Method for automatically monitoring advancement of guide wire in robotic vascular intervention surgery

Abstract

The present application relates to the field of surgical navigation technology, and in particular, to a method for automatically monitoring the advancement of a guide wire in a robotic vascular intervention surgery. The method comprises: extracting an intervention path from a preoperative CT radiographic image; placing an electromagnetic navigation device in a surgical space, acquiring coordinate values of an experimental model with adhered electromagnetic sensor mark points in a magnetic field space and corresponding coordinate values in an image coordinate space, and calculating a registered transformation matrix; sequentially binding three to five electromagnetic sensors at the front end of the guide wire, and pushing the guide wire to an intervention start point; acquiring, in the process where the guide wire travels to an intervention end point, positions of the electromagnetic sensors at time t using the electromagnetic navigation device, acquiring positions in the image coordinate space on the basis of the registered transformation matrix, fitting the shape of the front end of the guide wire, and displaying in a reconstructed image; and performing the monitoring according to the relationship between relative positions of the intervention path and the electromagnetic sensors.

Description

A method for automatically monitoring guidewire advancement in vascular interventional robotic surgery Technical Field

[0001] The present application relates to the field of surgical navigation technology, and in particular to a method for automatically monitoring the progress of a guidewire in vascular interventional robotic surgery. Background Art

[0002] In some cases, interventional robots not only have good stability, but also can prevent doctors from being exposed to radiation for a long time. When the robot clamps the guidewire and pushes it into the human body, in order to monitor the guidewire's movement status, a large amount of X-rays can be used for imaging. However, because the interventional instrument itself is made of flexible materials and has hysteresis after moving along the blood vessels for a long distance, doctors sometimes find that the guidewire does not show the correct movement trajectory in the X-ray image, and the guidewire movement between two X-ray acquisitions cannot be captured in real time. This brings some challenges to observing the advancement of the guidewire, especially near the bifurcation of the blood vessels. Summary of the Invention

[0003] In response to the defects of the existing technology, in order to better capture the movement of the guidewire, the present application provides an automatic monitoring method for the guidewire's progress in vascular interventional robotic surgery, which can automatically track the movement status of the guidewire in the blood vessel in real time, and provide a progress deviation warning based on the relative position relationship between the front end of the guidewire and the intervention path.

[0004] To achieve the above objectives, this application provides the following solutions:

[0005] A method for automatically monitoring the progress of a guidewire in a vascular interventional robotic surgery includes extracting the intervention path from a preoperative CT angiography image and obtaining the coordinate value P of a discrete center point in the image coordinate system. j and the corresponding vascular radius R j , where j = 1,…, n, n represents the number of center points, P j represents the jth center point position of the intervention path, R j Represents the vascular radius value at the jth center point; Place the electromagnetic navigation device in the surgical space to obtain the experimental model coordinate value U with the electromagnetic sensor marker in the magnetic field space i The coordinate value V of the corresponding image coordinate space i , where i=1,…,w, w represents the number of marking points, U i With V i The positions in space correspond one to one, and the registration transformation matrix T is obtained Mag->Img; 3 to 5 electromagnetic sensors are sequentially attached to the front end of the guidewire, and the interventional robot pushes the guidewire to the intervention starting point; while the interventional robot pushes the guidewire to the intervention end point, the electromagnetic navigation device is used to obtain the electromagnetic sensor position P at time t i,t , i = 1, ..., m, m represents the number of electromagnetic sensors, and the image coordinate space position P` is obtained based on the registration transformation matrix i,t =P i,t *T Mag->Img , and then the front end morphology of the guidewire is fitted and fused and displayed in the reconstructed image; monitoring is performed according to the intervention path and the relative position relationship of the electromagnetic sensor.

[0006] A method for automatically monitoring guidewire movement in vascular interventional robotic surgery, comprising: extracting an interventional path from a preoperative CT angiography image; determining a registration transformation matrix; the registration transformation matrix being determined based on the coordinate values ​​of an experimental model of a marking point with an electromagnetic sensor attached in a magnetic field space and the coordinate values ​​in an image coordinate space; obtaining the position of the electromagnetic sensor during guidewire movement, and determining the corresponding image coordinate space position based on the electromagnetic sensor position and the registration transformation matrix; fitting the guidewire front end morphology based on the image coordinate space position corresponding to each electromagnetic sensor position at multiple moments and displaying it in a fusion manner in a reconstructed image; determining the guidewire movement status based on the interventional path and the image coordinate space position corresponding to each electromagnetic sensor position at multiple moments; the guidewire movement status being either normal guidewire movement or deviation of the guidewire movement.

[0007] A system for automatically monitoring the progress of a guidewire in vascular interventional robotic surgery, comprising: an interventional path extraction module for extracting the interventional path from a preoperative CT angiography image; a transformation matrix calculation module for determining a registration transformation matrix; the registration transformation matrix is ​​determined based on the coordinate values ​​of an experimental model of a marking point with an electromagnetic sensor attached in a magnetic field space and the coordinate values ​​in an image coordinate space; an image coordinate space position calculation module for obtaining the position of the electromagnetic sensor during the progress of the guidewire, and determining the corresponding image coordinate space position based on the electromagnetic sensor position and the registration transformation matrix; a fitting and reconstruction module for fitting the guidewire front end morphology based on the image coordinate space position corresponding to each electromagnetic sensor position at multiple moments and displaying the resultant image coordinate space in a reconstructed image; a state monitoring module for determining the guidewire progress status based on the interventional path and the image coordinate space position corresponding to each electromagnetic sensor position at multiple moments; the guidewire progress status is whether the guidewire progress is normal or the guidewire progress has deviated. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0009] FIG1 is a flow chart illustrating a method for automatically monitoring guidewire advancement in robotic vascular interventional surgery according to one or more embodiments. DETAILED DESCRIPTION

[0010] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0011] This application can not only locate the movement status of the moving guidewire in real time, but also perform monitoring and early warning based on the relative position relationship between the guidewire and the center line of the interventional path, providing richer visual feedback to serve the implementation of interventional robotic surgery, and has good application prospects.

[0012] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0013] It should be noted that the algorithms for data collection, transmission, storage and processing steps not specifically described in the embodiments, as well as the hardware structures, circuit connections, etc. not specifically described can all be implemented through the disclosed content of the prior art.

[0014] This embodiment discloses a method for automatically monitoring the progress of a guidewire in vascular interventional robotic surgery, comprising the following steps:

[0015] Step 1: Extract the intervention path from the preoperative CT angiography image and obtain the discrete center point coordinate value P{P j ,j=1,…,n} and the corresponding blood vessel radius value R{R j ,j=1,…,n}, where P j represents the jth center point position of the intervention path, n represents the number of center points, R j Represents the radius of the blood vessel at the jth center point.

[0016] Step 2: Place the electromagnetic navigation device in the surgical space and obtain the coordinate value of the experimental model with the electromagnetic sensor mark in the magnetic field space U = {U i,i=1,…,w} and the coordinate value V={V i ,i=1,…,w}, where w is the number of markers, the number of U and V is equal, U i With V i The positions in space correspond one to one. According to the constraint that the distance between the markers is minimum, the registration transformation matrix T is obtained by the following formula. Mag->Img :

[0017] Where r and s represent the rotation matrix and translation matrix respectively, and ||.|| represents the Euclidean norm.

[0018] Step 3: Bind 3 to 5 electromagnetic sensors to the front end of the guide wire in sequence and place them at the starting point of intervention.

[0019] Step 4: When moving to the intervention endpoint, use the electromagnetic navigation device to obtain the electromagnetic sensor position P at time t t ={P i,t ,i=1,…,m}, m represents the number of electromagnetic sensors, and the image coordinate space position P` is obtained based on the registration transformation matrix i,t =P i,t *T Mag->Img , and then the fitted guidewire front end morphology is fused and displayed in the reconstructed image.

[0020] Step 5: Monitor based on the relative position relationship between the intervention path and the electromagnetic sensor. The basis for monitoring based on the relative position relationship between the intervention path and the electromagnetic sensor is:

[0021] Among them, D i,t It represents the difference between the distance between the i-th electromagnetic sensor of the guidewire and the corresponding nearest center point at time t and the corresponding blood vessel radius value. D' represents the average value of the shortest distance between all electromagnetic sensors and the center point of the interventional path. When D'≤0, the guidewire moves normally. When D'>0, the guidewire moves away from the center point, and the robot system should issue a warning.

[0022] Of course, the present invention may have many other embodiments. Without departing from the spirit and essence of the present invention, those skilled in the art may make various corresponding changes and modifications based on the present invention, but these corresponding changes and modifications should all fall within the scope of protection of the claims attached to the present invention.

[0023] In another exemplary embodiment, a system for automatically monitoring the progress of a guidewire in robotic vascular interventional surgery is provided. The system provides a solution to a problem similar to the solution described in the aforementioned method. Therefore, the specific limitations of one or more system embodiments provided below can be found in the aforementioned method limitations and are not further described here. The system for automatically monitoring the progress of a guidewire in robotic vascular interventional surgery includes multiple modules, as shown below.

[0024] The interventional pathway extraction module is used to extract the interventional pathway from preoperative CT angiography images.

[0025] The transformation matrix calculation module is used to determine the registration transformation matrix; the registration transformation matrix is ​​determined based on the experimental model coordinate values ​​of the marking points with electromagnetic sensors in the magnetic field space and the coordinate values ​​in the image coordinate space.

[0026] The image coordinate space position calculation module is used to obtain the position of the electromagnetic sensor during the guidewire's travel and determine the corresponding image coordinate space position based on the electromagnetic sensor position and the registered transformation matrix. In one application, the image coordinate space position calculation module can be provided in an electromagnetic navigation device, which uses the electromagnetic navigation device to obtain the electromagnetic sensor position at time t; alternatively, the image coordinate space position calculation module is connected to the electromagnetic navigation device to collect the electromagnetic sensor position at time t obtained by the electromagnetic navigation device.

[0027] The fitting reconstruction module is used to fit the guidewire front end shape according to the image coordinate space position corresponding to the position of each electromagnetic sensor at multiple moments and fuse it into the reconstructed image.

[0028] The status monitoring module is used to determine the guidewire travel status according to the intervention path and the image coordinate space position corresponding to the position of each electromagnetic sensor at multiple moments; the guidewire travel status is normal guidewire travel or guidewire travel deviation.

[0029] In another exemplary embodiment, a computer device is provided, which may be a server or a terminal. The computer device includes a processor, a memory, an input / output interface (I / O) and a communication interface. The processor, the memory and the input / output interface are connected via a system bus, and the communication interface is connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a method for automatically monitoring the progress of a guidewire in vascular interventional robotic surgery is implemented.

[0030] In an exemplary embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor implements the steps in the above method embodiments when executing the computer program.

[0031] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0032] In an exemplary embodiment, a non-transitory computer program product is provided, including a computer program. When the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0033] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0034] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0035] The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may include, but are not limited to, general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic units, data processing logic units based on quantum computing, and the like.

[0036] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0037] This document uses specific examples to illustrate the principles and implementation methods of this application. The description of the above examples is only intended to help understand the method and core concept of this application. At the same time, for those skilled in the art, based on the concept of this application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for automatically monitoring the progress of a guidewire in a vascular interventional robotic surgery, comprising: Extract the intervention path from the preoperative CT angiography image and obtain the discrete center point coordinate value P in the image coordinate system j and the corresponding vascular radius R j , where j = 1, ..., n, n represents the number of center points, P j represents the jth center point position of the intervention path, R j Represents the radius of the blood vessel at the jth center point; Place an electromagnetic navigation device in the surgical space to obtain the coordinate value U of the experimental model with electromagnetic sensor markers in the magnetic field space. i and the coordinate value V of the corresponding image coordinate space i , where i = 1,…,w, w represents the number of marking points, U i With V i The positions in space correspond one to one, and the registration transformation matrix T is obtained Mag->Img ; 3 to 5 electromagnetic sensors are sequentially attached to the front end of the guide wire, and the interventional robot pushes the guide wire to the intervention starting point; When the interventional robot pushes the guide wire to the intervention endpoint, the electromagnetic navigation device is used to obtain the electromagnetic sensor position P at time t. i,t , i = 1, ..., m, m represents the number of electromagnetic sensors, and the image coordinate space position P' is obtained based on the registration transformation matrix i,t =P i,t *T Mag->Img , then the front end morphology of the fitted guidewire is fused and displayed in the reconstructed image; Monitoring is performed based on the intervention path and the relative position relationship of the electromagnetic sensors.

2. The method for automatically monitoring the progress of a guidewire in a vascular interventional robotic surgery according to claim 1, wherein: Calculate the registration transformation matrix T based on the minimum distance between markers Mag->Img , the corresponding calculation formula is as follows: Among them, r and s represent the rotation matrix and translation matrix respectively, and ||.|| represents the Euclidean norm.

3. The method for automatically monitoring the progress of a guidewire in a vascular interventional robotic surgery according to claim 1, wherein: The basis for monitoring based on the intervention path and the relative position relationship of the electromagnetic sensor is: Among them, D i,t It represents the difference between the distance between the ith electromagnetic sensor of the guidewire and the corresponding nearest discrete center point at time t and the corresponding blood vessel radius value. D` represents the average value of the shortest distance between all electromagnetic sensors and the center point of the intervention path. When D`≤0, the guidewire moves normally. When D`>0, the guidewire deviates and the robot system should give a warning.

4. A method for automatically monitoring the progress of a guidewire in a vascular interventional robotic surgery, comprising: Extract intervention pathways from preoperative CT angiography images; Determine the registration transformation matrix; The registration transformation matrix is ​​determined based on the coordinate values ​​of the experimental model of the marking point with the electromagnetic sensor attached in the magnetic field space and the coordinate values ​​in the image coordinate space; Acquire the position of the electromagnetic sensor during the guidewire's advancement, and determine the corresponding image coordinate space position according to the electromagnetic sensor position and the registration transformation matrix; According to the image coordinate space positions corresponding to the positions of the electromagnetic sensors at multiple moments, the front end shape of the guidewire is fitted and fused and displayed in the reconstructed image; The guidewire travel state is determined according to the intervention path and the image coordinate space positions corresponding to the positions of the electromagnetic sensors at multiple moments; the guidewire travel state is that the guidewire travels normally or the guidewire travel deviates.

5. The method for automatically monitoring the progress of a guidewire in a vascular interventional robotic surgery according to claim 1, wherein: The calculation formula of the image coordinate space position corresponding to each electromagnetic sensor position at multiple moments is: P` i,t =P i,t *T Mag->Img ; Among them, P` i,t is the spatial coordinate position of the i-th image at time t, P i,t is the position of the i-th electromagnetic sensor at time t, T Mag->Img is the registration transformation matrix.

6. The method for automatically monitoring guidewire advancement in vascular interventional robotic surgery according to claim 1, wherein: Determining the guidewire advancing state according to the intervention path and the image coordinate space positions corresponding to the positions of the electromagnetic sensors at multiple moments, including: Extracting each center point in the intervention path and the blood vessel radius value at each center point; Calculate the average value D' of the shortest distances between all electromagnetic sensors and the center points in the intervention path according to the center points in the intervention path, the blood vessel radius values ​​at each center point, and the image coordinate space positions corresponding to the positions of each electromagnetic sensor at multiple moments; When D`≤0, the guidewire travel status is marked as normal guidewire travel; when D`>0, the guidewire travel status is marked as guidewire travel deviation, and a warning prompt is issued.

7. An automatic guidewire advancement monitoring system for vascular interventional robotic surgery, comprising: An interventional pathway extraction module is used to extract interventional pathways from preoperative CT angiography images; A transformation matrix calculation module, used to determine the registration transformation matrix; The registration transformation matrix is ​​determined based on the coordinate values ​​of the experimental model of the marking point with the electromagnetic sensor attached in the magnetic field space and the coordinate values ​​in the image coordinate space; An image coordinate space position calculation module is used to obtain the position of the electromagnetic sensor during the guide wire's advancement, and determine the corresponding image coordinate space position according to the electromagnetic sensor position and the registration transformation matrix; A fitting reconstruction module is used to fit the front end shape of the guidewire according to the image coordinate space position corresponding to each electromagnetic sensor position at multiple moments and fuse it into the reconstructed image; The state monitoring module is used to determine the guidewire travel state according to the intervention path and the image coordinate space position corresponding to each electromagnetic sensor position at multiple moments; the guidewire travel state is that the guidewire travels normally or the guidewire travel deviates.

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