JP6087604B2 - Medical image processing device - Google Patents

Description

  Embodiments described herein relate generally to a medical image processing apparatus.

  In recent years, stent graft insertion has rapidly spread as a treatment method for aortic aneurysm diseases. Stent graft endoscopy is a treatment for preventing the rupture of an aortic aneurysm by attaching a stent graft having an artificial blood vessel (graft) attached to the inside of the stent to the inside of the aortic aneurysm formed in the aorta. For example, the stent graft is inserted into the distal end of the catheter, inserted from the artery at the base of the leg to the position of the aortic aneurysm, and attached to the inside of the aorta where the aortic aneurysm is formed by the spring of the stent and blood pressure.

  This type of stent graft insertion is less invasive than abdominal aortic aneurysm resection or artificial blood vessel replacement. However, when an endoleak that leaks blood around the stent graft occurs after the stent graft is placed. There is. For example, endoleaks may be caused by migration (position movement) of a stent graft, those caused by backflow from a branch vessel, those that occur at a damaged or joined portion of a stent graft, or via a graft material. What is generated when blood infiltrates is known.

  Among them, an endoleak in which blood leaks from a gap caused by migration of a stent graft occurs when the stent does not match the size of the blood vessel wall, and when it lasts for several months, the aortic aneurysm expands or ruptures. For this reason, the diameter of the aneurysm is measured at the time of the flow-up diagnosis of the patient, and when endoleak is observed through the enlargement of the aneurysm diameter, treatment by re-stenting the stent graft or laparotomy is performed. However, in the above-described prior art, it is difficult to predict when end leaks occur.

Special table 2011-512204 gazette

  The problem to be solved by the present invention is to provide a medical image processing apparatus that makes it possible to predict the time of end leakage of a stent graft.

The medical image processing apparatus according to the embodiment includes a detection unit, an extraction unit, and a display control unit. Detection means has a function of detecting a blood vessel and the stent graft contained in the three-dimensional medical image data. Extraction means, based on the coordinates in the three-dimensional medical image data, extracts the contact area between the detected blood vessel and the stent graft by said detecting means. Display control means controls the display image showing the relative positional relationship between the extracted contact area by the end portion and the extraction means of the stent graft so as to display in a predetermined display unit. The extraction means is a boundary where end leakage occurs at a position on the center side of the stent graft among positions where the blood vessel and the stent graft are in contact with each other over the entire circumference of the blood vessel in the longitudinal direction of the blood vessel. Extracted as end leak boundary position.

FIG. 1 is a diagram illustrating an example of a configuration of a medical image processing apparatus according to the first embodiment. FIG. 2 is a diagram schematically illustrating an example of a cross-section extraction process by the extraction unit according to the first embodiment. FIG. 3 is a diagram schematically illustrating an example of contact portion extraction processing by the extraction unit according to the first embodiment. FIG. 4 is a diagram schematically illustrating an example of contact area extraction processing by the extraction unit according to the first embodiment. FIG. 5 is a diagram schematically illustrating an example of the extraction process of the end leak boundary position by the extraction unit according to the first embodiment. FIG. 6 is a flowchart illustrating a processing procedure performed by the medical image processing apparatus according to the first embodiment. FIG. 7 is a diagram for explaining an example of processing by the calculation unit according to the second embodiment. FIG. 8 is a flowchart illustrating a processing procedure performed by the medical image processing apparatus according to the second embodiment. FIG. 9 is a diagram illustrating an example of a configuration of a medical image processing apparatus according to the third embodiment. FIG. 10 is a diagram schematically illustrating information stored in the stent information storage unit according to the third embodiment. FIG. 11 is a diagram for explaining an example of processing by the extraction unit according to the third embodiment. FIG. 12 is a diagram illustrating an example of a display image whose display is controlled by the display control unit according to the third embodiment. FIG. 13 is a flowchart illustrating a processing procedure performed by the medical image processing apparatus according to the third embodiment. FIG. 14 is a diagram for explaining a first modification according to the fourth embodiment. FIG. 15 is a diagram for explaining a second modification example according to the fourth embodiment. FIG. 16 is a diagram for explaining a third modification according to the fourth embodiment. FIG. 17 is a diagram for explaining a fourth modification example according to the fourth embodiment.

(First embodiment)
FIG. 1 is a diagram illustrating an example of a configuration of a medical image processing apparatus 100 according to the first embodiment. As illustrated in FIG. 1, the medical image processing apparatus 100 includes an input unit 110, a display unit 120, a communication unit 130, a storage unit 140, and a control unit 150. For example, the medical image processing apparatus 100 is a workstation, an arbitrary personal computer, or the like, and is connected to a medical image diagnosis apparatus or an image storage apparatus (not shown) via a network. The medical image diagnostic apparatus is, for example, an X-ray CT (Computed Tomography) apparatus, an MRI (Magnetic Resonance Imaging) apparatus, or an X-ray diagnostic apparatus. The medical image diagnostic apparatus can generate three-dimensional medical image data (for example, three-dimensional image data of blood vessels such as the aorta). Hereinafter, the three-dimensional image data may be referred to as volume data. The image storage device is a database that stores medical images. Specifically, the image storage device stores the three-dimensional medical image data transmitted from the medical image diagnostic device in the storage unit and stores it.

  The medical image processing apparatus 100, the medical image diagnostic apparatus, and the image storage apparatus described above can communicate with each other directly or indirectly by, for example, a hospital LAN (Local Area Network) installed in the hospital. It is in a state. For example, when PACS (Picture Archiving and Communication System) is introduced, each device transmits and receives medical images and the like according to DICOM (Digital Imaging and Communications in Medicine) standards.

  The input unit 110 is a mouse, a keyboard, a trackball, or the like, and receives input of various operations on the medical image processing apparatus 100 from an operator. Specifically, the input unit 110 receives input of information for acquiring, from the image storage device, three-dimensional medical image data to be processed, which is a target for performing predictive analysis of stent graft endoleak. For example, the input unit 110 receives an input for acquiring a CT image taken after a stent-graft insertion is performed on a patient with an aortic aneurysm.

  The display unit 120 is a liquid crystal panel or the like as a stereoscopic display monitor, and displays various types of information. Specifically, the display unit 120 displays a GUI (Graphical User Interface) for receiving various operations from the operator, a display image generated by processing by the control unit 150 described later, and the like. The display image generated by the control unit 150 will be described later. The communication unit 130 is a NIC (Network Interface Card) or the like, and performs communication with other devices.

  As shown in FIG. 1, the storage unit 140 includes an image data storage unit 141 and an analysis result storage unit 142. For example, the storage unit 140 is a hard disk, a semiconductor memory element, or the like, and stores various types of information. The image data storage unit 141 stores three-dimensional medical image data acquired from the image storage device via the communication unit 130. The analysis result storage unit 142 stores image data being processed by the control unit 150 described later, a display image generated by the processing, and the like.

  The control unit 150 is, for example, an electronic circuit such as a CPU (Central Processing Unit) or MPU (Micro Processing Unit), an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array), and medical image processing Overall control of the apparatus 100 is performed.

  Further, as illustrated in FIG. 1, the control unit 150 includes, for example, an image data acquisition unit 151, a detection unit 152, an extraction unit 153, a calculation unit 154, and a display control unit 155. Then, the control unit 150 performs predictive analysis of stent graft endoleak by executing various processes on the three-dimensional medical image data.

  The image data acquisition unit 151 acquires three-dimensional medical image data from an image storage device (not shown) via the communication unit 130 and stores it in the image data storage unit 141. For example, the image data acquisition unit 151 acquires three-dimensional medical image data corresponding to information input from the operator via the input unit 110 from the image storage device via the communication unit 130. For example, the image data acquisition unit 151 acquires volume data of the aorta collected by an X-ray CT apparatus, an MRI apparatus, or the like after performing a stent graft insertion on a patient with an aortic aneurysm, and the image data storage unit 141 To store.

  The detection unit 152 detects blood vessels and stent grafts included in the three-dimensional medical image data. Specifically, the detection unit 152 reads the volume data stored by the image data storage unit 141, and extracts blood vessels and stent grafts from the read volume data. More specifically, the detection unit 152 extracts the shape of the blood vessel at the position where the stent graft is placed and the shape of the stent graft. In other words, the detection unit 152 extracts the blood vessel and stent graft coordinate information in the volume data. For example, the detection unit 152 extracts the shape of the blood vessel and the stent graft included in the volume data by the CT value for each voxel of the volume data, the region expansion method using the MRI signal intensity, or the like. Any method may be used for extracting blood vessels and stent grafts from the volume data described above as long as they can extract blood vessels and stent grafts from volume data.

  The extraction unit 153 extracts a contact area between the blood vessel and the stent graft detected by the detection unit 152 based on the coordinates in the three-dimensional medical image data. Specifically, the extraction unit 153 extracts a plurality of cross sections orthogonal to the core line along the blood vessel core line, and a contact portion between the cross section of the blood vessel wall and the cross section of the stent graft respectively included in the extracted plurality of cross sections. Extraction is performed based on the coordinates of the cross section of the blood vessel wall and the stent graft, and the contact area is extracted by combining the extracted contact portions. Here, the extraction unit 153 determines a portion where the distance from the point on the cross section of the blood vessel wall to the cross section of the stent graft, or the distance from the point on the cross section of the stent graft to the cross section of the blood vessel wall falls below a predetermined threshold. Extract as a contact part.

  FIG. 2 is a diagram schematically illustrating an example of a cross-section extraction process by the extraction unit 153 according to the first embodiment. For example, as illustrated in FIG. 2, the extraction unit 153 extracts the core wire 30 of the blood vessel 10 detected by the detection unit 152, and a plurality of cross sections that are perpendicular to the core wire 30 along the extracted core wire 30. To extract. Then, as illustrated in FIG. 2, the extraction unit 153 extracts the blood vessel wall cross section 11 and the stent cross section 21 in the plurality of extracted cross sections based on the positional information (coordinate information) of the blood vessel 10 and the stent graft 20. The core wire 30 of the blood vessel 10 is extracted by, for example, a Bessel tracking method or a method of thinning the inner region of the blood vessel.

  FIG. 3 is a diagram schematically illustrating an example of a contact portion extraction process performed by the extraction unit 153 according to the first embodiment. FIG. 3 shows processing after the processing of FIG. For example, as illustrated in FIG. 3A, the extraction unit 153 extracts a point 22 on the stent cross section 21 in the extracted cross section, and calculates the radius of a circle circumscribing the blood vessel wall cross section 11. Then, the extraction unit 153 marks the point 22 when the calculated circle radius falls below a predetermined threshold (≈0). The extraction unit 153 performs the calculation of the radius of the circle circumscribing the blood vessel wall section 11, the determination using a predetermined threshold, and the marking process for all points on the stent section 21.

  When the above-described processing is executed for all points, the extraction unit 153 connects adjacent marked points and extracts the contact portion 40 as shown in FIG. In FIG. 2, only one cross section is shown, but in practice, the extraction unit 153 extracts the contact portion described above for all cross sections including the blood vessel wall cross section 11 and the stent cross section 21. Execute the process.

  FIG. 4 is a diagram schematically illustrating an example of contact area extraction processing by the extraction unit 153 according to the first embodiment. FIG. 4 shows processing after the processing in FIG. For example, as illustrated in FIG. 4, the extraction unit 153 extracts the contact portion 40 between the blood vessel wall cross section 11 and the stent cross section 21, and generates a cylindrical model by stacking the cross sections. Here, the extraction unit 153 determines the reference direction of the cylindrical model and generates the cylindrical model, as indicated by an arrow 50 in FIG. That is, the extraction unit 153 generates a cylindrical model in which the orientations of the cross sections in the volume data coordinates are aligned. Thereby, for example, it is possible to correct the deviation of the orientation when the cross section is extracted along the core wire 30. And the extraction part 153 extracts the whole area | region which connected the contact part 40 shown by the side surface of the produced | generated cylindrical model as a contact area.

  Further, for example, the extraction unit 153 generates an end leak at a position on the center side of the stent graft 20 among positions where the blood vessel 10 and the stent graft 20 are in contact with each other in the longitudinal direction of the blood vessel 10. It is extracted as an end leak boundary position that is a boundary to be detected. That is, the extraction unit 153 extracts a stent boundary position that is a boundary between the blood vessel 10 and the stent graft 20. FIG. 5 is a diagram schematically illustrating an example of an end leak boundary position extraction process performed by the extraction unit 153 according to the first embodiment. Here, FIG. 5 shows a development view of the cylindrical model shown in FIG.

  For example, as illustrated in FIG. 5, the extraction unit 153 extracts, as the end leak boundary position 52, a position that is in contact with the entire circumference of the blood vessel in the contact region 41 between the blood vessel and the stent graft. In other words, the extraction unit 153 extracts a position where an end leak physically occurs as the end leak boundary position 52 when the end of the stent graft moves below this position. Further, as illustrated in FIG. 5, the extraction unit 153 extracts a stent boundary position 51 that is a boundary between the blood vessel wall section 11 and the stent section 21. Note that the contact region 41 shown in FIG. 5 is a region where the contact portion 40 shown in FIG. 4 is coupled. The arrow 53 in FIG. 5 will be described later.

  Returning to FIG. 1, the calculation unit 154 calculates the distance between the stent boundary position, which is the boundary between the blood vessel and the stent graft, and the endoleak boundary position. Specifically, the calculation unit 154 calculates the shortest distance between the stent boundary position and the end leak boundary position. For example, as illustrated in FIG. 5, the calculation unit 154 calculates a boundary distance 53 that is a distance between the stent boundary position 51 and the end leak boundary position 52. For example, the calculation unit 154 calculates “2.7 cm” as the boundary distance 53 as illustrated in FIG. 5. That is, the calculation unit 154 calculates the movement distance of the stent graft until an endoleak occurs.

  Then, the calculation unit 154 stores information such as a cylindrical model, a development view of the cylindrical model, and a boundary distance in the analysis result storage unit 142 as a display image. For example, the calculation unit 154 stores the cylindrical model illustrated in FIG. 4, the development illustrated in FIG. 5, and the like in the analysis result storage unit 142.

  Returning to FIG. 1, the display control unit 155 controls the display unit 120 to display a display image indicating the relative positional relationship between the end portion of the stent graft and the contact area extracted by the extraction unit 153. Specifically, the display control unit 155 causes the display unit 120 to display information indicating the positional relationship between the stent boundary position and the end leak boundary position. For example, the display control unit 155 reads out from the analysis result storage unit 142 a display image showing the development view of the cylindrical model and the boundary distance shown in FIG. At this time, the display control unit 155 can simultaneously display the process from the blood vessel 10 to the cylindrical model shown in FIG. Thereby, the observer can easily image the positional relationship and the boundary distance between the blood vessel and the stent graft. The observer can easily predict the end leak occurrence time from these pieces of information.

  In the above-described embodiment, the case where the contact portion is extracted based on the distance from the point on the stent cross section to the blood vessel wall cross section when extracting the contact portion between the blood vessel wall cross section and the stent cross section has been described. However, the embodiment is not limited to this. For example, the contact portion may be extracted based on the distance from the point on the blood vessel wall cross section to the stent cross section.

  FIG. 6 is a flowchart illustrating a processing procedure performed by the medical image processing apparatus 100 according to the first embodiment. As shown in FIG. 6, in the medical image processing apparatus 100 according to the first embodiment, first, the image data acquisition unit 151 acquires volume data from the image data storage unit 141 (step S101).

  Then, the detection unit 152 extracts blood vessels and stent grafts from the volume data acquired by the image data acquisition unit 151 (step S102). Thereafter, the extraction unit 153 extracts the contact area between the blood vessel and the stent graft extracted by the detection unit 152 (step S103). Further, the extraction unit 153 extracts the stent boundary position and the end leak boundary position based on the position information of the blood vessel, the stent graft, and the extracted contact region (step S104).

  Thereafter, the calculation unit 154 calculates the boundary distance (step S105), and the display control unit 155 causes the display unit 120 to display a display image including the boundary distance information (step S106).

  As described above, according to the first embodiment, the detection unit 152 detects blood vessels and stent grafts included in the three-dimensional medical image data. Then, the extraction unit extracts the contact area between the blood vessel and the stent graft detected by the detection unit 152 based on the coordinates in the three-dimensional medical image data. The display control unit 155 controls the display unit 120 to display a display image indicating the relative positional relationship between the end portion of the stent graft and the contact area extracted by the extraction unit 153. Therefore, the medical image processing apparatus 100 according to the first embodiment can provide information on the positional relationship between the contact region between the stent graft and the blood vessel and the end portion of the stent to the observer, and the end leak of the stent graft. Makes it possible to predict the timing of

  For example, the observer refers to the boundary distance immediately after the stent graft insertion has been performed, predicts when the end graft will occur when the stent graft moves, and before that, again before the X-ray The state can be observed by performing imaging with a CT apparatus or the like.

  Further, according to the first embodiment, the extraction unit 153 extracts a plurality of cross sections orthogonal to the core line along the blood vessel core line, and the cross section of the blood vessel wall and the cross section of the stent graft respectively included in the extracted plurality of cross sections The contact area is extracted based on the coordinates of the cross section of the blood vessel wall and the stent graft, and the contact area is extracted by combining the extracted contact areas. Therefore, the medical image processing apparatus 100 according to the first embodiment makes it possible to accurately extract a contact area from volume data.

  Further, according to the first embodiment, the extraction unit 153 has a predetermined distance from a point on the cross section of the blood vessel wall to the cross section of the stent graft or a distance from a point on the cross section of the stent graft to the cross section of the blood vessel wall. A portion that falls below the threshold is extracted as a contact portion. Therefore, the medical image processing apparatus 100 according to the first embodiment makes it possible to accurately extract the contact portion between the blood vessel wall and the stent graft.

  In addition, according to the first embodiment, the extraction unit 153 endoleaks the position on the center side of the stent graft among the positions where the blood vessel and the stent graft are in contact with each other in the longitudinal direction of the blood vessel. It is extracted as the end leak boundary position, which is the boundary where the occurrence of. Therefore, the medical image processing apparatus 100 according to the first embodiment makes it possible to accurately determine whether or not an end leak occurs.

  Further, according to the first embodiment, the calculation unit 154 calculates the distance between the stent boundary position, which is the boundary between the blood vessel and the stent graft, and the endoleak boundary position. Therefore, the medical image processing apparatus 100 according to the first embodiment makes it possible to provide optimal information for predicting the occurrence of an end leak to the observer.

(Second Embodiment)
In the first embodiment described above, a case has been described in which end leak is predicted using volume data at one point in time (for example, immediately after placement of a stent graft). In the second embodiment, a case where end leak is predicted using volume data collected at a plurality of times will be described. Note that in the medical image processing apparatus 100 according to the second embodiment, the processing content by the calculation unit 154 is different from that of the medical image processing apparatus according to the first embodiment. Hereinafter, this will be mainly described.

  In the medical image processing apparatus 100 according to the second embodiment, first, the image data acquisition unit 151 acquires volume data with different time phases collected from the same subject. Then, the detection unit 152 extracts a blood vessel and a stent graft from the plurality of volume data. Thereafter, the extraction unit 153 extracts the stent boundary position and the end leak boundary position from the plurality of volume data.

  The calculation unit 154 according to the second embodiment calculates the distance between the stent boundary position and the end leak position respectively extracted from the three-dimensional medical image data having different time phases by the extraction unit 153, and calculates the calculated distance. Estimate the end leak time based on the change in.

  FIG. 7 is a diagram for explaining an example of processing by the calculation unit 154 according to the second embodiment. For example, as shown in FIG. 7, the calculation unit 154 uses the stent boundary position and the end leak boundary position extracted from the volume data immediately after placement, one month later, and three months later, respectively, immediately after placement, for one month. The boundary distance after and after 3 months is calculated respectively.

  Then, the calculation unit 154 predicts the end leak time based on the change in the boundary distance resulting from the movement of the stent boundary position. For example, as shown in FIG. 7, the calculation unit 154 plots the values of the boundary distance immediately after placement on the graph with the time on the horizontal axis and the boundary distance on the vertical axis, immediately after placement, and after three months. Estimate the end leak time. Then, the calculation unit 154 stores the graph shown in FIG. 7 in the analysis result storage unit 142 as a display image.

  In the above-described embodiment, a case has been described in which a plurality of time phase volume data are processed simultaneously. However, the embodiment is not limited to this. For example, every time volume data is collected by the X-ray CT apparatus, the boundary distance is calculated and the graph shown in FIG. 7 is created to estimate the end leak time. It may be the case. Moreover, the boundary distance memorize | stored by the analysis result memory | storage part 142 may be read at arbitrary timings, the case where the graph shown in FIG. 7 is produced and an end leak time may be estimated may be sufficient.

  The display control unit 155 according to the second embodiment causes the display unit 120 to display a display image including the end leak time estimated by the calculation unit 154. For example, the display control unit 155 reads the graph shown in FIG. 7 stored by the analysis result storage unit 142 and causes the display unit 120 to display the graph.

  FIG. 8 is a flowchart illustrating a processing procedure performed by the medical image processing apparatus 100 according to the second embodiment. FIG. 8 shows a case where a plurality of time phase volume data are processed simultaneously. As shown in FIG. 8, in the medical image processing apparatus 100 according to the second embodiment, first, the image data acquisition unit 151 acquires volume data of each time phase from the image data storage unit 141 (step S201). .

  Then, the detection unit 152 extracts a blood vessel and a stent graft from each time-phase volume data acquired by the image data acquisition unit 151 (step S202). Thereafter, the extraction unit 153 extracts the contact regions between the blood vessels of each phase extracted by the detection unit 152 and the stent graft (step S203). Further, the extraction unit 153 extracts the stent boundary position and the end leak boundary position based on the position information of the blood vessel, the stent graft, and the extracted contact region (step S204).

  Thereafter, the calculation unit 154 calculates the boundary distances (step S205), and estimates the end leak time from the boundary distances of the respective time phases (step S206). The display control unit 155 displays a display image including the end leak time on the display unit 120 (step S207).

  As described above, according to the second embodiment, the extraction unit 153 extracts the stent boundary position and the end leak boundary position from volume data with different time phases collected from the same subject. Then, the calculation unit 154 calculates the distance between the stent boundary position and the end leak boundary position respectively extracted from the volume data having different time phases by the extraction unit 153, and based on the change in the calculated distance, the end leak Estimate when. Therefore, the medical image processing apparatus 100 according to the second embodiment makes it possible to provide the end leak time to the observer.

(Third embodiment)
In the above-described embodiment, the case where the boundary distance is calculated by extracting the contact area between the blood vessel and the stent graft using the volume data collected after the stent graft insertion is performed has been described. In the third embodiment, a case will be described in which contact area extraction and boundary distance calculation are executed virtually using the size of a stent graft.

  FIG. 9 is a diagram illustrating an example of the configuration of the medical image processing apparatus 100 according to the third embodiment. Here, compared with the medical image processing apparatus according to the first embodiment, the medical image processing apparatus 100 according to the third embodiment newly includes a stent information storage unit 143 and the processing of the extraction unit 153. The contents are different. Hereinafter, these will be mainly described.

  The stent information storage unit 143 stores various information related to the shape of the stent graft. FIG. 10 is a diagram schematically illustrating information stored in the stent information storage unit 143 according to the third embodiment. For example, the stent information storage unit 143 stores information relating to the shapes of various types of stent grafts as shown in FIG. For example, as shown in FIG. 10, the stent information storage unit 143 stores stent information such as a diameter and a total length at each position of the stent.

  The extraction unit 153 according to the third embodiment extracts a virtual contact region that is a virtual contact region between the blood vessel and the stent graft when the stent graft is virtually placed on the blood vessel detected by the detection unit 152. To do. Specifically, the extraction unit 153 reads information on the shape of the stent graft selected by the observer from the stent information storage unit 143, and performs virtual contact when the read stent graft is placed in the blood vessel extracted by the detection unit 152. Extract regions.

  FIG. 11 is a diagram for explaining an example of processing by the extraction unit 153 according to the third embodiment. For example, as illustrated in FIG. 11, the extraction unit 153 extracts the virtual contact portion 42 by arranging the virtual cross section 23 of the stent graft with respect to the blood vessel wall cross section 11 including the information of the core wire 30. More specifically, the extraction unit 153 acquires the virtual cross section 23 from the diameter information of the stent graft. Then, the extraction unit 153 arranges the virtual cross section 23 so that the position of the core line 30 of the blood vessel wall cross section 11 matches the position of the center of the virtual cross section 23 of the stent graft.

  Thereafter, the extraction unit 153 sets a point on the virtual cross section 23 or the blood vessel wall cross section 11 of the stent graft, and extracts a virtual contact portion 42 that is a virtual contact portion between the blood vessel wall and the stent graft. In addition, since the extraction method of the virtual contact part 42 is the same as that of 1st Embodiment, detailed description is abbreviate | omitted. Then, the extraction unit 153 virtually arranges the stent grafts for all the cross sections to extract the virtual contact portion 42, and generates a cylindrical model in which the virtual contact region is shown on the side surface.

  The display control unit 155 according to the third embodiment controls the display unit 120 to display a display image indicating the relative positional relationship between the end portion of the stent graft and the virtual contact region extracted by the extraction unit 153. To do. FIG. 12 is a diagram illustrating an example of a display image whose display is controlled by the display control unit 155 according to the third embodiment.

  For example, as shown in FIG. 12, the display control unit 155 causes the display unit 120 to display a display image in which cross-section information, a cylindrical model, and a developed view of the cylindrical model are shown. Here, in the display image displayed on the display unit 120, as shown in FIG. 12, the boundary distance “3.5 cm” that is the distance from the stent boundary position to the end leak boundary position is shown. That is, the calculation unit 154 according to the third embodiment calculates a boundary position from the stent boundary position and the end leak boundary position extracted by the extraction unit 153.

  FIG. 13 is a flowchart illustrating a processing procedure performed by the medical image processing apparatus 100 according to the third embodiment. As shown in FIG. 13, in the medical image processing apparatus 100 according to the first embodiment, the image data acquisition unit 151 first acquires volume data from the image data storage unit 141 (step S301).

  Then, the detection unit 152 extracts blood vessels from the volume data acquired by the image data acquisition unit 151 (step S302). Thereafter, the extraction unit 153 determines whether or not the shape of the stent graft has been selected (step S303). Here, when the shape of the stent graft is selected (Yes in step S303), the extraction unit 153 extracts a virtual contact region from the blood vessel extracted by the detection unit 152 and information on the shape of the selected stent graft ( Step S304).

  Further, the extraction unit 153 extracts the stent boundary position and the end leak boundary position based on the position information of the blood vessel, the selected stent graft, and the extracted virtual contact region (step S305). Thereafter, the calculation unit 154 calculates the boundary distance (step S306), and the display control unit 155 causes the display unit 120 to display a display image including information on the boundary distance (step S307).

  Then, the extraction unit 153 determines whether or not the shape of the stent graft has been changed (step S308). Here, when the shape of the stent graft is changed (step S308 Yes), the extraction unit 153 returns to step S304, and extracts the virtual contact region from the changed shape and blood vessel information of the stent graft. On the other hand, when the shape of the stent graft is not changed (No in step S308), the medical image processing apparatus 100 ends the process. In step S303, the medical image processing apparatus 100 is in a standby state until a stent graft shape is selected (No in step S303).

  As described above, according to the third embodiment, when the stent graft is virtually placed on the blood vessel detected by the detection unit 152, the extraction unit 153 has a virtual contact region between the blood vessel and the stent graft. The virtual contact area which is is extracted. Then, the display control unit 155 controls the display unit 120 to display a display image indicating the relative positional relationship between the end portion of the stent graft and the virtual contact area extracted by the extraction unit 153. Therefore, the medical image processing apparatus 100 according to the third embodiment can execute simulations with various shapes of stent grafts before performing stent graft insertion, and the user can determine the optimal stent shape for the case in advance. Allows you to decide.

(Fourth embodiment)
The first, second and third embodiments have been described so far, but may be implemented in various different forms other than the first, second and third embodiments described above. .

  In the first, second, and third embodiments described above, the case where one position of the stent graft is targeted has been described. However, the embodiment is not limited to this, and may be, for example, a case where a plurality of positions of the stent graft are targeted.

  FIG. 14 is a diagram for explaining a first modification according to the fourth embodiment. For example, as illustrated in FIG. 14, the medical image processing apparatus 100 according to the fourth embodiment calculates boundary distances at the upper end, lower end, and joint portion of a stent graft including a plurality of parts, and displays the distance on the display unit 120. Can be displayed. Thereby, the medical image processing apparatus 100 according to the fourth embodiment makes it possible to analyze and evaluate each part.

  In the first and third embodiments described above, the case where the boundary distance is displayed as the information for predicting the end leak time has been described. However, the embodiment is not limited to this. For example, the width of the contact area may be displayed as information for predicting the end leak time.

  FIG. 15 is a diagram for explaining a second modification example according to the fourth embodiment. For example, as illustrated in FIG. 15, the medical image processing apparatus 100 according to the fourth embodiment has a contact area that is the shortest distance between the upper boundary curve 54 and the lower boundary curve 55 in the development view of the cylindrical model. The width 56 can be calculated and displayed on the display unit 120. In such a case, the extraction unit 153 extracts the upper boundary curve 54 and the lower boundary curve 55. Then, the calculation unit 154 calculates the contact area width.

  Thereby, the medical image processing apparatus 100 according to the fourth embodiment allows the user to make various determinations based on the value of the contact area width. For example, the user can determine the next schedule for follow-up based on the value of the contact area width. That is, the user can decide to perform the next follow-up observation before the value of the contact area width becomes “0”.

  In the first, second, and third embodiments described above, the case where only the contact area is displayed in the development view of the cylindrical model has been described. However, the embodiment is not limited to this, and for example, a region where the distance between the blood vessel wall and the stent graft is less than a predetermined value may be displayed.

  FIG. 16 is a diagram for explaining a third modification according to the fourth embodiment. For example, as illustrated in FIG. 16, the medical image processing apparatus 100 according to the fourth embodiment has a contact area where the distance between the blood vessel wall and the stent is “≈0” and the distance between the blood vessel wall and the stent is “ It is also possible to display on the display unit 120 a developed view showing a region different from <0.5 cm ”in a different color. Thereby, the medical image processing apparatus 100 according to the fourth embodiment can provide the contact state of the stent graft with the blood vessel wall in more detail.

  In the first, second, and third embodiments described above, the case where a cylindrical model or a developed view is used as the display image has been described. However, the embodiment is not limited to this, and may be a case where, for example, the contact area is displayed superimposed on the image.

  FIG. 17 is a diagram for explaining a fourth modification example according to the fourth embodiment. For example, as illustrated in FIG. 17, the medical image processing apparatus 100 according to the fourth embodiment may cause the display unit 120 to display a curved MPR image or an image in which a contact region is superimposed on a stretched MPR image. Is possible. In such a case, the contact area is superimposed on the image based on the coordinates of the contact area in the volume data.

  In the first, second, and third embodiments described above, the contact portion is extracted based on the distance between the blood vessel wall cross section and the stent cross section, and the extracted contact portions are combined on the cylindrical model, thereby making contact. The case of extracting an area has been described. However, the embodiment is not limited to this. For example, the contact area may be extracted using the coordinates of the blood vessel wall and the coordinates of the stent graft in the volume data.

  For example, the extraction unit 153 plots 8 points shifted by 45 degrees on the circumference of the blood vessel at the position where the stent graft is placed, and further plots 10 points in the longitudinal direction of the blood vessel. Then, the extraction unit 153 extracts the coordinates of the blood vessel wall and the coordinates of the stent graft at each point. Then, the extraction unit 153 calculates the distance between the coordinates at each extracted point, and when the calculated distance is below a predetermined threshold (for example, ≈0), the blood vessel wall and the stent graft are in contact with each other. It is determined that

  The extraction unit 153 performs the above-described determination at all points, and extracts contact points between the blood vessel wall and the stent graft. And the extraction part 153 extracts the area | region enclosed by four contact points as a contact area. Note that the criterion for determining the contact area can be arbitrarily set by the user. For example, it may be a case where an area in which three of the four surrounding points are contact points is extracted as a contact area. In addition, for example, a region where three of the four surrounding points are contact points and one point is “distance between coordinates <0.5 cm” may be extracted as the contact region.

  According to the medical image processing apparatus of at least one embodiment described above, it is possible to predict the end leak time of the stent graft.

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

DESCRIPTION OF SYMBOLS 100 Medical image processing apparatus 150 Control part 151 Image data acquisition part 152 Detection part 153 Extraction part 154 Calculation part 155 Display control part

Claims (6)

Detection means having a function of detecting blood vessels and stent grafts included in the three-dimensional medical image data;
Extraction means for extracting a contact area between the blood vessel and the stent graft detected by the detection means based on the coordinates in the three-dimensional medical image data;
Display control means for controlling the display image indicating the relative positional relationship between the end portion of the stent graft and the contact area extracted by the extraction means to be displayed on a predetermined display section;
Equipped with a,
The extraction means is a boundary where end leakage occurs at a position on the center side of the stent graft among positions where the blood vessel and the stent graft are in contact with each other over the entire circumference of the blood vessel in the longitudinal direction of the blood vessel. A medical image processing apparatus characterized by extracting as an end leak boundary position .   The extraction means extracts a plurality of cross sections orthogonal to the core line along the core line of the blood vessel, and a contact portion between the cross section of the blood vessel wall and the cross section of the stent graft respectively included in the extracted plurality of cross sections The medical image processing apparatus according to claim 1, wherein the contact area is extracted by extracting the contact areas by combining the extracted contact portions based on the coordinates of the cross section of the wall and the stent graft.   The extraction means calculates a portion where a distance from a point on the cross section of the blood vessel wall to the cross section of the stent graft, or a distance from a point on the cross section of the stent graft to the cross section of the blood vessel wall falls below a predetermined threshold. The medical image processing apparatus according to claim 2, wherein the medical image processing apparatus is extracted as the contact portion. According to any one of claims 1 to 3, further comprising a calculating means for calculating the distance between said end leakage boundary position between the stent boundary position is the boundary between the blood vessel and the stent-graft Medical image processing apparatus. The extraction means extracts the stent boundary position and the endoleak boundary position from three-dimensional medical image data having different time phases collected from the same subject,
The calculation unit calculates a distance between the stent boundary position and the endoleak boundary position respectively extracted from three-dimensional medical image data having different time phases by the extraction unit, and based on the calculated change in distance. The medical image processing apparatus according to claim 4 , wherein an end leak time is estimated. The extraction unit extracts a virtual contact region that is a virtual contact region between the blood vessel and the virtually placed stent graft when the stent graft is virtually placed on the blood vessel detected by the detection unit. And
The display control unit is configured to display a display image indicating a relative positional relationship between the end portion of the virtually placed stent graft and the virtual contact region extracted by the extraction unit on a predetermined display unit. The medical image processing apparatus according to claim 1, wherein:

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