Spatially fractionated radiotherapy target volume placement method and system

Abstract

The application provides a space segmentation radiotherapy target area arrangement method and system, and belongs to the technical field of radiation oncology. The space segmentation radiotherapy target area is composed of multiple sub-target areas. The arrangement of the sub-target areas comprises the following steps: obtaining patient radiotherapy data, wherein the radiotherapy data comprises patient normal tissue and tumor area data, so as to obtain the range of the space segmentation radiotherapy target area that can be arranged; determining the initial positions of all the sub-target areas of the space segmentation radiotherapy by using the closest packing method; determining the size of the sub-target areas according to the size of the tumor area; and optimizing and adjusting the initial positions of all the sub-target areas, moving the tumor as a whole, and obtaining the final positions of all the sub-target areas. The application utilizes the data of the patient normal tissue and the tumor target area, arranges more radiotherapy target areas in the arrangeable radiotherapy target area region according to the closest packing method, uses the optimization method to optimize the arrangement of the radiotherapy target area, further increases the number of the radiotherapy target areas, and realizes the maximization of the peak-to-valley ratio.

Description

Technical Field

[0001] This invention relates to the field of radiation oncology technology, specifically to a method and system for spatially segmented radiotherapy target area arrangement. Background Technology

[0002] Spatially fractionated radiation therapy (SFRT) delivers a high dose (10–25 Gy) to the target area in a single radiotherapy session, creating a non-uniform dose distribution similar to brachytherapy. Studies have shown that SFRT can overcome the limitations of normal tissue tolerance in conventional radiotherapy, significantly increasing the dose within the tumor. It has achieved good clinical results in treating large-volume / radiation-resistant / recurrent tumors that do not respond well to conventional radiotherapy, reducing radiotherapy toxicity. The overall response rate for palliative treatment of large, intermediate-to-late-stage tumors is as high as 80–90%, and the overall response rate can be further improved when combined with external beam radiation therapy. SFRT can be used as an induction therapy to increase dose, sensitize, and elicit an immune response before conventional radiotherapy. SFRT is considered a revolutionary innovation in the field of radiation oncology by radiation oncology experts.

[0003] The key parameter of SFRT is the peak-to-valley ratio, which is the ratio of high dose (peak dose) to low dose (valley dose) within the tumor. The higher this value, the more significant the advantages of SFRT. Collimators are the main means of implementing SFRT, including two-dimensional grid collimators and multi-leaf collimators (MLC). However, existing accelerators cannot achieve this, require additional grid collimators to be fabricated using precision machining techniques, cannot arbitrarily change the size and spacing of the grid apertures, can only achieve two-dimensional SFRT, and have difficulty reducing skin dose and dose to organs at risk. The advantages of MLC are that it interfaces with the planning system, which is beneficial for the evaluation and comparison of the planning system; using accelerator-equipped MLCs can be widely used in various radiotherapy centers; it can arbitrarily change the size of small fields and the distance between fields; it can achieve three-dimensional SFRT, but its treatment time is longer; the movement restrictions of the accelerator lead gate increase the treatment time and difficulty; and it has a lower peak-to-valley ratio compared to grid collimators.

[0004] Designing a SFRT (Surgical Target Therapy) plan requires the placement of SFRT-specific target regions within the tumor. These target regions, located within the tumor area, consist of a set of discrete sub-target regions. Through inverse optimization design, three-dimensional peak and trough doses can be achieved. The tumor region with sub-target regions produces the peak dose, while the tumor region without sub-target regions produces the trough dose. Currently, no radiotherapy planning system considers the specific requirements of SFRT plan design. Professionals must manually place SFRT sub-target regions using conventional radiotherapy planning systems. This involves manually placing spheres as sub-target regions using simple geometric tools provided by the planning system, such as distance measurement, checkerboard display, and 3D stereoscopic display. This method is acceptable when the tumor volume is small. However, when the tumor volume is large, the workload becomes unbearable, and the optimal placement of the spheres cannot be guaranteed. Summary of the Invention

[0005] The purpose of this invention is to provide a method and system for segmented radiotherapy target placement that can ensure that the volume of all sub-target areas accounts for a certain proportion of the tumor volume, and also ensure the maximum distance between spheres, thereby improving the peak-to-valley ratio, so as to solve at least one of the technical problems existing in the above-mentioned background art.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] On one hand, the present invention provides a method for arranging a spatially segmented radiotherapy target area, wherein the spatially segmented radiotherapy target area is composed of multiple sub-target areas, and the arrangement of the sub-target areas includes:

[0008] Acquire patient radiotherapy data, including data on normal tissue and tumor area, to determine the extent of a spatially segmentable radiotherapy target area;

[0009] Determine the center location and initial size of the first densest packing cell;

[0010] The size of the sub-target area is determined based on the size of the tumor area;

[0011] The initial positions of all sub-target areas for spatial fractionation radiotherapy were determined using the densest packing method.

[0012] The initial positions of all sub-target areas are optimized and adjusted, and the entire system is moved within the tumor to obtain the final positions of all sub-target areas.

[0013] Preferably, the closest packing method includes:

[0014] The first densest stacking unit is determined, which can be arranged at the center of the area where the radiotherapy target can be arranged or at any other location within it;

[0015] Identify other densest packing cells, which are the same size as the first densest packing cell and are located around the first densest packing cell;

[0016] Obtain the initial position of the center of the densest stacked unit, i.e. the initial position of the center of the spatially segmented radiotherapy sub-target area, and arrange the sub-target area, i.e. the radiotherapy target area, at the position within the area where the target area can be arranged.

[0017] Preferably, the optimization adjustment of the initial position of all sub-target regions includes: keeping the target region volume unchanged, optimizing the position of all sub-target regions through an optimization method, increasing the number of sub-target regions, reducing the size of sub-target regions, and increasing the peak-to-valley ratio.

[0018] Preferably, the optimization adjustment of the initial position of all sub-target regions includes: keeping the target region volume unchanged, optimizing the position of all sub-target regions through an optimization method, increasing the distance between sub-target regions, and increasing the peak-to-valley ratio.

[0019] Preferably, the optimization method includes:

[0020] Step 1: Obtain the position, volume, spacing between sub-target regions, and diameter, denoted as (x... i ,y i ,z i V0, d, and d';

[0021] Step 2: n = 1;

[0022] Step 3: Calculate the distance d between the spheres n =d+0.1 or calculate the diameter of the sphere d' n =d'-0.1

[0023] Step 4: In the domain Δy∈(-d, d), Within the ranges Δα∈(-π, π), Δβ∈(-π, π), and Δγ∈(-π, π), an adaptive simulated annealing method is used to adjust the parameter temperature to control the probability distribution of random numbers, and (x) is randomly generated. i ,y i ,z i ) movement amount (Δx, Δy, Δz, Δα, Δβ, Δγ);

[0024] Step 5: Read the data of the deployable target area;

[0025] Step 6: Calculate the optimized target radiotherapy volume V n ;

[0026] Step 7: Determine V n Is it greater than or equal to V0? If so, proceed to step 8 and increase the diameter of the densest packed spheres, i.e., the spacing between spheres in the target area; if not, proceed to step 4.

[0027] Step 8: Determine V n If the value is greater than V0, and n = n + 1, go to step 3; otherwise, output the position of the radiotherapy sphere (x). i ,y i ,z i The judgment ends.

[0028] Preferably, the deployable radiotherapy target area is obtained by indenting the tumor by a certain distance and avoiding normal tissue; the densest stacking unit can be of any shape, and the size of the densest stacking unit is smaller than the deployable radiotherapy target area; the sub-target area has the same shape as the densest stacking unit, and the size of the sub-target area is smaller than the densest stacking unit.

[0029] Secondly, the present invention also provides a spatially segmented radiotherapy target area arrangement system, wherein the spatially segmented radiotherapy target area is composed of multiple sub-target areas, including:

[0030] The data acquisition module is used to acquire patient radiotherapy data, which includes data on normal tissue and conventional large-field radiotherapy target area, in order to obtain the range of spatially segmentable radiotherapy target areas that can be arranged.

[0031] The radiotherapy target layout module is used to determine the initial positions of all sub-targets for spatial segmentation radiotherapy using the densest packing method.

[0032] The radiotherapy target size determination module is used to determine the size of the sub-target area based on the size of the tumor area;

[0033] The radiotherapy target optimization module is used to optimize and adjust the initial position of all sub-targets, move them as a whole within the tumor, and obtain the final position of all sub-targets.

[0034] Thirdly, the present invention provides a non-transitory computer-readable storage medium for storing computer instructions, which, when executed by a processor, implement the spatial segmentation radiotherapy target area arrangement method as described above.

[0035] Fourthly, the present invention provides a computer program product, including a computer program that, when run on one or more processors, is used to implement the spatial segmentation radiotherapy target area arrangement method as described above.

[0036] Fifthly, the present invention provides an electronic device, comprising: a processor, a memory, and a computer program; wherein the processor is connected to the memory, the computer program is stored in the memory, and when the electronic device is running, the processor executes the computer program stored in the memory to cause the electronic device to execute instructions for implementing the spatial segmentation radiotherapy target area arrangement method as described above.

[0037] The beneficial effects of this invention are: by utilizing data on the patient's normal tissue and tumor target area, more radiotherapy target areas are arranged in the densest possible area according to the densest stacking method; by using optimization methods, the arrangement of radiotherapy target areas is optimized, further increasing the number of radiotherapy target areas and maximizing the peak-to-valley ratio.

[0038] The advantages of additional aspects of the invention will be set forth more clearly in the following description or will be learned by practice of the invention. Attached Figure Description

[0039] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0040] Figure 1 This is a flowchart of the spatial segmentation radiotherapy target area arrangement method according to an embodiment of the present invention.

[0041] Figure 2 This is a schematic diagram of the area where the radiotherapy target area can be arranged in the spatial segmentation radiotherapy according to an embodiment of the present invention.

[0042] Figure 3 This is a schematic diagram of the arrangement of the three-layer spheres according to the closest packing method in an embodiment of the present invention.

[0043] Figure 4 This is a sphere outline diagram drawn on a plane through the center of the outermost sphere, as described in an embodiment of the present invention.

[0044] Figure 5 This is a schematic diagram of spatial segmentation radiotherapy target region generation according to an embodiment of the present invention.

[0045] Figure 6 This is a schematic diagram of the spatial segmentation radiotherapy target area arrangement according to an embodiment of the present invention.

[0046] Figure 7 This is a functional block diagram of the row space segmentation radiotherapy target area arrangement system described in an embodiment of the present invention.

[0047] Figure 8 This is a flowchart illustrating the optimization of spatial segmentation for radiotherapy target areas according to an embodiment of the present invention. Detailed Implementation

[0048] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0049] It will be understood by those skilled in the art that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0050] It should also be understood that terms such as those defined in general dictionaries should be understood to have meanings consistent with their meanings in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless defined as here.

[0051] Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the term “comprising” as used in this specification means the presence of the stated features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, and / or groups thereof.

[0052] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of those different embodiments or examples.

[0053] To facilitate understanding of the present invention, the present invention will be further explained and described below with reference to the accompanying drawings and specific embodiments. However, the specific embodiments do not constitute a limitation on the embodiments of the present invention.

[0054] Those skilled in the art should understand that the accompanying drawings are merely schematic diagrams of embodiments, and the components in the drawings are not necessarily essential for implementing the present invention.

[0055] Example 1

[0056] In this embodiment 1, a spatially segmented radiotherapy target area arrangement system is first provided. The spatially segmented radiotherapy target area is composed of multiple sub-target areas, including:

[0057] The acquisition module is used to acquire patient radiotherapy data, which includes data on the patient's normal tissues and tumor areas, in order to obtain the range of the spatially segmentable radiotherapy target area.

[0058] The radiotherapy target layout module is used to determine the initial positions of all sub-targets for spatial segmentation radiotherapy using the densest packing method.

[0059] The radiotherapy target size determination module is used to determine the size of the sub-target area based on the size of the tumor area;

[0060] The radiotherapy target optimization module is used to optimize and adjust the initial position of all sub-targets, move them as a whole within the tumor, and obtain the final position of all sub-targets.

[0061] In this embodiment 1, the above-described system is used to implement a method for arranging spatially segmented radiotherapy target areas. The spatially segmented radiotherapy target area is composed of multiple sub-target areas, and the arrangement of the sub-target areas includes:

[0062] Acquire patient radiotherapy data, including data on normal tissue and tumor area, to determine the extent of a spatially segmentable radiotherapy target area;

[0063] The initial positions of all sub-target areas for spatial fractionation radiotherapy were determined using the densest packing method.

[0064] The size of the sub-target area is determined based on the size of the tumor area;

[0065] The initial positions of all sub-target areas are optimized and adjusted, and the entire system is moved within the tumor to obtain the final positions of all sub-target areas.

[0066] The closest packing method includes:

[0067] The first densest stacking unit is determined, which can be arranged at the center of the area where the radiotherapy target can be arranged or at any other location within it;

[0068] Identify other densest packing cells, which are the same size as the first densest packing cell and are located around the first densest packing cell;

[0069] Obtain the initial position of the center of the densest stacked unit, i.e. the initial position of the center of the spatially segmented radiotherapy sub-target area, and arrange the sub-target area, i.e. the radiotherapy target area, at the position within the area where the target area can be arranged.

[0070] In this embodiment 1, the optimization and adjustment of the initial position of all sub-target regions includes: keeping the target region volume unchanged, optimizing the position of all sub-target regions through optimization methods, increasing the number of sub-target regions, reducing the size of sub-target regions, and increasing the peak-to-valley ratio.

[0071] The optimization method includes:

[0072] Step 1: Obtain the position, volume, spacing between sub-target regions, and diameter, denoted as (x... i ,y i ,z i V0, d, and d';

[0073] Step 2: n = 1;

[0074] Step 3: Calculate the diameter d' of the sphere n =d'-0.1

[0075] Step 4: In the domain Δy∈(-d, d), Within the ranges Δα∈(-π, π), Δβ∈(-π, π), and Δγ∈(-π, π), an adaptive simulated annealing method is used to adjust the parameter temperature to control the probability distribution of random numbers, and (x) is randomly generated. i ,y i ,z i ) movement amount (Δx, Δy, Δz, Δα, Δβ, Δγ);

[0076] Step 5: Read the data of the deployable target area;

[0077] Step 6: Calculate the optimized target radiotherapy volume V n ;

[0078] Step 7: Determine V n Is it greater than or equal to V0? If so, proceed to step 8 and increase the diameter of the densest packed spheres, i.e., the spacing between spheres in the target area; if not, proceed to step 4.

[0079] Step 8: Determine V n If the value is greater than V0, and n = n + 1, go to step 3; otherwise, output the position of the radiotherapy sphere (x). i ,y i ,z i The judgment ends.

[0080] The deployable radiotherapy target area is obtained by indenting the tumor by a certain distance and avoiding normal tissue; the densest stacking unit can be of any shape and the unit size is smaller than the deployable radiotherapy target area; the sub-target area has the same shape as the densest stacking unit and the sub-target area is smaller than the densest stacking unit.

[0081] Example 2

[0082] In this embodiment 2, a spatially segmented radiotherapy target area arrangement system is provided. The spatially segmented radiotherapy target area is composed of multiple sub-target areas, including:

[0083] The acquisition module is used to acquire patient radiotherapy data, which includes data on the patient's normal tissues and tumor areas, in order to obtain the range of the spatially segmentable radiotherapy target area.

[0084] The radiotherapy target layout module is used to determine the initial positions of all sub-targets for spatial segmentation radiotherapy using the densest packing method.

[0085] The radiotherapy target size determination module is used to determine the size of the sub-target area based on the size of the tumor area;

[0086] The radiotherapy target optimization module is used to optimize and adjust the initial position of all sub-targets, move them as a whole within the tumor, and obtain the final position of all sub-targets.

[0087] In this embodiment 2, the above-described system is used to implement a method for arranging spatially segmented radiotherapy target areas. The spatially segmented radiotherapy target area is composed of multiple sub-target areas, and the arrangement of the sub-target areas includes:

[0088] Acquire patient radiotherapy data, including data on normal tissue and tumor area, to determine the extent of a spatially segmentable radiotherapy target area;

[0089] The initial positions of all sub-target areas for spatial fractionation radiotherapy were determined using the densest packing method.

[0090] The size of the sub-target area is determined based on the size of the tumor area;

[0091] The initial positions of all sub-target areas are optimized and adjusted, and the entire system is moved within the tumor to obtain the final positions of all sub-target areas.

[0092] The closest packing method includes:

[0093] The first densest stacking unit is determined, which can be arranged at the center of the area where the radiotherapy target can be arranged or at any other location within it;

[0094] Identify other densest packing cells, which are the same size as the first densest packing cell and are located around the first densest packing cell;

[0095] Obtain the initial position of the center of the densest stacked unit, i.e. the initial position of the center of the spatially segmented radiotherapy sub-target area, and arrange the sub-target area, i.e. the radiotherapy target area, at the position within the area where the target area can be arranged.

[0096] In this embodiment 2, unlike embodiment 1, the optimization adjustment of the initial position of all sub-target regions includes: keeping the target region volume unchanged, optimizing the position of all sub-target regions through an optimization method, increasing the distance between sub-target regions, and increasing the peak-to-valley ratio.

[0097] The optimization method described herein follows the same steps as those in Example 1.

[0098] The deployable radiotherapy target area is obtained by indenting the tumor by a certain distance and avoiding normal tissue; the densest stacking unit can be of any shape and the unit size is smaller than the deployable radiotherapy target area; the sub-target area has the same shape as the densest stacking unit and the sub-target area is smaller than the densest stacking unit.

[0099] Example 3

[0100] To address the issue of SFRT target placement, this embodiment 3 provides a method and system for SFRT target placement. By acquiring and analyzing data from the patient's normal tissues and tumor areas, the target placement is optimized, providing a reference for spatial segmentation radiotherapy target placement.

[0101] The spatially segmented radiotherapy target area consists of multiple sub-target areas. The arrangement of the sub-target areas includes five steps: Step S110, acquiring patient radiotherapy data, which includes data on the patient's normal tissue and tumor area, to obtain the range in which the spatially segmented radiotherapy target area can be arranged; Step S120, determining the size of the sub-target area, which is determined by the size of the tumor area; Step S130, determining the center position and initial size of the first densest stacking unit; Step S140, determining the initial positions of all sub-target areas in the spatially segmented radiotherapy, which are determined using the densest stacking method; Step S150, optimizing and adjusting the final positions of the sub-target areas, which are obtained by using an optimization method after overall movement within the tumor.

[0102] like Figure 1 As shown, the method begins in step S110, acquiring the patient's radiotherapy data. This data includes data on the patient's normal tissue and tumor area, which can be derived from common hospital imaging techniques such as CT, MRI, ultrasound, and PET / CT. The normal tissue and tumor area are thus delineated. The relative positional relationship between the normal tissue and the tumor target area is analyzed to generate a region where the radiotherapy target area can be placed. Because spatial fractionation radiotherapy delivers a high single dose, to protect normal tissue, the high-dose radiotherapy target area should be located a certain distance from the normal tissue. The size of this range is related to the tumor volume. For example... Figure 2 As shown, in one example, the tumor volume is 2450cc, and the radiotherapy target area (white curve) is 2cm away from the tumor boundary (black curve), which can better protect the normal tissues around the tumor, such as the spinal cord, larynx, and skin.

[0103] In step S120, in one example, the radiotherapy sub-target area has the same shape as the densest packed unit, both being spheres, with a size determined by the tumor area size of 2450 cc. The diameter of the sub-target sphere is calculated to be 1.5 cm using Formula 11.

[0104]

[0105] In step S130, the center position and initial size of the first densest packing cell are determined.

[0106] In one example, the first densest unit is a sphere, centered at the geometric center of the area where the radiotherapy target can be placed. The diameter of the sphere, i.e., the spacing between sub-targets, is 4 cm. Figure 5 As shown in (b), by public

[0107] Calculate using Equation 1.

[0108]

[0109] In step S140, the densest-packed unit is a sphere, and its plane is parallel or perpendicular to the transverse section of the patient's image. A schematic diagram of the three spheres arranged according to the densest-packing method is shown below. Figure 3 As shown, the distance between the spheres is equal in three dimensions. Figure 4 The diagram shows the outline of a sphere drawn from the center of the outermost sphere. The central circle is tangent to the six surrounding circles, indicating a densely packed radiotherapy target area. The center of the sphere generated using the densest packing method is the center of the radiotherapy sub-target area. The radiotherapy sub-target area is arranged at this center according to the required diameter, such as... Figure 5 As shown in (a).

[0110] The number of rows, columns, and layers of the stacked spheres are related to the area (x, y, z) of the radiotherapy target region and the first sphere (x0, y0, z0), calculated using the following formula:

[0111]

[0112]

[0113]

[0114]

[0115]

[0116]

[0117] Wherein, LineNum1, LineNum2, RowNum1, RowNum2, LayerNum1, and LayerNum2 represent the number of columns, rows, and layers of the densest-packed spheres required in the left, right, front, back, top, and bottom directions (in the patient's coordinate system), respectively. d is the diameter of the densest-packed spheres. The densest-packed spheres exhibit spatial repetition between every two layers; the "2" ensures a complete solution space for obtaining the optimal solution during subsequent target area optimization.

[0118] Stacked sphere coordinates (xi ,y i ,z i ), Calculation formula:

[0119]

[0120]

[0121]

[0122] In step S150, the optimization of the radiotherapy target area arrangement, in one example, involves using an optimization method to move the entire target area within the tumor, optimizing and adjusting the initial positions of all radiotherapy sub-target areas to obtain their final positions. While keeping the volume of all target areas constant, the optimization method increases the distance between sub-target areas and the peak-to-valley ratio by optimizing the target area positions.

[0123] In one example, the process is as follows Figure 8 As shown, the optimization method includes the following steps:

[0124] Step 1: Obtain the data of the deployable target area, the center position and size of the first densest stacked unit d = 4cm, and the size of the sub-target area d' = 1.4cm;

[0125] Step 2: n = 1;

[0126] Step 3: Calculate the size d of the closest packing cell. n =d + 0.1 × (n - 1);

[0127] Step 4: Use the closest packing method to generate the initial position of the sub-target area and calculate the initial volume V0 of the sub-target area;

[0128] Step 5: In the domain Δy∈(-d, d), Within the ranges Δα∈(-π, π), Δβ∈(-π, π), and Δγ∈(-π, π), an adaptive simulated annealing method is used to adjust the parameter temperature to control the probability distribution of random numbers, and (x) is randomly generated. i ,y i ,z i ) movement amount (Δx, Δy, Δz, Δα, Δβ, Δγ);

[0129] Step 6: Calculate the optimized target radiotherapy volume V n ;

[0130] Step 7: Determine V n Is it greater than or equal to V0? If so, proceed to step 8 and increase the diameter of the densest packed spheres, i.e., the spacing between spheres in the target area; if not, proceed to step 4.

[0131] Step 8: Determine V nIf the value is greater than V0, and n = n + 1, go to step 3; otherwise, output the position of the radiotherapy sphere (x). i ,y i ,z i The judgment ends.

[0132] In one example, after optimization using the adaptive simulated annealing method, the target spacing increased from 4 cm to 4.3 cm, as shown below. Figure 6 As shown in (b). Combined with Figure 6 As shown in (a), a conventional C-arm accelerator equipped with a 2.5mm multi-leaf collimator is used, and the reverse optimization method is used to design the following: Figure 6 The volumetric rotation intensity-modulated beam schemes with target spacing of 4 cm and 4.3 cm (optimized) are shown. The results indicate that... Figure 6 At the target region level shown, the peak-to-valley ratio increased from 1.99 to 2.32 after optimization, an increase of 16.6%.

[0133] The above describes some specific embodiments of the present invention using the densest spherical packing method and adaptive simulated annealing method to optimize the radiotherapy target area layout as examples. It should be understood that the principles of the present invention are not limited to these embodiments. Rather, the present invention can also be applied to the layout and optimization of radiotherapy target areas of other shapes, such as cylindrical target areas and optimization methods. The application process of dosimetric peak-to-trough ratio evaluation is basically the same as the embodiments described above, and will not be repeated here.

[0134] Figure 7 The functions of each module of the spatial segmentation radiotherapy target placement system shown have been discussed above, so only a brief description is given here.

[0135] like Figure 7 As shown, the spatial segmentation radiotherapy target area layout system includes an input module 10, a sub-target initial position layout module 20, a radiotherapy sub-target optimization module 30, and an output module 40.

[0136] Input module 10 can be used to receive patient radiotherapy data input, which may include data on normal tissue and tumor area. The received radiotherapy data is stored in subtarget initial position arrangement module 20, which may include densest stacking unit arrangement unit 22 and subtarget size determination unit 24. Densest stacking unit arrangement unit 22 is used to analyze the relative positional relationship between normal tissue and tumor target area, obtain the area where radiotherapy target area can be arranged, arrange densest stacking units according to the densest stacking method, and determine the initial position of the densest stacking units. Subtarget size determination unit 24 determines the subtarget size based on the size of the tumor area.

[0137] The radiotherapy sub-target optimization module 30 receives the initial sub-target position, sub-target size, and sub-target spacing generated by the initial sub-target position arrangement module. It sets the optimization target in the optimization target unit 32 and the optimization method in the optimization method unit 34, ultimately generating an optimized radiotherapy sub-target arrangement. In some embodiments, while keeping the volume of all target areas constant, the target area position is optimized using an adaptive simulated annealing method to increase the inter-target distance and the peak-to-valley ratio.

[0138] Finally, the output module 40 can output the layout result. In some embodiments, the output unit 42 can be a planning contour definition unit 42 and a planning contour evaluation unit 44 in the planning system, used for spatial segmentation of the radiotherapy target area editing and evaluation.

[0139] In summary, this embodiment utilizes patient normal tissue and tumor target area data, and arranges more radiotherapy target areas in the area where radiotherapy target areas can be arranged according to the densest stacking method; it also uses optimization methods to optimize the arrangement of radiotherapy target areas, further increasing the number of radiotherapy target areas and maximizing the peak-to-valley ratio.

[0140] Example 3

[0141] This embodiment 3 provides a non-transitory computer-readable storage medium for storing computer instructions. When executed by a processor, the computer instructions implement the spatial segmentation radiotherapy target area arrangement method described above. The method includes:

[0142] The spatially segmented radiotherapy target region is composed of multiple sub-target regions, and the arrangement of the sub-target regions includes:

[0143] Acquire patient radiotherapy data, including data on normal tissue and tumor area, to determine the extent of a spatially segmentable radiotherapy target area;

[0144] Determine the center location and initial size of the first densest packing cell;

[0145] The size of the sub-target area is determined based on the size of the tumor area;

[0146] The initial positions of all sub-target areas for spatial fractionation radiotherapy were determined using the densest packing method.

[0147] The initial positions of all sub-target areas are optimized and adjusted, and the entire system is moved within the tumor to obtain the final positions of all sub-target areas.

[0148] Example 4

[0149] This embodiment 4 provides a computer program product, including a computer program that, when run on one or more processors, is used to implement the spatial segmentation radiotherapy target area arrangement method described above. The method includes:

[0150] The spatially segmented radiotherapy target region is composed of multiple sub-target regions, and the arrangement of the sub-target regions includes:

[0151] Acquire patient radiotherapy data, including data on normal tissue and tumor area, to determine the extent of a spatially segmentable radiotherapy target area;

[0152] Determine the center location and initial size of the first densest packing cell;

[0153] The size of the sub-target area is determined based on the size of the tumor area;

[0154] The initial positions of all sub-target areas for spatial fractionation radiotherapy were determined using the densest packing method.

[0155] The initial positions of all sub-target areas are optimized and adjusted, and the entire system is moved within the tumor to obtain the final positions of all sub-target areas.

[0156] Example 5

[0157] This embodiment 5 provides an electronic device, including: a processor, a memory, and a computer program; wherein, the processor is connected to the memory, and the computer program is stored in the memory. When the electronic device is running, the processor executes the computer program stored in the memory to cause the electronic device to execute instructions for implementing the spatial segmentation radiotherapy target area arrangement method as described above, the method including:

[0158] The spatially segmented radiotherapy target region is composed of multiple sub-target regions, and the arrangement of the sub-target regions includes:

[0159] Acquire patient radiotherapy data, including data on normal tissue and tumor area, to determine the extent of a spatially segmentable radiotherapy target area;

[0160] Determine the center location and initial size of the first densest packing cell;

[0161] The size of the sub-target area is determined based on the size of the tumor area;

[0162] The initial positions of all sub-target areas for spatial fractionation radiotherapy were determined using the densest packing method.

[0163] The initial positions of all sub-target areas are optimized and adjusted, and the entire system is moved within the tumor to obtain the final positions of all sub-target areas.

[0164] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0165] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0166] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0167] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment, whereby a series of operational steps are performed to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0168] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that, based on the technical solutions disclosed in the present invention, various modifications or variations that can be made by those skilled in the art without creative effort should be included within the scope of protection of the present invention.

Claims

1. A method of arranging a spatially fractionated radiotherapy target volume, the spatially fractionated radiotherapy target volume consisting of a plurality of sub-target volumes, characterized in that, The arrangement of the sub-target regions comprises: Obtaining patient radiotherapy data, the radiotherapy data comprising patient normal tissue and tumor region data, to obtain a range of a space-divided radiotherapy target region that can be arranged; Determining a first closest packing unit center position and an initial size; Determining a sub-target region size according to a tumor region size; Determining initial positions of all sub-target regions of the space-divided radiotherapy by using a closest packing method; Optimizing and adjusting the initial positions of all sub-target regions, moving the whole within the tumor, to obtain final positions of all sub-target regions; The closest packing method is used to arrange a plurality of closest packing units, comprising: determining a first closest packing unit, which is arranged at a center of a radiotherapy target region that can be arranged or at any other position inside the center; determining other closest packing units, which are the same in size as the first closest packing unit and are arranged around the first closest packing unit; and obtaining initial positions of centers of the closest packing units, i.e. initial positions of centers of sub-target regions of the space-divided radiotherapy, to arrange the sub-target regions, i.e. the radiotherapy target regions, at the center of the radiotherapy target region that can be arranged or at any other position inside the center; The optimizing and adjusting of the initial positions of all sub-target regions comprises: keeping a target region volume unchanged, optimizing positions of all sub-target regions by using an optimization method, increasing a number of sub-target regions, reducing a size of the sub-target regions, and increasing a peak-valley ratio; or the optimizing and adjusting of the initial positions of all sub-target regions comprises: keeping a target region volume unchanged, optimizing positions of all sub-target regions by using an optimization method, increasing distances between the sub-target regions, and increasing the peak-valley ratio; The optimization method comprises: Step 1: Obtain the data of the region where the radiotherapy target can be arranged, the first most densely packed unit center position, size d, and the sub-target region size ; Step 2: = 1 ; Step 3: Calculate the size of the most densely packed unit or calculate the size of the sub-target region -0.1 ; Step 4: Generate initial positions for sub-target regions, calculate initial volumes for sub-target regions using closest packing method ; Step 5: In the domain (- d, d), (-d, d), (- d, d), (- , ), (- , ), (- , Within this range, an adaptive simulated annealing method is used to adjust the temperature parameter to control the probability distribution of random numbers, randomly generating (…). , , The amount of movement () ); Step 6: Calculate optimized target volume for radiotherapy ; Step 7: Determine whether greater than , if yes, go to Step 8, increase the close-packed sphere diameter, i.e. the target zone sphere spacing; if no, go to Step 4; Step 8: judging whether greater than , if satisfying, = +1, turn to step 3; if not satisfying, output the radiotherapy sphere position (x, y, z), end the judgment. , , ​ 2. The spatially fractionated radiotherapy target volume arrangement method of claim 1, wherein, The radiotherapy target region that can be arranged is obtained by moving in a tumor by a certain distance and avoiding normal tissue; the closest packing unit is smaller in size than the radiotherapy target region that can be arranged; and the sub-target region is the same in shape as the closest packing unit and smaller in size than the closest packing unit.

3. A spatially fractionated radiotherapy target volume arrangement system based on the spatially fractionated radiotherapy target volume arrangement method according to claim 1 or 2, the spatially fractionated radiotherapy target volume being composed of a plurality of sub-target volumes, characterized in that, The method comprises: An obtaining module is configured to obtain patient radiotherapy data, the radiotherapy data comprising patient normal tissue and tumor region data, to obtain a range of a space-divided radiotherapy target region that can be arranged; A radiotherapy target region arrangement module is configured to determine a closest packing first unit center position and an initial size, and to determine initial positions of all sub-target regions of the space-divided radiotherapy by using a closest packing method; A radiotherapy target region size determination module is configured to determine a sub-target region size according to a tumor region size; A radiotherapy target region optimization module is configured to optimize and adjust the initial positions of all sub-target regions, move the whole within the tumor, and obtain final positions of all sub-target regions.

4. A non-transitory computer-readable storage medium, comprising: The non-transitory computer readable storage medium is configured to store computer instructions, which, when executed by a processor, implement the space-divided radiotherapy target region arrangement method according to claim 1 or 2.

5. A computer program product, characterised in that, The computer program, when running on one or more processors, is configured to implement the space-divided radiotherapy target region arrangement method according to claim 1 or 2.

6. An electronic device, comprising: The method comprises: A processor, a memory and a computer program; wherein the processor is connected with the memory, the computer program is stored in the memory, and when the electronic device is running, the processor executes the computer program stored in the memory, so that the electronic device executes instructions for implementing the spatially fractionated radiotherapy target region arrangement method according to claim 1 or 2.

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