Method and device for constructing pen-shaped beam model in particle treatment planning system

Abstract

The invention provides a pen-shaped beam model construction method and device in a particle treatment planning system, equipment, a medium and a program product, which can be applied to the technical field of radiotherapy. The pen beam model construction method in the particle therapy planning system comprises the following steps: obtaining integral depth dose measurement data, beam spot measurement data and absolute dose measurement data of particle therapy equipment in the particle therapy planning system; respectively constructing an integral depth dose model, a beam spot model and an absolute dose model based on the integral depth dose measurement data, the beam spot measurement data and the absolute dose measurement data, and forming a pen beam model of the particle therapy equipment; performing simulation verification on the pen-shaped beam model, and adjusting corresponding parameters in the pen-shaped beam model according to difference data between simulation data and actual measurement data; and generating at least one quality assurance plan of the adjusted pen-shaped beam model under the condition that the adjusted pen-shaped beam model meets a preset error condition.

Description

Technical Field

[0001] The present invention relates to the field of radiotherapy technology, and in particular to a method, device, equipment, medium and program product for constructing a pencil beam model in a particle therapy planning system. Background Art

[0002] Particle therapy (such as carbon ion therapy) is an advanced radiotherapy technology with Bragg peak characteristics, which can kill tumor cells more accurately while reducing damage to surrounding normal tissues. The Pencil Beam Model is the core model used for dose calculation in the particle therapy planning system, and its accuracy directly affects the accuracy of the treatment plan and the treatment effect.

[0003] At present, in some particle therapy planning systems (TPS), the modeling process of pencil beam models mainly relies on manual measurement and supplier modeling, which is time-consuming and lacks automation. Therefore, it is particularly important to develop a method that can automatically and accurately establish pencil beam models in particle therapy planning systems. Summary of the invention

[0004] In view of the above problems, the present invention provides a method, device, equipment, medium and program product for constructing a pencil beam model in a particle therapy planning system, which improves the efficiency and accuracy of pencil beam model construction.

[0005] According to a first aspect of the present invention, a method for constructing a pencil beam model in a particle therapy planning system is provided, comprising: acquiring integrated depth dose measurement data, beam spot measurement data and absolute dose measurement data of a particle therapy device in the particle therapy planning system; constructing an integrated depth dose model, a beam spot model and an absolute dose model based on the integrated depth dose measurement data, the beam spot measurement data and the absolute dose measurement data, respectively, to form a pencil beam model of the particle therapy device; performing simulation verification on the pencil beam model, and adjusting corresponding parameters in the pencil beam model according to difference data between the simulation data and the measured data; and generating at least one quality assurance plan for the adjusted pencil beam model when the adjusted pencil beam model meets a preset error condition.

[0006] According to an embodiment of the present invention, integrated depth dose measurement data, beam spot measurement data and absolute dose measurement data of a particle therapy device in a particle therapy planning system are obtained, including: performing data cleaning on the collected data of the particle therapy device to obtain format-standardized data; and extracting the integrated depth dose measurement data, beam spot measurement data and absolute dose measurement data from the format-standardized data.

[0007] According to an embodiment of the present invention, integrated depth dose measurement data, beam spot measurement data and absolute dose measurement data are extracted from format standardized data, including: identifying abnormal data in the format standardized data; extracting integrated depth dose measurement data, beam spot measurement data and absolute dose measurement data from the format standardized data that avoids the abnormal data.

[0008] According to an embodiment of the present invention, based on the integrated depth dose measurement data, the beam spot measurement data and the absolute dose measurement data, an integrated depth dose model, a beam spot model and an absolute dose model are respectively constructed, including: obtaining a Monte Carlo standard basic database, the Monte Carlo standard basic database containing simulation results of monoenergetic beam spots within the therapeutic energy range in pure water; extracting monoenergetic Monte Carlo integrated depth dose data close to the beam energy drawn out by each accelerator from the Monte Carlo standard basic database; based on the integrated depth dose measurement data, performing weighted fitting on the monoenergetic Monte Carlo integrated depth dose data, and determining the weighted energy spectrum after fitting.

[0009] According to an embodiment of the present invention, based on the integrated depth dose measurement data, the beam spot measurement data and the absolute dose measurement data, an integrated depth dose model, a beam spot model and an absolute dose model are respectively constructed, including: fitting the beam spot measurement data, determining the transport parameters of the beam spot in the air, and establishing a beam spot model in the air; fitting the Gaussian distribution of the lateral scattering of particles in water, determining the lateral scattering parameters of the beam spot in the water, and establishing a beam spot model in water; determining the beam spot size at any underwater depth according to the beam spot sizes determined by the beam spot model in the air and the beam spot model in water.

[0010] According to an embodiment of the present invention, based on the integrated depth dose measurement data, the beam spot measurement data and the absolute dose measurement data, an integrated depth dose model, a beam spot model and an absolute dose model are respectively constructed, including: extracting lattice information and beam characteristic information from the absolute dose measurement data; determining the theoretical dose at the calibration depth based on the lattice information and the beam characteristic information; calibrating the theoretical dose to the absolute dose measurement data through a correction coefficient to generate an absolute dose correction curve.

[0011] According to an embodiment of the present invention, a pencil beam model is simulated and verified, and corresponding parameters in the pencil beam model are adjusted according to the difference data between the simulation data and the measured data, including: determining the theoretical half-width data of a single beam spot in water according to the pencil beam model; comparing the theoretical half-width data with the measured half-width data, and completing the transport characteristic verification of the single beam spot when the comparison error is within a preset range.

[0012] According to an embodiment of the present invention, a particle therapy planning system includes a range shifter; forming a pencil beam model of a particle therapy device further includes: determining a transport parameter downstream of the range shifter based on the scattering power of a material of the range shifter and a transport parameter upstream of the range shifter, and the downstream transport parameter is used as an updated transport parameter.

[0013] A second aspect of the present invention provides a device for constructing a pencil beam model in a particle therapy planning system, comprising: an acquisition module, used to acquire integrated depth dose measurement data, beam spot measurement data and absolute dose measurement data of a particle therapy device in the particle therapy planning system; a modeling module, used to construct an integrated depth dose model, a beam spot model and an absolute dose model respectively based on the integrated depth dose measurement data, the beam spot measurement data and the absolute dose measurement data, so as to form a pencil beam model of the particle therapy device; a verification module, used to simulate and verify the pencil beam model, and adjust corresponding parameters in the pencil beam model according to difference data between the simulation data and the measured data; and a generation module, used to generate at least one quality assurance plan for the adjusted pencil beam model when the adjusted pencil beam model meets a preset error condition.

[0014] A third aspect of the present invention provides an electronic device, comprising: one or more processors; a memory for storing one or more computer programs, wherein the one or more processors execute the one or more computer programs to implement the steps of the above method.

[0015] The fourth aspect of the present invention further provides a computer-readable storage medium on which a computer program or instruction is stored, and the steps of the above method are implemented when the above computer program or instruction is executed by a processor.

[0016] The fifth aspect of the present invention also provides a computer program product, including a computer program or instructions, which implement the steps of the above method when executed by a processor.

[0017] According to the pencil beam model construction method, device, equipment, medium and program product in the particle therapy planning system of the embodiment of the present invention, by integrating the integrated depth dose, beam spot and absolute dose data, a high-precision pencil beam model can be quickly constructed. Based on the difference between the simulation and the measured data, the model parameters are dynamically adjusted to ensure the accuracy of the model. A quality assurance plan is generated to verify the reliability of the model, thereby supporting the safety and effectiveness of clinical treatment. The use of automated processes to improve modeling efficiency can meet clinical and regulatory requirements and provide a reliable foundation for particle therapy. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The above contents and other objects, features and advantages of the present invention will become more apparent through the following description of the embodiments of the present invention with reference to the accompanying drawings, in which:

[0019] Figure 1 A flowchart of a method for constructing a pencil beam model in a particle therapy planning system according to an embodiment of the present invention is schematically shown;

[0020] Figure 2 A diagram schematically shows a comparison of integrated depth dose results of measurement and automatic modeling according to an embodiment of the present invention;

[0021] Figure 3 A beam spot automatic modeling parameter curve diagram according to an embodiment of the present invention is schematically shown;

[0022] Figure 4 A diagram schematically shows a comparison between the measurement and calculation of the automatic modeling of a beam spot in air according to an embodiment of the present invention;

[0023] Figure 5 A schematic diagram showing a comparison of beam spot sizes measured by RS and automatically modeled according to an embodiment of the present invention;

[0024] Figure 6 A curve diagram schematically showing the result of automatic modeling of an absolute dose conversion curve according to an embodiment of the present invention;

[0025] Figure 7 A schematic diagram showing a comparison of depth dose curves measured by a national standard plan and calculated by automatic modeling according to an embodiment of the present invention;

[0026] Figure 8 A diagram schematically shows a comparison of transverse dose curves measured by a national standard plan and calculated by automatic modeling according to an embodiment of the present invention;

[0027] Fig. 9 A diagram schematically shows a comparison of the results of patient plan measurement and dose calculation based on automatic modeling according to an embodiment of the present invention;

[0028] Fig.10 A schematic diagram of a structure of a pencil beam model building device in a particle therapy planning system according to an embodiment of the present invention is shown;

[0029] Fig.11 The block diagram of an electronic device suitable for implementing a pencil beam model building method in a particle therapy planning system according to an embodiment of the present invention is schematically shown. DETAILED DESCRIPTION

[0030] Below, embodiments of the present invention will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present invention. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of embodiments of the present invention. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of concepts of the present invention.

[0031] The terms used herein are only for describing specific embodiments and are not intended to limit the present invention. The terms "comprise", "include", etc. used herein indicate the existence of features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0032] All terms (including technical and scientific terms) used herein have the meanings commonly understood by those skilled in the art unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification and should not be interpreted in an idealized or overly rigid manner.

[0033] When using expressions such as "at least one of A, B, and C, etc.", they should generally be interpreted according to the meaning of the expression commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

[0034] In this article, the particles used in the treatment planning system can be carbon ions or protons. The present invention does not limit specific particles, and other particles that can be applied to the pencil beam model construction method of the present invention should be included in the protection scope of the present invention.

[0035] Figure 1 The flowchart of the method for constructing a pencil beam model in a particle therapy planning system according to an embodiment of the present invention is schematically shown.

[0036] like Figure 1 As shown, the method for constructing a pencil beam model in the particle therapy planning system of this embodiment includes operations S110 to S140.

[0037] In operation S110 , integrated depth dose measurement data, beam spot measurement data, and absolute dose measurement data of a particle therapy device in a particle therapy planning system are acquired.

[0038] Integrated Depth Dose (IDD) can describe the variation of the dose deposited by a particle beam in a material with depth, with depth (cm) as the horizontal axis and dose (Gy or relative dose) as the vertical axis. IDD measurement data may include measured depth, measured dose, etc. Spot profile can describe the dose distribution of a particle beam in a direction perpendicular to the beam, and can be used to evaluate the lateral characteristics of the beam. Spot measurement data may include energy, measured depth, spot size, and other data. Absolute dose refers to the absolute dose value measured under specific conditions, and can be used for dose calibration and verification. Absolute dose measurement data may include energy, calibration depth, water surface distance, dose, and other data.

[0039] In operation S120, based on the integrated depth dose measurement data, the beam spot measurement data and the absolute dose measurement data, an integrated depth dose model, a beam spot model and an absolute dose model are respectively constructed to form a pencil beam model of the particle therapy device.

[0040] Automatic modeling is carried out around IDD, beam spot, and absolute dose. Specifically, the integrated depth dose model is constructed based on the integrated depth dose measurement data, the beam spot model is constructed based on the beam spot measurement data, and the absolute dose model is constructed based on the absolute dose measurement data. The integrated depth dose model, beam spot model, and absolute dose model and their parameters together form a pencil beam model.

[0041] In operation S130 , simulation verification is performed on the pencil beam model, and corresponding parameters in the pencil beam model are adjusted according to difference data between the simulation data and the measured data.

[0042] During the simulation verification process, the integrated depth dose model, beam spot model and absolute dose model can be verified separately, and the parameters in the corresponding models can be adjusted according to the verification data. When each model passes the verification, the verification process of the entire pencil beam model is completed.

[0043] In operation S140 , if the adjusted pencil beam model meets a preset error condition, at least one quality assurance plan of the adjusted pencil beam model is generated.

[0044] The preset error condition can be reasonably set according to specific needs, and this embodiment does not make specific limitations. As an example, the quality assurance (QA) plan may include a QA plan that complies with the relevant laws and regulations of the region where the particle therapy planning system is located, and may also include a treatment plan for a specific patient. Through these quality assurance plans, the generated pencil beam model is further verified to ensure device performance, treatment plan accuracy, and patient safety.

[0045] According to the method for constructing a pencil beam model in a particle therapy planning system according to an embodiment of the present invention, a high-precision pencil beam model can be quickly constructed by integrating the integrated depth dose, beam spot and absolute dose data. Based on the difference between the simulation and measured data, the model parameters are dynamically adjusted to ensure the accuracy of the model. A quality assurance plan is generated to verify the reliability of the model, thereby supporting the safety and effectiveness of clinical treatment. The use of automated processes to improve modeling efficiency can meet clinical and regulatory requirements and provide a reliable foundation for particle therapy.

[0046] Based on the above embodiment, the above operation S110 may include: performing data cleaning on the collected data of the particle therapy device to obtain format-standardized data; and extracting integrated depth dose measurement data, beam spot measurement data and absolute dose measurement data from the format-standardized data.

[0047] In this embodiment, data collection can be completed by the monitoring system, external detector or log file of the device. The collected data is formatted and converted into a standard format that can be read by the automatic modeling algorithm. For example, data from different sources can be converted into a unified format, such as CSV, JSON or database format. When data comes from multiple devices or sensors, timestamp alignment can be performed to ensure that the timestamps of all data are aligned. Unit unification can also be performed to unify the data units into international standard units, such as dose units unified into Gy and depth units unified into cm.

[0048] As an example, the required parameters can be automatically extracted from the header in the format standardized data, for example, the range modulator, isocenter to snout distance, isocenter to phantom surface distance, detector lateral side / diameter, nominal beam energy, air profile Z pos, spot spacing and other parameters. Then, the integrated depth dose measurement data, beam spot measurement data and absolute dose measurement data are automatically extracted from these data. The depth dose measurement data may include the measured depth and the measured dose. The beam spot measurement data may extract different parameter data according to different measurement methods. For example, when measured by Lynx, the energy, measured depth, measured horizontal coordinate and measured dose may be extracted. For example, when measured by a stripe detector, the energy, measured depth and beam spot size may be extracted. The absolute dose measurement data may include energy, calibration depth, water surface distance and dose. The extracted data may be listed in an energy list, and the energy list may be used as a collection of all beam energies used in the treatment plan.

[0049] In some embodiments, integrated depth dose measurement data, beam spot measurement data and absolute dose measurement data are extracted from format standardized data, including: identifying abnormal data in the format standardized data; extracting integrated depth dose measurement data, beam spot measurement data and absolute dose measurement data from the format standardized data avoiding the abnormal data.

[0050] Abnormal data can refer to some wrong data. For example, the beam spot size should be larger the farther away from the source, and it should conform to the quadratic divergence. When the measured data does not conform to the quadratic divergence, it can be considered as wrong data. To avoid wrong data, an outlier detection algorithm based on Z-score can be used to automatically avoid data with a Z score exceeding 1.

[0051] By automatically preprocessing, cleaning, format conversion and calibration of the measurement data obtained from the particle therapy equipment, it not only reduces manual intervention and improves the efficiency and accuracy of data processing, but also ensures the stability and reliability of the subsequent modeling process.

[0052] Based on the above embodiments, the following describes the process of constructing an integrated depth dose model, a beam spot model and an absolute dose model based on the integrated depth dose measurement data, the beam spot measurement data and the absolute dose measurement data.

[0053] The process of automatically constructing an integrated depth dose model may include: obtaining a Monte Carlo standard basic database, which contains simulation results of monoenergetic beam spots in a therapeutic energy range in pure water; extracting monoenergetic Monte Carlo integrated depth dose data close to the beam energy drawn out by each accelerator from the Monte Carlo standard basic database; and performing weighted fitting on the monoenergetic Monte Carlo integrated depth dose data based on the integrated depth dose measurement data to determine the weighted energy spectrum after fitting.

[0054] In the systematization of treatment planning, the Bragg peak of the beam drawn from the accelerator is broadened after transportation and passing through the ridge filter, and its longitudinal distribution forms a broadened IDD curve. Because each treatment head has different transmission lines and different ridge filter processing designs, the IDD curve of each treatment head must be modeled separately. The broadened IDD curve can be regarded as the weighted sum of multiple single-energy IDDs, and its physical meaning is that the energy spectrum has changed after passing through the ridge filter. For each beam energy drawn from the accelerator, the automatic modeling algorithm finds its neighboring single-energy Monte Carlo IDD data, and fits the weighted energy spectrum through the automatic fitting algorithm so that its sum is equal to the measured IDD curve. The single-energy Monte Carlo IDD data comes from the Monte Carlo standard basic database, which is usually a single-energy beam spot covering all energy ranges for treatment in pure water, such as 10 MeV / u to 450MeV / u, and the IDD is recorded with a set virtual detector radius. The energy interval can be 1mm as the range interval, and the source geometry is a point source.

[0055] The process of automatically constructing a beam spot model may include: fitting the beam spot measurement data, determining the transport parameters of the beam spot in the air, and establishing a beam spot model in the air; fitting the Gaussian distribution of the lateral scattering of particles in water, determining the lateral scattering parameters of the beam spot in water, and establishing a beam spot model in water; determining the beam spot size at any underwater depth based on the beam spot sizes determined by the beam spot model in the air and the beam spot model in water.

[0056] The automatic modeling of beam spot can be divided into two parts: the modeling of beam spot in air and the modeling of beam spot in water. The automatic modeling of beam spot in air can be based on the Fermi-Eyges theory. Specifically, the automatic modeling algorithm can automatically fit the half-width at half maximum (Lynx measurement) or directly read the FWHM (strip measurement) for the beam spot measurement data in air. Based on the Fermi-Eyges theory, the transport of the beam spot in air is fitted for each energy. The fitting parameters are a, b, and c, which represent angular spread, beam divergence, and spot size, also known as transport parameters. The relationship between them can be shown in Formula 1:

[0057] (Formula 1)

[0058] Where z represents the measurement depth in air, c(0) and c(z) represent the beam spot size at depth 0 and depth z, respectively, and a(0) and b(0) represent the angular divergence and beam divergence at depth 0, respectively. In order to make the fitting results comply with the physical meaning and the fitting algorithm converge better, the upper and lower limits of a, b, and c can be set to (0, 0.01) rad, (0, 0.1) mm rad, and (0, 2*half-height width) mm.

[0059] Automatic modeling of beam spot in water can be based on the Monte Carlo standard basic database. Usually, a monoenergetic beam spot covering all energy ranges for treatment is simulated in pure water, and the scattering radius of each particle type in the lateral direction at each depth is recorded. Since the lateral scattering of carbon ions is not accurately described by a single Gaussian distribution, the particle type needs to be distinguished as primary particles, secondary heavy ions (atomic number greater than or equal to 3), and secondary light ions (atomic number less than 3), and three Gaussian superpositions of different sizes are used. The three Gaussian distributions can be automatically fitted to the Monte Carlo simulation data through the automatic modeling algorithm.

[0060] Through the above-mentioned beam spot modeling in air and water, the automatic modeling of the beam spot at any underwater depth can be described by Formula 2:

[0061] (Formula 2)

[0062] Where z0 represents the water (or patient) surface, FHWM air (z0) represents the beam spot size (full width at half maximum) when entering the water surface, FWHM water (z) represents the beam spot size (full width at half maximum) at the underwater depth z.

[0063] The process of automatically constructing an absolute dose model may include: extracting lattice information and beam characteristic information from absolute dose measurement data; determining the theoretical dose at the calibration depth based on the lattice information and beam characteristic information; calibrating the theoretical dose to the absolute dose measurement data through a correction coefficient to generate an absolute dose correction curve.

[0064] Absolute dose calibration of particle therapy (including carbon ion, proton, etc.) can use a dot matrix, such as an N*N square dot matrix, with the same count for each scanning point. The ratio of the absolute dose (unit Gy) measured at the calibration depth to the total count is the absolute dose calibration curve. The automatic modeling algorithm can extract the dot matrix information from the absolute dose measurement file header, including the number of points, point count, point spacing, etc., automatically calculate the dose at the calibration depth, and calibrate it to the measured value by multiplying it by a correction factor.

[0065] Through the above process, the integrated depth dose model, beam spot model and absolute dose model can be established in turn. The present invention introduces algorithms such as Monte Carlo standard basic library data to automatically establish a pencil beam model, which can comprehensively consider the physical properties of the therapeutic particles (such as range, energy deposition distribution, etc.) and the dose distribution during the treatment process, thereby generating a more accurate model that meets the treatment needs. Compared with the existing manual modeling method, the automatic modeling algorithm of the present invention has significantly improved efficiency and accuracy.

[0066] In some embodiments, the particle therapy planning system may include a range shifter (RS). The RS can be used to adjust the range of the particle beam so that the Bragg peak position in the patient's body more accurately matches the tumor depth. The RS can usually be made of low atomic number materials and change the energy and direction of the beam through the scattering effect. In the case of using RS, the pencil beam model construction can also include the RS model construction process: according to the scattering ability of the material of the range shifter and the transport parameters upstream of the range shifter, the transport parameters downstream of the range shifter are determined, and the downstream transport parameters are used as the updated transport parameters.

[0067] The scattering power T of RS material can be calculated by Rossi formula (Formula 3):

[0068] (Formula 3)

[0069] Among them, p is the momentum of the particle, β is the relative velocity of the particle, c is the speed of light, Z is the atomic number of the particle, and X0 is the radiation length of the RS material.

[0070] Based on the calculated scattering power T and the transport parameters obtained by beam spot modeling, ray tracing is performed from the upstream of RS to the downstream, and the transport parameters of the downstream become the new transport parameters. The calculation process can be shown in Formulas 4 to 6:

[0071] (Formula 4)

[0072] (Formula 5)

[0073] (Formula 6)

[0074] Wherein, a(0), b(0), and c(0) represent the transport parameters of the RS inlet, z represents the measured depth of the downstream from the inlet, and a(z), b(z), and c(z) represent the transport parameters of the RS downstream z depth position. Therefore, this embodiment fully considers the influence of the range shifter on the beam spot, thereby establishing a model of the range shifter, which can make the obtained pencil beam model more accurate.

[0075] Please continue reading Figure 1In operation S130, the pencil beam model is simulated and verified, and corresponding parameters in the pencil beam model are adjusted according to the difference data between the simulation data and the measured data. As an example, visualization and verification of IDD, visualization and verification of beam spot transport in air, visualization and verification of beam spot transport in water, and visualization and verification of absolute dose can be performed respectively. When a range shifter is used, visualization and verification of beam spot transport in air after passing through the range shifter can also be performed.

[0076] As an example, in the visualization and verification of IDD, the IDD calculated by the model can be compared with the measured IDD, and the error between the measured and calculated IDD for the same energy can be controlled within 3%, for example. In the visualization and verification of beam spot transport in air, the beam divergence and beam spot size and energy follow a monotonically decreasing trend, and the angular divergence shows a smooth trend. The calculation error between the beam spot size in air calculated based on the transport parameters and the measured beam spot size can be controlled within 1 mm. In the visualization and verification of absolute dose, the measurement and calculation errors can be controlled within 3%. It should be noted that the error range between the model calculation results and the measurement results can be set according to demand, and the present invention is not limited to this.

[0077] For data with large errors, some warning marks can be used to mark them, or data with large errors can be highlighted to facilitate the discovery that the automatic modeling results do not conform to the measured parameters. For parameters with large errors, manual fine-tuning of model parameters can be supported to facilitate iterative optimization of automatic modeling results and improve model optimization efficiency. For example, it can support fine-tuning of single IDD fitting parameters, support IDD correction based on detector diameter, support fine-tuning of single beam spot transport parameters, and support fine-tuning of single absolute dose conversion coefficient. The fitting of IDD is based on the Monte Carlo basic database, and the diameter of the data recorded in Monte Carlo usually does not match the actual detector. In other words, there are various choices for detector diameter in actual operation. If the detector diameter is lower than that in Monte Carlo simulation, a correction less than 1 can be introduced for the calculated data, and vice versa. The modeling of absolute dose usually has an error of 2% to 3% from the measurement. The error source is the dose calculation grid. A correction factor can be introduced for each energy to correct the error of absolute dose to 0%.

[0078] In the above verification process, the dose distribution calculated by the pencil beam model is equivalent to the dose distribution in water. The smallest unit of the particle plan consists of a single beam spot, so the verification of a single beam spot in water is particularly important. The theoretical half-width data of a single beam spot in water can be determined based on the pencil beam model; the theoretical half-width data is compared with the measured half-width data, and the transport characteristics of a single beam spot are verified when the comparison error is within the preset range.

[0079] According to the verification and optimization process of the above embodiment, potential problems in the model can be discovered in time, and the model can be optimized according to the verification results. Through continuous iteration and optimization, feedback on the accuracy of the model can be provided in real time to ensure that the pencil beam model finally generated is accurate and reliable.

[0080] Please continue reading Figure 1 In operation S140, when the adjusted pencil beam model meets a preset error condition, at least one quality assurance plan of the adjusted pencil beam model is generated.

[0081] Take the formulation of the national standard plan as an example. According to the dose calculation accuracy requirements of the YY light ion beam radiotherapy planning system, the national standard plan includes three energy segments of 10*10*10 cm in the virtual water phantom, which can be called low energy (LOW), medium energy (MID) and high energy (DEEP) plans. Among them, the low energy and high energy plans need to cover the lowest energy and highest energy for carbon ion therapy respectively, and the medium energy plan needs to cover the median energy. According to the energy range, the national standard plan is automatically generated, and the dose is automatically optimized and calculated. Taking the low energy plan (LOW) as an example, the lowest energy of 120 MeV / u must be covered. This energy range is 33 mm, so the highest energy range of the low energy plan is 133 mm. Find the energy with the closest range to 133 mm from the automatic modeling model, consider appropriate expansion, and perform automatic energy selection (energy spacing is calculated according to machine properties, which can be equal spacing or automatic energy spacing calculated according to the high energy Bragg peak width) and automatic point distribution (horizontally with automatic point spacing, defined as 70% beam spot half-height width, covering a 10*10cm square area). The automatic energy selection and point placement algorithms for medium and high energy plans are similar to those for low energy plans. Based on the point placement coordinates, the algorithm can automatically optimize the national standard plan, with a dose target of usually 1 Gy, and calculate the final dose.

[0082] Take patient planning as an example. Patient plan validation covers patient geometric diversity, including multiple tumor sites. Pre-prepare patient CT images and outline databases, including head and neck, chest, abdomen and pelvis, and limbs, and unify the target area outline names, such as "PTV". Place the CT-HU conversion curves corresponding to the patient's CT images in the same folder. Store the field angle, prescription dose, and minimum count limit applicable to each patient in a pre-prepared table. The algorithm can automatically optimize and calculate the dose based on the prescription dose of "PTV".

[0083] Let's take the range shifter (RS) plan as an example. RS is used to shorten the range of the superficial target. The calculation accuracy of the RS plan depends on the modeling of RS, so the plan verification needs to include RS plan verification. According to the energy range, a shallow 10*10*10cm plan can be automatically generated, and the dose can be automatically optimized and calculated. Similar to the automatic formulation of the national standard plan, as an example, the range of the minimum treatment energy of 120 MeV / u is about 33 mm, and the range after RS ​​is about 3 mm. Then the range of the highest energy in the shallow (including RS) plan is 103 mm. Find the energy with the closest range to 103 mm (through RS) from the automatic modeling model, and then perform automatic energy and point selection. Based on the point coordinates, the algorithm automatically optimizes, the dose target can be 1Gy, and the final dose is calculated.

[0084] The developed quality assurance plan can be pushed to the Treatment Control System (TCS) for measurement, and then the measurement file can be imported for automatic partitioning comparison with the calculated structure. For patient plans, gamma analysis can be performed on the data. For national standard plans and RS plans, the algorithm can automatically partition the data according to the partitioning requirements mentioned in the YY light ion beam radiotherapy planning system dose calculation accuracy requirements, and automatically calculate the error according to the partitioning requirements. Since the partitioning requirements for the depth dose curve and the lateral dose curve are different, for example, an automatic partitioning algorithm can be developed separately for the two curves.

[0085] i. Automatic zoning algorithm for the depth dose curve: Zone 1 is the dose depth interval corresponding to 95% of the dose at the center of the Spread-Out Bragg Peak (SOBP) on both sides of the near and far ends; Zone 2 is the dose climbing and distal drop zone, which is the interval between SOBP 95% and SOBP 10%; Zone 3 is from the incident surface to Zone 2 (climbing zone); Zone 4 is the area farther than Zone 3.

[0086] ii. For the automatic partitioning algorithm of the lateral dose curve: Zone 1 is the width corresponding to 95% of SOBP; Zone 2 is the area from 10% to 95% of SOBP; Zone 3 is the area below 10% of SOBP.

[0087] iii. For all zones, the relative error between measurement and calculation is calculated, and data points exceeding 5% are considered to have failed. For zone 2, distance consistency calculation is performed additionally, and data points exceeding 2mm are considered to have failed. Within zone 2, as long as one condition is met, it is considered to have passed.

[0088] The automatic modeling method provided by the present invention is described below in conjunction with specific embodiments. Taking a certain type of carbon ion therapy equipment as an example, the automatic modeling method provided by the present invention can complete the automatic modeling of the pencil beam model within 5 minutes after data collection is completed.

[0089] In this specific embodiment, the comparison between the modeling calculation results and the measurement results can be as follows: Figures 2 to 6 As shown. Among them, Figure 2 A comparison diagram of the integrated depth dose results of measurement and automatic modeling according to an embodiment of the present invention is schematically shown, where the abscissa represents depth, the ordinate represents relative dose, the red dots represent measured values, and the blue dots represent calculated values. Figure 3 A beam spot automatic modeling parameter curve diagram according to an embodiment of the present invention is schematically shown. Figure 3 The small and medium figures (a), (b), and (c) are the angular dispersion curve, divergence curve, and beam spot size curve, respectively. Figure 3 The blue color represents the transport parameter in the X direction, and the red color represents the transport parameter in the Y direction. In the curve, since the blue part of the curve and the red part of the curve overlap, only the red part of the curve is displayed, which indicates that the transport parameters in the X and Y directions are consistent. Figure 4 A comparison diagram of the automatic modeling measurement and calculation of the beam spot in the air according to an embodiment of the present invention is schematically shown, where the horizontal axis represents the depth, the vertical axis represents the size of the beam spot in the air, the red dots represent the measured values, and the blue dots represent the calculated values. Figure 5 A comparison diagram of the beam spot sizes measured by RS and automatically modeled according to an embodiment of the present invention is schematically shown, where the horizontal axis represents depth, the vertical axis represents the beam spot size after RS, the red dots represent measured values, and the blue dots represent calculated values. Figure 6 A curve chart of the automatic modeling result of the absolute dose conversion curve according to an embodiment of the present invention is schematically shown, where the abscissa represents energy and the ordinate represents the correction factor.

[0090] In this specific embodiment, the model accuracy is verified by the national standard plan and the patient plan to meet the clinical use requirements. Figure 7~Figure 9 As shown. Among them, Figure 7 A schematic diagram showing a comparison of depth dose curves measured by a national standard plan and calculated by automatic modeling according to an embodiment of the present invention is shown. Figure 7 In the depth dose curve of Figure 7 The small and medium figures (a), (b), and (c) correspond to the comparison of the results of low-energy (LOW), medium-energy (MID), and high-energy (DEEP) planned measurements with automatic modeling calculations, respectively. Figure 8 A schematic diagram showing a comparison of the lateral dose curves measured by the national standard plan and calculated by automatic modeling according to an embodiment of the present invention is shown. Figure 8 In the horizontal dose curve of Figure 8The small and medium figures (a), (b), and (c) correspond to the comparison of the results of low-energy (LOW), medium-energy (MID), and high-energy (DEEP) planned measurements with automatic modeling calculations, respectively. Fig. 9 A schematic diagram showing a comparison of the results of patient plan measurement and dose calculation based on automatic modeling according to an embodiment of the present invention is shown. Fig. 9 In the figure, the first two rows are the plans of two patients, the measured column is the measured data, the calculated column is the calculated results, the third column is the gamma analysis results, and the last column is the linear dose comparison along the X or Y axis. The solid line is the calculation and the data points are the measured results.

[0091] According to the pencil beam model construction method in the particle therapy planning system of the above-mentioned multiple embodiments, an automatic modeling method is adopted, which significantly reduces the time and labor cost required for manual measurement and modeling, and speeds up the formulation of treatment plans. The automatic modeling method adopted can accurately and intuitively reflect the physical properties of carbon ions and the dose distribution during the treatment process, thereby improving the accuracy and safety of the treatment. The formulated QA plan can ensure that the model meets the relevant standards or industry specifications, and promote the comparison and verification of model results between different institutions. With the improvement of modeling efficiency and the guarantee of accuracy, it can be more widely used in clinical practice, providing patients with more treatment options and better treatment effects. In addition, it can be easily adapted to particle therapy equipment of different models and specifications, as well as different treatment scenarios and patient needs through modular design and parameterized configuration. This feature makes the pencil beam model construction method in the particle therapy planning system provided by the present invention have a wider application prospect and stronger market competitiveness.

[0092] Based on the above-mentioned method for constructing a pencil beam model in a particle therapy planning system, the present invention also provides a device for constructing a pencil beam model in a particle therapy planning system. Fig.10 The device is described in detail.

[0093] Fig.10 The structure block diagram of the pencil beam model building device in the particle therapy planning system according to an embodiment of the present invention is schematically shown.

[0094] like Fig.10 As shown, the pencil beam model building device 1000 in the particle therapy planning system of this embodiment includes an acquisition module 1010 , a modeling module 1020 , a verification module 1030 and a generation module 1040 .

[0095] The acquisition module 1010 is used to acquire the integrated depth dose measurement data, beam spot measurement data and absolute dose measurement data of the particle therapy device in the particle therapy planning system. In one embodiment, the acquisition module 1010 can be used to perform the operation S110 described above, which will not be described in detail here.

[0096] The modeling module 1020 is used to construct an integrated depth dose model, a beam spot model and an absolute dose model based on the integrated depth dose measurement data, the beam spot measurement data and the absolute dose measurement data, respectively, to form a pencil beam model of the particle therapy device. In one embodiment, the modeling module 1020 can be used to perform the operation S120 described above, which will not be repeated here.

[0097] The verification module 1030 is used to perform simulation verification on the pencil beam model and adjust corresponding parameters in the pencil beam model according to the difference data between the simulation data and the measured data. In one embodiment, the verification module 1030 can be used to perform the operation S130 described above, which will not be described in detail here.

[0098] The generating module 1040 is used to generate at least one quality assurance plan for the adjusted pencil beam model when the adjusted pencil beam model meets the preset error condition. In one embodiment, the generating module 1040 can be used to perform the operation S140 described above, which will not be described in detail here.

[0099] According to an embodiment of the present invention, the acquisition module 1010 is also used to clean the collected data of the particle therapy device to obtain format-standardized data; and extract the integrated depth dose measurement data, beam spot measurement data and absolute dose measurement data from the format-standardized data.

[0100] According to an embodiment of the present invention, the acquisition module 1010 is further used to identify abnormal data in the format standardized data; and extract the integrated depth dose measurement data, the beam spot measurement data and the absolute dose measurement data from the format standardized data avoiding the abnormal data.

[0101] According to an embodiment of the present invention, the modeling module 1020 may include a first modeling module. The first modeling module is used to obtain a Monte Carlo standard basic database, which contains simulation results of a monoenergetic beam spot in a therapeutic energy range in pure water; extract monoenergetic Monte Carlo integrated depth dose data close to the beam energy drawn by each accelerator from the Monte Carlo standard basic database; and perform weighted fitting on the monoenergetic Monte Carlo integrated depth dose data based on the integrated depth dose measurement data to determine a weighted energy spectrum after fitting.

[0102] According to an embodiment of the present invention, the modeling module 1020 may include a second modeling module. The second modeling module may be used to fit the beam spot measurement data, determine the transport parameters of the beam spot in the air, and establish a beam spot model in the air; fit the Gaussian distribution of the lateral scattering of particles in water, determine the lateral scattering parameters of the beam spot in the water, and establish a beam spot model in water; and determine the beam spot size at any underwater depth according to the beam spot sizes determined by the beam spot model in the air and the beam spot model in water.

[0103] According to an embodiment of the present invention, the modeling module 1020 may include a third modeling module. The third modeling module may be used to extract lattice information and beam characteristic information from absolute dose measurement data; determine the theoretical dose at the calibration depth based on the lattice information and beam characteristic information; calibrate the theoretical dose to the absolute dose measurement data through a correction coefficient, and generate an absolute dose correction curve.

[0104] According to an embodiment of the present invention, the modeling module 1020 may include a fourth modeling module for determining the transport parameters downstream of the range shifter according to the scattering power of the material of the range shifter and the transport parameters upstream of the range shifter, and the transport parameters downstream are used as updated transport parameters.

[0105] According to an embodiment of the present invention, the verification module 1030 can be used to determine the theoretical half-width data of a single beam spot in water based on a pencil beam model; compare the theoretical half-width data with the measured half-width data, and complete the verification of the transport characteristics of the single beam spot when the comparison error is within a preset range.

[0106] According to an embodiment of the present invention, any multiple modules among the acquisition module 1010, the modeling module 1020, the verification module 1030 and the generation module 1040 can be combined into one module for implementation, or any one of the modules can be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules can be combined with at least part of the functions of other modules and implemented in one module. According to an embodiment of the present invention, at least one of the acquisition module 1010, the modeling module 1020, the verification module 1030 and the generation module 1040 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application specific integrated circuit (ASIC), or can be implemented by hardware or firmware such as any other reasonable way of integrating or packaging the circuit, or implemented in any one of the three implementation methods of software, hardware and firmware or in a proper combination of any of them. Alternatively, at least one of the acquisition module 1010, the modeling module 1020, the verification module 1030, and the generation module 1040 may be at least partially implemented as a computer program module, and when the computer program module is executed, the corresponding function may be performed.

[0107] Fig.11 The block diagram of an electronic device suitable for implementing a pencil beam model building method in a particle therapy planning system according to an embodiment of the present invention is schematically shown.

[0108] like Fig.11As shown, the electronic device 1100 according to an embodiment of the present invention includes a processor 1101, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1102 or a program loaded from a storage part 1108 to a random access memory (RAM) 1103. The processor 1101 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 1101 may also include an onboard memory for caching purposes. The processor 1101 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present invention.

[0109] In RAM 1103, various programs and data required for the operation of electronic device 1100 are stored. Processor 1101, ROM 1102 and RAM 1103 are connected to each other through bus 1104. Processor 1101 performs various operations of the method flow according to the embodiment of the present invention by executing the program in ROM 1102 and / or RAM 1103. It should be noted that the program can also be stored in one or more memories other than ROM 1102 and RAM 1103. Processor 1101 can also perform various operations of the method flow according to the embodiment of the present invention by executing the program stored in one or more memories.

[0110] According to an embodiment of the present invention, the electronic device 1100 may further include an input / output (I / O) interface 1105, which is also connected to the bus 1104. The electronic device 1100 may further include one or more of the following components connected to the input / output (I / O) interface 1105: an input portion 1106 including a keyboard, a mouse, etc.; an output portion 1107 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage portion 1108 including a hard disk, etc.; and a communication portion 1109 including a network interface card such as a LAN card, a modem, etc. The communication portion 1109 performs communication processing via a network such as the Internet. A drive 1110 is also connected to the input / output (I / O) interface 1105 as needed. A removable medium 1111, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 1110 as needed, so that a computer program read therefrom is installed into the storage portion 1108 as needed.

[0111] The present invention also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiment; or may exist independently without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present invention is implemented.

[0112] According to an embodiment of the present invention, the computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, may include but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, the computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, an apparatus or a device. For example, according to an embodiment of the present invention, the computer-readable storage medium may include the ROM 1102 and / or RAM 1103 described above and / or one or more memories other than ROM 1102 and RAM 1103.

[0113] The embodiment of the present invention also includes a computer program product, which includes a computer program, and the computer program contains program code for executing the method shown in the flowchart. When the computer program product is run in a computer system, the program code is used to enable the computer system to implement the pencil beam model construction method in the particle therapy planning system provided by the embodiment of the present invention.

[0114] The computer program executes the above functions defined in the system / device of the embodiment of the present invention when it is executed by the processor 1101. According to the embodiment of the present invention, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0115] In one embodiment, the computer program may rely on tangible storage media such as optical storage devices, magnetic storage devices, etc. In another embodiment, the computer program may also be transmitted and distributed in the form of signals on a network medium, and downloaded and installed through the communication part 1109, and / or installed from a removable medium 1111. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0116] In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 1109, and / or installed from the removable medium 1111. When the computer program is executed by the processor 1101, the above functions defined in the system of the embodiment of the present invention are performed. According to the embodiment of the present invention, the system, device, means, module, unit, etc. described above can be implemented by a computer program module.

[0117] According to an embodiment of the present invention, the program code for executing the computer program provided by the embodiment of the present invention can be written in any combination of one or more programming languages. Specifically, these computing programs can be implemented using high-level process and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, Java, C++, python, "C" language or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on the remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (e.g., using an Internet service provider to connect through the Internet).

[0118] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present invention. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0119] It will be appreciated by those skilled in the art that the features described in the various embodiments of the present invention may be combined and / or combined in various ways, even if such combinations or combinations are not explicitly described in the present invention. In particular, without departing from the spirit and teachings of the present invention, the features described in the various embodiments of the present invention may be combined and / or combined in various ways. All of these combinations and / or combinations fall within the scope of the present invention.

[0120] The embodiments of the present invention are described above. However, these embodiments are only for the purpose of illustration, and are not intended to limit the scope of the present invention. Although each embodiment is described above, it does not mean that the measures in each embodiment cannot be used in combination advantageously. Without departing from the scope of the present invention, those skilled in the art may make various substitutions and modifications, which should all fall within the scope of the present invention.

Claims

1. A method for constructing a pencil beam model in a particle therapy planning system, characterized in that: include: Obtain the integrated depth dose measurement data, beam spot measurement data and absolute dose measurement data of the particle therapy equipment in the particle therapy planning system; Based on the integrated depth dose measurement data, the beam spot measurement data and the absolute dose measurement data, an integrated depth dose model, a beam spot model and an absolute dose model are constructed respectively to form a pencil beam model of the particle therapy device; Performing simulation verification on the pencil beam model, and adjusting corresponding parameters in the pencil beam model according to difference data between simulation data and measured data; In a case where the adjusted pencil beam model meets a preset error condition, at least one quality assurance plan of the adjusted pencil beam model is generated.

2. The method for constructing a pencil beam model according to claim 1, characterized in that: The step of obtaining the integrated depth dose measurement data, beam spot measurement data and absolute dose measurement data of the particle therapy device in the particle therapy planning system includes: Cleaning the collected data of the particle therapy device to obtain data in a standardized format; The integrated depth dose measurement data, beam spot measurement data and absolute dose measurement data are extracted from the format standardized data.

3. The method for constructing a pencil beam model according to claim 2, characterized in that: The step of extracting the integrated depth dose measurement data, the beam spot measurement data and the absolute dose measurement data from the format standardized data comprises: identifying abnormal data in the format-standardized data; The integrated depth dose measurement data, beam spot measurement data and absolute dose measurement data are extracted from the format standardized data avoiding the abnormal data.

4. The method for constructing a pencil beam model according to any one of claims 1 to 3, characterized in that: The method of constructing an integrated depth dose model, a beam spot model and an absolute dose model based on the integrated depth dose measurement data, the beam spot measurement data and the absolute dose measurement data respectively comprises: Acquire a Monte Carlo standard basic database, wherein the Monte Carlo standard basic database includes simulation results of a monoenergetic beam spot in a therapeutic energy range in pure water; Extracting the single-energy Monte Carlo integrated depth dose data close to the beam energy drawn from each accelerator from the Monte Carlo standard basic database; Based on the integrated depth dose measurement data, weighted fitting is performed on the monoenergetic Monte Carlo integrated depth dose data to determine a weighted energy spectrum after fitting.

5. The method for constructing a pencil beam model according to any one of claims 1 to 3, characterized in that: The method of constructing an integrated depth dose model, a beam spot model and an absolute dose model based on the integrated depth dose measurement data, the beam spot measurement data and the absolute dose measurement data respectively comprises: Fitting the beam spot measurement data, determining the transport parameters of the beam spot in the air, and establishing a beam spot model in the air; Fitting the Gaussian distribution of the lateral scattering of particles in water, determining the lateral scattering parameters of the beam spot in water, and establishing a beam spot model in water; The beam spot size at any underwater depth is determined according to the beam spot sizes determined by the beam spot model in air and the beam spot model in water.

6. The method for constructing a pencil beam model according to any one of claims 1 to 3, characterized in that: The method of constructing an integrated depth dose model, a beam spot model and an absolute dose model based on the integrated depth dose measurement data, the beam spot measurement data and the absolute dose measurement data respectively comprises: extracting dot matrix information and beam characteristic information from the absolute dose measurement data; Determining a theoretical dose at a calibration depth based on the dot matrix information and the beam characteristic information; The theoretical dose is calibrated to the absolute dose measurement data by using a correction coefficient to generate an absolute dose correction curve.

7. The method for constructing a pencil beam model according to claim 1, characterized in that: The simulating and verifying the pencil beam model, and adjusting corresponding parameters in the pencil beam model according to difference data between the simulation data and the measured data, comprises: According to the pencil beam model, determining theoretical half-width at half maximum of a single beam spot in water; The theoretical half-width data is compared with the measured half-width data, and when the comparison error is within a preset range, the transport characteristic verification of the single beam spot is completed.

8. The method for constructing a pencil beam model according to claim 1, characterized in that: The particle therapy planning system includes a range shifter; the pencil beam model forming the particle therapy device also includes: The transport parameter downstream of the range shifter is determined according to the scattering power of the material of the range shifter and the transport parameter upstream of the range shifter, and the transport parameter downstream is used as the updated transport parameter.

9. A device for constructing a pencil beam model in a particle therapy planning system, characterized in that: The device comprises: An acquisition module, used for acquiring integrated depth dose measurement data, beam spot measurement data and absolute dose measurement data of a particle therapy device in a particle therapy planning system; A modeling module, for constructing an integrated depth dose model, a beam spot model and an absolute dose model based on the integrated depth dose measurement data, the beam spot measurement data and the absolute dose measurement data, respectively, to form a pencil beam model of the particle therapy device; A verification module, used for performing simulation verification on the pencil beam model, and adjusting corresponding parameters in the pencil beam model according to difference data between simulation data and measured data; A generating module is used for generating at least one quality assurance plan of the adjusted pencil beam model when the adjusted pencil beam model meets a preset error condition.

10. An electronic device, comprising: one or more processors; a memory for storing one or more computer programs, It is characterized in that the one or more processors execute the one or more computer programs to implement the steps of the method according to any one of claims 1 to 8.

11. A computer-readable storage medium having a computer program or instruction stored thereon, characterized in that: When the computer program or instruction is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

12. A computer program product comprising a computer program or instructions, characterized in that When the computer program or instruction is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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