JP2017217460A - Medical information processor, x-ray ct apparatus, and medical information processing program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a medical information processor capable of reducing an exposure dose at the time of follow-up, and an X-ray CT apparatus and a medical information processing program.SOLUTION: The medical information processor has a collection part, a positioning part, a generation part and an analysis part. The collection part collects past image data related to a plurality of time phases including at least a part of coronary arteries of a heart and new image data of one time phase which includes at least a part of the coronary arteries of the heart and is acquired after acquiring the past image data. The positioning part executes positioning among a plurality of pieces of past image data collected and executes positioning between any of the plurality of pieces of past image data and the new image data. The generation part generates combined image data corresponding to the plurality of time phases of the past image data other than the past image data for which positioning processing with the new image data is executed by reflecting shapes of the new image data on the basis of the a result of the positioning processing. The analysis part executes a fluid analysis by using the combined image data and obtains a fluid parameter for the coronary arteries.SELECTED DRAWING: Figure 2

Description

  Embodiments described herein relate generally to a medical information processing apparatus, an X-ray CT 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 2009-142300 A JP 2013-172793 A JP 2009-195586 A

  The problem to be solved by the present invention is to provide a medical information processing apparatus, an X-ray CT apparatus, and a medical information processing program that can reduce the exposure dose during follow-up.

  The medical information processing apparatus according to the embodiment includes a collection unit, an alignment unit, a generation unit, and an analysis unit. The collection unit includes at least a part of the coronary artery of the heart, the past image data related to a plurality of time phases, and at least a part of the coronary artery, and a new one-time phase acquired after the acquisition of the past image data Image data. The alignment unit performs alignment between the collected past image data, and further aligns any of the plurality of past image data with the new image data. The generation unit reflects the shape of the new image data based on the result of the alignment process, so that the past image data other than the past image data for which the alignment process with the new image data has been executed is performed. Composite image data corresponding to the phase is generated. The analysis unit performs fluid analysis using the composite image data, and obtains fluid parameters related to 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 medical information processing 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 a plurality of time phases used in the fluid analysis according to the first embodiment. FIG. 5 is a diagram for explaining an example of a target image according to the first embodiment. FIG. 6A is a diagram for explaining an example of a registration process between past images according to the first embodiment. FIG. 6B is a diagram for explaining an example of the alignment process by the alignment function according to the first embodiment. FIG. 7 is a diagram for explaining an example of processing by the extraction function according to the first embodiment. FIG. 8 is a diagram for explaining an example of image generation processing by the image generation function according to the first embodiment. FIG. 9 is a diagram for explaining an example of correction processing by the image generation function according to the first embodiment. FIG. 10 is a flowchart illustrating a processing procedure performed by the medical information processing apparatus according to the first embodiment. FIG. 11 is a diagram illustrating an example of the configuration of the X-ray CT apparatus according to the second embodiment.

  Exemplary embodiments of a medical information processing apparatus, an X-ray CT 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 medical information processing apparatus, the X-ray CT 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 a medical information processing apparatus will be described. Hereinafter, a medical information processing system including a medical information processing 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 medical information processing apparatus 300 according to the first embodiment is connected to the X-ray CT apparatus 100 and the image storage apparatus 200 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 X-ray CT apparatus 100 collects CT image data (volume 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.

  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.

  FIG. 2 is a diagram illustrating an example of the configuration of the medical information processing apparatus 300 according to the first embodiment. For example, as illustrated in FIG. 2, 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 medical image diagnostic apparatuses 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 medical information 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.

  Based on such a configuration, the medical information processing apparatus 300 according to the present embodiment can reduce the exposure dose during follow-up. Specifically, the medical information processing apparatus 300 is collected in the past when 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). Use medical images to reduce exposure during follow-up. For example, when the four-phase data is used for fluid analysis, the medical information processing apparatus 300 uses a newly collected one-phase medical image and three-phase medical images collected in the past during follow-up. By performing fluid analysis, a new medical image can be collected in one time phase and the exposure dose can be reduced.

  Examples of the index value related to blood flow include a myocardial blood flow reserve ratio (FFR: Fractional Flow Reserve), a mechanical index within 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 four-phase CT image data is used in the fluid analysis for the coronary artery will be described as an example. As illustrated in FIG. 2, the processing circuit 350 according to the present embodiment executes a control function 351, an alignment function 352, an extraction function 353, an image generation function 354, and an analysis function 355. Here, the control function 351 is an example of a collection unit in the claims. The alignment function 352 is an example of an alignment unit in the claims. The extraction function 353 is an example of an extraction unit in the claims. The image generation function 354 is an example of a generation unit in the claims. The analysis function 355 is an example of an analysis unit in the claims.

  Here, first, fluid analysis by the analysis function 355 will be described. The analysis function 355 performs fluid analysis based on the CT image data. Specifically, the analysis function 355 extracts time-series blood vessel shape data representing the blood vessel shape from the three-dimensional CT image data. For example, the analysis function 355 reads CT image data of a plurality of time phases collected over time from the storage circuit 320, 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 355 sets a target region for calculating an index value in a blood vessel region included in the CT image data. Specifically, the analysis function 355 sets a target region in the blood vessel region by an instruction from the operator via the input circuit 330 or image processing. The analysis function 355, for example, as the blood vessel shape data of the set target region, includes, 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, and 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 355 can extract other various blood vessel shape data according to the analysis method.

  Furthermore, the analysis function 355 sets analysis conditions for fluid analysis. Specifically, the analysis function 355 sets a physical property value of blood, a condition for repeated calculation, an initial value for analysis, and the like as analysis conditions. For example, the analysis function 355 sets the viscosity, density, etc. of blood as the physical property value of blood. Also, the analysis function 355 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. In addition, the analysis function 355 sets a flow rate, a pressure, a fluid resistance, an initial value of a pressure boundary, and the like as initial values for analysis. Various values used by the analysis function 355 may be incorporated in the system in advance, or may be defined interactively by the operator.

  The analysis function 355 sets a treatment target site in a blood vessel in the image data. Specifically, the analysis function 355 manually or automatically sets a treatment target site in the blood vessel. For example, the analysis function 355 sets the range received via the input circuit 330 as the treatment target site. In such a case, the input circuit 330 receives a range (treatment target site) for changing the analysis condition, and the analysis function 355 sets the received range as the treatment target site. The analysis function 355 automatically sets a treatment target region based on the shape in the target region. For example, the analysis function 355 extracts a stenosis part based on the shape in the target region, and sets a stenosis part having a certain stenosis degree or more among the extracted stenosis parts as a treatment target part. Note that any method can be used to extract the stenosis.

  The analysis function 355 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 355 performs fluid analysis using the blood vessel shape data and analysis conditions, and calculates an index value related to blood flow in the target region of the blood vessel. For example, the analysis function 355 is based on blood vessel shape data such as blood vessel lumen and outer wall contours, blood vessel cross-sectional areas and core wires, and 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. Then, the analysis function 355 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 355 according to the first embodiment. As shown in FIG. 3, for example, the analysis function 355 extracts blood vessel shape data including the 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. Further, the analysis function 355 sets analysis conditions for analysis on the extracted LAD. Then, the analysis function 355 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 the 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 355 calculates distributions such as pressure, blood flow rate, blood flow rate, vector, and shear stress for the target region. Then, the analysis function 355 calculates the FFR at each position in the target region, for example, based on the calculated pressure distribution.

  As described above, the analysis function 355 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. As described above, the analysis function 355 executes fluid analysis using CT image data of a plurality of time phases, in order to increase the accuracy of the result of fluid analysis. Here, in order to obtain a highly accurate analysis result, a plurality of CT image data of a plurality of time phases include a change in the shape of the coronary artery (for example, a change in cross-sectional area) as much as possible, and a plurality of motions associated with pulsation are small. It is desirable to use time-phase CT image data. 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).

  FIG. 4 is a diagram for explaining a plurality of time phases used in the fluid analysis 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 analysis function 355 performs fluid analysis using cardiac phase CT image data included in the range of 70% to 99% 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. In other words, the analysis function 355 can use CT image data having a small movement associated with the pulsation by using the CT image data of the cardiac phase included in the cardiac phase 70% to 99% where the movement is stable.

  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 analysis function 355 can calculate a more accurate analysis result by using CT image data within the range of 70% to 99% cardiac phase so as to include the change in the area of the coronary artery as much as possible.

  As described above, the analysis function 355 uses CT image data corresponding to a plurality of cardiac phases in the fluid analysis for the coronary artery. Here, the analysis function 355 performs fluid analysis by using past CT image data before and at the time of an examination at the time of follow-up after an operation or after an examination. Specifically, the analysis function 355 uses the CT image data of one time phase collected at the time of follow-up after surgery or examination and the past CT image data of a plurality of time phases to determine the state at the time of follow-up. Perform fluid analysis for analysis. More specifically, an alignment function 352, an extraction function 353, and an image generation function 354 described below generate CT image data of a plurality of cardiac phases simulating the state at the time of follow-up, and an analysis function 355 includes: Fluid analysis is executed using the generated CT image data and the CT image data of one time phase collected at the follow-up. Details of these will be described below.

  Returning to FIG. 2, the control function 351 executes overall control of the medical information processing apparatus 300. The control function 351 controls the collection of CT image data. Specifically, the control function 351 includes at least a part of the coronary artery of the heart and includes past image data related to a plurality of time phases and at least a part of the coronary artery, and is acquired after the acquisition of the past image data. Also, control is performed so that new image data of one time phase is collected from the X-ray CT apparatus 100 and the image storage apparatus 200.

  The alignment function 352 includes an alignment process between CT image data of a plurality of cardiac phases acquired over time in the past, and CT image data of one cardiac phase among the CT image data of a plurality of past cardiac phases and a new one. Alignment processing with image data of one cardiac phase is executed. More specifically, the alignment function 352 includes past CT image data that has been subjected to alignment processing with new CT image data and past past other than the past CT image data in the past CT image data of a plurality of time phases. Alignment processing with the CT image data is executed.

  FIG. 5 is a diagram for explaining an example of a target image according to the first embodiment. For example, as shown in FIG. 5, CT image data of “70%”, “80%”, “90%”, and “99%” in the fluid analysis in the past (for example, before surgery or at the time of examination) , Which is also referred to as a past image), and present (after surgery, post-examination, etc.) CT image data with a cardiac phase of “74%” (hereinafter also referred to as a current image) is collected. Performs a registration process between past images. Here, the alignment function 352 executes alignment processing between the current image and past image data for which alignment processing is performed, and other past image data.

  FIG. 6A is a diagram for explaining an example of a registration process between past images according to the first embodiment. For example, since the cardiac phase of the newly collected current image is “74%”, the alignment function 352 has a position between the past image of “70%” that is the closest cardiac phase in the past image and the current image. Execute the matching process. In this case, as shown in FIG. 6A, the alignment function 352 executes alignment processing between the past image of the cardiac phase “70%” and other past images. That is, the registration function 352 performs registration processing between the “70%” past image and the “80%” past image, registration processing between the “70%” past image and the “90%” past image, Alignment processing between the past image of “70%” and the past image of “99%” is executed.

  For example, the alignment function 352 extracts the corresponding points of the coronary arteries from the CT image data to be subjected to the alignment process, and executes a non-rigid alignment process that is deformed to match the extracted corresponding points. FIG. 6B is a diagram for explaining an example of alignment processing by the alignment function 352 according to the first embodiment. FIG. 6B shows the alignment process between the past image of “70%” and the past image of “80%”. For example, as shown in FIG. 6B, the alignment function 352 extracts corresponding points “P1” to “P8” from the past image of “70%” and the past image of “80%”, respectively.

  Then, the alignment function 352 calculates coordinate conversion information for matching the extracted corresponding points. For example, as shown in FIG. 6B, the alignment function 352 converts the corresponding points “P1” to “P8” in the past image of “70%” to the corresponding points “P1” to “P8” in the past image of “80%”. ", Coordinate conversion information in a three-dimensional coordinate system for matching each of the two is calculated.

  Similarly, the registration function 352 performs registration processing between the past image of “70%” and the past image of “90%”, and the position of the past image of “70%” and the past image of “99%”. The coordinate conversion information is calculated by executing the alignment process.

  Further, the alignment function 352 executes an alignment process between the past image and the current image. For example, the alignment function 352 aligns the newly acquired CT image data of the cardiac phase “74%” of the current image with the CT image data of “70%” that is the closest cardiac phase in the past image. Execute. Note that the alignment function 352 also performs the same processing as the alignment processing of the non-rigid body described above for the alignment processing of the past image and the current image.

  The extraction function 353 extracts the difference area by comparing the past CT image data on which the alignment process has been executed with the newly collected CT image data. That is, the extraction function 353 extracts a region (for example, a treatment region) that has changed from the past to the present by extracting a difference between the past and the current CT image data on which the alignment processing has been performed. FIG. 7 is a diagram for explaining an example of processing by the extraction function 353 according to the first embodiment. In FIG. 7, corresponding points “P1” to “P8” are extracted from the past CT image data of the cardiac phase “70%” and the current CT image data of the cardiac phase “74%”, and the position of the non-rigid body The process by the extraction function 353 after a matching process is performed is shown. For example, as illustrated in FIG. 7, the extraction function 353 extracts a difference between CT image data on which the alignment process has been performed, thereby extracting a stent region placed by treatment.

  Based on the result of the alignment process, the image generation function 354 generates composite image data corresponding to the time phase of past CT image data other than the past CT image data for which the alignment process with new CT image data has been executed. Is generated. Specifically, the image generation function 354 uses the result of the alignment process between new CT image data and past CT image data and the result of the alignment process between past CT image data to generate a new Composite image data corresponding to the time phase of past CT image data other than the past CT image data subjected to the alignment processing with the CT image data is generated.

  For example, the image generation function 354 outputs the result of the alignment process between the past image with the cardiac phase “70%” and the past image with the cardiac phase “80%”, the past image with the cardiac phase “70%”, and the cardiac phase “74”. The current image of the cardiac phase “80%” is generated using the result of the alignment process with the current image of “%”. Further, the image generation function 354 performs the alignment processing result between the past image having the cardiac phase “70%” and the past image having the cardiac phase “90%”, and the past image having the cardiac phase “70%” and the cardiac phase “74”. The current image of the cardiac phase “90%” is generated using the result of the alignment process with the current image of “%”. Further, the image generation function 354 performs the alignment processing result between the past image with the cardiac phase “70%” and the past image with the cardiac phase “99%”, the past image with the cardiac phase “70%”, and the cardiac phase “74”. The current image of the cardiac phase “99%” is generated using the result of the alignment process with the current image of “%”.

  FIG. 8 is a diagram for explaining an example of image generation processing by the image generation function 354 according to the first embodiment. In FIG. 8, the result of the alignment process between the past image of the cardiac phase “70%” and the past image of the cardiac phase “80%”, and the past image of the cardiac phase “70%” and the cardiac phase “74%”. The case where the current image of the cardiac phase “80%” is generated using the result of the alignment process with the current image is shown. For example, as shown in FIG. 8, the image generation function 354 converts the corresponding points “P1” to “P8” in the past image of “70%” to the corresponding points “P1” to “P8” in the past image of “80%”. And the corresponding points “P1” to “P8” in the past image of “70%”, and the corresponding points “P1” to “P1” in the current image of “74%”. By transforming the past image of “70%” using the coordinate transformation information obtained by integrating the coordinate transformation information in the three-dimensional coordinate system for matching with “P8”, the current image of the cardiac phase “80%” is transformed. Generate.

  Similarly, the image generation function 354 generates a current image having a cardiac phase “90%” and a current image having a cardiac phase “99%”. Then, the image generation function 354 generates CT image data obtained by combining the difference image extracted by the extraction function 353 with the generated current image of each cardiac phase. For example, the image generation function 354 specifies the position (coordinates) of the difference region in the current image of the generated cardiac phase “80%”, and replaces the specified position with the difference region to the current CT of the cardiac phase “80%”. Generate image data. Further, the image generation function 354 specifies the position (coordinates) of the difference area in the current image of the generated cardiac phase “90%”, and replaces the specified position with the difference area for the current CT of the cardiac phase “90%”. Generate image data. Further, the image generation function 354 specifies the position (coordinates) of the difference area in the current image of the generated cardiac phase “99%”, and replaces the specified position with the difference area for the current CT of the cardiac phase “90%”. Generate image data.

  Here, when a difference area includes a stent, the image generation function 354 corrects the area corresponding to the difference area in the generated current CT image data in accordance with the size of the stent. For example, the image generation function 354 further deforms the blood vessel wall of each CT image data so that the cross-sectional area of the stent is maintained. FIG. 9 is a diagram for explaining an example of correction processing by the image generation function 354 according to the first embodiment. For example, as illustrated in FIG. 9, the image generation function 354 corrects the blood vessel wall in the current image of the cardiac phase “80%” in accordance with the size of the stent in the difference image when the difference region includes a stent.

  For example, the image generation function 354 specifies the position of the stent in the current image of the cardiac phase “80%”, and deforms the blood vessel wall in contact with the specified position according to the size of the stent. Similarly, the image generation function 354 deforms the blood vessel wall according to the size of the stent for the current image of the cardiac phase “90%” and the current image of the cardiac phase “99%”.

  The analysis function 355 performs fluid analysis using CT image data obtained by synthesizing a difference region with CT image data. For example, the analysis function 355 includes the current CT image data of the cardiac phase “80%” including the difference region, the current CT image data of the cardiac phase “90%” including the difference region, and the cardiac phase “including the difference region”. 99% "current CT image data and fluid analysis is performed. The current CT image data with the cardiac phase “74%” may be the case where new CT image data is used as it is, or the past CT image data with the cardiac phase “70%” is used. It may be. When the past CT image data of the cardiac phase “70%” is used, the position for matching the past CT image data of the cardiac phase “70%” with the current CT image data of the cardiac phase “74%” The CT image data generated by executing the matching process and replacing the difference area is used.

  Next, a processing procedure performed by the medical information processing apparatus 300 according to the first embodiment will be described. FIG. 10 is a flowchart illustrating a processing procedure performed by the medical information processing apparatus 300 according to the first embodiment. Here, step S101 to step S103 in FIG. 10 are realized, for example, by the processing circuit 350 calling and executing a program corresponding to the alignment function 352 from the storage circuit 320. Further, step S104 is realized, for example, when the processing circuit 350 calls and executes a program corresponding to the extraction function 353 from the storage circuit 320. Steps S <b> 105 to S <b> 107 are realized, for example, by the processing circuit 350 calling and executing a program corresponding to the image generation function 354 from the storage circuit 320. Further, step S108 is realized, for example, when the processing circuit 350 calls and executes a program corresponding to the analysis function 355 from the storage circuit 320.

  In the medical information processing apparatus 300 according to the present embodiment, first, the processing circuit 350 executes an alignment process between CT image data of each past cardiac phase (step S101). Then, the processing circuit 350 acquires the current CT image data (step S102), and executes the alignment process between the past one-phase CT image data and the current CT image data (step S103). Thereafter, the processing circuit 350 generates a difference image by subtracting the past CT image data on which the alignment processing has been executed from the current CT image data (step S104).

  Then, the processing circuit 350 generates current CT image data corresponding to each past cardiac phase based on the alignment information (step S105), and determines whether or not the site included in the difference image is a stent. (Step S106). Here, when the site included in the difference image is a stent (Yes in step S106), the processing circuit 350 corrects the current CT image data corresponding to each generated cardiac phase (step S107).

  Then, the processing circuit 350 performs fluid analysis using the acquired current CT image data and the generated current CT image data (step S108). In step S106, when the site included in the difference image is not a stent (No in step S106), the processing circuit 350 proceeds to step S108, and acquires the acquired current CT image data, the generated current CT image data, and Is used to perform fluid analysis (step S108).

  As described above, according to the first embodiment, the alignment function 352 includes the alignment process between past CT image data of a plurality of time phases collected over time, and the past CT images of a plurality of time phases. Among the data, a registration process between the past CT image data of one time phase and the new CT image data of one time phase is executed. The extraction function 353 extracts the difference area by comparing the past CT image data on which the alignment process has been performed with new CT image data. The image generation function 354 generates CT image data corresponding to the time phase of past CT image data other than past CT image data for which alignment processing with new CT image data has been performed based on the result of the alignment processing. Is generated. The analysis function 355 performs fluid analysis using CT image data obtained by synthesizing the difference regions. Therefore, the medical information processing apparatus 300 according to the first embodiment can suppress the image collection at the time of follow-up to one time phase, and can reduce the exposure dose at the time of follow-up.

  In addition, according to the first embodiment, the registration function 352 includes, in the past CT image data of a plurality of time phases, new CT image data, past CT image data that has undergone the registration process, and the past CT image. Alignment processing with past CT image data other than image data is executed. The image generation function 354 uses the result of the alignment process between the new CT image data and the past CT image data and the result of the alignment process between the past CT image data, CT image data corresponding to the time phase of past CT image data other than the past CT image data for which the matching process has been executed is generated. Therefore, the medical information processing apparatus 300 according to the first embodiment can easily generate current CT image data corresponding to the cardiac phase of past CT image data.

  Further, according to the first embodiment, when the difference area includes a stent, the image generation function 354 corrects the area corresponding to the difference area in the CT image data according to the size of the stent. Therefore, the medical information processing apparatus 300 according to the first embodiment makes it possible to perform fluid analysis with high accuracy.

(Second Embodiment)
Although the first embodiment has been described so far, the present invention may be implemented in various different forms other than the first embodiment described above.

  In the above-described embodiment, the case where newly collected CT image data is used as the current CT image data has been described. However, the embodiment is not limited to this, and may be generated based on past CT image data, for example. In such a case, for example, the image generation function 354 predicts the current state of the coronary artery based on information regarding the progress after the treatment, and transforms past CT image data so that the predicted state is obtained, Current CT image data is generated.

  In the above-described embodiment, the case where one past image is aligned with the current image has been described. However, the embodiment is not limited to this. For example, all past images and the current image may be aligned. For example, in addition to the alignment of the current image of “74%” and the past image of “70%”, the alignment of the current image of “74%” and the past image of “80%”, “74%” It may be a case where the alignment between the current image and the “90%” past image and the alignment between the “74%” current image and the “99%” past image are performed. In such a case, the extraction function 353 extracts a difference area from each CT image data after alignment.

  Further, in the above-described embodiment, the case has been described in which the difference area between the past image and the current image is extracted and the extracted difference areas are combined. However, the embodiment is not limited to this, and may be a case where a difference area is not extracted, for example. In such a case, for example, the image generation function 354 uses the result of the alignment process between the new CT image data and the past CT image data and the result of the alignment process between the past CT image data, CT image data corresponding to the time phase of past CT image data other than the past CT image data subjected to the alignment processing with the new CT image data is generated.

  For example, the image generation function 354 includes coordinate conversion information in a three-dimensional coordinate system for matching the corresponding points in the “70%” past image with the corresponding points in the “80%” past image, and “70%”. Using the coordinate conversion information obtained by integrating the coordinate conversion information in the three-dimensional coordinate system for matching the corresponding points in the past image with the corresponding points in the current image of “74%”. By deforming the CT image data, CT image data of the current image having the cardiac phase “80%” is generated. Similarly, the image generation function 354 generates other cardiac phase CT image data. The analysis function 355 performs fluid analysis using the generated CT image data.

  In the above-described embodiment, the case where a stent is placed in a blood vessel has been described as an example. However, the embodiment is not limited to this, and CT image data before and after various procedures can be targeted. For example, the medical information processing apparatus 300 is collected before procedures such as drug therapy, DCA (Directional Coronary Atherectomy), and rotablator (Rotational Coronary Atherectomy). The above-described processing is performed on the CT image data of a plurality of time phases and the CT image data of one time phase collected after the above procedure. In this case, the extraction function 353 extracts a region whose shape has been deformed by the above-described procedure as a difference region. Then, the image generation function 354 generates CT image data obtained by combining the extracted difference areas. Furthermore, the analysis function 355 performs fluid analysis using the generated CT image data.

  In the above-described embodiment, the case where the medical information processing apparatus 300 executes various processes has been described. However, the embodiment is not limited to this. For example, the X-ray CT apparatus 100 may execute various processes. FIG. 11 is a diagram illustrating an example of the configuration of the X-ray CT apparatus 100 according to the second embodiment.

  As shown in FIG. 11, the X-ray CT apparatus 100 according to the second 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 12b 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. 11). Specifically, the detector 13 in the second embodiment has 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 using projection data collected by the gantry 10. As shown in FIG. 11, 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.

  Then, as shown in FIG. 11, the processing circuit 37 executes a control function 37a, an alignment function 37b, an extraction function 37c, an image generation function 37d, and an analysis function 37e. The control function 37a controls the entire X-ray CT apparatus 100. The alignment function 37b performs the same process as the alignment function 352 described above. The extraction function 37c performs the same process as the extraction function 353 described above. The image generation function 37d executes the same processing as the image generation function 354 described above. The analysis function 37e performs the same process as the analysis function 355 described above.

  In the above-described embodiment, an example in which each processing function is realized by a single processing circuit (the processing circuit 350 and the processing circuit 37) has been described, but the embodiment is not limited thereto. For example, the processing circuit 350 and the processing circuit 37 may be configured by combining a plurality of independent processors, and each processing function may be realized by each processor executing each program. The processing functions of the processing circuit 350 and the processing circuit 37 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), or an application specific integrated circuit (ASIC). Circuits such as programmable logic devices (for example, Simple Programmable Logic Device (SPLD), Complex Programmable Logic Device (CPLD), and Field Programmable Gate Array (FPGA)) Means. 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 circuit, 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 described later. 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, the exposure dose during follow-up can be reduced.

  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, 352 Positioning function 37c, 353 Extraction function 37d, 354 Image generation function 37e, 355 Analysis function 300 Medical information processing apparatus

Claims (8)

Past image data relating to a plurality of time phases including at least a part of a coronary artery of the heart, and new image data of one time phase including at least a part of the coronary artery and acquired after acquisition of the past image data; A collecting section for collecting
An alignment unit that performs alignment between the collected plurality of past image data, and further performs alignment between any of the plurality of past image data and the new image data;
By reflecting the shape of the new image data based on the result of the alignment process, it corresponds to the time phase of past image data other than the past image data for which the alignment process with the new image data has been executed. A generation unit for generating composite image data;
An analysis unit for performing fluid analysis using the composite image data and obtaining a fluid parameter related to the coronary artery;
A medical information processing apparatus comprising: The new image data is image data related to a coronary artery in which the coronary artery shape has been deformed by a procedure with respect to the coronary artery in the past image data,
The medical information processing apparatus according to claim 1, further comprising an extraction unit that extracts a region whose shape has been deformed by the procedure as a difference region. An extraction unit that extracts the difference area by comparing the past image data that has been subjected to the alignment process and the new image data;
The generation unit responds to the time phase of past image data other than the past image data on which the alignment processing with the new image data is performed by reflecting the shape of the difference area in the new image data. The medical information processing apparatus according to claim 1, wherein composite image data to be generated is generated. The alignment unit performs alignment processing of past image data that has been subjected to alignment processing with the new image data and past image data other than the past image data in the past image data of the plurality of time phases,
The generation unit performs the alignment process with the new image data using the result of the alignment process between the new image data and the past image data and the result of the alignment process between the past image data. The medical information processing apparatus according to claim 1, wherein synthetic image data corresponding to a time phase of past image data other than the executed past image data is generated.   The medical information processing apparatus according to claim 2, wherein when the difference area includes a stent, the generation unit corrects an area corresponding to the difference area in the composite image data according to a size of the stent.   The medical information processing apparatus according to claim 1, wherein the new image data is generated by deforming the past image data. Past image data relating to a plurality of time phases including at least a part of a coronary artery of the heart, and new image data of one time phase including at least a part of the coronary artery and acquired after acquisition of the past image data; A collecting section for collecting
An alignment unit that performs alignment between the collected plurality of past image data, and further performs alignment between any of the plurality of past image data and the new image data;
By reflecting the shape of the new image data based on the result of the alignment process, it corresponds to the time phase of past image data other than the past image data for which the alignment process with the new image data has been executed. A generation unit for generating composite image data;
An analysis unit for performing fluid analysis using the composite image data and obtaining a fluid parameter related to the coronary artery;
An X-ray CT apparatus comprising: Past image data relating to a plurality of time phases including at least a part of a coronary artery of the heart, and new image data of one time phase including at least a part of the coronary artery and acquired after acquisition of the past image data; Collecting steps to collect,
An alignment step of performing alignment between the plurality of collected past image data, and further aligning any of the plurality of past image data with the new image data;
By reflecting the shape of the new image data based on the result of the alignment process, it corresponds to the time phase of past image data other than the past image data for which the alignment process with the new image data has been executed. A generation step for generating composite image data;
Performing a fluid analysis using the composite image data to determine a fluid parameter for the coronary artery;
Medical information processing program that causes a computer to execute.

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