JP7066415B2 - Medical image processing equipment, medical diagnostic imaging equipment and medical image processing programs - Google Patents

Description

Embodiments of the present invention relate to a medical image processing device, a medical diagnostic imaging device, and a medical image processing program.

In recent years, the evolution of medical devices has been remarkable, and in particular, the evolution of medical devices for endovascular treatment using catheters has been remarkable. For example, Flow Diverter (Pipeline, etc.) has attracted attention as a stent used for embolization of cerebral aneurysms, and is beginning to be used in clinical practice. Unlike conventional cerebral aneurysm treatment stents, Flow Diverter is characterized by a high-density mesh and flexibility in shape, and it is also possible to change the density of the mesh locally.

Japanese Unexamined Patent Publication No. 2013-31655

An object to be solved by the present invention is to understand the effect of indwelling a medical device on blood flow.

The medical image processing apparatus according to the embodiment includes an acquisition unit, an extraction unit, a calculation unit, and an output control unit. The acquisition unit acquires medical image data including a blood flow region through which blood flows. The extraction unit extracts the shape of the medical device placed in the blood flow region. The calculation unit calculates an index value indicating the degree of blood permeation of the medical device indwelled in the blood flow region based on the shape when the medical device is indwelled. The output control unit controls to output the index value.

FIG. 1 is a diagram showing an example of a configuration of a medical image processing system according to a first embodiment. FIG. 2 is a diagram showing an example of the configuration of the medical image processing apparatus according to the first embodiment. FIG. 3 is a diagram for explaining the Flow Diverter according to the first embodiment. FIG. 4 is a diagram showing an example of correspondence information stored by the storage circuit according to the first embodiment. FIG. 5 is a diagram for explaining an example of processing by the extraction function according to the first embodiment. FIG. 6 is a diagram for explaining an example of processing by the extraction function according to the first embodiment. FIG. 7 is a diagram showing an example of an index value displayed by controlling the control function according to the first embodiment. FIG. 8 is a diagram showing an example of an index value displayed by controlling the control function according to the first embodiment. FIG. 9 is a flowchart showing a processing procedure by the medical image processing apparatus according to the first embodiment. FIG. 10 is a flowchart showing a processing procedure by the medical image processing apparatus according to the first embodiment. FIG. 11 is a diagram for explaining an example of processing by the extraction function according to the second embodiment. FIG. 12 is a flowchart showing a processing procedure by the medical image processing apparatus according to the second embodiment. FIG. 13 is a diagram showing an example of processing by the control function according to the third embodiment. FIG. 14 is a flowchart showing a processing procedure by the medical image processing apparatus according to the third embodiment. FIG. 15 is a diagram showing an example of processing by the control function according to the fourth embodiment. FIG. 16 is a flowchart showing a processing procedure by the medical image processing apparatus according to the fourth embodiment. FIG. 17 is a diagram showing an example of the configuration of the X-ray diagnostic apparatus according to the fifth embodiment.

Hereinafter, embodiments of the medical image processing apparatus, the medical diagnostic imaging apparatus, and the medical image processing program according to the present application will be described in detail with reference to the accompanying drawings. The medical image processing device, the medical image diagnostic device, and the medical image processing program according to the present application are not limited to the embodiments shown below.

(First Embodiment)
First, the first embodiment will be described. In the first embodiment, an example in which the technique disclosed in the present application is applied to a medical image processing apparatus will be described. Hereinafter, a medical image processing system including a medical image processing device will be described as an example.

FIG. 1 is a diagram showing an example of a configuration of a medical image processing system according to a first embodiment. As shown in FIG. 1, the medical image processing system according to the first embodiment includes a medical image diagnostic device 100, an image storage device 200, and a medical image processing device 300.

For example, in the medical image processing system, the medical image processing device 300 according to the first embodiment is connected to the medical image diagnostic device 100 and the image storage device 200 via the network 400 as shown in FIG. To.

The medical image diagnosis device 100 is a modality used for a procedure using a medical device, and is, for example, an X-ray diagnostic device, an X-ray CT (Computed Tomography) device, an ultrasonic diagnostic device, an MRI (Magnetic Resonance Imaging) device, and the like. Is. For example, the medical diagnostic imaging apparatus 100 collects projection data by photographing a subject, and collects two-dimensional or three-dimensional medical image data based on the collected projection data. The medical image diagnostic apparatus 100 can also collect two-dimensional or three-dimensional contrast image data by photographing a subject into which a contrast medium has been injected. For example, an X-ray CT device as a medical image diagnostic device 100 collects CTA (CT Angio) image data from a subject into which a contrast medium is injected as three-dimensional contrast image data. Further, for example, the X-ray diagnostic apparatus as the medical image diagnostic apparatus 100 collects X-ray image data from a subject into which a contrast medium is injected as two-dimensional contrast image data.

Further, the medical image diagnosis device 100 transmits the collected medical image data to the image storage device 200 and the medical image processing device 300. When the medical image diagnosis device 100 transmits the medical image data to the image storage device 200 or the medical image processing device 300, as incidental information, for example, a patient ID for identifying a patient, an examination ID for identifying an examination, and the like. A device ID for identifying the medical image diagnosis device 100, a series ID for identifying one imaging by the medical image diagnosis device 100, and the like are transmitted.

The image storage device 200 stores the medical image data collected by the medical image diagnostic device 100 via the network 400. For example, the image storage device 200 is realized by a computer device such as a server device. In the present embodiment, the image storage device 200 acquires two-dimensional or three-dimensional medical image data from the medical image diagnostic device 100 via the network 400, and the acquired medical image data is provided inside or outside the device. Store in the storage circuit.

The medical image processing device 300 acquires medical image data from the medical image diagnostic device 100 and the image storage device 200 via the network 400, and processes the acquired medical image data. For example, the medical image processing device 300 is realized by a computer device such as a workstation. In the present embodiment, the medical image processing device 300 acquires medical image data from the medical image diagnostic device 100 or the image storage device 200 via the network 400, and performs various image processing on the acquired medical image data. Then, the medical image processing apparatus 300 displays the medical image after the image processing, the analysis result obtained by the image processing, and the like on a display or the like.

FIG. 2 is a diagram showing an example of the configuration of the medical image processing apparatus 300 according to the first embodiment. For example, as shown in FIG. 2, the medical image processing apparatus 300 includes an I / F (interface) circuit 310, a storage circuit 320, an input interface 330, a display 340, and a processing circuit 350.

The I / F circuit 310 is connected to the processing circuit 350 and controls the transmission and communication of various data with the medical image diagnostic device 100 or the image storage device 200 connected via the network 400. For example, the I / F circuit 310 is realized by a network card, a network adapter, a NIC (Network Interface Controller), or the like. In the present embodiment, the I / F circuit 310 receives medical image data from the medical image diagnostic device 100 or the image storage device 200, and outputs the received medical image data to the processing circuit 350. Here, the I / F circuit 310 can also receive real-time medical image data collected by the medical image diagnostic apparatus 100 and output it to the processing circuit 350.

The storage circuit 320 is connected to the processing circuit 350 and stores various data. For example, the storage circuit 320 is realized by a semiconductor memory element such as a RAM (Random Access Memory) or a flash memory, a hard disk, an optical disk, or the like. In the present embodiment, the storage circuit 320 stores medical image data received from the medical image diagnostic device 100 or the image storage device 200. For example, the storage circuit 320 stores CT image data collected over time by an X-ray CT device, X-ray image data collected by an X-ray diagnostic device, ultrasonic image data collected by an ultrasonic diagnostic device, and the like. Remember. As an example, the storage circuit 320 stores CTA image data, X-ray image data, and the like collected by photographing a subject into which a contrast medium is injected.

Further, the storage circuit 320 stores various information used for the processing of the processing circuit 350, the processing result of the processing circuit 350, and the like. For example, the storage circuit 320 stores the corresponding information referred to by the processing circuit 350. The details of the correspondence information will be described later.

The input interface 330 includes a trackball for setting a predetermined area (for example, a treatment target site), a switch button, a mouse, a keyboard, a touch pad for performing input operations by touching an operation surface, and a display screen and touch. It is realized by a touch screen integrated with a pad, a non-contact input circuit using an optical sensor, a voice input circuit, a foot switch for irradiating X-rays, and the like.

The input interface 330 is connected to the processing circuit 350, converts the input operation received from the operator into an electric signal, and outputs the input operation to the processing circuit 350. In the present specification, the input interface 330 is not limited to the one provided with physical operation parts such as a mouse and a keyboard. For example, an example of an input interface includes an electric signal processing circuit that receives an electric signal corresponding to an input operation from an external input device provided separately from the device and outputs the electric signal to a control circuit.

The display 340 is connected to the processing circuit 350 and displays various information and various images output from the processing circuit 350. For example, the display 340 is realized by a liquid crystal monitor, a CRT (Cathode Ray Tube) monitor, a touch panel, or the like. For example, the display 340 displays a GUI (Graphical User Interface) for receiving an operator's instruction, various images, and various processing results by the processing circuit 350.

The processing circuit 350 controls each component of the medical image processing apparatus 300 in response to an input operation received from the operator via the input interface 330. For example, the processing circuit 350 is realized by a processor. In the present embodiment, the processing circuit 350 stores the medical image data output from the I / F circuit 310 in the storage circuit 320. Further, the processing circuit 350 reads the medical image data from the storage circuit 320, and displays the medical image generated from the read medical image data on the display 340. Further, the processing circuit 350 executes various analysis processes on the medical image data and displays the analysis results on the display 340.

Under such a configuration, the medical image processing apparatus 300 according to the present embodiment makes it possible to grasp the effect of the placement of the medical device on the blood flow. Specifically, the medical image processing device 300 causes the operator to grasp the effect of the placement of the medical device by displaying an index value indicating the degree of blood permeation in the medical device placed in the blood vessel. Here, as described above, the evolution of medical devices for endovascular treatment using catheters has been remarkable in recent years. For example, Flow Diverter is highly flexible and can change the density of the mesh (metal density).

FIG. 3 is a diagram for explaining the Flow Diverter according to the first embodiment. As shown in FIG. 3, the Flow Diverter has a finer mesh (higher mesh density) than the conventional stent. The Flow Diverter has high flexibility, and the mesh changes as the shape changes. For example, the Flow Diverter expands and contracts in the radial direction, and the shape of the mesh changes as the diameter changes. As an example, in Flow Diverter, as shown by the arrow on the left side of FIG. 3, the smaller the diameter, the sharper the diagonal angle in the longitudinal direction of the mesh formed by the square. Further, for example, in the Flow Diverter, as shown by the arrow on the right side of FIG. 3, as the diameter becomes larger, the diagonal angle in the longitudinal direction of the mesh formed by the square becomes obtuse.

Here, in Flow Diverter, the length of each side of the square of the mesh does not change even if the diameter changes. Therefore, the area of the mesh in the Flow Diverter is maximum when the mesh is square, and becomes smaller as the diameter becomes smaller or as the diameter becomes larger. In other words, the Flow Diverter can increase the density of the mesh by reducing the diameter or increasing the diameter.

In addition, the Flow Diverter can locally change the density of the mesh. For example, the Flow Diverter can also increase the density of the mesh in the range "a" by narrowing the area of only the mesh included in the range "a" in the longitudinal direction shown in FIG.

When such a Flow Diverter is placed in a treatment target site such as an aneurysm, the density is high in the site where blood inflow is desired to be reduced (for example, the neck surface of the aneurysm), and other parts. A high therapeutic effect is expected by indwelling the surrounding area so as to cover it with a low density. That is, the Flow Diverter covers the neck surface of the aneurysm with a high-density mesh to reduce the inflow of blood from the mother blood vessel into the aneurysm, while reducing the density with respect to other peripheral parts. By covering with the mesh of the aneurysm, it is possible to suppress the reduction of the inflow of blood to the vascular branch around the aneurysm.

In this way, treatment using a highly flexible medical device such as Flow Diverter that can change the density of the mesh is expected to have a high therapeutic effect, but at present, the therapeutic effect is directly applied. Difficult to confirm. That is, in the prior art, it is difficult to discern the difference in local mesh density, and it is difficult to grasp the more accurate effect of the placement of the medical device on the blood flow. Therefore, the medical image processing apparatus 300 according to the present application makes it possible to grasp the more accurate effect of the placement of the medical device on the blood flow by discriminating the difference in the density of the local mesh.

Hereinafter, the details of the medical image processing apparatus 300 according to the present embodiment will be described. In the medical image processing apparatus 300 according to the present embodiment, the storage circuit 320 stores the shape of the medical device when it is placed and the index value for each type of the medical device in association with each other. Specifically, the storage circuit 320 provides correspondence information in which the shape that the medical device can take and the index value indicating the degree of blood permeation for each shape are associated with each medical device placed in the blood vessel. Remember. For example, the storage circuit 320 stores corresponding information associated with an index value for each shape indicated by the diameter and inclination (curvature) of the cross section orthogonal to the core wire of the medical device.

FIG. 4 is a diagram showing an example of correspondence information stored by the storage circuit 320 according to the first embodiment. As shown in FIG. 4, the storage circuit 320 stores correspondence information in which the “medical device”, the “diameter”, the “inclination”, the “density”, and the “coverage” are associated with each other. Here, the “medical device” in FIG. 4 means a device indwelled with respect to a blood vessel, and is, for example, “FD (Flow Diverter)” as shown in FIG. Further, the “diameter” in FIG. 4 indicates the diameter of the cross section orthogonal to the core wire of the medical device. Further, the "inclination" in FIG. 4 indicates an inclination with respect to an arbitrary position on the core line of a cross section orthogonal to the core line (for example, a position on the core line of an adjacent cross section). Further, the "density" in FIG. 4 indicates the density of the mesh of the medical device. Further, the “coverage” in FIG. 4 indicates the ratio of the area covered by the medical device to the treatment target site of the blood vessel.

Here, the "coverage" according to the present application will be described. The "coverage" according to the present application means the area of the medical device with respect to the area of the target site (for example, the neck surface of an aneurysm) in which the inflow of blood is desired to be reduced. That is, the "coverage" according to the present application is represented by "coverage = area of the medical device itself / area of the target site". For example, when the target site is the neck surface and the medical device is a stent, the coverage of the neck surface is "coverage of the neck surface = metal area of the stent / area of the neck surface". Therefore, in the case of a medical device such as Flow Diverter, which has high flexibility and can change the density of the mesh, the higher the density of the mesh, the higher the “coverage”.

For example, the storage circuit 320 stores the index value “density” and the index value “coverage” for each shape indicated by “diameter” and “inclination” for “medical device: FD”. That is, the storage circuit 320 stores an index value of how much blood permeates the medical device for each shape that the medical device can take. As described above, in a medical device such as Flow Diverter, which has high flexibility and can change the density of the mesh, the density of the mesh changes according to the shape, and the degree of blood permeation changes. Therefore, in the present embodiment, the index value for each shape is acquired in advance and stored in the storage circuit 320.

The correspondence information shown in FIG. 4 is merely an example, and the embodiment is not limited to this. For example, as the shape of the medical device, something other than "diameter" and "tilt" may be stored. For example, instead of "inclination", the distance between points having a circumferential shape in each cross section may be stored in a plurality of cross sections orthogonal to the core wire. Further, for example, a case other than "density" and "coverage" may be stored as an index value, or either "density" or "coverage" may be stored. You may.

Returning to FIG. 2, the processing circuit 350 executes the control function 351 and the extraction function 352 and the calculation function 353. Here, the control function 351 is an example of an acquisition unit and an output control unit within the scope of claims. Further, the extraction function 352 is an example of an extraction unit within the scope of claims. Further, the calculation function 353 is an example of a calculation unit within the scope of claims. Here, in the first embodiment, an example of grasping the effect of the indwelling plan formulated when indwelling a medical device (for example, Flow Diverter) will be described.

The control function 351 executes overall control of the medical image processing apparatus 300. For example, the control function 351 acquires medical image data from the medical image diagnostic device 100 or the image storage device 200 via the I / F circuit 310. Specifically, the control function 351 acquires medical image data including a blood flow region through which blood flows. As an example, the control function 351 acquires CT image data (CTA image data) of the head into which the contrast medium is injected. Then, the control function 351 stores the acquired CTA image data in the storage circuit 320. Further, the control function 351 generates a CT image from the CTA image data by various image processing, and controls the generated CT image to be displayed on the display 340. Further, the control function 351 controls so that the information based on the calculation result by the calculation function 353 is displayed on the display 340.

The extraction function 352 extracts the shape of the medical device placed in the blood flow region. Specifically, the extraction function 352 extracts the shape of the medical device placed in the blood flow region (for example, a blood vessel) through which blood flows, which is included in the medical image data acquired by the control function 351. For example, when extracting the shape of a medical device arranged according to the indwelling plan when the Flow Diverter is indwelled, the extraction function 352 uses the extraction function 352 to extract the shape of the medical device included in the medical image data collected after the Flow Diverter is indwelled. To extract.

In the indwelling plan of the medical device, for example, the doctor determines the type and size of the medical device to be indwelled at the treatment target site of the blood vessel while referring to the blood vessel in the CT image generated from the CTA image data. That is, the doctor determines the position and state of the treatment target site of the subject by referring to the CT image, and determines the medical device to be indwelled. Here, the medical image processing apparatus 300 according to the present embodiment accepts an operation of virtually indwelling a medical device in a blood vessel via an input interface 330.

For example, the control function 351 generates a CT image of a blood vessel including a treatment target site from the CTA image data and displays it on the display 340. The operator (for example, a doctor or the like) operates the input interface 330 while referring to the CT image displayed on the display 340 to perform an input operation of placing the medical device on the blood vessel on the CT image.

As described above, in the indwelling plan of the medical device, the medical device is virtually indwelled with respect to the medical image data collected from the subject, and the actual procedure is performed based on the indwelling position. For example, a doctor who performs a procedure for indwelling a medical device performs an actual procedure while referring to a CT image in which a Flow Diverter is virtually indwelled at a treatment target site of a blood vessel. In this case, the control function 351 causes the display 340 to display a CT image in which the Flow Diverter is virtually placed at the treatment target site of the blood vessel.

The medical image processing apparatus 300 according to the first embodiment is indwelled at a treatment target site by calculating and displaying the density and coverage of the medical device (for example, Flow Diverter) indwelled in this way. It makes it possible to grasp the actual effect of the medical device. Hereinafter, the details of the process of calculating and displaying the density and coverage of the medical device will be described.

In such a case, first, the control function 351 acquires medical image data collected after the medical device is placed from the medical image diagnostic device 100 or the image storage device 200 via the I / F circuit 310. For example, the control function 351 acquires CT image data collected after the Flow Diverter is placed on the neck surface of the arterial flow.

The extraction function 352 extracts the shape of the medical device indwelled with respect to the blood vessel region. Specifically, the extraction function 352 identifies the position of the medical device (the position of the voxel corresponding to the position of the medical device) in the medical image data collected after the medical device is placed. Then, the extraction function 352 extracts the shape of the indwelling medical device based on the position of the specified medical device. For example, the extraction function 352 identifies the position of the Flow Diverter included in the CT image data based on the CT value of the CT image data. Extract the shape of the specified Flow Diverter.

FIG. 5 is a diagram for explaining an example of processing by the extraction function 352 according to the first embodiment. Here, FIG. 5 shows an example in which the Flow Diverter is detained according to the detention plan. For example, as shown in the upper part of FIG. 5, for the Flow Diverter placed on the neck surface of the aneurysm, the extraction function 352 determines the type of the placed Flow Diverter and the position of the Flow Diverter in the CT image data. To identify.

As an example, the extraction function 352 identifies the type of Flow Diverter based on the information of the Flow Diverter selected based on the shape of the blood vessel and the position and size of the treatment target site in the indwelling plan. Further, the extraction function 352 specifies the position of the voxel corresponding to the Flow Diverter in the CT image data based on the specified type of Flow Diverter and the CT value in the CT image data of the indwelling Flow Diverter. That is, the extraction function 352 specifies the three-dimensional position of the Flow Diverter in the CT image data.

Then, the extraction function 352 extracts the core wire of the Flow Diverter based on the three-dimensional position of the specified Flow Diverter, and extracts the cross section orthogonal to the extracted core wire. For example, the extraction function 352 uses a vessel tracking method, a method of thinning the internal region, and the like, as shown in the middle diagram of FIG. 5, from the three-dimensional position of the Flow Diverter in the CT image data. The core wire L1 of the above is extracted. Further, the extraction function 352 extracts a cross section on the Flow Diverter orthogonal to the extracted core wire. For example, the extraction function 352 extracts cross sections 31 to 38 of the Flow Diverter orthogonal to the extracted core wire L1 as shown in the lower figure of FIG. Here, the interval between the cross sections to be extracted is arbitrary, and may be a case where the interval between the cross sections is determined according to the diameter of the cross section, for example. As an example, the larger the diameter of the cross section, the larger the interval between the cross sections may be. Further, for example, a cross section may be extracted at predetermined distances in the longitudinal direction of the medical device.

As described above, when the cross section orthogonal to the core wire in the Flow Diverter is extracted, the extraction function 352 extracts the diameter and the inclination of the cross section with respect to the core wire for each cross section. For example, the extraction function 352 extracts the diameters of the cross sections 31 to 38, respectively. That is, the extraction function 352 extracts the diameter of each cross section in order to calculate the density of the mesh. Here, when the Flow Diverter bends along the bend of the blood vessel, a density difference occurs between the inside and the outside of the bend. Therefore, the extraction function 352 extracts the inclination of each cross section in addition to the above-mentioned diameter.

FIG. 6 is a diagram for explaining an example of processing by the extraction function 352 according to the first embodiment. Here, in FIG. 6, the case of extracting the inclination between the cross section 34 and the cross section 35 will be described as an example. For example, as shown in FIG. 6, the extraction function 352 extracts an angle “α” and an angle “β” between the cross section 34 and the cross section 35. That is, the extraction function 352 extracts the degree of bending of the Flow Diverter placed in the blood vessel. Here, the Flow Diverter bends along the running of the blood vessel, but the running of the blood vessel is complicated and bends in various directions. Therefore, since the bending of the Flow Diverter placed in the blood vessel becomes complicated, the extraction function 352 extracts at least two or more inclinations when extracting the inclination between the cross sections, as shown in FIG. It is desirable to do.

In the above-mentioned example, the case where the bending condition of the Flow Diverter is extracted by the inclination of the cross section has been described. However, the embodiment is not limited to this, and may be, for example, a case where the distance between points on the circumference of a plurality of cross sections is calculated. As an example, the extraction function 352 has a point on the circumference of the cross section 34 and a point on the circumference of the cross section 35 in the two straight lines forming the angle “α” in the cross section 34 and the cross section 35 shown in FIG. Calculate the distance to the point. Similarly, in the cross section 34 and the cross section 35 shown in FIG. 6, the extraction function 352 includes a point on the circumference of the cross section 34 and a point on the circumference of the cross section 35 in the two straight lines forming the angle “β”. Calculate the distance of. Since the distance between the points on the circumference of a plurality of cross sections changes according to the inclination of the cross section, the extraction function 352 calculates the inclination of each cross section by calculating the distance between the points on the circumference of the cross section. Can be extracted.

Returning to FIG. 2, the calculation function 353 calculates an index value indicating the degree of blood permeation for the medical device indwelled in the blood flow region based on the shape when the medical device is indwelled. Specifically, the calculation function 353 calculates the index value by reading out the associated index value stored in the storage circuit 320 based on the shape when the medical device is placed. That is, the calculation function 353 calculates the index value for each position in the medical device from which the shape is extracted based on the correspondence information. For example, the calculation function 353 calculates an index value for each position of the medical device based on the corresponding information and the diameter and inclination of the cross section orthogonal to the core wire for each position of the medical device. Hereinafter, an example of processing by the calculation function 353 will be described with reference to FIG. For example, the calculation function 353 is on the circumference of the cross section 34 of two straight lines forming the angle "α" based on the corresponding information, the diameter of the cross section 34, the diameter of the cross section 35, and the angle "α". The density of the mesh between the point and the point on the circumference of the cross section 35 is calculated.

As described above, the corresponding information stored by the storage circuit 320 is information in which the "diameter" of the cross section orthogonal to the core wire and the "density" for each "inclination" are associated with each other. Here, as the "density" in the corresponding information, the density on the inclined side and the density on the opposite side are stored. For example, the correspondence information stores the density of the side tilted at the angle "α" and the density of the side facing the tilted side at the angle "α" on the surface of the Flow Diverter. Therefore, the calculation function 353 obtains the diameter of the cross section 34, the diameter of the cross section 35, and the density corresponding to the angle “α” from the corresponding information, so that the side tilted at the angle “α” on the surface of the Flow Diverter. The density and the density of the side facing the side inclined at the angle "α" are calculated.

Here, when the diameter of the cross section 34 and the diameter of the cross section 35 are substantially the same, the calculation function 353 has a point on the circumference of the two straight lines forming the angle "α" and the circumference of the cross section 35. The density of the mesh between the upper points is calculated as the same density. On the other hand, when the diameter of the cross section 34 and the diameter of the cross section 35 are different, the calculation function 353 divides, for example, between the point on the circumference of the cross section 34 and the point on the circumference of the cross section 35 into two ranges from the center. do. Then, the calculation function 353 acquires the density corresponding to the diameter and the angle “α” of the cross section 34 from the corresponding information as the density of the mesh in the range on the cross section 34 side. Further, the calculation function 353 acquires the density corresponding to the diameter and the angle “α” of the cross section 35 from the corresponding information as the density of the mesh in the range on the cross section 35 side.

Similarly, the calculation function 353 obtains the diameter of the cross section 34, the diameter of the cross section 35, and the density corresponding to the angle “β” from the corresponding information, so that the side tilted at the angle “β” on the surface of the Flow Diverter. And the density of the side facing the side inclined at the angle "β" are calculated.

Then, the calculation function 353 has a density on the surface of the Flow Diverter on the side tilted at the angle "α", a density on the side facing the tilted side at the angle "α", and a density on the side tilted at the angle "β". And the density of the side facing the tilted side at the angle "β" are used to calculate the density distribution of the entire surface of the Flow Diverter. For example, the calculation function 353 divides the space between the side tilted at the angle “α” and the side tilted at the angle “β” into two ranges from the center. Then, the calculation function 353 applies the density of the side tilted at the angle “α” as the density of the mesh in the range of the side tilted at the angle “α”. Further, the calculation function 353 applies the density of the side tilted at the angle "β" as the density of the mesh in the range of the side tilted at the angle "β".

Similarly, the calculation function 353 divides the space between the side tilted at the angle “α” and the side facing the side tilted at the angle “β” into two ranges from the center. Then, the calculation function 353 applies the density of the side tilted at the angle “α” as the density of the mesh in the range of the side tilted at the angle “α”. Further, the calculation function 353 applies the density of the side facing the tilted side at the angle "β" as the density of the mesh in the range of the side facing the tilted side at the angle "β".

Similarly, the calculation function 353 faces the side facing the tilted side at the angle "β" and the side facing the tilted side at the angle "α", and faces the side facing the tilted side at the angle "α". The density distribution is calculated for the range between the side and the side tilted at the angle "β".

The above-mentioned calculation of the density is only an example, and the calculation function 353 can calculate the density by various other methods. For example, the storage circuit 320 stores in advance the corresponding information associated with the density distribution of the entire surface of the Flow Diverter for each “diameter” and “inclination” of the Flow Diverter. As an example, the storage circuit 320 stores in advance the corresponding information associated with the density distribution of the entire surface of the Flow Diverter for each combination of the “diameter” and the “inclination” of the cross section. Then, the calculation function 353 calculates the mesh density of the Flow Diverter by acquiring the density distribution corresponding to the "diameter" and the "slope" of the Flow Diverter extracted by the extraction function 352.

Further, the calculation function 353 calculates, as an index value, a coverage ratio indicating the ratio of the region covered by the medical device to the treatment target site of the blood vessel. Specifically, the calculation function 353 calculates the coverage for each position of the blood vessel covered by the Flow Diverter based on the calculated mesh density. For example, the calculation function 353 calculates the coverage on the neck surface of the cerebral aneurysm. Here, as shown in FIG. 4, when the corresponding information includes the covering ratio, the calculation function 353 obtains the corresponding covering ratio for each range in which the density is calculated, so that the blood vessels covered in each range can be covered. Calculate the coverage for each position.

Returning to FIG. 2, the control function 351 controls to output the index value for each position. For example, the control function 351 controls the display 340 to display the density and coverage calculated by the calculation function 353. 7 and 8 are diagrams showing an example of an index value displayed by the control of the control function 351 according to the first embodiment. Here, FIG. 7 shows a case where the mesh density of the Flow Diverter is displayed as an index value. Further, FIG. 8 shows a case where the coverage by Flow Diverter is displayed as an index value.

For example, as shown in FIG. 7, the control function 351 generates a color map showing the high and low densities by different colors and displays it on the display 340. As an example, the Flow Diverter of the CT image generated based on the CT image data collected after the Flow Diverter is indwelled is displayed in a color-coded display image according to the difference in density. Here, it can be seen that the Flow Diverter placed in the aneurysm shown in FIG. 7 has a high density inside the bend and a low density outside the bend.

Further, for example, the control function 351 causes the display 340 to display the coverage on the neck surface of the aneurysm, as shown in FIG. Here, the image of the neck surface on the right side in FIG. 8 shows an image when the region R1 is viewed from the direction of the arrow 41. For example, the control function 351 generates an image when the region R1 is viewed from the direction of the arrow 41 using CT image data, and together with the generated image, the neck surface of the aneurysm (the mesh in the figure on the right side of FIG. 8 is formed). The coverage rate "87.5%" of the covered area) is displayed. Here, as shown in FIG. 8, the control function 351 may display the distance distribution between the tissue and the stent (Flow Diverter) together.

As described above, in the medical image processing apparatus 300 according to the first embodiment, the density and coverage of the mesh for each position of the medical device in which the medical device (for example, Flow Diverter) is indwelled according to the indwelling plan is displayed. .. This allows the operator to visually grasp the effect of the medical device indwelled according to the indwelling plan. For example, the operator can determine how much blood can be suppressed from flowing into the aneurysm based on the coverage of the neck surface of the aneurysm. For example, the operator can more accurately grasp the risk of aneurysm rupture (that is, obtain a high therapeutic effect) by confirming whether or not the coverage of the neck surface of the aneurysm is equal to or higher than a predetermined value. It can be determined whether or not it has been obtained).

Here, in the above-mentioned example, the case of displaying the index value of the medical device detained according to the detention plan has been described. The medical image processing apparatus 300 can also display simulation information of the optimum indwelling plan. For example, the control function 351 simulates the type of medical device to be indwelled and the shape of the medical device in the blood vessel so that the index value of the position of the medical device corresponding to the treatment target site of the blood vessel satisfies a preset condition. Display information. For example, the control function 351 displays information on the type of a candidate medical device in the indwelling plan and the shape of the medical device whose index value is equal to or higher than a predetermined value when the medical device is placed in the treatment target site. .. As an example, the control function 351 displays the shape of the Flow Diverter in which the coverage on the neck surface of the aneurysm is equal to or higher than a predetermined value.

Further, in the above-mentioned example, a case where the density and the coverage are calculated using the corresponding information stored by the storage circuit 320 has been described. However, the embodiment is not limited to this, and may be calculated from the acquired medical image data. In such a case, for example, the calculation function 353 calculates the density and coverage of the medical device from the mesh state of the medical device extracted by the extraction function 352.

Next, the procedure of processing by the medical image processing apparatus 300 according to the first embodiment will be described with reference to FIGS. 9 and 10. 9 and 10 are flowcharts showing a processing procedure by the medical image processing apparatus 300 according to the first embodiment. Here, FIG. 10 shows the process corresponding to step S105 in the flowchart of FIG. Further, FIGS. 9 and 10 show an example of indwelling a Flow Diverter for a cerebral aneurysm.

Step S101, step S102, and step S107 in FIG. 9 are realized, for example, by the processing circuit 350 reading a program corresponding to the control function 351 from the storage circuit 320 and executing the program. Further, step S103 is realized by, for example, the input interface 330 receiving an input operation from the operator. Further, step S104 is realized, for example, by the processing circuit 350 reading a program corresponding to the extraction function 352 from the storage circuit 320 and executing the program. Further, steps S105 and S106 are realized, for example, by the processing circuit 350 reading a program corresponding to the calculation function 353 from the storage circuit 320 and executing the program.

In the medical image processing device 300 according to the present embodiment, first, the processing circuit 350 acquires head CTA image data from the medical image diagnostic device 100 or the image storage device 200 (step S101). Then, the processing circuit 350 extracts the cerebral blood vessels and aneurysms included in the acquired CTA image data (step S102). Then, when the input interface 330 receives an input operation from the operator, a virtual Flow Diverter is placed in the CTA image data (step S103).

After that, when the Flow Diverter is detained according to the detention plan and the CT image data after the detention is acquired, the processing circuit 350 detects the shape and position of the detained Flow Diverter based on the position of the virtual Flow Diverter. (Step S104), the metal density on the surface of the Flow Diverter is calculated (step S105). Further, the processing circuit 350 calculates the coverage on the neck surface of the cerebral aneurysm (step S106) and displays the calculated metal density and coverage (step S107).

Further, in the medical image processing apparatus 300, in the calculation of the metal density on the surface of the Flow Diverter, as shown in FIG. 10, the processing circuit 350 extracts the core wire of the Flow Diverter (step S1051) and refers to the core wire of the Flow Diverter. The orthogonal cross section is detected (step S1052). Then, the processing circuit 350 calculates the diameter of the orthogonal cross section (step S1053), and calculates the inclination of the orthogonal cross section with respect to the core wire (step S1054). Further, the processing circuit 350 calculates the metal density on the surface of the Flow Diverter from the diameter and inclination of the orthogonal cross section (step S1055).

As described above, according to the first embodiment, the control function 351 acquires medical image data including a blood flow region through which blood flows. The extraction function 352 extracts the shape of the medical device placed in the blood flow region. The calculation function 353 calculates an index value indicating the degree of blood permeation of the medical device indwelled in the blood flow region based on the shape when the medical device is indwelled. The control function 351 controls to output an index value. Therefore, the medical image processing apparatus 300 according to the first embodiment can provide information on the ease of blood passage for each position of the medical device, and can grasp the effect of the placement of the medical device on the blood flow. to enable.

Further, according to the first embodiment, the storage circuit 320 stores the shape of the medical device when it is placed and the index value in association with each other for each type of medical device. The calculation function 353 calculates the index value by reading out the associated index value stored in the storage circuit 320 based on the shape when the medical device is placed. Therefore, the medical image processing apparatus 300 according to the first embodiment makes it possible to reduce the processing load related to the calculation of the index value.

Further, according to the first embodiment, the storage circuit 320 stores the corresponding information associated with the index value for each shape indicated by the diameter and inclination of the cross section orthogonal to the core wire of the medical device. The extraction function 352 extracts the diameter and inclination of the cross section orthogonal to the core wire for each position of the medical device placed in the blood flow region. The calculation function 353 calculates an index value for each position of the medical device based on the corresponding information and the diameter and inclination of the cross section orthogonal to the core wire for each position of the medical device. Therefore, the medical image processing apparatus 300 according to the first embodiment has high flexibility and more accurately grasps the effect of indwelling a medical device such as Flow Diverter whose density changes with a change in shape. Allows you to.

Further, according to the first embodiment, the extraction function 352 extracts the shape of the medical device included in the medical image data collected after the medical device is indwelled according to the indwelling plan of the medical device. The calculation function 353 calculates an index value for each position in the medical device based on the shape of the medical device. Therefore, the medical image processing apparatus 300 according to the first embodiment makes it possible to more accurately grasp the effect of the indwelling of the medical device indwelled according to the indwelling plan.

Further, according to the first embodiment, the control function 351 relates to the shape of the medical device in the blood vessel so that the index value of the position of the medical device corresponding to the treatment target site of the blood vessel satisfies a preset condition. Display simulation information. Therefore, the medical image processing apparatus 300 according to the first embodiment makes it possible to formulate an optimum indwelling plan.

Further, according to the first embodiment, the calculation function 353 calculates, as an index value, a coverage ratio indicating the ratio of the region covered by the medical device to the treatment target site of the blood vessel. The control function 351 displays the calculated coverage. Therefore, the medical image processing apparatus 300 according to the first embodiment can present information on how much blood flow is blocked by the medical device, and can easily determine the effect of indwelling the medical device. to enable.

Further, according to the first embodiment, the calculation function 353 calculates the coverage on the neck surface of the cerebral aneurysm. The control function 351 displays the calculated coverage on the medical image showing the neck surface of the cerebral aneurysm. Therefore, the medical image processing apparatus 300 according to the first embodiment makes it possible to provide an index regarding the inflow of blood into the aneurysm.

(Second embodiment)
In the first embodiment described above, the case of displaying the index value of the medical device (for example, Flow Diverter) indwelled according to the indwelling plan has been described. In the second embodiment, the case where the index value is displayed during the treatment will be described. Hereinafter, the same components as those in the first embodiment may be designated by the same reference numerals and description thereof may be omitted. Further, in the second embodiment, a case where a Flow Diverter is placed in a cerebral aneurysm by using an X-ray diagnostic device (X-ray angio device) will be described as an example.

The control function 351 according to the second embodiment acquires X-ray image data collected by the X-ray diagnostic apparatus. Specifically, the control function 351 acquires contrast-enhanced Angio image data taken by injecting a contrast medium into the subject and non-contrast-enhanced Angio image data taken without injecting the contrast medium. For example, the control function 351 acquires the collected contrast-enhanced Angio image data for alignment with the CTA image data used in the indwelling plan. Further, for example, the control function 351 acquires real-time non-contrast Angio image data collected during the indwelling (during treatment) of the Flow Diverter.

Further, the control function 351 executes the alignment between the images. Specifically, the control function 351 executes the alignment of the medical image data used in the indwelling plan with the medical image data collected during the treatment. For example, the control function 351 executes alignment between the CTA image data used in the indwelling plan and the contrast-enhanced Angio image data. Here, the control function 351 extracts a blood vessel and a treatment target site (for example, an aneurysm) in the contrast-enhanced Angio image data prior to the alignment between the images.

Then, the control function 351 executes alignment between images based on anatomical landmarks of bones, geometric features such as blood vessel structures, and the like. For example, the control function 351 calculates an alignment matrix for aligning the CTA image data and the non-contrast Angio image data by aligning the CTA image data and the contrast-enhanced Angio image data. The control function 351 can use not only the above-mentioned alignment but also various existing alignment methods.

As described above, the control function 351 is a medical device included in the medical image data collected during the operation by preliminarily aligning the medical image data used for the indwelling plan with the medical image data used during the operation. It makes it possible to estimate a three-dimensional position and shape (attitude). For example, when a two-dimensional X-ray image such as non-contrast Angio image data is used during surgery, it is difficult to estimate the three-dimensional position and shape (posture) of the medical device included in the X-ray image in the blood vessel. Is. Therefore, the control function 351 aligns the medical image data used in the indwelling plan with the medical image data used during the operation to determine the three-dimensional position of the medical device indwelled during the operation in the blood vessel. It makes it possible to estimate the shape (attitude).

The extraction function 352 according to the second embodiment extracts the shape of the medical device included in the medical image data collected during the operation. Specifically, the extraction function 352 estimates the position and shape (posture) of the medical device from the medical image data collected during the indwelling of the medical device. For example, the extraction function 352 estimates the three-dimensional position and shape (posture) of the Flow Diverter included in the real-time non-contrast Angio image data collected during the indwelling (during treatment) of the Flow Diverter.

FIG. 11 is a diagram for explaining an example of processing by the extraction function 352 according to the second embodiment. For example, the extraction function 352 first aligns the CTA image data and the non-contrast Angio image data by applying the alignment matrix to the non-contrast Angio image data shown in the upper part of FIG. 11. Then, the extraction function 352 extracts the Flow Diverter region from the non-contrast Angio image data as shown in the middle figure of FIG. For example, the extraction function 352 may perform subtraction between the non-angiographic Angio image data before the placement of the Flow Diverter and the non-contrast Angio image data after the placement of the Flow Diverter, a region search limited to the region around the aneurysm extracted in advance, and a metal X-ray. The Flow Diverter region is extracted from the non-contrast Angio image data by combining the extraction of the signal value distribution of the Flow Diverter from the absorption rate.

Then, the extraction function 352 estimates the position and shape (posture) of the Flow Diverter in the three-dimensional CTA image data using the Flow Diverter region extracted from the non-contrast Angio image data. Specifically, the extraction function 352 estimates the position and orientation of the Flow Diverter in the three-dimensional space by projecting the extracted Flow Diverter region onto the aligned CTA image data. For example, the extraction function 352 first samples a plurality of landmarks from the blood vessels in the Flow Diverter region and the CTA image data, respectively. Further, the extraction function 352 associates a plurality of landmarks in the Flow Diverter region with a plurality of landmarks in the CTA image data.

Then, the extraction function 352 acquires a plurality of projection results while changing the projection direction of the Flow Diverter region with respect to the CTA image data. After that, the extraction function 352 calculates the total distance between the associated landmarks for each projection result. The extraction function 352 extracts the projection result having the smallest value among the calculated total distances as the position and orientation of the Flow Diverter in the three-dimensional space.

When the position and orientation of the Flow Diverter in the three-dimensional space are estimated as described above, the extraction function 352 executes the same processing as in the first embodiment. That is, the extraction function 352 extracts the core wire of the Flow Diverter based on the position and orientation of the Flow Diverter in the three-dimensional space, and calculates the diameter and inclination of the cross section orthogonal to the extracted core wire. The calculation function 353 calculates the surface density of the Flow Diverter and the coverage based on the calculated diameter and inclination. The control function 351 displays the calculated density and coverage.

Next, the procedure of processing by the medical image processing apparatus 300 according to the second embodiment will be described with reference to FIG. FIG. 12 is a flowchart showing a processing procedure by the medical image processing apparatus 300 according to the second embodiment. Here, in FIG. 12, the processing in each process of "treatment plan (indwelling plan)", "treatment preparation", and "during treatment" is shown. Further, FIG. 12 shows an example of indwelling a Flow Diverter for a cerebral aneurysm.

Steps S201 to S206 and step S209 in FIG. 12 are realized, for example, by the processing circuit 350 reading a program corresponding to the control function 351 from the storage circuit 320 and executing the program. Further, step S207 is realized, for example, by the processing circuit 350 reading a program corresponding to the extraction function 352 from the storage circuit 320 and executing the program. Further, step S208 is realized, for example, by the processing circuit 350 reading a program corresponding to the calculation function 353 from the storage circuit 320 and executing the program.

In the medical image processing device 300 according to the present embodiment, first, in the process of treatment planning (indwelling plan), the processing circuit 350 acquires head CTA image data from the medical image diagnostic device 100 or the image storage device 200. Cerebral blood vessels and aneurysms are extracted (step S101, step S102).

Then, in the process of preparing for treatment, the processing circuit 350 acquires contrasting Angio image data from the X-ray diagnostic apparatus or the image storage apparatus 200 (step S201), and extracts cerebrovascular vessels and aneurysms (step S202). After that, the processing circuit 350 executes image-to-image alignment between the head CTA image data from which the cerebral blood vessels and the aneurysm are extracted in step S102 and the contrast-enhanced Angio image data (step S203).

Then, in the process of treatment, the processing circuit 350 acquires real-time non-contrast Angio image data from the X-ray diagnostic apparatus (step S204) and applies an alignment matrix to the non-contrast Angio image data (step). S205). Further, the processing circuit 350 detects the shape and position of the Flow Diverter in the non-contrast Angio image data (step S206). Then, the processing circuit 350 estimates the three-dimensional position and orientation of the Flow Diverter in the non-contrast Angio image data (step S207), and calculates the metal density and coverage of the surface of the Flow Diverter (step S208). After that, the processing circuit 350 displays the calculated metal density and coverage (step S209).

As described above, according to the second embodiment, the extraction function 352 extracts the shape of the medical device included in the medical image data collected intraoperatively. The calculation function 353 calculates an index value for each position in the medical device included in the medical image data collected during the operation based on the correspondence information. Therefore, the medical image processing apparatus 300 according to the second embodiment can provide information on the ease of blood passage for each position of the medical device during the operation, and the effect of the placement of the medical device on the blood flow is performed during the operation. It makes it possible to grasp.

Further, according to the second embodiment, the medical image processing apparatus 300 can provide information on the ease of blood passage for each position of the medical device during the operation by using the non-contrast Angio image data. That is, the medical image processing apparatus 300 can reduce the amount of the contrast medium used during the operation, reduce the burden on the subject, and suppress the increase in the treatment cost.

(Third embodiment)
In the second embodiment described above, the case where the index value is displayed during the treatment has been described. A third embodiment describes the case of navigating the placement of a medical device during treatment. Hereinafter, the same components as those in the first embodiment may be designated by the same reference numerals and description thereof may be omitted. Further, in the third embodiment, a case where a Flow Diverter is placed in a cerebral aneurysm by using an X-ray diagnostic device (X-ray angio device) will be described as an example.

The control function 351 according to the third embodiment displays navigation information for eliminating the dissociation during treatment with respect to the optimal indwelling plan formulated at the time of planning. Specifically, the control function 351 calculates the difference between the index value calculated at the time of indwelling planning and the index value calculated during treatment, and the calculated difference satisfies a predetermined condition (for example, a predetermined threshold value or less). To display the navigation information. For example, the control function 351 calculated and calculated the difference between the density and coverage in the optimal indwelling plan described in the first embodiment and the density and coverage during treatment described in the second embodiment. Display the navigation information so that the difference satisfies a predetermined condition.

FIG. 13 is a diagram showing an example of processing by the control function 351 according to the third embodiment. For example, the control function 351 provides real-time non-real-time navigation information "pack 5 mm more closely" so that the end 51 of the Flow Diverter is packed "5 mm" toward the center, as shown in the figure on the left side of FIG. Display on the contrast-enhanced Angio image. Further, for example, the control function 351 provides navigation information "closely packed by 2 mm" so that the upper half of the Flow Diverter mesh on the neck surface is packed by "2 mm" as shown in the figure on the right side of FIG. It is displayed on the cross-sectional image of the neck surface.

In order to perform the above navigation, for example, the control function 351 first calculates the difference between the coverage in the optimum placement plan formulated using the CTA image data and the coverage calculated from the non-contrast Angio image data. Then, the control function 351 calculates the adjustment amount (movement amount) of the Flow Diverter so that the calculated difference satisfies a predetermined condition based on the corresponding information. As an example, the control function 351 uses the corresponding information to adjust the amount of adjustment for changing the inclination of the cross section orthogonal to the core line of the Flow Diverter in the real-time non-contrast Angio image data to the inclination of the cross section satisfying the condition. calculate. Then, as shown in FIG. 13, the control function 351 displays the calculated adjustment amount on the image.

Although FIG. 13 shows a case where only navigation information is displayed, the embodiment is not limited to this, and for example, an index value at the time of indwelling plan, an index value during treatment, and an index value at the time of indwelling plan are shown. It may be the case that the difference between the index value and the index value under treatment is appropriately displayed. Further, the control function 351 provides navigation information (for example, navigation for moving the entire Flow Diverter) so as to adjust when the position of the Flow Diverter detained in real time deviates from the detention position determined at the time of detention planning. , Navigation to adjust the position of the end, etc.) can also be displayed. Further, the control function 351 can also distinguish and highlight a region where the difference between the index values exceeds the threshold value and a portion deviated from the indwelling position in the real-time non-contrast Angio image.

Next, the procedure of processing by the medical image processing apparatus 300 according to the third embodiment will be described with reference to FIG. FIG. 14 is a flowchart showing a processing procedure by the medical image processing apparatus 300 according to the third embodiment. Here, in FIG. 14, the processing in each process of “treatment plan (indwelling plan)”, “treatment preparation”, and “during treatment” is shown. Further, FIG. 14 shows an example of indwelling a Flow Diverter for a cerebral aneurysm.

Steps S301 and S302 in FIG. 14 are realized, for example, by the processing circuit 350 reading a program corresponding to the control function 351 from the storage circuit 320 and executing the program.

In the medical image processing device 300 according to the present embodiment, first, in the process of treatment planning (indwelling plan), the processing circuit 350 acquires head CTA image data from the medical image diagnostic device 100 or the image storage device 200. Cerebral blood vessels and aneurysms are extracted (step S101, step S102). Then, when the input interface 330 receives an input operation from the operator, a virtual Flow Diverter is placed in the CTA image data (step S103), and the processing circuit 350 formulates an optimum placement plan for the Flow Diverter (step S103). Step S108).

Then, in the process of preparing for treatment, the processing circuit 350 acquires contrasting Angio image data from the X-ray diagnostic apparatus or the image storage apparatus 200 (step S201), and extracts cerebrovascular vessels and aneurysms (step S202). After that, the processing circuit 350 executes image-to-image alignment between the head CTA image data from which the cerebral blood vessels and the aneurysm are extracted in step S102 and the contrast-enhanced Angio image data (step S203).

Then, in the process of treatment, the processing circuit 350 acquires real-time non-contrast Angio image data from the X-ray diagnostic apparatus (step S204) and applies an alignment matrix to the non-contrast Angio image data (step). S205). Further, the processing circuit 350 detects the shape and position of the Flow Diverter in the non-contrast Angio image data (step S206). Then, the processing circuit 350 estimates the three-dimensional position and orientation of the Flow Diverter in the non-contrast Angio image data (step S207), and calculates the metal density and the coverage (step S208). After that, the processing circuit 350 calculates the difference from the optimum indwelling plan (step S301) and displays the navigation for eliminating the deviation from the optimum indwelling plan (step S302).

As described above, according to the third embodiment, the control function 351 is a medical device in the blood vessel so that the index value of the position of the medical device corresponding to the treatment target site of the blood vessel satisfies a preset condition. Display simulation information about the shape of. Therefore, the medical image processing apparatus 300 according to the third embodiment makes it possible to navigate the optimal placement of the medical device during the operation.

(Fourth Embodiment)
In the fourth embodiment, a case where the index value is displayed during the follow-up will be described. Hereinafter, the same components as those in the first embodiment may be designated by the same reference numerals and description thereof may be omitted.

The storage circuit 320 according to the fourth embodiment stores the index value for each subject calculated over time. Specifically, the storage circuit 320 stores index values during indwelling planning, treatment, and follow-up after treatment for each subject. Here, during the follow-up, not only the X-ray CT device and the X-ray diagnostic device but also an intravascular ultrasound (IVUS) may be performed. The processing circuit 350 calculates index values for various medical image data as described above, and stores the calculated index values in the storage circuit 320.

Then, the control function 351 displays display information in which index values are arranged in chronological order for each subject. FIG. 15 is a diagram showing an example of processing by the control function 351 according to the fourth embodiment. For example, as shown in FIG. 15, the control function 351 displays a graph showing the coverage on the vertical axis and the time on the horizontal axis on the display 340. Here, as shown in FIG. 15, the control function 351 displays a graph including the coverage at the time of treatment planning, the coverage at the time of treatment, and the coverage at the time of follow-up. This allows the operator to easily confirm whether or not the indwelling medical device maintains a stable state.

For example, coverage is expected to be a factor in assessing whether an aneurysm ruptures. As shown in FIG. 15, by monitoring the state of coverage, for example, when the Flow Diverter moves due to hitting the head, or when an aneurysm or neck surface expands after treatment, the coverage decreases. , The state of the subject can be easily observed. For example, lower coverage and less physical coverage of the neck surface increases the likelihood of blood flowing into the aneurysm, resulting in the placement of additional Flow Diverters and other treatments (eg Clip). It is determined whether or not to do.

Next, the procedure of processing by the medical image processing apparatus 300 according to the fourth embodiment will be described with reference to FIG. FIG. 16 is a flowchart showing a processing procedure by the medical image processing apparatus 300 according to the fourth embodiment. Here, in FIG. 16, the processing in each process of “treatment plan (indwelling plan)”, “treatment”, and “follow-up” is shown. Further, FIG. 16 shows an example of indwelling a Flow Diverter for a cerebral aneurysm.

Step S1101, step S1102, step S2101, step S2102, step S3101, step S3102, and step S401 in FIG. 16 are realized, for example, by the processing circuit 350 reading a program corresponding to the control function 351 from the storage circuit 320 and executing the program. Will be done. Further, step S2104 and step S3104 are realized, for example, by the processing circuit 350 reading a program corresponding to the extraction function 352 from the storage circuit 320 and executing the program. Further, step S2105, step S2106, step S3105, and step S3106 are realized, for example, by the processing circuit 350 reading a program corresponding to the calculation function 353 from the storage circuit 320 and executing the program.

In the medical image processing device 300 according to the present embodiment, first, in the process of treatment planning (indwelling plan), the processing circuit 350 acquires medical image data from the medical image diagnosis device 100 or the image storage device 200, and the cerebral blood vessels. And the aneurysm is extracted (step S1101, step S1102). Then, when the input interface 330 receives an operation from the operator, the virtual Flow Diverter is placed in the medical image data (step S1103). Then, the processing circuit 350 formulates an optimum detention plan for the Flow Diverter (step S1108), and stores the formulation result in the storage circuit 320. The processing circuit 350 executes the above-mentioned processing each time the treatment plan is implemented.

Next, in the process of treatment, the processing circuit 350 acquires medical image data from the medical image diagnostic device 100 or the image storage device 200, and extracts cerebral blood vessels and aneurysms (step S2101, step S2102). Then, when the doctor indwells the Flow Diverter (step S2103), the processing circuit 350 detects the shape and position of the Flow Diverter (step S2104), and calculates the metal density on the surface of the Flow Diverter (step S2105). Further, the processing circuit 350 calculates the coverage of the neck surface of the cerebral aneurysm (step S2106), and stores the calculation result in the storage circuit 320. The processing circuit 350 executes the above-mentioned processing every time the treatment is performed.

Next, in the process of follow-up, the processing circuit 350 acquires medical image data from the medical image diagnostic device 100 or the image storage device 200, and extracts cerebral blood vessels and aneurysms (step S3101, step S3102). Then, the processing circuit 350 detects the shape and position of the Flow Diverter (step S3104), and calculates the metal density on the surface of the Flow Diverter (step S3105). Further, the processing circuit 350 calculates the coverage of the neck surface of the cerebral aneurysm (step S3106), and stores the calculation result in the storage circuit 320. The processing circuit 350 executes the above-mentioned processing every time medical image data is collected in the follow-up observation.

Then, the processing circuit 350 causes the display 340 to display the change with time of the calculation result (metal density and coverage) stored by the storage circuit 320 (step S401). In addition, the display of the change with time may be executed every time the index value is calculated in any one of the treatment plan, the treatment, and the follow-up.

As described above, according to the fourth embodiment, the storage circuit 320 stores the index value for each subject calculated over time. The control function 351 displays display information in which index values are arranged in chronological order for each subject. Therefore, the medical image processing apparatus 300 according to the fourth embodiment makes it possible to display the optimum information indicating the state of prognosis. For example, the medical image processing device 300 can present information that can be compared regardless of the type of the medical image diagnostic device 100 that has collected the medical image data by using the density and the coverage.

(Fifth Embodiment)
By the way, although the first to fourth embodiments have been described so far, various different embodiments may be implemented in addition to the above-mentioned first to fourth embodiments.

In the above-described embodiment, the case where the medical device is placed for the cerebral aneurysm has been described as an example, but the embodiment is not limited to this. For example, it may be applied to the placement of a medical device for treating aortic aneurysm, coronary artery stenosis, ventricular / atrial septal defect, and lower limb CTO (Chronic Total Occlusion).

Further, in the above-described embodiment, the case where the Flow Diverter is placed at the treatment target site has been described as an example, but the embodiment is not limited to this, and for example, a coil, a stent, and an atrial septal defect treatment. It may be the case where a device (Amplazzer: Amplatzer, etc.) is placed.

Further, in the above-described embodiment, the case where the medical image processing apparatus 300 executes various processes has been described. However, the embodiment is not limited to this, and various medical diagnostic imaging devices may perform various processes. For example, various processes may be executed in the X-ray diagnostic apparatus. FIG. 17 is a diagram showing an example of the configuration of the X-ray diagnostic apparatus 100a according to the fifth embodiment.

As shown in FIG. 17, the X-ray diagnostic apparatus 100a according to the fifth embodiment includes a high voltage generator 11, an X-ray tube 12, an X-ray throttle 13, a top plate 14, and a C-arm 15. X-ray detector 16, C-arm rotation / movement mechanism 17, top plate movement mechanism 18, C-arm / top plate mechanism control circuit 19, throttle control circuit 20, processing circuit 21, input interface 22. It has a display 23, an image data generation circuit 24, a storage circuit 25, and an image processing circuit 26.

In the X-ray diagnostic apparatus 100a shown in FIG. 17, 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 plate mechanism control circuit 19, aperture control circuit 20, processing circuit 21, image data generation circuit 24, and image processing circuit 26 correspond to each program by reading and executing the program from the storage circuit 25. It is a processor that realizes the function. 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 by using the high voltage supplied from the high voltage generator 11.

Under the control of the diaphragm control circuit 20, the X-ray diaphragm 13 narrows down the X-rays generated by the X-ray tube 12 so as to selectively irradiate the region of interest of the subject P. For example, the X-ray diaphragm 13 has four sliding diaphragm blades. The X-ray diaphragm 13 arbitrarily changes the shape, size, and position of the opening by sliding these diaphragm blades under the control of the diaphragm control circuit 20. By adjusting the size and position of the opening by the X-ray diaphragm 13 in this way, the size and position of the X-ray irradiation region on the detection surface of the X-ray detector 16 are adjusted. That is, the X-rays generated by the X-ray tube 12 are narrowed down by the opening of the X-ray diaphragm 13 and irradiated to the subject P. Further, the X-ray diaphragm 13 can be provided with an additional filter for adjusting the radiation quality. The additional filter is set according to the inspection, for example. The top plate 14 is a bed on which the subject P is placed, and is arranged on a bed (not shown).

The X-ray detector 16 detects the X-rays that have passed through the subject P. For example, the X-ray detector 16 has detection elements arranged in a matrix. Each detection element converts X-rays transmitted through the subject P into an electric signal and stores it, and transmits the stored electric signal to the image data generation circuit 24.

The C-arm 15 holds an X-ray tube 12, an X-ray diaphragm 13, and an X-ray detector 16. The C-arm 15 is rotated at high speed like a propeller around a subject P lying on the top plate 14 by a motor provided on a support portion (not shown). Here, the C-arm 15 is rotatably supported with respect to the XYZ axes, which are three orthogonal axes, and is individually rotated on each axis by a drive unit (not shown). The X-ray tube 12, the X-ray diaphragm 13, and the X-ray detector 16 are arranged so as to face each other with the subject P interposed therebetween by the C arm 15.

The C-arm rotation / movement mechanism 17 is a mechanism for rotating and moving the C-arm 15. Further, the C-arm rotation / movement mechanism 17 can change the SID (Source Image receptor Distance), which is the distance between the X-ray tube 12 and the X-ray detector 16. Further, the C-arm rotation / movement mechanism 17 can also rotate the X-ray detector 16 held by the C-arm 15. The top plate moving mechanism 18 is a mechanism for moving the top plate 14.

The C-arm / top plate mechanism control circuit 19 controls the C-arm rotation / movement mechanism 17 and the top plate movement mechanism 18 under the control of the processing circuit 21 to rotate and move the C-arm 15 and the top plate 14. Adjust the movement. Under the control of the processing circuit 21, the diaphragm control circuit 20 changes the shape, size, and position of the aperture by adjusting the opening degree of the diaphragm blades of the X-ray diaphragm 13, and irradiates the subject P with light. Control the X-ray irradiation range.

The image data generation circuit 24 generates projection data using an electric signal converted from X-rays by the X-ray detector 16, and stores the generated projection data in the storage circuit 25. For example, the image data generation circuit 24 performs current / voltage conversion, A (Analog) / D (Digital) conversion, and parallel / serial conversion on the electric signal received from the X-ray detector 16 to generate projection data. do. Then, the image data generation circuit 24 stores the generated projection data (X-ray image data) in the storage circuit 25.

The storage circuit 25 receives and stores the projection data generated by the image data generation circuit 24. Further, the storage circuit 25 stores programs corresponding to various functions read and executed by each circuit shown in FIG. Further, the storage circuit 25 stores the correspondence information and the calculation result such as the coverage ratio, similarly to the storage circuit 320. The storage circuit 25 is an example of a storage unit within the scope of claims.

The image processing circuit 26 generates an X-ray image by performing various image processing on the projection data stored in the storage circuit 25 under the control of the processing circuit 21. Alternatively, the image processing circuit 26 directly acquires projection data from the image data generation circuit 24 under the control of the processing circuit 21 described later, and performs various image processing on the acquired projection data to obtain an X-ray image. Generate. The image processing circuit 26 can also store the X-ray image after image processing in the storage circuit 25. For example, the image processing circuit 26 can execute various processes by an image processing filter such as a moving average (smoothing) filter, a Gaussian filter, a median filter, a recursive filter, and a bandpass filter.

The input interface 22 includes a trackball for setting a predetermined area (for example, ROI in partial fluoroscopy), a switch button, a mouse, a keyboard, a touch pad for performing an input operation by touching an operation surface, and a display screen. It is realized by a touch screen integrated with a touch pad, a non-contact input circuit using an optical sensor, a voice input circuit, and a foot switch for irradiating X-rays.

The input interface 22 is connected to the processing circuit 21, converts the input operation received from the operator into an electric signal, and outputs the input operation to the processing circuit 21. In the present specification, the input interface 22 is not limited to the one provided with physical operation parts such as a mouse and a keyboard. For example, an example of an input interface includes an electric signal processing circuit that receives an electric signal corresponding to an input operation from an external input device provided separately from the device and outputs the electric signal to a control circuit. The display 23 displays a GUI (Graphical User Interface) for receiving instructions from the operator and various images generated by the image processing circuit 26. Further, the display 23 displays various processing results by the processing circuit 21.

The processing circuit 21 controls the operation of the entire X-ray diagnostic apparatus 100a. 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. X-ray dose and ON / OFF are controlled. Further, for example, the processing circuit 21 controls the C-arm / top plate 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 plate 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 blades of the X-ray diaphragm 13, so that the X-rays irradiated to the subject P are emitted. Control the irradiation range of. Further, the processing circuit 21 controls the projection data generation processing by the image data generation circuit 24, the image processing by the image processing circuit 26, the analysis processing, and the like according to the instruction of the operator. Further, the processing circuit 21 controls the GUI for receiving the instruction of the operator, the image stored in the storage circuit 25, the processing result, and the like so as to be displayed on the display 23.

Then, as shown in FIG. 17, the processing circuit 21 executes the control function 211, the extraction function 212, and the calculation function 213. The control function 211 controls the entire X-ray diagnostic apparatus 100a. Further, the control function 211 executes the same processing as the control function 351 described above. The extraction function 212 executes the same processing as the extraction function 352 described above. The calculation function 213 executes the same processing as the calculation function 353 described above.

In the above-described embodiment, the blood vessel has been described as the main treatment target, but as mentioned in the case of inserting an atrial septal defect treatment device (Amplatzer, etc.) for the atrial septal defect, the target area. Is not limited to blood vessels. The treatment can be applied in the embodiment as long as it is a blood flow region through which blood flow flows and a part of the blood flow region is covered with a surgical device. Further, in the above-described embodiment, an example in which each processing function is realized by a single processing circuit (processing circuit 350 and processing circuit 21) has been described, but the embodiment is not limited to this. For example, the processing circuit 350 and the processing circuit 21 may be configured by combining a plurality of independent processors, and each processor may execute each program to realize each processing function. Further, each processing function of the processing circuit 350 and the processing circuit 21 may be appropriately distributed or integrated into a single or a plurality of processing circuits.

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

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

According to at least one embodiment described above, the effect of indwelling a medical device on blood flow can be grasped.

Although some embodiments of the present invention have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other embodiments, and various omissions, replacements, and changes can be made without departing from the gist of the invention. These embodiments and variations thereof are included in the scope of the invention described in the claims and the equivalent scope thereof, as are included in the scope and gist of the invention.

100 Medical image diagnostic device 100a X-ray diagnostic device 211,351 Control function 212,352 Extraction function 213,353 Calculation function 300 Medical image processing device

Claims (11)

An acquisition unit that acquires medical image data including the blood flow area through which blood flows, and
An extraction unit that extracts the shape of the medical device placed in the blood flow region,
With respect to the medical device indwelled in the blood flow region, a calculation unit for calculating an index value indicating the degree of the amount of blood permeating the medical device based on the shape when the medical device is indwelled. ,
An output control unit that controls to output the index value,
A medical image processing device. Each type of the medical device further has a storage unit for storing the shape of the medical device when it is placed and the index value in association with each other.
The medical device according to claim 1, wherein the calculation unit calculates the index value by reading out the associated index value stored in the storage unit based on the shape when the medical device is placed. Image processing device. The storage unit stores corresponding information associated with the index value for each shape indicated by the diameter and inclination of the cross section orthogonal to the core wire of the medical device.
The extraction unit extracts the diameter and inclination of the cross section orthogonal to the core wire for each position of the medical device placed in the blood flow region.
The medical device according to claim 2, wherein the calculation unit calculates the index value for each position of the medical device based on the corresponding information and the diameter and inclination of the cross section orthogonal to the core wire for each position of the medical device. Image processing device. The extraction unit extracts the shape of the medical device included in the medical image data collected after the medical device is indwelled according to the indwelling plan of the medical device.
The medical image processing apparatus according to claim 2 or 3, wherein the calculation unit calculates the index value for each position in the medical device based on the shape of the medical device. The extraction unit extracts the shape of the medical device included in the medical image data collected during the operation.
The medical image processing apparatus according to claim 3, wherein the calculation unit calculates the index value for each position in the medical device included in the medical image data collected during the operation based on the corresponding information. The output control unit displays simulation information regarding the shape of the medical device in the blood vessel so that the index value of the position of the medical device corresponding to the treatment target site of the blood vessel satisfies a preset condition. The medical image processing apparatus according to claim 4 or 5. The storage unit stores the index value for each subject calculated over time, and stores the index value.
The medical image processing apparatus according to any one of claims 2 to 6, wherein the output control unit displays display information in which the index values are arranged in chronological order for each subject. As the index value, the calculation unit calculates a coverage ratio indicating the ratio of the region covered by the medical device to the treatment target site of the blood vessel.
The medical image processing apparatus according to any one of claims 1 to 7, wherein the output control unit displays the calculated coverage. The calculation unit calculates the coverage on the neck surface of the cerebral aneurysm.
The medical image processing apparatus according to claim 8, wherein the output control unit displays a calculated coverage on a medical image showing the neck surface of the cerebral aneurysm. A collection unit that collects medical image data including the blood flow area where blood flows,
An extraction unit that extracts the shape of the medical device placed in the blood flow region,
With respect to the medical device indwelled in the blood flow region, a calculation unit for calculating an index value indicating the degree of the amount of blood permeating the medical device based on the shape when the medical device is indwelled. ,
An output control unit that controls to output the index value,
A medical diagnostic imaging device. The acquisition procedure for acquiring medical image data including the blood flow area through which blood flows, and
An extraction procedure for extracting the shape of a medical device placed in the blood flow region, and
With respect to the medical device indwelled in the blood flow region, a calculation procedure for calculating an index value indicating the degree of the amount of blood permeating the medical device based on the shape when the medical device is indwelled. ,
An output control procedure for controlling the output of the index value and
A medical image processing program that lets a computer run.

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