Multi-energy-level multi-machine-head dose optimization method and device, equipment and storage medium

Abstract

The invention discloses a multi-energy-level multi-machine-head dose optimization method, device and equipment and a storage medium, and the method comprises the steps: setting a machine head included angle and an irradiation mode based on target region distribution, and determining a radiation field set; aiming at each radiation field, based on ray path organization characteristics of the radiation field, by calculating correlation between a percentage depth dose curve and ideal dose distribution, screening an optimal irradiation energy level; calculating a dose deposition matrix based on the optimal energy level of each radiation field, and constructing an optimization model to perform joint optimization on all radiation field intensity graphs; segmenting the optimized intensity distribution, calculating an actual delivery dose, reducing the difference between the actual delivery dose and an ideal dose through iterative optimization, and finally outputting a dose optimization parameter. According to the invention, through combination of multi-machine-head cooperative irradiation and multi-energy-level adaptive selection, the treatment efficiency is significantly improved, and the dose distribution is optimized.

Description

Technical Field

[0001] This invention belongs to the field of radiotherapy technology, specifically relating to a multi-level, multi-head dose optimization method, apparatus, equipment, and storage medium. Background Technology

[0002] When performing radiotherapy on tumors (i.e., the target area), in order to protect healthy tissues from damage, a multi-leaf collimator (MLC) is generally used to adjust the beam irradiation range and intensity, so as to achieve radiotherapy with adjustable beam intensity, namely intensity-modulated radiotherapy (IMRT).

[0003] In radiotherapy, the energy selection of the photon beam has a significant impact on dose distribution. Low-energy photons (e.g., 1MV to 6MV) have a high surface dose but weak penetration, and the dose decreases rapidly with depth, making them suitable for superficial tumors or thin tissue areas. High-energy photons (e.g., 10MV to 18MV) have strong penetration, with the maximum dose point occurring in deeper subcutaneous locations, resulting in a relatively low surface dose on the skin, making them suitable for obese patients or deep tumors.

[0004] Current intensity-modulated radiotherapy (IMRT) techniques have significant drawbacks: Firstly, due to the limitations of different photon energy levels, no single radiation energy can meet the treatment needs of all patients, tumor locations, and depths. In clinical practice, it is necessary to change the radiation energy level by replacing the radionuclide head, which is cumbersome and time-consuming, reducing treatment efficiency and increasing the patient's treatment time. Secondly, within the same radiotherapy plan, current technology does not use different energy levels to adapt to target areas at different angles and depths, resulting in suboptimal dose deposition and difficulty in achieving optimal treatment effects. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention proposes a multi-level, multi-head dose optimization method, apparatus, device, and storage medium.

[0006] To achieve the above objectives, the technical solution of the present invention is as follows:

[0007] In a first aspect, the present invention discloses a dose optimization method for a multi-level, multi-head radiotherapy device, used to optimize the dose of radiotherapy through at least two heads, specifically including the following steps:

[0008] Step S1: Based on the target area distribution, set the relative angle between at least two heads, and select either multi-head synchronous irradiation or single-head irradiation mode to determine the set of firing fields to be optimized;

[0009] In the multi-head synchronous illumination mode, the firing fields of each head are coordinated to illuminate the target area at a fixed angle.

[0010] Step S2: For each radiation field in the radiation field set, based on the tissue characteristics along its ray path, the optimal irradiation energy level is selected from multiple irradiation energy levels by calculating the correlation between its percentage depth dose curve and the preset ideal dose distribution.

[0011] Step S3: Based on the optimal irradiation energy level of each field, calculate the corresponding dose deposition matrix and construct an intensity optimization model. Perform joint optimization on the intensity maps of all fields in the field set to obtain the optimized intensity distribution.

[0012] Step S4: Segment the optimized intensity distribution, calculate the actual delivery dose after segmentation, and optimize it iteratively;

[0013] Step S5: Compare the difference between the actual delivered dose and the ideal dose corresponding to the optimized intensity distribution, and iteratively optimize the segmentation parameters based on the difference until the difference between the two meets the preset requirements, thereby outputting the final dose optimization parameters.

[0014] Based on the above technical solution, the following improvements can be made:

[0015] As a preferred approach, the specific steps for selecting the optimal irradiation energy level for each radiation field in step S2 are as follows:

[0016] Step S2.1: For the ray path of the current radiation field, calculate the effective path length by integrating its relative electron density, and combine it with the tumor size to establish a phantom equivalent to the target area in the equivalent water phantom;

[0017] Step S2.2: Obtain the percentage depth-dose curve for each candidate irradiation level for this radiation field;

[0018] Step S2.3: Define four key dose calculation points on each percentage depth dose curve: the incident point of the radiation entering the human body, the incident point of the radiation entering the target area, the exit point of the radiation leaving the target area, and the exit point of the radiation leaving the human body.

[0019] Step S2.4: Based on the preset ideal dose distribution, assign ideal dose values ​​to the four key points;

[0020] Step S2.5: Calculate the degree of matching between the percentage depth dose curve and the ideal dose distribution at each candidate energy level using the following correlation formula:

[0021]

[0022] in:

[0023] This is the ideal dose value;

[0024] This is the actual dose value;

[0025] The weighting coefficient for the i-th critical dose calculation point;

[0026] Step S2.6: Compare the correlation coefficients (CC) calculated from all candidate energy levels, and select the irradiation energy level with the largest CC value as the optimal irradiation energy level for the radiation field.

[0027] As a preferred approach, step S3 achieves joint optimization of the intensity maps of all shooting fields in the shooting field set by constructing and solving the following intensity optimization model:

[0028] ;

[0029] ;

[0030] Where: x k Let be the intensity distribution vector to be optimized for the k-th field;

[0031] D k The dose deposition matrix is ​​calculated based on the optimal irradiation energy level of the k-th radiation field;

[0032] K represents the total number of shooting fields in the shooting field set;

[0033] The goal of the intensity optimization model is to optimize the intensity distribution vector x of each field. k , so that the objective function f obj To achieve the optimal, thus obtaining the optimized intensity distribution.

[0034] As a preferred option, in step S4, the sliding window method is used to segment the optimized intensity distribution.

[0035] Secondly, this invention discloses a multi-level, multi-head dose optimization device for radiotherapy equipment equipped with at least two heads, which optimizes the dose of radiotherapy through at least two heads, specifically including:

[0036] The firing field configuration module is used to set the relative angle between at least two heads based on the target area distribution, and select the multi-head synchronous irradiation or single-head irradiation mode to determine the set of firing fields to be optimized.

[0037] In the multi-head synchronous illumination mode, the firing fields of each head are coordinated to illuminate the target area at a fixed angle.

[0038] The energy level optimization module is used to select the optimal irradiation energy level for each irradiation field in the irradiation field set based on the tissue characteristics along its ray path by calculating the correlation between its percentage depth dose curve and the preset ideal dose distribution.

[0039] The intensity optimization module is used to calculate the corresponding dose deposition matrix based on the optimal irradiation energy level of each field, and to construct an intensity optimization model to jointly optimize the intensity maps of all fields in the field set to obtain the optimized intensity distribution.

[0040] The segmentation calculation module is used to segment the optimized intensity distribution and calculate the actual delivery dose after segmentation.

[0041] The iterative optimization module is used to compare the difference between the actual delivered dose and the ideal dose corresponding to the optimized intensity distribution, and iteratively optimize the segmentation parameters based on the difference until the difference between the two meets the preset requirements, thereby outputting the final dose optimization parameters.

[0042] As a preferred option, the energy level optimization module is used to select the optimal irradiation energy level for each radiation field, specifically including:

[0043] The path parameter calculation unit is used to calculate the effective path length by integrating the relative electron density of the ray path for the current radiation field, and, in combination with the tumor size, to establish a phantom equivalent to the target area in the equivalent water phantom.

[0044] The dose curve acquisition unit is used to acquire the percentage depth dose curve of the radiation field at each candidate irradiation energy level.

[0045] The key point definition unit is used to define four key dose calculation points on each percentage depth dose curve: the incident point of the radiation entering the human body, the incident point of the radiation entering the target area, the exit point of the radiation leaving the target area, and the exit point of the radiation leaving the human body.

[0046] The ideal dose distribution unit is used to assign ideal dose values ​​to four key points based on a preset ideal dose distribution.

[0047] The correlation calculation unit is used to calculate the degree of matching between the percentage depth dose curve and the ideal dose distribution at each candidate energy level using the following correlation formula:

[0048]

[0049] in:

[0050] This is the ideal dose value;

[0051] This is the actual dose value;

[0052] The weighting coefficient for the i-th critical dose calculation point;

[0053] The energy level decision unit is used to compare the correlation coefficients (CC) calculated from all candidate energy levels and select the irradiation energy level with the largest CC value as the optimal irradiation energy level for the radiation field.

[0054] As a preferred approach, the strength optimization module achieves joint optimization of the strength maps of all shooting fields in the shooting field set by constructing and solving the following strength optimization model:

[0055] ;

[0056] ;

[0057] Where: x k Let be the intensity distribution vector to be optimized for the k-th field;

[0058] D k The dose deposition matrix is ​​calculated based on the optimal irradiation energy level of the k-th radiation field;

[0059] K represents the total number of shooting fields in the shooting field set;

[0060] The goal of the intensity optimization model is to optimize the intensity distribution vector x of each field. k , so that the objective function f obj To achieve the optimal, thus obtaining the optimized intensity distribution.

[0061] As a preferred approach, the segmentation calculation module uses a sliding window method to segment the optimized intensity distribution.

[0062] Thirdly, the present invention discloses a computing device, comprising:

[0063] One or more processors;

[0064] Memory;

[0065] And one or more programs, wherein the one or more programs are stored in memory and configured to be executed by one or more processors, and the one or more programs include instructions for any of the above-described multi-level multi-head dose optimization methods.

[0066] Fourthly, the present invention discloses a storage medium storing one or more computer-readable programs, the one or more programs including instructions adapted to be loaded by a memory and executed for any of the above-described multi-level multi-head dose optimization methods.

[0067] This invention discloses a multi-level, multi-head dose optimization method, apparatus, device, and storage medium, which have the following beneficial effects:

[0068] First, this invention uses at least two fixed-angled headpieces to achieve synchronous irradiation, changing traditional sequential irradiation to parallel irradiation, which significantly shortens the total treatment time. Simultaneously, the multi-angle radiation field set is jointly optimized through an intensity optimization model, ensuring that the dose distribution is highly conformal to the target area, thereby improving the overall accuracy and quality of the treatment plan.

[0069] Secondly, this invention innovatively proposes a correlation coefficient scoring standard to dynamically select the optimal irradiation energy level for each radiation field angle based on its specific path characteristics. This multi-energy-level hybrid irradiation mode enables intelligent dose distribution according to target depth, significantly improving target dose coverage and effectively reducing irradiation damage to surrounding normal tissues. Attached Figure Description

[0070] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0071] Figure 1 The flowchart illustrates the multi-level, multi-head dose optimization method provided in this embodiment of the invention. Detailed Implementation

[0072] The preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0073] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0074] The expression “includes” is an “open-ended” expression, which means that there is a corresponding component or step, and should not be interpreted as excluding additional components or steps.

[0075] To achieve the objectives of this invention, in some embodiments of a multi-level, multi-head dose optimization method, it is used in a radiotherapy device configured with two heads to optimize the radiotherapy dose through the two heads. The method specifically includes the following steps: Figure 1 As shown:

[0076] Step S101: Based on the target area distribution, set the relative angle between the two heads, and select the multi-head synchronous irradiation or single-head irradiation mode to determine the set of firing fields to be optimized;

[0077] In the multi-head synchronous illumination mode, the firing fields of each head are coordinated to illuminate the target area at a fixed angle.

[0078] Step S102: For each radiation field in the radiation field set, based on the tissue characteristics along its ray path, the optimal irradiation energy level is selected from multiple irradiation energy levels by calculating the correlation between its percentage depth dose curve and the preset ideal dose distribution.

[0079] Step S103: Based on the optimal irradiation energy level of each field, calculate the corresponding dose deposition matrix and construct an intensity optimization model. Perform joint optimization on the intensity maps of all fields in the field set to obtain the optimized intensity distribution.

[0080] Step S104: Segment the optimized intensity distribution and calculate the actual delivery dose after segmentation;

[0081] Step S105: Compare the difference between the actual delivered dose and the ideal dose corresponding to the optimized intensity distribution, and iteratively optimize the segmentation parameters based on the difference until the difference between the two meets the preset requirements, thereby outputting the final dose optimization parameters.

[0082] Each of the above steps will be explained in detail below.

[0083] Step S101 adds a firing field. Since there are two camera heads, two firing fields that are simultaneously irradiated at a fixed angle can be added. Of course, you can also use only one camera head for irradiation.

[0084] The specific steps for selecting the optimal irradiation energy level for each radiation field in step S102 are as follows:

[0085] Step S102.1: For the ray path of the current radiation field, calculate the effective path length (EP) by integrating its relative electron density, and combine it with the tumor size (TS) to establish a phantom equivalent to the target area in the equivalent water phantom;

[0086] Based on the conversion of CT value to relative electron density, and by integrating and summing along the ray path, the formula for calculating EP is as follows:

[0087] ;

[0088] in:

[0089] The relative electron density along ray path I;

[0090] It represents a tiny length element on the path;

[0091] The size of the tumor is represented by the effective path length along the path of the ray entering and exiting the target area. A spherical phantom with a diameter equal to the tumor size TS is placed in a water phantom. The distance between the center of the sphere and the incident point of the water phantom is the effective path length. The ideal dose is set to... The actual dose is set as Two doses were obtained using the Monte Carlo dosing algorithm;

[0092] Step S102.2: Obtain the percentage depth dose curves (PDDs) of the field at each candidate irradiation level (e.g., 1MV, 6MV, and 10MV).

[0093] Step S102.3: Define four key dose calculation points on each percentage depth dose curve: the incident point where the radiation enters the human body (point 1), the incident point where the radiation enters the target area (point 2), the exit point where the radiation leaves the target area (point 3), and the exit point where the radiation leaves the human body (point 4).

[0094] Step S102.4: Based on the preset ideal dose distribution, assign ideal dose values ​​to the four key points;

[0095] Among them, the ideal dose value of the two points entering and leaving the target area (i.e., points 2 and 3) is 100% of the target area dose, and the ideal dose value of the two points entering and leaving the human body (i.e., points 1 and 4) is 10% of the target area dose.

[0096] Step S102.5: Calculate the degree of matching between the percentage depth dose curve and the ideal dose distribution at each candidate energy level using the following correlation formula:

[0097]

[0098] in:

[0099] This is the ideal dose value;

[0100] This is the actual dose value;

[0101] The weighting coefficient for the i-th critical dose calculation point;

[0102] For example: ω(1)=0.5, ω(2)=ω(3)=ω(4)=1.

[0103] Step S102.6: Compare the correlation coefficients (CC) calculated from all candidate energy levels, and select the irradiation energy level with the largest CC value as the optimal irradiation energy level for the radiation field.

[0104] Furthermore, step S103 achieves joint optimization of the intensity maps of all shooting fields in the shooting field set by constructing and solving the following intensity optimization model:

[0105] ;

[0106] ;

[0107] Where: x k Let be the intensity distribution vector to be optimized for the k-th field;

[0108] D k The dose deposition matrix is ​​calculated based on the optimal irradiation energy level of the k-th radiation field;

[0109] K is the total number of firing fields in the firing field set (which includes the firing fields of two heads that are simultaneously irradiated).

[0110] The goal of the intensity optimization model is to optimize the intensity distribution vector x of each field. k , so that the objective function f obj To achieve the optimal, thus obtaining the optimized intensity distribution.

[0111] Furthermore, in step S104, the sliding window (SW) method is used to segment the optimized intensity distribution, as shown in the following model:

[0112]

[0113] in:

[0114] This is the intensity value;

[0115] Dose rate;

[0116] This is the grid width;

[0117] For blade velocity;

[0118] To divide the field intensity map into row and column numbers, , These represent the rows and columns of the segmented field intensity map. These refer to the optimized ideal strength and the segmented actual strength, respectively.

[0119] The actual delivery dose is calculated using the Monte Carlo dosing algorithm.

[0120] Furthermore, step S105 uses the difference between the optimized ideal dose and the segmented actual delivery dose to iteratively optimize the segmentation, narrowing the distance between the two until the preset requirements are met, thereby outputting the final dose optimization parameters.

[0121] This invention discloses a multi-level, multi-head dose optimization method for intensity-modulated radiotherapy (IMRT), which has the following significant advantages compared to existing technologies:

[0122] First, it significantly improves treatment efficiency and precision.

[0123] By configuring at least two irradiation heads and supporting multi-head synchronous irradiation, this method enables simultaneous irradiation of the target area from multiple angles. Compared to traditional single-head sequential irradiation, this parallel irradiation method significantly shortens the total treatment time, reduces the risk of errors caused by patient repositioning, and improves the turnover rate of the treatment bed. Simultaneously, multi-angle coordinated irradiation provides a basis for generating more complex dose distributions, thereby improving treatment accuracy and conformity.

[0124] Second, it enables individualized and adaptive energy level selection to optimize dose distribution.

[0125] One of the core innovations of this method lies in breaking the limitations of traditional single-energy-level irradiation and proposing to dynamically select the optimal irradiation energy level for each radiation field path. By establishing an equivalent phantom based on the effective path length and tumor size, and using a specific correlation coefficient formula to quantitatively evaluate the matching degree between different energy levels and the ideal dose distribution, this method can automatically select the most suitable radiation energy (e.g., 1MV, 6MV, 10MV) for target areas at different depths and angles. This makes the dose distribution more intelligent, with high energy levels used to penetrate deeper tissues and low energy levels used for superficial tumors, thereby achieving better target area dose coverage and better protection of healthy normal tissues overall.

[0126] Third, it enhances adaptability to complex clinical situations.

[0127] By combining the advantages of multiple heads and multiple energy levels, this method broadens the scope of clinical applications. Whether for deep tumors in obese patients, superficial tumors in lean patients, or complex target areas with irregular shapes and intersecting with critical organs, this method can develop more targeted and optimized treatment plans through flexible head configurations and energy level combinations, demonstrating excellent clinical adaptability.

[0128] In other embodiments, the present invention discloses a multi-level, multi-head dose optimization device for radiotherapy equipment configured with at least two heads, which optimizes the dose of radiotherapy through at least two heads, specifically including:

[0129] The firing field configuration module is used to set the relative angle between at least two heads based on the target area distribution, and select the multi-head synchronous irradiation or single-head irradiation mode to determine the set of firing fields to be optimized.

[0130] In the multi-head synchronous illumination mode, the firing fields of each head are coordinated to illuminate the target area at a fixed angle.

[0131] The energy level optimization module is used to select the optimal irradiation energy level for each irradiation field in the irradiation field set based on the tissue characteristics along its ray path by calculating the correlation between its percentage depth dose curve and the preset ideal dose distribution.

[0132] The intensity optimization module is used to calculate the corresponding dose deposition matrix based on the optimal irradiation energy level of each field, and to construct an intensity optimization model to jointly optimize the intensity maps of all fields in the field set to obtain the optimized intensity distribution.

[0133] The segmentation calculation module is used to segment the optimized intensity distribution and calculate the actual delivery dose after segmentation.

[0134] The iterative optimization module is used to compare the difference between the actual delivered dose and the ideal dose corresponding to the optimized intensity distribution, and iteratively optimize the segmentation parameters based on the difference until the difference between the two meets the preset requirements, thereby outputting the final dose optimization parameters.

[0135] Furthermore, the energy level optimization module is used to select the optimal irradiation energy level for each radiation field, specifically including:

[0136] The path parameter calculation unit is used to calculate the effective path length by integrating the relative electron density of the ray path for the current radiation field, and, in combination with the tumor size, to establish a phantom equivalent to the target area in the equivalent water phantom.

[0137] The dose curve acquisition unit is used to acquire the percentage depth dose curve of the radiation field at each candidate irradiation energy level.

[0138] The key point definition unit is used to define four key dose calculation points on each percentage depth dose curve: the incident point of the radiation entering the human body, the incident point of the radiation entering the target area, the exit point of the radiation leaving the target area, and the exit point of the radiation leaving the human body.

[0139] The ideal dose distribution unit is used to assign ideal dose values ​​to four key points based on a preset ideal dose distribution.

[0140] The correlation calculation unit is used to calculate the degree of matching between the percentage depth dose curve and the ideal dose distribution at each candidate energy level using the following correlation formula:

[0141]

[0142] in:

[0143] This is the ideal dose value;

[0144] This is the actual dose value;

[0145] The weighting coefficient for the i-th critical dose calculation point;

[0146] The energy level decision unit is used to compare the correlation coefficients (CC) calculated from all candidate energy levels and select the irradiation energy level with the largest CC value as the optimal irradiation energy level for the radiation field.

[0147] Furthermore, the strength optimization module achieves joint optimization of the strength maps of all shooting fields in the shooting field set by constructing and solving the following strength optimization model:

[0148] ;

[0149] ;

[0150] Where: x k Let be the intensity distribution vector to be optimized for the k-th field;

[0151] D k The dose deposition matrix is ​​calculated based on the optimal irradiation energy level of the k-th radiation field;

[0152] K represents the total number of shooting fields in the shooting field set;

[0153] The goal of the intensity optimization model is to optimize the intensity distribution vector x of each field. k , so that the objective function f obj To achieve the optimal, thus obtaining the optimized intensity distribution.

[0154] Furthermore, the segmentation calculation module uses a sliding window method to segment the optimized intensity distribution.

[0155] Furthermore, it should be noted that the multi-level multi-head dose optimization device provided in the above embodiments is only illustrated by the division of the above functional modules when performing dose optimization. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the multi-level multi-head dose optimization device can be divided into different functional modules to complete all or part of the functions described above.

[0156] Furthermore, the multi-level multi-head dose optimization device and the multi-level multi-head dose optimization method provided in the above embodiments belong to the same concept, and their specific implementation process can be found in the method embodiments, which will not be repeated here.

[0157] In other embodiments, the present invention discloses a computing device comprising:

[0158] One or more processors;

[0159] Memory;

[0160] And one or more programs, wherein the one or more programs are stored in memory and configured to be executed by one or more processors, and the one or more programs include instructions for any of the above-described multi-level multi-head dose optimization methods.

[0161] In other embodiments, the present invention discloses a storage medium storing one or more computer-readable programs, the programs including instructions adapted to be loaded by memory and executed for any of the above-described multi-level multi-head dose optimization methods.

[0162] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the present invention. Various changes and modifications can be made to the present invention without departing from its spirit and scope. All such changes and modifications fall within the scope of the present invention as claimed, which is defined by the appended claims and their equivalents.

Claims

1. A dosage optimization method for multi-level, multi-head devices, characterized in that, A radiotherapy device configured with at least two access heads, wherein the dose optimization of radiotherapy is achieved through the at least two access heads, specifically includes the following steps: Step S1: Based on the target area distribution, set the relative angle between the at least two heads, and select the multi-head synchronous irradiation or single-head irradiation mode to determine the set of firing fields to be optimized; In the multi-head synchronous illumination mode, the firing fields of each head are coordinated to illuminate the target area at a fixed angle. Step S2: For each radiation field in the radiation field set, based on the tissue characteristics along its ray path, the optimal irradiation energy level is selected from multiple irradiation energy levels by calculating the correlation between its percentage depth dose curve and the preset ideal dose distribution. Step S3: Based on the optimal irradiation energy level of each radiation field, calculate the corresponding dose deposition matrix and construct an intensity optimization model. Perform joint optimization on the intensity maps of all radiation fields in the radiation field set to obtain the optimized intensity distribution. Step S4: Segment the optimized intensity distribution and calculate the actual delivery dose after segmentation; Step S5: Compare the difference between the actual delivered dose and the ideal dose corresponding to the optimized intensity distribution, and iteratively optimize the segmentation parameters based on the difference until the difference between the two meets the preset requirements, thereby outputting the final dose optimization parameters.

2. The dosage optimization method according to claim 1, characterized in that, The specific steps for selecting the optimal irradiation energy level for each radiation field in step S2 are as follows: Step S2.1: For the ray path of the current radiation field, calculate the effective path length by integrating its relative electron density, and combine it with the tumor size to establish a phantom equivalent to the target area in the equivalent water phantom; Step S2.2: Obtain the percentage depth-dose curve for each candidate irradiation level for this radiation field; Step S2.3: Define four key dose calculation points on each percentage depth dose curve: the incident point of the radiation entering the human body, the incident point of the radiation entering the target area, the exit point of the radiation leaving the target area, and the exit point of the radiation leaving the human body. Step S2.4: Based on the preset ideal dose distribution, assign ideal dose values ​​to the four key points; Step S2.5: Calculate the degree of matching between the percentage depth dose curve and the ideal dose distribution at each candidate energy level using the following correlation formula: in: This is the ideal dose value; This is the actual dose value; The weighting coefficient for the i-th critical dose calculation point; Step S2.6: Compare the correlation coefficients (CC) calculated from all candidate energy levels, and select the irradiation energy level with the largest CC value as the optimal irradiation energy level for the radiation field.

3. The dosage optimization method according to claim 1, characterized in that, Step S3 achieves joint optimization of the intensity maps of all shooting fields in the shooting field set by constructing and solving the following intensity optimization model: ； ； Where: x k Let be the intensity distribution vector to be optimized for the k-th field; D k The dose deposition matrix is ​​calculated based on the optimal irradiation energy level of the k-th radiation field; K is the total number of shooting fields in the set of shooting fields; The goal of the intensity optimization model is to optimize the intensity distribution vector x of each firing field. k , so that the objective function f obj The optimal intensity distribution is obtained by achieving the optimal level.

4. The dosage optimization method according to claim 1, characterized in that, In step S4, the optimized intensity distribution is segmented using a sliding window method.

5. A multi-level, multi-head dose optimization device, characterized in that, A radiotherapy device configured with at least two access heads, wherein the at least two access heads are used to optimize the dose of radiotherapy, specifically including: The firing field configuration module is used to set the relative angle between the at least two heads based on the target area distribution, and select the multi-head synchronous irradiation or single-head irradiation mode to determine the set of firing fields to be optimized. In the multi-head synchronous illumination mode, the firing fields of each head are coordinated to illuminate the target area at a fixed angle. The energy level optimization module is used to select the optimal irradiation energy level for each irradiation field in the set of irradiation fields based on the tissue characteristics along its ray path and by calculating the correlation between its percentage depth dose curve and the preset ideal dose distribution. The intensity optimization module is used to calculate the corresponding dose deposition matrix based on the optimal irradiation energy level of each field, and to construct an intensity optimization model to jointly optimize the intensity maps of all fields in the field set to obtain the optimized intensity distribution. The segmentation calculation module is used to segment the optimized intensity distribution and calculate the actual delivery dose after segmentation. The iterative optimization module is used to compare the difference between the actual delivered dose and the ideal dose corresponding to the optimized intensity distribution, and iteratively optimize the segmentation parameters based on the difference until the difference between the two meets the preset requirements, thereby outputting the final dose optimization parameters.

6. The dosage optimization device according to claim 5, characterized in that, The energy level optimization module is used to select the optimal irradiation energy level for each radiation field, specifically including: The path parameter calculation unit is used to calculate the effective path length by integrating the relative electron density of the ray path for the current radiation field, and, in combination with the tumor size, to establish a phantom equivalent to the target area in the equivalent water phantom. The dose curve acquisition unit is used to acquire the percentage depth dose curve of the radiation field at each candidate irradiation energy level. The key point definition unit is used to define four key dose calculation points on each percentage depth dose curve: the incident point of the radiation entering the human body, the incident point of the radiation entering the target area, the exit point of the radiation leaving the target area, and the exit point of the radiation leaving the human body. An ideal dose distribution unit is used to assign ideal dose values ​​to the four key points based on a preset ideal dose distribution. The correlation calculation unit is used to calculate the degree of matching between the percentage depth dose curve and the ideal dose distribution at each candidate energy level using the following correlation formula: in: This is the ideal dose value; This is the actual dose value; The weighting coefficient for the i-th critical dose calculation point; The energy level decision unit is used to compare the correlation coefficients (CC) calculated from all candidate energy levels and select the irradiation energy level with the largest CC value as the optimal irradiation energy level for the radiation field.

7. The dosage optimization device according to claim 5, characterized in that, The intensity optimization module achieves joint optimization of the intensity maps of all shooting fields in the shooting field set by constructing and solving the following intensity optimization model: ； ； Where: x k Let be the intensity distribution vector to be optimized for the k-th field; D k The dose deposition matrix is ​​calculated based on the optimal irradiation energy level of the k-th radiation field; K is the total number of shooting fields in the set of shooting fields; The goal of the intensity optimization model is to optimize the intensity distribution vector x of each firing field. k , so that the objective function f obj The optimal intensity distribution is obtained by achieving the optimal level.

8. The dosage optimization device according to claim 5, characterized in that, The segmentation calculation module uses a sliding window method to segment the optimized intensity distribution.

9. A computing device, characterized in that, include: One or more processors; Memory; And one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by one or more processors, and the one or more programs include instructions for the multi-level multi-head dose optimization method as described in any of claims 1-4.

10. A storage medium, characterized in that, The storage medium stores one or more computer-readable programs, the programs including instructions adapted to be loaded by memory and executed as described in any of claims 1-4 for dose optimization of the multi-level multi-head method.

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