JP6933498B2 - Medical information processing equipment, X-ray CT equipment and medical information processing program - Google Patents

Description

Embodiments of the present invention relate to a medical information processing device, an X-ray CT device, and a medical information processing program.

Conventionally, it is known that the causes of ischemic diseases of organs are roughly classified into blood circulation disorders and dysfunctions of organs themselves. For example, stenosis, which is an example of coronary artery blood circulation disorder, is a serious lesion leading to ischemic heart disease. In such ischemic heart disease, whether drug treatment should be performed, stent treatment, etc. should be performed. You need to judge. In recent years, as a diagnosis for evaluating hematogenous ischemia of coronary arteries, a method of measuring myocardial blood flow reserve (FFR: Fractional Flow Reserve) using a pressure wire in coronary angiography (CAG) using a catheter has been used. It is being recommended.

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

JP-A-2009-142300 Japanese Unexamined Patent Publication No. 2013-172793 Japanese Unexamined Patent Publication No. 2009-195586

An object to be solved by the present invention is to provide a medical information processing device, an X-ray CT device, and a medical information processing program capable of reducing the exposure dose at the time of 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 collecting unit includes past image data relating to a plurality of time phases including at least a part of the coronary arteries of the heart, and a new one time phase including at least a part of the coronary arteries and acquired after the acquisition of the past image data. Collect various image data. The alignment unit aligns the collected past image data with each other, and further aligns any one of the collected past image data with the new image data. When the generation unit reflects the shape of the new image data based on the result of the alignment process, the past image data other than the past image data for which the alignment process with the new image data is executed is performed. Generate composite image data corresponding to the phase. The analysis unit executes fluid analysis using the synthetic image data and obtains fluid parameters related to the coronary arteries.

FIG. 1 is a diagram showing an example of a configuration of a medical information processing system according to the first embodiment. FIG. 2 is a diagram showing an example of the configuration of the medical information processing device 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 the target image according to the first embodiment. FIG. 6A is a diagram for explaining an example of the alignment 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 an image generation process 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 showing a processing procedure by the medical information processing apparatus according to the first embodiment. FIG. 11 is a diagram showing an example of the configuration of the X-ray CT apparatus according to the second embodiment.

Hereinafter, embodiments of the medical information processing apparatus, the X-ray CT apparatus, and the medical information processing program according to the present application will be described in detail with reference to the accompanying drawings. The medical information processing device, the X-ray CT device, and the medical information processing program according to the present application are not limited to the embodiments shown 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 device will be described. Hereinafter, a medical information processing system including a medical information processing device will be described as an example. Further, in the following, as an example, an example in which a blood vessel of the heart is analyzed will be described.

FIG. 1 is a diagram showing an example of a configuration of a medical information processing system according to the first embodiment. As shown in FIG. 1, the medical information processing system according to the first embodiment includes an X-ray CT (Computed Tomography) device 100, an image storage device 200, and a medical information processing device 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 the network 400, as shown in FIG. The medical information processing system may be further connected to other medical image diagnostic devices such as an MRI device, an ultrasonic diagnostic device, and a PET (Positron Emission Tomography) device via the network 400.

The X-ray CT apparatus 100 collects CT image data (volume data) of a subject. Specifically, the X-ray CT apparatus 100 swirls the X-ray tube and the X-ray detector around the subject, detects the X-rays that have passed through the subject, and collects projection data. 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 devices. For example, the image storage device 200 is realized by a computer device such as a server device. In the present embodiment, the image storage device 200 acquires CT image data (volume data) from the X-ray CT device 100 via the network 400, and stores the acquired CT image data in or outside the device. To memorize.

The medical information processing device 300 acquires image data from various medical image diagnostic devices 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 processing on the acquired CT image data. Then, the medical information processing apparatus 300 displays the CT image data before or after performing the image processing on a display or the like.

FIG. 2 is a diagram showing an example of the configuration of the medical information processing device 300 according to the first embodiment. For example, as shown 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 controls the transmission and communication of various data performed with various medical image diagnostic devices or image storage devices 200 connected to the processing circuit 350 and 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 device 100 or the image storage device 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 element 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 device 100 or the image storage device 200.

The input circuit 330 is connected to the processing circuit 350, converts the input operation received from the operator into an electric signal, and outputs the input operation 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, and 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 of the medical information processing apparatus 300 in response to 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 stores the CT image data output from the I / F circuit 310 in the storage circuit 320. Further, the processing circuit 350 reads CT image data from the storage circuit 320 and displays it on the display 340.

Under such a configuration, the medical information processing apparatus 300 according to the present embodiment makes it possible to reduce the exposure dose at the time of follow-up. Specifically, the medical information processing apparatus 300 has been 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 or the like). By using medical images, the exposure dose during follow-up is reduced. For example, when the medical information processing apparatus 300 uses the 4-time phase data for fluid analysis, the medical information processing apparatus 300 uses the newly collected 1-phase medical image and the 3-time-phase medical image collected in the past at the time of follow-up. By performing fluid analysis, new medical images can be collected in one hour 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 in a blood vessel, and an index related to blood flow rate. FFR is the ratio of the pressure in the proximal part of the blood vessel near the heart to the pressure in the distal part far from the heart, for example, "FFR = Pd (distal pressure) / Pa (proximal pressure). ) ”. For example, when a blood vessel has a stenosis (a site to be treated), the pressure in the distal portion decreases due to the stenosis, so that the FFR value decreases. The fluid analysis is used to determine the necessity of treatment by calculating such an FFR value or the like. Examples of the mechanical index in the blood vessel include pressure, vector, and shear stress. In addition, as an index regarding the blood flow rate, the flow rate, the flow velocity, and the like can be mentioned.

Hereinafter, in the first embodiment, a case where CT image data of four phase phases is used in fluid analysis for a coronary artery will be described as an example. As shown in FIG. 2, the processing circuit 350 according to the present embodiment executes the control function 351, the alignment function 352, the extraction function 353, the image generation function 354, and the analysis function 355. Here, the control function 351 is an example of a collecting unit within the scope of claims. Further, the alignment function 352 is an example of an alignment unit within the scope of claims. Further, the extraction function 353 is an example of an extraction unit within the scope of claims. Further, the image generation function 354 is an example of a generation unit within the scope of claims. Further, the analysis function 355 is an example of an analysis unit within the scope of claims.

Here, first, the fluid analysis by the analysis function 355 will be described. The analysis function 355 executes the fluid analysis based on the CT image data. Specifically, the analysis function 355 extracts time-series blood vessel shape data representing the shape of blood vessels from three-dimensional CT image data. For example, the analysis function 355 reads the CT image data of the 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 to perform time-series blood vessels. Extract shape data.

Here, the analysis function 355 sets a target region for calculating an index value in the blood vessel region included in the CT image data. Specifically, the analysis function 355 sets the target region in the blood vessel region by an instruction or image processing by the operator via the input circuit 330. Then, the analysis function 355 uses, for example, the core wire (coordinate information of the core wire) of the blood vessel, the cross-sectional area of the blood vessel and the lumen in the cross section perpendicular to the core wire, and the cross section perpendicular to the core wire as the blood vessel shape data of the set target region. The distance from the core wire to the inner wall and the distance from the core wire to the outer wall in the columnar direction of the above are extracted from the CT image data. The analysis function 355 can extract various other blood vessel shape data depending on the analysis method.

Further, the analysis function 355 sets the analysis conditions for fluid analysis. Specifically, the analysis function 355 sets the physical characteristic value of blood, the condition of iterative calculation, the initial value of analysis, and the like as the analysis condition. For example, the analysis function 355 sets the viscosity, density, and the like of blood as physical property values of blood. Further, the analysis function 355 sets the maximum number of iterations in the iterative calculation, the relaxation coefficient, the allowable value of the residual, and the like as the conditions for the iterative calculation. Further, the analysis function 355 sets the flow rate, pressure, fluid resistance, initial value of the pressure boundary, and the like as the initial value of the analysis. The various values used by the analysis function 355 may be incorporated in the system in advance, or may be defined interactively by the operator.

In addition, the analysis function 355 sets a treatment target site in the blood vessel in the image data. Specifically, the analysis function 355 manually or automatically sets the treatment target site in the blood vessel. For example, the analysis function 355 sets a range received via the input circuit 330 as a treatment target site. In such a case, the input circuit 330 accepts a range for changing the analysis condition (treatment target site), and the range in which the analysis function 355 is accepted is set as the treatment target site. In addition, the analysis function 355 automatically sets the treatment target site based on the shape in the target region. For example, the analysis function 355 extracts a stenosis portion based on the shape in the target region, and sets a stenosis portion having a certain degree of stenosis or more as a treatment target site among the extracted stenosis portions. Any method can be used to extract the stenotic portion.

Then, the analysis function 355 calculates an index value related to blood flow in the blood vessel by fluid analysis using image data including the blood vessel. Specifically, the analysis function 355 executes fluid analysis using the blood vessel shape data and the 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 contour, blood vessel cross-sectional area and core wire, and setting conditions such as blood physical properties, iterative calculation conditions, and initial analysis values. , Calculate index values such as pressure, blood flow rate, blood flow rate, vector and shear stress for each predetermined position of blood vessel. 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 core line coordinates and cross-sectional information for LAD, which is a target region, from three-dimensional CT image data including aorta and coronary arteries. Further, the analysis function 355 sets the analysis conditions for the analysis of the extracted LAD. Then, the analysis function 355 performs a fluid analysis using the extracted blood vessel shape data of the LAD and the set conditions, for example, from the boundary of the entrance of the target region LAD to the boundary of the exit, a predetermined along the core line. Index values such as pressure, blood flow rate, blood flow velocity, vector and shear stress are calculated for each position. That is, the analysis function 355 calculates the distribution of pressure, blood flow rate, blood flow velocity, vector, shear stress, and the like for the target region. Then, the analysis function 355 calculates the FFR of each position in the target region based on, for example, the calculated pressure distribution.

As described above, the analysis function 355 extracts blood vessel shape data from the CT image data of the plurality of time phases collected over time, and fluid analysis using the extracted blood vessel shape data of the plurality of time phases and analysis conditions. By performing the above, the index value related to blood flow is calculated. As described above, the analysis function 355 executes the fluid analysis using the CT image data of the plurality of time phases, in order to improve the accuracy of the result of the fluid analysis. Here, in order to obtain highly accurate analysis results, 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 the cross-sectional area) as much as possible and has little movement due to pulsation. It is desirable to use CT image data of the time phase. That is, the time-series blood vessel shape data is based on pulsation while including 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 CT image data of the time phase with little image movement (blurring).

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 heartbeat is shown in the upper row, the movement of the heart is shown in the middle row, and the area of the coronary artery is shown in the lower row. Further, in FIG. 4, the lateral direction indicates time, and the heartbeat, the movement of the heart, and the time change of the area of the coronary artery are shown in association with each other. For example, the analysis function 355 executes fluid analysis using CT image data of the cardiac phase included in the range of 70% to 99% of the cardiac phase. Here, the cardiac phase of 70% to 99% is a time phase 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 by contraction and expansion, and as shown in the middle part of FIG. 4, the movement stabilizes in the latter half of the diastole (heart phase 70% to 99%). That is, the analysis function 355 can use the CT image data having a small movement associated with the pulsation by using the CT image data of the heart phase included in the heart phase of 70% to 99% in which the movement is stable.

Further, as shown in the lower part of FIG. 4, the area of the coronary artery is maximum at around 70% of the cardiac phase and minimum at around 99%. This is because blood begins to flow into the coronary arteries at around 70% of the cardiac phase, and then blood flows out as it progresses to 99%. The analysis function 355 can calculate a more accurate analysis result by using the CT image data in the range of the cardiac phase of 70% to 99% 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 arteries. Here, the analysis function 355 executes the fluid analysis by using the past CT image data such as before the operation or at the time of the examination at the time of follow-up after the operation or after the examination. Specifically, the analysis function 355 uses the 1-time phase CT image data collected at the time of follow-up after surgery or after the examination and the past CT image data of multiple time-phases to determine the state at the time of follow-up. Perform a fluid analysis for analysis. More specifically, the alignment function 352, the extraction function 353, and the 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 the analysis function 355 provides A fluid analysis is performed using the generated CT image data and the 1-time phase CT image data collected at the time of follow-up. The 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. Further, the control function 351 controls the collection of CT image data. Specifically, the control function 351 includes past image data relating to a plurality of time phases including at least a part of the coronary arteries of the heart, and at least a part of the coronary arteries, and is acquired after the acquisition of the past image data. The new image data of the one-time phase is controlled to be collected from the X-ray CT device 100 and the image storage device 200.

The alignment function 352 provides alignment processing between CT image data of multiple core phases collected over time in the past, CT image data of one core phase among the CT image data of multiple core phases in the past, and new ones. Alignment processing with the image data of one core phase is executed. More specifically, in the alignment function 352, in the past CT image data of a plurality of time phases, the past CT image data obtained by performing the alignment process with the new CT image data and the past other than the past CT image data. Alignment process with CT image data of.

FIG. 5 is a diagram for explaining an example of the target image according to the first embodiment. For example, as shown in FIG. 5, CT image data of "70%", "80%", "90%" and "99%" in past fluid analysis (for example, before surgery or at the time of examination) (hereinafter, , Also referred to as past image) is used, and when CT image data (hereinafter, also referred to as current image) with a cardiac phase of "74%" is collected at present (after surgery, after examination, etc.), the alignment function 352 Executes the alignment process between past images. Here, the alignment function 352 executes the alignment process of the past image data for executing the alignment process with the current image and other past image data.

FIG. 6A is a diagram for explaining an example of the alignment process between past images according to the first embodiment. For example, in the alignment function 352, since the core phase of the newly collected current image is "74%", the position between the past image and the current image of "70%", which is the closest core phase in the past image. Execute the matching process. In this case, as shown in FIG. 6A, the alignment function 352 executes the alignment process of the past image having the core phase "70%" and the other past images. That is, the alignment function 352 aligns the "70%" past image with the "80%" past image, and aligns the "70%" past image with the "90%" past image. The alignment process of the "70%" past image and the "99%" past image is executed respectively.

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 the alignment process of the non-rigid body which is deformed in order to match the extracted corresponding points. FIG. 6B is a diagram for explaining an example of the alignment process by the alignment function 352 according to the first embodiment. In FIG. 6B, the alignment process of the “70%” past image and the “80%” past image is shown. For example, as shown in FIG. 6B, the alignment function 352 extracts corresponding points "P1" to "P8" from the "70%" past image and the "80%" past image, respectively.

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

Similarly, the alignment function 352 aligns the "70%" past image with the "90%" past image, and positions the "70%" past image with the "99%" past image. Coordinate conversion information is calculated by executing the matching process.

Further, the alignment function 352 executes the alignment process of the past image and the present image. For example, the alignment function 352 aligns the newly collected CT image data of the core phase "74%" of the current image with the CT image data of the closest core phase "70%" in the past image. To execute. As for the alignment process between the past image and the current image, the alignment function 352 executes the same process as the above-described non-rigid body alignment process.

The extraction function 353 extracts the difference region by comparing the past CT image data in 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 therapeutic region) that has changed from the past to the present by extracting the difference between the past and present CT image data in which the alignment process has been executed. 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 core phase “70%” and the current CT image data of the core phase “74%”, and the positions of the non-rigid bodies are extracted. The processing by the extraction function 353 after the matching processing is executed is shown. For example, as shown in FIG. 7, the extraction function 353 extracts the stent region placed by the treatment by extracting the difference between the CT image data in which the alignment process has been executed.

The image generation function 354 is a composite image data corresponding to the time phase of the past CT image data other than the past CT image data in which the alignment process with the new CT image data is executed based on the result of the alignment process. To generate. Specifically, 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 to make a new one. Generates composite image data corresponding to the time phase of the past CT image data other than the CT image data and the past CT image data for which the alignment process has been executed.

For example, the image generation function 354 has a result of alignment processing between a past image having a core phase of "70%" and a past image having a core phase of "80%", and a past image having a core phase of "70%" and a core phase of "74". Using the result of the alignment process with the current image of "%", the current image of the cardiac phase "80%" is generated. Further, the image generation function 354 provides the result of the alignment processing between the past image having the core phase "70%" and the past image having the core phase "90%", and the past image having the core phase "70%" and the core phase "74". Using the result of the alignment process with the current image of "%", the current image of the cardiac phase "90%" is generated. Further, the image generation function 354 provides the result of the alignment processing between the past image having the core phase "70%" and the past image having the core phase "99%", and the past image having the core phase "70%" and the core phase "74". Using the result of the alignment process with the current image of "%", the current image of the cardiac phase "99%" is generated.

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 processing between the past image of the heart phase “70%” and the past image of the heart phase “80%”, and the past image of the heart phase “70%” and the heart phase “74%” are shown. A case where a current image having a cardiac phase of "80%" is generated by 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 sets the corresponding points “P1” to “P8” in the “70%” past image and the corresponding points “P1” to “P8” in the “80%” past image. The coordinate conversion information in the three-dimensional coordinate system to match with "", 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 conversion information obtained by integrating the coordinate conversion information in the three-dimensional coordinate system for matching with "P8", the current image of the cardiac phase "80%" can be obtained. Generate.

Similarly, the image generation function 354 generates a current image having a heart phase of "90%" and a current image having a heart phase of "99%", respectively. Then, the image generation function 354 generates CT image data in which the difference region extracted by the extraction function 353 is combined with the current image of each generated core phase. For example, the image generation function 354 specifies the position (coordinates) of the difference region in the current image of the generated core phase "80%", and replaces the specified position with the difference region, and replaces the specified position with the current CT of the core phase "80%". Generate image data. Further, the image generation function 354 specifies the position (coordinates) of the difference region in the current image of the generated core phase "90%", and replaces the specified position with the difference region, and replaces the specified position with the current CT of the core phase "90%". Generate image data. Further, the image generation function 354 specifies the position (coordinates) of the difference region in the current image of the generated core phase "99%", and replaces the specified position with the difference region, and replaces the specified position with the current CT of the core phase "90%". Generate image data.

Here, when the difference region includes the stent, the image generation function 354 corrects the region corresponding to the difference region in the generated current CT image data according to the size of the stent. For example, the image generation function 354 further deforms the 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 shown in FIG. 9, the image generation function 354 corrects the blood vessel wall in the current image having a cardiac phase of "80%" according to the size of the stent in the difference image when the stent is included in the difference region.

As an example, the image generation function 354 identifies 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 also 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 executes fluid analysis using the CT image data obtained by synthesizing the difference region with the CT image data. For example, the analysis function 355 has a current CT image data having a core phase "80%" including a difference region, a current CT image data having a core phase "90%" including a difference region, and a core phase "90%" including the difference region. A fluid analysis is performed using the current CT image data of "99%". The current CT image data of the heart phase "74%" may be the case where the new CT image data is used as it is, or the case where the past CT image data of the heart phase "70%" is used. It may be. When the past CT image data of the heart phase "70%" is used, the position for matching the past CT image data of the heart phase "70%" with the current CT image data of the heart phase "74%". The CT image data generated by executing the matching process and replacing the difference region is used.

Next, the procedure of processing by the medical information processing apparatus 300 according to the first embodiment will be described. FIG. 10 is a flowchart showing a processing procedure by the medical information processing apparatus 300 according to the first embodiment. Here, steps S101 to S103 in FIG. 10 are realized, for example, by the processing circuit 350 calling a program corresponding to the alignment function 352 from the storage circuit 320 and executing the program. Further, step S104 is realized, for example, by the processing circuit 350 calling a program corresponding to the extraction function 353 from the storage circuit 320 and executing the program. Further, steps S105 to S107 are realized, for example, by the processing circuit 350 calling a program corresponding to the image generation function 354 from the storage circuit 320 and executing the program. Further, step S108 is realized, for example, by the processing circuit 350 calling a program corresponding to the analysis function 355 from the storage circuit 320 and executing the program.

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

Then, the processing circuit 350 generates current CT image data corresponding to each past core 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 (affirmation in step S106), the processing circuit 350 corrects the current CT image data corresponding to each generated core phase (step S107).

Then, the processing circuit 350 executes the 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 (step S106 is negative), the processing circuit 350 proceeds to step S108 to obtain the current CT image data and the generated current CT image data. Performs fluid analysis using (step S108).

As described above, according to the first embodiment, the alignment function 352 performs alignment processing between past CT image data of a plurality of time phases collected over time and past CT images of a plurality of time phases. Of the data, the alignment process of the past CT image data of the 1-time phase and the new CT image data of the 1-time phase is executed. The extraction function 353 extracts the difference region by comparing the past CT image data in which the alignment process has been executed with the new CT image data. The image generation function 354 is CT image data corresponding to the time phase of the past CT image data other than the past CT image data in which the alignment process with the new CT image data is executed based on the result of the alignment process. To generate. The analysis function 355 executes fluid analysis using the CT image data obtained by synthesizing the difference region. Therefore, the medical information processing apparatus 300 according to the first embodiment can suppress the image collection at the time of follow-up to the one-time phase, and can reduce the exposure dose at the time of follow-up.

Further, according to the first embodiment, the alignment function 352 uses the past CT image data of the plurality of time phases, the past CT image data obtained by performing the alignment process with the new CT image data, and the past CT. Alignment processing with past CT image data other than image data is executed. The image generation function 354 uses the result of the alignment processing between the new CT image data and the past CT image data and the result of the alignment processing between the past CT image data to obtain the new CT image data and the position. The CT image data corresponding to the time phase of the 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 makes it possible to easily generate the current CT image data corresponding to the cardiac phase of the past CT image data.

Further, according to the first embodiment, when the difference region includes the stent, the image generation function 354 corrects the region corresponding to the difference region 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 highly accurate fluid analysis.

(Second Embodiment)
By the way, although the first embodiment has been described so far, it may be implemented in various different forms other than the above-mentioned first embodiment.

In the above-described embodiment, the case where the 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 the information on the course after the treatment, and transforms the past CT image data so as to be in the predicted state. Generate current CT image data.

Further, 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, and may be, for example, a case where all past images and present images are aligned. For example, in addition to the alignment of the "74%" current image and the "70%" past image, the alignment of the "74%" current image and the "80%" past image, "74%" It may be the case that the alignment of the current image and the past image of "90%" and the alignment of the current image of "74%" and the past image of "99%" are executed, respectively. In such a case, the extraction function 353 extracts the difference region from each CT image data after the alignment.

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

For example, the image generation function 354 has 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 corresponding points in the past image of "74%" with the coordinate conversion information in the three-dimensional coordinate system for matching the corresponding points in the current image of "74%", the past image of "70%" By transforming the CT image data, the CT image data of the current image having the coordinate phase "80%" is generated. Similarly, the image generation function 354 generates CT image data of other cardiac phases. The analysis function 355 executes fluid analysis using the generated CT image data.

Further, in the above-described embodiment, the case where the stent is placed in the 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 was collected before drug therapy, DCA (Directional Coronary Atherectomy), Rotational Coronary Atherectomy (Rotational Coronary Atherectomy), and the like. The above-mentioned processing is executed on the CT image data of the plurality of time phases and the CT image data of the one-time phase collected after the above-mentioned procedure. In this case, the extraction function 353 extracts the region whose shape has been deformed by the above procedure as the difference region. Then, the image generation function 354 generates CT image data obtained by synthesizing the extracted difference regions. Further, the analysis function 355 executes fluid analysis using the generated CT image data.

Further, 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, and may be, for example, a case where various processes are executed in the X-ray CT apparatus 100. FIG. 11 is a diagram showing 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 sleeper 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 the X-rays to the console 30. The X-ray irradiation control circuit 11 and the X-ray generator are generated. It has a device 12, a detector 13, a data acquisition circuit (DAS: Data Acquisition System) 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 in between, and rotates at high speed in a circular orbit centered on the subject P by a gantry drive circuit 16 described later. It is a circular frame.

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

Further, the X-ray irradiation control circuit 11 switches the wedge 12b. Further, the X-ray irradiation control circuit 11 adjusts the X-ray irradiation range (fan angle and cone angle) by adjusting the opening degree of the collimator 12c. In this embodiment, the operator may manually switch between a plurality of types of wedges.

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

The X-ray tube 12a is a vacuum tube that irradiates the subject P with an X-ray beam by a high voltage supplied by a high voltage generator (not shown), and the X-ray beam is sent to the subject P as the rotating frame 15 rotates. Irradiate against. 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 12a is continuously exposed to X-rays all around the subject P for full reconstruction, or half-reconstructable for half-reconstruction. It is possible to continuously expose X-rays within the range (180 degrees + fan angle). Further, under the control of the X-ray irradiation control circuit 11, the X-ray tube 12a can 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 X-rays exposed 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 the X-ray tube 12a to a range other than the specific tube position. Decreases the intensity of the emitted X-rays.

The wedge 12b is an X-ray filter for adjusting the X-ray dose of X-rays exposed 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 radiated from the X-ray tube 12a to the subject P have a predetermined distribution. It is a filter that attenuates. For example, the wedge 12b is a filter made of aluminum so as to have a predetermined target angle and 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 down 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 drive circuit 16 rotates the rotating frame 15 to rotate the X-ray generator 12 and the detector 13 on a circular orbit centered on the subject P.

The detector 13 is a two-dimensional array type detector (surface detector) that detects X-rays that have passed through the subject P, and the detection element sequence 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 that have passed through the subject P over a wide range, such as in the 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, sensitivity correction processing between channels, and the like on the X-ray intensity distribution data detected by the detector 13. The projected projection data is transmitted to the console 30 described later. For example, when X-rays are continuously exposed from the X-ray tube 12a during the rotation of the rotating frame 15, the data acquisition circuit 14 collects the projection data group for the entire circumference (360 degrees). Further, the data collection circuit 14 associates the tube position with each of the collected projection data and transmits the data to the console 30 described later. The tube position is information indicating the projection direction of the projection data. The sensitivity correction processing between channels may be performed by the preprocessing circuit 34, which will be described later.

The sleeper device 20 is a device on which the subject P is placed, and has a sleeper drive device 21 and a top plate 22 as shown in FIG. The sleeper drive device 21 moves the top plate 22 in the Z-axis direction to move the subject P into the rotating frame 15. The top plate 22 is a plate on which the subject P is placed.

The gantry 10 executes, for example, a helical scan in which the rotating frame 15 is rotated while the top plate 22 is moved to scan the subject P in a spiral shape. Alternatively, the gantry 10 executes a conventional scan in which the rotating frame 15 is rotated while the position of the subject P is fixed after the top plate 22 is moved to scan the subject P in a circular orbit. Alternatively, the gantry 10 executes a step-and-shoot method in which the position of the top plate 22 is moved at regular intervals to perform a conventional scan in a plurality of scan areas.

The console 30 is a device that accepts the operation of the X-ray CT device 100 by the operator and reconstructs the CT image data using the 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 has a mouse, keyboard, trackball, switch, button, joystick, etc. used by the operator of the X-ray CT device 100 to input various instructions and various settings, and information on the instructions and settings received from the operator. Is transferred to the processing circuit 37. For example, the input circuit 31 receives from the operator the imaging conditions for the CT image data, the reconstruction conditions for reconstructing the CT image data, the image processing conditions for the CT image data, and the like. Further, the input circuit 31 accepts an operation for selecting a test for the subject P. Further, the input circuit 31 accepts a designation operation for designating a portion on the image.

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

The scan control circuit 33 controls the operations of the X-ray irradiation control circuit 11, the gantry drive circuit 16, the data acquisition circuit 14, and the sleeper drive device 21 under the control of the processing circuit 37, thereby displaying the projection data on the gantry 10. Control the collection process. Specifically, the scan control circuit 33 controls the collection process of projection data in the imaging for collecting the positioning image (scano image) and the main imaging (scan) for collecting the image used for diagnosis.

The preprocessing circuit 34 performs logarithmic transformation processing and correction processing such as offset correction, sensitivity correction, and beam hardening correction on the projection data generated by the data collection circuit 14, and obtains the 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 collection circuit 14 and the projection data collected by the main shooting, and the storage circuit 35. Store in.

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 projection data for diagnosis collected by the main imaging. Further, the storage circuit 35 stores CT image data and the like reconstructed by the image reconstruction circuit 36 described later. Further, the storage circuit 35 appropriately stores the processing result by the 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 projection data of the positioning image and the projection data of the image used for diagnosis. Here, there are various reconstruction methods, and examples thereof include back projection processing. Further, as the back projection process, for example, a back projection process by the FBP (Filtered Back Projection) method can be mentioned. Alternatively, the image reconstruction circuit 36 can reconstruct the CT image data using the successive approximation method.

Further, the image reconstruction circuit 36 generates image data by performing various image processing on the CT image data. Then, 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 controls the operation of the gantry 10, the sleeper device 20, and the console 30 to control the entire X-ray CT device 100. Specifically, the processing circuit 37 controls the CT scan performed on the gantry 10 by controlling the scan control circuit 33. Further, the processing circuit 37 controls the image reconstruction processing and the image generation processing in the console 30 by controlling the image reconstruction circuit 36. Further, 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 the control function 37a, the alignment function 37b, the extraction function 37c, the image generation function 37d, and the analysis function 37e. The control function 37a controls the entire X-ray CT apparatus 100. The alignment function 37b executes the same processing as the alignment function 352 described above. The extraction function 37c executes the same processing 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 executes the same processing 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 (processing circuit 350 and processing circuit 37) has been described, but the embodiment is not limited to this. For example, the processing circuit 350 and the processing circuit 37 may be configured by combining a plurality of independent processors, and each processor may execute each program to realize each processing function. Further, each processing function of the processing circuit 350 and the processing circuit 37 may be appropriately distributed or integrated into a single or a plurality of processing circuits.

Further, the word "processor" used in the description of each of the above-described embodiments is, for example, a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), or an integrated circuit for a specific application (Application Specific Integrated Circuit: ASIC). , Programmable logic devices (eg, 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 configured to be directly embedded in the circuit of the processor. In this case, the processor realizes the function by reading and executing the program embedded in the circuit. Further, each processor of the present embodiment is not limited to the case where each processor is configured as a single circuit, and a plurality of independent circuits may be combined to be configured as one processor to realize its function. good.

Here, the program executed by the processor is provided by being incorporated in a ROM (Read Only Memory), a storage circuit, or the like in advance. This program is a file in a format that can be installed or executed on these devices, such as CD (Compact Disk) -ROM, FD (Flexible Disk), CD-R (Recordable), DVD (Digital Versatile Disk), etc. It may be recorded and provided on a computer-readable storage medium. Further, this 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 part described later. In actual hardware, the CPU reads a program from a storage medium such as a ROM and executes it, so that 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 at the time of follow-up can be reduced.

Although some embodiments of the present invention have been described, these embodiments are presented as examples 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 gist of the invention. These embodiments and modifications thereof are included in the scope and gist of the invention, as well as in the scope of the invention described in the claims and the equivalent scope thereof.

100 X-ray CT device 37b, 352 Alignment function 37c, 353 Extraction function 37d, 354 Image generation function 37e, 355 Analysis function 300 Medical information processing device

Claims (8)

Past image data relating to multiple time phases including at least a part of the coronary arteries of the heart, and new image data of one time phase including at least a part of the coronary arteries and acquired after the acquisition of the past image data. And the collection department that collects
An alignment unit that aligns the collected past image data with each other, and further aligns one of the collected 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 the past image data other than the past image data in which the alignment process with the new image data is executed. A generator that generates composite image data,
An analysis unit that executes fluid analysis using the synthetic image data and obtains fluid parameters related to the coronary arteries.
A medical information processing device equipped with. The new image data is image data relating to the coronary artery after the procedure for deforming the shape of the coronary artery is performed on 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. Before Symbol generator, said that past is reflected image data and the shape of the differential area based on the results of the alignment processing of the new image data, past the alignment process between the new image data is performed The medical information processing apparatus according to claim 1, wherein synthetic image data corresponding to the time phase of past image data other than image data is generated. In the past image data of the plurality of time phases, the alignment unit executes an alignment process of the past image data that has been subjected to the alignment process with the new image data and the past image data other than the past image data.
The generation unit uses 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 to perform the alignment process with the new image data. The medical information processing apparatus according to claim 1, which generates composite image data corresponding to the time phase of past image data other than the executed past image data. The generator claims that when the difference region is a region whose shape is deformed by a procedure for placing a stent, the region corresponding to the difference region in the synthetic image data is corrected according to the size of the stent. The medical information processing apparatus according to 2 or 3. The medical information processing apparatus according to any one of claims 1 to 5, wherein the new image data is generated by transforming the past image data. Past image data relating to multiple time phases including at least a part of the coronary arteries of the heart, and new image data of one time phase including at least a part of the coronary arteries and acquired after the acquisition of the past image data. And the collection department that collects
An alignment unit that aligns the collected past image data with each other, and further aligns one of the collected 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 the past image data other than the past image data in which the alignment process with the new image data is executed. A generator that generates composite image data,
An analysis unit that executes fluid analysis using the synthetic image data and obtains fluid parameters related to the coronary arteries.
An X-ray CT apparatus. Past image data relating to multiple time phases including at least a part of the coronary arteries of the heart, and new image data of one time phase including at least a part of the coronary arteries and acquired after the acquisition of the past image data. And the collection steps to collect
An alignment step of aligning the collected past image data with each other, and further aligning one of the collected 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 the past image data other than the past image data in which the alignment process with the new image data is executed. Generation steps to generate composite image data and
An analysis step of performing fluid analysis using the synthetic image data to obtain fluid parameters related to the coronary arteries, and
A medical information processing program that lets a computer execute.

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