Radiation delivery plan quality control method and device and computer storage medium

Abstract

The invention relates to a radiation delivery plan quality control method and device and a computer storage medium, and the method comprises the steps: obtaining a second radiation delivery plan through combining error data with a first radiation delivery plan, determining the plan passing rate of the first radiation delivery plan and the second radiation delivery plan, and carrying out the quality control of the radiation delivery plan based on the plan passing rate. The probability that the first radiation delivery plan can pass the quality control is determined, various errors possibly existing in actual execution are considered in the quality control process of the radiation delivery plan, the problem that the quality control precision of the radiation treatment plan is low is solved, the accuracy and reliability of the quality control method are improved, and the precision of clinical quality control is ensured.

Description

Technical Field

[0001] The present application relates to the technical field of quality control for radiation delivery planning, and particularly to a method, device, computer device, and storage medium for quality control of radiation delivery planning. Background Art

[0002] Radiation delivery (such as radiotherapy, radiation flaw detection, radiation processing, radiation testing, etc.) requires a treatment plan for planning the delivery location and amount of radiation (i.e., dose). To ensure that the desired effect can be achieved in radiation delivery, quality control (also known as quality assurance (QA)) of the radiation delivery plan is required to monitor whether the radiation delivery plan can meet the requirements.

[0003] As an example, radiotherapy is one of the common means for treating tumors. The quality of the radiotherapy plan has a crucial impact on the treatment effect. When the target dose deviates from the prescribed dose by more than a certain percentage, it is possible to cause the primary tumor to get out of control or increase radiation complications, affecting the safety of radiotherapy. Therefore, quality control of the radiation delivery plan is required during treatment.

[0004] In related technologies, when performing quality control on a radiation delivery plan, physical phantoms are usually used for quality control, or the in-built electronic imaging device of the accelerator is used for quality control, or quality control software is used for secondary dose verification. Physical phantoms quality control means using a dose measurement device from a third-party manufacturer to measure the point dose or surface dose in the phantom, and then comparing the measured value with the calculated value to perform quality control based on the comparison result. For physical phantoms quality control and using the in-built electronic imaging device of the accelerator for quality control, the accuracy of quality control is usually poor, and the ability to assist in error analysis is weak. It is impossible to trace the key causes of errors in quality control and relies on empirical data for judgment, resulting in low efficiency of quality control. Moreover, using the in-built electronic imaging device of the accelerator for quality control is limited by the actual size of the electronic imaging device, resulting in some plans with large radiation fields that cannot use the electronic imaging device for quality control. Using quality control software for plan quality control mainly involves performing secondary dose calculation on the original radiation delivery plan through the quality control software, and judging whether the original plan can pass quality control according to the preset plan pass rate standard by comparing the dose distribution or monitor units obtained from the original plan and the secondary calculation. Using quality control software for plan quality control does not require occupying the accelerator and can directly calculate the dose distribution in the actual patient image. However, due to errors in the actual process of the accelerator when executing the plan, the quality control accuracy is affected.

[0005] Currently, for the problem of low quality control accuracy in radiotherapy plans in related technologies, no effective solution has been proposed. Summary of the Invention

[0006] Based on this, it is necessary to provide a radiotherapy delivery plan quality control method, device, computer device, and storage medium that can improve the quality control accuracy of radiotherapy plans for the above-mentioned technical problems.

[0007] In a first aspect, the present application provides a radiotherapy delivery plan quality control method. The method includes:

[0008] Combining error data with a first radiotherapy delivery plan to obtain a second radiotherapy delivery plan;

[0009] Determining the plan passing rates of the first radiotherapy delivery plan and the second radiotherapy delivery plan; and

[0010] Based on the plan passing rates, determining the probability that the first radiotherapy delivery plan can pass quality control.

[0011] In one embodiment, the error data includes one or more of gantry angle error data, multi-leaf collimator in-position error data, monitor unit error data, and setup error data.

[0012] In one embodiment, combining error data with a first radiotherapy delivery plan includes:

[0013] Determining first error data;

[0014] Discretizing the first error data to obtain second error data; and

[0015] Combining the second error data with the first radiotherapy delivery plan.

[0016] In one embodiment, discretizing the first error data to obtain second error data includes:

[0017] Setting the discretization parameters of the first error data, where the discretization parameters include one or more of a discretization allowable range, the number of discretizations, and the discretized data distribution form.

[0018] In one embodiment, discretizing the first error data to obtain second error data further includes:

[0019] Within the discretization allowable range of the first error data, discretizing the first error data according to the discretized data distribution form to obtain the same number of the second error data as the number of discretizations.

[0020] In one embodiment, combining error data with a first radiotherapy delivery plan to obtain a second radiotherapy delivery plan includes:

[0021] Update the parameters corresponding to the error data in the first radiation delivery plan according to the error data to obtain the second radiation delivery plan.

[0022] In one embodiment, determining the plan passing rates of the first radiation delivery plan and the second radiation delivery plan includes:

[0023] Set the first preset range, where the first preset range includes a distance deviation range and a dose deviation range;

[0024] Calculate the distance deviation and dose deviation between the first radiation delivery plan and the second radiation delivery plan; and

[0025] Determine the plan passing rates of the first radiation delivery plan and the second radiation delivery plan by calculating whether the distance deviation is within the distance deviation range and / or whether the dose deviation is within the dose deviation range.

[0026] In one embodiment, obtaining the probability that the first radiation delivery plan can pass quality control according to the plan passing rate includes:

[0027] Determine a target radiation delivery plan from the first radiation delivery plan and the second radiation delivery plan, where the plan passing rate of the target radiation delivery plan is greater than or equal to a preset threshold;

[0028] Calculate the proportion of the number of the target radiation delivery plans in the total number of the first radiation delivery plan and the second radiation delivery plan; and

[0029] Determine the probability that the first radiation delivery plan can pass quality control according to the proportion.

[0030] In a second aspect, the present application further provides a radiation delivery plan quality control device. The device includes:

[0031] An error combination module, configured to combine error data with a first radiation delivery plan to obtain a second radiation delivery plan;

[0032] A plan passing rate calculation module, configured to determine the plan passing rates of the first radiation delivery plan and the second radiation delivery plan;

[0033] A probability calculation module, configured to determine the probability that the first radiation delivery plan can pass quality control based on the plan passing rate.

[0034] In a third aspect, the present application further provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0035] Combine the error data with the first radiation delivery plan to obtain a second radiation delivery plan;

[0036] Determine the planned passing rates of the first radiation delivery plan and the second radiation delivery plan; and

[0037] Based on the planned passing rates, determine the probability that the first radiation delivery plan can pass quality control.

[0038] The above radiation delivery plan quality control method, device and computer storage medium combine error data with the first radiation delivery plan to obtain a second radiation delivery plan, determine the planned passing rates of the first radiation delivery plan and the second radiation delivery plan, and based on the planned passing rates, determine the probability that the first radiation delivery plan can pass quality control. By considering various errors that may exist during actual execution in the process of quality control of the radiation delivery plan, it solves the problem of low quality control accuracy of the radiotherapy plan, improves the accuracy and reliability of the quality control method, and ensures the accuracy of clinical quality control. Brief Description of the Drawings

[0039] Figure 1 It is an application environment diagram of the radiation delivery plan quality control method in an embodiment;

[0040] Figure 2 It is a flowchart of the radiation delivery plan quality control method in an embodiment;

[0041] Figure 3 It is an overall flowchart of the radiation delivery plan quality control method in an embodiment;

[0042] Figure 4 It is a structural block diagram of the radiation delivery plan quality control device in an embodiment;

[0043] Figure 5 It is an internal structure diagram of a computer device in an embodiment. Detailed Description of the Embodiments

[0044] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0045] The radiation delivery plan quality control method provided by the embodiments of the present application can be applied as follows Figure 1In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or can be placed on the cloud or other network servers. Among them, the terminal 102 can be, but is not limited to, various personal computers, laptop computers, smart phones, and tablet computers. The server 104 can be implemented by an independent server or a server cluster composed of multiple servers.

[0046] In one embodiment, as Figure 2 shown, a method for quality control of a radiation delivery plan is provided, including the following steps:

[0047] Step S202, combining the error data with the first radiation delivery plan to obtain a second radiation delivery plan. The error data can include various error data such as one or more machine error data and time error data within a reasonable range. The first radiation delivery plan is the original radiation delivery plan. Combining the error data with the first radiation delivery plan can refer to considering the influence of the error data on the parameters of the first radiation delivery plan, and updating the relevant parameters in the first radiation delivery plan based on this. As a non-limiting example, the influence of the error data on the values of one or more parameters of the first radiation delivery plan can be calculated, and based on this, the one or more parameters of the first radiation delivery plan can be modified to obtain the second radiation plan. As another non-limiting example, the corresponding type of error data can be directly added to or subtracted from the parameters of the first radiation delivery plan to obtain the second radiation plan.

[0048] Step S204, determining the plan passing rates of the first radiation delivery plan and the second radiation delivery plan.

[0049] Among them, the plan passing rate can represent the ratio of the data points (such as the parameter values in the radiation delivery plan, the dose points in the predicted dose distribution space corresponding to the radiation delivery plan, etc.) in the first radiation delivery plan and the second radiation delivery plan that are within the standard range. As an example, the plan passing rate can be represented by the γ passing rate, the machine parameter deviation rate, the dose deviation rate of each point in a specific area, etc. In this application, the case where the plan passing rate is mainly represented by the γ passing rate is used as an example for illustration.

[0050] For the first radiotherapy delivery plan and the second radiotherapy delivery plan, the plan passing rate can be calculated in terms of dose and / or position. As an example, the γ passing rate can be calculated based on the dose distributions obtainable through the first radiotherapy delivery plan and the second radiotherapy delivery plan (the dose distribution can be calculated based on dose algorithms such as the Monte Carlo algorithm and the pencil beam algorithm), the position deviation of the same dose points, and the dose deviation of the same position points. Data points in the first radiotherapy delivery plan and the second radiotherapy delivery plan can be selected respectively and compared with the set standard range to determine whether the data points fall within the preset standard range. If they are within the standard range, it is considered passed. Among them, the data points and their comparison ranges can be a single point, multiple data points in a plane, or multiple data points in a three-dimensional space, and the present application does not limit this.

[0051] Step S206: Determine the probability that the first radiotherapy delivery plan can pass quality control based on the plan passing rate.

[0052] Among them, when determining the plan passing rate, when the proportion of the number of passed data points is greater than or equal to the preset threshold (corresponding to when the plan passing rate is greater than or equal to the preset threshold), it is determined to pass the verification (i.e., pass quality control). According to the proportion of the number of plans passing the verification in the first radiotherapy delivery plan and the second radiotherapy delivery plan, the probability that the first radiotherapy delivery plan can pass quality control can be obtained.

[0053] In the above radiotherapy delivery plan quality control method, by combining error data into the first radiotherapy delivery plan to obtain the second radiotherapy delivery plan, determining the plan passing rates of the first radiotherapy delivery plan and the second radiotherapy delivery plan, and determining the probability that the first radiotherapy delivery plan can pass quality control based on the plan passing rate, various errors that may exist during actual execution are considered during the quality control process of the radiotherapy delivery plan, solving the problem of low quality control accuracy of radiotherapy treatment plans, improving the accuracy and reliability of the quality control method, and ensuring the accuracy of clinical quality control.

[0054] In one embodiment, the error data may include one or more of gantry angle error data, multi-leaf collimator in-position error data, monitor unit error data, and setup error data.

[0055] Among them, the gantry angle error data represents the error of the accelerator gantry angle generated during the execution of the first radiotherapy delivery plan, the multi-leaf collimator in-position error data represents the error between the actual position where the multi-leaf collimator arrives and the ideal position in the first radiotherapy delivery plan during the execution of the first radiotherapy delivery plan, the monitor unit error data represents the error between the actual monitor units output during the execution of the radiotherapy delivery plan and the ideal monitor units in the first radiotherapy delivery plan, and the setup error represents the error between the actual patient setup and the ideal setup in the first radiotherapy delivery plan during the execution of the first radiotherapy delivery plan.

[0056] In this embodiment, by considering machine errors within a plurality of reasonable ranges, the accuracy of the radiation delivery plan is improved.

[0057] In one embodiment, combining error data into a first radiation delivery plan includes: determining first error data; discretizing the first error data to obtain second error data; and combining the second error data into the first radiation delivery plan.

[0058] Wherein, the first error data is the original error data, and the second error data is the error data obtained by discretizing the first error data. Discretizing the first error data means discretizing a plurality of first error data within the allowable reasonable error range. Combining the second error data into the first radiation delivery plan means considering the influence of the second error data on the parameters of the first radiation delivery plan and updating the first radiation delivery plan based on this.

[0059] In this embodiment, the first error data is discretized separately to generate second error data, ensuring that the second error data is within the allowable reasonable error range, and improving the accuracy of the quality control of the radiation delivery plan.

[0060] In one embodiment, discretizing the first error data to obtain second error data includes:

[0061] Setting discretization parameters for discretizing the first error data, where the discretization parameters include one or more of a discretization allowable range, a discretization number, and a discretized data distribution form.

[0062] Wherein, the discretization parameters of the first error data are set to regulate the discretization process of the first error data. The discretization allowable range includes the upper and lower limits of the maximum allowable error of the first error data. The discretization number represents the number of discretized data (i.e., the second error data) obtained when discretizing the first error data. The discretized data distribution form includes a uniform distribution and a normal distribution. The discretization number includes the number of the second radiation delivery plans obtained after the discretization process.

[0063] Exemplarily, for gantry angle error data, the error allowable range can be set to ±0.2°, the discretization number can be set to 4, and the discretized data distribution form can be a uniform distribution; for multi-leaf collimator in-position error data, the error allowable range can be set to ±0.5 mm, the discretization number can be set to 10, and the discretized data distribution form can be a normal distribution; for monitor unit error data, the error allowable range can be set to ±1%, the discretization number can be set to 10, and the discretized data distribution form can be a normal distribution; for setup error data, the error allowable range can be set to ±2 mm, the discretization number can be set to 20, and the discretized data distribution form can be a normal distribution.

[0064] In this embodiment, by setting the discrete allowable range, the number of discrete points, and the discrete data distribution form of the first error data, it is ensured that an appropriate number and distribution form of second error data are generated after discretization, and the second error data is within a reasonable error allowable range, facilitating subsequent updates to the first radiation delivery plan and improving the efficiency and accuracy of radiation delivery plan quality control.

[0065] In one embodiment, discretizing the first error data to obtain the second error data further includes: within the discrete allowable range of the first error data, discretizing the first error data according to the discrete data distribution form to obtain the same number of second error data as the number of discrete points.

[0066] Among them, in order to generate the second radiation delivery plan within the optimal calculation time, the embodiments of the present application only consider the individual impact of each single error on the first radiation delivery plan. Therefore, after combining multiple error data into the first radiation delivery plan, a second radiation delivery plan with the same number as the second error data will be generated. In this embodiment, by considering the individual impact of unidirectional errors on the first radiation delivery plan and generating a second radiation delivery plan with the same number as the second error data based on this, the optimal calculation time is ensured and the efficiency of radiation delivery plan quality control is improved.

[0067] In one embodiment, combining the error data into the first radiation delivery plan to obtain the second radiation delivery plan includes: according to the error data, updating the parameters in the first radiation delivery plan corresponding to the error data to obtain the second radiation delivery plan.

[0068] Among them, the radiation delivery plan may include only radiotherapy equipment machine parameters, such as the movement trajectory of the treatment head, beam-on time, beam intensity, beam angle, bed movement trajectory, etc., or may include only the radiation dose distribution or monitor units in space obtained based on the radiotherapy equipment machine parameters, or both. For the update of the first radiation delivery plan including radiotherapy equipment machine parameters, it may be to confirm or modify the radiotherapy equipment machine parameters in the first radiation delivery plan based on the error data. For the update of the first radiation delivery plan including non-radiotherapy equipment machine parameters such as radiation dose distribution or monitor units, it may be to calculate the corresponding parameters based on the radiotherapy equipment machine parameters in the error data and confirm or modify the relevant parameters in the first radiation delivery plan according to the calculation results.

[0069] Exemplarily, for the device machine parameters, take the gantry angle parameter as an example. When the number of discrete gantry angle error data is 4, select one of the discrete error data, and update the gantry angle in the first radiation delivery plan to the gantry angle corresponding to this error data. In this way, a second radiation delivery plan with only the gantry angle updated can be obtained. Since the number of discrete gantry angle error data is 4, four different second radiation delivery plans with the gantry angle updated can be obtained. For non-device machine parameters, take the monitor units as an example. Based on the radiotherapy device machine parameters in the error data, multiple monitor unit data can be obtained. When the number of discrete gantry angle error data is 10, select one of the discrete error data, and update the monitor units in the first radiation delivery plan to the monitor units determined based on this error data. In this way, a second radiation delivery plan with only the monitor units updated can be obtained. Since the number of discrete monitor unit error data is 10, 10 different second radiation delivery plans with the monitor units updated can be obtained.

[0070] In this embodiment, when updating the first radiation delivery plan, only one parameter corresponding to the error data in the first radiation delivery plan is updated each time, so as to trace the key cause of the error during quality control and improve the efficiency of data processing.

[0071] In one embodiment, determining the plan passing rate of the first radiation delivery plan and the second radiation delivery plan includes: setting a first preset range, where the first preset range includes a distance deviation range and a dose deviation range; calculating the distance deviation and dose deviation of the first radiation delivery plan and the second radiation delivery plan; and determining the plan passing rate in the first radiation delivery plan and the second radiation delivery plan by calculating whether the distance deviation and dose deviation are respectively within the distance deviation range and the dose deviation range.

[0072] Among them, the first preset range is used to characterize the ideal standard deviation range of the radiation delivery plan, including the distance deviation range and the dose deviation range. The deviation between the first radiation delivery plan and the second radiation delivery plan is calculated in two dimensions of distance and dose respectively. When the distance deviation between the data points of the first radiation delivery plan and the second radiation delivery plan and the reference data points is within the distance deviation range, and the dose deviation between the data points and the reference data points is within the dose deviation range, the data points are determined to pass the inspection; calculate the proportion of the number of data points passing the inspection in each of the first radiation delivery plan and the second radiation delivery plan, and this proportion is the plan passing rate in the first radiation delivery plan and the second radiation delivery plan.

[0073] Exemplarily, taking the case where in the γ analysis method, the distance deviation range is set to 3 mm and the dose deviation range is set to 3% through the standard. When the distance deviation between the data points in the first radiation delivery plan and the second radiation delivery plan and the reference data point does not exceed 3 mm, and the dose deviation does not exceed 3%, this data point is determined to pass the inspection, that is, the γ passing rate standard is the (3 mm, 3%) standard. At this time, the ratio of the data points passing the inspection (for example, each dose data point in the dose distribution space calculated based on the plan) in each of the first radiation delivery plan and the second radiation delivery plan to the total number of data points can be calculated, and this ratio is used as the plan passing rate of the corresponding radiation delivery plan.

[0074] In this embodiment, the effect of the radiation delivery plan is measured based on the plan passing rate, so as to accurately obtain the actual effect of the radiation delivery plan under the influence of a certain error, which is convenient for subsequent optimization of the radiation delivery plan and improves the accuracy of the quality control of the radiation delivery plan.

[0075] In one embodiment, obtaining the probability that the first radiation delivery plan can pass the quality control according to the plan passing rate includes: determining the target radiation delivery plan from the first radiation delivery plan and the second radiation delivery plan, where the plan passing rate of the target radiation delivery plan is greater than or equal to a preset threshold; calculating the proportion of the number of target radiation delivery plans in the total number of the first radiation delivery plan and the second radiation delivery plan; and determining the probability that the first radiation delivery plan can pass the quality control according to the proportion.

[0076] Among them, the target radiation delivery plan is a radiation delivery plan whose plan passing rate meets the requirements. The preset threshold can be set according to actual quality control needs. In this embodiment, the preset threshold is set to 90%. The proportion of the number of target radiation delivery plans in the total number of the first radiation delivery plan and the second radiation delivery plan is the probability that the first radiation delivery plan can pass the quality control. Set the number of target radiation delivery plans to number N pass , the total number of plans of the first radiation delivery plan and the second radiation delivery plan is N total , then the probability P that the first radiation delivery plan can pass the quality control is:

[0077] P = N pass / N total * 100%

[0078] Exemplarily, taking the discrete parameters including the maximum allowable error, discrete data, and discrete data distribution, and the error data including gantry angle error data, multi-page grating in-place error data, machine hop count error data, and setup error data, and the discrete numbers of these four types of error data being 4, 10, 10, and 20 respectively (refer to Table 1) as an example, the number of the second radiation delivery plans can be 44 at this time, and the total number of the first radiation delivery plans and the second radiation delivery plans can be 45. When 45 radiation delivery plans pass the inspection, that is, when the number of the target radiation delivery plans is 45, the probability that the first radiation delivery plan can pass the quality control is 100%.

[0079] Table 1 Example error data and discrete parameter table

[0080] Maximum allowable error Number of discrete points Discrete data distribution Gantry angle ±0.2° 4 Uniform distribution Multi-page grating in place ±0.5 mm 10 Normal distribution Machine hop count ±1％ 10 Normal distribution Setup ±2 mm 20 Normal distribution

[0081] In this embodiment, the passing rates of the radiation delivery plans under different error effects are obtained respectively, and the probability of passing the quality control is calculated based on the passing rates of the plans, which improves the accuracy and comprehensiveness of the quality control inspection. In addition, in this embodiment, the number of the second radiation delivery plans is obtained based on 4 + 10 + 10 + 20 = 44, that is, each second radiation delivery plan only combines one value of one type of error without combining other types of errors (for example, in the case where the computing power of the applicable computing device is relatively weak). However, it is not limited thereto, and the second radiation delivery plans can also be determined in other ways. For example, each second radiation plan combines multiple errors. As an example, based on the types of error data and discrete parameters in Table 1, the first radiation delivery plan can be discretized to obtain 4 * 10 * 10 * 20 = 8000 second radiation delivery plans (for example, in the case where the computing power of the applicable computing device is very strong). Considering the computing power of the computing device, the discrete parameters and the number of the discretized second radiation delivery plans can be appropriately selected, and no special limitation is made here.

[0082] In one embodiment, Figure 3 is the overall process schematic diagram of the radiation delivery plan quality control method. As Figure 3 shown, multiple error data are introduced into the original radiation delivery plan (i.e., the first radiation delivery plan) to generate several new plans (i.e., the second radiation delivery plans), the secondary dose calculation is performed on the original radiation delivery plan and the new radiation delivery plans, the passing rates of each plan are compared, and by counting the number of the radiation delivery plans that pass (i.e., the target radiation delivery plans), the probability that the radiation delivery plan can pass the quality control is obtained.

[0083] It should be understood that although the steps in the flowcharts involved in the above-described embodiments are sequentially shown according to the indications of the arrows, these steps are not necessarily executed sequentially in the order indicated by the arrows. Unless there is a clear indication in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-described embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or in turn with at least a part of other steps or steps or stages in other steps.

[0084] Based on the same inventive concept, an embodiment of the present application further provides a radiation delivery plan quality control device for implementing the above-mentioned radiation delivery plan quality control method. The solution provided by this device to solve the problem is similar to the solution described in the above method. Therefore, the specific limitations in one or more embodiments of the radiation delivery plan quality control device provided below can refer to the limitations on the radiation delivery plan quality control method in the above text, and will not be repeated here.

[0085] In one embodiment, as Figure 4 shown, a radiation delivery plan quality control device is provided, including: an error combination module 41, a plan pass rate calculation module 42, and a probability calculation module 43; where:

[0086] The error combination module 41 is configured to combine error data into a first radiation delivery plan to obtain a second radiation delivery plan;

[0087] The plan pass rate calculation module 42 is configured to determine the plan pass rates of the first radiation delivery plan and the second radiation delivery plan;

[0088] The probability calculation module 43 is configured to determine the probability that the first radiation delivery plan can pass quality control based on the plan pass rate.

[0089] Each module in the above radiation delivery plan quality control device can be implemented in whole or in part by software, hardware, and their combination. The above modules can be embedded in the processor of the computer device in hardware form or independent of it, or stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to the above modules.

[0090] In one embodiment, a computer device is provided. This computer device can be a server, and its internal structure diagram can be as Figure 5As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O), and a communication interface. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store radiation delivery plan data and error data. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with an external terminal through a network connection. The computer program, when executed by the processor, implements a method for quality control of a radiation delivery plan.

[0091] Those skilled in the art can understand that Figure 5 the structure shown in is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0092] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0093] Combine the error data with the first radiation delivery plan to obtain a second radiation delivery plan;

[0094] Determine the planned passing rates of the first radiation delivery plan and the second radiation delivery plan; and, based on the planned passing rates, determine the probability that the first radiation delivery plan can pass quality control.

[0095] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented:

[0096] Combine the error data with the first radiation delivery plan, where the error data includes one or more of gantry angle error data, multi-leaf collimator in-place error data, monitor unit error data, and setup error data.

[0097] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented:

[0098] Determine the first error data; discretize the first error data to obtain second error data; and combine the second error data with the first radiation delivery plan.

[0099] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0100] Set the discrete parameter of the first error data; within the error tolerance range of the first error data, discretize the corresponding first error data according to the discrete data distribution form to obtain the same number of second error data as the number of discretizations.

[0101] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0102] Set the discrete tolerance range, the number of discretizations, and the discrete data distribution form of the first error data; and within the discrete tolerance range of the first error data, discretize the first error data according to the discrete data distribution form to obtain the same number of second error data as the number of discretizations.

[0103] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0104] Update the parameters corresponding to the error data in the first radiation delivery plan according to the error data to obtain a second radiation delivery plan.

[0105] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0106] Set a first preset range, where the first preset range includes a distance deviation range and a dose deviation range; calculate the distance deviation and dose deviation between the first radiation delivery plan and the second radiation delivery plan; and determine the plan passing rate between the first radiation delivery plan and the second radiation delivery plan by calculating whether the distance deviation and dose deviation are respectively within the distance deviation range and the dose deviation range.

[0107] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0108] Determine a target radiation delivery plan from the first radiation delivery plan and the second radiation delivery plan, where the plan passing rate of the target radiation delivery plan is greater than or equal to a preset threshold; calculate the proportion of the number of target radiation delivery plans in the total number of the first radiation delivery plan and the second radiation delivery plan; and determine the probability that the first radiation delivery plan can pass quality control according to the proportion.

[0109] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with the relevant laws, regulations, and standards of relevant countries and regions.

[0110] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memories can include read-only memory (ROM), magnetic tapes, floppy disks, flash memories, optical memories, high-density embedded non-volatile memories, resistive random access memories (ReRAMs), magnetoresistive random access memories (MRAMs), ferroelectric random access memories (FRAMs), phase change memories (PCMs), graphene memories, etc. Volatile memories can include random access memory (RAM) or external cache memories, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, data processing logics based on quantum computing, etc., without limitation.

[0111] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0112] The above-described embodiments merely represent several implementation manners of the present application. The description thereof is relatively specific and detailed, but it should not be construed as a limitation on the patent scope of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all fall within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.

Claims

1. A quality control method for radiotherapy delivery planning, characterized in that, Comprising: Combining error data with a first radiation delivery plan to obtain a second radiation delivery plan; Determining the planned passing rates of the first radiation delivery plan and the second radiation delivery plan; And Based on the planned passing rates, determining the probability that the first radiation delivery plan can pass quality control.

2. The quality control method for radiation delivery planning according to claim 1, wherein The error data includes one or more of gantry angle error data, multi-leaf collimator in-position error data, monitor unit error data, and setup error data.

3. The quality control method for radiotherapy delivery planning according to claim 1, characterized in that, Combining error data with a first radiation delivery plan includes: Determining first error data; Discretizing the first error data to obtain second error data; and Combining the second error data with the first radiation delivery plan.

4. The quality control method for radiotherapy delivery plan according to claim 3, characterized in that, Discretizing the first error data to obtain second error data includes: Setting discretization parameters for discretizing the first error data, where the discretization parameters include one or more of a discretization allowable range, a number of discretizations, and a discretized data distribution form.

5. The quality control method for radiation delivery planning according to claim 4, wherein Discretizing the first error data to obtain second error data further includes: Within the discretization allowable range of the first error data, discretizing the first error data according to the discretized data distribution form to obtain the same number of the second error data as the number of discretizations.

6. The quality control method for radiation delivery planning according to claim 1, wherein Combining error data with a first radiation delivery plan to obtain a second radiation delivery plan includes: According to the error data, updating parameters in the first radiation delivery plan corresponding to the error data to obtain the second radiation delivery plan.

7. The quality control method for radiation delivery planning according to claim 1, characterized in that Determining the planned passing rates of the first radiation delivery plan and the second radiation delivery plan includes: Setting the first preset range, where the first preset range includes a distance deviation range and / or a dose deviation range; Calculating the distance deviation and / or dose deviation of the first radiation delivery plan and the second radiation delivery plan; and Determining the planned passing rates of the first radiation delivery plan and the second radiation delivery plan by calculating whether the distance deviation is within the distance deviation range and / or whether the dose deviation is within the dose deviation range.

8. The quality control method for radiation delivery planning according to claim 1, characterized in that, Based on the planned passing rates, obtaining the probability that the first radiation delivery plan can pass quality control includes: Determining a target radiation delivery plan from the first radiation delivery plan and the second radiation delivery plan, where the planned passing rate of the target radiation delivery plan is greater than or equal to a preset threshold; Calculating the proportion of the number of the target radiation delivery plans in the total number of both the first radiation delivery plan and the second radiation delivery plan; and Based on the proportion, determining the probability that the first radiation delivery plan can pass quality control.

9. A quality control device for a radiation delivery plan, characterized in that, Comprising: An error combination module for combining error data with a first radiation delivery plan to obtain a second radiation delivery plan; A planned passing rate calculation module for determining the planned passing rates of the first radiation delivery plan and the second radiation delivery plan; A probability calculation module for determining the probability that the first radiation delivery plan can pass quality control based on the planned passing rates.

10. A computer-readable storage medium having instructions stored thereon, characterized in that, The instructions, when executed by a processor, implement the steps of the radiation delivery plan quality control method according to any one of claims 1 to 7.

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