CN116672078A - Method and device for determining operation plan - Google Patents
Method and device for determining operation plan Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 38
- 210000004204 blood vessel Anatomy 0.000 claims abstract description 185
- 230000002792 vascular Effects 0.000 claims abstract description 88
- 230000002980 postoperative effect Effects 0.000 claims abstract description 44
- 230000000877 morphologic effect Effects 0.000 claims description 16
- 230000002308 calcification Effects 0.000 claims description 14
- 208000031481 Pathologic Constriction Diseases 0.000 claims description 8
- 239000000463 material Substances 0.000 claims description 8
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- 238000012986 modification Methods 0.000 claims description 8
- 230000036262 stenosis Effects 0.000 claims description 8
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- 238000010801 machine learning Methods 0.000 claims description 7
- 238000004590 computer program Methods 0.000 claims description 4
- 238000010276 construction Methods 0.000 claims description 4
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- 230000003993 interaction Effects 0.000 abstract description 6
- 238000004088 simulation Methods 0.000 abstract description 6
- 238000004891 communication Methods 0.000 description 6
- 230000006870 function Effects 0.000 description 4
- 238000001356 surgical procedure Methods 0.000 description 4
- 230000008878 coupling Effects 0.000 description 3
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- 239000003814 drug Substances 0.000 description 2
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- 229910001000 nickel titanium Inorganic materials 0.000 description 2
- 238000006467 substitution reaction Methods 0.000 description 2
- HZEWFHLRYVTOIW-UHFFFAOYSA-N [Ti].[Ni] Chemical compound [Ti].[Ni] HZEWFHLRYVTOIW-UHFFFAOYSA-N 0.000 description 1
- 229910045601 alloy Inorganic materials 0.000 description 1
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- 239000000788 chromium alloy Substances 0.000 description 1
- 210000004351 coronary vessel Anatomy 0.000 description 1
- 229940079593 drug Drugs 0.000 description 1
- 238000002608 intravascular ultrasound Methods 0.000 description 1
- 238000003062 neural network model Methods 0.000 description 1
- HLXZNVUGXRDIFK-UHFFFAOYSA-N nickel titanium Chemical compound [Ti].[Ti].[Ti].[Ti].[Ti].[Ti].[Ti].[Ti].[Ti].[Ti].[Ti].[Ni].[Ni].[Ni].[Ni].[Ni].[Ni].[Ni].[Ni].[Ni].[Ni].[Ni].[Ni].[Ni].[Ni] HLXZNVUGXRDIFK-UHFFFAOYSA-N 0.000 description 1
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- A61B34/10—Computer-aided planning, simulation or modelling of surgical operations
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- A—HUMAN NECESSITIES
- 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
- A61B2034/101—Computer-aided simulation of surgical operations
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Abstract
The application provides a method and a device for determining a surgical plan, comprising the following steps: acquiring a medical image of a target blood vessel region; performing plaque analysis on a target blood vessel region based on medical images of the target blood vessel region to obtain blood vessel plaque parameters; constructing an initial vessel model of the target vessel region based on the medical image; predicting a post-operation blood vessel model after different surgical consumables are placed according to the blood vessel plaque parameters, the surgical consumable parameters and the initial blood vessel model; and determining a surgical plan according to the postoperative vessel model after placing different surgical consumables. In this way, according to the vascular plaque parameters, the surgical consumable parameters and the initial vascular model, the postoperative vascular model after different surgical consumables are placed is predicted, the interaction between the vascular plaque and the surgical consumable is considered, the reality degree of the surgical plan simulation can be improved, and the surgical implementation is better guided.
Description
Technical Field
The application relates to the technical field of medical treatment, in particular to a method and a device for determining a surgical plan.
Background
Surgical planning (PCI Planner) refers to simulating the procedure of surgery, such as simulating the morphology of a vessel after stent placement, using software to predict the morphology of the vessel after surgery. However, current surgical planning considerations are simple, often assuming that the vessel is sufficiently dilated. For example, a physician places a 3mm stent, and the surgical plan assumes that the vessel can return to normal vessel diameter, or that the vessel returns to 3mm vessel diameter. However, in practice, there are often cases of poor adhesion in clinic, one of the reasons is that lesions in blood vessels affect the expansion of blood vessels, obstruct the expansion of blood vessels, and the blood vessels cannot be really restored to the caliber of the corresponding size of the stent. Therefore, the existing operation plan is disjointed with the actual operation, and the guiding function is lost.
Disclosure of Invention
Accordingly, the present application is directed to a method and apparatus for determining a surgical plan, which predicts a post-operation blood vessel model after different surgical consumables are placed according to a blood vessel plaque parameter, a surgical consumable parameter and an initial blood vessel model, considers the interaction between the blood vessel plaque and the surgical consumable, and can improve the reality of the surgical plan simulation, thereby better guiding the surgical implementation.
The embodiment of the application provides a method for determining a surgical plan, which comprises the following steps:
acquiring a medical image of a target blood vessel region;
performing plaque analysis on a target blood vessel region based on medical images of the target blood vessel region to obtain blood vessel plaque parameters;
constructing an initial vessel model of the target vessel region based on the medical image;
predicting a post-operation blood vessel model after different surgical consumables are placed according to the blood vessel plaque parameters, the surgical consumable parameters and the initial blood vessel model;
and determining a surgical plan according to the postoperative vessel model after placing different surgical consumables.
Further, predicting a post-operation blood vessel model after placing different surgical consumables according to the blood vessel plaque parameter, the surgical consumable parameter and the initial blood vessel model, including:
predicting the deformation parameters of the blood vessel after different surgical consumables are placed according to the blood vessel plaque parameters and the surgical consumable parameters; wherein the vascular plaque parameter comprises at least one of: plaque type, plaque location, plaque stenosis, blood vessel wall thickness, calcification score, plaque angle, plaque volume, plaque thickness, reconstitution index, fat attenuation index, whether positive reconstitution, napkin ring sign, punctual calcification, low density plaque; the surgical consumable parameters include at least one of: the type, material properties and mechanical characteristics of the surgical consumable;
and correcting the initial blood vessel model based on the blood vessel deformation parameters after the different surgical consumables are placed, so as to obtain a postoperative blood vessel model after the different surgical consumables are placed.
Further, predicting the deformation parameters of the blood vessel after placing different surgical consumables according to the plaque parameters and the surgical consumable parameters, including:
and predicting the vascular deformation parameters after different surgical consumables are placed by using a pre-trained machine learning model or a pre-fitted specific relational expression according to the vascular plaque parameters and the surgical consumable parameters.
Further, according to the vascular plaque parameter and the surgical consumable parameter, predicting vascular deformation parameters after placing different surgical consumables, further comprising:
selecting a plurality of cross sections of the blood vessel in the target blood vessel area aiming at any surgical consumable, and selecting a plurality of control points on each cross section;
predicting a vascular deformation parameter of the surgical consumable after the surgical consumable is placed at the control point according to the surgical consumable parameter of the surgical consumable and the vascular plaque parameter corresponding to the control point for each control point in a plurality of control points on any cross section;
and interpolating to obtain the vascular deformation parameters of the cross section after the surgical consumable is placed based on the vascular deformation parameters of the control points.
Further, based on the vessel deformation parameters after placing different surgical consumables, correcting the initial vessel model to obtain a post-operation vessel model after placing different surgical consumables, including:
for each surgical consumable and each cross section, adding and deleting vascular pixels or modifying the diameter of the vascular profile at the corresponding position of the cross section in the initial vascular model according to the vascular deformation parameters of the cross section after the surgical consumable is placed;
and obtaining a post-operation blood vessel model after placing the surgical consumable according to the modification result of each cross section in the initial blood vessel model and the initial blood vessel model.
Further, determining a surgical plan according to a post-operative vascular model after placement of different surgical consumables, comprising:
according to the postoperative blood vessel model after placing different surgical consumables, performing functional analysis and/or morphological analysis to obtain functional parameters and/or morphological parameters of the postoperative blood vessel;
and selecting surgical consumables according to the functional parameters and/or morphological parameters of the postoperative blood vessel to determine a surgical plan.
The embodiment of the application also provides a device for determining the operation plan, which comprises the following steps:
the acquisition module is used for acquiring medical images of the target blood vessel region;
the analysis module is used for carrying out plaque analysis on the target blood vessel region based on the medical image of the target blood vessel region to obtain blood vessel plaque parameters;
the construction module is used for constructing an initial blood vessel model of the target blood vessel area based on the medical image;
the prediction module is used for predicting a post-operation blood vessel model after different surgical consumables are placed according to the blood vessel plaque parameters, the surgical consumable parameters and the initial blood vessel model;
the determining module is used for determining the operation plan according to the postoperative vessel model after different operation consumables are placed.
Further, when the prediction module is used for predicting a post-operation blood vessel model after different surgical consumables are placed according to the blood vessel plaque parameter, the surgical consumable parameter and the initial blood vessel model, the prediction module is used for:
predicting the deformation parameters of the blood vessel after different surgical consumables are placed according to the blood vessel plaque parameters and the surgical consumable parameters; wherein the vascular plaque parameter comprises at least one of: plaque type, plaque location, plaque stenosis, blood vessel wall thickness, calcification score, plaque angle, plaque volume, plaque thickness, reconstitution index, fat attenuation index, whether positive reconstitution, napkin ring sign, punctual calcification, low density plaque; the surgical consumable parameters include at least one of: the type, material properties and mechanical characteristics of the surgical consumable;
and correcting the initial blood vessel model based on the blood vessel deformation parameters after the different surgical consumables are placed, so as to obtain a postoperative blood vessel model after the different surgical consumables are placed.
The embodiment of the application also provides electronic equipment, which comprises: a processor, a memory and a bus, the memory storing machine-readable instructions executable by the processor, the processor and the memory in communication over the bus when the electronic device is operating, the machine-readable instructions when executed by the processor performing the steps of a method of determining a surgical plan as described above.
Embodiments of the present application also provide a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of a method of determining a surgical plan as described above.
According to the method and the device for determining the operation plan, provided by the embodiment of the application, the postoperative vessel model after different operation consumables are placed is predicted according to the vessel plaque parameters, the operation consumable parameters and the initial vessel model, the interaction between the vessel plaque and the operation consumable is considered, the actual degree of the operation plan simulation can be improved, and the operation implementation is better guided.
In order to make the above objects, features and advantages of the present application more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 illustrates a flow chart of a method of determining a surgical plan provided by an embodiment of the present application;
FIG. 2 is a cross-sectional view of a blood vessel before and after expansion of a stent according to an embodiment of the present application;
FIG. 3 is a schematic view showing the construction of an apparatus for determining a surgical plan according to an embodiment of the present application;
fig. 4 shows a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. The components of the embodiments of the present application generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the application, as presented in the figures, is not intended to limit the scope of the application, as claimed, but is merely representative of selected embodiments of the application. Based on the embodiments of the present application, every other embodiment obtained by a person skilled in the art without making any inventive effort falls within the scope of protection of the present application.
It has been found that surgical planning (PCI Planner) refers to the use of software to simulate the procedure performed by surgery, such as simulating the morphology of a vessel after stent placement, and thereby predicting the morphology of the vessel after surgery. However, current surgical planning considerations are simple, often assuming that the vessel is sufficiently dilated. For example, a physician places a 3mm stent, and the surgical plan assumes that the vessel can return to normal vessel diameter, or that the vessel returns to 3mm vessel diameter. However, in practice, there are often cases of poor adhesion in clinic, one of the reasons is that lesions in blood vessels affect the expansion of blood vessels, obstruct the expansion of blood vessels, and the blood vessels cannot be really restored to the caliber of the corresponding size of the stent. Therefore, the existing operation plan is disjointed with the actual operation, and the guiding function is lost.
Based on the above, the embodiment of the application provides a method and a device for determining a surgical plan, which predict a post-operation blood vessel model after different surgical consumables are placed according to blood vessel plaque parameters, surgical consumable parameters and an initial blood vessel model, consider the interaction between the blood vessel plaque and the surgical consumable, improve the reality degree of the surgical plan simulation, and better guide the surgical implementation.
Referring to fig. 1, fig. 1 is a flowchart of a method for determining a surgical plan according to an embodiment of the present application. As shown in fig. 1, a method provided by an embodiment of the present application includes:
s101, acquiring a medical image of a target blood vessel region.
In this step, the target vessel region may be a coronary vessel region, and the medical image may be acquired by the image acquisition apparatus. The medical image may be DICOM (Digital Imaging and Communications in Medicine), i.e. digital imaging and communication in medicine, is an international standard for medical images and related information, defining a medical image format with quality that satisfies clinical requirements and that can be used for data exchange. Medical images for which plaque analysis may follow-up include, but are not limited to: CTA, IVUS, OCT; medical images for which a vascular model may be subsequently constructed include, but are not limited to: CTA, MRI, DSA.
S102, performing plaque analysis on a target blood vessel region based on medical images of the target blood vessel region to obtain blood vessel plaque parameters.
In practice, plaque analysis may be performed based on medical images of the target vessel region using methods known in the art to obtain vessel plaque parameters. The plaque here includes calcified plaque, non-calcified plaque and mixed plaque. Illustratively, taking CTA as an example, the nature of plaque may be determined from the gray value of the medical image taken. Vascular plaque parameters include, but are not limited to: plaque type, plaque location, plaque stenosis, blood vessel wall thickness, calcification score, plaque angle, plaque volume, plaque thickness, reconstitution index, fat attenuation index, whether positive reconstitution, napkin ring sign, punctual calcification, low density plaque, etc.
S103, constructing an initial blood vessel model of the target blood vessel region based on the medical image.
In practice, the initial vessel model may be constructed based on medical images of the target vessel region using prior art techniques. Taking CTA as an example, the gray value of a blood vessel region is obviously different from that of a non-blood vessel region, and the blood vessel can be judged according to the gray value of a photographed medical image, so that the blood vessel is segmented, and then a blood vessel model is established. The vessel model herein mainly refers to a geometric model, including a single vessel or a plurality of vessels.
S104, predicting a post-operation blood vessel model after different surgical consumables are placed according to the blood vessel plaque parameters, the surgical consumable parameters and the initial blood vessel model.
Here, the research of the embodiment of the application finds that plaque lesions in the blood vessel have an influence on the expansion of the blood vessel, and the situation of poor adhesion often occurs, so that the blood vessel cannot be really restored to the pipe diameter of the corresponding size of the stent. Therefore, by considering the interaction between the vascular plaque and the surgical consumable, combining the vascular plaque parameter and the surgical consumable parameter, a more accurate post-operative vascular model can be obtained.
In one possible implementation, step S104 may include:
s1041, predicting the deformation parameters of the blood vessel after different surgical consumables are placed according to the blood vessel plaque parameters and the surgical consumable parameters.
Wherein the surgical consumable parameters include at least one of: the type, material properties and mechanical characteristics of the surgical consumable. Types of surgical consumables include, but are not limited to, stents, balloons, and the like; material properties include, but are not limited to, nickel-titanium alloys, cobalt-chromium alloys, and the like; mechanical characteristics include, but are not limited to, stiffness, strength, foreshortening rate, rebound, compliance, fatigue resistance, and the like. Here, the surgical consumable parameters of the different surgical consumables may be determined in advance through experimental determination or acquisition from a manufacturer, or the like.
In the specific implementation, the vascular deformation parameters after different surgical consumables are placed can be predicted by using a pre-trained machine learning model or a pre-fitted specific relational expression according to the vascular plaque parameters and the surgical consumable parameters. Here, a machine learning model may be trained or fitted to a particular relationship based on statistical past clinical actual data. Exemplary, statistics is carried out to obtain actual post-operation vascular medical images obtained after operation under different vascular plaque parameters and operation consumable parameters; comparing the actual postoperative vascular medical image with the preoperative vascular medical image to determine vascular deformation parameters; the parameters of vascular plaque and surgical consumable materials are used as input, the parameters of vascular deformation are used as output, and a neural network model is trained or a specific relational expression is fitted.
Referring to fig. 2, fig. 2 is a cross-sectional view of a blood vessel before and after expansion of a stent according to an embodiment of the present application. As shown in fig. 2, in one possible implementation, step S1041 may include: selecting a plurality of cross sections of the blood vessel in the target blood vessel area aiming at any surgical consumable, and selecting a plurality of control points on each cross section; predicting a vascular deformation parameter of the surgical consumable after the surgical consumable is placed at the control point according to the surgical consumable parameter of the surgical consumable and the vascular plaque parameter corresponding to the control point for each control point in a plurality of control points on any cross section; and interpolating to obtain the vascular deformation parameters of the cross section after the surgical consumable is placed based on the vascular deformation parameters of the control points.
In the implementation, for each control point of a plurality of control points on any cross section, the surgical consumable parameters of the surgical consumable and the vascular plaque parameters corresponding to the control point can be input into a machine learning model or a specific relation, and the vascular deformation parameters output by the machine learning model or the specific relation are determined as the vascular deformation parameters of the control point after the surgical consumable is placed. The deformation degree of the control point is represented by the deformation parameters of the blood vessel, and the deformation degree can be diameter, diameter ratio, area and area ratio and the like. The specific relationship can be expressed as:
Δu＝f(x1,x2,x3,...,xn,y1,y2,y3,...,yn)
wherein Deltau represents the vascular deformation parameter of the control point; x1, x2, x3, xn represents the vascular plaque parameter corresponding to the control point; y1, y2, y3,..yn represents a surgical consumable parameter.
Further, by way of example, the vessel deformation parameter is diameter, the vessel plaque parameter is vessel wall thickness and calcification angle, the surgical consumable parameter is the stiffness of the nitinol stent, and the following formula form of a specific relationship is given:
diameter expansion distance Δu=a vessel wall thickness+b calcification angle+c stent stiffness+d
Wherein a, b, c and d are parameters obtained by fitting.
Through the formula, the vascular deformation parameters of each control point on the vascular cross section can be calculated, and further the vascular deformation parameters of the vascular cross section after the surgical consumable is placed can be obtained through spline curve interpolation. Therefore, the process does not need finite element simulation or other complex analysis, the calculation time is very short, and the blood vessel morphology after stent expansion can be accurately and rapidly determined.
S1042, revising the initial blood vessel model based on the blood vessel deformation parameters after placing different surgical consumables, and obtaining the postoperative blood vessel model after placing different surgical consumables.
In one possible implementation, step S1042 may include: for each surgical consumable and each cross section, adding and deleting vascular pixels or modifying the diameter of the vascular profile at the corresponding position of the cross section in the initial vascular model according to the vascular deformation parameters of the cross section after the surgical consumable is placed; and obtaining a post-operation blood vessel model after placing the surgical consumable according to the modification result of each cross section in the initial blood vessel model and the initial blood vessel model.
Here, the initial vessel model may be modified to be converted into a post-operative vessel model after placement of the surgical consumable according to vessel deformation parameters of each cross section after placement of the surgical consumable. The vessel model can be composed of pixel points or can be formed by drawing a smooth outline. For a blood vessel model composed of pixel points, the modification to the blood vessel model can be adding or deleting the pixel points corresponding to the blood vessel; for a smooth contoured vessel model, a modification to it may be to change the diameter of the partial contour, thereby changing the model. And obtaining a post-operation blood vessel model of the whole blood vessel after the surgical consumable is placed in an interpolation mode and the like according to the relative position of each cross section in the initial blood vessel model after the modification result of each cross section in the initial blood vessel model is obtained.
S105, determining a surgical plan according to the postoperative vessel model after placing different surgical consumables.
In the step, the postoperative effect of different surgical consumables can be evaluated by comparing postoperative blood vessel models after different surgical consumables are placed and comparing subsequent results on the basis of the postoperative blood vessel models, and then an appropriate surgical plan is comprehensively determined by combining other conditions of a patient, so that the surgical implementation is better guided.
In one possible implementation, step S105 may include: according to the postoperative blood vessel model after placing different surgical consumables, performing functional analysis and/or morphological analysis to obtain functional parameters and/or morphological parameters of the postoperative blood vessel; and selecting surgical consumables according to the functional parameters and/or morphological parameters of the postoperative blood vessel to determine a surgical plan.
Among the functionally related parameters include, but are not limited to: parameters such as FFR, IMR, blood flow velocity, pressure, WSS, APS, residual FFR, TIMI rating, etc.; morphological parameters include, but are not limited to: parameters such as stenosis degree, diameter, stenosis area and the like after vascular operation. According to the functional parameters and/or morphological parameters of the blood vessel after operation, and comparing the functional parameters and/or morphological parameters with the functional parameters and/or morphological parameters before operation, thereby selecting surgical consumables and evaluating the advantages and disadvantages of the surgical scheme.
Further, after the postoperative model is obtained, the model can be subjected to visual modeling, the postoperative vascular morphology is displayed, the postoperative effect corresponding to the operation scheme is conveniently checked, doctors are helped to finish operations better, and the operation efficiency is improved.
The method for determining the operation plan provided by the embodiment of the application comprises the following steps: acquiring a medical image of a target blood vessel region; performing plaque analysis on a target blood vessel region based on medical images of the target blood vessel region to obtain blood vessel plaque parameters; constructing an initial vessel model of the target vessel region based on the medical image; predicting a post-operation blood vessel model after different surgical consumables are placed according to the blood vessel plaque parameters, the surgical consumable parameters and the initial blood vessel model; and determining a surgical plan according to the postoperative vessel model after placing different surgical consumables.
In this way, according to the vascular plaque parameters, the surgical consumable parameters and the initial vascular model, the postoperative vascular model after different surgical consumables are placed is predicted, the interaction between the vascular plaque and the surgical consumable is considered, the reality degree of the surgical plan simulation can be improved, and the surgical implementation is better guided.
Referring to fig. 3, fig. 3 is a schematic structural diagram of an apparatus for determining a surgical plan according to an embodiment of the application. As shown in fig. 3, the apparatus 300 includes:
an acquisition module 310, configured to acquire a medical image of a target blood vessel region;
an analysis module 320, configured to perform plaque analysis on a target blood vessel region based on a medical image of the target blood vessel region, to obtain a blood vessel plaque parameter;
a construction module 330, configured to construct an initial vessel model of the target vessel region based on the medical image;
a prediction module 340, configured to predict a post-operation blood vessel model after different surgical consumables are placed according to the blood vessel plaque parameter, the surgical consumable parameter and the initial blood vessel model;
a determining module 350, configured to determine a surgical plan according to the post-operative blood vessel model after placing different surgical consumables.
Further, when the prediction module 340 is configured to predict a post-operation blood vessel model after placing different surgical consumables according to the blood vessel plaque parameter, the surgical consumable parameter and the initial blood vessel model, the prediction module 340 is configured to:
predicting the deformation parameters of the blood vessel after different surgical consumables are placed according to the blood vessel plaque parameters and the surgical consumable parameters; wherein the vascular plaque parameter comprises at least one of: plaque type, plaque location, plaque stenosis, blood vessel wall thickness, calcification score, plaque angle, plaque volume, plaque thickness, reconstitution index, fat attenuation index, whether positive reconstitution, napkin ring sign, punctual calcification, low density plaque; the surgical consumable parameters include at least one of: the type, material properties and mechanical characteristics of the surgical consumable;
and correcting the initial blood vessel model based on the blood vessel deformation parameters after the different surgical consumables are placed, so as to obtain a postoperative blood vessel model after the different surgical consumables are placed.
Further, when the prediction module 340 is configured to predict the deformation parameters of the blood vessel after placing different surgical consumables according to the plaque parameters and the surgical consumable parameters, the prediction module 340 is configured to:
and predicting the vascular deformation parameters after different surgical consumables are placed by using a pre-trained machine learning model or a pre-fitted specific relational expression according to the vascular plaque parameters and the surgical consumable parameters.
Further, when the prediction module 340 is configured to predict the deformation parameters of the blood vessel after the placement of different surgical consumables according to the plaque parameters and the surgical consumable parameters, the prediction module 340 is further configured to:
selecting a plurality of cross sections of the blood vessel in the target blood vessel area aiming at any surgical consumable, and selecting a plurality of control points on each cross section;
predicting a vascular deformation parameter of the surgical consumable after the surgical consumable is placed at the control point according to the surgical consumable parameter of the surgical consumable and the vascular plaque parameter corresponding to the control point for each control point in a plurality of control points on any cross section;
and interpolating to obtain the vascular deformation parameters of the cross section after the surgical consumable is placed based on the vascular deformation parameters of the control points.
Further, when the prediction module 340 is configured to correct the initial blood vessel model based on the blood vessel deformation parameters after the placement of the different surgical consumables, and obtain the post-operation blood vessel model after the placement of the different surgical consumables, the prediction module 340 is configured to:
for each surgical consumable and each cross section, adding and deleting vascular pixels or modifying the diameter of the vascular profile at the corresponding position of the cross section in the initial vascular model according to the vascular deformation parameters of the cross section after the surgical consumable is placed;
and obtaining a post-operation blood vessel model after placing the surgical consumable according to the modification result of each cross section in the initial blood vessel model and the initial blood vessel model.
Further, when the determining module 350 is configured to determine the surgical plan according to the post-operative blood vessel model after placing different surgical consumables, the determining module 350 is configured to:
according to the postoperative blood vessel model after placing different surgical consumables, performing functional analysis and/or morphological analysis to obtain functional parameters and/or morphological parameters of the postoperative blood vessel;
and selecting surgical consumables according to the functional parameters and/or morphological parameters of the postoperative blood vessel to determine a surgical plan.
Referring to fig. 4, fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the application. As shown in fig. 4, the electronic device 400 includes a processor 410, a memory 420, and a bus 430.
The memory 420 stores machine-readable instructions executable by the processor 410, and when the electronic device 400 is running, the processor 410 communicates with the memory 420 through the bus 430, and when the machine-readable instructions are executed by the processor 410, the steps of a method for determining a surgical plan in one of the method embodiments shown in fig. 1 can be executed, and a specific implementation is referred to the method embodiments and is not described herein.
The embodiment of the present application further provides a computer readable storage medium, where a computer program is stored, where the computer program when executed by a processor may perform the steps of a method for determining a surgical plan in the method embodiment shown in fig. 1, and the specific implementation manner may refer to the method embodiment and will not be described herein.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.
In the several embodiments provided by the present application, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. The above-described apparatus embodiments are merely illustrative, for example, the division of the units is merely a logical function division, and there may be other manners of division in actual implementation, and for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some communication interface, device or unit indirect coupling or communication connection, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer readable storage medium executable by a processor. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Finally, it should be noted that: the above examples are only specific embodiments of the present application, and are not intended to limit the scope of the present application, but it should be understood by those skilled in the art that the present application is not limited thereto, and that the present application is described in detail with reference to the foregoing examples: any person skilled in the art may modify or easily conceive of the technical solution described in the foregoing embodiments, or perform equivalent substitution of some of the technical features, while remaining within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application. Therefore, the protection scope of the application is subject to the protection scope of the claims.
Claims (10)
1. A method of determining a surgical plan, the method comprising:
acquiring a medical image of a target blood vessel region;
performing plaque analysis on a target blood vessel region based on medical images of the target blood vessel region to obtain blood vessel plaque parameters;
constructing an initial vessel model of the target vessel region based on the medical image;
predicting a post-operation blood vessel model after different surgical consumables are placed according to the blood vessel plaque parameters, the surgical consumable parameters and the initial blood vessel model;
and determining a surgical plan according to the postoperative vessel model after placing different surgical consumables.
2. The method of claim 1, wherein predicting a post-operative vascular model after placement of a different surgical consumable based on the vascular plaque parameter, surgical consumable parameter, and the initial vascular model comprises:
predicting the deformation parameters of the blood vessel after different surgical consumables are placed according to the blood vessel plaque parameters and the surgical consumable parameters; wherein the vascular plaque parameter comprises at least one of: plaque type, plaque location, plaque stenosis, blood vessel wall thickness, calcification score, plaque angle, plaque volume, plaque thickness, reconstitution index, fat attenuation index, whether positive reconstitution, napkin ring sign, punctual calcification, low density plaque; the surgical consumable parameters include at least one of: the type, material properties and mechanical characteristics of the surgical consumable;
and correcting the initial blood vessel model based on the blood vessel deformation parameters after the different surgical consumables are placed, so as to obtain a postoperative blood vessel model after the different surgical consumables are placed.
3. The method of claim 2, wherein predicting the vessel deformation parameters after placement of the different surgical consumables based on the vessel plaque parameters and the surgical consumable parameters comprises:
and predicting the vascular deformation parameters after different surgical consumables are placed by using a pre-trained machine learning model or a pre-fitted specific relational expression according to the vascular plaque parameters and the surgical consumable parameters.
4. The method according to claim 2 or 3, wherein predicting the vascular deformation parameters after placing different surgical consumables according to the vascular plaque parameters and the surgical consumable parameters, further comprises:
selecting a plurality of cross sections of the blood vessel in the target blood vessel area aiming at any surgical consumable, and selecting a plurality of control points on each cross section;
predicting a vascular deformation parameter of the surgical consumable after the surgical consumable is placed at the control point according to the surgical consumable parameter of the surgical consumable and the vascular plaque parameter corresponding to the control point for each control point in a plurality of control points on any cross section;
and interpolating to obtain the vascular deformation parameters of the cross section after the surgical consumable is placed based on the vascular deformation parameters of the control points.
5. The method of claim 4, wherein modifying the initial vessel model based on the vessel deformation parameters after placement of the different surgical consumables results in a post-operative vessel model after placement of the different surgical consumables, comprising:
for each surgical consumable and each cross section, adding and deleting vascular pixels or modifying the diameter of the vascular profile at the corresponding position of the cross section in the initial vascular model according to the vascular deformation parameters of the cross section after the surgical consumable is placed;
and obtaining a post-operation blood vessel model after placing the surgical consumable according to the modification result of each cross section in the initial blood vessel model and the initial blood vessel model.
6. The method of claim 1, wherein determining the surgical plan based on the post-operative vascular model after placement of the different surgical consumables comprises:
according to the postoperative blood vessel model after placing different surgical consumables, performing functional analysis and/or morphological analysis to obtain functional parameters and/or morphological parameters of the postoperative blood vessel;
and selecting surgical consumables according to the functional parameters and/or morphological parameters of the postoperative blood vessel to determine a surgical plan.
7. An apparatus for determining a surgical plan, the apparatus comprising:
the acquisition module is used for acquiring medical images of the target blood vessel region;
the analysis module is used for carrying out plaque analysis on the target blood vessel region based on the medical image of the target blood vessel region to obtain blood vessel plaque parameters;
the construction module is used for constructing an initial blood vessel model of the target blood vessel area based on the medical image;
the prediction module is used for predicting a post-operation blood vessel model after different surgical consumables are placed according to the blood vessel plaque parameters, the surgical consumable parameters and the initial blood vessel model;
the determining module is used for determining the operation plan according to the postoperative vessel model after different operation consumables are placed.
8. The apparatus of claim 7, wherein the prediction module, when configured to predict a post-operative vascular model after placement of a different surgical consumable based on the vascular plaque parameter, surgical consumable parameter, and the initial vascular model, is configured to:
predicting the deformation parameters of the blood vessel after different surgical consumables are placed according to the blood vessel plaque parameters and the surgical consumable parameters; wherein the vascular plaque parameter comprises at least one of: plaque type, plaque location, plaque stenosis, blood vessel wall thickness, calcification score, plaque angle, plaque volume, plaque thickness, reconstitution index, fat attenuation index, whether positive reconstitution, napkin ring sign, punctual calcification, low density plaque; the surgical consumable parameters include at least one of: the type, material properties and mechanical characteristics of the surgical consumable;
and correcting the initial blood vessel model based on the blood vessel deformation parameters after the different surgical consumables are placed, so as to obtain a postoperative blood vessel model after the different surgical consumables are placed.
9. An electronic device, comprising: a processor, a memory and a bus, said memory storing machine readable instructions executable by said processor, said processor and said memory communicating via said bus when the electronic device is running, said machine readable instructions when executed by said processor performing the steps of a method of determining a surgical plan as claimed in any one of claims 1 to 6.
10. A computer-readable storage medium, characterized in that it has stored thereon a computer program which, when executed by a processor, performs the steps of a method of determining a surgical plan according to any of claims 1 to 6.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202310806758.3A CN116672078A (en) | 2023-07-03 | 2023-07-03 | Method and device for determining operation plan |
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| CN202310806758.3A CN116672078A (en) | 2023-07-03 | 2023-07-03 | Method and device for determining operation plan |
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