tomographic image 600, a reference point 601 for generating an arterial input function designated by the operator, and a reference point 601 for an arterial input function designated by the operator, and 610 shows an arterial input function which is a time-concentration curve of the point 601 designated by the operator. The graph and formula of (t) are shown. Further, reference numerals 620 and 630 in FIG. 6 show a graph and an expression of a time-density curve TDC1 (t) in a pixel around an artery and a time-density curve TDC2 (t) in a pixel of interest. In addition, the full width at half maximum and peak value of the time-concentration curve TDC1 (t) in the pixels around the artery, the arrival times are W1, H1, AT1, respectively, the full width at half maximum and peak value of the time-density curve TDC2 (t) in the target pixel, The arrival times are W2, H2, and AT2, respectively. AIForg (t) can be approximated by a gamma function as shown in equation (1). 550 calculates a correction parameter 540 from the comparison of the full width at half maximum, the peak value, and the arrival time, and the correction unit 21f corrects AIForg (t) as shown in Equation 3 to obtain an arterial input function AIFcor ( t) is determined.

数３式に従って1画素ごとに決定したAIFcor(t)を用いて伝達関数の算出を行うことにより、操作者の手間や負担を増やすことなくDelayおよびDispersionの影響を補正可能である。第二の補正方法（図６参照）では、操作が設定した動脈入力関数に対してのみガンマ関数によるフィッテングを行い、動脈周辺の画素における時間-濃度曲線や注目画素における時間-濃度曲線に対してはフィッテングを行わないため、第一の補正方法（図５参照）に比べて短時間でDelayおよびDispersionの影響を補正可能である。

By calculating the transfer function using AIFcor (t) determined for each pixel according to the equation (3), it is possible to correct the effects of delay and dispersion without increasing the labor and burden on the operator. In the second correction method (see FIG. 6), only the arterial input function set by the operation is fitted by the gamma function, and the time-density curve at the pixel around the artery and the time-density curve at the target pixel are corrected. Since no fitting is performed, the influence of delay and dispersion can be corrected in a shorter time than the first correction method (see FIG. 5).

<Third Correction Parameter Calculation Method and Correction Method>
FIG. 7 is a schematic diagram showing a third correction parameter calculation method and correction method.

  As in FIG. 5, FIG. 7 is a tomogram 700, a reference point for generating an arterial input function designated by the operator is a point 701, and 710 is an arterial input function that is a time-concentration curve of the point 701 designated by the operator. The graph and formula of (t) are shown. Further, reference numerals 720 and 730 in FIG. 7 show graphs and expressions of a time-density curve TDC1 (t) in a pixel around an artery and a time-density curve TDC2 (t) in a pixel of interest. In addition, the full width at half maximum and peak value of the time-concentration curve TDC1 (t) in the pixels around the artery, the arrival times are W1, H1, AT1, respectively, the full width at half maximum and peak value of the time-density curve TDC2 (t) in the target pixel, The arrival times are W2, H2, and AT2, respectively. When curve fitting is not performed, AIForg (t) is expressed as discrete data such as the following equation.

半値全幅とピーク値、到達時間の比較から補正パラメータ７４０を求め、この補正パラメータ７４０に基づいてAIForg(t)を次式のように補正し、補正後の注目画素に対する動脈入力関数AIFcor(t)を決定する。７５０は、補正後の動脈入力関数を示す。

A correction parameter 740 is obtained from the comparison between the full width at half maximum, the peak value, and the arrival time, and AIForg (t) is corrected based on the correction parameter 740 as shown in the following equation, and the arterial input function AIFcor (t) for the corrected pixel of interest To decide. Reference numeral 750 denotes a corrected arterial input function.

数５式に従って1画素ごとに決定したAIFcor(t)を用いて伝達関数の算出を行うことにより、操作者の手間や負担を増やすことなくDelayおよびDispersionの影響を補正可能である。第三の補正方法では、ガンマ関数によるフィッテングをまったく行わないため、第二の補正方法よりもさらに短時間でDelayおよびDispersionの影響を補正可能である。

By calculating the transfer function using AIFcor (t) determined for each pixel in accordance with Equation 5, it is possible to correct the effects of delay and dispersion without increasing the operator's effort and burden. In the third correction method, since fitting by a gamma function is not performed at all, the influence of Delay and Dispersion can be corrected in a shorter time than the second correction method.

<Second embodiment>
FIG. 8 is a schematic diagram showing an overall configuration showing an embodiment of an MRI apparatus according to the present invention.

  An MRI apparatus 80 shown in FIG. 8 is, for example, a vertical magnetic field type 0.3T permanent magnet MRI apparatus, which connects an upper magnet 81 and a lower magnet 82 that generate a vertical static magnetic field, and connects the upper magnet 81 to the upper magnet 81. It includes a supporting column 83, a control unit 84, and the like. A gradient magnetic field generator (not shown) of the MRI apparatus 1 generates a gradient magnetic field in a pulse manner, has a maximum gradient magnetic field strength of 15 mT / m and a slew rate of 20 mT / m / ms. Furthermore, the MRI apparatus 1 includes an RF transmitter (not shown) for generating nuclear magnetic resonance in the subject 85 in a static magnetic field, and an RF receiver (not shown) for receiving a nuclear magnetic resonance signal from the subject 85. Consists of a 12.8 MHz resonant coil.

  The control unit 84 is configured by a workstation and controls a gradient magnetic field generation unit, an RF transmitter, an RF receiver, and the like.

The monitor 95 displays an image of the tomographic plane of the subject 85.
The control unit 84 is connected to the image processing apparatus 90. The image processing apparatus 90 receives the magnetic resonance signal of the subject 85 from the control unit 84, generates a tomographic image based on the magnetic resonance signal, and displays it on the monitor 95.

  As in the first embodiment, the image processing apparatus 90 includes the CPU, memory, magnetic disk, display memory, monitor 95, mouse 97, controller, keyboard, and bus shown in FIG. Further, the image processing apparatus 90 stores a blood flow dynamic analysis program shown in FIG. The CPU of the image processing apparatus 90 includes an image data reading unit 21a, an artery setting unit 21b, a calculation unit 21c, a correction parameter calculation unit 21d, a correction unit 21f, a transfer function calculation unit 21g, a function information calculation unit 21h, and an image generation program. The unit 21i is executed. These programs are stored in the magnetic disk 23, and are appropriately read by the CPU 21 to the memory 22 and executed. The processing flow of these programs and the calculation method of correction parameters are the same as in the first embodiment.

<Third embodiment>
In the above embodiment, only one main artery is set, but the analysis target area in the tomogram may be divided into a plurality of areas, and the main artery may be set for each of the divided areas. FIG. 9 is a schematic diagram showing the setting of the main artery according to the third embodiment. The head tomogram of the subject is divided into two regions on the left and right along the dotted line, and the main artery is divided into each divided region. It is a figure which shows the set state.

  In FIG. 9, the left area is indicated by a left oblique line. Similarly, the right area is indicated by a right diagonal line.

  The operator designates one main artery 100 included in the left region. Similarly, the operator designates one main artery 110 included in the right region. The image processing apparatus obtains an arterial input function based on the main arteries 100 and 110, respectively. Then, for each pixel included in the left region, a corrected arterial input function obtained by correcting the arterial input function of the main artery 100 is calculated. Then, a transfer function is calculated based on the output function for each pixel included in the left region and the corrected arterial input function obtained by correcting the arterial input function of the main artery 100.

  Similarly, a corrected arterial input function obtained by correcting the arterial input function of the main artery 110 is calculated for each pixel included in the right region. Then, a transfer function is calculated based on the output function for each pixel included in the right region and the corrected arterial input function obtained by correcting the arterial input function of the main artery 110.

  Functional information is calculated using these transfer functions, and a functional image is generated.

  According to the present embodiment, the arterial input function in each pixel can be obtained with higher accuracy.

Schematic configuration diagram showing an X-ray CT apparatus to which the present invention is applied Block diagram showing hardware configuration of image processing apparatus Functional block diagram of hemodynamic analysis program Flowchart showing the flow of processing of the first embodiment Schematic diagram showing a first correction parameter calculation method and correction method 1 Schematic diagram showing calculation method and correction method of second correction parameter Schematic diagram showing third correction parameter calculation method and correction method Schematic configuration diagram of an MRI apparatus to which the present invention is applied Schematic diagram showing the setting of the main artery according to the third embodiment

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 ... X-ray CT apparatus, 10 ... Scanner, 12 ... Bed, 14 ... Top plate, 20 ... Image processing apparatus, 25 ... Monitor, 28 ... Keyboard, 80 ... MRI apparatus, 81 ... Upper magnet 81, 82 ... Lower magnet, 83 ... Stand, 84 ... Control unit, 85 ... Subject, 90 ... Image processing device, 95 ... Monitor, 97 ... Mouse

Claims (8)

A setting means for setting an inflow artery included in a tomographic image of a subject injected with a contrast agent photographed by a medical image photographing device;
The tomographic image time represents information of a temporal change in the pixel values for each pixel on the basis of - a computing means for determining the density curve, the time representing the information of a temporal change in the pixel values of the pixels constituting the inflow artery - and arterial input function is the concentration curve, time of the pixel near the inflow artery - and concentration curve, time in each pixel of interest - a calculating means for calculating an output function, which is the concentration curve,
The time difference between the blood flow arrival time in bloodstream arrival time and the respective output function before Symbol arterial input function, and for correcting at least one of a shape accent, the arterial input function in each pixel of interest, A correction parameter used for calculating the arterial input function corresponding to each pixel of interest is calculated based on a time-density curve of pixels around the inflow artery and an output function corresponding to each pixel of interest. A calculation means;
Correction means for correcting the arterial input function using a correction parameter corresponding to each pixel of interest, and obtaining a corrected arterial input function corresponding to each pixel of interest ;
Transfer function calculating means for obtaining a transfer function for each pixel of interest based on each output function and the corrected arterial input function corresponding to the pixel of interest for which the output function was obtained;
Function information calculating means for calculating biological function information based on each of the transfer functions;
An apparatus for analyzing blood flow dynamics. The correction parameter calculation means calculates the correction parameter using a coefficient of a time-concentration curve of a pixel around the inflow artery that has been fitted with a gamma function and a coefficient of the output function that has been fitted with a gamma function .
The blood flow dynamic analysis apparatus according to claim 1. The correction parameter calculation means calculates the correction parameter using a time-concentration curve of pixels around the inflow artery, a half width of the output function, a peak value, and a blood flow arrival time .
The blood flow dynamic analysis apparatus according to claim 1. The correction parameter calculation means includes a half-value width, a peak value, and a blood flow arrival time of pixels around the inflow artery made of discrete data , and a half-value width, a peak value of the output function made of discrete data , and blood flow arrival time, and calculates the correction parameters using,
The correction means corrects the arterial input function composed of discrete data using the calculated correction parameter, and obtains a corrected arterial input function corresponding to each pixel of interest.
The blood flow dynamics analysis device according to claim 3 characterized by things. The setting means divides the tomographic image into a plurality of regions, sets an inflow artery for each region,
The calculation means obtains an arterial input function for each inflow artery,
The correction parameter means calculates a correction parameter based on a time-density curve of pixels around the inflow artery obtained for each region and an output function of each pixel of interest in the region including the inflow artery. To
The blood flow dynamic analysis device according to any one of claims 1 to 4, wherein An X-ray tube for irradiating a subject injected with a contrast agent with X-rays;
An X-ray detector that is disposed opposite to the X-ray tube with the subject interposed therebetween, detects X-rays transmitted through the subject, and outputs X-ray transmission data;
Rotating means capable of rotating by mounting the X-ray source and the X-ray detector;
An image processing apparatus that generates a tomogram by performing reconstruction calculation processing based on the X-ray transmission data;
A display device for displaying the tomographic image;
In an X-ray CT apparatus equipped with
Setting means for setting at least one inflow artery included in the tomogram;
The tomographic image time represents information of a temporal change in the pixel values for each pixel on the basis of - a computing means for determining the density curve, the time representing the information of a temporal change in the pixel values of the pixels constituting the inflow artery - and arterial input function is the concentration curve, time of the pixel near the inflow artery - and concentration curve, time in each pixel of interest - a calculating means for calculating an output function, which is the concentration curve,
The time difference between the blood flow arrival time in bloodstream arrival time and the respective output function before Symbol arterial input function, and for correcting at least one of a shape accent, the arterial input function in each pixel of interest, A correction parameter used for calculating the arterial input function corresponding to each pixel of interest is calculated based on a time-density curve of pixels around the inflow artery and an output function corresponding to each pixel of interest. A calculation means;
Correction means for correcting the arterial input function using a correction parameter corresponding to each pixel of interest, and obtaining a corrected arterial input function corresponding to each pixel of interest ;
Transfer function calculating means for obtaining a transfer function for each pixel of interest based on each output function and the corrected arterial input function corresponding to the pixel of interest for which the output function was obtained;
Function information calculating means for calculating biological function information based on each transfer function,
Displaying a biological function image based on the biological function information on the display device;
An X-ray CT apparatus characterized by that. An imaging sequence for applying a static magnetic field, a high-frequency pulse, and a gradient magnetic field to a subject injected with a contrast agent is executed to receive a magnetic resonance signal generated from the subject, and a tomography is performed based on the received magnetic resonance signal An MRI apparatus for generating and displaying an image, wherein the application of the high-frequency pulse and the gradient magnetic field is controlled based on a cross-sectional position of a subject output from a cross-sectional position output means, and a tomographic image of the cross-sectional position is obtained. In an MRI apparatus that generates and displays:
Setting means for setting at least one inflow artery included in the tomogram;
The tomographic image time represents information of a temporal change in the pixel values for each pixel on the basis of - a computing means for determining the density curve, the time representing the information of a temporal change in the pixel values of the pixels constituting the inflow artery - and arterial input function is the concentration curve, time of the pixel near the inflow artery - and concentration curve, time in each pixel of interest - a calculating means for calculating an output function, which is the concentration curve,
The time difference between the blood flow arrival time in bloodstream arrival time and the respective output function before Symbol arterial input function, and for correcting at least one of a shape accent, the arterial input function in each pixel of interest, A correction parameter used for calculating the arterial input function corresponding to each pixel of interest is calculated based on a time-density curve of pixels around the inflow artery and an output function corresponding to each pixel of interest. A calculation means;
Correction means for correcting the arterial input function using a correction parameter corresponding to each pixel of interest, and obtaining a corrected arterial input function corresponding to each pixel of interest ;
Transfer function calculating means for obtaining a transfer function for each pixel of interest based on each output function and the corrected arterial input function corresponding to the pixel of interest for which the output function was obtained;
Function information calculating means for calculating biological function information based on each of the transfer functions;
Display means for displaying a biological function image based on the biological function information;
An MRI apparatus characterized by comprising: A step of reading imaging data obtained by a medical imaging apparatus imaging a subject injected with a contrast agent;
Receiving a setting of an inflow artery included in a tomogram generated based on the read imaging data;
The tomographic image time represents information of a temporal change in the pixel values for each pixel on the basis of - a step of obtaining the concentration curve, time represents the information of a temporal change in the pixel values of the pixels constituting the inflow artery - Concentration and arterial input function is a curve, the time of the pixels near the inflow artery - and concentration curve, time in each pixel of interest - and determining an output function, which is the concentration curve,
The time difference between the blood flow arrival time in bloodstream arrival time and the respective output function before Symbol arterial input function, and for correcting at least one of a shape accent, the arterial input function in each pixel of interest, wherein the correction parameters used in the calculation of the arterial input function corresponding to each pixel of interest, the inflow artery around the pixel of time - and concentration curves, the output function for each pixel of interest, and calculating on the basis of the ,
Correcting the arterial input function using a correction parameter corresponding to each pixel of interest, and obtaining a corrected arterial input function corresponding to each pixel of interest ;
Obtaining a transfer function for each pixel of interest based on each output function and the corrected arterial input function corresponding to the pixel of interest for which the output function was determined;
Calculating biological function information based on each transfer function;
A computer program for analyzing blood flow dynamics.

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