JP2017217459A - X-ray ct apparatus, medical information processor, and medical information processing program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an X-ray CT apparatus capable of easily selecting appropriate data, and a medical information processor and a medical information processing program.SOLUTION: The X-ray CT apparatus has a collection part, a selection part and an analysis part. The collection part collects image data related to a plurality of time phases including at least a part of coronary arteries of a heart. The selection part acquires image indexes regarding a plurality of pieces of image data and extracts a combination of pieces of image data from combinations of pieces of image data having a time interval greater than a specific time interval among the plurality of pieces of image data on the basis of the image index in each piece of the image data. The analysis part executes a fluid analysis regarding the coronary arteries on the basis of the extracted combination of pieces of image data and obtains a fluid parameter for the coronary arteries.SELECTED DRAWING: Figure 2

Description

  Embodiments described herein relate generally to an X-ray CT apparatus, a medical information processing apparatus, and a medical information processing program.

  Conventionally, it is known that the causes of an ischemic disease of an organ are roughly classified into a blood circulation disorder and an organ dysfunction. For example, stenosis, which is an example of coronary artery circulation disorder, is a serious lesion that leads to ischemic heart disease. In such ischemic heart disease, whether drug treatment or stent treatment should be performed, etc. It is necessary to judge. In recent years, as a diagnosis for evaluating ischemic ischemia of coronary arteries, there is a method of measuring a myocardial blood flow reserve (FFR) using a pressure wire in a coronary angiography (CAG) using a catheter. It is being recommended.

  On the other hand, for example, coronary artery ischemic ischemia using medical images of the heart collected by a medical image diagnostic apparatus such as an X-ray CT (Computed Tomography) apparatus, an MRI (Magnetic Resonance Imaging) apparatus, or an ultrasonic diagnostic apparatus. A technique for non-invasive evaluation is also known. In recent years, hematogenous ischemia is evaluated by such various methods, and treatment according to the evaluation is performed.

JP 2014-108208 A JP 2014-087635 A JP2015-110155A

  The problem to be solved by the present invention is to provide an X-ray CT apparatus, a medical information processing apparatus, and a medical information processing program capable of easily selecting appropriate data.

  The X-ray CT apparatus according to the embodiment includes an acquisition unit, a selection unit, and an analysis unit. The collection unit collects image data related to a plurality of time phases including at least a part of the coronary artery of the heart. The selection unit obtains an image index related to the plurality of image data, and based on the image index in each image data, a combination of image data having a time interval larger than a predetermined time interval among the plurality of image data. A set of image data is extracted from the inside. The analysis unit performs a fluid analysis on the coronary artery based on the extracted set of image data to obtain a fluid parameter on the coronary artery.

FIG. 1 is a diagram illustrating an example of a configuration of a medical information processing system according to the first embodiment. FIG. 2 is a diagram illustrating an example of the configuration of the X-ray CT apparatus according to the first embodiment. FIG. 3 is a diagram for explaining an example of processing by the analysis function according to the first embodiment. FIG. 4 is a diagram for explaining selection of a time phase by the selection function according to the first embodiment. FIG. 5 is a diagram illustrating an example of a change in image quality of each cardiac phase according to the first embodiment. FIG. 6 is a diagram for explaining an example of selection processing by the selection function according to the first embodiment. FIG. 7 is a diagram for explaining an example of the optimum cardiac phase search process by the selection function according to the first embodiment. FIG. 8 is a diagram for explaining an example of threshold processing by the selection function according to the first embodiment. FIG. 9 is a diagram for explaining an example of selection processing by the selection function according to the first embodiment. FIG. 10 is a flowchart illustrating a processing procedure performed by the X-ray CT apparatus according to the first embodiment. FIG. 11 is a diagram for explaining an example of selection processing by the selection function according to the second embodiment. FIG. 12 is a flowchart illustrating a processing procedure performed by the X-ray CT apparatus according to the second embodiment. FIG. 13 is a diagram for explaining selection of a time phase by the selection function according to the third embodiment. FIG. 14 is a flowchart illustrating a processing procedure performed by the X-ray CT apparatus according to the third embodiment. FIG. 15 is a diagram illustrating an example of a configuration of a medical information processing apparatus according to the third embodiment.

  Exemplary embodiments of an X-ray CT apparatus, a medical information processing apparatus, and a medical information processing program according to the present application will be described below in detail with reference to the accompanying drawings. The X-ray CT apparatus, the medical information processing apparatus, and the medical information processing program according to the present application are not limited to the embodiments described below.

(First embodiment)
First, the first embodiment will be described. In the first embodiment, an example in which the technique disclosed in the present application is applied to an X-ray CT apparatus will be described. Hereinafter, a medical information processing system including an X-ray CT apparatus will be described as an example. In the following, an example in which a cardiac blood vessel is an analysis target will be described as an example.

  FIG. 1 is a diagram illustrating an example of a configuration of a medical information processing system according to the first embodiment. As illustrated in FIG. 1, the medical information processing system according to the first embodiment includes an X-ray CT (Computed Tomography) apparatus 100, an image storage apparatus 200, and a medical information processing apparatus 300.

  For example, the X-ray CT apparatus 100 according to the first embodiment is connected to an image storage apparatus 200 and a medical information processing apparatus 300 via a network 400 as shown in FIG. The medical information processing system may be further connected via the network 400 to another medical image diagnostic apparatus such as an MRI apparatus, an ultrasonic diagnostic apparatus, or a PET (Positron Emission Tomography) apparatus.

  The image storage device 200 stores image data collected by various medical image diagnostic apparatuses. For example, the image storage device 200 is realized by a computer device such as a server device. In this embodiment, the image storage apparatus 200 acquires CT image data (volume data) from the X-ray CT apparatus 100 via the network 400, and the acquired CT image data is stored in the apparatus or outside the apparatus. Remember me.

  The medical information processing apparatus 300 acquires image data from various medical image diagnostic apparatuses via the network 400, and processes the acquired image data. For example, the medical information processing apparatus 300 is realized by a computer device such as a workstation. In the present embodiment, the medical information processing apparatus 300 acquires CT image data from the X-ray CT apparatus 100 or the image storage apparatus 200 via the network 400, and performs various image processes on the acquired CT image data. The medical information processing apparatus 300 displays CT image data before or after performing image processing on a display or the like.

  The X-ray CT apparatus 100 collects CT image data of a subject. Specifically, the X-ray CT apparatus 100 collects projection data by detecting the X-rays transmitted through the subject by rotating the X-ray tube and the X-ray detector around the subject. Then, the X-ray CT apparatus 100 generates time-series three-dimensional CT image data based on the collected projection data. FIG. 2 is a diagram illustrating an example of the configuration of the X-ray CT apparatus 100 according to the first embodiment. As shown in FIG. 2, the X-ray CT apparatus 100 according to the first embodiment includes a gantry 10, a bed apparatus 20, and a console 30.

  The gantry 10 is a device that irradiates the subject P (patient) with X-rays, detects the X-rays transmitted through the subject P, and outputs them to the console 30. The gantry 10 and the X-ray irradiation control circuit 11 generate X-rays. The apparatus 12 includes a detector 13, a data acquisition circuit (DAS) 14, a rotating frame 15, and a gantry drive circuit 16.

  The rotating frame 15 supports the X-ray generator 12 and the detector 13 so as to face each other with the subject P interposed therebetween, and is rotated at a high speed in a circular orbit around the subject P by a gantry driving circuit 16 described later. It is an annular frame.

  The X-ray irradiation control circuit 11 is a device that supplies a high voltage to the X-ray tube 12 a as a high voltage generator, and the X-ray tube 12 a uses the high voltage supplied from the X-ray irradiation control circuit 11 to Generate a line. The X-ray irradiation control circuit 11 adjusts the X-ray dose irradiated to the subject P by adjusting the tube voltage and tube current supplied to the X-ray tube 12a under the control of the scan control circuit 33 described later. .

  The X-ray irradiation control circuit 11 switches the wedge 12b. The X-ray irradiation control circuit 11 adjusts the X-ray irradiation range (fan angle and cone angle) by adjusting the aperture of the collimator 12c. In addition, this embodiment may be a case where an operator manually switches a plurality of types of wedges.

  The X-ray generator 12 is an apparatus that generates X-rays and irradiates the subject P with the generated X-rays, and includes an X-ray tube 12a, a wedge 12b, and a collimator 12c.

  The X-ray tube 12 a is a vacuum tube that irradiates the subject P with an X-ray beam with a high voltage supplied by a high voltage generator (not shown). The X-ray beam is applied to the subject P as the rotating frame 15 rotates. Irradiate. The X-ray tube 12a generates an X-ray beam that spreads with a fan angle and a cone angle. For example, under the control of the X-ray irradiation control circuit 11, the X-ray tube 12 a continuously exposes X-rays around the subject P for full reconstruction or exposure that can be reconfigured for half reconstruction. It is possible to continuously expose X-rays in the irradiation range (180 degrees + fan angle). Further, the X-ray irradiation control circuit 11 can control the X-ray tube 12a to intermittently emit X-rays (pulse X-rays) at a preset position (tube position). The X-ray irradiation control circuit 11 can also modulate the intensity of the X-rays emitted from the X-ray tube 12a. For example, the X-ray irradiation control circuit 11 increases the intensity of X-rays emitted from the X-ray tube 12a at a specific tube position, and exposes from the X-ray tube 12a at a range other than the specific tube position. Reduce the intensity of the emitted X-rays.

  The wedge 12b is an X-ray filter for adjusting the X-ray dose of X-rays emitted from the X-ray tube 12a. Specifically, the wedge 12b transmits the X-rays exposed from the X-ray tube 12a so that the X-rays irradiated from the X-ray tube 12a to the subject P have a predetermined distribution. Attenuating filter. For example, the wedge 12b is a filter obtained by processing aluminum so as to have a predetermined target angle or a predetermined thickness. The wedge is also called a wedge filter or a bow-tie filter.

  The collimator 12c is a slit for narrowing the X-ray irradiation range in which the X-ray dose is adjusted by the wedge 12b under the control of the X-ray irradiation control circuit 11 described later.

  The gantry driving circuit 16 rotates the rotary frame 15 to rotate the X-ray generator 12 and the detector 13 on a circular orbit around the subject P.

  The detector 13 is a two-dimensional array type detector (surface detector) that detects X-rays transmitted through the subject P, and a detection element array formed by arranging X-ray detection elements for a plurality of channels is the subject P. A plurality of rows are arranged along the body axis direction (Z-axis direction shown in FIG. 2). Specifically, the detector 13 in the first embodiment includes X-ray detection elements arranged in multiple rows such as 320 rows along the body axis direction of the subject P. For example, the lungs of the subject P It is possible to detect X-rays transmitted through the subject P over a wide range, such as a range including the heart and the heart.

  The data collection circuit 14 is a DAS, and collects projection data from the X-ray detection data detected by the detector 13. For example, the data collection circuit 14 generates projection data by performing amplification processing, A / D conversion processing, inter-channel sensitivity correction processing, and the like on the X-ray intensity distribution data detected by the detector 13. The projected data is transmitted to the console 30 described later. For example, when X-rays are continuously emitted from the X-ray tube 12a while the rotary frame 15 is rotating, the data acquisition circuit 14 collects projection data groups for the entire circumference (for 360 degrees). Further, the data collection circuit 14 associates the tube position with each collected projection data and transmits it to the console 30 described later. The tube position is information indicating the projection direction of the projection data. Note that the sensitivity correction processing between channels may be performed by the preprocessing circuit 34 described later.

  The couch device 20 is a device on which the subject P is placed, and includes a couch driving device 21 and a top plate 22 as shown in FIG. The couch driving device 21 moves the subject P into the rotary frame 15 by moving the couchtop 22 in the Z-axis direction. The top plate 22 is a plate on which the subject P is placed.

  For example, the gantry 10 executes a helical scan that rotates the rotating frame 15 while moving the top plate 22 to scan the subject P in a spiral shape. Alternatively, the gantry 10 performs a conventional scan in which the subject P is scanned in a circular orbit by rotating the rotating frame 15 while the position of the subject P is fixed after the top plate 22 is moved. Alternatively, the gantry 10 performs a step-and-shoot method in which the position of the top plate 22 is moved at regular intervals and a conventional scan is performed in a plurality of scan areas.

  The console 30 is a device that accepts an operation of the X-ray CT apparatus 100 by an operator and reconstructs CT image data (volume data) using projection data collected by the gantry 10. As shown in FIG. 2, the console 30 includes an input circuit 31, a display 32, a scan control circuit 33, a preprocessing circuit 34, a storage circuit 35, an image reconstruction circuit 36, and a processing circuit 37. .

  The input circuit 31 includes a mouse, a keyboard, a trackball, a switch, a button, a joystick, and the like that are used by the operator of the X-ray CT apparatus 100 to input various instructions and various settings, and instructions and setting information received from the operator. Is transferred to the processing circuit 37. For example, the input circuit 31 receives, from the operator, imaging conditions for CT image data, reconstruction conditions for reconstructing CT image data, image processing conditions for CT image data, and the like. Further, the input circuit 31 receives an operation for selecting an examination for the subject P. Further, the input circuit 31 accepts a designation operation for designating a part on the image.

  The display 32 is a monitor that is referred to by the operator. The display 32 displays image data generated from the CT image data to the operator under the control of the processing circuit 37, and displays various data from the operator via the input circuit 31. A GUI (Graphical User Interface) for receiving instructions and various settings is displayed. The display 32 displays a plan screen for a scan plan, a screen being scanned, and the like.

  The scan control circuit 33 controls the operations of the X-ray irradiation control circuit 11, the gantry driving circuit 16, the data acquisition circuit 14, and the bed driving device 21 under the control of the processing circuit 37, thereby Control the collection process. Specifically, the scan control circuit 33 controls projection data collection processing in the photographing for collecting the positioning image (scano image) and the main photographing (scanning) for collecting the image used for diagnosis.

  The preprocessing circuit 34 performs logarithmic conversion processing and correction processing such as offset correction, sensitivity correction, and beam hardening correction on the projection data generated by the data acquisition circuit 14 to obtain corrected projection data. Generate. Specifically, the preprocessing circuit 34 generates corrected projection data for each of the projection data of the positioning image generated by the data acquisition circuit 14 and the projection data acquired by the main photographing, and the storage circuit 35. To store.

  The storage circuit 35 stores the projection data generated by the preprocessing circuit 34. Specifically, the storage circuit 35 stores the projection data of the positioning image generated by the preprocessing circuit 34 and the diagnostic projection data collected by the main imaging. The storage circuit 35 stores CT image data reconstructed by an image reconstruction circuit 36 described later. Further, the storage circuit 35 appropriately stores a processing result by a processing circuit 37 described later.

  The image reconstruction circuit 36 reconstructs CT image data using the projection data stored in the storage circuit 35. Specifically, the image reconstruction circuit 36 reconstructs CT image data from the positioning image projection data and the image projection data used for diagnosis. Here, as the reconstruction method, there are various methods, for example, back projection processing. Further, as the back projection process, for example, a back projection process by an FBP (Filtered Back Projection) method can be cited. Alternatively, the image reconstruction circuit 36 can reconstruct CT image data using a successive approximation method.

  The image reconstruction circuit 36 performs image processing on the CT image data to generate image data. The image reconstruction circuit 36 stores the reconstructed CT image data and the image data generated by various image processes in the storage circuit 35.

  The processing circuit 37 performs overall control of the X-ray CT apparatus 100 by controlling the operations of the gantry 10, the couch device 20, and the console 30. Specifically, the processing circuit 37 controls the CT scan performed on the gantry 10 by controlling the scan control circuit 33. The processing circuit 37 controls the image reconstruction circuit 36 and the image generation process in the console 30 by controlling the image reconstruction circuit 36. In addition, the processing circuit 37 controls the display 32 to display various image data stored in the storage circuit 35.

  Under such a configuration, the X-ray CT apparatus 100 according to the present embodiment makes it possible to easily select appropriate data. Specifically, the X-ray CT apparatus 100 simply uses appropriate data as data for calculating an index value related to blood flow by fluid analysis using a medical image including blood vessels (for example, three-dimensional CT image data). Allows you to choose. For example, the X-ray CT apparatus 100 selects CT image data having an appropriate time phase as data used for fluid analysis from CT image data having a plurality of time phases collected over time.

  Here, examples of the index value related to blood flow include a myocardial blood flow reserve ratio (FFR: Fractional Flow Reserve), a mechanical index in a blood vessel, and an index related to blood flow. FFR is the ratio of the pressure at the proximal part near the heart in the blood vessel to the pressure at the distal part far from the heart, eg, “FFR = Pd (distal pressure) / Pa (proximal pressure) ) ”. For example, when the stenosis (the site to be treated) occurs in the blood vessel, the FFR value decreases because the pressure in the distal portion decreases due to the stenosis. The fluid analysis is used to determine whether or not treatment is necessary by calculating the FFR value and the like. Examples of the mechanical index in the blood vessel include pressure, vector, and shear stress. In addition, examples of the index relating to the blood flow rate include a flow rate and a flow rate.

  Hereinafter, in the first embodiment, a case where appropriate CT image data is selected in the fluid analysis for the coronary artery will be described as an example. As illustrated in FIG. 2, the processing circuit 37 according to the present embodiment executes a control function 37a, an analysis function 37b, a selection function 37c, an acquisition function 37d, and a presentation function 37e. Here, for example, each processing function executed by the control function 37a, the analysis function 37b, the selection function 37c, the acquisition function 37d, and the presentation function 37e, which are components of the processing circuit 37 shown in FIG. In the storage circuit 35. The processing circuit 37 is a processor that implements a function corresponding to each program by reading each program from the storage circuit 35 and executing the program. In other words, the processing circuit 37 in a state where each program is read has each function shown in the processing circuit 37 of FIG. The analysis function 37b described in the present embodiment is an example of an analysis unit described in the claims. The selection function 37c is an example of a selection unit described in the claims. The acquisition function 37d is an example of an acquisition unit. The presentation function 37e is an example of a presentation unit described in the claims.

  The control function 37a executes overall control of the X-ray CT apparatus 100. For example, the control function 37a performs the control related to the scan described above, the reconstruction of the CT image data, the control related to the generation of various images from the CT image data, the display control of the generated various images, and the like.

  The analysis function 37b performs fluid analysis based on the CT image data. Specifically, the analysis function 37b extracts time-series blood vessel shape data representing the blood vessel shape from the three-dimensional CT image data. For example, the analysis function 37b reads CT image data of a plurality of time phases collected from the storage circuit 35 over time, and performs image processing on the read CT image data of the plurality of time phases, thereby obtaining a time-series blood vessel. Extract shape data.

  Here, the analysis function 37b sets a target region for calculating an index value in a blood vessel region included in the CT image data. Specifically, the analysis function 37b sets a target region in the blood vessel region by an instruction from the operator via the input circuit 31 or image processing. Then, the analysis function 37b, as the blood vessel shape data of the set target region, for example, a blood vessel core line (coordinate information of the core line), a cross-sectional area of blood vessels and lumens in a cross section perpendicular to the core line, The distance from the core line to the inner wall and the distance from the core line to the outer wall in the cylindrical direction are extracted from the CT image data. The analysis function 37b can extract other various blood vessel shape data according to the analysis method.

  Furthermore, the analysis function 37b sets analysis conditions for fluid analysis. Specifically, the analysis function 37b sets a physical property value of blood, an iterative calculation condition, an initial value of analysis, and the like as analysis conditions. For example, the analysis function 37b sets blood viscosity, density, and the like as the physical property values of blood. Further, the analysis function 37b sets the maximum number of iterations in the iterative calculation, a relaxation coefficient, an allowable value of the residual, and the like as conditions for the iterative calculation. Moreover, the analysis function 37b sets a flow rate, a pressure, a fluid resistance, an initial value of a pressure boundary, and the like as initial values for analysis. Note that various values used by the analysis function 37b may be incorporated in the system in advance, or may be defined interactively by the operator.

  The analysis function 37b sets a treatment target site in a blood vessel in the image data. Specifically, the analysis function 37b manually or automatically sets a treatment target site in a blood vessel. For example, the analysis function 37b sets a range received via the input circuit 31 as a treatment target site. In such a case, the input circuit 31 receives a range (treatment target site) for changing the analysis condition, and the analysis function 37b sets the received range as the treatment target site. The analysis function 37b automatically sets a treatment target region based on the shape in the target region. For example, the analysis function 37b extracts a stenosis portion based on the shape in the target region, and sets a stenosis portion having a certain stenosis degree or more among the extracted stenosis portions as a treatment target site. Note that any method can be used to extract the stenosis.

  Then, the analysis function 37b calculates an index value related to blood flow of the blood vessel by fluid analysis using image data including the blood vessel. Specifically, the analysis function 37b performs fluid analysis using blood vessel shape data and analysis conditions, and calculates an index value (fluid parameter) related to blood flow in the target region of the blood vessel. For example, the analysis function 37b is based on blood vessel shape data such as a blood vessel lumen or outer wall contour, a blood vessel cross-sectional area, and a core line, and setting conditions such as blood physical property values, iterative calculation conditions, and analysis initial values. For each predetermined position of the blood vessel, index values such as pressure, blood flow rate, blood flow rate, vector, and shear stress are calculated. The analysis function 37b further calculates an index value such as FFR from the calculated index value.

  FIG. 3 is a diagram for explaining an example of processing by the analysis function 37b according to the first embodiment. As shown in FIG. 3, for example, the analysis function 37b extracts blood vessel shape data including coordinates of the core line and cross-sectional information for the LAD that is the target region from the three-dimensional CT image data including the aorta and the coronary artery. Furthermore, the analysis function 37b sets analysis conditions for analysis on the extracted LAD. Then, the analysis function 37b performs fluid analysis using the extracted LAD blood vessel shape data and the set conditions, for example, from the entrance boundary to the exit boundary of the target region LAD, along a predetermined core line. For each position, index values such as pressure, blood flow rate, blood flow rate, vector, and shear stress are calculated. That is, the analysis function 37b calculates distributions such as pressure, blood flow rate, blood flow rate, vector, and shear stress for the target region. And the analysis function 37b calculates FFR of each position in an object field based on the calculated pressure distribution, for example.

  As described above, the analysis function 37b extracts blood vessel shape data from CT image data of a plurality of time phases collected over time, and performs fluid analysis using the extracted plurality of time phase blood vessel shape data and analysis conditions. To calculate an index value related to blood flow. Here, in order to obtain a highly accurate analysis result when performing such a fluid analysis of the coronary artery, it is a plurality of time phases including a change in the shape of the coronary artery (for example, a change in the cross-sectional area) as much as possible, In addition, it is desirable that the CT image data of each time phase is as sharp as possible. That is, the time-series blood vessel shape data includes, as much as possible, a series of changes from the time phase in which blood flows in and the area of the coronary artery is maximized to the time phase in which blood flows out and the area is minimized. It is desirable to use time-phase CT image data with little image motion (blur). Therefore, in the first embodiment, the selection function 37c selects a time phase corresponding to the above-described CT image data from each time phase of the CT image data collected over time.

  The selection function 37c selects a time phase that includes a change in the shape of the coronary artery and has less blur of the image due to pulsation, from the CT image data of a plurality of time phases collected over time. Specifically, the selection function 37c is a time phase in which the motion associated with the pulsation is relatively small from each time phase corresponding to the plurality of CT image data, and the time interval between the time phases is increased. Select multiple time phases. More specifically, the selection function 37c extracts a time phase range in which the motion associated with the pulsation is relatively small in each time phase corresponding to a plurality of CT image data, and includes the time phases included in the extracted range. Based on the evaluation of motion associated with pulsation in image data corresponding to, the time phase associated with pulsation is relatively small from the time phases included in the range, and the time interval between time phases is large. Select multiple time phases to be

  Here, the selection function 37c evaluates the motion associated with the heartbeat of the heart based on the image index in each CT image data, and is a time phase in which the motion associated with the heartbeat is relatively small, and the time between the time phases. Select multiple time phases to increase the interval. That is, the selection function 37c acquires an image index for each CT image data. Then, the selection function 37c selects a set of CT image data from a combination of CT image data having a time interval larger than a predetermined time interval among a plurality of CT image data based on the image index in each image data. Extract. For example, the selection function 37c extracts a set of CT image data in which the image quality index in each CT image data is equal to or greater than a predetermined threshold from the combination of CT image data. Here, the image quality index is an example of an image index. Hereinafter, an example of selecting a plurality of time phases (selecting a set of CT image data) based on the image quality index will be described.

  FIG. 4 is a diagram for explaining selection of a time phase by the selection function 37c according to the first embodiment. In FIG. 4, the heart rate is shown in the upper stage, the heart movement is shown in the middle stage, and the area of the coronary artery is shown in the lower stage. In FIG. 4, the horizontal direction indicates time, and the heartbeat, heart motion, and coronary artery area change with time are shown in association with each other. For example, the selection function 37c selects a cardiac phase included in the range of 70% to 99% of the cardiac phase. Here, the cardiac phases 70% to 99% are time phases in which there is not much movement of the heart and the change in the area of the coronary artery is large, as shown in FIG. The heart moves due to contraction and dilation, and as shown in the middle part of FIG. The selection function 37c selects a time phase in which the movement accompanying the pulsation is relatively small by selecting a cardiac phase included in the cardiac phase 70% to 99% in which the movement is stable. The cardiac phase of 70% to 99% corresponds to the wave free period. The wave free period is a time phase in the middle diastole without the influence of the ejection pressure wave descending the coronary artery from the pulse and the reflex pressure formed by the left ventricular pressure and traveling retrogradely through the coronary artery.

  Further, as shown in the lower part of FIG. 4, the area of the coronary artery is the maximum near the cardiac phase 70% and the minimum is near 99%. This is because blood begins to flow into the coronary artery near the cardiac phase of 70% and then flows out as it reaches 99%. The selection function 37c selects a plurality of time phases so that the time interval between the time phases becomes as large as possible in the range of 70% to 99% of the cardiac phase so as to include the change in the area of the coronary artery as much as possible.

  Here, in the cardiac phase of 70 to 99%, there is not much movement of the heart and it is stable, but the image quality varies in the actually collected CT image data. Further, in the vicinity of the cardiac phase of 99%, there is a case where blurring occurs due to the influence of the next contraction of the heart. FIG. 5 is a diagram illustrating an example of a change in image quality of each cardiac phase according to the first embodiment. FIG. 5 shows time on the horizontal axis and image quality on the vertical axis. For example, as shown in FIG. 5, the image quality of CT image data gradually improves toward the vicinity of 70% of the cardiac phase, and changes while fluctuating near a certain image quality. The image quality of the CT image data rapidly decreases in the vicinity of 99% cardiac phase. As described above, the image quality of the CT image data is not constant even within the range of 70% to 99% of the cardiac phase, and varies greatly.

  Therefore, the selection function 37c evaluates the motions associated with the pulsations of the respective CT image data corresponding to the cardiac phases 70% to 99% in which the motions associated with the pulsations are relatively small, thereby causing the cardiac phases 70% to 99%. Select the cardiac phase from which the movement with the beat is smaller. Here, the selection function 37c selects the cardiac phase from the cardiac phases of 70% to 99% so that the movement accompanying the pulsation is smaller and the time interval is larger. Hereinafter, the process of the selection function 37c will be described by taking as an example the case of selecting four cardiac phases from the cardiac phases 70% to 99%.

  In such a case, the selection function 37c selects a plurality of cardiac phases so that each time interval between adjacent cardiac phases in a plurality of time phases is large and approximates each other. For example, when the selection function 37c selects four cardiac phases from the cardiac phases 70% to 99%, the CT image data in each cardiac phase has a smaller motion associated with the pulsation, and adjacent cardiac phases. The four cardiac phases are selected so that the time intervals between them are close to equal intervals. This is because the coronary artery fluid analysis analyzes how the area of the coronary artery fluctuates (the tendency of fluctuation), so the cardiac phases of the CT image data applied to the fluid analysis are as equally spaced as possible. This is because it is desirable.

  Hereinafter, an example of selection processing of four cardiac phases by the selection function 37c will be described. For example, the selection function 37c divides the range (Wave Free Period) into a plurality of partial ranges, and for each partial range, selects a time phase in which the movement associated with the pulsation is relatively small from among the time phases included in the partial range. Select each one. That is, the selection function 37c divides the cardiac phase 70% to 99% into four regions, and selects one cardiac phase from each of the divided regions. FIG. 6 is a diagram for explaining an example of the selection process by the selection function 37c according to the first embodiment. For example, the selection function 37c converts the cardiac phase from 70% to 99% into four regions of “70 to 76%”, “77% to 83%”, “84% to 91%”, and “92 to 99%”. The optimal phase is searched and selected in each region. Then, the optimal CT image data of four cardiac phases are reconstructed from the cardiac phase data corresponding to the four cardiac phases selected from each region by the selection function 37c.

  The search for the optimum cardiac phase in each region shown in FIG. 6 is, for example, searching for a cardiac phase with a smaller movement associated with the pulsation. For example, the selection function 37c evaluates the degree of blur (definition) in the image using the cardiac phase data for every 1% in the projection data of the cardiac phase 70% to 90% collected in the electrocardiogram synchronization. The cardiac phase data with the least blur is selected as the cardiac phase data to be reconstructed.

  FIG. 7 is a diagram for explaining an example of the optimum cardiac phase search process by the selection function 37c according to the first embodiment. FIG. 7 shows a case where an optimal cardiac phase of “70 to 76%” is searched. For example, the selection function 37c extracts one slice of sinogram including coronary arteries from projection data for a plurality of heartbeats. Then, as shown in FIG. 7, the selection function 37 c uses “70%” cardiac phase data, “71%” cardiac phase data, “72%” cardiac phase data, and “73%” from the extracted sinograms. The cardiac phase data of “74%”, the cardiac phase data of “75%”, the cardiac phase data of “75%” and the cardiac phase data of “76%” are extracted and reconstructed to include coronary arteries in each cardiac phase. An image of one slice is generated.

  Then, the selection function 37c calculates an SD value for each generated image of each cardiac phase, extracts an image with little blur (high definition) based on the calculated SD value, and extracts the cardiac phase of the extracted image. Is selected as the optimal cardiac phase. For example, as illustrated in FIG. 7, the selection function 37 c sets the cardiac phase “74%” of the image having a narrow skirt width in the distribution of the signal intensity (pixel value) for each pixel of each image to “70 to 76%”. As the optimal cardiac phase in the region. The SD value described above is a standard deviation of signal intensity for each pixel included in an image, and is an index value indicating noise characteristics.

  The selection function 37c executes the above-described selection processing for the three regions “77% to 83%”, “84% to 91%”, and “92 to 99%”, and selects the optimum center from each region. Select the phase. Here, when the optimal cardiac phase is selected from each region as described above, the time interval of the optimal cardiac phase selected in each region may be shortened. For example, when the optimal cardiac phase in the region “70 to 76%” is selected as “74%” and the optimal cardiac phase in the region “77% to 83%” is selected as “77%”, the time interval is “ 3% ". As described above, in CT image data used for fluid analysis, it is desirable that the time interval between cardiac phases is large and uniform.

  Therefore, the selection function 37c selects a plurality of cardiac phases so that the time interval between the cardiac phases is equal to or greater than a predetermined threshold in the cardiac phases included in the range. FIG. 8 is a diagram for explaining an example of threshold processing by the selection function 37c according to the first embodiment. For example, as illustrated in FIG. 8, the selection function 37 c executes the selection process using “5%” as the time interval threshold. For example, when the optimum cardiac phase in the region of “70 to 76%” is selected as “74%”, the selection function 37c is “79%” spaced from “74%” by “5%” or more. The optimal cardiac phase in the region of “77 to 83%” is searched for with the lower end of. That is, the selection function 37c searches for the optimum cardiac phase in the region “79 to 83%”. The time interval threshold is arbitrarily set.

  As described above, when the selection function 37c selects the optimum cardiac phase from the four regions of “70 to 76%”, “77% to 83%”, “84% to 91%”, and “92 to 99%”. The acquisition function 37d acquires cardiac phase data corresponding to a plurality of time phases selected by the selection function 37c. Specifically, the acquisition function 37d acquires cardiac phase data for reconstructing CT image data of each selected optimal cardiac phase. That is, the acquisition function 37d acquires cardiac phase data in each column in the body axis direction for each selected optimal cardiac phase. The image reconstruction circuit 36 reconstructs three-dimensional CT image data of the four optimal cardiac phases using the cardiac phase data corresponding to the acquired four optimal cardiac phases. The analysis function 37b performs the above-described fluid analysis using the reconstructed four cardiac phase CT image data.

  Here, in the X-ray CT apparatus 100 according to the first embodiment, it is possible to present a warning when the optimum cardiac phase selected by the selection function 37c does not meet a predetermined condition. Specifically, the presentation function 37e presents a warning to the operator when a plurality of cardiac phases selected by the selection function 37c do not meet a predetermined condition. For example, the presentation function 37e displays a warning on the display 32 when the time interval between the upper and lower cardiac phases is shorter than a predetermined threshold in the selected optimal cardiac phase. In this case, the presentation function 37e can display a warning and present an alternative. For example, the presentation function 37e presents, as an alternative, a cardiac phase in which the time interval between the upper and lower cardiac phases is longer than a predetermined threshold and the motion associated with the beat is smallest.

  In the above-described embodiment, the case where the process is executed by dividing the range of the cardiac phase “70% to 99%” into four regions has been described. However, cardiac phase data in the range of the cardiac phase “70% to 99%” may not be collected in an actual scan. Therefore, the selection function 37c can also divide the range of the actually collected cardiac phase. FIG. 9 is a diagram for explaining an example of selection processing by the selection function according to the first embodiment. For example, the selection function 37c divides the range of the actually collected cardiac phase into four regions out of the projection data collected at the cardiac phase of 70% to 99% in the electrocardiogram synchronous scan, and the optimum phase in each region. Search for and select. Then, the optimal CT image data of four cardiac phases are reconstructed from the cardiac phase data corresponding to the four cardiac phases selected from each region by the selection function 37c.

  As an example, when the range of the actually collected cardiac phase is “68 to 95%”, the selection function 37c divides “68 to 95%” into four regions. Here, the selection function 37c divides the region so that the cardiac phase included in each region does not exceed the range of “70% to 99%”. For example, the selection function 37c does not target “68%” and “69%” among “68 to 95%”, but “68 to 95%” is “70 to 76%” and “77 to 82%”. ”,“ 83 to 88% ”, and“ 89 to 95% ”.

  In the above-described embodiment, the case where an image for one slice is generated from the cardiac phase data and the optimum cardiac phase search is performed has been described as an example. However, the embodiment is not limited to this. For example, the optimal cardiac phase search may be performed by reconstructing CT image data corresponding to each cardiac phase. In this case, for example, the selection function 37c can search for the optimum cardiac phase by generating an image of a slice including the coronary artery from the reconstructed CT image data and comparing the SD value of the generated slice. Further, for example, the selection function 37c extracts the three-dimensional region of the coronary artery from the reconstructed CT image data, and searches for the optimum cardiac phase by comparing the SD values for the extracted three-dimensional region of the coronary artery (each voxel). You can also.

  Further, in the above-described embodiment, the case where the optimum cardiac phase is selected from each region has been described as an example. However, the embodiment is not limited to this. For example, the upper end and the lower end of the range may be fixedly selected. For example, the selection function 37c may be a case where the cardiac phases “70%” and “99%” are fixedly selected as the optimal cardiac phase in the range of the cardiac phase “70% to 99%”. Alternatively, the selection function 37c may select at least a heart phase near the upper end and a heart phase near the lower end in the range as a plurality of heart phases. As an example, the selection function 37c is a case where, in the range of the cardiac phase “70% to 99%”, the vicinity of the cardiac phase “70%” and the vicinity of “99%” are preferentially selected as the optimal cardiac phase. Also good.

  Next, a processing procedure performed by the X-ray CT apparatus 100 according to the first embodiment will be described. FIG. 10 is a flowchart showing a processing procedure performed by the X-ray CT apparatus 100 according to the first embodiment. Note that FIG. 10 shows a processing procedure when the range of the cardiac phase of 70 to 99% is divided.

  Here, step S101 in FIG. 10 is realized by, for example, the processing circuit 37 calling and executing a program corresponding to the control function 37a from the storage circuit 35. Further, step S102, step S103, and step S107 are realized, for example, when the processing circuit 37 calls and executes a program corresponding to the selection function 37c from the storage circuit 35. Moreover, step S104 and step S106 are implement | achieved when the processing circuit 37 calls and executes the program corresponding to the presentation function 37e from the memory circuit 35, for example. Further, step S105 is realized, for example, when the image reconstruction circuit 36 reads the corresponding program from the storage circuit 35 and executes it. Further, step S108 is realized, for example, when the processing circuit 37 calls and executes a program corresponding to the analysis function 37b from the storage circuit 35.

  In the X-ray CT apparatus 100 according to the present embodiment, first, the processing circuit 37 collects projection data (step S101). Then, the processing circuit 37 divides the cardiac phase 70 to 99% into a plurality of regions (step S102), and selects a cardiac phase in which the movement of the coronary artery is small in each region (step S103). Subsequently, the processing circuit 37 determines whether or not the selected cardiac phase satisfies the condition (step S104). If the selected cardiac phase satisfies the condition (Yes at Step S104), the image reconstruction circuit 36 reconstructs the volume data corresponding to the selected cardiac phase (Step S105).

  On the other hand, when the selected cardiac phase does not satisfy the condition (No at Step S104), the processing circuit 37 displays a warning (Step S106). Then, the processing circuit 37 determines whether or not a reselection operation has been accepted (step S107). Here, when a reselection operation is accepted (Yes at Step S107), the processing circuit 37 returns to Step S103 and selects a cardiac phase with less movement of the coronary artery. On the other hand, when the reselection operation is not accepted (No at Step S107), the image reconstruction circuit 36 reconstructs the volume data corresponding to the selected cardiac phase (Step S105). In step S105, when the volume data corresponding to each cardiac phase is reconstructed, the processing circuit 37 performs fluid analysis using the reconstructed volume data of each cardiac phase (step S108).

  As described above, according to the first embodiment, the data collection circuit 14 collects a plurality of projection data over time. The selection function 37c selects a plurality of cardiac phases from each time phase corresponding to a plurality of projection data so that the motion accompanying the pulsation is relatively small and the time interval between the time phases is large. To do. The acquisition function 37d acquires projection data corresponding to a plurality of cardiac phases selected by the selection function 37c. Therefore, the X-ray CT apparatus 100 according to the first embodiment makes it possible to easily acquire appropriate data when performing fluid analysis.

  In addition, according to the first embodiment, the selection function 37c extracts a cardiac phase range in which movement associated with pulsation is relatively small in each time phase corresponding to a plurality of projection data, and is included in the extracted range. Based on the evaluation of the motion associated with the pulsation in the image data corresponding to the cardiac phase, the motion associated with the pulsation is relatively small from the cardiac phases included in the range, and between the cardiac phases A plurality of cardiac phases are selected so that the time interval is increased. Therefore, the X-ray CT apparatus 100 according to the first embodiment makes it possible to acquire more appropriate data when performing fluid analysis.

  Further, according to the first embodiment, the selection function 37c evaluates the motion associated with the pulsation based on the sharpness in the coronary artery region included in the projection data. Therefore, the X-ray CT apparatus 100 according to the first embodiment makes it possible to easily evaluate the movement associated with the pulsation.

  In addition, according to the first embodiment, the selection function 37c divides the range into a plurality of partial ranges, and the movement accompanying the pulsation is relatively out of the cardiac phases included in the partial ranges for each partial range. Choose a smaller cardiac phase. The selection function 37c divides the range into partial ranges so that the widths of the plurality of partial ranges are approximated. Therefore, the X-ray CT apparatus 100 according to the first embodiment makes it possible to easily select cardiac phases having a certain interval.

  According to the first embodiment, the selection function 37c selects at least a heart phase near the upper end and a heart phase near the lower end in the range as a plurality of heart phases. Therefore, the X-ray CT apparatus 100 according to the first embodiment makes it possible to easily select a cardiac phase that maximizes the coronary artery area and a cardiac phase that is close to the minimal cardiac phase.

  Further, according to the first embodiment, the selection function 37c selects a plurality of cardiac phases so that the time interval between the cardiac phases is equal to or greater than a predetermined threshold in the cardiac phases included in the range. Therefore, the X-ray CT apparatus 100 according to the first embodiment makes it possible to bring the time interval between the cardiac phases closer to an equal interval.

  Further, according to the first embodiment, the selection function 37c selects a plurality of cardiac phases so that each time interval between adjacent cardiac phases is large and approximates each other in the plurality of cardiac phases. Therefore, the X-ray CT apparatus 100 according to the first embodiment makes it possible to make the time interval between cardiac phases larger and close to equal intervals.

  Further, according to the first embodiment, the presentation function 37e presents a warning to the operator when a plurality of cardiac phases selected by the selection function 37c do not meet a predetermined condition. Therefore, the X-ray CT apparatus 100 according to the first embodiment makes it possible to prevent the execution of fluid analysis using CT image data that is not very appropriate in advance.

(Second Embodiment)
Next, a second embodiment will be described. Note that the configuration of the X-ray CT apparatus 100 according to the present embodiment is basically the same as the configuration of the X-ray CT apparatus 100 shown in FIG. Therefore, in the following, differences from the X-ray CT apparatus 100 according to the first embodiment will be mainly described, and constituent elements that play the same role as the constituent elements shown in FIG. Detailed description will be omitted.

  In the first embodiment described above, the case where the optimum cardiac phase is selected by dividing the range of the cardiac phase into a plurality of regions has been described as an example. In the second embodiment, a case where the optimum cardiac phase is selected without dividing the range of the cardiac phase will be described. For example, the X-ray CT apparatus 100 according to the second embodiment evaluates movements associated with pulsation with respect to the whole heart phase, and selects an optimal cardiac phase based on the evaluation result.

  FIG. 11 is a diagram for explaining an example of the selection process by the selection function 37c according to the second embodiment. FIG. 11 shows a case where the optimum cardiac phase is selected from the range of 70 to 99% cardiac phase. For example, the selection function 37c calculates the above-described SD value for each 1% cardiac phase in the range of 70 to 99% cardiac phase. Then, as shown in FIG. 11, the selection function 37 c selects the optimum cardiac phase by ranking the respective cardiac phases in descending order of the SD value. Here, the selection function 37c does not simply select the cardiac phases in order from the highest ranking, but selects the optimal cardiac phase in consideration of the time interval between the cardiac phases. For example, the optimal cardiac phase is selected such that the time interval between the cardiac phases is “5%” or more and the evaluation ranking based on the SD value is high.

  In the second embodiment, the vicinity of the upper end and the vicinity of the lower end of the range (for example, 70 to 99%) may be preferentially selected as the optimum cardiac phase. In this case, the selection function 37c first selects a cardiac phase having a higher rank near the upper end and the lower end of the range as the optimum cardiac phase. Then, the selection function 37c further selects the optimum cardiac phase from the cardiac phase separated from the selected optimum cardiac phase by a predetermined time interval (for example, “5%”) or more.

  Next, a processing procedure by the X-ray CT apparatus 100 according to the second embodiment will be described. FIG. 12 is a flowchart showing a processing procedure performed by the X-ray CT apparatus 100 according to the second embodiment. FIG. 12 shows a processing procedure when the optimum cardiac phase is selected from the range of 70 to 99% cardiac phase.

  Here, step S201 in FIG. 12 is realized by, for example, the processing circuit 37 calling and executing a program corresponding to the control function 37a from the storage circuit 35. Moreover, step S202 and step S203 are implement | achieved when the processing circuit 37 calls and executes the program corresponding to the selection function 37c from the memory circuit 35, for example. Further, step S204 is realized, for example, by the image reconstruction circuit 36 reading the corresponding program from the storage circuit 35 and executing it. Further, step S205 is realized, for example, when the processing circuit 37 calls and executes a program corresponding to the analysis function 37b from the storage circuit 35.

  In the X-ray CT apparatus 100 according to the present embodiment, first, the processing circuit 37 collects projection data (step S201). Then, the processing circuit 37 evaluates the movement in each cardiac phase with a cardiac phase of 70 to 99% (step S202). Then, the processing circuit 37 selects a cardiac phase based on the small amount of movement and the time interval (step S203). Thereafter, the image reconstruction circuit 36 reconstructs volume data corresponding to the selected cardiac phase (step S204). In step S204, when the volume data corresponding to each cardiac phase is reconstructed, the processing circuit 37 performs fluid analysis using the reconstructed volume data of each cardiac phase (step S205).

  As described above, according to the second embodiment, the selection function 37c evaluates the motion associated with the pulsation for each cardiac phase included in the range of the cardiac phase in which the motion associated with the pulsation is relatively small. Select the optimal cardiac phase. Therefore, the X-ray CT apparatus 100 according to the second embodiment makes it possible to acquire appropriate data when performing fluid analysis.

(Third embodiment)
Although the first and second embodiments have been described so far, the present invention may be implemented in various different forms other than the first and second embodiments described above.

  The optimal cardiac phase selection process described in the first and second embodiments described above can be executed at an arbitrary timing. For example, the selection function 37c selects a plurality of optimum cardiac phases during data transfer. For example, the selection function 37c selects the optimum cardiac phase using the volume data when transferring the reconstructed volume data to the medical information processing apparatus 300 or the like. Alternatively, the selection function 37c selects a plurality of optimum cardiac phases when starting the fluid analysis application. For example, the selection function 37c selects an optimum cardiac phase when an operation for starting a fluid analysis application is received via the input circuit 31. In this case, the selection function 37c may execute a selection process using cardiac phase data, or may execute a selection process using volume data (CT image data).

  In the above-described embodiment, the case where the image quality index is used as the image index has been described as an example. However, the embodiment is not limited to this, and the X-ray CT apparatus 100 can use various image indexes. For example, the X-ray CT apparatus 100 can use a region extraction capability as an image index. The X-ray CT apparatus 100 can perform extraction processing of the shape of a part such as the above-described blood vessel shape data. Here, the accuracy of the extraction of the part from the CT image data varies depending on the state of the collected CT image data. For example, when the movement associated with the heart beat is large, the accuracy of extracting the part may be reduced. That is, the X-ray CT apparatus 100 according to the third embodiment uses the extraction ability of the part caused by such image data as an image index.

  Specifically, the selection function 37c according to the third embodiment performs the selection of CT image data used for fluid analysis from among a combination of CT image data based on the extraction result of a predetermined part included in each CT image data. Extract a pair. Here, the selection function 37c uses, for example, the blood vessel wall of the coronary artery or the core wire of the coronary artery as the predetermined portion. Hereinafter, an example of selection of a plurality of time phases (selection of a set of CT image data) based on the extraction ability of these parts will be described.

  Here, first, in the X-ray CT apparatus 100 according to the third embodiment, CT image data of each time phase is reconstructed when extracting a part. That is, the image reconstruction circuit 36 reconstructs CT image data corresponding to each cardiac phase from the collected projection data for a plurality of heartbeats. For example, the image reconstruction circuit 36 reconstructs CT image data of each cardiac phase from each cardiac phase data of 70% to 99% cardiac phase.

  When the CT image data of each cardiac phase is reconstructed, the analysis function 37b extracts a part from the CT image data of each cardiac phase. Here, the analysis function 37b can extract a part from CT image data of each cardiac phase by various methods. For example, the analysis function 37b performs extraction processing on each CT image data to extract a blood vessel wall and a core line. That is, the analysis function 37b extracts parts from all CT image data by performing part extraction on all CT image data reconstructed by the image reconstruction circuit 36. Note that the analysis function 37b can appropriately use an existing algorithm as an extraction algorithm used for part extraction.

  The analysis function 37b extracts a region from CT image data of one cardiac phase, and aligns the CT image data from which the region has been extracted with the CT image data of another cardiac phase, so that A site in CT image data can also be extracted. In such a case, the analysis function 37b first extracts a blood vessel wall and a core line by performing extraction processing on CT image data of one cardiac phase. Next, the analysis function 37b aligns CT image data obtained by extracting blood vessel walls and cores with CT image data of other cardiac phases. For example, the analysis function 37b extracts a feature point from each CT image data to be subjected to the alignment process, and executes a non-rigid alignment process that is deformed to match the extracted feature points.

  For example, the analysis function 37b extracts corresponding feature points (anatomical feature points) from CT image data obtained by extracting blood vessel walls and core lines and CT image data of other cardiac phases. Then, the analysis function 37b calculates coordinate conversion information for matching the extracted feature points. For example, the analysis function 37b calculates coordinate conversion information in a three-dimensional coordinate system for matching feature points in CT image data of other cardiac phases with feature points in CT image data obtained by extracting blood vessel walls and core lines. That is, the analysis function 37b calculates conversion information for calculating a position corresponding to each position of CT image data obtained by extracting blood vessel walls and core lines in CT image data of other cardiac phases. The analysis function 37b can specify the coordinates of the blood vessel wall and the core line in the CT image data of other cardiac phases by using the conversion information for the extracted blood vessel wall and the core line coordinates.

  As described above, when a part is extracted, the selection function 37c selects a plurality of time phases (a set of CT image data) based on the extraction result. Hereinafter, an example of using the extraction result of the coronary artery blood vessel wall and an example of using the extraction result of the coronary artery core line will be described in order. For example, the selection function 37c selects a plurality of time phases based on the change in the cross-sectional area of the blood vessel wall extracted by the analysis function 37b. FIG. 13 is a diagram for explaining time phase selection by the selection function 37c according to the third embodiment. Here, in FIG. 13, the horizontal axis indicates the time phase, and the horizontal axis indicates the cross-sectional area. For example, the selection function 37c calculates a cross-sectional area of a predetermined cross section in the blood vessel wall extracted by the analysis function 37b for each CT image data, as indicated by the points in the graph of FIG. The selection function 37c compares the slope of the straight line L1 indicating a general change in the cross-sectional area of the coronary artery with the calculated cross-sectional area of each cardiac phase, CT image data is excluded from selection targets. For example, the selection function 37c excludes CT image data of the cardiac phase P1 shown in FIG. 13 from selection targets. That is, the selection function 37c compares adjacent cross-sectional area values with each other, and excludes CT image data having a cardiac phase having a large degree of deviation from the adjacent cross-sectional area values from selection targets.

As an example, the selection function 37c first determines whether there is a cardiac phase from four regions of “70 to 76%”, “77% to 83%”, “84% to 91%”, and “92 to 99%”. The cardiac phase is selected so that each time interval becomes equal to or greater than a predetermined threshold. Then, the selection function 37c calculates a cross-sectional area at each selected cardiac phase and compares it with each other. Furthermore, the selection function 37c determines whether or not the cross-sectional area has changed beyond the allowable range based on the slope of the straight line L1. Here, when the change in the cross-sectional area at each selected cardiac phase does not exceed the allowable range based on the slope of the straight line L1, the selection function 37c is “70 to 76%”, “77% to 83%”, “84”. The cardiac phase selected from the four regions of “% to 91%” and “92 to 99%” is determined as the optimum cardiac phase.
On the other hand, when the change in the cross-sectional area at each selected cardiac phase exceeds the allowable range based on the slope of the straight line L1, the selection function 37c reselects the cardiac phase based on a predetermined condition. For example, when the change in the cross-sectional area in the cardiac phase selected from “77% to 83%” exceeds the allowable range, the selection function 37c selects the cardiac phase again from “77% to 83%”. Here, the selection function 37c starts from “77% to 83%” so as to maintain the time interval with the selected cardiac phase in the adjacent regions “70 to 76%” and “84% to 91%” as much as possible. Reselect the cardiac phase.

  For example, when the cardiac phase is reselected, the selection function 37c selects a cardiac phase adjacent to the cardiac phase determined to be inappropriate. For example, if “79%” was selected in the first selection, the selection function 37c selects the heart phase of “78%” or “80%”.

  Alternatively, the selection function 37c selects cardiac phases separated by a predetermined number of phases (for example, 3%) when reselecting the cardiac phase. As an example, if “79%” was selected in the first selection, the selection function 37c selects a cardiac phase of “82%”. As described above, the accuracy of extracting a part from CT image data may decrease when the movement is large. Therefore, when the cardiac phase adjacent to the cardiac phase determined to be inappropriate is reselected, the reselected cardiac phase may also be inappropriate. Therefore, the selection function 37c can perform reselection with high accuracy by selecting the cardiac phases separated by a predetermined number of phases as described above.

  Note that the selection function 37c may be a case where the time interval between the four cardiac phases is readjusted when the cardiac phases are reselected. For example, when the cardiac phase of “79%” is inappropriate and the cardiac phase of “82%” is reselected, the selection function 37c has already been selected from “84% to 91%” and “92 to 99%”. Reselect the cardiac phase. That is, the selection function 37c reselects the cardiac phase at “84% to 91%” and the cardiac phase at “92 to 99%” so that the time interval between the cardiac phases becomes wide.

  In the above-described example, the case where the cross-sectional areas of the coronary arteries in each cardiac phase selected from the four regions are calculated and compared with each other has been described. However, the embodiment is not limited to this, and the cross-sectional line of the coronary artery in all cardiac phases may be calculated and compared with each other. In such a case, for example, the selection function 37c calculates the cross-sectional line of the coronary artery in all the cardiac phases, and determines the cardiac phase whose cross-sectional area does not exceed the allowable range based on the slope of the straight line L1. The time interval is selected to be wider.

  Further, in the above-described example, the case where the extraction of the coronary artery wall is determined using the cross-sectional area has been described. However, the embodiment is not limited to this. For example, it may be a case where whether or not the blood vessel wall of the coronary artery is extracted is used. In such a case, for example, the selection function 37c excludes CT image data from which the blood vessel wall has not been extracted from the selection target. Further, for example, the selection function 37c can determine the accuracy of extraction of the blood vessel wall using the similarity of the contour of the blood vessel wall. In such a case, for example, the selection function 37c compares the contour of the blood vessel wall in the cardiac phase to be determined with the contour of the blood vessel wall in the adjacent cardiac phase, and when the similarity is below a predetermined threshold value, The cardiac phase to be determined is excluded from the selection targets.

  Next, the case where the extraction result of the coronary artery core wire is used will be described. In such a case, for example, the selection function 37c determines the accuracy of the core line extraction by comparing the lengths of the core lines of the coronary artery extracted by the analysis function 37b. For example, when extracting the core lines from all the CT image data, the extraction of the core lines may fail and become shorter. The selection function 37c calculates the length of each core line extracted from the CT image data of each cardiac phase. Then, the selection function 37c compares the calculated lengths of the core wires between the respective cardiac phases, and excludes the cardiac phase whose core length is shorter than the others from the selection targets.

  In the example described above, the case has been described in which the selection function 37c automatically performs reselection based on the extracted blood vessel wall and core line. However, the embodiment is not limited to this. For example, the extraction result may be presented to the operator and an instruction to perform reselection may be accepted. In such a case, for example, the presentation function 37e causes the display 32 to display the result of the part extraction process performed by the analysis function 37b. The operator refers to the result of the extraction process displayed on the display 32 and determines whether to perform reselection. Then, the operator inputs an instruction as to whether or not to perform reselection via the input circuit 31. Here, when the input circuit 31 receives an instruction to reselect, the selection function 37c reselects the cardiac phase. On the other hand, when the input circuit 31 receives an instruction not to perform reselection, the analysis function 37b performs fluid analysis using CT image data of the selected cardiac phase.

  In the above, the example in the case of using the part extracting ability as the image index has been described. Next, a processing procedure performed by the X-ray CT apparatus 100 according to the third embodiment will be described. FIG. 14 is a flowchart showing a processing procedure performed by the X-ray CT apparatus 100 according to the third embodiment. FIG. 14 shows the procedure of processing when the coronary artery wall extraction ability is used as an image index.

  Here, step S301 in FIG. 14 is realized by, for example, the processing circuit 37 calling and executing a program corresponding to the control function 37a from the storage circuit 35. Further, step S302 is realized, for example, by the image reconstruction circuit 36 reading the corresponding program from the storage circuit 35 and executing it. Moreover, step S303 and step 307 are implement | achieved when the processing circuit 37 calls and executes the program corresponding to the analysis function 37b from the memory circuit 35, for example. Further, step S304, step S305, and step S310 are realized, for example, by the processing circuit 37 calling and executing a program corresponding to the selection function 37c from the storage circuit 35. Moreover, step S306 and step S308 are implement | achieved when the processing circuit 37 calls and executes the program corresponding to the presentation function 37e from the memory circuit 35, for example.

  In the X-ray CT apparatus 100 according to the present embodiment, first, the processing circuit 37 collects projection data (step S301). Then, the image reconstruction circuit 36 reconstructs the volume data of each cardiac phase (step S302). Subsequently, the processing circuit 37 extracts coronary vascular walls from the reconstructed volume data of each cardiac phase (step S303). Then, the processing circuit 37 divides the cardiac phase 70 to 99% into a plurality of regions (step S304), and selects a cardiac phase in each region (step S305).

  Subsequently, the processing circuit 37 determines whether or not the selected cardiac phase satisfies the condition (step S306). If the selected cardiac phase satisfies the condition (Yes at step S306), the processing circuit 37 executes fluid analysis using the volume data of each selected cardiac phase (step S307).

  On the other hand, when the selected cardiac phase does not satisfy the condition (No at Step S306), the processing circuit 37 displays a warning (Step S308) and determines whether or not a reselection operation has been accepted (Step S309). . If a reselection operation is accepted (Yes at step S309), the processing circuit 37 reselects the phase based on the condition (step S310). On the other hand, if the reselection operation has not been accepted (No at Step S309), the processing circuit 37 executes fluid analysis using the volume data of each selected cardiac phase (Step S307).

  In the above-described embodiment, the case where the X-ray CT apparatus 100 executes various processes has been described. However, the embodiment is not limited to this. For example, the medical information processing apparatus 300 may execute various processes. FIG. 13 is a diagram illustrating an example of a configuration of a medical information processing apparatus 300 according to the third embodiment.

  For example, as illustrated in FIG. 13, the medical information processing apparatus 300 includes an I / F (interface) circuit 310, a storage circuit 320, an input circuit 330, a display 340, and a processing circuit 350.

  The I / F circuit 310 is connected to the processing circuit 350 and controls transmission and communication of various data performed with various X-ray CT apparatuses 100 or image storage apparatuses 200 connected via the network 400. For example, the I / F circuit 310 is realized by a network card, a network adapter, a NIC (Network Interface Controller), or the like. In the present embodiment, the I / F circuit 310 receives CT image data from the X-ray CT apparatus 100 or the image storage apparatus 200 and outputs the received CT image data to the processing circuit 350.

  The storage circuit 320 is connected to the processing circuit 350 and stores various data. For example, the storage circuit 320 is realized by a semiconductor memory device such as a RAM (Random Access Memory) or a flash memory, a hard disk, an optical disk, or the like. In the present embodiment, the storage circuit 320 stores CT image data received from the X-ray CT apparatus 100 or the image storage apparatus 200.

  The input circuit 330 is connected to the processing circuit 350, converts an input operation received from the operator into an electrical signal, and outputs the electrical signal to the processing circuit 350. For example, the input circuit 330 is realized by a trackball, a switch button, a mouse, a keyboard, a touch panel, or the like.

  The display 340 is connected to the processing circuit 350 and displays various information and various image data output from the processing circuit 350. For example, the display 340 is realized by a liquid crystal monitor, a CRT (Cathode Ray Tube) monitor, a touch panel, or the like.

  The processing circuit 350 controls each component included in the image processing apparatus 300 in accordance with an input operation received from the operator via the input circuit 330. For example, the processing circuit 350 is realized by a processor. In the present embodiment, the processing circuit 350 causes the storage circuit 320 to store CT image data output from the I / F circuit 310. Further, the processing circuit 350 reads out CT image data from the storage circuit 320 and displays it on the display 340.

  Then, the processing circuit 350 executes a control function 351, a selection function 352, an acquisition function 353, a presentation function 354, and an analysis function 355, as shown in FIG. The control function 351 controls the entire medical information processing apparatus 300. The selection function 352 performs the same processing as the selection function 37c described above. The acquisition function 353 performs the same processing as the acquisition function 37d described above. The presentation function 354 performs the same processing as the presentation function 37e described above. The analysis function 355 executes the same processing as the analysis function 37b described above.

  In the embodiment described above, an example in which each processing function is realized by a single processing circuit (the processing circuit 37 and the processing circuit 350) has been described, but the embodiment is not limited thereto. For example, the processing circuit 37 and the processing circuit 350 may be configured by combining a plurality of independent processors, and each processor may implement each processing function by executing each program. The processing functions of the processing circuit 37 and the processing circuit 350 may be realized by appropriately distributing or integrating the processing functions in a single or a plurality of processing circuits.

  The term “processor” used in the description of each embodiment described above is, for example, a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), an application specific integrated circuit (ASIC), or a programmable. Means circuits such as logic devices (for example, Simple Programmable Logic Device (SPLD), Complex Programmable Logic Device (CPLD), and Field Programmable Gate Array (FPGA)) To do. Here, instead of storing the program in the storage circuit, the program may be directly incorporated in the circuit of the processor. In this case, the processor realizes the function by reading and executing the program incorporated in the circuit. In addition, each processor of the present embodiment is not limited to being configured as a single circuit for each processor, but may be configured as a single processor by combining a plurality of independent circuits to realize its function. Good.

  Here, the program executed by the processor is provided by being incorporated in advance in a ROM (Read Only Memory), a storage unit, or the like. This program is a file in a format installable or executable in these apparatuses, such as a CD (Compact Disk) -ROM, an FD (Flexible Disk), a CD-R (Recordable), a DVD (Digital Versatile Disk), or the like. It may be provided by being recorded on a computer-readable storage medium. The program may be provided or distributed by being stored on a computer connected to a network such as the Internet and downloaded via the network. For example, this program is composed of modules including each functional unit. As actual hardware, the CPU reads a program from a storage medium such as a ROM and executes it, whereby each module is loaded on the main storage device and generated on the main storage device.

  According to at least one embodiment described above, appropriate data can be easily selected.

  Although several embodiments of the present invention have been described, these embodiments are presented by way of example and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the spirit of the invention. These embodiments and their modifications are included in the scope and gist of the invention, and are also included in the invention described in the claims and the equivalents thereof.

100 X-ray CT apparatus 37b, 355 Analysis function 37c, 352 Selection function 37d, 353 Acquisition function 37e, 354 Presentation function 300 Medical information processing apparatus

Claims (18)

A collection unit for collecting image data according to a plurality of time phases including at least a part of a coronary artery of the heart;
Image data relating to a plurality of the image data is acquired, and image data is selected from among a plurality of the image data having a time interval larger than a predetermined time interval based on the image index in each image data. A selection unit for extracting a set of
Based on the set of the extracted image data, performing a fluid analysis on the coronary artery and obtaining a fluid parameter on the coronary artery;
An X-ray CT apparatus comprising:   The X-ray CT apparatus according to claim 1, wherein the selection unit extracts the set of image data from a time phase that becomes a wave free period in a heartbeat time phase of one heartbeat.   2. The X-ray CT apparatus according to claim 1, wherein the selection unit extracts the set of image data from a heart time phase of 70% or more in one heart beat time phase.   4. The X according to claim 1, wherein the selection unit extracts a set of image data in which an image quality index in each of the image data is equal to or greater than a predetermined threshold from the combination of the image data. Line CT device.   The selection unit according to any one of claims 1 to 3, wherein the selection unit extracts the set of image data from a combination of the image data based on an extraction result of a predetermined part included in each image data. The X-ray CT apparatus described.   The X-ray CT apparatus according to claim 5, wherein the predetermined part is a blood vessel wall of the coronary artery or a core wire of the coronary artery.   The selection unit evaluates the movement associated with the pulsation of the heart of each piece of image data included in the wave free period based on the image index, and the movement associated with the pulsation is relatively small. The X-ray CT apparatus according to claim 1, wherein a set of image data is extracted.   The X-ray CT apparatus according to claim 7, wherein the selection unit evaluates a motion associated with the pulsation based on a definition in a coronary artery region included in the image data.   The selection unit divides the Wave Free Period into a plurality of partial ranges, and each partial range corresponds to a time phase in which the movement associated with the pulsation is relatively small from among the time phases included in the partial range. The X-ray CT apparatus according to claim 7 or 8, wherein a set of image data is extracted.   The X-ray CT apparatus according to claim 9, wherein the selection unit divides the wave free period into the partial ranges so that widths of the plurality of partial ranges are approximated.   The X-ray CT apparatus according to claim 7 or 8, wherein the selection unit extracts image data corresponding to at least a time phase near the upper end and a time phase near the lower end in the Wave Free Period as the set of image data.   The selection unit extracts image data corresponding to the plurality of time phases so that a time interval between the time phases is equal to or greater than a predetermined threshold in the time phases included in the Wave Free Period. 8. The X-ray CT apparatus according to 8.   The said selection part extracts the said image data set so that each time interval between the adjacent time phases in the said image data set is large, and it approximates mutually. X-ray CT apparatus described in 1.   The X-ray CT apparatus according to claim 1, wherein the selection unit extracts the set of image data when the image data is transferred.   The X-ray CT apparatus according to claim 1, wherein the selection unit extracts the set of image data when the fluid analysis application is activated.   16. The X according to claim 1, further comprising a presentation unit that presents a warning to an operator when the set of image data extracted by the selection unit does not meet a predetermined condition. Line CT device. An image index related to image data related to a plurality of time phases including at least a part of a coronary artery of the heart is acquired, and a time larger than a predetermined time interval among the plurality of image data based on the image index in each image data A selection unit for extracting a set of image data from a combination of image data having an interval;
Based on the set of the extracted image data, performing a fluid analysis on the coronary artery and obtaining a fluid parameter on the coronary artery;
Comprising
Medical information processing device. An image index related to image data related to a plurality of time phases including at least a part of a coronary artery of the heart is acquired, and a time larger than a predetermined time interval among the plurality of image data based on the image index in each image data A selection step of extracting a set of image data from a combination of image data having an interval;
Analyzing the coronary artery based on the extracted set of image data and analyzing the coronary artery to obtain a fluid parameter;
Medical information processing program that causes a computer to execute.