Method and system for determining radiotherapy tolerance limit value

Abstract

The invention relates to the technical field of radiotherapy, and discloses a radiotherapy tolerance limit value determination method and system, and the method comprises the steps: obtaining a historical passing rate set of a target disease; performing normalization transformation and screening on the historical passing rate set to obtain an intermediate passing rate set; taking the intermediate passing rate set as a converted passing rate set; repeatedly performing screening on the converted passing rate set until a controlled passing rate set in a controlled state is obtained; performing control lower limit calculation on the controlled passing rate set to obtain a current tolerance limit value of the target disease; acquiring a current passing rate set of a target object suffering from the target disease; and adding the current passing rate set into the historical passing rate set for updating to obtain an updated passing rate set. The method has the beneficial effects that the tolerance limit can be dynamically adjusted according to the data of the actual target object, and the accuracy of the tolerance limit value is improved and the reliability of radiotherapy out-of-control judgment is improved by converting and screening the passing rate data.

Description

Technical Field

[0001] The present application relates to the field of radiotherapy technology, and in particular to a method and system for determining a radiotherapy tolerance limit. Background Art

[0002] Radiotherapy is the full name of radiotherapy, which is the use of radiation as a way to treat diseases. The principle is that the energy generated by a large amount of radiation can damage the chromosomes of cells, stop the cells from growing, and thus eliminate cancer cells that can divide and grow rapidly. Radiotherapy is most commonly used as a direct or auxiliary treatment for cancer. During treatment, the treatment process needs to be controlled so that the treatment process proceeds according to the plan to ensure the treatment effect. The treatment effect can be determined by setting tolerance limits for radiotherapy fractions and judging whether the radiotherapy fractions are out of control based on the tolerance limits. When the relevant technology is actually applied, there are problems such as inaccurate radiotherapy tolerance limits, which lead to errors in the judgment results. Summary of the invention

[0003] The present application provides a method and system for determining radiotherapy tolerance limits, which solves the technical problem that the accuracy of the calculated radiotherapy tolerance limits is low due to the skewed distribution of actual data, and achieves the technical effect of being able to dynamically adjust the radiotherapy tolerance limits according to the data of the actual target object, improve the accuracy of the obtained radiotherapy tolerance limits by transforming and screening the pass rate data, and improve the reliability of judging the radiotherapy fractionation out of control.

[0004] In order to achieve the above objectives, the main technical solutions adopted in this application include:

[0005] In a first aspect, an embodiment of the present application provides a method for determining a radiotherapy tolerance limit, the method comprising:

[0006] Obtaining a historical pass rate data set for a target disease; wherein the historical pass rate data set includes gamma pass rates of subjects suffering from the target disease in historical radiotherapy fractions;

[0007] Performing a normalization transformation on the historical pass rate number set to obtain a transformed pass rate number set; screening the transformed pass rate number set according to the control lower limit of the transformed pass rate number set to determine an intermediate pass rate number set in a state to be verified; using the intermediate pass rate number set as the transformed pass rate number set; repeatedly performing the above steps of screening the transformed pass rate number set until a controlled pass rate number set in a controlled state is obtained; calculating the control lower limit of the controlled pass rate number set to obtain the current tolerance limit value of the target disease;

[0008] Acquire a current pass rate number set of a target subject suffering from the target disease; wherein the current pass rate number set includes the gamma pass rate of the target subject in the current radiotherapy fraction;

[0009] The current pass rate number set of the target object is added to the historical pass rate number set for updating to obtain an updated pass rate number set; the updated pass rate number set is used as the historical pass rate number set of the target disease to perform the next tolerance limit calculation.

[0010] The method for determining the tolerance limit of radiotherapy proposed in the embodiment of the present application first determines the initial tolerance limit according to the historical pass rate number set corresponding to the target disease suffered by the target object, and after the target object is subjected to radiotherapy, the historical pass rate number set is updated based on the statistical data of the gamma pass rate in the radiotherapy fractions of the target object subjected to radiotherapy in the same cycle, so that in the next calculation, the updated tolerance limit is obtained based on the updated pass rate number set, so that the updated tolerance limit can take into account the impact of the actual radiotherapy process on the target object, thereby dynamically adjusting the tolerance limit of the target disease, improving the guidance of the treatment effect of the target object, and ensuring that the radiotherapy fractions can be carried out normally. In addition, the present application improves the normality of the pass rate number set by normalizing the pass rate number set, so that the pass rate number set can meet the requirements for normality in the tolerance limit calculation, improves the accuracy of the tolerance limit, and the reliability of the out-of-control judgment of the current radiotherapy fraction of the target object based on the obtained tolerance limit.

[0011] Optionally, performing a normalization transformation on the historical pass rate number set to obtain a transformed pass rate number set includes:

[0012] Determine the target normalization transformation form according to the distribution of the gamma pass rate in the historical pass rate data set; wherein the distribution includes the central value of the historical pass rate data set and the quantile values ​​corresponding to different gamma pass rates;

[0013] The historical pass rate number set is subjected to normalization transformation in the form of the target normalization transformation.

[0014] Optionally, determining the target normalization transformation form according to the distribution of the gamma pass rate in the historical pass rate data set includes:

[0015] Determine four standard deviation points; wherein each of the standard deviation points corresponds to a gamma pass rate and is within the interval range of the historical pass rate number set, the standard deviation points are symmetrical about the central value of the historical pass rate number set, and the lengths between the standard deviation points are the same;

[0016] respectively determining the percentile values ​​corresponding to the standard deviation points in the historical pass rate data set;

[0017] Determine the percentile ratio of the historical pass rate number set according to the difference between adjacent percentile values;

[0018] The target normalization transformation form for normalizing the historical pass rate number set is determined according to the quantile ratio.

[0019] Optionally, the target normalized transformation form includes Johnson SB distribution, Johnson SU distribution and Johnson SL distribution; the step of determining the target normalized transformation form for normalizing the historical pass rate number set according to the quantile ratio includes:

[0020] If the quantile ratio is greater than 1, the target normalized transformation form is Jonhson SU distribution;

[0021] If the quantile ratio is equal to 1, the target normalized transformation form is Jonhson SL distribution;

[0022] If the quantile ratio is less than 1, the target normalized transformation form is the Jonhson SB distribution.

[0023] Optionally, the method for determining the control lower limit of the controlled pass rate number set is the same as the method for determining the control lower limit of the transformed pass rate number set; the control lower limit of the transformed pass rate number set is determined by the following method:

[0024] According to the gamma pass rate mean and gamma pass rate range of each radiotherapy fraction in the transformed pass rate set, determine the overall mean and overall range of the transformed pass rate set;

[0025] The lower control limit is determined based on the difference between the population mean and the population range.

[0026] Optionally, the controlled pass rate number set in the controlled state is the transformed pass rate number set after screening; screening the transformed pass rate number set according to the control lower limit of the transformed pass rate number set to determine the intermediate pass rate number set in the state to be verified includes:

[0027] Determining, from the transformed pass rate number set, an out-of-control pass rate that is lower than a control lower limit of the transformed pass rate number set;

[0028] According to the error cause corresponding to the out-of-control pass rate, the out-of-control pass rate that needs to be removed is determined, and the out-of-control pass rate that needs to be removed is removed from the transformed pass rate number set to obtain the intermediate pass rate number set in the state to be verified.

[0029] Optionally, the method for finding out the cause of the out-of-control pass rate includes IGRT image inspection; and determining the out-of-control pass rate to be removed according to the error cause corresponding to the out-of-control pass rate includes:

[0030] If the cause of the out-of-control pass rate can be found, then the out-of-control pass rate is removed;

[0031] If the cause of the out-of-control pass rate cannot be found, the out-of-control pass rate shall be retained;

[0032] The proportion of all the removed out-of-control pass rates in the transformed pass rate set does not exceed one third.

[0033] Optionally, the step of obtaining a current pass rate number set of a target subject suffering from the target disease includes:

[0034] Acquiring, by means of EPID, the in-body dose distribution of the target object in the current radiotherapy fraction;

[0035] According to the in-body dose distribution and the planned dose distribution of the current radiotherapy fraction, the gamma pass rate of the target object in the current radiotherapy fraction is obtained as the current pass rate number set.

[0036] Optionally, the method further comprises:

[0037] If the mean gamma pass rate of the target object in the current radiotherapy fraction is lower than the current tolerance limit, it is determined that there is an out-of-control problem in the current radiotherapy fraction, and a warning is issued for the current radiotherapy fraction.

[0038] In a second aspect, an embodiment of the present application provides a system for determining a radiotherapy tolerance limit, the system comprising:

[0039] A historical data acquisition module, used to acquire a historical pass rate data set of a target disease; wherein the historical pass rate data set includes the gamma pass rate of subjects suffering from the target disease in historical radiotherapy fractions;

[0040] The tolerance limit update module is used to perform a normalization transformation on the historical pass rate number set to obtain a transformed pass rate number set; screen the transformed pass rate number set according to the control lower limit of the transformed pass rate number set to determine an intermediate pass rate number set in a state to be verified; use the intermediate pass rate number set as the transformed pass rate number set; repeatedly perform the above steps of screening the transformed pass rate number set until a controlled pass rate number set in a controlled state is obtained; calculate the control lower limit of the controlled pass rate number set to obtain the current tolerance limit value of the target disease;

[0041] A current data acquisition module, used to acquire a current pass rate number set of a target subject suffering from the target disease; wherein the current pass rate number set includes a gamma pass rate of the target subject in a current radiotherapy fraction;

[0042] The historical data updating module is used to add the current pass rate number set of the target object to the historical pass rate number set for updating to obtain an updated pass rate number set; and use the updated pass rate number set as the historical pass rate number set of the target disease to perform the next tolerance limit calculation.

[0043] In a third aspect, an embodiment of the present application provides a computer device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, computer instructions are stored in the memory, and the processor executes the method for determining the radiotherapy tolerance limit value described in any one of the above embodiments by executing the computer instructions.

[0044] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which computer instructions are stored, and the computer instructions are used to enable a computer to execute the method for determining the radiotherapy tolerance limit value described in any one of the above embodiments.

[0045] In a fifth aspect, an embodiment of the present application provides a computer program product, comprising computer instructions, wherein the computer instructions are used to enable a computer to execute the method for determining a radiotherapy tolerance limit value described in any one of the above embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the specific implementation methods of the present application or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0047] Figure 1 A step diagram of a method for determining a radiotherapy tolerance limit provided in an embodiment of the present application;

[0048] Figure 2 It is a schematic diagram of ±3σ criterion;

[0049] Figure 3 A flow chart of obtaining the current tolerance limit of the target disease in an embodiment of the present application;

[0050] Figure 4 A diagram showing the steps of normalizing the updated pass rate number set in an embodiment of the present application;

[0051] Figure 5 A diagram showing the steps for determining the target normalization transformation form in an embodiment of the present application;

[0052] Figure 6 A step diagram for determining a target normalization transformation form according to the quantile ratio in an embodiment of the present application;

[0053] Figure 7 A diagram showing the steps for determining the lower control limit of the transformed pass rate number set in an embodiment of the present application;

[0054] Figure 8 This is a step diagram for removing the out-of-control pass rate according to the control lower limit in the embodiment of the present application;

[0055] Fig. 9 This is a step diagram for screening out-of-control pass rate in an embodiment of the present application;

[0056] Fig.10 A module diagram of a system for determining radiotherapy tolerance limits provided in an embodiment of the present application.

[0057] The figure numbers of the drawings in the specification are as follows: 100. Historical data acquisition module, 200. Tolerance limit update module, 300. Current data acquisition module, 400. Historical data update module. DETAILED DESCRIPTION

[0058] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present application.

[0059] Radiotherapy is the full name of radiotherapy, which is the use of radiation as a way to treat diseases. The principle is that the energy generated by a large amount of radiation can damage the chromosomes of cells, stop the cells from growing, and thus eliminate cancer cells that can divide and grow rapidly. Radiotherapy is most commonly used as a direct or auxiliary treatment for cancer. During treatment, the treatment process needs to be controlled so that the treatment process proceeds according to plan and ensures the treatment effect.

[0060] In-body dose monitoring is currently the most direct way to reflect the actual dose received by the target object. In-body dose monitoring can be analyzed using gamma pass rate. Gamma pass rate (GPR) refers to an indicator used in radiotherapy to evaluate the consistency and matching degree between the planned dose distribution simulated by the computer and the actual measured carrier dose distribution. The higher the gamma pass rate, the higher the matching degree between the in-body dose distribution and the planned dose distribution, indicating that the current radiotherapy fraction is proceeding normally according to the plan; the lower the gamma pass rate, the lower the matching degree between the in-body dose distribution and the planned dose distribution, indicating that the current radiotherapy fraction is out of control. At this time, the current radiotherapy fraction may have systematic errors, including positioning errors and changes in anatomical structures of the target object. Systematic errors may occur in all radiotherapy fractions of the target object, affecting the treatment effect of the target object.

[0061] In order to improve the gamma pass rate of radiotherapy fractions and ensure that radiotherapy fractions can be carried out as planned, it is necessary to set tolerance limits for radiotherapy fractions during the radiotherapy process, and screen whether the radiotherapy fractions are out of control based on the tolerance limits, and pay attention to the screened radiotherapy fractions to reduce the systematic errors in the overall radiotherapy process, so that the radiotherapy fractions can be carried out as planned, thereby ensuring the treatment effect.

[0062] Based on the above problems, the present application provides a method and system for determining radiotherapy tolerance limits, the method comprising: obtaining a historical pass rate number set of a target disease; normalizing and filtering the historical pass rate number set to obtain an intermediate pass rate number set; using the intermediate pass rate number set as a transformed pass rate number set; repeatedly filtering the transformed pass rate number set until a controlled pass rate number set under a controlled state is obtained; calculating a control lower limit on the controlled pass rate number set to obtain a current tolerance limit value of the target disease; obtaining a current pass rate number set of a target object suffering from the target disease; adding the current pass rate number set to the historical pass rate number set for updating to obtain an updated pass rate number set; using the updated pass rate number set as the historical pass rate number set of the target disease to perform the next tolerance limit value calculation.

[0063] The present application provides a method and system for determining radiotherapy tolerance limits. By normalizing a set of gamma pass rates of a target object in a current radiotherapy fraction, the technical problem of low accuracy of the calculated radiotherapy tolerance limits caused by skewed distribution of actual data is solved. The method achieves the technical effect of being able to update the radiotherapy tolerance limits according to the data of the target object, so that the updated tolerance limits can take into account the impact of the actual radiotherapy process on the target object, thereby dynamically adjusting the tolerance limits of the target disease and improving the reliability of judging the loss of control of radiotherapy fractions.

[0064] The present specification provides a method and system for determining a radiotherapy tolerance limit, which can be applied to analyze the quality of the radiotherapy process and whether it is out of control, wherein the radiotherapy process can correspond to any disease that requires radiotherapy, including but not limited to various types of tumors and cancers. In addition, the target object of the above-mentioned diseases can be a human, and the method provided in the present specification can also be an animal or other possible target object after adaptive changes.

[0065] According to an embodiment of the present application, an embodiment of a method for determining a radiotherapy tolerance limit is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0066] In this embodiment, a method for determining a radiotherapy tolerance limit is provided, which can be used for the process control of the above-mentioned radiotherapy fractionation. Figure 1 The step diagram of the method for determining the radiotherapy tolerance limit provided in the embodiment of the present application, as shown in the figure, includes the following steps:

[0067] S100. Obtain a historical pass rate data set of the target disease; wherein the historical pass rate data set includes the gamma pass rates of subjects suffering from the target disease in historical radiotherapy fractions.

[0068] S200. Perform a normalization transformation on the historical pass rate number set to obtain a transformed pass rate number set; screen the transformed pass rate number set according to the control lower limit of the transformed pass rate number set to determine the intermediate pass rate number set in the state to be verified; use the intermediate pass rate number set as the transformed pass rate number set; repeat the above steps of screening the transformed pass rate number set until a controlled pass rate number set in a controlled state is obtained; calculate the control lower limit of the controlled pass rate number set to obtain the current tolerance limit value of the target disease.

[0069] S300. Obtain a current pass rate number set of a target subject suffering from a target disease; wherein the current pass rate number set includes a gamma pass rate of the target subject in a current radiotherapy fraction.

[0070] S400. Add the current pass rate number set of the target object to the historical pass rate number set for updating, and obtain an updated pass rate number set; use the updated pass rate number set as the historical pass rate number set of the target disease type for the next tolerance limit calculation.

[0071] Specifically, unlike the method of performing pre-radiotherapy analysis through an ideal phantom in the related art, the target object in this embodiment has specificity and can reflect the impact of the radiotherapy process on the actual target object. Therefore, the historical pass rate data set is updated according to the data of the target object in the current radiotherapy fraction, so that the tolerance limit of the target disease can be periodically and dynamically adjusted, which improves the guidance of the treatment effect of the target object with the target disease in different radiotherapy fractions, and ensures that the radiotherapy fractions can be carried out normally according to the plan.

[0072] Specifically, in the process of acquiring the current pass rate data set, the gamma pass rate of the target object at multiple angles can be collected, and the number of collected angles and the specific angle sizes can be different. The gamma pass rate is related to the in-body dose distribution and planned dose distribution of the target object. In some embodiments, the measurement method includes but is not limited to: surface or intracavitary detector monitoring, accelerator head radiation monitoring, log file-based monitoring, Adaptivo prediction algorithm and EPIgray prediction model, etc.

[0073] Among them, the method based on body surface or intracavity detector monitoring is to complete the measurement of in-body dose distribution by placing a detector on the body surface of the target object or in a natural cavity close to the target object's part of interest. According to the measurement results of the detector and the corresponding conversion relationship, the in-body dose distribution of the target object's part of interest can be calculated. The method based on the accelerator head output radiation monitoring is to measure the output change of the dose distribution of the incident field by a specific device placed between the radiation head and the part of interest of the target object, so as to achieve the purpose of in-body dose distribution measurement. The method based on log file monitoring is to record the real-time information of the linear accelerator at ms time intervals through the accelerator control system, including: the position information of the multi-leaf grating blades, the angle information of the linear accelerator frame, and the dose distribution and dose distribution rate information of the field corresponding to each moment. The above information is stored as an independent log file for each target object. After the treatment is completed, these log files can be imported back to the treatment planning system. At this time, the three-dimensional dose distribution can be reconstructed on the planned CT according to the log file information to obtain the in-body dose distribution, and then compared with the planned dose distribution. The Adaptivo prediction algorithm uses an open density matrix derived from multi-leaf modulator control points to convolve with an energy-dependent EPID dose distribution deposition kernel to simulate the response of EPID, which takes into account beam attenuation based on planning CT. The prediction model of EPIgray is that after EPID calibration, multiple conversion factors are needed to obtain the reconstructed dose distribution in the target object's part of interest, and then these conversion factors are applied to the calculated dose distribution to obtain the in-body dose distribution in the target object's part of interest. In actual scenarios, the appropriate measurement method can be selected according to actual needs and limitations.

[0074] Furthermore, in actual radiotherapy fractionation, a certain degree of anatomical error will inevitably occur, resulting in an increase in the in vivo dose of the target object's site of interest in the radiotherapy fractionation, causing a decrease in the gamma pass rate. Therefore, in actual scenarios, the normality of the gamma pass rate is generally negatively skewed, resulting in the historical pass rate number set not conforming to the normal distribution, and the control lower limit obtained by directly calculating the control lower limit is inaccurate and cannot reflect the actual data situation. In order to solve the above problems, it is necessary to normalize the historical pass rate number set to improve the normality of the historical pass rate number set, thereby improving the accuracy and reliability of the control lower limit calculation results. In some embodiments, the normalization transformation methods include but are not limited to: logarithmic transformation, square root transformation, inverse transformation, Burke-Cox transformation and Young-Johnson transformation.

[0075] Specifically, refer to Figure 2 , Figure 2 This is a schematic diagram of the ±3σ criterion. As shown in the figure, according to the ±3σ principle, for data that obey the normal distribution, 99.73% of the statistics are located within In the range, ， is the mean of the data, and σ is the standard deviation of the data. Defined as the upper control limit, Defined as the lower control limit; when data exceeds the upper control limit or the lower control limit, the data is a low-probability event, indicating that the data has mutated during the control process, causing the data to be out of control. In this embodiment, after obtaining the transformed pass rate number set of the normal distribution, the control lower limit of the transformed pass rate number set is calculated according to the mean and range of the transformed pass rate number set, thereby obtaining the control lower limit of the transformed pass rate number set. It should be noted that the upper control limit of the transformed pass rate number set in this embodiment is 100%, that is, the upper limit of the gamma pass rate.

[0076] Further, refer to Figure 3 , Figure 3 This is a flow chart for obtaining the current tolerance limit of the target disease in an embodiment of the present application. As shown in the figure, in the process of obtaining the current tolerance limit of the target disease, the above-mentioned steps of screening the transformed pass rate number set are repeatedly performed until the end condition is met, thereby obtaining the controlled pass rate number set under the controlled state. Among them, the end condition may include an out-of-control acceptance condition, an out-of-control removal condition, and an iteration number condition, wherein: the out-of-control acceptance condition is that the number of out-of-control pass rates that are lower than the tolerance limit of the controlled pass rate number set at this time is within the allowable range; the out-of-control removal condition is that the number of removed out-of-control pass rates exceeds the set ratio of the historical pass rate number set, and exceeding the set ratio will cause the transformed pass rate number set to be unable to correctly reflect the treatment process of the target object; the iteration number condition is that the number of times the above steps are repeated reaches the preset number.

[0077] Further, the control lower limit of the controlled pass rate number set is calculated to obtain the current tolerance limit of the target disease, which also includes: obtaining the control lower limit of the controlled pass rate number set, and performing an inverse normalization transformation on the control lower limit of the controlled pass rate number set to obtain the current tolerance limit of the target disease. It can be understood that the inverse normalization transformation is the opposite transformation to the normalization transformation of the transformed pass rate number set, and the two should belong to the same type of normalization change method. The current tolerance limit is used to determine whether the current radiotherapy fractionation of the target object suffering from the target disease is out of control, and determines the judgment standard for the subsequent radiotherapy process. In some embodiments, it is also possible to make a judgment directly through the control lower limit of the controlled pass rate number set. Accordingly, at this time, the judgment should be made after the radiotherapy fractionation to be judged is normalized.

[0078] The method for determining the tolerance limit of radiotherapy proposed in the embodiment of the present application first determines the initial tolerance limit according to the historical pass rate number set corresponding to the target disease suffered by the target object, and after the target object is subjected to radiotherapy, the historical pass rate number set is updated based on the statistical data of the gamma pass rate in the radiotherapy fractions of the target object subjected to radiotherapy in the same cycle, and finally the updated tolerance limit is obtained based on the updated pass rate number set, so that the updated tolerance limit can take into account the impact of the actual radiotherapy process on the target object, thereby dynamically adjusting the tolerance limit of the target disease, improving the guidance of the treatment effect of the target object, and ensuring that the radiotherapy fractions can be carried out normally. In addition, the present application improves the normality of the pass rate number set by normalizing the pass rate number set, so that the pass rate number set can meet the requirements for normality in the tolerance limit calculation, improves the accuracy of the tolerance limit, and the reliability of the out-of-control judgment of the current radiotherapy fraction of the target object based on the obtained tolerance limit.

[0079] refer to Figure 4 , Figure 4 This is a step diagram for normalizing a historical pass rate number set in an embodiment of the present application. As shown in the figure, as an embodiment of the present application, a normalization transformation is performed on a historical pass rate number set to obtain a transformed pass rate number set, including:

[0080] S210. Determine the target normalization transformation form according to the distribution of the gamma pass rate in the historical pass rate data set; wherein the distribution includes the central value of the historical pass rate data set and the quantile values ​​corresponding to different gamma pass rates.

[0081] S230. Perform normalization transformation on the historical pass rate number set in the form of target normalization transformation.

[0082] Specifically, in the present embodiment, the normalization transformation is the Johnson distribution, which was proposed in 1949 and includes three normal transformation forms. The data can be transformed into a standard normal variable by using the function of the Johnson distribution for normalization transformation. The Johnson distribution has the characteristics of multiple parameters and multiple types, and more overall distribution characteristics can be expressed by fitting the sample. The Johnson distribution also has strong adaptability, and by selecting the appropriate type and adjustment parameters, it can be close to a continuous distribution model. Therefore, when the historical pass rate number set is normalized, it is necessary to select an appropriate normalization transformation form as the target normalization transformation form.

[0083] In some embodiments, the method for determining the target normalized transformation form includes but is not limited to: Moment Matching, Least Squares, and Minimum Lp Norm Estimation. Through the above method, according to the distribution of gamma pass rate in the historical pass rate data set, a satisfactory estimation of the four parameters in the Johnson distribution can be achieved. It can be understood that the data types included in the distribution are different in different methods, and the specific data type needs to be selected according to the method adopted.

[0084] refer to Figure 5 , Figure 5 The step diagram for determining the target normalized transformation form in the embodiment of the present application is shown in the figure. As an embodiment of the present application, the target normalized transformation form is determined according to the distribution of the gamma pass rate in the historical pass rate number set, including:

[0085] S212. Determine four standard deviation points; wherein each standard deviation point corresponds to a gamma pass rate and is within the range of the historical pass rate number set. The standard deviation points are symmetrical about the center value of the historical pass rate number set, and the lengths between the standard deviation points are the same.

[0086] S214. Determine the percentile values ​​corresponding to the standard deviation points in the historical pass rate data set respectively.

[0087] S216. Determine the quantile ratio of the historical pass rate data set based on the difference between adjacent quantile values.

[0088] S218. According to the quantile ratio, determine the target normalization transformation form for normalizing the historical pass rate data set.

[0089] Specifically, the quantile method is used in this embodiment to determine the target normalization transformation form. In 1980, James F. Slifker and Samuel S. Shapiro published "The Johnson System: Selection and Parameter Estimation" in Technometrics, which proposed a simple standard that can be used to select different Johnson distributions to fit a set of data.

[0090] Exemplarily, in this method, an arbitrary positive number z is first determined, with the central value of the historical pass rate number set as the center, and the values ​​of the central value ±z and the central value ±3z as the standard deviation points. It can be understood that the standard deviation points corresponding to the central value ±3z should also be within the range of the historical pass rate number set; the distances between the standard deviation points are the same, and the standard deviation points are symmetrical around the central value.

[0091] After obtaining the standard deviation point, determine the probability of the gamma pass rate corresponding to the standard deviation point in the historical pass rate data set, and obtain the quantile value corresponding to the standard deviation point based on the corresponding probability. According to the quantile value corresponding to the standard deviation point, the quantile value ratio of the historical pass rate data set can be obtained, and the quantile value ratio is in the following form:

[0092]

[0093] Among them, d is the percentile ratio; m, n and p are the differences between different percentiles, respectively, in the following form:

[0094] m=x 3z -x z ,p=x z -x -z ,n=x -z -x -3z

[0095] Among them, x 3z 、x z 、x -z and x -3z are the quantile values ​​corresponding to each standard deviation point. According to the size of the quantile value ratio, the target normalization transformation form can be determined.

[0096] refer to Figure 6 , Figure 6The step diagram of determining the target normalization transformation form according to the quantile ratio in the embodiment of the present application, as shown in the figure, as an embodiment of the present application, the target normalization transformation form includes Johnson SB distribution, Johnson SU distribution and Johnson SL distribution; according to the quantile ratio, determining the target normalization transformation form for normalizing the historical pass rate number set includes:

[0097] S220. If the quantile ratio is greater than 1, the target normalization transformation form is the Jonhson SU distribution.

[0098] S222. If the quantile ratio is equal to 1, the target normalization transformation form is the Jonhson SL distribution.

[0099] S224. If the quantile ratio is less than 1, the target normalization transformation form is the Jonhson SB distribution.

[0100] Specifically, the target normalization transformation form is the three normal transformation forms included in the Johnson distribution, including Johnson SB distribution, Johnson SU distribution and Johnson SL distribution. Among them, Johnson SB distribution indicates that the data is bounded, Johnson SU distribution indicates that the data is log-normal, and Johnson SL distribution indicates that the data is unbounded. The above normal transformation forms can be used to transform the data into a standard normal variable.

[0101] Specifically, if the quantile ratio is greater than 1, it means that the historical pass rate data set follows the Jonhson SU distribution, which is as follows:

[0102]

[0103] Among them, X is the gamma pass rate in the historical pass rate data set; ξ is the location parameter; λ is the scale parameter; γ and δ are shape parameters; the form of each parameter is as follows:

[0104]

[0105]

[0106]

[0107]

[0108] Specifically, if the percentile ratio is equal to 1, it means that the historical pass rate data set follows the Jonhson SL distribution, which is as follows:

[0109]

[0110] The parameters are in the following format:

[0111]

[0112]

[0113]

[0114] Specifically, if the percentile ratio is less than 1, it means that the historical pass rate data set follows the Jonhson SB distribution, which is as follows:

[0115]

[0116] The parameters are in the following format:

[0117]

[0118]

[0119]

[0120]

[0121] Exemplarily, the radiotherapy tolerance limit values ​​determined according to the method for determining the radiotherapy tolerance limit values ​​provided in the present application are applicable to disease sites including: brain, head and neck, esophagus, lungs, rectum, cervix and prostate, etc. Through actual calculations, it is found that the data of the above-mentioned disease sites all conform to the Johnson SB distribution, and the Johnson SB distribution can be used to perform a normal transformation on the historical pass rate number set.

[0122] refer to Figure 7 , Figure 7 This is a step diagram for determining the control lower limit of the transformed pass rate number set in an embodiment of the present application. As shown in the figure, as an embodiment of the present application, the method for determining the control lower limit of the controlled pass rate number set is the same as the method for determining the control lower limit of the transformed pass rate number set; the control lower limit of the transformed pass rate number set is determined by the following method:

[0123] S240. Determine the overall mean and overall range of the transformed pass rate set based on the mean gamma pass rate and the range of gamma pass rate of each radiotherapy fraction in the transformed pass rate set.

[0124] S242. Determine the lower control limit based on the difference between the overall mean and the overall range.

[0125] Specifically, during the calculation process, the data of the radiotherapy fractions at multiple different angles contained in the transformed pass rate data set are averaged to obtain the mean gamma pass rate of the radiotherapy fractions, which is in the following form:

[0126]

[0127] in, is the mean value of the gamma pass rate of the ith radiotherapy fraction in the transformed pass rate number set; X ij is the gamma pass rate of the jth angle in the i-th radiotherapy fraction in the transformed pass rate number set; J is the total number of angles.

[0128] Specifically, the maximum gamma pass rate and the minimum gamma pass rate in the same radiotherapy fraction are subtracted to obtain the gamma pass rate range of the radiotherapy fraction, which is in the following form:

[0129] R i =|X imax -X imin |

[0130] Among them, R i is the gamma pass rate extreme difference of the i-th radiotherapy fraction in the transformed pass rate number set; X imax is the maximum gamma pass rate of the i-th radiotherapy fraction in the transformed pass rate number set; X imin is the minimum gamma pass rate of the i-th radiotherapy fraction in the transformed pass rate number set.

[0131] Correspondingly, according to the mean of gamma pass rate of different radiotherapy fractions, the overall mean of all radiotherapy fractions in the transformed pass rate number set can be obtained, which is in the following form:

[0132]

[0133] in, is the overall mean of the transformed pass rate set; I is the total number of radiotherapy fractions in the transformed pass rate set.

[0134] Correspondingly, according to the range of gamma pass rate of different radiotherapy fractions, the overall range of all radiotherapy fractions in the transformed pass rate set can be obtained, which is in the following form:

[0135]

[0136] in, is the overall range of the set of pass rates after transformation.

[0137] Furthermore, according to the overall mean and overall range, the control lower limit of the transformed pass rate set can be obtained. The specific formula is as follows:

[0138]

[0139] Among them, LCL xis the lower control limit; A2 is the coefficient, which can be determined according to the size of the subgroup in accordance with the national standard document GB / T17989.2; it can be understood that the subgroup here is the set of pass rate numbers after transformation.

[0140] refer to Figure 8 , Figure 8 This is a step diagram for removing the out-of-control pass rate according to the control lower limit in the embodiment of the present application. As shown in the figure, as an embodiment of the present application, the controlled pass rate number set in the controlled state is the transformed pass rate number set after screening; the transformed pass rate number set is screened according to the control lower limit of the transformed pass rate number set to determine the intermediate pass rate number set in the state to be verified, including:

[0141] S250. Determine the out-of-control pass rate that is lower than the control lower limit of the transformed pass rate set in the transformed pass rate set.

[0142] S252. According to the error cause corresponding to the out-of-control pass rate, determine the out-of-control pass rate that needs to be removed, and remove the out-of-control pass rate that needs to be removed from the transformed pass rate number set to obtain the intermediate pass rate number set in the state to be verified.

[0143] Specifically, the control lower limit of the transformed pass rate number set is used to determine whether the radiotherapy fractions in the transformed pass rate number set are out of control. When the gamma pass rate of the radiotherapy fractions in the transformed pass rate number set is lower than the control lower limit, it indicates that a small probability event has occurred and the radiotherapy fractions may be out of control. Exemplarily, if the gamma pass rate is higher than the control lower limit, it indicates that the gamma pass rate is at a normal level and the radiotherapy fractions corresponding to the gamma pass rate are under control; if the gamma pass rate is lower than the control lower limit, it indicates that the gamma pass rate is too low and the radiotherapy fractions corresponding to the gamma pass rate have errors during the treatment process, resulting in the treatment fractions being out of control.

[0144] Furthermore, by removing the gamma pass rate below the control lower limit, that is, the out-of-control pass rate, the intermediate pass rate number set in the state to be verified is obtained. It can be understood that the radiotherapy fractions corresponding to the gamma pass rate in the intermediate pass rate number set may be in a controlled state, and they are all in a state to be verified. Therefore, the intermediate pass rate number set is used as the transformed pass rate number set, and the control lower limit is performed on the transformed pass rate number set at this time. According to the control lower limit calculated at this time, the transformed pass rate number set is further screened, thereby improving the control degree of the data in the transformed pass rate number set, and finally obtaining a controlled pass rate number set in a controlled state.

[0145] refer to Fig. 9 , Fig. 9The step diagram for screening out-of-control pass rate in the embodiment of the present application is shown in the figure. As an embodiment of the present application, the method for finding out the cause of the out-of-control pass rate includes IGRT image inspection; according to the error cause corresponding to the out-of-control pass rate, determining the out-of-control pass rate to be removed includes:

[0146] S254. If the cause of the out-of-control pass rate can be found, the out-of-control pass rate is removed.

[0147] S256. If the reason for the out-of-control pass rate cannot be found, the out-of-control pass rate shall be retained.

[0148] S258. Among them, the proportion of all removed out-of-control pass rates in the transformed pass rate set does not exceed one third.

[0149] Specifically, the method for determining the uncontrolled pass rate includes IGRT image verification. IGRT (Image-guided radiation therapy) is a modern radiotherapy technology that combines medical imaging and radiotherapy technology to perform real-time or quasi-real-time anatomical and positional verification of patients during radiotherapy.

[0150] Furthermore, after image verification through IGRT, if the cause of the uncontrolled pass rate can be found, it means that the cause of the uncontrolled pass rate is an occasional specific error, so the uncontrolled pass rate can be directly removed from the transformed pass rate set; if the cause of the uncontrolled pass rate cannot be found, it means that the cause of the uncontrolled pass rate is a system error, and the system error requires further investigation by the doctor to solve it, so it is necessary to retain the uncontrolled pass rate with an unidentified cause.

[0151] It should be noted that the proportion of the removed out-of-control pass rate in the transformed pass rate data set does not exceed one-third, so as to avoid removing too much data, which will lead to a decrease in the credibility of the data in the subsequent calculation process.

[0152] As an embodiment of the present application, obtaining a current pass rate number set of a target subject suffering from a target disease includes:

[0153] S310. Collect the in-body dose distribution of the target object in the current radiotherapy fraction through EPID.

[0154] S320. According to the in-body dose distribution and the planned dose distribution of the current radiotherapy fraction, the gamma pass rate of the target object in the current radiotherapy fraction is obtained as the current pass rate number set.

[0155] Specifically, EPID (Electronic Portal Imaging Device) is a device used in radiotherapy, which is used to provide high-quality images during simulation positioning and planning, and monitor the treatment dose during treatment. EPID achieves the purpose of in-body dose monitoring by measuring the output change of the target object's transmission dose. Its main implementation method includes: first, the target object's transmission dose is estimated, and then the transmission dose is actually measured. According to the actual measurement result of the transmission dose, the actual dose distribution in the target object is reversed or reconstructed, and then compared with the planned dose distribution to obtain the corresponding gamma pass rate. This dose verification method based on the transmission monitoring of the target object, the obtained data not only includes the factors of radiotherapy equipment, but also includes the change factors of the target object, and almost takes into account all the factors that affect the actual dose distribution of the target object, which is the most ideal in-body dose verification method. In addition, EPID has the characteristics of high resolution, no angle response, simple and convenient measurement without affecting treatment, and real-time dose monitoring.

[0156] Furthermore, the in-body dose distribution in the radiotherapy fractionation is data collected by EPID at the time point corresponding to the radiotherapy fractionation, which is continuous data. In some embodiments, during the collection, the EPID device rotates around the part of interest of the target object, and measures the in-body dose distribution of the part of interest of the target object at the angle when reaching the set multiple angles.

[0157] In some embodiments, EPID can also be used to collect in-vivo data of the target object. In-vivo data generally refers to data collected in living animals or humans. These data reflect the real situation of the internal environment of the organism and are of great significance for evaluating drug safety, toxicity, and drug metabolism and dynamics. It can be understood that in this embodiment, the in-vivo data includes the in-vivo dose distribution and gamma pass rate of the target object's site of interest. In other embodiments, the corresponding data type can also be selected according to the actual scenario.

[0158] As an embodiment of the present application, the method further includes:

[0159] S330. If the mean gamma pass rate of the target object in the current radiotherapy fraction is lower than the current tolerance limit, it is determined that there is an out-of-control problem in the current radiotherapy fraction, and a warning is issued for the current radiotherapy fraction.

[0160] Specifically, if the current radiotherapy fractionation is out of control, it means that positioning errors or anatomical changes may occur in the current radiotherapy fractionation. At this time, it is necessary to alert the doctor performing radiotherapy that the current radiotherapy fractionation is out of control, thereby reminding the doctor to check the current radiotherapy fractionation and solve the possible problems in the current radiotherapy fractionation.

[0161] In some embodiments, when the gamma pass rate of the current radiotherapy fraction is collected through EPID, since EPID can perform real-time dose monitoring, after the gamma pass rate measurement at any angle of the part of interest of the target object is completed, it can be directly compared with the current tolerance limit, and it can be determined whether the current radiotherapy fraction is out of control. Therefore, the method for determining the radiotherapy tolerance limit provided in this embodiment is also real-time, and it is not necessary to determine whether it is out of control after the radiotherapy fraction is completed. It can be quickly determined during the radiotherapy fraction, and the radiotherapy fraction can be stopped in time when the out-of-control problem occurs.

[0162] In other embodiments, the method for determining the radiotherapy tolerance limit provided by the present application can also be used to monitor the radiotherapy process of a single target object in a targeted manner. In this embodiment, the method includes the following steps: obtaining the current tolerance limit of the target object suffering from the target disease; obtaining the current pass rate number set of the target object; using the current pass rate number set to update the historical pass rate number set of the target object to obtain an updated pass rate number set; performing normalization transformation and screening on the updated pass rate number set to obtain a transformed pass rate number set; repeatedly performing the step of screening the transformed pass rate number set until a controlled pass rate number set under a controlled state is obtained; using the control lower limit of the controlled pass rate number set to update the current tolerance limit value to obtain an updated tolerance limit value of the target object.

[0163] Among them, obtaining the current tolerance limit value of the target object suffering from the target disease includes:

[0164] S510. If the current radiotherapy fraction is the first radiotherapy fraction for the target object, the current tolerance limit is the initial tolerance limit;

[0165] S520. If the current radiotherapy fraction is not the first radiotherapy fraction for the target object, the current tolerance limit is the updated tolerance limit for the target object in the previous radiotherapy fraction.

[0166] Specifically, if the current radiotherapy fraction is the first radiotherapy fraction of the target object, the historical pass rate data set of the target object does not contain any data at this time. Therefore, for the first radiotherapy fraction of the target object, the initial tolerance limit of the target disease suffered by the target object can be used to make an out-of-control judgment, or the initial tolerance limit can be used for subsequent calculations.

[0167] Furthermore, if the current radiotherapy fraction is not the first radiotherapy fraction of the target object, the historical pass rate data set of the target object includes the gamma pass rate data of the target object in the radiotherapy fractions that have been performed. Therefore, for the subsequent radiotherapy fractions of the target object, the current tolerance limit value obtained by calculation can be used for out-of-control judgment and subsequent calculation.

[0168] In this embodiment, the method updates the historical pass rate number set based on the statistical data of the gamma pass rate of the target object in the radiotherapy fractionation, and finally obtains the updated tolerance limit value based on the updated pass rate number set, thereby improving the specificity of the updated tolerance limit value to the target object, thereby improving the guidance of the treatment effect on the target object and ensuring that the radiotherapy fractionation can be carried out normally.

[0169] The present application also provides a method for determining a radiotherapy tolerance limit, the method comprising:

[0170] S602. Obtain a historical pass rate data set of the target disease; wherein the historical pass rate data set includes the gamma pass rates of subjects suffering from the target disease in historical radiotherapy fractions.

[0171] S604. Determine four standard deviation points; wherein each standard deviation point corresponds to a gamma pass rate and is within the range of the historical pass rate number set. The standard deviation points are symmetrical about the center value of the historical pass rate number set, and the lengths between the standard deviation points are the same.

[0172] S606. Determine the percentile values ​​corresponding to the standard deviation points in the historical pass rate data set respectively.

[0173] S608. Determine the quantile ratio of the historical pass rate data set according to the difference between adjacent quantile values.

[0174] S610. Determine the target normalization transformation form for normalizing the historical pass rate data set according to the quantile ratio.

[0175] S612. If the quantile ratio is greater than 1, the target normalization transformation form is Jonhson SU distribution.

[0176] S614. If the quantile ratio is equal to 1, the target normalized transformation form is the Jonhson SL distribution.

[0177] S616. If the quantile ratio is less than 1, the target normalization transformation form is the Jonhson SB distribution.

[0178] S618. Perform a normalization transformation on the historical pass rate number set in the form of a target normalization transformation to obtain a transformed pass rate number set.

[0179] Specifically, steps S604 to S618 determine the target normalization transformation form, and perform normalization transformation on the historical pass rate number set in the target normalization transformation form, thereby obtaining a transformed pass rate number set, so that the transformed pass rate number set can meet the normality requirements in the calculation of radiotherapy tolerance limits, thereby improving the accuracy of radiotherapy tolerance limits, and the reliability of out-of-control judgment of the current radiotherapy fractionation of the target object based on the obtained radiotherapy tolerance limits.

[0180] S620. Determine the overall mean and overall range of the transformed pass rate set based on the mean gamma pass rate and the range of gamma pass rate of each radiotherapy fraction in the transformed pass rate set.

[0181] S622. Determine the lower control limit based on the difference between the overall mean and the overall range.

[0182] S624. Determine the out-of-control pass rate that is lower than the control lower limit of the transformed pass rate set in the transformed pass rate set.

[0183] S626. If the cause of the out-of-control pass rate can be identified, remove the out-of-control pass rate; if the cause of the out-of-control pass rate cannot be identified, retain the out-of-control pass rate; wherein, the proportion of the removed out-of-control pass rate in the transformed pass rate set does not exceed one third.

[0184] S628. Screen the transformed pass rate number set according to the control lower limit of the transformed pass rate number set to determine the intermediate pass rate number set in the state to be verified; and use the intermediate pass rate number set as the transformed pass rate number set.

[0185] S630. Repeat the above step of screening the transformed pass rate number set until a controlled pass rate number set in a controlled state is obtained; the controlled pass rate number set in a controlled state is the screened transformed pass rate number set.

[0186] S632. Calculate the lower control limit of the controlled pass rate set to obtain the current tolerance limit of the target disease.

[0187] Specifically, through the mean range control chart, the control lower limit of the data is calculated according to the overall mean and the overall range, so as to judge whether the radiotherapy fractionation is out of control according to the obtained control lower limit. The mean range control chart is simple and easy to use, can detect early problems in the control process, and has a wide range of applications. In other embodiments, the corresponding control chart type can also be selected according to the actual scenario, including but not limited to: mean standard deviation control chart, median range control chart and single value moving range control chart.

[0188] Furthermore, the method for determining the radiotherapy tolerance limit provided in the embodiment of the present application applies the statistical process control method to monitor the radiotherapy process, so as to update the historical pass rate data of the target disease according to the current pass rate number set of the target object, thereby dynamically adjusting the tolerance limit of the target disease and improving the guidance of the treatment effect on the target object.

[0189] Furthermore, the out-of-control judgment of the current radiotherapy fractionation of the target object suffering from the target disease is made based on the dynamically updated tolerance limit, thereby improving the controllability and stability of the radiotherapy process. At the same time, a quick judgment can be made when the radiotherapy fractionation is out of control, thereby analyzing the out-of-control radiotherapy fractionation, ensuring that the radiotherapy fractionation can proceed normally and improving the effect of the subsequent treatment process.

[0190] Accordingly, please refer to Fig.10 , an embodiment of the present application provides a system for determining a radiotherapy tolerance limit, the system comprising:

[0191] The historical data acquisition module 100 is used to acquire a historical pass rate data set of a target disease; wherein the historical pass rate data set includes the gamma pass rate of subjects suffering from the target disease in historical radiotherapy fractions.

[0192] The tolerance limit update module 200 is used to perform a normalization transformation on the historical pass rate number set to obtain a transformed pass rate number set; screen the transformed pass rate number set according to the control lower limit of the transformed pass rate number set to determine the intermediate pass rate number set in the state to be verified; use the intermediate pass rate number set as the transformed pass rate number set; repeat the above steps of screening the transformed pass rate number set until a controlled pass rate number set in a controlled state is obtained; calculate the control lower limit of the controlled pass rate number set to obtain the current tolerance limit of the target disease.

[0193] The current data acquisition module 300 is used to acquire a current pass rate number set of a target object suffering from a target disease; wherein the current pass rate number set includes the gamma pass rate of the target object in the current radiotherapy fraction.

[0194] The historical data updating module 400 is used to add the current pass rate set of the target object to the historical pass rate set for updating, and obtain an updated pass rate set; wherein the updated pass rate set is used as the historical pass rate set of the target disease for the next tolerance limit calculation.

[0195] As an embodiment of the present application, the tolerance limit value updating module 200 includes:

[0196] The target normalization transformation form determination unit is used to determine the target normalization transformation form according to the distribution of the gamma pass rate in the historical pass rate number set; wherein the distribution includes the central value of the historical pass rate number set and the quantile values ​​corresponding to different gamma pass rates.

[0197] The normalization transformation unit is used to perform normalization transformation on the historical pass rate number set in the form of target normalization transformation.

[0198] As an embodiment of the present application, the target normalization transformation form determination unit includes:

[0199] The standard deviation point determination subunit is used to determine four standard deviation points; wherein each standard deviation point corresponds to a gamma pass rate, and all are within the interval range of the historical pass rate number set, the standard deviation points are symmetrical around the central value of the historical pass rate number set, and the lengths between the standard deviation points are the same.

[0200] The quantile value determination subunit is used to respectively determine the quantile values ​​corresponding to the standard deviation points in the historical pass rate data set.

[0201] The quantile ratio determination subunit is used to determine the quantile ratio of the historical pass rate data set according to the difference between adjacent quantile values.

[0202] The target determination subunit is used to determine the target normalization transformation form for normalizing the historical pass rate data set according to the quantile value ratio.

[0203] As an embodiment of the present application, the target normalization transformation form includes Johnson SB distribution, Johnson SU distribution and Johnson SL distribution; the target determination subunit determines the target normalization transformation form according to the following rules:

[0204] If the quantile ratio is greater than 1, the target normalization transformation form is the Jonhson SU distribution.

[0205] If the quantile ratio is equal to 1, the target normalized transformation form is the Jonhson SL distribution.

[0206] If the quantile ratio is less than 1, the target normalization transformation form is the Jonhson SB distribution.

[0207] As an embodiment of the present application, the method for determining the control lower limit of the controlled pass rate number set is the same as the method for determining the control lower limit of the transformed pass rate number set; the tolerance limit value updating module 200 also includes:

[0208] The mean and range calculation unit is used to determine the overall mean and overall range of the transformed pass rate number set according to the gamma pass rate mean and gamma pass rate range of each radiotherapy fraction in the transformed pass rate number set.

[0209] The first lower control limit calculation unit is used to determine the lower control limit according to the difference between the overall mean and the overall range.

[0210] As an embodiment of the present application, the controlled pass rate number set in the controlled state is a transformed pass rate number set after screening; the tolerance limit value updating module 200 also includes:

[0211] The out-of-control pass rate determination unit is used to determine the out-of-control pass rate below the control lower limit in the transformed pass rate data set.

[0212] The out-of-control pass rate removal unit is used to determine the out-of-control pass rate that needs to be removed according to the error cause corresponding to the out-of-control pass rate, and remove the out-of-control pass rate that needs to be removed from the transformed pass rate number set to obtain an intermediate pass rate number set in a state to be verified.

[0213] As an embodiment of the present application, the tolerance limit value updating module 200 further includes:

[0214] The first judgment unit is used to remove part of the out-of-control pass rate, and if the cause of the out-of-control pass rate can be found, the out-of-control pass rate is removed;

[0215] The second judgment unit is used to retain part of the out-of-control pass rate. If the cause of the out-of-control pass rate cannot be found out, the out-of-control pass rate is retained;

[0216] Among them, the proportion of all out-of-control pass rates removed by the first judgment unit in the transformed pass rate number set does not exceed one third.

[0217] As an embodiment of the present application, the current data acquisition module 300 includes:

[0218] The in-body dose distribution acquisition unit is used to acquire the in-body dose distribution of the target object in the current radiotherapy fraction through EPID.

[0219] The gamma pass rate calculation unit is used to obtain the gamma pass rate of the target object in the current radiotherapy fraction according to the in-body dose distribution and the planned dose distribution of the current radiotherapy fraction as the current pass rate number set.

[0220] As an embodiment of the present application, the embodiment of the present application provides a system for determining a radiotherapy tolerance limit, which also includes an out-of-control warning module, for issuing a warning for out-of-control radiotherapy fractions. If the average gamma pass rate of the target object in the current radiotherapy fraction is lower than the current tolerance limit, it is determined that the current radiotherapy fraction has an out-of-control problem, and a warning is issued for the current radiotherapy fraction.

[0221] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0222] The radiotherapy tolerance limit determination system in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0223] The present application embodiment also provides a computer device, which includes: one or more processors, memory, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. The various components are connected to each other using different buses for communication, and can be installed on a common motherboard or installed in other ways as needed. The processor can process instructions executed in the computer device, including instructions stored in or on the memory to display graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system).

[0224] The processor may be a central processing unit, a network processor or a combination thereof. The processor may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0225] The memory stores instructions executable by at least one processor, so that the at least one processor executes the method shown in the above embodiment.

[0226] The memory may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory may optionally include a memory remotely arranged relative to the processor, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0227] The memory may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid state drive; the memory may also include a combination of the above types of memory.

[0228] The computer device also includes a communication interface, which is used for the computer device to communicate with other devices or a communication network.

[0229] The embodiment of the present application also provides a computer-readable storage medium. The above method according to the embodiment of the present application can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0230] The embodiment of the present application provides a computer program product, which includes computer instructions, which are stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the method of any embodiment of the present application.

[0231] Although the embodiments of the present application are described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present application, and such modifications and variations are all within the scope defined by the appended claims.

[0232] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0233] For the convenience of description, the above device is described in various units according to their functions. Of course, when implementing the present application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0234] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0235] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0236] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0237] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0238] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0239] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0240] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

[0241] Although the embodiments of the present application have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present application, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A method for determining a radiotherapy tolerance limit, characterized in that: The method comprises: Obtaining a historical pass rate data set for a target disease; wherein the historical pass rate data set includes gamma pass rates of subjects suffering from the target disease in historical radiotherapy fractions; Performing a normalization transformation on the historical pass rate number set to obtain a transformed pass rate number set; screening the transformed pass rate number set according to the control lower limit of the transformed pass rate number set to determine an intermediate pass rate number set in a state to be verified; using the intermediate pass rate number set as the transformed pass rate number set; repeatedly performing the above steps of screening the transformed pass rate number set until a controlled pass rate number set in a controlled state is obtained; calculating the control lower limit of the controlled pass rate number set to obtain the current tolerance limit value of the target disease; Acquire a current pass rate number set of a target subject suffering from the target disease; wherein the current pass rate number set includes a gamma pass rate of the target subject in a current radiotherapy fraction; The current pass rate number set of the target object is added to the historical pass rate number set for updating to obtain an updated pass rate number set; the updated pass rate number set is used as the historical pass rate number set of the target disease to perform the next tolerance limit calculation.

2. The method according to claim 1, characterized in that The normalization transformation of the historical pass rate number set to obtain the transformed pass rate number set includes: Determine the target normalization transformation form according to the distribution of the gamma pass rate in the historical pass rate data set; wherein the distribution includes the central value of the historical pass rate data set and the quantile values ​​corresponding to different gamma pass rates; The historical pass rate number set is subjected to normalization transformation in the target normalization transformation form.

3. The method according to claim 2, characterized in that Determining the target normalization transformation form according to the distribution of the gamma pass rate in the historical pass rate data set includes: Determine four standard deviation points; wherein each of the standard deviation points corresponds to a gamma pass rate and is within the interval range of the historical pass rate number set, the standard deviation points are symmetrical about the central value of the historical pass rate number set, and the lengths between the standard deviation points are the same; respectively determining the percentile values ​​corresponding to the standard deviation points in the historical pass rate data set; Determine the percentile ratio of the historical pass rate number set according to the difference between adjacent percentile values; The target normalization transformation form for normalizing the historical pass rate data set is determined according to the quantile ratio.

4. The method according to claim 3, characterized in that The target normalized transformation forms include Johnson SB distribution, Johnson SU distribution and Johnson SL distribution; the target normalized transformation form for normalizing the historical pass rate data set is determined according to the quantile ratio, including: If the quantile ratio is greater than 1, the target normalized transformation form is Jonhson SU distribution; If the quantile ratio is equal to 1, the target normalized transformation form is Jonhson SL distribution; If the quantile ratio is less than 1, the target normalized transformation form is the Jonhson SB distribution.

5. The method according to claim 1, characterized in that The method for determining the control lower limit of the controlled pass rate number set is the same as the method for determining the control lower limit of the transformed pass rate number set; the control lower limit of the transformed pass rate number set is determined by the following method: According to the gamma pass rate mean and gamma pass rate range of each radiotherapy fraction in the transformed pass rate set, determine the overall mean and overall range of the transformed pass rate set; The lower control limit is determined based on the difference between the population mean and the population range.

6. The method according to claim 1, characterized in that The controlled pass rate number set in the controlled state is the transformed pass rate number set after screening; screening the transformed pass rate number set according to the control lower limit of the transformed pass rate number set to determine the intermediate pass rate number set in the state to be verified includes: Determining, from the transformed pass rate number set, an out-of-control pass rate that is lower than a control lower limit of the transformed pass rate number set; According to the error cause corresponding to the out-of-control pass rate, the out-of-control pass rate that needs to be removed is determined, and the out-of-control pass rate that needs to be removed is removed from the transformed pass rate number set to obtain the intermediate pass rate number set in the state to be verified.

7. The method according to claim 6, characterized in that The method for finding out the cause of the uncontrolled pass rate includes IGRT image inspection; the determining the uncontrolled pass rate to be removed according to the error cause corresponding to the uncontrolled pass rate includes: If the cause of the out-of-control pass rate can be found, then the out-of-control pass rate is removed; If the cause of the out-of-control pass rate cannot be found, the out-of-control pass rate shall be retained; The proportion of all the removed out-of-control pass rates in the transformed pass rate set does not exceed one third.

8. The method according to claim 1, characterized in that The step of obtaining a current pass rate number set of a target subject suffering from the target disease includes: Acquiring, by means of EPID, the in-body dose distribution of the target object in the current radiotherapy fraction; According to the in-body dose distribution and the planned dose distribution of the current radiotherapy fraction, the gamma pass rate of the target object in the current radiotherapy fraction is obtained as the current pass rate number set.

9. The method according to any one of claims 1 to 8, characterized in that The method further comprises: If the mean gamma pass rate of the target object in the current radiotherapy fraction is lower than the current tolerance limit, it is determined that there is an out-of-control problem in the current radiotherapy fraction, and a warning is issued for the current radiotherapy fraction.

10. A system for determining a radiotherapy tolerance limit, characterized in that: The system comprises: A historical data acquisition module, used to acquire a historical pass rate data set of a target disease; wherein the historical pass rate data set includes the gamma pass rate of subjects suffering from the target disease in historical radiotherapy fractions; The tolerance limit update module is used to perform a normalization transformation on the historical pass rate number set to obtain a transformed pass rate number set; screen the transformed pass rate number set according to the control lower limit of the transformed pass rate number set to determine an intermediate pass rate number set in a state to be verified; use the intermediate pass rate number set as the transformed pass rate number set; repeatedly perform the above steps of screening the transformed pass rate number set until a controlled pass rate number set in a controlled state is obtained; calculate the control lower limit of the controlled pass rate number set to obtain the current tolerance limit value of the target disease; A current data acquisition module, used to acquire a current pass rate number set of a target subject suffering from the target disease; wherein the current pass rate number set includes a gamma pass rate of the target subject in a current radiotherapy fraction; The historical data updating module is used to add the current pass rate number set of the target object to the historical pass rate number set for updating to obtain an updated pass rate number set; and use the updated pass rate number set as the historical pass rate number set of the target disease to perform the next tolerance limit calculation.

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