CN112336460A

CN112336460A - Greedy criterion-based autonomous path planning algorithm for cardiovascular and cerebrovascular interventional surgical robot

Info

Publication number: CN112336460A
Application number: CN202011218868.0A
Authority: CN
Inventors: 宋荆洲; 李振东; 陈子建
Original assignee: Beijing University of Posts and Telecommunications
Current assignee: Beijing University of Posts and Telecommunications
Priority date: 2020-11-04
Filing date: 2020-11-04
Publication date: 2021-02-09

Abstract

The invention discloses a greedy criterion-based autonomous wire feeding algorithm for a cardiovascular and cerebrovascular interventional surgical robot. In the traditional manual wire feeding process, the wire feeding efficiency is often very low, and the blood vessel of a patient is easily damaged. The invention provides an improved autonomous wire feeding algorithm, which converts a complex guide wire conveying problem into a plurality of simple guide wire steering problems of the blood vessel section, and realizes a mechanical autonomous wire feeding process by a Lagrange multiplier method based on a greedy criterion. Not only improves the wire feeding efficiency in the cardiovascular and cerebrovascular interventional operation process, but also can effectively avoid accidental injury to patients caused by improper operation. Through MATLAB simulation experiments, after a target path is constructed, the algorithm can enable the guide wire to be stably pushed along the target path within a small error, and the effectiveness of the algorithm is further verified.

Description

Greedy criterion-based autonomous path planning algorithm for cardiovascular and cerebrovascular interventional surgical robot

Technical Field

The invention belongs to the field of cardiovascular and cerebrovascular intervention operations, and particularly relates to a greedy criterion-based autonomous wire feeding navigation algorithm for a cardiovascular and cerebrovascular intervention operation robot.

Background

At present, cardiovascular and cerebrovascular diseases seriously harm human health. The incidence of the disease increases with the age of the person and once it occurs there is a great possibility of disabling the patient or even directly dying. Therefore, the method is particularly important for treating the cardiovascular and cerebrovascular diseases. In the cardio cerebrovascular interventional operation process, an operator carries out interventional therapy operation on a patient by teleoperation of the wire feeding robot, so that the radiation injury of the doctor in the operation process can be greatly reduced. And at present, the wire feeding process is manually operated by a doctor, the wire feeding efficiency is very low, the whole operation process consumes a long time, and the waste of human resources is caused. Therefore, how to realize the autonomous navigation wire feeding of the robot is a main problem to be solved currently.

Greedy criterion is an important and widely applied solution to the problem. A greedy criterion may be utilized when a complex problem may be composed of several simpler sub-problems, and the set of locally optimal solutions for each sub-problem is exactly the optimal solution for the original complex problem. In the wire feeding process, the guide wire has an optimal rotation direction at the current position at every moment, and if the guide wire can be ensured to be in the optimal rotation direction at any moment, the wire feeding process is certainly the most effective. Therefore, the whole complex wire feeding process can be converted into a plurality of subproblems for solving the optimal rotation direction of the guide wire at the current position, and the solution of the original problem is obtained by solving the subproblems.

Disclosure of Invention

The purpose of the invention is as follows: the invention aims to improve the wire feeding efficiency and safety of doctors in the cardiovascular and cerebrovascular intervention operation process, and provides an autonomous wire feeding path planning algorithm of a vascular intervention operation robot based on a greedy criterion.

In order to achieve the purposes, the invention adopts the following technical scheme: after a three-dimensional coordinate system of a blood vessel contour and a guide wire tail end is established by identifying DSA angiography images of a patient, the guide wire tail end and the blood vessel coordinates under the current section are respectively obtained in each section according to a plurality of sections of a wire feeding step length in the extending direction vertical to the blood vessel. Determining a blood vessel center coordinate through a current blood vessel wall, then constructing a constraint equation set by using the blood vessel center coordinate and a coordinate at the tail end of the guide wire in a simultaneous mode, and determining the optimal rotation direction of the guide wire under the current section by using a Lagrange multiplier method.

The invention has the advantages that:

according to the invention, the greedy criterion-based autonomous wire feeding path selection algorithm of the cardiovascular and cerebrovascular interventional surgical robot is adopted, so that the terminal of the guide wire is in the safest direction at each moment in the wire feeding process, and the safety of the whole surgical process is ensured. In addition, due to mechanical operation, the problems of excessive twisting of the guide wire and the like during manual operation can be avoided.

Drawings

FIG. 1 schematic drawing of guidewire shape

FIG. 2 is a schematic view of a high risk wire feeding process

FIG. 3 is a schematic view of a target wire feeding process

FIG. 4 is a schematic cross-sectional view of a blood vessel during a wire feeding process

FIG. 5 is a graph of an autonomous wire feeding process simulation result based on greedy criterion

FIG. 6 is a graph of an autonomous wire feeding process simulation result based on greedy criterion

Detailed Description

In order to ensure the safety of the operation during the wire feeding process of the cardiovascular and cerebrovascular intervention operation, the bending direction of the tail end of the guide wire should be always close to the center of the blood vessel. As shown in fig. 2, the dark gray portion represents the contour of the blood vessel, the colorless portion represents the ideal position of the wire feeding under the contour of the blood vessel, and the black portion represents the guide wire that has been pushed into the blood vessel, when the guide wire is pushed at the angle shown in fig. 2, the local stress is too large at the bending part of the blood vessel due to the contact of the end of the guide wire with the inner wall of the blood vessel, which may cause the breakage of the blood vessel. Referring to fig. 3, when the distal end of the guide wire is directed toward the center of the blood vessel, the portion of the guide wire that contacts the inner wall of the blood vessel is changed into a bent portion of the guide wire, thereby greatly reducing the phenomenon of local stress concentration on the inner wall of the blood vessel. The primary goal in the wire feeding process is to have the guidewire pass through the vessel curve in the manner shown in fig. 3.

For the blood vessel interventional process, how to convey the guide wire to the lesion part is a more complex problem, but when the problem is converted into the optimal steering problem of the tail end of the guide wire in each blood vessel section perpendicular to the extending direction of the blood vessel, if the guide wire is in the optimal steering at each moment, the pushing mode of the guide wire in the whole wire feeding process is also better. The problem of vascular intervention is greedy and can be solved using a greedy criterion.

The nature of the greedy criterion is that a locally optimal solution is formed each time, in other words, a best solution is processed each time. That is, a solution to the problem is constructed through a series of steps, each of which makes an extension to the partial solution currently constructed until a complete solution to the problem is obtained. The core of the method is that each step of selection must satisfy:

(1) it is feasible that: i.e. it must satisfy the constraints of the problem.

(2) Local optimization: it is the best local choice among all the possible choices in the current step.

(3) Can not be cancelled: i.e. the selection, once made, cannot be changed in the later steps of the algorithm.

For condition (1), when the guidewire is in the optimal steering in the current plane, it is also a safe location inside the vessel, so it is feasible to satisfy condition 1.

For condition (2), when the guide wire turns to the ideal target position closest to the blood vessel in the current section, the optimal local selection is obtained, and therefore, the condition 2 local optimal is satisfied.

For the condition (3), when the guide wire is selected at a certain angle, the subsequent part can pass through the current position due to the continuity of the guide wire, and therefore the condition (3) is satisfied.

For any cross section in the blood vessel, as shown in fig. 4, point a is an ideal target point under the current cross section obtained after DSA contrast image processing of the patient blood vessel; the point B is the self position point of the guide wire; point C is the position of the curved end of the guide wire. Because the shape of the guide wire is kept unchanged in the whole operation process, when an operator twists the guide wire, the point C is on a circle which takes the point B as the center of the circle and the length of the point BC as the radius R.

When the coordinate of the point A is (x)₀,y₀) And the coordinate of the point B is (x)₁,y₁) And when the coordinates of the point C are (x, y), the quantitative relation exists:

(x-x₁)²+(y-y₁)²＝R²

this quantitative relationshipI.e. a fixed constraint in the task of feeding the wire, and the task to be performed is to distance the end C of the guide wire from point a

At a minimum, for

The following relationships exist:

by utilizing the two formulas, after introducing the Lagrange multiplier lambda, an equation can be constructed:

F(x，y)＝λU(x，y)+G(x，y)

U(x，y)＝(x-x₁)²+(y-y₁)²-R²

G(x,y)＝(x-x₀)²+(y-y₀)²＝|CA|

wherein U (x, y) is the inherent constraint of the shape of the guide wire in the wire feeding process, and G (x, y) is the target equation required to be solved. For the above equation solution, we can solve the partial derivatives for x, y and λ separately, i.e.:

and (x, y) meeting the three conditions is the optimal target point coordinate of the guide wire terminal. The point is taken as a guide wire terminal target point in the current section, and the automatic wire feeding path can be formed by continuous circulation.

Example (b):

carrying out simulation experiments in MATLAB by using the algorithm, and stretching to an interval of (-4, 1) as an ideal intravascular target position in the wire feeding process by using a sine function y-sinx in the z axis; points (0.6,0.6, -4) are used as the initial position of the guide wire end; the step size of the advancement was set to 0.1 and the guidewire tip bend radius was 1. The simulation results are shown in fig. 5 and 6.

Each point in the figure is an ideal target position under each section of the blood vessel, and a black line segment is the position of the tail end path of the guide wire. It can be seen that the guide wire is always pushed around the ideal target point during the entire wire feeding process, and although there is a slight deviation at the individual points, the bending radius does not exceed the preset bending radius, so that the method is effective.

Claims

1. The method for planning the autonomous wire feeding path of the vascular intervention operation based on the greedy criterion is provided, and the specific construction process is characterized by comprising the following steps of:

1) the entire complex wire feeding problem is converted into a guide wire tip turning problem on each cross section perpendicular to the extending direction of the blood vessel.

2) And (4) solving a point which is closest to the ideal target point on the cross section of each advancing step length along the guide wire advancing process by using a greedy criterion method.

3) And (4) solving the coordinate of the closest point to the ideal target point (the point on the centerline of the blood vessel) in the current section by using a Lagrange multiplier method.

2. The greedy criterion-based autonomous wire feeding method for vascular intervention surgery according to claim 1, wherein the method comprises the following steps:

the method for determining the coordinates of the guide wire tail end and the target point in the step 1) comprises the following steps: firstly, a patient DSA (digital radiography) contrast image sequence is analyzed, an overall blood vessel contour map is constructed by fusing contrast sequence images under each frame, and then an ideal target point is constructed by utilizing a plurality of blood vessel contour maps with different angles.

3. The greedy criterion-based autonomous wire feeding path planning method for vascular intervention surgery according to claim 1, characterized in that:

the requirement of using the greedy criterion in the step 1) is as follows: the point through which the end of the guide wire passes remains unchanged throughout the procedure; the rotating direction of the tail end of the guide wire is the closest direction to the ideal target point in the current section; the point through which the guidewire tip passes must be a viable safety point.