JP2019111207A - Medical information processing system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To reduce the load on an operator at the time of treatment. A medical information processing system according to an embodiment includes an acquisition unit, a setting unit, and an analysis unit. The acquisition unit acquires a plurality of two-dimensional images in chronological order in the first phase of the treatment of the subject, and is the second phase after the first phase of the treatment of the subject. Acquire a plurality of two-dimensional images in chronological order in the second phase. The setting unit uses the three-dimensional image of the subject generated before the treatment is performed, and the second setting unit corresponds to the first region of interest set in the plurality of two-dimensional images in the first phase. The region of interest of is set to a plurality of two-dimensional images in the second phase. The analysis unit analyzes the blood flow dynamics in the first region of interest and the second region of interest. [Selection diagram] Fig. 1

Description

  Embodiments of the present invention relate to a medical information processing system.

  In the treatment of liver cancer, a treatment called hepatic artery embolization (TAE: Transcatheter Arterial Embolization) or TACE: Transcatheter Arterial Chemo-Embolization, which embolizes a feeding blood vessel to cancer, is performed.

  Hepatic artery embolization is a therapeutic method that can only cut off the blood supply to cancer cells without losing the function of normal tissue because it only embolizes feeding blood vessels. In this treatment method, the operator performs, for example, angiography, and visually observes that the contrast agent stains the cancer cells by X-ray image. Then, the operator determines that the treatment is completed when the contrast agent does not stain cancer cells and nutrient vessels.

  Also, in recent years, a technique called parametric imaging (Parametric imaging) is known. This technique is a technique for extracting, as a quantitative value, a feature of temporal change in which a contrast agent administered to a blood vessel is diffused in each tissue. For example, in parametric imaging, the time density curve of each pixel is measured in images of a plurality of frames collected continuously, and parameters such as PH (Peak Height) and TTP (Time to peak) of this time density curve are output Be done. As a result, for example, the operator can quantitatively grasp the change in staining by the contrast agent during treatment by comparing the parameter immediately after the start of the treatment with the parameter under treatment.

JP, 2017-074123, A

  The problem to be solved by the present invention is to reduce the burden on the operator during treatment.

  A medical information processing system according to an embodiment includes an acquisition unit, a setting unit, and an analysis unit. The acquiring unit acquires a plurality of two-dimensional images in time series in a first phase when performing treatment of a subject, and is a time of performing treatment of the subject, the first after the first phase. A plurality of two-dimensional images are acquired in time series in the second phase. The setting unit uses a three-dimensional image of the subject generated prior to the implementation of the treatment to generate a second region corresponding to a first region of interest set in the plurality of two-dimensional images in the first phase. The region of interest is set to a plurality of two-dimensional images in the second phase. The analysis unit analyzes blood flow dynamics in the first region of interest and the second region of interest.

FIG. 1 is a diagram showing an example of the configuration of a medical information processing system according to the first embodiment. FIG. 2 is a flowchart showing a processing procedure by the processing circuit according to the first embodiment. FIG. 3 is a diagram for explaining the first embodiment. FIG. 4 is a flowchart showing the processing procedure of the processing circuit according to the first embodiment. FIG. 5 is a flowchart showing the processing procedure of the processing circuit according to the first embodiment. FIG. 6 is a flowchart showing the processing procedure of the processing circuit according to the first embodiment. FIG. 7 is a diagram for explaining the first embodiment. FIG. 8 is a diagram for explaining the first embodiment. FIG. 9 is a diagram for explaining the second embodiment. FIG. 10 is a flowchart showing the processing procedure of the processing circuit according to the second embodiment. FIG. 11A is a diagram for describing a second embodiment. FIG. 11B is a diagram for describing the second embodiment. FIG. 11C is a diagram for describing the second embodiment. FIG. 12 is a flowchart showing the processing procedure of the processing circuit according to the second embodiment. FIG. 13 is a diagram for explaining the second embodiment. FIG. 14 is a flowchart showing the processing procedure of the processing circuit according to the third embodiment. FIG. 15 is a diagram for explaining the third embodiment.

  Hereinafter, a medical information processing system according to an embodiment will be described with reference to the drawings. Further, hereinafter, a medical information processing system having a medical image processing apparatus and an X-ray diagnostic apparatus will be described. The embodiment is not limited to the following embodiment. In addition, the contents described in one embodiment apply in principle to the other embodiments as well. For example, when a PACS (Picture Archiving and Communication System) is introduced to a medical information processing system, each device is medical image data of DICOM (Digital Imaging and Communications in Medicine) format in which incidental information is added to medical image data, etc. Send and receive each other. Here, the incidental information includes, for example, a patient ID (Identifier) identifying a patient, an examination ID identifying an examination, a device ID identifying each device, a series ID identifying one imaging by each device, etc. Be

First Embodiment
FIG. 1 is a diagram showing an example of the configuration of the medical information processing system 1 according to the first embodiment. As shown in FIG. 1, the medical information processing system 1 according to the first embodiment includes an X-ray diagnostic apparatus 100 and a medical image processing apparatus 200.

  The X-ray diagnostic apparatus 100 includes a high voltage generator 11, an X-ray tube 12, a collimator 13, a top 14, a C-arm 15, and an X-ray detector 16. In addition, the X-ray diagnostic apparatus 100 according to the first embodiment includes the C-arm rotation and movement mechanism 17, the top moving mechanism 18, the C-arm and top mechanism control circuit 19, the aperture control circuit 20, and the processing. A circuit 21, an input interface 22 and a display 23 are provided. Further, the X-ray diagnostic apparatus 100 according to the first embodiment includes an image data generation circuit 24, a storage circuit 25, an image processing circuit 26, and a communication interface 27. The X-ray diagnostic apparatus 100 is also connected to the injector 30. And as shown in FIG. 1, each circuit is mutually connected, and the X-ray diagnostic apparatus 100 transmits / receives various electrical signals between each circuit, and transmits / receives an electrical signal with the injector 30.

  The injector 30 is a device for injecting a contrast agent from a catheter inserted into the subject P. Here, the contrast agent injection from the injector 30 is performed according to the injection instruction received via the processing circuit 21 described later. Specifically, the injector 30 executes a contrast agent injection according to a contrast agent injection condition including an injection start instruction of the contrast agent received from the processing circuit 21 described later, an injection stop instruction, and an injection rate. The injector 30 can also execute injection start or injection stop according to the injection instruction directly input to the injector 30 by the operator.

  In the X-ray diagnostic apparatus 100 shown in FIG. 1, each processing function is stored in the storage circuit 25 in the form of a program that can be executed by a computer. The C arm / top mechanism control circuit 19, the aperture control circuit 20, the processing circuit 21, the image data generation circuit 24, and the image processing circuit 26 read programs from the storage circuit 25 and execute them to correspond to the respective programs. It is a processor that realizes functions. In other words, each circuit in the state where each program is read has a function corresponding to the read program.

  The high voltage generator 11 generates a high voltage under the control of the processing circuit 21 and supplies the generated high voltage to the X-ray tube 12. The X-ray tube 12 generates X-rays using the high voltage supplied from the high voltage generator 11.

  The collimator 13 narrows down the X-ray generated by the X-ray tube 12 so that the region of interest of the subject P is selectively irradiated under the control of the diaphragm control circuit 20. For example, the collimator 13 has four slidable diaphragm blades. The collimator 13 slides these diaphragm blades under the control of the diaphragm control circuit 20 to narrow down the X-rays generated by the X-ray tube 12 and irradiate the object P with the X-rays. The top 14 is a bed on which the subject P is placed, and is disposed on a bed (not shown). The subject P is not included in the X-ray diagnostic apparatus 100.

  The X-ray detector 16 detects X-rays transmitted through the subject P. For example, the X-ray detector 16 has detection elements arranged in a matrix. Each detection element converts the X-rays transmitted through the subject P into an electrical signal and accumulates the signal, and transmits the accumulated electrical signal to the image data generation circuit 24.

  The C-arm 15 holds the X-ray tube 12, the collimator 13 and the X-ray detector 16. The X-ray tube 12, the collimator 13, and the X-ray detector 16 are disposed so as to face each other across the subject P by the C-arm 15. In addition, although the case where the X-ray diagnostic apparatus 100 is a single plane is mentioned as an example and demonstrated in FIG. 1, the embodiment is not limited to this, and may be a case of a biplane.

  The C-arm rotation and movement mechanism 17 is a mechanism for rotating and moving the C-arm 15, and the top moving mechanism 18 is a mechanism for moving the top 14. The C-arm and top mechanism control circuit 19 controls the C-arm rotation and movement mechanism 17 and the top movement mechanism 18 under the control of the processing circuit 21 to rotate or move the C-arm 15. Adjust the movement. The diaphragm control circuit 20 controls the irradiation range of the X-ray irradiated to the object P by adjusting the opening degree of the diaphragm blade of the collimator 13 under the control of the processing circuit 21.

  The image data generation circuit 24 generates image data using the electrical signal converted from the X-ray by the X-ray detector 16, and stores the generated image data in the storage circuit 25. For example, the image data generation circuit 24 performs current-voltage conversion, A (Analog) / D (Digital) conversion, parallel-serial conversion on the electric signal received from the X-ray detector 16 to generate image data. Do. As an example, the image data generation circuit 24 generates image data (mask image) captured in a state in which a contrast agent is not injected and image data (contrast image) captured in a state in which a contrast agent is injected. Do. Then, the image data generation circuit 24 stores the generated mask image and contrast image in the storage circuit 25.

  The storage circuit 25 receives and stores the image data generated by the image data generation circuit 24. For example, the storage circuit 25 stores image data of the subject P before and after the contrast agent is administered. Further, the storage circuit 25 stores a difference image to be described later.

  The image processing circuit 26 performs various image processing on the image data stored in the storage circuit 25. For example, the image processing circuit 26 reads the mask image and the contrast image stored in the storage circuit 25 and performs subtraction (Log sub) to generate a difference image.

  The image processing circuit 26 can minimize misregistration due to body movement by using one frame immediately before administration of the contrast agent as a mask image. The image processing circuit 26 can also execute noise reduction processing by an image processing filter such as a moving average (smoothing) filter, a Gaussian filter, or a median filter. That is, the image processing circuit 26 can perform preprocessing including positional deviation correction and noise removal on each of a plurality of X-ray image groups captured temporally using a contrast agent.

  The input interface 22 is realized by a track ball, a switch button, a mouse, a keyboard or the like for setting a predetermined area (for example, a target area of correction processing in a difference image). The input interface 22 is connected to the processing circuit 21, converts an input operation received from the operator into an electrical signal, and outputs the signal to the processing circuit 21.

  The display 23 displays a GUI (Graphical User Interface) for receiving an instruction of the operator, a difference image generated by the image processing circuit 26, a color image by parametric imaging, and the like.

  The communication interface 27 is connected to the processing circuit 21 and controls transmission and communication of various data performed with other apparatuses such as the medical image processing apparatus 200 connected via the network. For example, the communication interface 27 is realized by a network card, a network adapter, an NIC (Network Interface Controller) or the like. In FIG. 1, the communication interface 27 transmits the X-ray image stored in the storage circuit 25 to the medical image processing apparatus 200.

  The processing circuit 21 controls the overall operation of the X-ray diagnostic apparatus 100. For example, the processing circuit 21 executes various processes by reading and executing a program corresponding to a control function for controlling the entire apparatus from the storage circuit 25. For example, the processing circuit 21 controls the high voltage generator 11 according to the instruction of the operator transferred from the input interface 22 and adjusts the voltage supplied to the X-ray tube 12 to irradiate the subject P. Control X-ray dose and ON / OFF. Further, for example, the processing circuit 21 controls the C-arm / top mechanism control circuit 19 according to the instruction of the operator, and adjusts the rotation and movement of the C-arm 15 and the movement of the top 14. Further, for example, the processing circuit 21 controls the diaphragm control circuit 20 according to the instruction of the operator, and adjusts the opening degree of the diaphragm blade of the collimator 13 to irradiate the X-ray irradiated to the object P. Control the range.

  Further, the processing circuit 21 controls image data generation processing by the image data generation circuit 24, image processing by the image processing circuit 26, analysis processing, and the like according to an instruction of the operator. Further, the processing circuit 21 controls to display on the display 23 a GUI for receiving an instruction of the operator, an image stored in the storage circuit 25 and the like. The processing circuit 21 also controls the injection timing of the contrast agent by transmitting signals of the contrast agent injection start and end to the injector 30.

  The medical image processing apparatus 200 includes an input interface 201, a display 202, a storage circuit 203, a communication interface 204, and a processing circuit 205.

  The communication interface 204 is connected to the processing circuit 205, and controls transmission and communication of various data performed with other apparatuses such as various medical image diagnostic apparatuses connected via a network. For example, the communication interface 204 is realized by a network card, a network adapter, an NIC (Network Interface Controller) or the like. In FIG. 1, the communication interface 204 receives an X-ray image from the X-ray diagnostic apparatus 100 and outputs the received X-ray image to the processing circuit 205.

  The storage circuit 203 is connected to the processing circuit 205 and stores various data. For example, the memory circuit 203 is realized by a semiconductor memory element such as a random access memory (RAM), a flash memory, a hard disk, an optical disk, or the like. The storage circuit 203 stores the X-ray image received from the X-ray diagnostic apparatus 100. For example, the storage circuit 203 stores a mask image and a contrast image as an X-ray image. Alternatively, the storage circuit 203 stores the difference image as an X-ray image. Alternatively, the storage circuit 203 stores, as an X-ray image, a mask image, a contrast image, and a difference image. Further, the memory circuit 203 stores the processing result of the processing circuit 205.

  The input interface 201 is connected to the processing circuit 205, converts an input operation received from the operator into an electrical signal, and outputs the signal to the processing circuit 205. For example, the input interface 201 is realized by a trackball, a switch button, a mouse, a keyboard, a touch panel or the like.

  The display 202 is connected to the processing circuit 205, and displays various information and various image data output from the processing circuit 205. For example, the display 202 is realized by a liquid crystal monitor, a CRT (Cathode Ray Tube) monitor, a touch panel, or the like.

  The processing circuit 205 controls each component of the medical image processing apparatus 200 according to an input operation received from the operator via the input interface 201. For example, the processing circuit 205 is implemented by a processor. The processing circuit 205 causes the storage circuit 203 to store the X-ray image output from the communication interface 204. The processing circuit 205 also reads X-ray image data from the storage circuit 203 and displays it on the display 202.

  Further, as shown in FIG. 1, the processing circuit 205 executes an acquisition function 205a, a setting function 205b, an analysis function 205c, and a reception function 205d. Here, for example, each processing function executed as the acquisition function 205a, the setting function 205b, the analysis function 205c, and the reception function 205d which are components of the processing circuit 205 shown in FIG. It is recorded in the memory circuit 203 in a form. The processing circuit 205 is a processor that implements each function corresponding to each program by reading each program from the memory circuit 203 and executing the program. In other words, the processing circuit 205 in the state of reading out each program has each function shown in the processing circuit 205 of FIG.

  The example of the configuration of the medical information processing system 1 has been described above. Based on this configuration, in the medical information processing system 1 according to the present embodiment, parametric imaging (Parametric) is performed, for example, when objectively determining the progress of treatment and determining the end of treatment in endovascular treatment of liver cancer. technology is used. Parametric imaging is a technique of administering a contrast agent to a blood vessel to acquire an X-ray two-dimensional projection image, and parameterizing and displaying a feature amount of temporal change in the X-ray two-dimensional projection image. For example, it has become possible for the operator to proceed with treatment while grasping the hemodynamics supplied to the cancer tissue during treatment by comparing the parameters.

  However, in order to compare parameters before and after treatment using this parametric imaging, the operator sets a region of interest for each region treated and compares the parameters before and after treatment in the region of interest. Specifically, the operator sets a region of interest (ROI) in a portion of cancer tissue during treatment, and the blood flow in the portion of cancer tissue is reduced after treatment compared to before treatment. Make sure. In addition, the operator also sets an ROI on a portion of normal tissue, and confirms that the blood flow of normal tissue is not reduced after treatment as compared to before treatment. For this reason, after creating an image by the first contrast during treatment, it is necessary to set up an ROI. Since the operation of setting the ROI during treatment is time-consuming for the operator, it is desirable to eliminate the operation of setting the ROI.

  Therefore, in the first embodiment, the medical image processing apparatus 200 executes the support processing described below in order to reduce the load on the operator during treatment. That is, the medical image processing apparatus 200 acquires a plurality of two-dimensional images in time series in the first phase at the time of the treatment of the subject P, and at the time of the treatment of the subject P, the first A plurality of two-dimensional images are acquired in time series in a second phase after the phase. Subsequently, the medical image processing apparatus 200 uses the three-dimensional image of the subject P generated before the execution of the treatment, to the first region of interest set in the plurality of two-dimensional images in the first phase. A corresponding second region of interest is set to the plurality of two-dimensional images in the second phase. Then, the medical image processing apparatus 200 analyzes blood flow dynamics in the first region of interest and the second region of interest. The support processing is realized by the processing circuit 205 executing the acquisition function 205a, the setting function 205b, the analysis function 205c, and the reception function 205d.

  Hereinafter, the support process according to the first embodiment will be described with reference to FIGS. 2 to 8. 2, 4, 5 and 6 are flowcharts showing the processing procedure by the processing circuit 205 according to the first embodiment, and FIGS. 3, 7 and 8 explain the first embodiment. It is a figure for.

  First, a process of setting a region of interest in the three-dimensional image of the subject P generated before the implementation of the treatment will be described using FIGS. 2 and 3. FIG. 2 shows a flowchart for explaining the operation of the processing circuit 205 of the medical image processing apparatus 200, and explains which step of the flowchart corresponds to each component. The process shown in FIG. 2 is preferably performed prior to the treatment. For example, the process shown in FIG. 2 is a support process performed at the time of preparation of a treatment plan to be performed prior to treatment.

  Steps S1 to S4 are steps corresponding to the receiving function 205d. This is a step in which the receiving function 205 d is realized by the processing circuit 205 calling and executing a predetermined program corresponding to the receiving function 205 d from the storage circuit 203. In step S1, the reception function 205d determines whether preparation of a treatment plan has been received. Here, when it is not determined that the preparation of the treatment plan has been received (No in step S1), the reception function 205d repeats the process of step S1.

  On the other hand, when it is determined that the preparation of the treatment plan has been received (Yes at Step S1), the reception function 205d acquires a 3D blood vessel image (Step S2). For example, the reception function 205d generates a contrast image with a three-dimensional image (3D mask image) in the absence of a contrast agent generated by imaging a region including the treatment target site of the subject P using an X-ray CT apparatus or the like. A three-dimensional image (3D contrast image) in the presence of an agent is acquired from the storage circuit 203. Then, the reception function 205d obtains a 3D blood vessel image by subtracting the 3D mask image and the 3D contrast image. When the reception function 205d stores the 3D blood vessel image obtained by subtracting the 3D mask image and the 3D contrast image in the storage circuit 203, the reception function 205d may acquire the 3D blood vessel image from the storage circuit 203. Good.

  In addition, the three-dimensional image (3D blood vessel image, 3D mask image, 3D contrast image) acquired by the reception function 205d is not limited to the three-dimensional image generated by the X-ray CT apparatus, for example, MRI (Magnetic) It may be a three-dimensional image generated by a resonance imaging apparatus or the X-ray diagnostic apparatus 100. Further, the image acquired by the reception function 205d is not limited to a three-dimensional image, and is a four-dimensional image obtained by time-sequentially imaging the treatment target site of the object P in the presence of a contrast agent. It may be.

  In step S3, the reception function 205d displays a 3D blood vessel image on the display 202. Then, in step S4, the reception function 205d receives the setting of the region of interest. The setting of the region of interest by the reception function 205d will be described with reference to FIG. FIG. 3 shows an example of a blood vessel structure in which a cancer tissue 51 and a nutrient blood vessel (shaded portion in FIG. 3) for supplying nutrition to the cancer tissue 51 are depicted. For example, as illustrated in FIG. 3, the reception function 205 d receives, from an operator such as a surgeon, the setting of the region of interest 52 in a feeding blood vessel connected to the cancer tissue 51. In addition, although FIG. 3 demonstrated the case where the setting of the region of interest 52 was received to the nutrition blood vessel connected to the cancer tissue 51, embodiment is not limited to this. For example, the reception function 205d may receive the setting of the region of interest in the cancer tissue 51.

  Further, although the reception function 205d omits illustration in FIG. 3, the reception function 205d also receives the setting of the region of interest in the portion of normal tissue. For example, the reception function 205d receives the setting of the region of interest also in normal tissue connected to the same feeding blood vessel as the cancer tissue. In this manner, the reception function 205d receives the setting of the region of interest in the three-dimensional image. In the following, for convenience of explanation, a region of interest set as a feeding blood vessel or a normal tissue connected to a treatment site or a treatment site will be appropriately described as “output ROI”.

  In the description of FIG. 2, the reception function 205 d is described as receiving the setting of the region of interest in the 3D blood vessel image from the operator, but the embodiment is not limited to this. For example, in the medical image processing apparatus 200, when the TACE support function is implemented, the reception function 205d may automatically set a portion of cancer tissue in the 3D blood vessel image as a region of interest. More specifically, the reception function 205d automatically identifies a feeding blood vessel in the acquired 3D blood vessel image, and automatically segments a portion of cancer tissue. Then, the reception function 205d sets a portion of the cancer tissue that has been segmented as a region of interest.

  Subsequently, processing of setting a first region of interest in a plurality of two-dimensional images in the first phase using the three-dimensional image of the subject P generated prior to the implementation of the treatment using FIG. 4; Processing for setting a second region of interest corresponding to the first region of interest to a plurality of two-dimensional images in the second phase using the three-dimensional image of the subject P generated prior to the implementation of the treatment And explain. That is, the process shown in FIG. 4 is a support process performed at the time of treatment implementation. FIG. 4 shows a flowchart for explaining the operation of the processing circuit 205 of the medical image processing apparatus 200, and describes which step of the flowchart corresponds to each component.

  Step S11, step S12, step S15, step S16 and step S20 are steps corresponding to the acquisition function 205a. When the processing circuit 205 calls a predetermined program corresponding to the acquisition function 205 a from the storage circuit 203 and executes the program, the acquisition function 205 a is realized. In step S11, the acquisition function 205a determines whether the start of the treatment has been received. Here, when it is not determined that the start of the treatment has been received (No in step S11), the acquisition function 205a repeats the process of step S11.

  On the other hand, when it is determined that the start of the treatment has been received (Yes in step S11), the acquiring function 205a acquires a 2D blood vessel image of the first phase (step S12). Here, the first phase is a phase after the start of treatment and is the first phase in which a plurality of 2D contrast images are collected. For example, the acquisition function 205a generates a contrast image with a two-dimensional image (2D mask image) in the absence of a contrast agent, generated by imaging the region including the treatment target site of the subject P by the X-ray diagnostic apparatus 100 A two-dimensional image (2D contrast image) in the presence of an agent is acquired from the X-ray diagnostic apparatus 100. Here, the acquisition function 205a acquires a plurality of 2D contrast images captured in time series. Then, the acquisition function 205a acquires a plurality of 2D blood vessel images by subtracting the 2D mask image and each 2D contrast image.

  The acquiring function 205 a may store the memory circuit 25 when a plurality of 2D blood vessel images obtained by subtracting the 2D mask image and each 2D contrast image are stored in the memory circuit 25 of the X-ray diagnostic apparatus 100. You may acquire a 2D blood vessel image from. Thus, the acquisition function 205a acquires a plurality of two-dimensional images in time series in the first phase when the treatment of the subject P is performed.

  Steps S13 and S17 correspond to the setting function 205b. The setting function 205 b is realized by the processing circuit 205 calling and executing a predetermined program corresponding to the setting function 205 b from the storage circuit 203. In step S13, the setting function 205b performs region-of-interest setting processing on the plurality of 2D blood vessel images of the first phase acquired in step S12. That is, the setting function 205 b sets the first region of interest in the plurality of 2D blood vessel images of the first phase using the region of interest set in the three-dimensional image. The region-of-interest setting process by the setting function 205b will be described with reference to FIG.

  FIG. 5 shows a flowchart for explaining the operation of the setting function 205b. The process shown in FIG. 5 corresponds to step S13 shown in FIG. Steps S101 to S105 are steps corresponding to the setting function 205b. The setting function 205 b is realized by the processing circuit 205 calling and executing a predetermined program corresponding to the setting function 205 b from the storage circuit 203.

  In step S101, the setting function 205b acquires geometric information at the time of shooting. For example, the setting function 205b acquires geometrical information when the two-dimensional image acquired in step S12 is captured by the X-ray diagnostic apparatus 100. As an example, the setting function 205b includes a C-arm 15 (LAO, RAO, CRA, CAU), an SID (Source Image Receptor Distance), and an SOD (Source Object) at the time of imaging by the X-ray diagnostic apparatus 100. Distance), FOV (Field of View), etc. are acquired as geometrical information. The geometric information may be attached as incidental information in the two-dimensional image acquired in step S12.

  In step S102, the setting function 205b generates a 2D projection image from the 3D blood vessel image based on the geometrical information. For example, the setting function 205b acquires a 3D blood vessel image in which a region of interest is set in step S4 of FIG. 2, and projects a 3D blood vessel image using the geometrical information acquired in step S101 to generate a 2D projection image Do. That is, in step S102, the setting function 205b generates, from the 3D blood vessel image, a 2D projection image taken from substantially the same direction as the two-dimensional image taken by the X-ray diagnostic apparatus 100.

  In step S103, the setting function 205b aligns the 2D blood vessel image and the 2D projection image using an anatomical feature value. Then, in step S104, a motion vector is calculated from the alignment result. In step S105, the setting function 205b deforms the region of interest on the 3D blood vessel image based on the motion vector to set the region of interest on the 2D blood vessel image. In this manner, the setting function 205 b projects a three-dimensional image to generate a two-dimensional projection image based on the geometrical information at the time of acquiring the two-dimensional image in the first phase. Then, the setting function 205 b sets the first region of interest in the two-dimensional image in the first phase by aligning the two-dimensional image and the two-dimensional projection image in the first phase. In this way, the first region of interest is set as a feeding blood vessel or normal tissue connected to the treatment site or treatment site of the subject P.

  Return to FIG. Steps S14, S18 and S19 in FIG. 4 correspond to the analysis function 205c. The processing circuit 205 calls and executes a predetermined program corresponding to the analysis function 205 c from the storage circuit 203, thereby realizing the analysis function 205 c. In step S14, the analysis function 205c performs parameter value acquisition processing using the plurality of 2D blood vessel images of the first phase in which the region of interest is set in step S13. The parameter value acquisition processing by the analysis function 205c will be described using FIG.

  FIG. 6 shows a flowchart for explaining the operation of the analysis function 205c. The process shown in FIG. 6 corresponds to step S14 shown in FIG. Steps S201 to S203 correspond to the analysis function 205c. The processing circuit 205 calls and executes a predetermined program corresponding to the analysis function 205 c from the storage circuit 203, thereby realizing the analysis function 205 c.

  In step S201, the analysis function 205c identifies the inflow time from the plurality of 2D blood vessel images of the first phase in which the region of interest is set in step S13. Here, the inflow time is a parameter that is defined based on a time-series change of each pixel value, considering the change of the pixel value at each position of the 2D blood vessel image as the change of the contrast agent concentration. In other words, the analysis function 205 c analyzes all pixels of a plurality of 2D blood vessel images, and identifies the inflow time of the contrast agent injected into the object based on the temporal change of the pixel value at each position. In addition, arbitrary methods can be selected as the calculation method of inflow time. For example, as a method of calculating the inflow time, it is possible to select TTP (Time-to-Peak), which is a method of identifying a time in which the time change of the pixel value is maximum as the inflow time. Further, for example, as a method of calculating the inflow time, a method of identifying time in which a time change of pixel value reaches a predetermined value or a time in which a predetermined ratio is reached with respect to a maximum value in time change of pixel value TTA (Time-to-Arrival) which is

  Subsequently, in step S202, the analysis function 205c generates a color code. For example, in the case of generating parametric image data as a still image, the analysis function 205 c generates one color code. In addition, when generating parametric image data as a moving image, the analysis function 205 c generates a number of color codes corresponding to the number of frames included in the moving image.

  In step S203, the analysis function 205c generates parametric image data. For example, the analysis function 205 c generates parametric image data by assigning a color according to the temporal change of the pixel value to each pixel of the 2D blood vessel image. That is, the analysis function 205 c assigns a color according to the identified inflow time to each position to generate a color image.

  Return to FIG. In step S15, the acquisition function 205a determines whether the imaging of the second phase has been started. Here, the second phase is a phase after the start of treatment, and is a phase in which a plurality of 2D contrast images are collected after the first phase. When the acquisition function 205a does not determine that the imaging of the second phase is started (No in step S15), the process of step S15 is repeated.

  On the other hand, when it is determined that the imaging of the second phase is started (Yes in step S15), the acquiring function 205a acquires a 2D blood vessel image of the second phase (step S16). Here, the acquiring function 205a acquires, for example, the same number of 2D blood vessel images of the second phase at the same time interval as the 2D blood vessel image of the first phase acquired in step S12. That is, the acquisition function 205a acquires a plurality of two-dimensional images in time series in the second phase after the first phase at the time of the treatment of the subject P. The details of the process by the acquisition function 205a in step S15 are the same as the details of the process by the acquisition function 205a described in step S12.

  In step S17, the setting function 205b performs region-of-interest setting processing on the plurality of 2D blood vessel images of the second phase acquired in step S16. Here, the setting function 205 b sets a second region of interest corresponding to the first region of interest set in the plurality of two-dimensional images in the first phase to the plurality of two-dimensional images in the second phase . That is, the setting function 205 b uses a three-dimensional image of the subject P generated prior to the execution of the treatment, and corresponds to a first region of interest set in a plurality of two-dimensional images in the first phase. Two regions of interest are set to a plurality of two-dimensional images in the second phase. The details of the process by the setting function 205b in step S17 are the same as the details of the process by the setting function 205b described in step S13. In other words, the setting function 205 b executes the region of interest setting process described with reference to FIG. 5. That is, the setting function 205 b projects a three-dimensional image to generate a two-dimensional projection image based on geometrical information at the time of acquiring the two-dimensional image in the second phase. Then, the setting function 205 b sets the second region of interest in the two-dimensional image in the second phase by aligning the two-dimensional image and the two-dimensional projection image in the second phase. In this way, the second region of interest is set as a feeding blood vessel or normal tissue connected to the treatment site or treatment site of the subject P.

  In step S18, the analysis function 205c executes parameter value acquisition processing using the plurality of 2D blood vessel images of the second phase in which the region of interest is set in step S17. The details of the process by the analysis function 205c in step S18 are the same as the details of the process by the analysis function 205c described in step S14. In other words, the analysis function 205c executes the parameter value acquisition process described with reference to FIG.

  Through the process of step S18, the analysis function 205c generates, for example, parametric image data shown in FIG. In FIG. 7, an example of the three-dimensional image 60 of the subject P is shown on the left, an example of the parametric image 62 of the first phase generated in step S14 is shown in the center, and the second generated in step S18 is shown on the right. An example of the parametric image 64 of the phase of.

  As shown in FIG. 7, a region of interest 61 is set in the three-dimensional image 60. Further, in the first-phase parametric image 62 and the second-phase parametric image 64, a region of interest 63 and a region of interest 65 are respectively set using the region of interest 61 set in the three-dimensional image 60.

  Return to FIG. In step S19, the analysis function 205c calculates an index value. For example, the analysis function 205c calculates the index value of the first region of interest in the parametric image data generated in step S14 and the index value of the second region of interest in the parametric image data generated in step S18. In other words, the analysis function 205c calculates the ratio of the parameter value in the first region of interest to the parameter value in the second region of interest as an index value.

  The process of step S19 by the analysis function 205c will be described with reference to FIG. In FIG. 8, an example of the time concentration curve in the region of interest 63 and the region of interest 65 shown in FIG. 7 is shown. In FIG. 8, the horizontal axis indicates the elapsed time from the start of acquisition of a 2D blood vessel image in each phase, and the vertical axis indicates pixel values. The time concentration curve 63a in FIG. 8 shows the time change of the average value of pixel values in the region of interest 63 shown in FIG. 7, and the time concentration curve 65a in FIG. 8 shows the average value of pixel values in the region of interest 65 shown in FIG. Change over time.

  For example, the analysis function 205 c calculates the time density curve 63 a and the time density curve 65 a shown in FIG. 8 as index values, and displays the time density curve 63 a and the time density curve 65 a on the display 202. Alternatively, the analysis function 205c may calculate the ratio of pixel values at the elapsed time t1 shown in FIG. In this manner, the analysis function 205c analyzes blood flow dynamics in the first region of interest and the second region of interest.

  Return to FIG. In step S20, the acquisition function 205a determines whether the end of the treatment has been received. For example, the operator refers to the index value calculated in step S19 to determine whether to end the treatment. For example, if the ratio between the index value indicating blood flow to cancer tissue in the second phase and the index value indicating blood flow to cancer tissue in the first phase is less than 50%, the operator is treated Judge to finish. On the other hand, if the ratio of index values is 50% or more, the operator judges that the treatment is not ended. Here, when it is determined that the operator ends the treatment, the operator instructs the end of the treatment via the input interface 201. Then, when it is determined that the end of the treatment has been received (Yes in step S20), the acquisition function 205a ends the process.

  On the other hand, when it is not determined that the end of the treatment has been received (No at step S20), the acquiring function 205a proceeds to step S15. Thereby, the surgeon continues the treatment until, for example, the ratio of index values is less than 50%.

  As described above, in the first embodiment, the medical image processing apparatus 200 uses the region of interest (output ROI) set in the three-dimensional image to generate a plurality of first two-dimensional images in the first phase. Set the area of interest. In the first embodiment, the medical image processing apparatus 200 is set to a plurality of two-dimensional images in the first phase using the three-dimensional image of the subject P generated prior to the implementation of the treatment. A second region of interest corresponding to the first region of interest is set to the plurality of two-dimensional images in the second phase. Thereby, in the first embodiment, the operator can omit the operation of specifying the ROI in the 2D blood vessel image during the operation. As a result, according to the first embodiment, the burden on the operator during treatment can be reduced.

  In the first embodiment, the medical image processing apparatus 200 calculates, as an index value, a ratio between the parameter value in the first region of interest and the parameter value in the second region of interest. Here, if the cancerous tissue or a nutrient vessel supplying nutrition to the cancerous tissue is set as the first region of interest and the second region of interest, the operator objectively concludes the treatment by referring to the index value. It is possible to judge

  Furthermore, in the first embodiment, the medical image processing apparatus 200 sets normal tissue as the first region of interest and the second region of interest, and analyzes blood flow dynamics in the normal tissue. This enables the operator to confirm that the hemodynamics have not changed immediately after the start of treatment and at the end of treatment in normal tissue. This enables the operator to confirm the presence or absence of the influence on the hemodynamics of the normal tissue by treating the cancerous tissue. The medical image processing apparatus 200 sets, as the first region of interest and the second region of interest, a cancer blood vessel or a nutrient blood vessel supplying nutrition to the cancer tissue, and sets a normal tissue as the first region of interest and the second interest. It does not have to be set as an area.

Second Embodiment
In the first embodiment described above, it has been described that the region of interest is set in the cancer tissue or the feeding blood vessel leading to the cancer tissue, and the normal tissue. In the second embodiment, the case of further setting the region of interest in the blood vessel into which the contrast agent has been injected will be described.

  The configuration of the medical information processing system 1 according to the second embodiment is the same as the configuration of the medical information processing system 1 except that a part of the setting function 205 b and a part of the analysis function 205 c executed by the processing circuit 205 of the medical image processing apparatus 200 are different. The configuration is the same as that of the medical information processing system 1 according to the first embodiment shown in FIG. Therefore, in the second embodiment, the setting function 205 b and the analysis function 205 c will be described in detail.

  The support processing according to the second embodiment will be described below with reference to FIGS. 9 to 13. FIG. 9, FIG. 11A, FIG. 11B, FIG. 11C and FIG. 13 are diagrams for explaining the second embodiment, and FIG. 10 and FIG. 12 are processing procedures by the processing circuit 205 according to the second embodiment. Is a flowchart showing

  First, the support process performed at the time of preparation of the treatment plan implemented prior to treatment will be described. The reception function 205d according to the second embodiment receives the setting of the region of interest in the three-dimensional image as support processing executed at the time of preparation of the treatment plan. Here, in the second embodiment, for example, in addition to setting a region of interest to a cancer tissue or a nutrient blood vessel leading to a cancer tissue and a normal tissue, a blood vessel that governs a region to be treated in treatment Further set the region of interest in the region.

  The processing by the reception function 205d according to the second embodiment is executed, for example, at the time of creation of a treatment plan to be performed prior to treatment, as in the first embodiment. Further, details of the processing of the reception function 205d according to the second embodiment are the processing procedure described using FIG. 2 except that the setting of the region of interest is further received in the blood vessel region that governs the treatment target region in treatment. Is the same as The setting of the region of interest by the reception function 205d will be described with reference to FIG.

  FIG. 9 shows an example of a blood vessel structure in which a catheter 50, a cancer tissue 51, and a nutrient blood vessel (shaded portion in FIG. 9) for supplying nutrition to the cancer tissue 51 are depicted. The reception function 205d receives the setting of the region of interest 53 downstream of the catheter 50 from the operator such as the operator, as shown in FIG. In the following, for convenience of explanation, the region of interest set upstream of the feeding blood vessel connected to the treatment site and downstream of the catheter will be appropriately described as "input ROI".

  Further, as shown in FIG. 9, the reception function 205d receives the setting of the region of interest 52 in the feeding blood vessel connected to the cancer tissue 51 from the operator such as the operator, as in the first embodiment. In addition, although FIG. 9 demonstrated the case where the setting of the region of interest 52 was received to the nutrition blood vessel connected to the cancer tissue 51, embodiment is not limited to this. For example, the reception function 205d may receive the setting of the region of interest in the cancer tissue 51. Further, although the acceptance function 205d omits illustration in FIG. 9, the acceptance function 205d also accepts setting of the region of interest in the portion of normal tissue. For example, the reception function 205d receives the setting of the region of interest also in normal tissue connected to the same feeding blood vessel as the cancer tissue.

  Then, the support process performed at the time of treatment implementation is demonstrated. The processing procedure of the support processing performed at the time of treatment execution according to the second embodiment is different in the procedures of the region of interest setting processing (steps S13 and S17) and the parameter value acquisition processing (steps S14 and S18). Except for the above, it is the same as the processing procedure of the support processing performed at the time of treatment execution according to the first embodiment described using FIG. 4.

  Hereinafter, the region-of-interest setting process by the setting function 205b and the parameter value acquisition process by the analysis function 205c according to the second embodiment will be described. As in the first embodiment, the acquisition function 205a according to the second embodiment acquires a plurality of two-dimensional images in time series in the first phase when the treatment of the subject P is performed. Further, as in the first embodiment, the acquisition function 205a according to the second embodiment is in time series in the second phase after the first phase, when the treatment of the subject P is performed. Acquire multiple 2D images.

  The setting function 205b according to the second embodiment executes region-of-interest setting processing on the plurality of 2D blood vessel images of the first phase acquired in step S12 in step S13 shown in FIG. Here, the setting function 205 b sets a first region of interest in the plurality of 2D blood vessel images of the first phase, using the region of interest set in the three-dimensional image.

  The setting function 205b according to the second embodiment executes the region of interest setting process on the plurality of 2D blood vessel images of the second phase acquired in step S16 in step S17 shown in FIG. Here, the setting function 205 b sets a second region of interest corresponding to the first region of interest set in the plurality of two-dimensional images in the first phase to the plurality of two-dimensional images in the second phase . That is, the setting function 205 b uses a three-dimensional image of the subject P generated prior to the execution of the treatment, and corresponds to a first region of interest set in a plurality of two-dimensional images in the first phase. Two regions of interest are set to a plurality of two-dimensional images in the second phase. Details of processing by the setting function 205 b in step S 13 and step S 17 will be described using FIG. 10.

  FIG. 10 shows a flowchart for explaining the operation of the setting function 205b. The process shown in FIG. 10 corresponds to step S13 shown in FIG. Steps S301 to S306 correspond to the setting function 205b. The setting function 205 b is realized by the processing circuit 205 calling and executing a predetermined program corresponding to the setting function 205 b from the storage circuit 203.

  In step S301, the setting function 205b acquires geometrical information at the time of shooting, as in step S101 shown in FIG. In step S302, the setting function 205b extracts the center line of the blood vessel from the 2D blood vessel image and the 3D blood vessel image. For example, the setting function 205b performs thinning processing on the 3D blood vessel image in which the region of interest is set in step S4 in FIG. 2 and the 2D blood vessel image acquired in step S12 in FIG. .

  In step S303, the setting function 205b projects the center line of the blood vessel of the 3D blood vessel image based on the geometrical information to generate a 2D projection image. For example, the setting function 205b projects the center line of the blood vessel extracted from the 3D blood vessel image using the geometrical information acquired in step S301 to generate a 2D projection image. That is, in step S303, the setting function 205b generates a 2D projection image in substantially the same direction as the center line of the blood vessel extracted from the two-dimensional image captured by the X-ray diagnostic apparatus 100 from the center line of the 3D blood vessel image. Do.

  In step S304, the setting function 205b aligns the center line of the blood vessel of the two-dimensional image with the 2D projection image using the anatomical feature value. Then, in step S305, the setting function 205b calculates a motion vector from the alignment result. In step S306, the setting function 205b deforms the region of interest on the 3D blood vessel image based on the motion vector to set the region of interest on the 2D blood vessel image. In this manner, the setting function 205 b projects a three-dimensional image to generate a two-dimensional projection image based on the geometrical information at the time of acquiring the two-dimensional image in the first phase. Then, the setting function 205 b aligns the center line of the blood vessel in the two-dimensional image in the first phase with the center line of the blood vessel in the two-dimensional projection image to obtain the first two-dimensional image in the first phase. Set the area of interest.

  The process corresponding to step S17 shown in FIG. 4 is also similar to the procedure of the process shown in FIG. That is, in step S17, the setting function 205b projects a three-dimensional image to generate a two-dimensional projection image based on the geometrical information at the time of acquiring the two-dimensional image in the second phase. Then, the setting function 205 b aligns the center line of the blood vessel in the two-dimensional image in the second phase with the center line of the blood vessel in the two-dimensional projection image to obtain the second two-dimensional image in the second phase. Set the area of interest.

  In step S14 shown in FIG. 4, the analysis function 205c according to the second embodiment executes parameter value acquisition processing using a plurality of 2D blood vessel images of the first phase in which the region of interest is set in step S13. . Also, in step S18 shown in FIG. 4, the analysis function 205c according to the second embodiment performs parameter value acquisition processing using a plurality of 2D blood vessel images of the second phase in which the region of interest is set in step S17. Run. Here, the analysis function 205c according to the second embodiment generates a parameter image of the first phase and a parameter image of the second phase, which are corrected by the input function in the first region of interest. First, the significance of correction with the input function in the first region of interest will be described using FIGS. 11A to 11C. 11A to 11C, the case of using the time density curve in the input ROI of the first phase as the input function will be described.

  11A to 11C show an example of time concentration curves in the region of interest 52 and the region of interest 53 shown in FIG. In FIG. 11A, the time concentration curve 71 in the region of interest 52 in the first phase and the time concentration curve 70 in the region of interest 53 are shown. In the example shown in FIG. 9, the administered contrast agent passes through the region of interest 53, and then flows out into each branched blood vessel to reach the region of interest 52. Therefore, as shown in FIG. 11A, the peak of the pixel value of the time density curve 71 in the area of interest 52 appears behind the peak of the pixel value of the time density curve 70 in the area of interest 53. In the example shown in FIG. 11A, the pixel value of the peak of the time density curve 70 is PV2, and the pixel value of the peak of the time density curve 71 is PV1 (PV2> PV1).

  In FIG. 11B, the time concentration curve 73 in the region of interest 52 in the second phase and the time concentration curve 72 in the region of interest 53 are shown. Here, originally, the blood flow to the region of interest 52 decreases with the progress of the treatment. That is, if the treatment is progressing smoothly, the peak of the time concentration curve 73 in progress of treatment shown in FIG. 11B should be lower than the peak of the time concentration curve 71 immediately after the start of treatment shown in FIG. 11A.

  However, the pixel value PV1 of the peak of the time concentration curve 73 in progress of treatment shown in FIG. 11B is the same value as the pixel value PV1 of the peak of the time concentration curve 71 immediately after the start of treatment shown in FIG. 11A. On the other hand, in FIG. 11B, the pixel value PV3 (PV3> PV2) of the peak of the time concentration curve 72 in the region of interest 53 is higher than the pixel value PV2 of the peak of the time concentration curve 70 immediately after the start of treatment shown in FIG. 11A. ing. That is, the amount of contrast agent administered during the treatment progress shown in FIG. 11B is larger than the amount of contrast agent administered immediately after the start of treatment shown in FIG. 11A. When the amount of contrast agent administered in this manner is larger than the amount of contrast agent administered immediately after the start of treatment, the blood flow in the region of interest 52 does not apparently decrease even if the treatment is progressing smoothly. become.

  Therefore, the analysis function 205c corrects the 2D blood vessel image of the first phase and the 2D blood vessel image of the second phase using the time concentration curve 70 of the region of interest 53 immediately after the start of the treatment. FIG. 11C shows a time concentration curve 72a corrected with the time concentration curve 72 shown in FIG. 11B and a time concentration curve 73a corrected with the time concentration curve 73 using the time concentration curve 70 of the region of interest 53 immediately after the start of treatment. Show.

  As shown in FIG. 11C, the pixel value PV2 of the peak of the time concentration curve 72a after correction in the region of interest 53 is the same value as the pixel value PV2 of the peak of the time concentration curve 70 immediately after the start of treatment shown in FIG. 11A. That is, in FIG. 11C, it is possible to evaluate the blood flow volume at the treatment site after aligning the amount of the contrast agent administered immediately after the start of the treatment and the amount of the contrast agent administered during the treatment progress. In the example shown in FIG. 11C, the pixel value PV4 (PV4 <PV1) of the peak of the time concentration curve 73a after correction in the region of interest 52 which is the treatment site is the peak of the time concentration curve 71 immediately after the start of treatment shown in FIG. It is lower than the pixel value PV1.

  Subsequently, a processing procedure of parameter value acquisition processing by the analysis function 205 c according to the second embodiment will be described using FIG. 12. The process shown in FIG. 12 corresponds to steps S14 and S18 shown in FIG. Steps S401 to S403 correspond to the analysis function 205c. The processing circuit 205 calls and executes a predetermined program corresponding to the analysis function 205 c from the storage circuit 203, thereby realizing the analysis function 205 c.

  In step S401, the analysis function 205c corrects the 2D blood vessel image with the input function. That is, the analysis function 205 c normalizes the 2D blood vessel image using the time concentration curve in the input ROI of the first phase as an input function. Steps S402 to S404 shown in FIG. 12 correspond to steps S201 to S203 shown in FIG. 6, respectively.

  Through the processing shown in FIG. 12, the analysis function 205c generates, for example, parametric image data shown in FIG. In FIG. 13, an example of the three-dimensional image 80 of the subject P is shown on the left, an example of the parametric image 83 of the first phase generated in step S14 is shown in the center, and the second generated in step S18 is shown on the right. An example of the parametric image 86 of the phase of.

  As shown in FIG. 13, a region of interest 81 (input ROI) and a region of interest 82 (output ROI) are set in the three-dimensional image 80. Further, in the parametric image 83 of the first phase, a region of interest 84 and a region of interest 85 are set using the region of interest 81 and the region of interest 82 set in the three-dimensional image 80, respectively. Further, in the parametric image 86 of the second phase, a region of interest 87 and a region of interest 88 are set using the region of interest 81 and the region of interest 82 set in the three-dimensional image 80, respectively.

  Here, in the parametric image 83 and the parametric image 86 shown in FIG. 13, the amount of contrast agent to be administered is normalized. Therefore, the operator can determine, for example, by comparing the color code in the region of interest 85 and the region of interest 88, whether the blood flow to the treatment site is reduced.

  As described above, in the second embodiment, the medical image processing apparatus 200 uses the region of interest (input ROI) set in the three-dimensional image to generate a plurality of first two-dimensional images in the first phase. Set the area of interest. In the second embodiment, the medical image processing apparatus 200 is set to a plurality of two-dimensional images in the first phase using the three-dimensional image of the subject P generated prior to the execution of the treatment. A second region of interest corresponding to the first region of interest is set to the plurality of two-dimensional images in the second phase. Thereby, in the second embodiment, the operator can omit the operation of designating the ROI in the 2D blood vessel image during the operation. As a result, according to the second embodiment, the load on the operator during treatment can be reduced.

  In the second embodiment, the medical image processing apparatus 200 sets a region of interest (input ROI) in the blood vessel into which the contrast agent has been injected, whereby a time-density curve (AIF: Arterial input function) as an input function is obtained. Get). Further, in the second embodiment, the medical image processing apparatus 200 sets a region of interest (output ROI) in a tissue and acquires a time density curve. Then, in the second embodiment, the medical image processing apparatus 200 corrects the output value with the input value. Thus, in the second embodiment, the medical image processing apparatus 200 generates a parametric image normalized with the input ROI of the first phase. This makes it possible to properly compare the index values even if the amount of contrast agent administered is different. As a result, according to the second embodiment, the operator can accurately grasp hemodynamics. That is, according to the second embodiment, the operator can improve the comparison accuracy before and after the treatment.

  Furthermore, in the second embodiment, the end of treatment can be objectively determined by referring to the portion corresponding to the output ROI in the parametric image without calculating the index value of the output ROI. Become. In the second embodiment described above, the analysis function 205 c may calculate the blood flow in the first region of interest and the blood flow in the second region of interest.

  In the second embodiment described above, the reception function 205d has described the case of receiving the input ROI and the output ROI, but the embodiment is not limited to this. For example, the reception function 205d may receive only the input ROI.

Third Embodiment
In the first embodiment and the second embodiment described above, by setting the region of interest using the three-dimensional image of the subject P at the time of treatment planning, the plurality of two-dimensional images in the first phase can be The case where one region of interest is set and a second region of interest corresponding to the first region of interest is set to a plurality of two-dimensional images in the second phase has been described. However, in some cases, a three-dimensional image of the subject P can not be acquired at the time of treatment planning, or a region of interest is not set in the three-dimensional image of the subject P at the time of treatment planning.

  Therefore, in the third embodiment, the input ROI is set as a first region of interest in the 2D blood vessel image of the first phase, and the second region of interest corresponding to the first region of interest is set to the second phase. The case of setting a 2D blood vessel image will be described. In the third embodiment, it is assumed that the imaging angle by the X-ray diagnostic apparatus 100 in the first phase immediately after the start of the treatment is different from the imaging angle by the X-ray diagnostic apparatus 100 in the second phase. The configuration of the medical information processing system 1 according to the third embodiment is the same as the configuration of the medical information processing system 200 except that a part of the reception function 205d and a part of the setting function 205b executed by the processing circuit of the medical image processing apparatus 200 are different. The configuration is the same as the configuration of the medical information processing system 1 according to the first embodiment shown in FIG. Therefore, in the third embodiment, the receiving function 205d and the setting function 205b will be described in detail.

  FIG. 14 is a flowchart showing the processing procedure of the processing circuit 205 according to the third embodiment. The process shown in FIG. 14 is a support process that is performed when a treatment is performed. In the third embodiment, the support process is not performed at the time of preparation of the treatment plan to be performed prior to the treatment.

  Steps S501, S502, S506, S507, and S410 correspond to the acquisition function 205a. When the processing circuit 205 calls a predetermined program corresponding to the acquisition function 205 a from the storage circuit 203 and executes the program, the acquisition function 205 a is realized. In step S501, the acquisition function 205a determines whether the start of the treatment has been received. Here, when the acquisition function 205a does not determine that the start of the treatment has been received (No in step S501), the process of step S501 is repeated.

  On the other hand, when it is determined that the start of the treatment has been received (Yes at Step S501), the acquiring function 205a acquires a 2D blood vessel image of the first phase (Step S502). The process of step S402 shown in FIG. 14 is the same as the process of step S12 shown in FIG.

  Step S503 is a step corresponding to the reception function 205d. This is a step in which the receiving function 205 d is realized by the processing circuit 205 calling and executing a predetermined program corresponding to the receiving function 205 d from the storage circuit 203. In step S503, the reception function 205d receives the setting of the first region of interest in the 2D blood vessel image of the first phase acquired in step S502. That is, the reception function 205d receives the setting of the first region of interest in the two-dimensional image in the first phase. The accepting function 205 d is described as accepting the input ROI as a first region of interest.

  Steps S504 and S508 correspond to the setting function 205b. The setting function 205 b is realized by the processing circuit 205 calling and executing a predetermined program corresponding to the setting function 205 b from the storage circuit 203. In step S504, the setting function 205b sets a region of interest in the 3D blood vessel image. For example, the setting function 205b acquires a 3D blood vessel image as in step S2. Then, the setting function 205 b sets a region of interest corresponding to the first region of interest for which the setting has been received in step S 503 as a 3D blood vessel image. That is, the setting function 205 b sets a region of interest corresponding to the first region of interest in the three-dimensional image.

  As an example, the setting function 205 b predicts a position corresponding to the first region of interest in the 3D blood vessel image, based on the first region of interest received in step S 503. Here, since the input ROI is generally set in the blood vessel, there are not many candidates. Therefore, when the input ROI is uniquely determined, the setting function 205 b sets the uniquely determined position as the region of interest corresponding to the input ROI. The setting function 205 b may also receive a selection from the user when there are two or more input ROI candidates.

  Steps S505 and S509 correspond to the analysis function 205c. The processing circuit 205 calls and executes a predetermined program corresponding to the analysis function 205 c from the storage circuit 203, thereby realizing the analysis function 205 c. In step S505, the analysis function 205c executes parameter value acquisition processing using a plurality of 2D blood vessel images of the first phase in which the first region of interest is set in step S503. The details of the process by the analysis function 205c in step S505 are the same as the details of the process by the analysis function 205c described in step S14. In other words, the analysis function 205c executes the parameter value acquisition process described with reference to FIG.

  In step S506, the acquisition function 205a determines whether imaging in the second phase has been started. If the acquisition function 205a does not determine that the imaging of the second phase has been started (No at step S506), the process of step S506 is repeated.

  On the other hand, when it is determined that the imaging of the second phase is started (Yes at Step S506), the acquiring function 205a acquires a 2D blood vessel image of the second phase (Step S507). The details of the process by the acquisition function 205a in step S507 are the same as the details of the process by the acquisition function 205a described in step S16.

  In step S508, the setting function 205b performs region of interest setting processing on the plurality of 2D blood vessel images of the second phase acquired in step S507. Here, the setting function 205 b sets the second region of interest in the two-dimensional image in the second phase based on the region of interest set in the three-dimensional image as the region of interest corresponding to the first region of interest. That is, the setting function 205 b uses a three-dimensional image of the subject P generated prior to the execution of the treatment, and corresponds to a first region of interest set in a plurality of two-dimensional images in the first phase. Two regions of interest are set to a plurality of two-dimensional images in the second phase. The details of the process by the setting function 205b in step S508 are the same as the details of the process by the setting function 205b described in step S13. In other words, the setting function 205b executes the region-of-interest setting process described with reference to FIG. That is, the setting function 205 b projects a three-dimensional image to generate a two-dimensional projection image based on geometrical information at the time of acquiring the two-dimensional image in the second phase. Then, the setting function 205 b aligns the center line of the blood vessel in the two-dimensional image in the second phase with the center line of the blood vessel in the two-dimensional projection image to obtain the second two-dimensional image in the second phase. Set the area of interest. In the case where the plurality of 2D blood vessel images in the first phase and the plurality of 2D blood vessel images in the second phase are captured at the same angle, the setting function 205 b does not need to use the 3D blood vessel image. It is possible to set the second region of interest simply by enlarging or reducing the position of the first region of interest.

  In step S509, the analysis function 205c executes parameter value acquisition processing using the plurality of 2D blood vessel images of the second phase in which the region of interest is set in step S508. The details of the process by the analysis function 205c in step S509 are the same as the details of the process by the analysis function 205c described in step S14. In other words, the analysis function 205c executes the parameter value acquisition process described with reference to FIG.

  By the process of step S509, the analysis function 205c generates, for example, parametric image data shown in FIG. FIG. 15 is a diagram for explaining the third embodiment. 15, the left side shows an example of the three-dimensional image 90 of the subject P, the center shows an example of the parametric image 93 of the first phase generated in step S505, and the right side shows the second generated in step S509. An example of the parametric image 96 of the phase of.

  As shown in FIG. 15, a region of interest 94 (input ROI) is set in the parametric image 93 of the first phase. Then, in the three-dimensional image 90, a region of interest 91 (input ROI) corresponding to the region of interest 94 is set. Further, in the parametric image 96 of the second phase, a region of interest 97 is set using the region of interest 91 set in the three-dimensional image 90. In FIG. 15, although not set as an output ROI, a cancer tissue 92, a cancer tissue 95 and a cancer tissue 98 are illustrated.

  Here, in the parametric image 93 and the parametric image 96 shown in FIG. 15, the amount of contrast agent to be administered is normalized. Therefore, the operator can determine, for example, whether the blood flow to the treatment site is reduced by comparing the color codes of the cancer tissue 95 and the cancer tissue 98.

  It returns to FIG. In step S410, the acquisition function 205a determines whether the end of the treatment has been received. For example, the operator determines whether to end the treatment by referring to the parametric image generated in step S509. For example, if the blood flow to the cancerous tissue in the second phase is significantly lower than the blood flow to the cancerous tissue in the first phase, the operator decides to end the treatment. Here, when it is determined that the operator ends the treatment, the operator instructs the end of the treatment via the input interface 201. Then, when it is determined that the end of the treatment has been received (Yes at Step S410), the acquisition function 205a ends the process.

  On the other hand, when it is not determined that the end of the treatment has been received (No at Step S410), the acquisition function 205a proceeds to Step S506. Thereby, the operator continues the treatment until, for example, the blood flow to the cancer tissue in the second phase is significantly lower than the blood flow to the cancer tissue in the first phase.

  As described above, in the third embodiment, the medical image processing apparatus 200 receives the setting of the first region of interest in the plurality of two-dimensional images in the first phase. Then, the medical image processing apparatus 200 uses the three-dimensional image of the subject P generated before the implementation of the treatment, and corresponds to the first region of interest set in the plurality of two-dimensional images in the first phase. The second region of interest is set to a plurality of two-dimensional images in the second phase. Thus, according to the third embodiment, even if the imaging angle of the 2D blood vessel image in the first phase and the imaging angle of the 2D blood vessel image in the second phase are changed, the operator can It is possible to omit the operation of specifying the ROI in the 2D blood vessel image of the second phase.

  Although the example shown in FIG. 14 is described as not accepting the setting of the output ROI, the embodiment is not limited to this. For example, in step S503 shown in FIG. 14, the accepting function 205d may accept the setting of the output ROI together with the input ROI. In such a case, the analysis function 205 c may further calculate the index value after performing the parameter value acquisition process in step S 509. In addition, in step S503 illustrated in FIG. 14, the receiving function 205d may receive the setting of only the output ROI without receiving the input ROI.

(Other embodiments)
Embodiments are not limited to the above-described embodiments.

  Although the medical image processing apparatus 200 has described the case of executing support processing in the above-described embodiment, the embodiment is not limited to this. For example, in the X-ray diagnostic apparatus 100, support processing may be performed. In such a case, the processing circuit 21 of the X-ray diagnostic apparatus 100 performs the same support processing as the processing circuit 205 of the medical image processing apparatus 200 according to the first to third embodiments described above. That is, in the X-ray diagnostic apparatus 100, when executing support processing, the processing circuit 21 executes the acquisition function 21a, the setting function 21b, the analysis function 21c, and the reception function 21d. Here, for example, the acquisition function 21a executes the same process as the acquisition function 205a described above. The setting function 21b executes the same processing as the setting function 205b described above. The analysis function 21c executes the same processing as the above-described analysis function 205c. The reception function 21d executes the same processing as the reception function 205d described above.

  Further, in the embodiment described above, the case where the medical information processing system 1 includes the injector 30 has been described, but the embodiment is not limited to this. For example, the medical information processing system 1 may not include the injector 30. In such a case, the contrast agent is injected into the subject P by the operator.

  The word “processor” used in the above description is, for example, a central processing unit (CPU), a graphics processing unit (GPU), an application specific integrated circuit (ASIC), a programmable logic device (for example, It means circuits such as Simple Programmable Logic Device (SPLD), Complex Programmable Logic Device (CPLD), and Field Programmable Gate Array (FPGA). The processor implements a function by reading and executing a program stored in a memory circuit. Note that instead of storing the program in the memory circuit, the program may be directly incorporated in the circuit of the processor. In this case, the processor implements the function by reading and executing a program embedded in the circuit. Each processor according to the present embodiment is not limited to being configured as a single circuit for each processor, and may be configured as one processor by combining a plurality of independent circuits to realize the function. Good. Furthermore, a plurality of components in FIG. 1 may be integrated into one processor to realize its function.

  In the above description of the embodiment, each component of each illustrated device is functionally conceptual and does not necessarily have to be physically configured as illustrated. That is, the specific form of the dispersion and integration of each device is not limited to that shown in the drawings, and all or a part thereof is functionally or physically dispersed in any unit depending on various loads, usage conditions, etc. It can be integrated and configured. Furthermore, all or any part of each processing function performed in each device may be realized by a CPU and a program analyzed and executed by the CPU, or may be realized as wired logic hardware.

  Further, the control method described in the above embodiment can be realized by executing a control program prepared in advance by a computer such as a personal computer or a workstation. This control program can be distributed via a network such as the Internet. The control program can also be recorded on a computer-readable recording medium such as a hard disk, a flexible disk (FD), a CD-ROM, an MO, and a DVD, and can be executed by being read from the recording medium by a computer.

  According to at least one embodiment described above, the burden on the operator during treatment can be reduced.

  While certain embodiments of the present invention have been described, these embodiments have been presented by way of example only, and are not intended to limit the scope of the invention. These embodiments can be implemented in other various forms, and various omissions, replacements, and modifications can be made without departing from the scope of the invention. These embodiments and modifications thereof are included in the invention described in the claims and the equivalents thereof as well as included in the scope and the gist of the invention.

Reference Signs List 1 medical information processing system 200 medical image processing apparatus 205 processing circuit 205a acquisition function 205b setting function 205c analysis function 205d reception function

Claims (10)

A plurality of two-dimensional images are acquired in time series in a first phase during treatment of a subject, and in a second phase after the first phase when treatment of the subject is performed. An acquisition unit that acquires a plurality of two-dimensional images in time series;
A second region of interest corresponding to a first region of interest set in a plurality of two-dimensional images in the first phase using the three-dimensional image of the subject generated prior to the implementation of the treatment A setting unit configured to set a plurality of two-dimensional images in the second phase;
An analysis unit that analyzes blood flow dynamics in the first region of interest and the second region of interest;
, A medical information processing system.   The setting unit projects the three-dimensional image to generate a two-dimensional projection image on the basis of geometrical information of an imaging system at the time of acquiring the two-dimensional image in the second phase, and the second The medical information processing system according to claim 1, wherein the second region of interest is set in the two-dimensional image in the second phase by aligning the two-dimensional image in the phase with the two-dimensional projection image.   The setting unit projects the three-dimensional image to generate a two-dimensional projection image on the basis of geometrical information of an imaging system at the time of acquiring the two-dimensional image in the second phase, and the second The second region of interest is set in the two-dimensional image in the second phase by aligning the center line of the blood vessel in the two-dimensional image in the phase with the center line of the blood vessel in the two-dimensional projection image. The medical information processing system according to Item 1. It further comprises a reception unit for receiving setting of a region of interest in the three-dimensional image,
The medical information processing system according to any one of claims 1 to 3, wherein the setting unit sets the first region of interest using the region of interest set in the three-dimensional image.   The setting unit projects the three-dimensional image to generate a two-dimensional projection image based on geometrical information at the time of acquiring the two-dimensional image in the first phase, and generates the two-dimensional projection image. The medical information processing system according to claim 4, wherein the first region of interest is set in the two-dimensional image in the first phase by aligning the two-dimensional projection image with the two-dimensional image.   The setting unit projects the three-dimensional image to generate a two-dimensional projection image based on geometrical information at the time of acquiring the two-dimensional image in the first phase, and generates the two-dimensional projection image. The first region of interest is set in the two-dimensional image in the first phase by aligning the center line of the blood vessel in the two-dimensional image with the center line of the blood vessel in the two-dimensional projection image. Medical information processing system as described. And a reception unit for receiving the setting of the first region of interest in the two-dimensional image in the first phase,
The setting unit sets a region of interest corresponding to the first region of interest in the three-dimensional image, and based on the set region of interest, the second region of interest in the two-dimensional image in the second phase is set. The medical information processing system according to any one of claims 1 to 3, which is set. The first region of interest and the second region of interest are set in a tissue of a subject,
The medical information according to any one of claims 1 to 7, wherein the analysis unit calculates a ratio of a parameter value in the first region of interest to a parameter value in the second region of interest as an index value. Processing system. The first region of interest and the second region of interest are set as a blood vessel region that governs a region to be treated in the treatment,
The said analysis part produces | generates the parameter image of a said 1st phase, and the parameter image of a said 2nd phase which were correct | amended by the input function in a said 1st area of interest. The medical information processing system described in. The first region of interest and the second region of interest are set as a blood vessel region that governs a region to be treated in the treatment,
The medical information processing system according to any one of claims 1 to 7, wherein the analysis unit calculates the blood flow volume in the first region of interest and the blood flow volume in the second region of interest.