An automatic monitoring method for guidewire travel in robotic interventional vascular surgery

Abstract

This invention discloses an automatic monitoring method for guidewire movement in vascular interventional robotic surgery, comprising the following steps: S1, extracting the interventional path from preoperative CT angiography images; S2, placing an electromagnetic navigation device in the surgical space, obtaining the coordinate values ​​of the experimental model with electromagnetic sensor markers attached in the magnetic field space and the corresponding coordinate values ​​in the image coordinate space, and obtaining the registration transformation matrix; S3, sequentially attaching 3 to 5 electromagnetic sensors to the front end of the guidewire and pushing the guidewire to the interventional starting point; S4, during the guidewire's movement to the interventional endpoint, using the electromagnetic navigation device to obtain the electromagnetic sensor position P at time t. i,t And obtain the image coordinate space position P` based on the registration transformation matrix. i,t The fitted guidewire tip morphology is fused and displayed in the reconstructed image; S5, monitoring is performed based on the intervention path and the relative positional relationship of the electromagnetic sensors. This invention can locate the movement state of the guidewire in real time and provide early warning of deviation.

Description

Technical Field

[0001] This invention relates to the field of surgical navigation technology, specifically to an automatic monitoring method for guidewire movement in vascular interventional robotic surgery. Background Technology

[0002] In recent years, the development of vascular interventional robots has been very rapid. Compared with traditional vascular interventional surgery, interventional robots not only have good stability but also avoid doctors' prolonged exposure to radiation. After the robot grips and pushes the guidewire into the body, the current mainstream method for monitoring the guidewire's movement relies on large amounts of X-ray imaging. However, because the interventional instruments themselves are made of flexible materials and exhibit hysteresis after moving a long distance along the blood vessel, doctors sometimes find that the guidewire does not show the correct trajectory in the X-ray image, and it is also impossible to capture the guidewire movement in real time between two X-ray acquisitions. This poses some challenges to observing guidewire advancement, especially near vascular bifurcation points. Summary of the Invention

[0003] To address the shortcomings of existing technologies and to better capture the movement of the guidewire, this invention proposes an automatic guidewire movement monitoring method in vascular interventional robotic surgery. The method aims to automatically and in real-time track the movement of the guidewire within the blood vessel and provide a warning of deviation based on the relative position of the guidewire tip and the interventional path.

[0004] To achieve the above-mentioned technical objectives, the technical solution adopted by the present invention is as follows:

[0005] An automatic monitoring method for guidewire movement in vascular interventional robotic surgery includes the following steps:

[0006] Step 1: Extract the interventional path from the preoperative CT angiography image and obtain the discrete center point coordinates P in the image coordinate system. j With the corresponding blood vessel radius value R j Where j = 1, ..., n, n represents the number of discrete points at the center, P j R represents the position of the j-th center point of the intervention path. j This represents the radius of the blood vessel at the j-th location.

[0007] Step 2: Place the electromagnetic navigation device in the operating space and obtain the coordinate values ​​U of the experimental model with electromagnetic sensor markers attached in the magnetic field space. i Coordinates V in the corresponding image coordinate space i Where i = 1, ..., w, w represents the number of markers, U i With V i The positions in space are corresponded one-to-one, and the registration transformation matrix T is obtained. Mag->Img ;

[0008] Step 3: Attach 3 to 5 electromagnetic sensors to the front end of the guidewire in sequence, and push the guidewire to the intervention starting point by the intervention robot;

[0009] Step 4: During the process of the interventional robot pushing the guidewire to the intervention endpoint, the electromagnetic sensor position P at time t is obtained using an electromagnetic navigation device. i,t Let i = 1, ..., m, where 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 shape of the guidewire tip is fitted and fused to display in the reconstructed image;

[0010] Step 5: Monitor according to the intervention path and the relative positional relationship of the electromagnetic sensors.

[0011] Preferably, in step 2, the registration transformation matrix T is calculated based on the principle of minimizing the distance between the marked points. Mag->Img ,

[0012]

[0013] Where r and s represent the rotation matrix and translation matrix, respectively, and ||.|| represents the Euclidean norm.

[0014] Furthermore, in step 5, the judgment criteria for monitoring based on the intervention path and the relative positional relationship of the electromagnetic sensors are as follows:

[0015]

[0016] Among them, D i,t Let represent the difference between the distance of the i-th electromagnetic sensor of the guidewire to its nearest discrete center point and the radius of the corresponding blood vessel at time t. Let D' represent the average of the shortest distances between all electromagnetic sensors and the center point of the interventional path. ` When D ≤ 0, the guidewire travels normally; when D ` When the value is greater than 0, the guide wire deviates from its intended path, and the robot system should issue a warning.

[0017] This invention can not only locate the movement status of the guidewire in real time, but also monitor and warn based on the relative position of the guidewire and the center line of the intervention path, providing richer visual feedback to support the implementation of interventional robotic surgery, and has great application prospects.

[0018] Obviously, based on the above description of the present invention, and according to common technical knowledge and conventional methods in the field, various other modifications, substitutions or alterations can be made without departing from the basic technical concept of the present invention.

[0019] The following detailed embodiments further illustrate the above-described content of the present invention. However, this should not be construed as limiting the scope of the present invention to the following examples. All technologies implemented based on the above-described content of the present invention fall within the scope of the present invention. Attached Figure Description

[0020] Figure 1 This is a flowchart illustrating an embodiment of the present invention. Detailed Implementation

[0021] It should be noted that the algorithms for data acquisition, transmission, storage and processing steps not specifically described in the embodiments, as well as the hardware structures and circuit connections not specifically described, can all be implemented using content already disclosed in the prior art.

[0022] This embodiment discloses an automatic monitoring method for guidewire movement in vascular interventional robotic surgery, specifically including the following steps:

[0023] Step 1: Extract the interventional path from the preoperative CT angiography image and obtain the discrete center point coordinates P{P} in the image coordinate system. j The values ​​of the blood vessel radius R{j=1,…,n} are related to the corresponding blood vessel radius values ​​R{R j ,j=1,…,n}, where P j R represents the position of the j-th center point of the intervention path, n represents the number of discrete center points, and R j This represents the radius of the blood vessel at the j-th location.

[0024] Step 2: Place the electromagnetic navigation device in the operating space and obtain the coordinate values ​​U = {U} of the experimental model with electromagnetic sensor markers attached in the magnetic field space. i The coordinates of the corresponding image coordinate space are V = {i = 1, ..., w}. i Let i = 1, ..., w, where w is the number of markers, and the number of U and V are equal. i With V i The positions in space correspond one-to-one. Based on the constraint of minimizing the distance between the marker points, the registration transformation matrix T can be obtained from the following formula. Mag->Img ,

[0025]

[0026] Where r and s represent the rotation matrix and translation matrix, respectively, and ||.|| represents the Euclidean norm.

[0027] Step 3: Attach 3 to 5 electromagnetic sensors to the front end of the guidewire and place it at the intervention point.

[0028] Step 4: During the journey to the intervention endpoint, use electromagnetic navigation equipment to obtain the electromagnetic sensor position P at time t. t ={P i,t The image coordinate space position P is obtained based on the registration transformation matrix, where i = 1, ..., m, and m represents the number of electromagnetic sensors. i ` ,t =P i,t *T Mag->Img Then, the morphology of the guidewire tip is fitted and fused to display in the reconstructed image.

[0029] Step 5: Monitor based on the intervention path and the relative positions of the electromagnetic sensors.

[0030]

[0031] Among them, P j Let represent the position of the j-th center point of the intervention path, n represent the number of discrete center points, ||.|| represents the Euclidean norm, and Rij. j D represents the radius of the blood vessel at the j-th location. i,t D represents the difference between the distance of the i-th electromagnetic sensor of the guidewire to its nearest center point and the radius of the blood vessel at time t. ` Represents the average of the shortest distances between all electromagnetic sensors and the center point of the intervention path; when D ` When D ≤ 0, the guidewire travels normally; when D ` When the value is greater than 0, the guide wire deviates from its intended path, and the robot system should issue a warning.

[0032] Of course, the present invention may have other various embodiments. Without departing from the spirit and essence of the present invention, those skilled in the art can make various corresponding changes and modifications according to the present invention, but these corresponding changes and modifications should all fall within the protection scope of the appended claims.

Claims

1. A guidewire advancement automatic monitoring system in a vascular intervention robotic surgery, characterized in that: The electromagnetic navigation device, a guide wire, and an interventional robot are included, the front end of the guide wire is sequentially bound with 3-5 electromagnetic sensors, and the interventional robot is used for pushing the guide wire; The automatic monitoring system is configured to perform the following steps: Step 1: Extract the interventional path from the preoperative CT angiography image and obtain the discrete center point coordinates in the image coordinate system. With the corresponding blood vessel radius value ,in n represents the number of discrete points at the center. The first representing the intervention path The location of the center point Representing the The radius value of the blood vessel at each location point; Step 2, place the electromagnetic navigation device in the surgical space, and obtain the coordinate values of the experimental model with the electromagnetic sensor marker points attached in the magnetic field space Coordinate values of the corresponding image coordinate space Wherein, , The number of marker points, And The position in space is one-to-one correspondence, and the registration transformation matrix is obtained ; Step 3, the guide wire with the front end bound with 3-5 electromagnetic sensors is pushed to the interventional starting point by the interventional robot; Step 4, during the process of pushing the intervention robot to the intervention endpoint, the electromagnetic navigation device is used to obtain the electromagnetic sensor position at time t , , m represents the number of electromagnetic sensors, and the image coordinate space position is obtained based on the registration transformation matrix Then the shape of the front end of the guide wire is fitted and fused and displayed in the reconstructed image Step 5, monitoring is performed according to the interventional path and the relative position relationship of the electromagnetic sensors; the judgment basis is: wherein, represents the difference between the distance of the guidewire at time t to the nearest discrete center point and the vessel radius at the corresponding location, represents the average of the shortest distance between all electromagnetic sensors and the center point of the intervention path, when 0, the guidewire is advancing normally; when 0, the guidewire is deviating from the normal advancement, and the robotic system should be alerted.​ 2. The automatic guidewire advancement monitoring system in vascular intervention robotics surgery of claim 1, wherein: In step 2, the registration transformation matrix is calculated according to the principle of minimum distance between the marked points , wherein and R and t represent a rotation matrix and a translation matrix, respectively, and ||. || represents the Euclidean norm.

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