CN111589000A - Method for verifying parameters of medical linear accelerator - Google Patents
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Abstract
The invention provides a method for verifying parameters of a medical linear accelerator, which solves the problem of radiotherapy safety accidents possibly caused in the radiotherapy process through information acquisition, analysis, simulation calculation and comparison methods. Log data is an important data resource existing in a linear accelerator system, but due to the huge log data amount, a common accelerator manufacturer only opens limited basic services for data acquisition and browsing. The invention provides a method for verifying parameters of a medical linear accelerator based on log data, which can monitor a linear accelerator system according to the actual requirements of a user, check the operation of an operator of the linear accelerator and analyze the log data.
Description
Technical Field
The invention belongs to the field of medical instruments, relates to an information acquisition, analysis, simulation calculation and comparison method of a medical linear accelerator control log file collector, and particularly relates to a method for verifying parameters of a medical linear accelerator.
Technical Field
In radiation therapy, strategies for treatment plan validation have evolved as the level of sophistication of the radiation therapy technique has changed. Currently, the strategy for treatment plan validation is to use a two-dimensional or three-dimensional ionization chamber matrix instead of the patient himself to validate the treatment plan. There are a number of drawbacks to doing so, including: 1. the two-dimensional or three-dimensional ionization chamber matrix is an off-line plan verification method, the operation state of the medical linear accelerator at the treatment moment cannot be acquired, and the difference of the operation states of the accelerator in the multiple treatment processes of a patient cannot be captured. For example, certain accelerator treatment errors or errors caused by changes of temperature, humidity, air pressure, electronic components and the like are difficult to capture through one-time off-line treatment plan verification; 2. the current verification method cannot give an alarm on the wrong treatment plan or the operation condition of the medical linear accelerator at the treatment moment. As mentioned above, using a two-dimensional or three-dimensional matrix of ionization chambers is an off-line planning validation method that does not allow estimation of accelerator parameter errors that may occur during treatment. In addition, in the operation process, accidents caused by improper operation cannot be eliminated through offline verification; 3. machine parameter performance analysis cannot be performed on a plan with a low ionization chamber matrix verification passing rate. The factors influencing the verification passing rate of the ionization chamber matrix are more, wherein one part of the factors is from errors or errors of parameters of the linear accelerator, the other part of the factors is from errors caused by executed treatment plans, and the errors or errors of the parameters of the linear accelerator are main factors and can be improved along with the improvement of the utilization rate and the failure rate of the linear accelerator; 4. the two-dimensional or three-dimensional ionization chamber matrix is influenced by the production process, and the ionization chamber has certain size limitation, so that the spatial resolution of the ionization chamber matrix can only reach a sub-centimeter level, and the problem of measurement noise exists. The treatment error required for intensity modulated radiotherapy cannot exceed 2mm, and for stereotactic radiotherapy the treatment error required cannot exceed 1 mm. The parameter error of millimeter level is difficult to find by the current ionization chamber matrix;
the problems are easy to cause the occurrence of radiotherapy safety accidents, and no effective solution is proposed at present.
Disclosure of Invention
The main purpose of the present application is to provide a method for verifying parameters of a medical linear accelerator, in order to achieve the above purpose, the present invention includes the following steps:
1. information acquisition: the log data of the medical linear accelerator host is acquired by a linear accelerator log data acquisition submodule 2 from the accelerator data processing control host 1 in a network mode.
1) On the data host 3, a UDP (User data packet Protocol) service process is created using a data transmission mode of a UDP Protocol, and log data transmitted through the UDP transmission mode is received to create data;
2) the acquisition mode comprises real-time acquisition of the running time of the linear accelerator (online mode) and acquisition from a patient database of the linear accelerator (offline mode);
3) the acquired data comprises parameters such as a rack angle, a collimator angle, a bed angle, a tungsten door position, a multi-leaf collimator leaf movement speed and the like in the treatment process of the linear accelerator;
4) and reading the data and updating the data into a database file of the data analysis processing host.
2. Data analysis and comparison: and acquiring an operation log file of the accelerator, and analyzing the operation log file. The plan data file is obtained according to the control point sequence, the running log file of the accelerator is obtained according to the time sequence, and the obtained running log file is converted into the control point sequence and compared with the plan data.
1) The log file analysis parameters comprise the frame angle, the collimator angle, the bed angle, the tungsten door position, the multi-leaf collimator leaf motion speed and the like acquired according to the time sequence in the treatment process of the linear accelerator, so as to obtain a parameterized self-defined file, store the parameterized self-defined file in a file management library module, and form formatted machine data according to the time sequence. Parameters from the planning system and operating parameters from the medical linear accelerator are mapped to a common Reference Coordinate Space (RCS) using analytical processing logic. And a linear accelerator log data analysis submodule 4 is used for converting a control point sequence into an analysis parameter file to be written in order, and simultaneously, the read-write load of a magnetic disk is reduced, and the data redundancy is reduced.
2) Treatment planning system 5 data is extracted and machine parameters in DICOMRT (digital imaging and communications in medicine) file format are extracted using a treatment planning data acquisition sub-module 6. The system is used for storing parameter information of the linear accelerator, including parameters such as a rack angle, a collimator angle, a bed angle, a tungsten door position, a multi-leaf collimator leaf movement speed and the like, test requirements and a matched diagnostic test sequence configuration file into a diagnostic test sequence database. And reading and updating the control point sequence into a database file of the data analysis processing host.
3) Acquiring trigger information of abnormal operation of the accelerator, comparing the plan parameters with the accelerator log parameters according to the control point sequence, and acquiring application program description information and recording the machine parameter state at the moment when the selected comparison parameters exceed a preset tolerance value; and sending an abnormal log record to a remote testing end according to the description information of the application program. So that the test end can call the corresponding case to carry out simulation verification; and further acquiring a simulation verification result fed back by the test end.
4) And (3) using the linear accelerator log data and the treatment plan data to query the submodule 7, and identifying the parameters needing to be compared according to the step 2) to obtain formatted data of the treatment machine. And the diagnostic test sequence configuration file is used for inquiring a preset diagnostic test sequence library according to the parameter information to be analyzed and compared and the test requirement, and acquiring the diagnostic test sequence configuration file matched with the parameter information to be diagnosed and the test tolerance value requirement. Comparing the parameters from the treatment planning system with the parameters from the medical linear accelerator to verify whether the parameters are performed correctly, wherein if the deviation of the two is less than the tolerance value, the treatment is verified.
5) And the plan and treatment data analysis processing submodule 8 is used for comparing the executed plan beam-out condition with the condition of a treatment plan system, and quickly analyzing and checking errors of actual in-place precision such as MU and actual irradiation, a frame angle, a collimator angle, a bed angle, a tungsten door position, a multi-leaf collimator leaf movement speed and the like. And acquiring a control point sequence configuration file matched with the parameter information to be diagnosed and the test requirement, and setting, listing, displaying and comparing according to different tolerance values.
3. And (3) flux simulation calculation: and (3) writing parameterization programs in different environments for a series of parameters generated by the log file by using a log file multi-leaf collimator data flux simulation submodule 9, constructing an isocentric plane flux geometric model of the linear accelerator, and performing analysis processing to implement comparison of simulation flux maps based on images. The simulated flux image results and the flux images from the treatment planning system mainframe 5 may be overlaid or displayed side-by-side in the linac log data and treatment plan data query sub-module 7. The comparative display may comprise lines, detection marks, showing the visible edges of the blade tip, using different colours. And displaying a blade warning boundary, a line representing the position of the front edge of the blade and the like according to the preset tolerance value. The analysis process may also perform simulated dose map comparisons from the image-based.
The flux simulation calculation is realized by the following steps:
(1) on the virtual treatment isocentric plane, a grid suitable for the calculated flux of the accelerator is established according to the geometric parameters of the leaves of the multi-leaf collimator, such as the leaf logarithm, the leaf width and the leaf stepping distance.
(2) And forming a gridding flux geometry by sub-fields according to the leaf log parameters of the multi-leaf collimator read from the log file.
(3) And determining the gridding flux size by sub-fields according to the sub-field machine hop number MU value read from the log file.
(4) And (4) superposing the results of the steps (2) to (3) by sub-fields to obtain simulated flux phi(s), wherein s represents any point in the flux map.
4 dose simulation calculation: the log file multi-leaf collimator data dose simulation submodule 10 is used for compiling parameterization programs of different environments for a series of parameters generated by a log file, constructing the equivalent water phantom dose distribution simulation calculation of the linear accelerator, obtaining the comparison between the actual irradiation dose and the planned dose distribution in the equivalent water phantom, and displaying the simulation result in the log data query submodule 7 of the linear accelerator and the treatment plan data query submodule. The compared dose distribution is absolute dose distribution or relative dose distribution, and whether the comparison result passes the verification is judged according to preset tolerance values.
The dose simulation calculation implementation steps are as follows:
(1) and establishing a geometric relation between the virtual source and the equivalent water phantom under a linear accelerator coordinate system.
(2) Dividing grids of a system consisting of a virtual source, an equivalent water mold body and air according to a fixed size, and endowing each grid with a certain density value, wherein if the grid is in the air, the density is 0; if the grid is in an equivalent water phantom, the density is 1.
(3) Starting from each grid in the equivalent water phantom, finding a path from the grid to the virtual source, recording medium density correction coefficients on the path, and recording the medium density correction coefficients as
Is any point in the phantom.
(4) Determining the flux obtained by each grid in the equivalent water phantom according to the flux in the module 22, and calculating the dose actually obtained after the flux attenuation of the grid according to the medium information in the step (3)
A pencil beam kernel.
(5) Calculating the equivalent water mold body grid by grid to obtain the simulation dosage
The invention relates to an information acquisition, analysis, simulation calculation and comparison method of a medical linear accelerator control log file collector, which aims to solve the problem of radiotherapy safety accidents possibly caused in the radiotherapy process. Log data is an important data resource existing in a linear accelerator system, but due to the huge log data amount, a common accelerator manufacturer only opens limited basic services for data acquisition and browsing. The invention provides a medical linear accelerator parameter verification method based on log data, which can monitor a linear accelerator system according to the actual requirements of a user, check the operation of an operator of the linear accelerator and analyze the log data. The verification method provided by the invention realizes the online verification of the radiotherapy plan by reading the high-precision log parameters and simulating the result of the simulation therapy plan, and the result more accurately reflects the actual irradiated dose of the patient. Compared with the existing method of verifying through a two-dimensional or three-dimensional detector array in an off-line mode, the method has more clinical practical significance.
Drawings
Fig. 1 is a flowchart of a method for collecting logs of control files of a medical linear accelerator according to the present invention.
Fig. 2 is a flowchart of a log file multi-leaf collimator data flux simulation method provided by the present invention.
Fig. 3 is a flowchart of a log file multi-leaf collimator data dose simulation method provided by the present invention.
Detailed Description
In order to make the technical solution of the present invention better understood, the technical solution of the present invention will be clearly and completely described below with reference to the accompanying drawings and examples, and it is obvious that the described examples are only a part of examples of the present invention, but not all examples. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1
Referring to fig. 1, the data host 3 uses the linear accelerator log data acquisition sub-module 2 to collect parameter data from the accelerator data processing control host 1. The acquired log data is written into a log file according to an accelerator beam-out control point sequence by using a linear accelerator log data analysis submodule 4, for example, a log file is generated during each subfield interval period and is sequentially written into the created log file, the log data is written into the log file according to the control point, the read-write load of a magnetic disk can be reduced, the data redundancy is reduced, the sequential writing of the log data can ensure the orderliness of the log data, and the comparison with a planned multi-leaf collimator file one by one is convenient. According to the application of the treatment plan data acquisition submodule 6 in the treatment plan system 5, the extracted DICOMRT data are compared, and a plurality of tolerance values are applied to different parameters. A confidence value is determined for each leaf position based on a comparison of the two, the deviation of the parameters is between 90% and 95%, the system may issue an alert, but the treatment may continue. If the deviation of the parameter has a confidence value of less than 90%, the system may generate an error and the treatment may be stopped. If the deviation of the parameter has a confidence value of 95% or higher, the system can determine that the plan is accurate and reliable.
Example 2
Referring to fig. 1, the linac log data and treatment plan data queries provide a continuous accelerator parameter data stream based on a medical linac validation system that continuously transmits real-time linac treatment status in a digitized form. The query submodule 7 may register pieces of information spatially and temporally using the linac log data and treatment plan data, and then present the pieces of information to the user in a unified form.
Example 3
Referring to fig. 1, readings of a displacement meter or encoder for each parameter from the accelerator data processing control main 1 may be acquired to determine analysis data. The linear accelerator log data acquisition submodule 2 accesses the parameter corresponding file every 50 ms. The gantry angle, collimator angle, bed angle, multi-leaf collimator, all have independent displacement meters or encoders to control the position of the recording of the corresponding parameters. The plan and treatment data analysis processing submodule 8 calls the log to perform detection firstly, including thread detection and method detection, wherein the thread detection mainly filters a thread which is similar to a timing task and continuously generates the log, the method detection detects the frequency of method calling within a certain time, filters out parameter values which are frequently and repeatedly called, and finally the extracted parameter values are processed and stored in a database in batch after reaching a fixed number. For the detected abnormal state, dynamically executing a section of code and reporting the result, and recording the abnormality according to two important occasions: the method is executed immediately and the method is executed thereafter. Immediately executing the following steps: after receiving the signaling, immediately executing and reporting the result; the method is followed by: and dynamically acquiring information such as return values, parameter change, object field change and the like after treatment is finished.
Example 4
Referring to fig. 1 and 2, a log file multi-leaf collimator data flux simulation submodule 9 written by a high-level programming language is used for simulating a simulation flux distribution file of the stop position, time, dose rate and corresponding sub-field machine hop count of the multi-leaf collimator by using a parameter output interface provided by a linear accelerator log data and treatment plan data query submodule 7, and parameters are identified. The static multi-leaf collimator stay position parameters are used for establishing the sub-field geometric shape, and the time and dose rate parameters are used for verifying and comparing with the corresponding sub-field machine hop count. Leaf placement accuracy analysis the treatment plan leaf position values were subtracted from the actual treatment leaf position values, assuming that there were n sub-fields in each main field direction, and 80 leaf positions in each sub-field, for a total of 80 x n position deviation values. The blade deviation of a single pair is σ ═ xp-xlWherein x ispFor the treatment planning position of the leaf, xlThe location for the blade obtained from the log file. In another embodiment, the dynamic multi-leaf collimator, for n control points, has total leaf deviation of
The change in the leaf pitch during treatment is judged by the value of σ being less than, equal to, or greater than 0.
Example 5
Referring to fig. 1 and 3, a log file multi-leaf collimator data dose simulation submodule 10 is used, the flux result obtained by a log file multi-leaf collimator data flux simulation submodule 9 is combined with a parameter output interface provided by a linear accelerator log data and treatment plan data query submodule 7, the actual irradiation dose in an equivalent water phantom is simulated and calculated and compared with the planned dose distribution, and the simulation result can be displayed in the linear accelerator log data and treatment plan data query submodule 7. Various dose alignment methods are employed, for example: comparing the distribution from the treatment planning system host 5 with the distribution from the simulation of the medical linear accelerator by methods such as dose distribution difference analysis, consistent distance analysis DTA, gamma analysis and the like; the dose distribution compared may be an absolute dose distribution or a relative dose distribution. And judging whether the comparison result passes the verification or not according to a preset tolerance value. For example, the criteria for comparison are that in gamma analysis, the dose deviation of the dose reference point within 3mm is within 3% and the gamma pass rate is above 95%. When the comparison meets this criterion, the treatment regimen is adapted to continue treatment; and if the standard requirements cannot be met, the plan is re-made.
Example 6
The DICOMRT-type treatment plan file may be parsed using a DICOMRT-regularized parsing rule. DICOMRT specifies many aspects of radiation therapy, including 5 basic subjects for radiation therapy images, radiation therapy dose, radiation therapy plan, etc. In the above steps, the analysis rule of the log file on the target host is determined according to the log type of the target host, and the analysis rule of the log file on the target host is determined. In one embodiment, the definition of the collimator's leaf boundary and leaf position data is based on DICOMRT and is referenced to a coordinate system defined by "radiotherapy apparatus-coordinate, motion and scale" in conjunction with the IEC 61217 standard. The coordinate data of the leaves of the multi-leaf collimator is stored according to 2 modes: (1) along the X direction, the storage sequence of the blade boundary is Y1 and Y2 … … Yn + l, and the blade positions are X11 and X12 … … X1 n; x21, X22 … … X2 n; (2) along the Y direction, the X and Y coordinates are inverted. According to the definition of DICOMRT, the concept of subdomain control points is used. The aim is to model the settings of the machine parameters for various types of external illumination (static, dynamic, arc) during the illumination process. Such as: a gantry, a collimator, a bed, etc., and can track parameters such as machine hop count during the illumination process. Each illumination process is described by a sequence of 1 control point. Typically, control point 0(CP0) includes all initial parameters except the bed position, and every 1 control point thereafter records changes in various machine parameters. In addition, the concept of accumulating the weight of the hop count of the machine is also introduced into the content of the control point. For calculating the machine jump value of the control point. According to the same method, namely a control point sequence structure, the log data is written into the log file, so that the orderliness of the log data is ensured, and the comparison is convenient.
Claims (5)
1. A method for verifying parameters of a medical linear accelerator is characterized by comprising the following steps:
(1) information acquisition: the log data of the medical linear accelerator host is acquired by a linear accelerator log data acquisition submodule (2) from the accelerator data processing control host (1) in a network mode;
(2) data analysis and comparison: acquiring an operation log file of an accelerator, analyzing the operation log file, acquiring a plan data file according to a control point sequence, acquiring the operation log file of the accelerator according to a time sequence, converting the acquired operation log file into the control point sequence, and comparing the acquired operation log file with plan data;
(3) and (3) flux simulation calculation: using a log file multi-leaf collimator data flux simulation submodule 9, compiling parameterization programs of different environments for a series of parameters generated by a log file, constructing a linear accelerator isocentric plane flux geometric model, displaying a simulation flux image result and a flux image from a treatment planning system host 5 in a linear accelerator log data and treatment planning data query submodule 7 in a covering or parallel mode, and displaying a leaf warning boundary and a line representing the position of a leaf front edge according to a preset tolerance value by using different colors, wherein the lines and detection marks show visible edges of the leaf tops and are displayed in a contrasting mode;
(4) dose simulation calculation: analyzing and processing the comparison of the simulated dose map based on the image, combining the flux result obtained by the log file multi-leaf collimator data flux simulation submodule 9, simulating and calculating the comparison between the actual irradiation dose and the planned dose distribution in the equivalent water phantom, displaying the simulation result in the linear accelerator log data and treatment plan data query submodule 7, and adopting a plurality of dose comparison methods, for example: comparing the distribution from the treatment planning system host 5 with the distribution from the simulation of the medical linear accelerator by methods such as dose distribution difference analysis, consistent distance analysis DTA, gamma analysis and the like; the compared dose distribution is absolute dose distribution or relative dose distribution, and whether the comparison result passes the verification is judged according to preset tolerance values.
2. The method according to claim 1, characterized in that step (1) is not achieved in particular by:
1) on a data host (3), a user data packet service process is established by using a data transmission mode of a user data packet protocol, and log data sent by the user data packet transmission mode is received to establish data;
2) the acquisition mode comprises the real-time acquisition of the running time of the linear accelerator and the acquisition from a patient database of the linear accelerator;
3) the acquired data comprises the angle of a frame, the angle of a collimator, the angle of a bed, the position of a tungsten door, the positions of the blades of a multi-blade collimator and the movement speed parameters of the blades of the multi-blade collimator in the treatment process of the linear accelerator;
4) and reading the data and updating the data into a database file of the data analysis processing host.
3. The method according to claim 1, characterized in that step (2) is realized in particular by the following steps:
1) the log file analysis parameters comprise a rack angle, a collimator angle, a bed angle, a tungsten door position, a multi-leaf collimator leaf position and a multi-leaf collimator leaf motion speed which are acquired according to a time sequence in the treatment process of the linear accelerator, a parameterized self-defined file is obtained and stored in a file management library module, formatted machine data is formed according to the time sequence, parameters from a planning system and operation parameters from the medical linear accelerator are mapped to a common reference coordinate space by using an analysis processing logic, a linear accelerator log data analysis submodule 4 is used for converting the parameters into a control point sequence and orderly writing the parameters into an analysis parameter file, the read-write load of a disk is reduced, and data redundancy is reduced;
2) extracting data of a treatment planning system 5, using a treatment planning data acquisition sub-module 6 to extract machine parameters in a format of a medical digital imaging and communication radiotherapy file, and storing parameter information of the linear accelerator, including a rack angle, a collimator angle, a bed angle, a tungsten door position, a leaf position of a multi-leaf collimator, a leaf movement speed parameter of the multi-leaf collimator, a test requirement and a matched diagnosis test sequence configuration file into a diagnosis test sequence database, reading and updating the data into a data analysis processing host database file according to a control point sequence;
3) acquiring trigger information of abnormal operation of the accelerator, comparing the plan parameters with the accelerator log parameters according to the control point sequence, and acquiring application program description information and recording the machine parameter state at the moment when the selected comparison parameters exceed a preset tolerance value; sending abnormal log records to a remote testing end according to the description information of the application program so as to be convenient for the testing end to call a corresponding case to carry out analog simulation verification; further acquiring a simulation verification result fed back by the test end;
4) using a linear accelerator log data and treatment plan data query submodule 7, identifying parameters to be compared according to the step 2), obtaining formatted data of a therapeutic machine, querying a preset diagnosis test sequence library according to the parameter information to be analyzed and compared and test requirements, obtaining a diagnosis test sequence configuration file matched with the parameter information to be diagnosed and the test tolerance value requirements, and comparing the parameters from a treatment plan system and the parameters from a medical linear accelerator to verify whether the parameters are correctly executed, wherein if the deviation of the parameters is smaller than the tolerance value, the treatment passes the verification;
5) and a plan and treatment data analysis processing submodule 8 is used for comparing the beam-out condition of the executed plan with the condition of a treatment plan system, quickly analyzing and checking errors of MU and actual irradiation, a frame angle, a collimator angle, a bed angle, a tungsten door position, leaf positions of a multi-leaf collimator and the actually-in-place precision of the leaf movement speed of the multi-leaf collimator, acquiring a control point sequence configuration file matched with parameter information to be diagnosed and test requirements, setting, listing, displaying and comparing according to different tolerance values.
4. The method of claim 1, wherein the step (3) of flux simulation calculation is implemented by the steps of:
(1) on a virtual treatment isocentric plane, establishing a grid suitable for the accelerator for calculating flux according to the geometric parameters of the leaves of the multi-leaf collimator, such as the leaf logarithm, the leaf width and the leaf stepping distance;
(2) forming a gridding flux geometric shape by sub-fields according to leaf log parameters of the multi-leaf collimator read from a log file;
(3) determining the size of gridding flux by sub-fields according to the sub-field machine hop number MU value read from the log file;
(4) and (4) superposing the results of the steps (2) to (3) by sub-fields to obtain simulated flux phi(s), wherein s represents any point in the flux map.
5. The method of claim 1, wherein the dose simulation calculation in step (4) is implemented by the steps of:
(1) establishing a geometric relation between a virtual source and an equivalent water mold body under a linear accelerator coordinate system;
(2) dividing grids of a system consisting of a virtual source, an equivalent water mold body and air according to a fixed size, and endowing each grid with a certain density value, wherein if the grid is in the air, the density is 0; if the grid is in an equivalent water mold body, the density is 1;
(3) starting from each grid in the equivalent water phantom, finding a path from the grid to the virtual source, recording medium density correction coefficients on the path, and recording the medium density correction coefficients as
Is any point in the die body;
(4) from the flux in module 22, each mesh in the equivalent water phantom is determinedThe flux is obtained, and then the dose actually obtained after the grid is attenuated by the flux is calculated according to the medium information in the step (3)
A pencil beam kernel;
(5) calculating the equivalent water mold body grid by grid to obtain the simulation dosage
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| CN116328214A (en) * | 2023-05-30 | 2023-06-27 | 福建自贸试验区厦门片区Manteia数据科技有限公司 | Detection device for execution status of radiotherapy plan, electronic device, and storage medium |
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