WO2013031744A1 - 血流性状診断のためのシステム、その方法及びコンピュータソフトウエアプログラム - Google Patents
血流性状診断のためのシステム、その方法及びコンピュータソフトウエアプログラム Download PDFInfo
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- WO2013031744A1 WO2013031744A1 PCT/JP2012/071627 JP2012071627W WO2013031744A1 WO 2013031744 A1 WO2013031744 A1 WO 2013031744A1 JP 2012071627 W JP2012071627 W JP 2012071627W WO 2013031744 A1 WO2013031744 A1 WO 2013031744A1
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Definitions
- the present invention relates to a system for blood flow property diagnosis, a method thereof, and a computer software program. More specifically, the present invention enables the onset and progress of future lesions in the target blood vessel site from the blood flow state of the target blood vessel site.
- the present invention relates to a system, a method, and a program that can determine the presence or absence of sex and can provide a prediction of a therapeutic effect.
- Circulatory system diseases include vascularization, hardening, and stenosis. These diseases involve lesions in the normal region due to the influence of blood flow, and many deaths are caused by subsequent development, but their treatment is extremely difficult because of the risk of life.
- engineering techniques such as fluid analysis and structural analysis in addition to basic medical approaches based on pathological sections.
- a cerebral aneurysm is a vascular disorder in which a part of the cerebral artery wall protrudes outward in a bag shape.
- a cerebral aneurysm is a blood vessel wall that changes to an aneurysm shape due to fragility of the arterial wall, etc., and is prone to failure because it lacks the media.
- Many cerebral aneurysms are in the subarachnoid space Because it is present in the largest cause of subarachnoid hemorrhage. Therefore, it is necessary to perform appropriate preventive treatment such as stent treatment for cerebral aneurysms that are likely to rupture.
- Japanese Patent Application Laid-Open No. 2010-207531 discloses an MRI apparatus that determines the risk of aneurysm rupture based on the viscous force of the fluid acting on the inner wall of the aneurysm, that is, the magnitude of fluid shear stress. Yes.
- the relationship between the size of the wall shear stress of the aneurysm and the growth of the aneurysm there are various theories that conflict with the discrimination results.
- WSS Wall shear stress
- the second theory is that when the wall shear stress falls below the threshold, platelets and leukocytes adhere to the endothelial cells, thereby reducing the endothelial function and lowering the mechanical strength of the aneurysm wall. There is. Since these two theories are conflicting theories, the magnitude of the wall shear stress does not mean a direct indicator of the growth and fracture of the aneurysm.
- the present invention has been made in view of such a situation, and an object of the present invention is to appropriately diagnose whether there is a possibility of causing a future lesion in the target blood vessel site based on the blood flow state of the target blood vessel site. And a method, system, and program for predicting treatment effect.
- a system for analyzing blood flow of a target blood vessel site by simulation in which a computer includes a boundary condition related to blood flow in the three-dimensional shape data of the target blood vessel site. And a fluid analysis unit that obtains a state quantity of blood flow at each position of the lumen of the target blood vessel site by calculation, and a computer corrects the three-dimensional shape data by simulating a surgical treatment method and A three-dimensional shape correction unit that outputs three-dimensional shape data, and a state quantity calculation by the fluid analysis unit is re-executed based on the corrected three-dimensional shape data, and the calculation result after correction of the shape data is There is provided a system including a comparison display unit that displays a calculation result in a comparable manner.
- the shape correction unit is configured to display at least a part of the three-dimensional shape data display on the display, wherein the computer graphically displays the three-dimensional shape data on the display.
- a correction part designating unit for accepting designation of one polygon a polygon moving unit for moving or distorting the polygon from the position of its center of gravity to the outside or inside of the blood vessel along the surface normal direction, and a computer
- the polygon moving unit preferably includes a smoothing unit that detects an acute-angle shape generated after moving or distorting one or more polygons and performs a smoothing process.
- the state quantity calculated by the fluid analysis unit is a flow velocity and a pressure of the fluid.
- an energy loss calculation unit that calculates an energy loss of blood flow in the target blood vessel site based on the state quantity calculated by the fluid analysis unit, and the comparison display unit includes the energy loss after correcting the shape data. It is preferable to display the calculation result so that it can be compared with the energy loss calculation result before correction.
- the computer reads the three-dimensional shape data of the lumen of the target blood vessel site, and the cross-sectional area of a plurality of blood vessel elements included in the target blood vessel site is obtained.
- a labeling unit that performs labeling based on the size of the cross-sectional area, and based on the labeling based on the size of the cross-sectional area, the degree of mesh division is changed for each vascular element, and the calculation of the state quantity is performed. .
- the labeling unit includes a storage unit in which a computer stores a name of a main blood vessel element and a name of another blood vessel element included in a specific target blood vessel part in association with the specific target blood vessel part, and a computer
- the shape of each vascular element included in a specific target vascular site is measured in a plurality of cross sections, the one having the largest median area is identified as the main blood vessel, and the other blood vessel is determined based on the discrimination of the main blood vessel
- the elements are specified, the names of these main vascular elements and other vascular elements are labeled, and output together with the three-dimensional shape data.
- the mesh detail is determined by the size of the median value of the area of the cross-sectional shape, and is determined in a plurality of stages from coarse to fine details.
- the system further includes a calculation condition value including a boundary condition for the computer to calculate a state quantity of blood flowing in the three-dimensional shape data.
- a calculation condition value including a boundary condition for the computer to calculate a state quantity of blood flowing in the three-dimensional shape data.
- a plurality of sets of calculation condition values wherein each of the plurality of sets of calculation condition values includes one or more different calculation condition values depending on a calculation speed requested by a user.
- a condition storage unit presenting a selection of calculation speed to the user, taking out a set of calculation condition values associated with the calculation speed in accordance with the selected calculation speed, and calculating conditions included in the set
- the blood flow state quantity is calculated based on the value, and the calculation result is output.
- At least one set of the plurality of sets of calculation setting values includes calculation condition values when the blood flow is assumed to be a steady flow corresponding to the case where the user places importance on calculation speed, and at least The other set preferably includes calculation condition values when the blood flow is assumed to be a pulsatile flow in response to a case where the user places importance on calculation accuracy rather than calculation speed.
- the at least one other set further includes a calculation condition value considering a case where the flow transitions from a laminar flow to a turbulent flow within the pulsating cycle of the pulsating flow.
- the system also includes a first processor that performs calculations when the user places importance on calculation speed, and a second processor that performs calculations when the user places more importance on calculation accuracy than calculation speed. It is preferable to further include a determination unit that determines which processor to use according to the selection. In this case, it is preferable that the second processor performs parallel analysis using a plurality of high-speed computing units, and the second processor is provided in another place where it can be connected via a communication network. The determination unit transmits a part or all of the conditions necessary for the calculation to the second processor via the communication network and receives the calculation result when it is determined that the second processor is used. It is preferable.
- the shape correction unit includes a surgical simulation unit that generates three-dimensional shape data of a target blood vessel site after surgery by simulation
- the surgical simulation unit includes: A treatment method in which a computer three-dimensionally displays the three-dimensional shape data generated by the three-dimensional shape extraction unit on a display and receives designation of a lesioned part on the display and selection of a surgical treatment method for the lesioned part
- a receiving unit a correction method storing unit that stores in advance a treatment method that can be selected by the computer and a three-dimensional shape data correction method corresponding to the treatment method, and a computer that stores the correction method based on the selection of the treatment method
- the correction method stored in the part is taken out, and the three-dimensional shape data of the lesion part according to the designation is corrected by the correction method.
- a modified three-dimensional shape output unit for outputting the three-dimensional shape data after corrected.
- the selectable treatment method includes coil embolization
- the three-dimensional shape data correction method corresponding to the coil embolization method is a method of correcting the three-dimensional shape data of the lumen of the target blood vessel site. It is desirable to have a program for disposing a porous structure in the part and to simulate a state in which a part of the lumen of the blood vessel is blocked with a coil. In this case, it is preferable to further have a program for changing the coil filling rate according to the aperture ratio of the porous structure.
- the selectable treatment method includes a clipping method, and the three-dimensional shape data correction method according to this treatment method constitutes a surface of a part of a blood vessel lumen (part constituting an aneurysm or the like) 1 Or a program for deleting a plurality of polygons and means for reproducing the deleted surface with another one or a plurality of polygons, and simulating a case where a part of the blood vessel lumen is completely closed Is preferred.
- the selectable treatment method includes stent placement, and the three-dimensional shape data correction method according to the treatment method moves or distorts the polygons on the unevenness of a part of the surface of the blood vessel lumen. It is desirable that a program for correcting the blood flow in the blood vessel is controlled by the stent, and the flow of blood in the blood vessel is controlled by the stent.
- the selectable treatment method includes a flow-diverting stent placement
- the three-dimensional shape data correction method according to this treatment method is the three-dimensional shape data converted into the lumen of the target blood vessel site. It is desirable to have a program that partially defines a lattice-like object and simulate a case where blood flow is restricted by flow-diverting stent. In this case, it is preferable that the system further includes a program for changing the lattice density of the flow-diverting stent by the aperture ratio of the lattice-like object.
- the system includes a wall shear stress at each position of the blood vessel wall surface of the target blood vessel site based on a blood flow state quantity obtained by the computer using the fluid analysis unit.
- the vector is obtained, the relative relationship between the direction of the wall shear stress vector at a specific wall position and the direction of the wall shear stress vector at the surrounding wall position is obtained, and the property of the blood flow at the wall position is determined from the form.
- It further has a blood flow property determination unit that outputs the determination result, and the comparison display unit can compare the calculation result of the blood property determination unit after correcting the three-dimensional shape data of the target blood vessel portion with the calculation result before correction Is displayed.
- the blood flow property determination unit determines that the relative relationship between the direction of the wall shear stress vector at the specific wall surface position and the direction of the wall shear stress vector at the surrounding wall surface position is “parallel”, “confluence” ”,“ Rotation ”or“ divergence ”. If“ parallel ”, blood flow is benign flow (non-malignant flow), otherwise malignant flow (non-benign flow) It is desirable to discriminate.
- the blood flow property determination unit It is determined that the thinning of the blood vessel wall occurs, and the position is output, and the comparison display unit makes a graphical display output of the position where the thinning is likely to occur with the three-dimensional shape model. desirable.
- the blood flow property determination unit calculates the scalar quantity of the vector field ⁇ from the relative angular relationship between the wall surface shear stress vector ⁇ at the specific wall surface position and a plurality of wall surface shear stress vectors at the surrounding wall surface positions.
- the blood flow property determination unit preferably treats the plurality of wall shear stress vectors as unit vectors for calculation, and the threshold value compared with the rotation rot ⁇ and the divergence div ⁇ is preferably 0.
- the blood flow property determination unit uses the value of the rotation rot ⁇ and the divergence div ⁇ of the randomness, the index value of the pressure acting in the normal direction on the wall surface position as the value of the rotation rot ⁇ and divergence div ⁇ It is more preferable that the pressure index value given when obtaining the values of the rotation rot ⁇ and the divergence div ⁇ of the randomness is the pressure acting on the wall surface. It is desirable that the value is divided by the average pressure value acting on the wall surface of the part. Further, it is preferable that the comparison display unit displays and outputs the value of the rotation rot ⁇ or / and the divergence div ⁇ of the randomness on the display together with the three-dimensional shape model.
- an invention relating to a computer software program for executing the system of the present invention is provided.
- an invention related to a method for executing the system of the present invention.
- FIG. 1 is a schematic configuration diagram showing an embodiment of the present invention.
- FIG. 2 is a graphical user interface of the blood vessel shape extraction unit.
- FIG. 3 is a schematic configuration diagram of a blood vessel shape extraction unit.
- FIG. 4 is a view for explaining extraction of a blood vessel shape from an image.
- FIG. 5 is a diagram for explaining thinning of a blood vessel shape.
- FIG. 6 is a diagram for explaining labeling of blood vessel names including main blood vessels.
- FIG. 7 is a diagram for explaining end face processing of an extracted blood vessel shape.
- FIG. 8 is a schematic diagram showing the entire cerebral blood vessel shape.
- FIG. 9 is a graphical user interface of the surgery simulation unit.
- FIG. 10 is a schematic configuration diagram of a surgery simulation unit.
- FIG. 10 is a schematic configuration diagram of a surgery simulation unit.
- FIG. 11 is a diagram showing a simulation in the first surgical simulation mode.
- FIG. 12 is a diagram showing a simulation in the second surgical simulation mode.
- FIG. 13 is a diagram showing a simulation in a third surgical simulation mode.
- FIG. 14 is a diagram showing an example of a shape correction result in the first surgical simulation mode.
- FIG. 15 is a schematic configuration diagram of a fluid analysis unit.
- FIG. 16 is a flowchart showing processing by the fluid analysis unit.
- FIG. 17 is a graphical user interface of the fluid analysis unit.
- FIG. 18 is a diagram for explaining the mesh detail level.
- FIG. 19 is a schematic diagram illustrating fluid shear stress.
- FIG. 20 is a schematic diagram illustrating fluid shear stress.
- FIG. 21 is a diagram showing a global coordinate system related to calculation of wall shear stress.
- FIG. 22 is a diagram showing a local coordinate system related to calculation of wall shear stress.
- FIG. 23 is a diagram graphically showing the shear stress vector superimposed on the three-dimensional shape of the blood vessel.
- FIG. 24 is a diagram graphically showing the shear stress vector and the pressure superimposed on the three-dimensional shape of the blood vessel.
- FIG. 25 is a diagram for explaining calculation of randomness.
- FIG. 26 is an explanatory diagram regarding the interpretation of the degree of randomness.
- FIG. 27 is a diagram showing a malignant / benign discrimination method based on a randomness map. Explanatory drawing regarding the thinning determination by randomness (dispersion). Graphical user interface of blood flow property discrimination unit.
- FIGS. 30A to 30D are diagrams showing examples of result display showing the effectiveness of the randomness in the thinning judgment of the aneurysm wall.
- the schematic block diagram which shows the surgery technique evaluation system which is other Embodiment of this invention.
- the first aspect of the present invention is a diagnostic apparatus for diagnosing the properties of a groin.
- this invention by correlating the shape of the shear stress vector group acting on the blood vessel wall surface in the cerebral aneurysm by the blood flow with the lumen shape, pathological information, and blood vessel thickness information of the aneurysm, They were classified into “malignant (not benign) blood flow patterns” that can be a factor that contributes to the onset and progression, and “benign blood flow patterns” that are less likely to be the cause.
- the form of the shear stress vector group generated as a result of the simulation corresponds to the malignant blood flow pattern or the benign blood flow pattern. If it is determined as a malignant blood flow pattern, it may be a factor that will lead to the development or progression of vascular tissue lesions in the future, so it will be necessary to consider surgery, and if it is determined as a benign blood flow pattern It is determined that it is difficult to be such a factor, and the risk of unnecessary surgery can be avoided.
- a second aspect of the present invention is to provide an apparatus for determining a therapeutic effect after surgically treating a cerebral aneurysm determined to have a malignant blood flow pattern, for example.
- the blood flow property determination method based on the malignant / benign blood flow pattern can be used to predict not only a cerebral aneurysm before treatment but also a therapeutic effect after treating the cerebral aneurysm.
- Surgical treatment methods for cerebral aneurysms include, for example, 1) clipping, 2) coil embolization, and 3) flow-diverting stent.
- the clip technique is to block the flow in the aneurysm by closing the aneurysm neck surface with the clip, in other words, to construct a new blood vessel shape without a cerebral aneurysm.
- a plurality of coils are placed in the aneurysm to make the inside of the aneurysm a thrombus and close the aneurysm.
- a mesh made of metal or the like is placed on the neck surface of the aneurysm, and the flow velocity in the aneurysm is reduced to clot the inside of the aneurysm and close the aneurysm.
- These therapies have the common feature of blocking the flow in the aneurysm, and artificially modify the lumen shape of the blood vessel to reconstruct a new aneurysm neck surface, that is, a new blood vessel shape It is.
- a complication associated with the treatment is that the reconstructed blood vessel shape is modified over time. For example, in a case where coil embolization has been performed, the aneurysm neck surface is compressed in the direction of the aneurysm lumen due to fluid force, so that the aneurysm lumen and the parent blood vessel are restarted, and there are many cases where treatment is performed again.
- the blood vessel shape that has been three-dimensionally modeled by a computer is corrected, and a new aneurysm neck surface is artificially created on the computer, so that the blood vessel shape is the same as in the case of actual surgery. Is built on a computer before surgery. Then, the form of the wall shear stress vector group acting on the blood vessel wall surface of the new blood vessel shape is visualized by simulation, and the method for discriminating the malignant / benign blood flow pattern is similarly applied to the form, The therapeutic effect can be evaluated.
- FIG. 1 is a schematic block diagram showing a blood flow property determination / treatment effect prediction system according to the present embodiment.
- This blood flow property determination / treatment effect prediction system corresponds to the first and second aspects and has the following two functions.
- the blood flow characteristics of the subject vascular site may be It is automatically determined whether the blood flow is a benign blood flow that is less likely to progress to rupture or a malignant blood flow that is likely to progress to the rupture (non-benign blood flow).
- this blood flow property diagnosis / treatment effect prediction system is provided in a site of a user such as a doctor (in a hospital) as shown in FIG.
- An imaging apparatus 1 that captures an image of a target blood vessel site, a user terminal 2 for a user such as a doctor to operate the system, and the imaging apparatus 1 and the user terminal 2 are connected to a communication network (in-hospital LAN, out-of-hospital WAN, or dedicated A blood flow property diagnosis / treatment effect prediction server 3 connected via a line).
- a communication network in-hospital LAN, out-of-hospital WAN, or dedicated
- a blood flow property diagnosis / treatment effect prediction server 3 connected via a line.
- a tomographic image of a target blood vessel part such as a CT apparatus (computer tomography apparatus), an MRI apparatus (magnetic resonance imaging diagnosis apparatus), a DSA apparatus (digital subtraction angiography) can be acquired.
- a CT apparatus computer tomography apparatus
- an MRI apparatus magnetic resonance imaging diagnosis apparatus
- a DSA apparatus digital subtraction angiography
- any apparatus that can acquire image data in the target blood vessel site such as an image captured by ultrasonic Doppler or near infrared imaging may be used.
- the user terminal 2 may be a workstation composed of a normal personal computer capable of executing display software such as a browser capable of displaying a graphical interface for performing communication with the blood flow property diagnosis / treatment effect prediction server 3. .
- the blood flow property diagnosis / treatment effect prediction server 3 includes a program storage unit 8 connected to a bus 7 to which an input / output interface 4 for communicating with the communication network, a memory 5 and a CPU 6 are connected.
- the program storage unit 8 includes a blood vessel shape extraction unit (i-Vessel) 10 that generates the three-dimensional shape data of the lumen of the target blood vessel site from the image data acquired by the imaging device 1, and an operation by processing the three-dimensional shape data.
- An operation simulation unit (i-Surgery) 11 that performs simulation
- i-CFD fluid analysis unit
- a blood flow property discriminating unit (i-Flow) 13 for discriminating whether the blood flow of a blood vessel site is a benign flow or a malignant flow, a user graphical interface generated by this system, and an image, an analysis result, and a discrimination result displayed there
- a display unit 14 for generating a display screen.
- the bus 7 is connected to a simulation setting DB 15 for storing various setting information necessary for the simulation and a simulation result DB 16 for storing simulation and analysis results by this system.
- the component of the server 3 (the blood vessel shape extraction unit 10, the surgery simulation unit 11, the fluid analysis unit 12, and the blood flow property determination unit 13) is actually computer software stored in a storage area of a hard disk. It is configured by software, and is configured to function as each component of the present invention by being called by the CPU 6 and expanded on the memory 5 and executed.
- the server 3 may be composed of a single computer, or may be composed of a plurality of computers in which each component is distributed.
- the blood flow property diagnosis / treatment effect prediction server 3 is connected to the user terminal 1 provided in the hospital via a communication network, but may be provided in the hospital. It may be provided in the high-speed arithmetic processing center 9 etc. outside the hospital. In the latter case, data and instructions are received from a large number of user terminals 2 and imaging devices 1 provided in a plurality of hospitals, and high-precision fluid analysis is performed in a short time using a high-speed arithmetic processor, and the analysis results are sent to each hospital. It is preferable that a user such as a doctor can display an analysis result on the spot for a patient or the like by feeding back to the user terminal.
- FIG. 2 shows a graphical user interface (GUI) 17 generated by the display unit 14 of the server 3 and displayed on the user terminal device 2.
- GUI graphical user interface
- FIG. 2 shows an example in which the blood vessel shape extraction unit “i-Vessel” 10 that will be described next is selected from the menu at the top of this screen.
- i-Surgery 11, i-CFD 12, and i-Flow 13 it is possible to switch to an interface (described later) corresponding to each function.
- the blood flow property diagnosis / treatment effect prediction system of this embodiment is used as a part of medical practice in a busy clinical environment. Therefore, time constraints on medical personnel and inconsistencies in analysis conditions between users and facilities are problems to be solved. Moreover, it is necessary to fully consider that the clinician and radiographer who are users are non-engineers who are not familiar with fluid dynamics. According to the system of this embodiment, since the apparatus group is integrated and automatic control processing can be performed collectively by a single interface 17, the above-described concerns are solved.
- FIG. 3 is a block diagram showing processing steps of the blood vessel shape extraction apparatus, and FIGS. 4 to 9 are explanatory diagrams thereof.
- step S1-1 the imaged image data of the target blood vessel part in DICOM format etc. imaged by the imaging device is input.
- step S1-2 the orientation of the image (up / down / left / right directions) is automatically recognized or manually designated.
- FIG. 2 shows the user interface of the blood vessel shape extraction unit (i-Vessel) as described above. The interface for confirming the orientation of the image corresponds to the display unit 41 at the upper left of the display units 41 to 44 displayed as being divided into four in FIG.
- the designation regarding the display direction of the blood vessel is, for example, “front (A)”, “rear (P)”, “ By pressing the left (L) ”and“ right (R) ”buttons 18 and rotating the screen, the image directions are changed to“ front (A) ”,“ rear (P) ”,“ left (L) ”,“ [Right (R)].
- the anatomical part is designated by, for example, selecting the radio button 24 (step S1-3).
- the anatomical region designated here is used when automatically labeling a blood vessel in a later step. For example, if the cerebral aneurysm is in the right middle cerebral artery (MCA), “Anterior Circulation” is selected. Similarly, “left front circulation”, “front circulation”, and “rear circulation” can be selected.
- This anatomical site is stored in the simulation setting DB 15 as indicated by reference numeral 19 in FIG.
- the threshold method, gradient method, region expansion method, etc. (the “selection (threshold method (or gradient method) shown in the screen of FIG. 2) Specify the region of interest by specifying the region of interest in) ”,“ Connectivity (the user specifies the target vessel in the region of interest, and only the continuous voxels are selected from there to select the target vessel Extract ”),“ Extension (area extension method that includes both threshold method (or gradient method) and voxel continuity, adding blood vessels that were deleted in spite of necessity in the blood vessel extraction process) ” , “Removal (the user manually deletes unnecessary blood vessels)”) is combined to construct a three-dimensional blood vessel shape (three-dimensional shape data).
- a target blood vessel region is extracted in step S1-4. This extraction is performed using, for example, a threshold method or a gradient method.
- FIG. 4 shows an extraction example when the threshold method is used.
- the threshold value setting unit 45 in the screen of FIG. 2 selects a histogram threshold value by the slider method, thereby changing the threshold value while viewing the image on the display unit 42 at the upper right, and extracting a characteristic characteristic of the blood vessel wall.
- the gradient method for example, the gradient of the luminance value is extracted from the luminance value distribution by a calculation process, and the characteristic peculiar to the blood vessel wall is extracted therefrom and used. Thereafter, by pressing the “Fix” button 46 in the screen of FIG.
- FIG. 4 is a schematic diagram showing the extraction of the blood vessel shape by this process.
- These threshold values are stored in the simulation setting DB 15 as setting conditions (indicated by reference numeral 29).
- step S1-7 when the user presses the “Lesion” button 47 on the screen of FIG. 2, the user manually designates a lesion using a mouse or the like on the display (step S1-7). Thereafter, the blood vessel is thinned in step S1-8, and the center line of the blood vessel is derived.
- This thinning process is automatically executed when the user presses the “Label” button 48 on the screen of FIG.
- FIG. 5 shows this thinning. After obtaining the center line, the center line is divided into elements for each blood vessel in step S1-9. This element division is performed by dividing the center line of each blood vessel at the blood vessel branch points A, B, C, D... As shown in FIG. FIG.
- FIG. 6 shows the division part in an enlarged manner. Portions (V1, V2,%) Between the branch points A, B, C,. Thereafter, in step S1-10, a plurality of cross sections (shown in FIG. 6) orthogonal to the center line in each element are determined, the equivalent diameter of the corresponding cross section is calculated, and the shape 25 of each element is measured.
- step S1-11 the name of the blood vessel is automatically labeled on each element.
- the median value of a plurality of equivalent diameters calculated in the plurality of cross sections 25 (in the case of an average aneurysm in the blood vessel and the diameter suddenly increasing)
- the blood vessel with the largest (to ensure accuracy) is determined to be the main blood vessel and is labeled.
- this labeling is automatically performed according to the designation of the anatomical site. That is, when the left anterior circulation is selected, the main blood vessel (the vascular element having the largest median equivalent diameter) is labeled “left internal carotid artery”, and when the posterior circulation is selected, the “basal artery” ".
- the simulation setting DB 9 stores anatomical site information 19, a main blood vessel name 20, and a blood vessel name 21 branched from the main blood vessel in association with each other.
- the labeling unit 35 of the shape extracting unit 10 can automatically perform labeling by referring to these pieces of information as a “blood vessel labeling template”.
- step S1-11 following the labeling of the main blood vessels, the main blood vessels V2, V3, etc. are tracked over the deep part, and the blood vessel names appearing for each branch are based on the information stored in the DB9. Automatically discriminate and label them sequentially.
- the labeling is performed up to 5 to 10 lower vascular elements counted from the main blood vessels.
- the branch blood vessel labeling is stored in the database 9 for other blood vessels that branch from the main blood vessel. In other words, it is automatically made based on the relationship between the name 20 of the main blood vessel as a template and the name 21 of the branch blood vessel (for each anatomical site 19).
- steps S1-12 and 13 based on the image direction (vertical and horizontal directions) designated in advance in step S1-2 and the anatomical site designated as the target, the entrance / exit surfaces of the blood vessels after labeling is completed. Are made orthogonal to each center line to construct a blood vessel end face.
- FIG. 7 is a diagram showing this end face construction.
- step S1-14 the three-dimensional shape constructed in this way is automatically output as polygon data.
- the shape data 22 of each blood vessel labeled (labeling information 23) is automatically calculated and written in the simulation result DB 16 (FIG. 3).
- the user can confirm on the interface 17 displayed on the display whether or not appropriate processing has been performed.
- FIG. 8 shows an outline of cerebrovascular names.
- FIG. 8 covers forward and backward circulation.
- the anterior traffic artery is known as a frequent site of cerebral aneurysms, but since it spans the left and right anterior circulations, the entire anterior circulation needs to be covered for analysis.
- (Surgery simulation device) 9 is a schematic diagram showing the user graphical interface 17 by the surgery simulation unit 11,
- FIG. 10 is a flowchart showing the operation of the surgery simulation unit 11, and FIGS. 11, 12, and 13 are explanatory diagrams thereof.
- FIG. 14 is a schematic configuration diagram of the shape correcting unit 35 that corrects the three-dimensional blood vessel data for the surgical simulation.
- the user can select three surgical simulation modes, that is, “Clipping / Coiling” 50 as the first surgical mode, “Stenting” 51 as the second surgical mode, One of the “Flow-diverting Stent” 52 as the operation mode is selected.
- this surgery simulation part 11 produces
- the first surgical simulation mode is the removal of the lesion and the reconstruction of the surface (Clipping / Coiling)
- the second surgical simulation mode is the reconstruction of the surface by correcting the unevenness of the lesion.
- the third surgical simulation mode is the placement of a grid-like object on an arbitrary cross section (Flow-diverting Stent).
- the blood vessel shape correction method (indicated by 37 in FIG. 15) corresponding to the first surgical simulation mode is a program group 50 (simulation for completely closing the aneurysm lumen as in clipping or coil embolization).
- ⁇ Positioning>, ⁇ Removal>, ⁇ Recon.>, ⁇ Shaping>, ⁇ Label> which attempts to simulate the fluid force acting on the ankle neck surface formed after treatment before surgery.
- the blood vessel shape correction method corresponding to the second simulation mode is a program group 51 ( ⁇ Positioning>, ⁇ Fitting>, ⁇ Fitting>, ⁇ Fitting>, ⁇ Shaping>, ⁇ Label>), which tries to simulate the fluid force acting on the lesion formed after treatment before surgery.
- the blood vessel shape correction method corresponding to the third operation simulation mode is a program group 52 ( ⁇ Positioning>, ⁇ Porosity>, ⁇ Shaping>, ⁇ Label>) for simulating treatment of a cerebral aneurysm by Flow-diverting stent. It is intended to simulate the effect of reducing the flow in the aneurysm.
- This simulation is actually performed by correcting the three-dimensional shape data of the blood vessel, and the surgery simulation unit has a treatment method reception unit 73 and a shape correction unit 35 as shown in FIG. It is a figure.
- the simulation setting unit DB15 selectable surgical modes (first to third surgical simulation modes in this example) and specific blood vessel shape correction methods defined in relation thereto are shown in the simulation setting unit DB15 as indicated by reference numerals 36 and 37 in FIG. Stored in
- the user selects the ⁇ Surgery> button 11 on the graphic interface 17, and displays the blood vessel shape created by the blood vessel shape extraction device through the browser screen of the user terminal 2 (step S2-0: FIG. 9).
- the display unit 54 in the upper left of the screen shown).
- the treatment method accepting unit 73 reads the blood vessel shape correcting method 37 (program group 50 ( ⁇ Positioning>, ⁇ Removal>, ⁇ Recon.>, ⁇ Shaping>, ⁇ Label>)) are loaded, and the user first selects a lesion by ⁇ Positioning> (step S2-1).
- the corrected region designating unit 38 shown in FIG. 15 displays the region designated above on the user interface 17 (the display unit on the upper right in FIG. 9). Since the three-dimensional shape data is polygon data in which the blood vessel surface / end is composed of a collection of minute triangular elements, the designated area can be enlarged / reduced according to the purpose of the surgical simulation.
- the polygon moving unit 39 shown in FIG. 15 cuts out the selected triangular element (step S2-2).
- the polygon moving unit 39 reconstructs the surface with polygons in the cut portion of ⁇ Recon>.
- the correction site designation unit 38 and the polygon moving unit 39 can be operated, and the user can correct the unevenness of the reconstructed surface by operating the mouse (step S2- 3)
- labeling is defined as a new surface by ⁇ Label> (labeling unit 35) (step S2-4).
- the reconstruction of the surface is performed by calculating the center of gravity of the excision region and connecting it to the apex of the triangle on the end surface of the excision part.
- the center of gravity is the vertex common to the triangular element before the movement by the user using the mouse wheel button in the direction of the outer circumference (or inner circumference) of the cut surface normal starting from the position of the center of gravity. This is done by moving and artificially distorting the triangle shape.
- An acute angle shape that can appear after the movement is dealt with by simultaneously applying a smoothing process (the above-mentioned configuration requirements 38 to 39).
- the user works with the display units 55 and 56 ⁇ Post-surgery >> in the lower left and lower right, the postoperative image is displayed, and the user performs a surgical simulation with the program group. Go.
- the shape is determined by ⁇ End>, the polygon data modified in the same manner as in the blood vessel shape extraction apparatus is automatically saved, and the simulation result DB 16 is updated (step S2-13: labeling information 23 and Update of the three-dimensional shape data 22).
- FIG. 11 is a schematic diagram showing an example of blood vessel shape correction in the first surgical simulation mode
- FIGS. 14A and 14B are diagrams showing three-dimensional shapes before and after simulation (before and after clipping treatment).
- the lesioned part is selected and enlarged / reduced in the same manner as described above by ⁇ Positioning> (step S2-5, display unit 55).
- the center of gravity of the lesion is calculated by ⁇ Fitting>
- the polygon is moved along the normal direction of the blood vessel wall surface from that point, and the lesion shape is interpolated by polynomial approximation by curve fitting (step S2-6).
- the user corrects the unevenness of the lesion by operating the mouse with ⁇ Shaping> (step S2-7), and finally labels the reconstructed surface by the same method as in the first surgical simulation mode (step S2). -8).
- FIG. 12 is a schematic diagram showing an example of shape correction in the second surgical simulation mode.
- the user forms a new surface inside the three-dimensional blood vessel shape by ⁇ Positioning> (step S2-9).
- a lattice-like object is defined by ⁇ Porosity> for the designated surface (step S2-10), the unevenness is corrected by the same method (step S2-11), and is labeled (step S2). -12).
- the lattice-like object used as the blood vessel shape correcting method 37 (FIG. 15) in this case is to simulate a flow-diverting stent.
- the lattice-like object is defined as an isotropic porous medium by the user setting the aperture ratio from a pull-down menu.
- FIG. 13 is a schematic diagram showing an example of shape correction in the third surgical simulation mode.
- reference numeral 25 denotes a lattice-like object.
- Whether or not this blood flow can be simulated is important in determining the coil filling rate (the ratio of the coil volume to the volume of the aneurysm).
- the coil filling rate the ratio of the coil volume to the volume of the aneurysm.
- a porous medium is used as a two-dimensional structure, but the state immediately after coil embolization can be simulated by using the technique as a three-dimensional structure. That is, it is possible to provide a function of simulating the coil filling rate with the opening ratio by placing a porous medium in the lumen of the aneurysm by the ⁇ Porosity>.
- the target blood vessel part is obtained by a known calculation based on the finite element method based on the three-dimensional shape of the target blood vessel part generated by the blood vessel shape extraction unit 10 (and the surgery simulation unit 11).
- the flow velocity and pressure (state quantity 33) of the blood flow in each unit region are obtained.
- FIG. 16 is a flowchart showing the processing by the fluid analysis unit 12, and FIG. 17 is a display example when the user selects “CFD” 12 from the menu of the graphical interface 17.
- step S 3-1 the fluid analysis unit 12 first selects the blood vessel to be calculated this time from the three-dimensional shape of the target blood vessel site generated by the blood vessel shape extraction unit 10 (and the surgery simulation unit 11). Select and read shape data.
- the displayed data is displayed on the display units 58, 59 and 60 at the upper left of the interface 17 of FIG.
- Pre-Sergery shape data is displayed on the display unit 58
- Post-Sergery # 1 shape data is displayed on the display unit 59
- Post-Sergery # 2 shape data is displayed on the display unit 60, respectively.
- step S3-2 the user selects “module”.
- the graphic interface 17 includes three items of “On-site” 26, “Quick” 27, and “Precision” 28. Displays two buttons for user selection.
- a user can select one of the three modules and perform a calculation with appropriate calculation conditions / accuracy using a preset set of calculation condition values 40 (FIGS. 1 and 16). It is configured as follows. In consideration of time constraints in the clinical field and non-specialties of the user for fluid analysis, this is consistent with the needs of the field and handles the conditions of the analysis method in a unified manner for reproducibility and standardization. It is to achieve. In the calculation conditions corresponding to On-site (immediate), steady analysis is adopted as a calculation condition. The blood flow is an unsteady flow called the pulsatile flow caused by the heart.
- the calculation condition value set 40 is set to handle pulsatile flow in Quick (rapid) and Precision (high accuracy).
- Precision high accuracy is a condition setting that can be used even when the flow transitions from laminar flow to turbulent flow within the pulsation cycle.
- the mesh detail level, blood property values, wall boundary conditions, inlet boundary conditions, outlet boundary conditions, and discretization conditions used at this time are determined in advance and stored in the setting DB 15 as a set 40 of calculation condition values. .
- Precision high precision
- the first processor 41 provided for the fluid analysis unit 12 performs the on-site processing with a small load, and a Precision (high accuracy) with a large load is provided at a remote location. Processing is performed by a second processor 42 provided in the high-speed arithmetic processing center 9.
- a second processor 42 provided in the high-speed arithmetic processing center 9.
- data is automatically transferred to the out-of-hospital processing center via the communication network, and after performing calculations by parallel analysis using multiple high-speed computing units, analysis is performed via the network. It consists of a system that feeds back results.
- step S3-3 and subsequent steps when the user presses the Run button 62 on the interface 17 shown in FIG. 17, the system takes out the calculation condition value set 40 and automatically executes the calculation according to the selection of the module.
- the target blood vessel region is divided into a plurality of elements (hereinafter referred to as “mesh”) on the finite element method based on the three-dimensional shape data.
- a mesh is generated with a mesh division detail according to the size of each blood vessel.
- the mesh detail used for the mesh division is stored in association with the name of the blood vessel, or the mesh detail can be dynamically determined according to the size of the cross section of the blood vessel.
- the calculation condition value 40 is set in FIG. Therefore, this apparatus takes out the mesh detail level from the setting DB 15 according to the labeling and uses it. That is, the mesh detail level of each blood vessel is determined according to the selection of the module and the type of blood vessel.
- 18A and 18B are diagrams showing an example in which the mesh detail level is changed for each blood vessel.
- the detail of the 1 mm diameter ophthalmic artery is set to be finer than the detail of the 5 mm diameter internal artery.
- the mesh division detail D mesh in this embodiment is defined as follows.
- D mesh D base ⁇ K scale ⁇ K module
- D mesh mesh division detail (in this example, the mesh's representative diameter D mesh to be calculated is used as detail)
- D base base mesh size (constant independent of scale factor)
- K scale blood vessel A scale factor that varies depending on the size of the module
- K module a scale factor that varies depending on the selection of the module.
- the scale factor as defined above is not taken into consideration, and the size of the mesh is determined by the base mesh alone. For this reason, the conventional method sometimes cannot cope with fluctuations in each blood vessel diameter.
- the problems due to the conventional method can be solved by introducing the scale factor as described above.
- the fluid analysis unit 12 calculates the equivalent diameter D of the blood vessel by cylindrical approximation of the volume of the target blood vessel and the centerline length and shape of the blood vessel, and quantifies and uses the size of the blood vessel. It is configured as follows.
- the size of the mesh may change discontinuously at the branch of the blood vessel.
- the discontinuous change of the mesh becomes a factor that deteriorates the convergence of the calculation by increasing the shape distortion of the mesh there.
- an upper limit value is given to the mesh shape distortion, and the smoothing process is repeatedly performed so that the maximum shape distortion falls within the threshold value. It is configured as follows.
- the size of the mesh cannot be dynamically changed according to the size of the blood vessel in this way, and the large blood vessel and the small blood vessel have to be divided with the same degree of detail.
- the mesh shape is sufficient for analyzing a large blood vessel, the analysis accuracy deteriorates due to insufficient mesh in the small blood vessel, and if the analysis accuracy of the small blood vessel is ensured, an excessive mesh is generated in the large blood vessel.
- the present invention can solve this problem.
- each pre-stored calculation condition 40 such as blood physical property value, boundary condition, analysis condition, etc. is sequentially taken out from the setting DB 15, and based on these conditions in step S3-8.
- the fluid analysis unit 12 solves a Navier-Stokes equation ((Navier-Stokes equations) fluid second-order nonlinear partial differential equation describing fluid motion) by a finite element method, and calculates the blood flow in each mesh. Determine flow rate and pressure.
- the solution of the finite element method (flow velocity U and pressure P) is obtained for each of the three directions of the global coordinate system, X-global, Y-global, and Z-global.
- the blood physical property value is blood viscosity or density.
- the boundary conditions include an inlet boundary condition that is a flow condition on the inlet side of the analysis target part and an outlet boundary condition that is a flow condition on the outlet side. These flow conditions are statistically averaged. The flow velocity and pressure of the target vascular site are applied.
- the default values are automatically selected and used for these setting conditions based on the selected module.
- the pre-calculation is performed according to the personal data of the subject. It is preferable that manual input to the fluid analysis unit 12 is also possible.
- step S3-10 After the calculation is automatically started, the calculation residual is displayed in step S3-10, and the calculation is repeated until the convergence criterion is satisfied. If the calculation residual does not satisfy the convergence criterion until the maximum number of iterations is reached, it is determined that the convergence is impossible (step S3-11). If it is determined that the convergence is impossible, the mesh distortion is optimized (step S3-12), and the calculation is executed again. When the residual reaches the convergence criterion, the end of calculation is displayed (step S3-13). The calculation result (state quantity 33 (U, P)) is automatically saved in the result DB 16 as described above.
- the blood flow property determination unit 13 is installed with a program that causes a computer to function as the following means. That is, as shown in FIG. 1, the blood flow property determination unit 13 calculates the fluid shear stress acting on the blood vessel wall surface by the blood flow and its vector (hereinafter simply referred to as “flow”) from the flow velocity and pressure of each mesh obtained by the fluid analysis device.
- “Wall surface shear stress vector”) for each mesh for each mesh, and a numerical index (randomness) for determining blood flow properties from the wall shear stress vector calculation unit 30 and the wall surface shear stress vector.
- a randomness calculation unit 31 and a determination unit 32 that determines the property of blood flow in each mesh in accordance with the magnitude of the randomness.
- FIGS. 19 and 20 are schematic diagrams showing a method of obtaining the shear stress vector ⁇ (x, y, z) based on the flow velocity U and the pressure P obtained for each mesh in the wall surface shear stress vector calculation unit 30. is there.
- the wall shear stress is a viscous force of a fluid acting in a direction parallel to the minute elements forming the blood vessel lumen
- the wall shear stress vector is a vector view of the numerical value.
- the wall shear stress vector and the pressure are orthogonal to each other, and the pressure is a fluid force acting in the surface normal direction with respect to the center of gravity of the microelement.
- the shear stress acting on the position of the blood vessel wall surface is tangent to the wall surface. It is necessary to convert the pressure and velocity into a local coordinate system based on the blood vessel wall surface in order to obtain the size.
- the global coordinate system is a single coordinate system for universally indicating the positions of the nodes of the mesh constituting the blood vessel surface and the inside thereof in this system.
- a calculation target is composed of a set of minute elements (triangle, tetrahedron, hexahedron, etc.). Each element has a vertex called a node, and the position information of each element is (X1 g , Y1 g , Z1 g ), (X2 g , Y2 g , Z2 g ), (X3 g ) using the global coordinate system. , Y3 g , Z3 g ).
- the local coordinate system is a local coordinate system defined for each minute triangle element (polygon) constituting the blood vessel surface.
- the center of gravity of the minute triangle element is defined as the origin.
- the surface normal vector as one axis (Z axis).
- the velocity and pressure at each node are acquired in the global coordinate system from the output of the fluid analysis unit 12 (i-CFD).
- the triangular element for which the wall shear stress vector is to be obtained is designated.
- a local coordinate system is set for the triangular element.
- a position G where a wall shear stress vector is desired to be calculated is determined (usually, the distance from the wall is made constant for each triangular element, for example, a point within 0.1 mm from the wall).
- the flow velocity at the position G is 0 because it is a wall surface as shown in FIG.
- the speed at each candidate point can be obtained by installing a plurality of candidate points on the Zl axis and interpolating the speed vector from the surrounding speed vector group.
- interpolation is performed by setting a weight function for the distance. Since the ambient velocity vector is described in the global coordinate system, the velocity component in the plane parallel direction at each candidate point is calculated by coordinate-transforming the interpolated velocity vector into the local coordinate system.
- the rate of change in the normal direction it may be calculated as a primary approximation using one candidate point near the wall, or a polynomial approximation is performed using a plurality of candidate points near the wall, Thereafter, a higher-order differentiation process of mathematical differentiation may be performed.
- ⁇ (Xl) ⁇ ⁇ dUt (Xl) / dZ
- ⁇ (Yl) ⁇ ⁇ dUt (Yl) / dZ
- a vector value ⁇ (Xl, Yl) obtained by combining the local coordinate axes becomes a wall shear stress vector.
- the wall shear stress vector is a vector having an x-direction component and a y-direction component with respect to the surface within the surface in contact with the blood vessel wall.
- FIG. 23 is a diagram showing the shear stress vector along the blood vessel wall obtained in this manner, pasted on the three-dimensional shape model.
- the force acting on the blood vessel wall acts as a pressure P not only in the direction along the blood vessel wall but also in the direction of collision with the blood vessel wall.
- This pressure is obtained by applying the pressure at the point G obtained in the global coordinate system to the local coordinate system. It can be obtained as the pressure value in the Zl-axis direction when converted.
- FIG. 24 shows the pressure values acting on the wall surface in a superimposed manner on FIG. The lighter the color, the higher the pressure.
- the wall shear stress 71 and its vector 72 thus obtained for each polygon are stored in the simulation result DB 16.
- the randomness calculation unit 31 obtains the randomness as an index that quantifies the form of the wall shear stress vector group in each mesh.
- This randomness is a numerical index indicating the degree of whether or not the wall shear stress vector of a certain mesh is aligned in the same direction as compared with the surrounding wall shear stress vector group. That is, each angle formed between the wall shear stress vector of a mesh for which the degree of randomness is obtained (hereinafter referred to as “target mesh”) and the wall shear stress vector of each mesh adjacent to the target mesh.
- target mesh each angle formed between the wall shear stress vector of a mesh for which the degree of randomness is obtained
- the degree of randomness is obtained by calculating ⁇ .
- FIG. 25 shows the relationship between the shear stress vector in the microelement G (approximate to a point for explanation) used in the system of this embodiment and the shear stress vector in the eight microelements surrounding the element G in a lattice shape. It is a thing. In this example, it is only necessary to extract not the magnitude of the shear stress but only the direction, so that the wall shear stress vector is handled as a unit vector. Strictly speaking, each microelement is in a three-dimensional configuration, but adjacent elements are sufficiently close to each other and are handled in two dimensions. That is, the processing is performed in such a way that each wall shear stress vector is projected onto a two-dimensional plane.
- FIG. 25 shows a state in which the minute element G and surrounding minute elements are mapped onto a two-dimensional orthogonal coordinate system.
- the form of the wall shear stress vector group is quantified by calculating ⁇ divergence (div) '' and ⁇ rotation (rotation) '' by the vector analysis with respect to the target mesh.
- a component display at a point G (x, y) obtained by mapping a vector field ⁇ (shear stress vector) of a mesh surrounding a space to the two-dimensional orthogonal coordinate system (x, y) is represented by the following expression.
- ⁇ (G) ( ⁇ x (x, y), ⁇ y (x, y)) It is expressed.
- FIG. 24 shows the relationship between the form of the wall shear stress vector group and the values of “divergence (div)” and “rotation (rot)”.
- the form of the wall shear stress vector group is roughly classified into 1) parallel type, 2) confluence type, 3) rotation type, and 4) divergent type.
- Fig. 27 shows the div and rot values mapped. That is, in this figure, the randomness (div, rot) is obtained for a typical example of the shear stress vector.
- a typical example is an ideal pattern that can be described mathematically, not experimental data.
- the degree of randomness has already been standardized, which enables comparison between patients. That is, according to this embodiment, the degree of randomness can be obtained as an index that can be evaluated as an absolute value.
- the damage determination to the blood vessel given when the blood flow collides with the blood vessel wall is performed with higher accuracy by combining the pressure of the target mesh as a weighting coefficient.
- a standardized pressure that is, a pressure index is used.
- a value obtained by dividing each pressure by the average pressure in the aneurysm is used as this pressure index after being calculated (multiplied in this example).
- the combination of the shape of the shear stress vector group and the pressure is effective in improving the accuracy, particularly in predicting the thinned portion of the cerebral aneurysm. That is, there are a plurality of ways of indexing the pressure, and a method of superimposing the pressure on the randomness calculated from the shear stress vector may be a multiplication or a power law, or may be a plurality.
- the determination unit 32 determines whether each mesh is a benign flow or a malignant flow from the randomness value of each mesh obtained by the randomness calculation unit 31.
- the wall shear stress vector states here include a parallel state parallel to the surrounding wall shear stress vector, a merged state extending in a direction approaching the surrounding wall shear stress vector, and the surrounding wall shear stress vector. There are a rotating state that rotates and a divergent state whose direction is radial with respect to the surrounding wall shear stress vector. If the wall shear stress vector corresponds to the parallel state, the blood flow property in the mesh is determined to be a benign flow, while if the wall shear stress vector corresponds to any of the confluence state, the rotation state, and the diverging state. The blood flow property in the mesh is determined as a malignant flow (non-benign flow).
- the risk is determined from the randomness value in the malignant flow.
- the index used as the threshold is that the inventor tracks the wall shear stress vector in the cerebral aneurysm of the cerebral aneurysm patient over time, and the actual wall brain stress sample collected from the patient. The value is set empirically based on the correlation with the vascular tissue of the aneurysm, but may be varied depending on the case.
- the threshold value is set in a stepwise manner, the state of the wall shear stress vector is further set in multiple steps, and the degree of benign flow and / or malignant flow is determined in steps.
- the wall thickness degree (lesion tendency) that becomes the thickness of the blood vessel wall can be classified according to the state of the wall surface shear stress vector. That is, if the wall shear stress vector corresponds to a parallel state, the wall thickness is of a normal level type. Further, when the wall shear stress vector corresponds to the confluence state and the rotation state, a soil in which blood cells and plasma proteins are easily deposited is formed, and the blood vessel is thickened and the wall thickness is increased. Furthermore, when the wall shear stress vector is in a divergent state, endothelial cell destruction and regeneration failure occur, so that soil in which blood cells infiltrate, proliferate, and migrate into the blood vessel is formed, and the mechanical strength of the blood vessel wall decreases. As a result, the blood vessel wall is thinned around the region, and the wall thickness is reduced.
- FIG. 28 is a schematic diagram showing the concept of the hardened portion and the thinned portion.
- FIG. 29 shows a user interface 17 for displaying the discrimination results by the blood flow property discrimination unit 13 (vector calculation unit 30, index calculation unit 31, and discrimination unit 32).
- the input of analysis data is read by pressing the ⁇ Load> button. Thereafter, the user can select items ⁇ streamline> 61 to ⁇ Flow disturbance index> 70 that the user wants to display, so that the display corresponding to the display unit of this interface can be performed.
- ⁇ Pressure ratio>, ⁇ Pressure loss coefficient>, and ⁇ Energy loss> can be selected as a parameter indicating the resistance of the blood vessel.
- the examination volume is set and each value is automatically calculated only by the user determining the start point and the end point with respect to the center line of the blood vessel. As a result, the discrimination result is displayed on the user interface 17.
- FIGS. 30A to 30D show an example of the discrimination result in an enlarged manner.
- the effectiveness and superiority of discrimination based on the degree of randomness ⁇ Flow disturbance index> will be described with reference to FIG.
- This system normalizes and displays the wall shear stress, pressure, and randomness with the maximum value on the wall.
- the display method means that the value is larger as the color is lighter, and the value is smaller as the color is darker.
- the display of the wall shear stress FIG. 30A
- three thin portions P1, 2, 3 identified from intraoperative observation and wall thickness analysis of the aneurysm wall are shown.
- P1 the wall shear stress shows a low value
- the distribution of P2 shows a high value unlike this, so it can be said that a specific distribution cannot be shown in the three thin sections.
- the wall shear stress vector FIG.
- the thin portion and the randomness (divergence) are correlated, and the thinned portion of the aneurysm wall of the patient can be predicted before surgery using the discrimination based on the randomness (divergence).
- the determination unit can determine whether the blood flow property of each mesh is a benign flow or a malignant flow based on the degree of randomness, and the result is visually displayed on the user interface. be able to.
- the blood flow state (streamline, flow velocity value, pressure value) of each mesh obtained by the fluid analysis device is visually displayed.
- the type of data to be displayed and the display mode are not particularly limited. For example, a three-dimensional image of a cerebral aneurysm is obtained from the three-dimensional image data of the cerebral aneurysm generated by the blood vessel shape extraction device. Display. By displaying the benign and malignant flow states obtained for each mesh in color on the surface of the 3D image. In the subject's cerebral aneurysm, it becomes possible to visually recognize an area of an aneurysm having a high density of malignant flow and an area not so.
- the randomness and blood flow property determination results obtained in this way are stored in the simulation result DB 16 as indicated by 74 and 75 in FIG.
- the determination result is preferably stored so that the position (and value) determined to be malignant flow is associated with the randomness value.
- the randomness calculation unit 13 may obtain, as the randomness index, a temporal variation degree representing a temporal variation degree of the randomness degree for each mesh. That is, here, after the degree of randomness is obtained, the degree of temporal change is calculated by time average of the randomness, its fluctuation, or frequency evaluation such as time series data, differentiation, and Fourier transform.
- the discrimination means discriminates the benign flow or the malignant flow by comparing the degree of time change with a threshold value stored in advance. That is, when the degree of time change is smaller than the threshold stored in advance, the blood flow in the mesh is determined to be benign, while when the degree of time change is greater than the threshold stored in advance, the mesh Blood flow is determined to be malignant flow.
- the threshold here is set to an empirical value based on the frequency corresponding to the heart beat. This is because the shear stress acting on the wall of the cerebral aneurysm over time acts at a frequency that exceeds the heart rate for some reason, destroying the endothelial cells of the blood vessel. Is based.
- the system for determining whether or not a cerebral aneurysm may be ruptured has been described.
- the present invention can also be applied to a system for determining whether or not there is any.
- the vector calculation unit can be configured as a single calculation device having the function.
- this computing device after obtaining the blood flow and pressure for each unit region in the target blood vessel part based on the image data of the target blood vessel part, the wall shear stress vector of the blood vessel wall surface is calculated for each unit region, The shear stress vector data can be output to an external device, and the data can be displayed on the interface 17.
- the surgical simulation described in the embodiment can be applied to the following surgical technique evaluation system, for example.
- a user who has performed a blood vessel anastomosis procedure using a blood vessel pseudo model can process the data by uploading the DICOM format data of the blood vessel suspected blood vessel model to the server 3 of this system.
- This upload may be performed by means such as sending by e-mail.
- the program storage unit of this system includes an energy loss calculation unit 77, a blood vessel shape correction unit 36, and a surgical technique evaluation unit 78.
- the energy loss calculation unit calculates the energy of blood flow at the inlet and outlet of the evaluation model based on the state quantity calculated by the fluid analysis unit, and calculates the loss. This loss is converted as the stenosis rate (stenosis degree) of the anastomosis by standardizing and converting the cross-sectional area and length of the blood vessel.
- the blood vessel shape correction unit 36 has the configuration of the shape correction unit 36 described in the above embodiment. Is used.
- the procedure evaluation unit 78 performs the following evaluation based on the energy loss (stenosis rate (stenosis degree) of the anastomosis portion).
- anastomosis technique training using a blood vessel model it is important to resume smooth blood flow when evaluating the result of the technique.
- Smooth means that there is no stenosis site in the anastomosis lumen.
- the presence of a stenosis site results in a loss of flow energy for the bloodstream. Therefore, in training for an anastomosis procedure, an ideal procedure is to perform anastomosis so as not to narrow the lumen of the anastomosis.
- the stenosis is considered to correspond to the above-mentioned lesion. That is, an immature procedure causes a stenosis in the vascular anastomosis, resulting in a situation where the energy loss of the resumed blood flow becomes high.
- the surgical simulation it is possible to evaluate how to improve the stenosis by interpreting the stenosis as a lesion in the embodiment.
- the user can arbitrarily edit the shape of the lesion, that is, the stenosis (according to the blood vessel shape editing function such as enlargement, reduction, deletion, etc.), thereby interpreting the relationship between the blood flow and the procedure.
- the evaluation unit uses the interface similar to the above-described embodiment so that the relationship between the procedure and the lumen shape and the relationship between the lumen shape and the blood flow can be quickly and intuitively shown on the computer display. It is configured.
- an anastomosis part joining part shape by an automatic anastomosis instrument becomes a T shape
- an anastomosis part cross-sectional shape approximates a circular shape.
- by enlarging or reducing the circular diameter in the anastomotic section it becomes possible to simulate the anastomosis result when blood vessels having different diameters are used.
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Abstract
Description
前述したように、本発明の第1の側面は、瘤の性状を診断するための診断装置である。この発明では、血流によって脳動脈瘤内の血管壁面に作用するせん断応力ベクトル群の形態を、瘤の内腔形状・病理情報・血管厚み情報に関連付けることで、将来的に血管組織の病変の発症や進展にもたらす一要因となり得る「悪性(良性でない)の血流パターン」と、当該要因になりにくい「良性の血流パターン」とに分類した。そして、シミュレーションの結果生成したせん断応力ベクトル群の形態が、前記悪性血流パターン若しくは良性血流パターンに該当するかを判定する。悪性血流パターンと判定されれば、将来的に血管組織の病変の発症や進展にもたらす一要因となり得るので手術の検討をする必要があることになるし、良性血流パターンと判定されればそのような要因になりづらいと判断し無用な手術によるリスクを回避することができることになる。
また、この発明の第2の側面は、例えば悪性血流パターンを有すると判断された脳動脈瘤を外科的に治療した後の治療効果を判定するための装置を提供することである。
このような場合、まず、コンピュータにより3次元モデル化された血管形状を修正し、新たな瘤ネック面をコンピュータ上で人為的に作成することで、実際に手術を行った場合と同様の血管形状を術前にコンピュータ上に構築する。そして、その新たな血管形状の血管壁面に作用する壁面せん断応力ベクトル群の形態を、シミュレーションにより可視化し、それに対して前記悪性・良性血流パターンの判別法を同様に適用することで、手術による治療効果を評価することができる。すなわち、前記悪性・良性血流パターンの判別法を適用することで、術後,当該部位に内皮細胞等の血管を構成する細胞が生着することで血管組織が適切に再生し十分な力学的強度を有するか否かの進展の方向を予測することができ、術後の合併症や死亡の可能性という観点から治療効果の予測に寄与することができる。
(本実施形態に係る血流性状診断・治療効果予測システムの構成)
図1は、本実施形態に係る血流性状判定・治療効果予測システムを示す概略ブロック構成図である。この血流性状判定・治療効果予測システムは、上記第1、第2の側面に対応し、以下の2つの機能を有する。
(ユーザグラフィカルインターフェース)
図2は、前記サーバ3の表示部14によって生成され前記ユーザ端末装置2上に表示されるグラフィカルユーザインターフェース(GUI)17を示すものである。このインターフェース17を通して、前記血管形状抽出部(i-Vessel)10、前記手術シミュレーション部(i-Surgery)11、前記流体解析部(i-CFD)12、前記血流性状判別部(i-Flow)13を一つのインターフェースを通して一括に操作できるように構成されている。
(血管形状抽出装置)
図3は、前記血管形状抽出装置の処理工程を示すブロック図であり、図4~図9はその説明図である。
(手術シミュレーション装置)
図9は、手術シミュレーション部11によるユーザグラフィカルインターフェース17を示す模式図、図10は、前記手術シミュレーション部11の動作を示すフローチャート、図11、12、図13はその説明図である。また図14は、この手術シミュレーションのために血管の三次元形状データを修正する形状修正部35の概略構成図である。
(流体解析部)
次に、流体解析部12で、上記血管形状抽出部10(及び手術シミュレーション部11)で生成された対象血管部位の三次元形状にデータに基づき、有限要素法による公知の演算によって、対象血管部位における各単位領域での血流の流速及び圧力(状態量33)を求める。
ここで:Dmesh:メッシュ分割詳細度(この例では算出したいメッシュの代表直径Dmeshを詳細度として用いる)、Dbase:ベースメッシュの大きさ(スケールファクターに依存しない定数)、Kscale:血管の大きさに応じて変動するスケールファクター、Kmodule:モジュールの選択に応じて変動するスケールファクターである。
Dbase=0.1 mm
Kscale=0.2 (D<1.5mmの場合)
Kscale=1.0(D>=1.5mmの場合)
Kmodule=1
(すなわちこのモジュールでは、等価直径Dが1.5mm未満のの細動脈にのみメッシュの大きさをベースメッシュの大きさから1/5に詳細化する)。
Dbase=0.1 mm
Kscale=0.2 (D<1.5mm)
Kscale=1.0(D>=1.5mm)
Kmodule=0.5
(すなわち、この例ではKmodule=0.5として全域的にメッシュを詳細化する)
なお、上記の方法では,血管の分岐部でメッシュの大きさが不連続的に変化してしまうということがある。メッシュの不連続変化は、そこでのメッシュの形状歪みを増加させることで計算の収束性を悪化させる要因となる。この問題の対処法として、この実施形態では、まずメッシュを前記手法で作成したのちに、メッシュ形状歪みに上限値を与えておき、最大形状歪みが閾値内に収まるように平滑化処理を繰り返し行うように構成されている。
(血流性状判別装置)
前記血流性状判別部13には、コンピュータを以下の各手段として機能させるプログラムがインストールされている。すなわち、前記血流性状判別部13は、図1に示すように、流体解析装置で求めた各メッシュの流速及び圧力から、血流によって血管壁面に作用する流体せん断応力及びそのベクトル(以下、単に、「壁面せん断応力ベクトル」と称する。)を各メッシュにそれぞれについて求める壁面せん断応力ベクトル演算部30と、壁面せん断応力ベクトルから、血流の性状を判別するための数値指標(乱雑度)を求める乱雑度演算部31と、前記乱雑度の大きさに応じて各メッシュにおける血流の性状を判別する判別部32とを備えている。
この図を説明する際には、グローバル座標系とローカル座標系への変換を理解する必要がある。すなわち、せん断応力ベクトルを求めるために使用する圧力P及び速度Uは前述したようにグローバル座標系で求められたものであるのに対して、血管壁面のある位置に作用するせん断応力は壁面の接線方向に向いているものでありその大きさを求めるには上記圧力及び速度を血管壁面を基準としたローカル座標系に変換する必要がある。
Un=n・dUt/dZ
で表わされる。
τ=μ・dUt/dZ
すなわち、壁面せん断応力ベクトルとは、微小要素に平行な速度ベクトルの法線方向での変化率を算出し、それに流体の粘性係数を乗じたものである。微小要素に対する平行方向速度ベクトルの法線方向変化率を算出する方法は幾つかの方法が考えられる。例えば、Zl軸上で複数の候補点を設置し、周囲速度ベクトル群から速度ベクトルを補間するという方式で各候補点での速度を得ることができる。なお、この場合、個々の周囲速度ベクトルごとに候補点との距離が異なるため、距離に対して重み関数を設定して補間を行う。周囲速度ベクトルはグローバル座標系で記述されているので、補間後の速度ベクトルをローカル座標系に座標変換することで各候補点での面平行方向の速度成分を算出する。後に、法線方向での変化率を算出する場合は、壁近傍の一つの候補点を用いて一次近似として算出しても良いし、壁近傍の複数の候補点を用いて多項式近似を行い、その後に数学的に微分するという高次の微分処理を行っても良い。
τ(Xl)=μ・dUt(Xl)/dZ
τ(Yl)=μ・dUt(Yl)/dZ
を算出することになる.
このローカル座標軸を総合したベクトル値τ(Xl、Yl)が壁面せん断応力ベクトルとなる。したがって、壁面せん断応力ベクトルは血管壁に接する面内でその面に対してx方向成分及びy方向成分を持つベクトルとなる。
次に、前記乱雑度演算部31で、各メッシュにおける壁面せん断応力ベクトル群の形態を数値化した指標としての乱雑度を求める。この乱雑度は、あるメッシュの壁面せん断応力ベクトルが、その周囲の壁面せん断応力ベクトル群と比較して同一方向に整列しているか否かの程度を表す数値指標である。すなわち、乱雑度を求める対象となるメッシュ(以下。「対象メッシュ」と称する。)の壁面せん断応力ベクトルと、対象メッシュの周囲で隣り合う各メッシュの壁面せん断応力ベクトルとの間になすそれぞれの角度θを演算によって求めることで乱雑度となる。
すなわち、空間のあるメッシュの囲のベクトル場τ(せん断応力ベクトル)を前記二次元直交座標系(x、 y)に写像した点G(x、 y)における成分表示を、次の式で表すとする。
であらわされる。
同様に、「ベクトル場τの回転」と呼ばれる「スカラー場rotτ」は、次の式で定義される。
図24は、壁面せん断応力ベクトル群の形態と、上記「発散(div)」及び「回転(rot)」の値の関係を示したものである。壁面せん断応力ベクトル群の形態とは、大きく、1)平行型、2)合流型、3)回転型、4)発散型、に分類される。
(判別部)
前記判別部32では、前記乱雑度演算部31で求めた各メッシュの乱雑度の値から、各メッシュそれぞれについて、良性流れか悪性流れかを判別する。ここでの壁面せん断応力ベクトルの状態としては、周囲の壁面せん断応力ベクトルに対してパラレルとなる平行状態と、周囲の壁面せん断応力ベクトルに近づく方向に伸びる合流状態と、周囲の壁面せん断応力ベクトルとともに回転する回転状態と、周囲の壁面せん断応力ベクトルに対して向きが放射状になる発散状態とがある。そして、壁面せん断応力ベクトルが平行状態に該当すれば、そのメッシュでの血流性状は良性流れと判定される一方、壁面せん断応力ベクトルが合流状態、回転状態、発散状態の何れかに該当すれば、そのメッシュでの血流性状は悪性流れ(良性でない流れ)と判定される。
(手術手技評価システムへの応用例)
前記一実施形態で説明した手術シミュレーションは、例えば以下のような手術手技評価システムに適用することも可能である。
吻合のトレーニングにおいて狭窄部は、上記クレームの病変に相当すると考えられる。すなわち未熟な手技により、血管吻合において狭窄部が生じ、結果として再開した血流のエネルギー損失が高値となる状況を招く。
Claims (43)
- 対象血管部位の血流をシミュレーションにより分析するシステムであって、
コンピュータが前記対象血管部位の三次元形状データに血流に関する境界条件を含む演算条件を与え、前記対象血管部位の内腔の各位置における血流の状態量を演算によって求める流体解析部と、
コンピュータが、前記三次元形状データを外科治療法をシュミレーションすることにより修正し修正後の三次元形状データを出力する三次元形状修正部と、
前記修正後の三次元形状データに基づいて前記流体解析部による状態量の演算を再実行させ、形状データ修正後の演算結果を修正前の演算結果と比較可能に表示する比較表示部と、
を有することを特徴とするシステム。 - 請求項1記載のシステムにおいて、
前記形状修正部は、
コンピュータが、前記三次元形状データをディスプレイ上にグラフィカル表示し、このディスプレイ上で三次元形状データ表示の凹凸を修正する部位の少なくとも1つのポリゴンの指定を受け付ける修正部位指定部と、
コンピュータが、上記ポリゴンをその重心の位置を起点として,面法線方向に沿う血管外側若しくは内側方向に移動若しくは歪ませるポリゴン移動部と、
コンピュータが、前記ポリゴン移動部が1以上のポリゴンを移動若しくは歪ませた後に生じた鋭角形状を検出して平滑化処理を行う平滑処理部と
を有することを特徴とするシステム。 - 請求項1記載のシステムおいて、
前記流体解析部により演算される状態量は流体の流速及び圧力である
ことを特徴とするシステム。 - 請求項1記載のシステムにおいて、
前記流体解析部により演算された状態量に基づいて、対象血管部位の血流のエネルギー損失を演算するエネルギー損失演算部をさらに有し、
前記比較表示部は、形状データ修正後のエネルギー損失演算結果を修正前のエネルギー損失演算結果と比較可能に表示する
ことを特徴とするシステム。 - 請求項1記載のシステムにおいて、
コンピュータが、前記対象血管部位の内腔の三次元形状データを読み込み、前記対象血管部位に含まれる複数の血管要素をその断面積の大きさに基づいてラベリングするラベリング部を有し、
前記断面積の大きさに基づくラベリングに基づき、血管要素毎にメッシュ分割詳細度を変動させて、前記状態量の演算を実行するものである
ことを特徴とするシステム。 - 請求項5記載のシステムにおいて、
前記ラベリング部は、
コンピュータが、特定の対象血管部位に含まれる主要血管要素の名称及びその他の血管要素の名称を、当該特定の対象血管部位に関連付けて格納する格納部と、
コンピュータが、特定の対象血管部位に含まれる各血管要素の形状を複数断面で測定し、その面積の中央値が最も大きいものを主要血管として特定すると共に、当該主要血管の判別に基づいて前記他の血管要素を特定し、これら主要血管要素及び他の血管要素の名称をラベリングし、前記三次元形状データと共に出力するものである
ことを特徴とするシステム - 請求項6のシステムにおいて、
前記メッシュ詳細度は、前記断面形状の面積の中央値の大きさによって決定され、詳細度の粗いものから細かいものまで複数段階で決定されるものである
ことを特徴とするシステム。 - 請求項1記載のシステムにおいて、
さらに、
コンピュータが、前記三次元形状データ内を流通する血流の状態量を演算するための境界条件を含む演算条件値のセットを複数格納する演算条件格納部であって、前記演算条件値の複数のセットは、それぞれ、ユーザが要求する計算速度に応じて1又はそれ以上の異なる演算条件値を含むものである、前記演算条件格納部を有し、
前記ユーザに、計算速度の選択を提示し、選択された計算速度に応じてこの計算速度に関連つけられた演算条件値のセットを取り出し、そのセットに含まれる演算条件値に基づいて上記血流の状態量の演算を実行し、演算結果を出力するものである
を有することを特徴とするシステム。 - 請求項8記載のシステムにおいて、
前記演算設定値の複数のセットのうち少なくとも1つのセットはユーザが計算速度を重視する場合に対応して血流を定常流と仮定した場合の演算条件値を含むものであり、少なくとも1つ他のセットはユーザが計算速度よりも計算精度を重視する場合に対応して血流を拍動流と仮定した場合の演算条件値を含むものである
ことを特徴とするシステム。 - 請求項9記載のシステムにおいて、
前記少なくとも1つ他のセットは、さらに、拍動流の拍動周期内で流れが層流から乱流へと遷移する場合を考慮した演算条件値を含むものである
ことを特徴とするシステム。 - 請求項9記載のシステムにおいて、
このシステムは、ユーザが計算速度を重視する場合に演算を行う第1のプロセッサと、ユーザが計算速度よりも計算精度を重視する場合に演算を行う第2のプロセッサとを有し、ユーザの選択に応じてどちらのプロセッサを使用するかを判断する判断部をさらに有するものである
ことを特徴とするシステム。 - 請求項11記載のシステムにおいて、
前記第2のプロセッサは、高速演算器を複数使用した並列解析を行うものである
ことを特徴とするシステム。 - 請求項11記載のシステムにおいて、前記第2のプロセッサは通信ネットワークを介して接続可能な別の場所に設けられており、前記判断部は、前記第2のプロセッサを使用すると判断した場合に計算に必要な条件の一部若しくはすべてを前記通信ネットワークを介して前記第2のプロセッサに送信し演算結果を受け取るものである
ことを特徴とするシステム。 - 請求項1記載のシステムにおいて、
前記形状修正部は、手術後の対象血管部位の三次元形状データをシミュレーションにより生成する手術シミュレーション部を有し、
この手術シミュレーション部は、
コンピュータが、前記三次元形状抽出部で生成された前記三次元形状データをディスプレイ上に3次元表示し、このディスプレイ上における病変部の指定及びこの病変部に対する外科的治療方法の選択を受け付ける治療方法受付部と、
コンピュータが、選択可能な治療方法と治療方法に応じた三次元形状データの修正方法を予め格納する修正方法格納部と、
コンピュータが、前記治療方法の選択に基づいて前記修正方法格納部に格納された修正方法を取り出し、当該修正方法で前記指定に係る病変部の三次元形状データを修正し、修正した後の三次元形状データを出力する修正済み三次元形状出力部と
を有することを特徴とするシステム。 - 請求項14記載のシステムにおいて、
前記選択可能な治療方法は、コイル塞栓術を含み、
このコイル塞栓術に応じた三次元形状データの修正方法は、上記三次元形状データ化された前記対象血管部位の内腔の一部に多孔質構造体を配置する手段を有し、上記血管の内腔の一部をコイルで閉塞した状態をシミュレーションするものである
ことを特徴とするシステム。 - 請求項15記載のシステムにおいて、
さらに、前記多孔質構造体の開口率でコイル充填率を変動させる手段を有する
ことを特徴とするシステム。 - 請求項14記載のシステムにおいて、
前記選択可能な治療方法は、クリッピング法を含み、
この治療法に応じた三次元形状データの修正方法は、血管内腔の一部(瘤等を構成する部分)の面を構成する1又は複数のポリゴンを削除する手段と、削除した面を別の1又は複数のポリゴンで再生する手段とを有し、前記血管内腔の一部を完全閉鎖させた場合をシミュレーションするものである
ことを特徴とするシステム。 - 請求項14記載のシステムにおいて、
前記選択可能な治療方法は、ステント留置術を含み、
この治療法に応じた三次元形状データの修正方法は、血管内腔の一部の面の凹凸を、ポリゴンを移動若しくは歪ませることで修正する手段を有し、前記ステントにより血管内の血流の流れを制御した場合をシミュレーションするものである
ことを特徴とするシステム。 - 請求項14記載のシステムにおいて、
前記選択可能な治療方法は、Flow-diverting stent留置術を含み、
この治療法に応じた三次元形状データの修正方法は、上記三次元形状データ化された前記対象血管部位の内腔の一部に格子状物体を定義する手段とを有し、Flow-diverting stentにより血流が制限される場合をシミュレーションするものである
ことを特徴とするシステム。 - 請求項19記載のシステムにおいて、
さらに、前記格子状物体の開口率でFlow-diverting stentの格子密度を変動させる手段を有する
ことを特徴とするシステム。 - 請求項1記載のシステムにおいて、
コンピュータが、前記流体解析部で求めた血流の状態量から、前記対象血管部位の血管壁面の各位置における壁面せん断応力ベクトルを求め、特定の壁面位置における当該壁面せん断応力ベクトルの方向とその周囲の壁面位置における壁面せん断応力ベクトルの方向の相対関係を求め、その形態から当該壁面位置における前記血流の性状を判別しその判別結果を出力する血流性状判別部
をさらに有し、
前記比較表示部は、対象血管部位の三次元形状データ修正後の前記血液性状判別部の演算結果を修正前の演算結果と比較可能に表示するものである
ことを特徴とするシステム。
することを特徴とするシステム。 - 請求項21記載のシステムにおいて、
前記血流性状判別部は、
コンピュータが、前記特定の壁面位置における壁面せん断応力ベクトルの方向とその周囲の壁面位置における壁面せん断応力ベクトルの方向の相対関係が、「平行」、「合流」、「回転」、「発散」のいずれにあるかを判別し、「平行」の場合には血流性状が良性流れ(非悪性流れ)、それ以外の場合は悪性流れ(非良性流)と判別するものである
ことを特徴とするシステム。 - 請求項22記載のシステムにおいて、
前記血流性状判別部は、
こ前記特定の壁面位置における壁面せん断応力ベクトルの方向とその周囲の壁面位置における壁面せん断応力ベクトルの方向の相対関係が「発散」である場合、当該壁面位置で血管壁の菲薄化が生じると判別してその位置を出力し、
前記比較表示部は、
前記菲薄化の生じる可能性のある位置を前記三次元形状モデルと重旦させてグラフィカル表示出力する
ことを特徴とするシステム。 - 請求項22記載のシステムにおいて、
前記血流性状判別部は、
前記特定の壁面位置における壁面せん断応力ベクトルτとその周囲の壁面位置における複数の壁面せん断応力ベクトルの相対角度関係から、ベクトル場τのスカラー量である回転rotτ及び発散divτを求め、それらの値を乱雑度として閾値と比較することで前記「平行」、「合流」、「回転」、「発散」のいずれにあるかを判別するもので、
前記乱雑度の回転rotτの値が所定の閾値範囲外の負値若しくは正値であるときに「回転」と判別し、
前記乱雑度の前記発散divτの値が所定の閾値範囲外の負値であるときに「合流」と判別し、
前記乱雑度の前記発散divτの値が所定の閾値範囲外の正値であるときに「発散」と判別し、
前記乱雑度の回転rotτの値及び前記発散divτの値の両方が所定の閾値内にあるときに「平行」と判別する
ことを特徴とするシステム。 - 請求項24記載のシステムにおいて、
前記血流性状判別部は、
前記複数の壁面せん断応力ベクトルを演算上単位ベクトルとして扱い、
前記回転rotτ及び発散divτと比較される閾値は0である
ことを特徴とするシステム。 - 請求項24記載のシステムにおいて、
前記血流性状判別部は、
前記乱雑度の前記回転rotτ及び発散divτの値を、前記回転rotτ及び発散divτの値に当該壁面位置に法線方向に作用する圧力の指標値を重み係数として与えることで求めるものである
ことを特徴とするシステム。 - 請求項26記載のシステムにおいて、
前記血流性状判別部は、
前記乱雑度の前記回転rotτ及び発散divτの値を求める際に与えられる圧力の指標値は、当該壁面位置に作用する圧力を対象血管部位の壁面に作用する平均の圧力値で除した値である
ことを特徴とするシステム。 - 請求項24記載のシステムにおいて、
前記比較表示部は、
前記乱雑度の前記回転rotτ若しくは/及び前記発散divτの値をディスプレイ上に前記三次元形状モデルと重旦させて表示出力する
ことを特徴とするシステム。 - 請求項21記載のシステムにおいて、
前記血流性状判別部は、前記特定の壁面位置における壁面せん断応力ベクトルτとその周囲の壁面位置における複数の壁面せん断応力ベクトルの相対関係から、ベクトル場τの回転rotτ及び発散divτを求め、その値を乱雑度として閾値と比較し、閾値範囲内の場合には良性流れ(非悪性流れ)、範囲外の場合には悪性流れ(非良性流れ)と判別する
ことを特徴とするシステム。 - 請求項29記載のシステムにおいて、
前記血流性状判別部は、
前記複数の壁面せん断応力ベクトルを演算上単位ベクトルとして扱い、
前記回転rotτ及び発散divτと比較される閾値は0である
ことを特徴とするシステム。 - 請求項29記載のシステムにおいて、
前記血流性状判別部は、
前記乱雑度の前記回転rotτ及び発散divτの値を、前記回転rotτ及び発散divτの値に当該壁面位置に法線方向に作用する圧力の指標値を重み係数として与えることで求めるものである
ことを特徴とするシステム。 - 請求項31記載のシステムにおいて、
前記血流性状判別部は、
前記乱雑度の前記回転rotτ及び発散divτの値を求める際に与えられる圧力の指標値は、当該壁面位置に作用する圧力を対象血管部位の壁面に作用する平均の圧力値で除した値である
ことを特徴とするシステム。 - 請求項30記載のシステムにおいて、
前記比較表示部は、
前記乱雑度の前記回転rotτ若しくは/及び前記発散divτの値をディスプレイ上に前記三次元形状モデルと重旦させて表示出力する
ことを特徴とするシステム。 - 対象血管部位の血流をシミュレーションにより分析するコンピュータソフトウエアプログラムであって、このプログラムは以下の命令:
コンピュータが前記対象血管部位の三次元形状データに血流に関する境界条件を含む演算条件を与え、前記対象血管部位の内腔の各位置における血流の状態量を演算によって求める流体解析部と、
コンピュータが、前記三次元形状データを外科治療法をシュミレーションすることにより修正し修正後の三次元形状データを出力する三次元形状修正部と、
前記修正後の三次元形状データに基づいて前記流体解析部による状態量の演算を再実行させ、形状データ修正後の演算結果を修正前の演算結果と比較可能に表示する比較表示部と、
を有することを特徴とするコンピュータソフトウエアプログラム。 - 請求項34記載のコンピュータソフトウエアプログラムにおいて、
前記形状修正部は、
コンピュータが、前記三次元形状データをディスプレイ上にグラフィカル表示し、このディスプレイ上で三次元形状データ表示の凹凸を修正する部位の少なくとも1つのポリゴンの指定を受け付ける修正部位指定部と、
コンピュータが、上記ポリゴンをその重心の位置を起点として,面法線方向に沿う血管外側若しくは内側方向に移動若しくは歪ませるポリゴン移動部と、
コンピュータが、前記ポリゴン移動部が1以上のポリゴンを移動若しくは歪ませた後に生じた鋭角形状を検出して平滑化処理を行う平滑処理部と
を有することを特徴とするコンピュータソフトウエアプログラム。 - 請求項34記載のコンピュータソフトウエアプログラムおいて、
前記流体解析部により演算される状態量は流体の流速及び圧力である
ことを特徴とするコンピュータソフトウエアプログラム。 - 請求項34記載のコンピュータソフトウエアプログラムにおいて、
前記流体解析部により演算された状態量に基づいて、対象血管部位の血流のエネルギー損失を演算するエネルギー損失演算部をさらに有し、
前記比較表示部は、形状データ修正後のエネルギー損失演算結果を修正前のエネルギー損失演算結果と比較可能に表示する
ことを特徴とするコンピュータソフトウエアプログラム。 - 請求項34記載のコンピュータソフトウエアプログラムにおいて、
コンピュータが、前記流体解析部で求めた血流の状態量から、前記対象血管部位の血管壁面の各位置における壁面せん断応力ベクトルを求め、特定の壁面位置における当該壁面せん断応力ベクトルの方向とその周囲の壁面位置における壁面せん断応力ベクトルの方向の相対関係を求め、その形態から当該壁面位置における前記血流の性状を判別しその判別結果を出力する血流性状判別部
をさらに有し、
前記比較表示部は、対象血管部位の三次元形状データ修正後の前記血液性状判別部の演算結果を修正前の演算結果と比較可能に表示するものである
ことを特徴とするコンピュータソフトウエアプログラム。 - 対象血管部位の血流をシミュレーションにより分析するコンピュータにより実行される方法であって、
コンピュータが前記対象血管部位の三次元形状データに血流に関する境界条件を含む演算条件を与え、前記対象血管部位の内腔の各位置における血流の状態量を演算によって求める流体解析工程と、
コンピュータが、前記三次元形状データを外科治療法をシュミレーションすることにより修正し修正後の三次元形状データを出力する三次元形状修正工程と、
前記修正後の三次元形状データに基づいて前記流体解析部による状態量の演算を再実行させ、形状データ修正後の演算結果を修正前の演算結果と比較可能に表示する比較表示工程と、
を有することを特徴とする方法。 - 請求項39記載の方法において、
前記形状修正工程は、
コンピュータが、前記三次元形状データをディスプレイ上にグラフィカル表示し、このディスプレイ上で三次元形状データ表示の凹凸を修正する部位の少なくとも1つのポリゴンの指定を受け付ける修正部位指定工程と、
コンピュータが、上記ポリゴンをその重心の位置を起点として,面法線方向に沿う血管外側若しくは内側方向に移動若しくは歪ませるポリゴン移動工程と、
コンピュータが、前記ポリゴン移動工程で1以上のポリゴンを移動若しくは歪ませた後に生じた鋭角形状を検出して平滑化処理を行う平滑処理工程と
を有することを特徴とする方法。 - 請求項39記載の方法おいて、
前記流体解析工程により演算される状態量は流体の流速及び圧力である
ことを特徴とする方法。 - 請求項39記載の方法において、
前記流体解析部により演算された状態量に基づいて、対象血管部位の血流のエネルギー損失を演算するエネルギー損失演算工程をさらに有し、
前記比較表示工程は、形状データ修正後のエネルギー損失演算結果を修正前のエネルギー損失演算結果と比較可能に表示する
ことを特徴とする方法。 - 請求項39記載の方法において、
コンピュータが、前記流体解析部で求めた血流の状態量から、前記対象血管部位の血管壁面の各位置における壁面せん断応力ベクトルを求め、特定の壁面位置における当該壁面せん断応力ベクトルの方向とその周囲の壁面位置における壁面せん断応力ベクトルの方向の相対関係を求め、その形態から当該壁面位置における前記血流の性状を判別しその判別結果を出力する血流性状判別工程
をさらに有し、
前記比較表示部は、対象血管部位の三次元形状データ修正後の前記血液性状判別部の演算結果を修正前の演算結果と比較可能に表示するものである
ことを特徴とする方法。
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