WO2024103115A1 - Procédé de modélisation d'une anastomose de canaux - Google Patents

Procédé de modélisation d'une anastomose de canaux Download PDF

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Publication number
WO2024103115A1
WO2024103115A1 PCT/AU2023/051159 AU2023051159W WO2024103115A1 WO 2024103115 A1 WO2024103115 A1 WO 2024103115A1 AU 2023051159 W AU2023051159 W AU 2023051159W WO 2024103115 A1 WO2024103115 A1 WO 2024103115A1
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model
channels
channel
anastomosis
model channels
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PCT/AU2023/051159
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English (en)
Inventor
James Graham WOOD
Fraser Maurice CALLAGHAN
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CFI Surgery Pty Ltd
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Priority claimed from AU2022903481A external-priority patent/AU2022903481A0/en
Application filed by CFI Surgery Pty Ltd filed Critical CFI Surgery Pty Ltd
Publication of WO2024103115A1 publication Critical patent/WO2024103115A1/fr

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    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B34/00—Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
    • A61B34/10—Computer-aided planning, simulation or modelling of surgical operations
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
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    • A61B34/25—User interfaces for surgical systems
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    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G06F30/28—Design optimisation, verification or simulation using fluid dynamics, e.g. using Navier-Stokes equations or computational fluid dynamics [CFD]
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    • G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
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    • G06T17/205—Re-meshing
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    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
    • G09B23/00—Models for scientific, medical, or mathematical purposes, e.g. full-sized devices for demonstration purposes
    • G09B23/28—Models for scientific, medical, or mathematical purposes, e.g. full-sized devices for demonstration purposes for medicine
    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
    • G09B23/00—Models for scientific, medical, or mathematical purposes, e.g. full-sized devices for demonstration purposes
    • G09B23/28—Models for scientific, medical, or mathematical purposes, e.g. full-sized devices for demonstration purposes for medicine
    • G09B23/30—Anatomical models
    • G09B23/303—Anatomical models specially adapted to simulate circulation of bodily fluids
    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
    • G09B9/00—Simulators for teaching or training purposes
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/40—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/50—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
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    • A61B2034/102—Modelling of surgical devices, implants or prosthesis
    • A61B2034/104—Modelling the effect of the tool, e.g. the effect of an implanted prosthesis or for predicting the effect of ablation or burring
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    • A61B34/00—Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
    • A61B34/10—Computer-aided planning, simulation or modelling of surgical operations
    • A61B2034/101—Computer-aided simulation of surgical operations
    • A61B2034/105—Modelling of the patient, e.g. for ligaments or bones
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Definitions

  • the present invention relates generally to modelling anastomosis of human body channels (e.g., blood vessels, intestines, etc.).
  • the present invention also relates to a method of training a trainee surgeon using the method of modelling anastomosis of human body channels.
  • anastomosis e.g., coronary anastomosis, which is the joining of coronary arteries with grafts for bypass surgery
  • anastomosis e.g., coronary anastomosis, which is the joining of coronary arteries with grafts for bypass surgery
  • the trainee surgeon After a significant period of time, the trainee surgeon starts to perform parts of the anastomosis operation. This is however a slow and difficult process to learn, especially when there is limited scope for failure or opportunity for feedback.
  • Fluid dynamics e.g., blood flow, blood pressure, etc.
  • stitching quality of the anastomosis can then be simulated on the model anastomosis.
  • a method of modelling internal parts of anastomosis of model channels wherein the model channels comprise a model native channel and a model graft channel, the method comprising: receiving a set of images of the model channels; receiving input identifying parameters relating to the model channels; segmenting the model channels based on the identified parameters; generating computational fluid dynamics mesh on the segmented model channels; and simulating fluid dynamics of the model channels using the computational fluid dynamics mesh.
  • a method of analysing stitching of anastomosis of model channels wherein the model channels comprise a model native channel and a model graft channel, the method comprising: receiving a three- dimensional model of the outer parts of the model channels; adding a spline curve to the three- dimensional model; and adding points of interest to the spline curve, wherein the points of interest relate to locations of the stitching.
  • a method of providing feedback to a surgeon performing anastomosis on model channels wherein the model channels comprise a model native channel and a model graft channel, the method comprising: receiving the model channels; performing the method described above on the model channels; displaying simulation results of the method on a user interface.
  • a computer program product including a computer readable medium having recorded thereon a computer program for implementing any one of the methods described above.
  • Fig. 1 shows anastomosis of model channels
  • Fig. 2 is a flow diagram of a method of modelling the internal parts of the model channels of Fig. 1 and simulating the fluid dynamics of the model channels of Fig. 1 according to the present disclosure;
  • Fig. 3 is a segmenting sub-process of the method of Fig. 2;
  • FIG. 4 is a flow diagram of a method of analysing the stitching of anastomosis of the model channels of Fig. 1;
  • FIGs. 5A and 5B show a user interface showing a video of a trainee surgeon performing anastomosis on model channels and simulation results of the anastomosis; and [0017] Figs. 6A and 6B form a schematic block diagram of a general purpose computer system upon which arrangements described can be practiced.
  • the present disclosure provides a method of providing feedback to a surgeon in performing anastomosis.
  • the method enables a trainee surgeon to perform anastomosis on model channels (i.e. , model blood vessels, model intestines, etc.). While performing the anastomosis, a video of the operation is captured. Such a video enables a trained surgeon to evaluate the performance of the trainee surgeon and to provide feedback. Alternatively, a trainee surgeon can learn by reviewing the video.
  • 3D models of both the internal parts and the outer parts of the joined model channels are acquired.
  • the 3D model of the internal parts is used to analyse the fluid dynamics of the joined model channels to determine whether the anastomosis would result in good quality fluid dynamics (e.g., blood flow, blood pressure, etc.) between the joined model channels.
  • the 3D model of the outer parts is used to analyse the stitching performed by the trainee surgeon. Both 3D models provide more data to a trained surgeon, so as to enable that trained surgeon to better advise the trainee surgeon on improving the anastomosis skills of that trainee surgeon. Alternatively, the trainee can learn by reviewing the provided data.
  • Fig. 1 shows model native channel 110 that is joined with model graft channel 120 through surgical anastomosis.
  • Model native channel 110 represents a human native channel such as blood vessel, intestines, etc.
  • Model graft channel 120 represents a human channel that is to be grafted onto model native channel 110.
  • Model native channel 110 is disposed on model block 130.
  • the joined model channels 110 and 120 are then scanned using micro computed tomography (pCT) imaging.
  • pCT micro computed tomography
  • the resulting images are used to generate a three-dimensional (3D) virtual model of the inner parts of the joined model channels 110 and 120.
  • the 3D virtual model can then be used to simulate a 3D, time dependent fluid dynamics (e.g., blood flow and pressure) through the channels 110 and 120.
  • the fluid dynamics of the joined channels 110 and 120 can then be analysed to assess the performance of the anastomosis.
  • the joined model channels 110 and 120 are scanned using a scanner (e.g., a laser scanner, a photogrammetry scanner, and the like) to obtain another 3D model representing the outer parts of the joined model channels 110 and 120.
  • the 3D model of the outer parts can then be analysed to determine whether the stitching joining channels 110 and 120 are of good quality (e.g., optimal spacing, etc.).
  • Fig. 2 shows a flow diagram of method 200 of modelling the internal parts of model channels 110 and 120 and simulating the fluid dynamics (e.g., blood flow and pressure) of model channels 110 and 120.
  • fluid dynamics e.g., blood flow and pressure
  • Method 200 is a software application program 1333 that is executable by the computer system 1300 (see the description below in relation to Figs. 6A and 6B).
  • Method 200 commences at step 205 by receiving a set of images of anastomosis of model channels 110 and 120 (as shown in Fig. 1).
  • the set of images are acquired using pCT imaging.
  • the pCT imaging scans model channels 110 and 120 across the orthogonal cross section of model native channel 110.
  • the pCT imaging then moves the scan along the longitudinal axis of model native channel 110.
  • a static generator and detector with a rotating sample i.e., the joined model channels 110 and 120 are used.
  • the set of images are saved in a single scalar format, such as DICOM or NIFTI data format.
  • the set of images includes low intensity data values defining air and high intensity values defining either model channel 110 or 120, or model block 130.
  • the set of images is associated with an identifier.
  • the identifier is associated with a trainee surgeon who performed the surgical anastomosis of model channels 110 and 120.
  • the identifier enables ease of identification of particular model channels 110 and 120 with the resulting fluid dynamics and stitching analysis.
  • the trainee surgeon may capture a video of the surgical anastomosis being performed on model channels 110 and 120.
  • Such identification of the video with the resulting fluid dynamics and stitching analysis provide feedback to the trainee surgeon.
  • a trained surgeon may then provide advice for improving the skills of the trainee surgeon based on the provided feedback.
  • the fluid dynamics analysis identifies that the blood flow through the joined model channels 110 and 120 is not optimal.
  • a trained surgeon may then identify that the stitching of model channels 110 and 120 is not optimally located, and therefore advise the trainee surgeon to amend the placement of the stitching.
  • step 210 proceeds from step 205 to step 210.
  • step 210 method 200 receives input identifying parameters relating to model channels 110 and 120.
  • the parameters identified are as follows:
  • model graft channel 120 - inlet 140 (see Fig. 1) of model graft channel 120;
  • model native channel 110 - inlet (not shown in Fig. 1) of model native channel 110;
  • a user provides the locations of the above noted parameters by manipulating mouse pointer device 1303 (see the description below in relation to Figs. 6A and 6B) and manually selecting the locations.
  • Method 200 then proceeds from step 210 to sub-process 300.
  • Sub-process 300 is a segmentation algorithm and is shown in Fig. 3.
  • Sub-process 300 is a software application program 1333 that is executable by the computer system 1300 (see the description below in relation to Figs. 6A and 6B).
  • Sub-process 300 commences at step 305 by fitting a cylindrical model to each inlet/outlet locations (e.g., 140, 150) of the set of images. Each cylindrical model is centred upon the inlet/outlet locations. The direction of orientation of the normal vector of each cylindrical model is pointed towards location 160 of the anastomosis.
  • Sub-process 300 then proceeds from step 305 to step 310.
  • sub-process 300 applies a filter to reduce the image noise from the pCT imaging.
  • the filtering provides a more homogenous signal relating to the air and model channels 110 and 120 and model block 130.
  • the filter includes two filters. The first filter is applied to each image by convolving each image with a mask that takes the mean of all values in the image weighted by similarity to a predefined value. The second filter is applied by convolving each image with a mask that represents a median smoothing operation.
  • Sub-process 300 then proceeds from step 310 to step 315.
  • sub-process 300 generates a three-dimensional (3D) model of model channels 110 and 120.
  • the 3D model is generated by applying a 3D isocontour of the set of images using a marching cubes algorithm, to extract a continuous 3D polygonal mesh composed of triangle elements.
  • the mesh is then clipped at the inlet/outlet locations (e.g., 140, 150) with a plane defined by the inlet/outlet point location and the normal orientation vector (described above).
  • Sub-process 300 then proceeds from step 315 to step 320.
  • step 320 sub-process 300 receives input from a user to adjust the 3D model.
  • the adjustment may be required if the 3D model generated at step 315 has inhomogeneities within the model channels 110 or 120, or model block 130, causing the marching cubes algorithm to generate an irregular surface.
  • the resultant surface is a single continuous surface defining the lumen of the model graft channel 120 and model native channel 110 with three open ends (i.e., inlet 140 of model graft channel 120; inlet of model native channel 110; and outlet 150 of model native channel 110).
  • Sub-process 300 concludes at the completion of step 320.
  • Method 200 proceeds from sub-process 300 to step 215.
  • step 215 method 200 adds ends to each of the inlet/outlet locations (e.g., 140, 150) to ensure that the distance between each inlet/outlet location and location 160 is equal to a predefined length.
  • Method 200 proceeds from step 215 to step 220.
  • step 220 method 200 adds caps to the extended ends at each of the inlet/outlet locations.
  • Each cap is formed by triangles, where a point of each triangle is disposed at the centre of the inlet/outlet locations and the two remaining points of the triangle are disposed at the boundary of the inlet/outlet locations.
  • the caps provide a closed “watertight” virtual simulation lumen surface.
  • the caps are labelled such that the spatial area that the caps cover is known for use during the computational fluid dynamics (CFD) simulation.
  • Method 200 proceeds from step 220 to step 225.
  • step 225 method 200 converts the watertight virtual simulation lumen surface (generated at step 315 of sub-process 300 and step 220) into a volumetric mesh of the internal parts of the joined model channels 110 and 120.
  • Method 200 concludes at the conclusion of step 225.
  • a CFD simulation of blood flow through the volumetric mesh (generated at step 225 of method 200) is then performed to estimate blood flow dynamics through model channels 110 and 120 (which are joined through surgical anastomosis).
  • the CFD simulations use finite volume analysis to solve the boundary value problem defined by solution of the Navier-Stokes equations of fluid dynamics on the volumetric mesh. Boundary conditions are set up as the positive pressure drop between inlet 140 of model graft channel 120 and outlet 150 of model native channel 110.
  • a small residual flow volume is set to enter via the inlet of model native channel 110 to represent a slight physiological perfusion of a native channel.
  • the simulated fluid flow is enforced to have zero velocity at the virtual simulation lumen surface of the volumetric mesh to represent a zero-slip flow condition at the channel internal walls.
  • the CFD simulation linearises the partial differential equations of the Navier-Stokes equation, using the finite volume technique.
  • the linear system is then solved via an optimisation routine that aims to reduce residual errors.
  • the optimisation scheme is run until residual errors are below an acceptable small value.
  • Fig. 4 shows a flow diagram of method 400 of analysing the 3D model of the outer parts of model channels 110 and 120 to analyse the stitching performed on model channels 110 and 120.
  • Method 400 is a software application program 1333 that is executable by the computer system 1300 (see the description below in relation to Figs. 6A and 6B).
  • Method 400 commences at step 405 by receiving a three-dimensional (3D) model of the outer parts of joined model channels 110 and 120 (as shown in Fig. 1).
  • the 3D model is acquired using a scanner (e.g., a laser scanner, a photogrammetry scanner, and the like).
  • the received 3D model is composed of small polygons. Each polygon is composed of nodes and edges.
  • the set of images processed by method 200 is associated with an identifier.
  • the 3D model received for processing by method 400 is also associated with the same identifier.
  • Method 400 then proceeds from step 405 to step 410.
  • step 410 method 400 adds a spline curve to the stitching locations (which are at the joining of model channels 110 and 120) on the 3D model.
  • a user manually adds the spline curve using mouse pointer device 1303 (see the description below in relation to Figs. 6A and 6B).
  • Method 400 then proceeds from step 410 to step 415.
  • step 415 points of interest are added to the spline curve.
  • the points of interest are the stitching locations joining model channels 110 and 120. These points of interest can then be used to determine and analyse the spacing of the stitching locations.
  • a user manually adds the spline curve using mouse pointer device 1303 (see the description below in relation to Figs. 6A and 6B).
  • the points of interest snap to coincide with points of the 3D model to assist with accurate measurement. Points of interest can be removed and added by the user.
  • the spline curve is then saved as an image file.
  • the image file is then used to provide a two-dimensional (2D) visual output of the 3D model with the spline curve overlaid upon the 3D model.
  • 2D visual outputs include: (1) a “birds eye” view of the spline curve projected upon a plane of best fit showing the spacing between points of interest; and (2) a linear representation of the spline curve with markers showing spacings between measurements.
  • the spacings between points of interest are identified by different colours according to a diverging colour scale that is centred on a measurement calculated as being the total distance of the spline curve divided by the number of points of interest (i.e., a curve made up of equidistant line segments between points of interest).
  • a first colour is used to illustrate measurements that are equal to the equidistant measurement.
  • a second colour is used to illustrate measurements smaller than the equidistant measurement minus an offset.
  • a third colour is used to illustrate measurements greater than the equidistant measurement plus an offset.
  • a linear scale between the equidistant measurement and the lower and upper offsets is established and a corresponding linear transform from the first colour to the second and third colours, respectively, is established, such that each measurement between points of interest can be assigned a colour that is indicative of its value relative to the equidistant measurement. If a measurement between two points is lower than the equidistant measurement minus the offset, then the colour assigned is the second colour. If a measurement between two points is greater than the equidistant measurement plus the offset, then it is assigned the third colour.
  • Figs. 5A and 5B show user interface 500 having a set of images 510 of the pCT imaging; the 3D model 520 of the internal parts of the joined model channels 110 and 120; the 3D model 530 of the outer parts of the joined model channels 110 and 120; the spline curve 540 of the 3D model 530; a video 550; and a simulation results 560 of the fluid dynamics of the 3D model 520.
  • the set of images 510 are the images received at step 205 of method 200.
  • the 3D model 520 is generated at step 225 of method 200.
  • the 3D model 530 is generated by the scanner described in relation to step 405 of method 400.
  • the spline curve 540 is described in relation to step 410 of method 400.
  • the simulation results 560 is the CFD simulation described following the description of method 200.
  • the video 550 is a video captured to record a trainee surgeon as described in relation to step 205 of method 200.
  • an identifier is associated with both the set of images 510 and the 3D model 530.
  • the identifier is also associated with a trainee surgeon performing the anastomosis.
  • the user interface 500 presents all related data (i.e. , 3D models 520, 530; spline curve 540, etc.) related to a particular joined model channels 110 and 120 performed by a particular trainee surgeon.
  • the set of images 510 are high resolution images. Therefore, in one optional arrangement, the set of images 510 are downsized to enable faster loading when presented to the user interface.
  • the downsizing of the set of images 510 is performed by a user selecting a start location and an end location in the centre of model native channel 110. This step may be performed at step 210 of method 200.
  • An algorithm then calculates equidistant spacings along a line segment formed between the start and end locations. In one arrangement, 50 equidistant spacings are calculated, resulting in 50 locations. At each of the locations, a cross sectional view of the pCT data is extracted, resized to a predefined size, and saved with a predefined naming convention.
  • user interface 500 is provided by a server that is accessible to trainee surgeons via the Internet. Accordingly, to access the services provided, the trainee surgeon captures a video of joining model channels 110 and 120. The trainee surgeon then provides the video to the server with details (such as the name of the trainee surgeon, a time and date, etc.). In turn, the server assigns an identifier to the video based on those details.
  • the trainee surgeon then sends the joined model channels 110 and 120 to be scanned.
  • the same details as the video are provided on the model channels 110 and 120.
  • a user scans model channels 110 and 120 to acquire the set of images 510 and 3D model 530.
  • the set of images 510 and 3D model 530 are assigned the same identifier as the video based on the details provided on model channels 110 and 120.
  • the server then processes the set of images 510 and 3D model 530 based on respective methods 200 and 400.
  • the outcomes of methods 200 and 400 are then provided on user interface 500.
  • the user interface displaying a video, models, and simulation results enables a trainee surgeon to perform a new anastomosis simulation on model channels while reviewing the previous video, results, and models.
  • FIGs. 6A and 6B depict a general-purpose computer system 1300, upon which the various arrangements described above can be practiced.
  • the computer system 1300 includes: a computer module 1301 ; input devices such as a keyboard 1302, a mouse pointer device 1303, a scanner 1326, a camera 1327, and a microphone 1380; and output devices including a printer 1315, a display device 1314 and loudspeakers 1317.
  • An external Modulator-Demodulator (Modem) transceiver device 1316 may be used by the computer module 1301 for communicating to and from a communications network 1320 via a connection 1321.
  • the communications network 1320 may be a wide-area network (WAN), such as the Internet, a cellular telecommunications network, or a private WAN.
  • WAN wide-area network
  • the modem 1316 may be a traditional “dial-up” modem.
  • the modem 1316 may be a broadband modem.
  • a wireless modem may also be used for wireless connection to the communications network 1320.
  • the computer module 1301 typically includes at least one processor unit 1305, and a memory unit 1306.
  • the memory unit 1306 may have semiconductor random access memory (RAM) and semiconductor read only memory (ROM).
  • the computer module 1301 also includes an number of input/output (I/O) interfaces including: an audio-video interface 1307 that couples to the video display 1314, loudspeakers 1317 and microphone 1380; an I/O interface 1313 that couples to the keyboard 1302, mouse 1303, scanner 1326, camera 1327 and optionally a joystick or other human interface device (not illustrated); and an interface 1308 for the external modem 1316 and printer 1315.
  • the modem 1316 may be incorporated within the computer module 1301, for example within the interface 1308.
  • the computer module 1301 also has a local network interface 1311, which permits coupling of the computer system 1300 via a connection 1323 to a local-area communications network 1322, known as a Local Area Network (LAN).
  • LAN Local Area Network
  • the local communications network 1322 may also couple to the wide network 1320 via a connection 1324, which would typically include a so-called “firewall” device or device of similar functionality.
  • the local network interface 1311 may comprise an Ethernet circuit card, a Bluetooth® wireless arrangement or an IEEE 802.11 wireless arrangement; however, numerous other types of interfaces may be practiced for the interface 1311.
  • the I/O interfaces 1308 and 1313 may afford either or both of serial and parallel connectivity, the former typically being implemented according to the Universal Serial Bus (USB) standards and having corresponding USB connectors (not illustrated).
  • Storage devices 1309 are provided and typically include a hard disk drive (HDD) 1310. Other storage devices such as secured cloud storage, a floppy disk drive and a magnetic tape drive (not illustrated) may also be used.
  • An optical disk drive 1312 is typically provided to act as a nonvolatile source of data.
  • Portable memory devices such optical disks (e.g., CD-ROM, DVD, Blu-ray DiscTM), USB-RAM, portable, external hard drives, and floppy disks, for example, may be used as appropriate sources of data to the system 1300.
  • the components 1305 to 1313 of the computer module 1301 typically communicate via an interconnected bus 1304 and in a manner that results in a conventional mode of operation of the computer system 1300 known to those in the relevant art.
  • the processor 1305 is coupled to the system bus 1304 using a connection 1318.
  • the memory 1306 and optical disk drive 1312 are coupled to the system bus 1304 by connections 1319.
  • Examples of computers on which the described arrangements can be practised include IBM-PC’s and compatibles, Sun Sparcstations, Apple MacTM or like computer systems.
  • the methods described in relation to Figs. 2 to 4 are implemented using the computer system 1300 may be implemented as one or more software application programs 1333 executable within the computer system 1300.
  • the steps of the methods described in relation to Figs. 2 to 4 are effected by instructions 1331 (see Fig. 6B) in the software 1333 that are carried out within the computer system 1300.
  • the software instructions 1331 may be formed as one or more code modules, each for performing one or more particular tasks.
  • the software may also be divided into two separate parts, in which a first part and the corresponding code modules perform the simulation and analysis methods and a second part and the corresponding code modules manage a user interface between the first part and the user.
  • the software may be stored in a computer readable medium, including the storage devices described below, for example.
  • the software is loaded into the computer system 1300 from the computer readable medium, and then executed by the computer system 1300.
  • a computer readable medium having such software or computer program recorded on the computer readable medium is a computer program product.
  • the use of the computer program product in the computer system 1300 preferably effects an advantageous apparatus for modelling model channels that have been joined through surgical anastomosis.
  • the software 1333 is typically stored in the HDD 1310 or the memory 1306.
  • the software is loaded into the computer system 1300 from a computer readable medium, and executed by the computer system 1300.
  • the software 1333 may be stored on an optically readable disk storage medium (e.g., CD-ROM) 1325 that is read by the optical disk drive 1312.
  • a computer readable medium having such software or computer program recorded on it is a computer program product.
  • the use of the computer program product in the computer system 1300 preferably effects an apparatus for modelling model channels that have been joined through surgical anastomosis.
  • the application programs 1333 may be supplied to the user encoded on one or more CD-ROMs 1325 and read via the corresponding drive 1312, or alternatively may be read by the user from the networks 1320 or 1322. Still further, the software can also be loaded into the computer system 1300 from other computer readable media.
  • Computer readable storage media refers to any non-transitory tangible storage medium that provides recorded instructions and/or data to the computer system 1300 for execution and/or processing.
  • Examples of such storage media include floppy disks, magnetic tape, CD-ROM, DVD, Blu-rayTM Disc, a hard disk drive, a ROM or integrated circuit, USB memory, a magneto-optical disk, or a computer readable card such as a PCMCIA card and the like, whether or not such devices are internal or external of the computer module 1301.
  • Examples of transitory or non-tangible computer readable transmission media that may also participate in the provision of software, application programs, instructions and/or data to the computer module 1301 include radio or infra-red transmission channels as well as a network connection to another computer or networked device, and the Internet or Intranets including e-mail transmissions and information recorded on Websites and the like.
  • GUIs graphical user interfaces
  • a user of the computer system 1300 and the application may manipulate the interface in a functionally adaptable manner to provide controlling commands and/or input to the applications associated with the GUI(s).
  • Other forms of functionally adaptable user interfaces may also be implemented, such as an audio interface utilizing speech prompts output via the loudspeakers 1317 and user voice commands input via the microphone 1380.
  • Fig. 6B is a detailed schematic block diagram of the processor 1305 and a “memory” 1334.
  • the memory 1334 represents a logical aggregation of all the memory modules (including the HDD 1309 and semiconductor memory 1306) that can be accessed by the computer module 1301 in Fig. 6A.
  • a power-on self-test (POST) program 1350 executes.
  • the POST program 1350 is typically stored in a ROM 1349 of the semiconductor memory 1306 of Fig. 6A.
  • a hardware device such as the ROM 1349 storing software is sometimes referred to as firmware.
  • the POST program 1350 examines hardware within the computer module 1301 to ensure proper functioning and typically checks the processor 1305, the memory 1334 (1309, 1306), and a basic input-output systems software (BIOS) module 1351, also typically stored in the ROM 1349, for correct operation. Once the POST program 1350 has run successfully, the BIOS 1351 activates the hard disk drive 1310 of Fig. 6A.
  • BIOS basic input-output systems software
  • Activation of the hard disk drive 1310 causes a bootstrap loader program 1352 that is resident on the hard disk drive 1310 to execute via the processor 1305.
  • the operating system 1353 is a system level application, executable by the processor 1305, to fulfil various high level functions, including processor management, memory management, device management, storage management, software application interface, and generic user interface.
  • the operating system 1353 manages the memory 1334 (1309, 1306) to ensure that each process or application running on the computer module 1301 has sufficient memory in which to execute without colliding with memory allocated to another process.
  • the different types of memory available in the system 1300 of Fig. 6A must be used properly so that each process can run effectively. Accordingly, the aggregated memory 1334 is not intended to illustrate how particular segments of memory are allocated (unless otherwise stated), but rather to provide a general view of the memory accessible by the computer system 1300 and how such is used.
  • the processor 1305 includes a number of functional modules including a control unit 1339, an arithmetic logic unit (ALU) 1340, and a local or internal memory 1348, sometimes called a cache memory.
  • the cache memory 1348 typically includes a number of storage registers 1344 - 1346 in a register section.
  • One or more internal busses 1341 functionally interconnect these functional modules.
  • the processor 1305 typically also has one or more interfaces 1342 for communicating with external devices via the system bus 1304, using a connection 1318.
  • the memory 1334 is coupled to the bus 1304 using a connection 1319.
  • the application program 1333 includes a sequence of instructions 1331 that may include conditional branch and loop instructions.
  • the program 1333 may also include data 1332 which is used in execution of the program 1333.
  • the instructions 1331 and the data 1332 are stored in memory locations 1328, 1329, 1330 and 1335, 1336, 1337, respectively.
  • a particular instruction may be stored in a single memory location as depicted by the instruction shown in the memory location 1330.
  • an instruction may be segmented into a number of parts each of which is stored in a separate memory location, as depicted by the instruction segments shown in the memory locations 1328 and 1329.
  • the processor 1305 is given a set of instructions which are executed therein.
  • the processor 1305 waits for a subsequent input, to which the processor 1305 reacts to by executing another set of instructions.
  • Each input may be provided from one or more of a number of sources, including data generated by one or more of the input devices 1302, 1303, data received from an external source across one of the networks 1320, 1302, data retrieved from one of the storage devices 1306, 1309 or data retrieved from a storage medium 1325 inserted into the corresponding reader 1312, all depicted in Fig. 6A.
  • the execution of a set of the instructions may in some cases result in output of data. Execution may also involve storing data or variables to the memory 1334.
  • the disclosed modelling of model channels arrangements use input variables 1354, which are stored in the memory 1334 in corresponding memory locations 1355, 1356, 1357.
  • the modelling of model channels arrangements produce output variables 1361 , which are stored in the memory 1334 in corresponding memory locations 1362, 1363, 1364.
  • Intermediate variables 1358 may be stored in memory locations 1359, 1360, 1366 and 1367.
  • each fetch, decode, and execute cycle comprises:
  • a fetch operation which fetches or reads an instruction 1331 from a memory location 1328, 1329, 1330;
  • a further fetch, decode, and execute cycle for the next instruction may be executed.
  • a store cycle may be performed by which the control unit 1339 stores or writes a value to a memory location 1332.
  • Each step or sub-process in the processes of Figs. 2 to 4 is associated with one or more segments of the program 1333 and is performed by the register section 1344, 1345, 1347, the ALU 1340, and the control unit 1339 in the processor 1305 working together to perform the fetch, decode, and execute cycles for every instruction in the instruction set for the noted segments of the program 1333.
  • the method described in relation to Figs. 2 to 4 may alternatively be implemented in dedicated hardware such as one or more integrated circuits performing the functions or sub functions of modelling the model channels.
  • dedicated hardware may include graphic processors, digital signal processors, or one or more microprocessors and associated memories.
  • the word “comprising” means “including principally but not necessarily solely” or “having” or “including”, and not “consisting only of’. Variations of the word “comprising”, such as “comprise” and “comprises” have correspondingly varied meanings.

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Abstract

La présente divulgation concerne un procédé de modélisation de parties internes d'une anastomose de canaux d'un modèle. Les canaux du modèle comprennent un canal natif du modèle et un canal de greffe du modèle. Le procédé comprend la réception d'un ensemble d'images des canaux du modèle ; la réception de paramètres d'identification d'entrée relatifs aux canaux du modèle ; la segmentation des canaux du modèle sur la base des paramètres identifiés ; la génération d'un maillage de mécanique des fluides numérique sur les canaux du modèle segmentés ; et la simulation de la mécanique des fluides numérique des canaux du modèle à l'aide du maillage de mécanique des fluides numérique.
PCT/AU2023/051159 2022-11-18 2023-11-15 Procédé de modélisation d'une anastomose de canaux WO2024103115A1 (fr)

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AU2022903481A AU2022903481A0 (en) 2022-11-18 Method of modelling anastomosis of channels
AU2022903481 2022-11-18

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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2017058351A1 (fr) * 2015-10-02 2017-04-06 Heartflow, Inc. Système et procédé de diagnostic et évaluation d'une maladie cardio-vasculaire par comparaison de la capacité d'apport artériel avec la demande d'organes terminaux
US9814531B2 (en) * 2011-08-26 2017-11-14 EBM Corporation System for diagnosing bloodflow characteristics, method thereof, and computer software program
JP2020076967A (ja) * 2018-10-03 2020-05-21 イービーエム株式会社 手術手技訓練用の人工臓器モデル、その人工臓器モデルの製造方法、及びその人工臓器モデルを用いた手術手技訓練方法
WO2021099245A1 (fr) * 2019-11-20 2021-05-27 Technische Universität Hamburg Modèle de formation médicale comprenant des modèles de vaisseaux personnalisables fabriqués de manière additive
WO2021195044A1 (fr) * 2020-03-23 2021-09-30 The Johns Hopkins University Procédés, systèmes et aspects associés pour l'optimisation et la planification d'une chirurgie cardiaque

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9814531B2 (en) * 2011-08-26 2017-11-14 EBM Corporation System for diagnosing bloodflow characteristics, method thereof, and computer software program
WO2017058351A1 (fr) * 2015-10-02 2017-04-06 Heartflow, Inc. Système et procédé de diagnostic et évaluation d'une maladie cardio-vasculaire par comparaison de la capacité d'apport artériel avec la demande d'organes terminaux
JP2020076967A (ja) * 2018-10-03 2020-05-21 イービーエム株式会社 手術手技訓練用の人工臓器モデル、その人工臓器モデルの製造方法、及びその人工臓器モデルを用いた手術手技訓練方法
WO2021099245A1 (fr) * 2019-11-20 2021-05-27 Technische Universität Hamburg Modèle de formation médicale comprenant des modèles de vaisseaux personnalisables fabriqués de manière additive
WO2021195044A1 (fr) * 2020-03-23 2021-09-30 The Johns Hopkins University Procédés, systèmes et aspects associés pour l'optimisation et la planification d'une chirurgie cardiaque

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