CN113456219A - Liver cancer radio frequency ablation operation path planning method and device based on CT image - Google Patents
Liver cancer radio frequency ablation operation path planning method and device based on CT image Download PDFInfo
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Abstract
The path planning method and the device for the liver cancer radio frequency ablation operation based on the CT image are completely automatic in path planning, a doctor does not need to mark a puncture region and a puncture target point in advance, a proper path can be generated in a complex planning environment, the size and the position of an optimal ablation region can be calculated, the planning result has high ablation efficiency, and the soft and hard constraints in clinic can be met. The method comprises the following steps: (1) data preprocessing: extracting and separating organ models related to planning, appropriately sampling, and calculating a related point set required by planning, wherein connecting lines between the target point set and the skin point set form an original total solution space; (2) path screening: sequentially screening the solution space according to the conditions of clinical constraint, whether the tumor can be completely covered, whether the tumor is a pareto optimal front part and the like; (3) calculating ablation zone positions: and finding out the position of the optimal ablation area in the residual path by using integer programming, and scoring through the set weight to obtain an optimal solution and outputting the optimal solution.
Description
Technical Field
The invention relates to the technical field of medical image processing, in particular to a liver cancer radio frequency ablation operation path planning method based on a CT image and a liver cancer radio frequency ablation operation path planning device based on the CT image.
Background
Radio frequency ablation is essentially a physical therapy method mainly using radio frequency waves as a medium, and is one of the most advanced physical therapy methods in the current liver cancer therapy methods.
The main working principle of the radio frequency ablation is that radio frequency waves generated by a radio frequency generator are guided to a part of a patient needing treatment by electric conduction and a professional key guide electrode, and water inside and outside cells is evaporated, dried and shrunk by rapid temperature rise, so that aseptic necrosis of local cells is caused. Within the effective range, local cells will be completely inactivated, corresponding to the "excision" of the local lesion.
The radiofrequency ablation has the advantages of high curative effect, small wound, quick recovery and few operation complications, can control the disease condition of the recurrence after the tumor operation, brings the hope of survival for liver cancer patients, and is a good choice for the recurrence patients after the tumor operation.
In the traditional liver cancer radio frequency ablation operation, a doctor before an operation roughly determines required ablation times, needle insertion points, puncture depth and the like according to CT images and experiences of a patient, a quantitative planning method is lacked to strictly calculate and plan an ablation range, the ablation range is easily overlarge (normal tissues are damaged), or ablation is incomplete (cancer cells cannot be completely killed), and particularly large tumors are easily caused. The doctor usually ablates the tumor under the guidance of ultrasound, CT image or perspective imaging, the ablation needle highly depends on the experience of the operating doctor during puncture, and is limited by artificial factors such as spatial imagination, and residual cancer is often caused by inaccurate arrangement of the ablation needle during treatment. With the development of robots and navigation technologies, high-precision ablation surgery is implemented at home and abroad by using the robot technology under the guidance of navigation. The radio frequency ablation surgical planning of liver tumors is an important component of a robot-assisted surgical system. However, currently, a physician is generally required to mark a perforable region and a target puncture point in advance.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides a path planning method for liver cancer radio frequency ablation surgery based on CT images, which is completely automatic in path planning, does not need doctors to mark a puncture region and a puncture target point in advance, can generate a proper path and calculate the optimal size and position of an ablation region in a complex planning environment, has higher ablation efficiency in a planning result, and can meet the soft and hard constraints in clinic.
The technical scheme of the invention is as follows: the liver cancer radio frequency ablation operation path planning method based on the CT image comprises the following steps:
(1) data preprocessing: extracting and separating organ models related to planning, appropriately sampling, and calculating a related point set required by planning, wherein connecting lines between the target point set and the skin point set form an original total solution space;
(2) path screening: sequentially screening the solution space according to the conditions of clinical constraint, whether the tumor can be completely covered, whether the tumor is a pareto optimal front part and the like;
(3) calculating ablation zone positions: and finding out the position of the optimal ablation area in the residual path by using integer programming, and scoring through the set weight to obtain an optimal solution and outputting the optimal solution.
The invention cuts and extracts point sets on the relevant tissue structure images of divided organs, skin, bones, livers and the like based on relevant areas and structures in the operation path planning, then generates all potential paths according to the extracted point sets, screens and calculates according to soft and hard constraints in clinic, then judges whether the given path can be subjected to single-needle ablation, calculates the minimum ablation zone radius required by the single-needle ablation, screens out pareto front edges from the existing path according to the ablation efficiency and the soft constraints, finally determines the number and the positions of the ablation zones by adopting integer planning, and obtains a path planning result according to a weight formula, so the path planning is completely automatic, a doctor does not need to mark a pierceable area and a piercing target point in advance, can generate a proper path under a complex planning environment and calculate the size and the position of the optimal ablation zone, the planning result has higher ablation efficiency and can meet the soft and hard constraints in clinic.
Still provide liver cancer radio frequency ablation operation route planning device based on CT image, it includes:
the data preprocessing module is configured to extract and separate organ models related to planning, appropriately sample the organ models and calculate related point sets required by the planning, wherein connecting lines between the targeted point sets and the skin point sets form all original solution spaces;
a path screening module configured to sequentially screen the set of solution spaces according to conditions such as clinical constraints, whether tumors can be completely covered, whether a pareto optimal frontier portion is present, and the like;
and the ablation region position calculating module is configured to find out the optimal ablation region position in the residual path by applying integer programming, and obtain and output the optimal solution through the set weight score.
Drawings
Fig. 1 is a flowchart of a method for planning a radio-frequency ablation surgical path of liver cancer based on CT images according to the present invention.
FIG. 2 is a flow chart of a point-to-line segment calculation method.
Fig. 3 is a schematic diagram of calculating upper and lower boundary points.
Fig. 4 shows the pareto frontier point.
Fig. 5 is a flowchart of determining the positional relationship between a point and an ellipsoid.
Fig. 6 shows a flow chart of a multi-needle planning.
Detailed Description
As shown in fig. 1, the method for planning a radio-frequency ablation surgical path of liver cancer based on CT image comprises the following steps:
(1) data preprocessing: extracting and separating organ models related to planning, appropriately sampling, and calculating a related point set required by planning, wherein connecting lines between the target point set and the skin point set form an original total solution space;
(2) path screening: sequentially screening the solution space according to the conditions of clinical constraint, whether the tumor can be completely covered, whether the tumor is a pareto optimal front part and the like;
(3) calculating ablation zone positions: and finding out the position of the optimal ablation area in the residual path by using integer programming, and scoring through the set weight to obtain an optimal solution and outputting the optimal solution.
The invention cuts and extracts point sets on the relevant tissue structure images of divided organs, skin, bones, livers and the like based on relevant areas and structures in the operation path planning, then generates all potential paths according to the extracted point sets, screens and calculates according to soft and hard constraints in clinic, then judges whether the given path can be subjected to single-needle ablation, calculates the minimum ablation zone radius required by the single-needle ablation, screens out pareto front edges from the existing path according to the ablation efficiency and the soft constraints, finally determines the number and the positions of the ablation zones by adopting integer planning, and obtains a path planning result according to a weight formula, so the path planning is completely automatic, a doctor does not need to mark a pierceable area and a piercing target point in advance, can generate a proper path under a complex planning environment and calculate the size and the position of the optimal ablation zone, the planning result has higher ablation efficiency and can meet the soft and hard constraints in clinic.
Preferably, the step (1) comprises the following substeps:
(1.1) separating related organ images, cutting and sampling an input model graph;
(1.2) generating a point set and a path, wherein the point set related to the operation path planning comprises the following steps: skin point set PsAnd the organ structure point set PoTarget point set PtAblation target coverage point set PaAblation target zone point set PrHealthy tissue point set PhIn which P issAnd PtThe connecting line between is the surgical path to be screened, PoFor determining the shortest distance, P, between the operative path and the impenetrable organ structureaFor judging whether tumors can be covered by ablation zones after adding a safety boundary, PrUsed for judging the coverage degree of the ablation area to the ablation target area and calculating the ablation efficiency PhUsed for judging the damage degree of the ablation area to healthy tissue and calculating the ablation efficiency.
Preferably, in step (1.1), the vtkClipPolyData class in VTK is clipped, and the class accepts a hidden function to clip the clipped graphics, where the hidden function is set as a rectangular box and its boundary coordinate form is { X }min,Xmax,Ymin,Ymax,Zmin,Zmax}; let the coordinate form of the bounding box of the liver be { lever 0, lever 1, lever 2, lever 3, lever 4, lever 5}, and let the coordinate of the cross-sectional center point of CT on the y-axis be ycThe length of the electrode needle for ablation is ln(ii) a The coordinate form of the rectangular frame for cutting the skin is set to be { lever 0-ln,liver1,liver2-ln,ycLiver4, liver5, which only concerns the organ structure inside the liver enclosure, and cuts out the rectangular frame format of organs, blood vessels, and bones set to { liver0-l }n,liver2-ln,liver3,liver4,liver5}。
Preferably, in step (1.2), the organ model is read in the form of vtkPolyData data, wherein the vtkPolyData data is expressed as vertexes, lines, polygons and triangle strips, all vertexes, point set P are obtained by directly calling relevant functions from vtkPolyData classs，PoRespectively obtaining skin and organ structure models after cutting; set of points PaObtained from vtkPolyData generated after the tumor is expanded according to the safety boundary, and the tumor added with the safety boundary is called an ablation target area, PaIf the ablation target area is covered, the whole ablation target area is considered to be covered; ptAcquiring a voxel central point after tumor corrosion, converting vtkPolyData data after tumor model corrosion into ImageData class formed by topological and geometric rule points by using a vtkPolyData ToImageStencil class, calling a related function from the ImageData to acquire a corresponding point set, and taking a tumor mass center as a half of the shortest distance from the tumor surface in the tumor corrosion depth; set of points PrAcquiring a voxel central point after a tumor expands by 5mm of a safety boundary, and representing an ablation target area; set of points PhThe acquisition mode is that the ablation target area is expanded according to the maximum ablation area radius to acquire the voxel center point, then the voxel center point outside the ablation target area is selected, and whether the VTK selected enclosedpoints in the VTK are outside VTK polyData or not is judged.
Preferably, in the step (2), adopting the hard constraint includes: the depth of the path can not exceed the maximum puncture length of the electrode needle, the included angle between the path and the liver membrane can not be less than 20 degrees, the path can not pass through important tissues and the distance between the path and the important tissues is at least more than 5mm, the path must pass through a section of normal liver tissues before passing through the tumor, and the thickness of the tissues is at least 5 mm; taking soft constraints includes: the path is as short as possible, the angle between the path and the liver membrane should be as close to 90 ° as possible, and the path should be as far away from the vital tissue as possible.
Preferably, in the step (2), the path depth ldIs the distance from the final dwell point to the skin point line segment; an included angle theta between the path and the liver membrane is determined by a triangular patch which is formed by a vtkObbtree type detection line segment and a liver model in an intersecting manner and an included angle between a normal vector of the triangular patch and the line segment; path to organ structure closest distance lsFrom line segment and organ structure point set PoThe shortest distance therebetween; the distance of the path passing through the normal liver tissue is obtained by respectively detecting the intersection points of the line segment, the tumor and the liver by a vtkObbtree class and then calculating the distance between the two points; computing a set of line segments and organ structure points PoThe shortest distance between any point and a given line segment is determined, the position relationship between the point and the line segment is classified, and then the shortest distance in each case is calculated (as shown in fig. 2).
The path is rejected as soon as a hard constraint violates the requirement. The path direction of the remaining path, the target point where the path is located, the insertion depth, the angle of the liver membrane, the closest distance to the critical structure will be recorded. Compared with the originally generated paths, the number of the surplus paths is greatly reduced, and the screened surplus paths avoid impenetrable structures such as gall bladder and bones and keep a certain distance.
Preferably, in the step (2), an ellipsoid is used as the ablation region model, the ellipsoid is symmetrical with the electrode needle as an axis center, the radius of the main axis is set as R, the radius of the paraxial axis is set as R, and a total of 12 groups of ablation regions with different sizes are adopted in the surgical planning and written into a form of R × R;
data are taken from the size of an ablation area generated by a cold circulation radio frequency ablation needle at a default power of 105w and normal temperature water of 16 ℃ at different exposed working ends and timing time in the in vitro pig liver, and are shown in table 1:
TABLE 1
Pull-back ablation, which is ablation performed by the physician every time the physician exits a distance along the track that the electrode needle has passed through during radio frequency ablation. After the retraction ablation technique is adopted, a plurality of ablation areas can be arranged on one electrode needle puncture path.
In order to calculate the maximum range of ablation regions possibly generated when using a pullback ablation skill, determining whether the ablation region generated when using one electrode needle can cover an ablation target region, assuming that the electrode needle starts to perform ablation from the bottommost end of a tumor, and judging whether a path can cover the tumor by a given ablation region radius r; continuing to extend the original path from the target point to the direction below the skin until the ablation target coverage point set PaVertically projecting the lower boundary point reached on the path, and simultaneously calculating an upper boundary point;
note down the boundary point as pbThe upper boundary point is ptScreening the paths again by applying clinical soft and hard constraints and updating numerical values corresponding to the soft constraints;
if the radius of the ablation zone is greater than PaFurthest distance, P, of point set to pathaThe point set can be covered by the ablation zone; because a certain interval exists between ablation by pulling back along the path, in order to ensure sufficient ablation, r-0.5 mm is taken as a standard for judging whether an ablation target area can be covered by an ablation area with the paraxial radius r on the path, and if r-0.5 is just larger than PaAnd (4) the points are collected to the farthest distance of the path, and the ablation target area can be ensured to be completely covered by using an ablation area with the paraxial radius r on the path, and the path is screened out from the plan if r is taken as the maximum value in the table and cannot be covered.
Preferably, in the step (2), the pareto optimization adopts ablation efficiency AE, liver membrane included angle theta and insertion depth ldThe closest distance l to the important tissuesAs an optimization objective; and screening paths of the pareto optimal front edge under the four-item optimization target, wherein the optimal solution is located in the screened paths.
Ablation efficiency is to be taken as one of targets of pareto optimization, and is defined as ae (ablation efficiency), and the calculation formula is as follows:
wherein n isrIs a set of ablation target points PrNumber of points, nhIs a healthy tissue point set PhThe number of points.
The above step finds the minimum ablation zone radius that can completely cover the ablation target area for any given path when performing single needle ablation, but the specific positions of these ellipsoidal ablation zones along the path cannot be known, so AE cannot be calculated, but AE can be roughly compared.
It can be foreseen that if p is givenbAs a starting point, ablation is carried out to p at intervals corresponding to the radius r of the ablation zonetAnd processing both ends into hemispheres with radius r, so that an ablation area must cover PrAblation efficiency is lower than actually achievable, but differences in the possible ablation efficiencies achieved for different paths may also be reflected. A path further from the central axis of the tumor requires a larger radius ablation zone, which necessarily also results in lower actual ablation efficiency after the ablation zone is determined, and vice versa.
Pareto optimal refers to: one individual is better without worsening the condition of the other individual until there is no room for improvement. Pareto optimal leading edge point refers to: in performing multi-objective optimization, a state is a pareto optimal leading point if for that state there is no state for which all of the optimization objective terms are better than it. FIG. 4 shows the pareto frontier (star markers) for only two optimization objective terms
Pareto optimization herein employs ablation efficiency AE, hepatic membrane angle θ, insertion depth ldThe closest distance l to the important tissuesAs an optimization objective. And screening paths of the pareto optimal front edge under the four optimization targets, and knowing that the optimal solution is necessarily located in the screened paths.
Preferably, in the step (3), integer programming is performed by using Gurobi to determine the ablation region position, and the solution process of Gurobi is divided into three steps: defining variables, setting an optimization target, and adding constraints;
the evaluation formula takes the form of a weighted product, which is formula (2.2)
Where score is the path score, k1，k2，k3，k4Is an adjustable parameter with a default value of 1.
Integer programming refers to programming in which the variables are integers, and is a division of linear programming and nonlinear programming. The problem of this chapter of planning belongs to linear integer programming. The solution process of Gurobi can be simply divided into three steps: defining variables, setting optimization targets and adding constraints.
Variables in the plan are set as a one-dimensional array of boolean variables. P is to bebThe point is a starting point and is at a set interval of lg(0.5mm) along pbTo ptTaking points in the direction until the last point just exceeds pt. The set of points is recorded as a point set Pg。PgThe number of midpoints is the length of the binary array. Whether ablation is performed at a certain point corresponds to a boolean value in the binary array.
The optimization goal is to have ablation regions covering the number of points n of healthy tissueh. Covering healthy tissue point set P through ablation region corresponding to one-dimensional Boolean array variablehThe condition of (2) is judged. Ablation region pair healthy tissue point set P corresponding to each position node in variable arrayhThe coverage condition of (a) is calculated in advance and recorded in the form of a two-dimensional boolean array.
The constraint is that the ablation zone must completely cover the set of points Pa. Target coverage point set P covered by fusion area correspondingly eliminated through one-dimensional Boolean array variableaAnd (6) judging. Target coverage point set P of ablation zone pair corresponding to each position node in variable arrayaThe coverage condition of (a) is calculated in advance and recorded in the form of a two-dimensional boolean array.
And judging the condition of the ablation area covering point set, namely judging the internal and external position relation between a certain point in the three-dimensional space and a given ellipsoid. Since the ablation zones are all ellipsoidal with axes of symmetry, a fast algorithm is presented herein. The ellipsoid shapes are classified, the internal and external relations between the points to be judged and the ellipse in the corresponding plane are calculated, the position relation between the points and the ellipsoid is judged, and the algorithm is shown in FIG. 5.
After the boolean variable array is solved, the point corresponding to the position where the boolean value is true is the position where the ablation should be performed on the path in the corresponding ablation zone. Simultaneous ablation efficiency AE, insertion depth ldThe closest distance l to the important tissuesNeed to be updated and again apply pareto optimization to pick out the pareto optimal leading edge path. In general, the path before and after optimization does not change because the corresponding numerical value does not change much. After this step, the number of remaining paths is typically between 10 and 60.
When the tumor volume is large, one electrode needle is not enough to complete the ablation task. As shown in fig. 6, a multi-needle planning method based on genetic algorithm is proposed, wherein two ablation region models are determined according to different ablation modes, then the size of an ablation region and the coverage condition of healthy tissues and tumors are calculated, and finally a problem model is converted into the genetic algorithm to obtain a multi-needle planning scheme.
It will be understood by those skilled in the art that all or part of the steps in the method of the above embodiments may be implemented by hardware instructions related to a program, the program may be stored in a computer-readable storage medium, and when executed, the program includes the steps of the method of the above embodiments, and the storage medium may be: ROM/RAM, magnetic disks, optical disks, memory cards, and the like. Therefore, corresponding to the method of the invention, the invention also comprises a liver cancer radio frequency ablation operation path planning device based on the CT image, and the device is generally expressed in the form of functional modules corresponding to the steps of the method. The device includes:
the data preprocessing module is configured to extract and separate organ models related to planning, appropriately sample the organ models and calculate related point sets required by the planning, wherein connecting lines between the targeted point sets and the skin point sets form all original solution spaces;
a path screening module configured to sequentially screen the set of solution spaces according to conditions such as clinical constraints, whether tumors can be completely covered, whether a pareto optimal frontier portion is present, and the like;
and the ablation region position calculating module is configured to find out the optimal ablation region position in the residual path by applying integer programming, and obtain and output the optimal solution through the set weight score.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention in any way, and all simple modifications, equivalent variations and modifications made to the above embodiment according to the technical spirit of the present invention still belong to the protection scope of the technical solution of the present invention.
Claims (10)
1. The liver cancer radio frequency ablation operation path planning method based on the CT image is characterized in that: which comprises the following steps:
(1) data preprocessing: extracting and separating organ models related to planning, appropriately sampling, and calculating a related point set required by planning, wherein connecting lines between the target point set and the skin point set form an original total solution space;
(2) path screening: sequentially screening the solution space according to the conditions of clinical constraint, whether the tumor can be completely covered, whether the tumor is a pareto optimal front part and the like;
(3) calculating ablation zone positions: and finding out the position of the optimal ablation area in the residual path by using integer programming, and scoring through the set weight to obtain an optimal solution and outputting the optimal solution.
2. The method for planning a radio-frequency ablation surgical path for liver cancer based on a CT image according to claim 1, wherein the method comprises the following steps: the step (1) comprises the following sub-steps:
(1.1) separating related organ images, cutting and sampling an input model graph;
(1.2) generating a point set and a path, wherein the point set related to the operation path planning comprises the following steps: skin point set PsAnd the organ structure point set PoTarget point set PtAblation target coverage point set PaAblation target zone point set PrHealthy tissue point set PhIn which P issAnd PtThe connecting line between is the surgical path to be screened, PoFor determining the shortest distance, P, between the operative path and the impenetrable organ structureaFor judging whether tumors can be covered by ablation zones after adding a safety boundary, PrUsed for judging the coverage degree of the ablation area to the ablation target area and calculating the ablation efficiency PhUsed for judging the damage degree of the ablation area to healthy tissue and calculating the ablation efficiency.
3. The method for planning a radio-frequency ablation surgical path for liver cancer based on a CT image as claimed in claim 2, wherein: in the step (1.1), a vtkClipPolyData class in the VTK is cut, the class receives a hidden function to cut the cut graph, the hidden function is set as a rectangular frame, and the boundary coordinate form of the hidden function is { X }min，Xmax，Ymin，Ymax，Zmin，Zmax}; let the coordinate form of the bounding box of the liver be { lever 0, lever 1, lever 2, lever 3, lever 4, lever 5}, and let the coordinate of the cross-sectional center point of CT on the y-axis be ycThe length of the electrode needle for ablation is ln(ii) a The coordinate form of the rectangular frame for cutting the skin is set to be { lever 0-ln，liver1，liver2-ln，ycLiver4, liver5, which only concerns the organ structure inside the liver enclosure, and cuts out the rectangular frame format of organs, blood vessels, and bones set to { liver0-l }n，liver2-ln，liver3，liver4，liver5}。
4. The CT-image-based liver cancer radio-frequency ablation surgical path planning method according to claim 3, wherein the CT-image-based liver cancer radio-frequency ablation surgical path planning method comprises the following steps: in the step (1.2), the organ model is expressed as vtkPolyData
The vtkPolyData data are expressed as vertexes, lines, polygons and triangle strips, all vertexes are obtained by directly calling related functions from the vtkPolyData class, and a point set P is obtaineds，PoRespectively obtaining skin and organ structure models after cutting; set of points PaObtained from vtkPolyData generated after tumor expansion by safety margin, with safety margin addedThe tumor is called an ablation target zone, PaIf the ablation target area is covered, the whole ablation target area is considered to be covered; ptAcquiring a voxel central point after tumor corrosion, converting vtkPolyData data after tumor model corrosion into ImageData class formed by topological and geometric rule points by using a vtkPolyData ToImageStencil class, calling a related function from the ImageData to acquire a corresponding point set, and taking a tumor mass center as a half of the shortest distance from the tumor surface in the tumor corrosion depth; set of points PrAcquiring a voxel central point after a tumor expands by 5mm of a safety boundary, and representing an ablation target area; set of points PhThe acquisition mode is that the ablation target area is expanded according to the maximum ablation area radius to acquire the voxel center point, then the voxel center point outside the ablation target area is selected, and whether the VTK selected enclosedpoints in the VTK are outside VTK polyData or not is judged.
5. The CT-image-based liver cancer radio-frequency ablation surgical path planning method according to claim 4, wherein the CT-image-based liver cancer radio-frequency ablation surgical path planning method comprises the following steps: in the step (2), the applying hard constraints includes: the depth of the path can not exceed the maximum puncture length of the electrode needle, the included angle between the path and the liver membrane can not be less than 20 degrees, the path can not pass through important tissues and the distance between the path and the important tissues is at least more than 5mm, the path must pass through a section of normal liver tissues before passing through the tumor, and the thickness of the tissues is at least 5 mm; taking soft constraints includes: the path is as short as possible, the angle between the path and the liver membrane should be as close to 90 ° as possible, and the path should be as far away from the vital tissue as possible.
6. The CT-image-based liver cancer radio-frequency ablation surgical path planning method according to claim 5, wherein the CT-image-based liver cancer radio-frequency ablation surgical path planning method comprises the following steps: in the step (2), the path depth ldIs the distance from the final dwell point to the skin point line segment; an included angle theta between the path and the liver membrane is determined by a triangular patch which is formed by a vtkObbtree type detection line segment and a liver model in an intersecting manner and an included angle between a normal vector of the triangular patch and the line segment; path to organ structure closest distance lsFrom line segment and organ structure point set PoThe shortest distance therebetween; the distance of the path passing through the normal liver tissue is determined byThe vtkObbtree type detects the intersection points of the line segment, the tumor and the liver respectively, and then calculates the distance between the two points to obtain the vtkObbtree type; computing a set of line segments and organ structure points PoThe shortest distance between any point and a given line segment is determined, the position relations between the points and the line segments are classified, and then the shortest distance under each condition is calculated respectively.
7. The CT-image-based liver cancer radio-frequency ablation surgical path planning method according to claim 6, wherein the CT-image-based liver cancer radio-frequency ablation surgical path planning method comprises the following steps: in the step (2), an ellipsoid is used as an ablation region model, the ellipsoid is symmetrical by taking the electrode needle as an axial center, the radius of a main shaft of the ellipsoid is set as R, the radius of a side shaft of the ellipsoid is set as R, and 12 groups of ablation regions with different sizes are adopted in surgical planning and written into a form of R multiplied by R;
in order to calculate the maximum range of ablation regions possibly generated when using a pullback ablation skill, determining whether the ablation region generated when using one electrode needle can cover an ablation target region, assuming that the electrode needle starts to perform ablation from the bottommost end of a tumor, and judging whether a path can cover the tumor by a given ablation region radius r; continuing to extend the original path from the target point to the direction below the skin until the ablation target coverage point set PaVertically projecting the lower boundary point reached on the path, and simultaneously calculating an upper boundary point;
note down the boundary point as pbThe upper boundary point is ptScreening the paths again by applying clinical soft and hard constraints and updating numerical values corresponding to the soft constraints;
if the radius of the ablation zone is greater than PaFurthest distance, P, of point set to pathaThe point set can be covered by the ablation zone; because a certain interval exists between ablation by pulling back along the path, in order to ensure sufficient ablation, r-0.5 mm is taken as a standard for judging whether an ablation target area can be covered by an ablation area with the paraxial radius r on the path, and if r-0.5 is just larger than PaAnd (4) the points are collected to the farthest distance of the path, and the ablation target area can be ensured to be completely covered by using an ablation area with the paraxial radius r on the path, and the path is screened out from the plan if r is taken as the maximum value in the table and cannot be covered.
8. The method for planning a radio-frequency ablation surgical path for liver cancer based on a CT image according to claim 7, wherein the method comprises the following steps: in the step (2), the pareto optimization adopts ablation efficiency AE, liver membrane included angle theta and insertion depth ldThe closest distance l to the important tissuesAs an optimization objective; and screening paths of the pareto optimal front edge under the four-item optimization target, wherein the optimal solution is located in the screened paths.
9. The method for planning a radio-frequency ablation surgical path for liver cancer based on a CT image according to claim 8, wherein the method comprises the following steps: in the step (3), integer programming is carried out by using Gurobi to determine the position of the ablation area, and the solution process of the Gurobi is divided into three steps: defining variables, setting an optimization target, and adding constraints;
the evaluation formula takes the form of a weighted product, which is formula (2.2)
Where score is the path score, k1，k2，k3，k4Is an adjustable parameter with a default value of 1.
10. Liver cancer radio frequency ablation operation route planning device based on CT image, its characterized in that: it includes:
the data preprocessing module is configured to extract and separate organ models related to planning, appropriately sample the organ models and calculate related point sets required by the planning, wherein connecting lines between the targeted point sets and the skin point sets form all original solution spaces;
a path screening module configured to sequentially screen the set of solution spaces according to conditions such as clinical constraints, whether tumors can be completely covered, whether a pareto optimal frontier portion is present, and the like;
and the ablation region position calculating module is configured to find out the optimal ablation region position in the residual path by applying integer programming, and obtain and output the optimal solution through the set weight score.
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