Integrated measurement device, beam parameter quality control method and related equipment

Abstract

The invention provides an integrated measurement device, a beam parameter quality control method and related equipment, relates to the technical field of particle radiotherapy, and is used for rapidly measuring beam parameters of pencil beam scanning points in arc proton therapy in real time. Comprising a plurality of measurement units which are arranged at intervals along a beam transmission direction, the plurality of measurement units are periodically and repeatedly arranged to form a two-dimensional orthogonal sampling grid, and time-space distribution data of a beam cross section are synchronously acquired through one-time beam output; the analysis module is used for processing the beam parameters output by the signal acquisition and processing module in real time, and the beam parameters comprise the scanning point position, the beam spot size, the charge quantity and the range; beam parameters of a pencil beam scanning point can be rapidly measured in real time, and accurate and efficient measurement is ensured; according to the matched beam parameter quality control method, the accuracy and reliability of arc proton treatment are improved through operations such as multi-angle measurement, parameter correction, quality control interval optimization and real-time dynamic adjustment.

Description

Technical Field

[0001] The present invention relates to the technical field of particle radiotherapy, and in particular to an integrated measurement device, a beam parameter quality control method and related equipment. Background Art

[0002] Arc particle beam radiotherapy, a key technological breakthrough in recent years, seamlessly integrates the unique Bragg peak physical properties of proton beams with the dynamic irradiation advantages of arc-type intensity-modulated radiotherapy. In traditional proton therapy, precise control of the proton beam's energy and position allows for efficient concentration of the radiation dose at the tumor target, significantly reducing the radiation dose to surrounding normal tissue. Arc-type irradiation technology, by leveraging multi-angle rotational irradiation and precise adjustment of a dynamic multileaf grating, significantly improves the conformality and uniformity of the target dose.

[0003] With the continued advancement of proton accelerator miniaturization, intelligent rotating gantries, and pencil-beam scanning technology, arc proton therapy has successfully achieved synchronized dynamic modulation of energy and angle in three-dimensional space. This achievement enables submillimeter dose sculpting in the treatment of complex anatomical sites, such as skull base, head and neck, and pelvic tumors. Clinical studies have clearly demonstrated that compared to traditional photon radiotherapy and static proton therapy, arc proton therapy exhibits superior advantages in protecting adjacent organs at risk, reducing radiation complications, and minimizing the risk of secondary cancers, effectively advancing the development of precision tumor radiotherapy to a higher level.

[0004] However, arc particle therapy requires numerous beam field angles, as well as precise and synchronized control of particle energy, intensity, scanning speed, and gantry rotation angle. Any slight timing error is likely to cause severe distortion of the dose distribution. Therefore, throughout the treatment process, extremely stringent requirements are placed on the positional accuracy and charge accuracy of the pencil beam scanning point. Currently, existing measurement methods struggle to meet the demands for real-time and rapid measurement of the beam parameters at pencil beam scanning points when faced with such complex and demanding measurement tasks. For example, conventional measurement devices are unable to synchronously acquire the spatiotemporal distribution data of the beam cross section upon beam emission, making it difficult to meet the requirements for comprehensive and rapid measurement of beam parameters. Effective measurement methods are lacking when dealing with high instantaneous saturation current intensities, leading to inaccurate measurement results. Furthermore, the measurement, correction, and quality control methods for beam parameters at different gantry rotation angles are inadequate, making it impossible to ensure the accuracy and stability of dose distribution under complex treatment conditions. Summary of the Invention

[0005] Based on the above problems, the present invention proposes an integrated measurement device, a beam parameter quality control method and related equipment, aiming to effectively solve the above problems and improve the safety and effectiveness of arc proton therapy.

[0006] In a first aspect, the present invention provides an integrated measurement device for real-time and rapid measurement of beam parameters at a pencil beam scanning point in arc proton therapy, the device comprising:

[0007] Signal acquisition and processing module; including multiple measurement units spaced apart along the beam propagation direction. The multiple measurement units are periodically and repeatedly arranged to form a two-dimensional orthogonal sampling grid, and the spatiotemporal distribution data of the beam cross section is synchronously acquired through a single beam output;

[0008] The analysis module is used to process the beam parameters output by the signal acquisition and processing module in real time, wherein the beam parameters include scanning point position, beam spot size, charge amount and range.

[0009] Preferably, the device further comprises:

[0010] a hanging adapter for mounting the device in a fixed position on the treatment machine, ensuring that the beam axis passes orthogonally through the detector array;

[0011] The high-voltage power supply module adopts a distributed topology to provide a gradient bias voltage for each measurement unit.

[0012] Preferably, the measuring unit includes, in sequence along the beam transmission direction:

[0013] The first high-voltage electrode is arranged at the starting end of the measurement unit, with its bias plane being orthogonal to the beam axis, generating a transverse confinement electric field;

[0014] A strip-type position sensor, comprising an X-direction position sensor and a Y-direction position sensor; the position measurement plane formed by the strip electrodes of the strip-type position sensor is parallel to the beam cross section, and is used to synchronously obtain the beam transverse position distribution;

[0015] a charge measurement sensor having a charge measurement plane coplanar with a position measurement plane;

[0016] The second high-voltage electrode is arranged at the end of the measuring unit, with its bias plane being orthogonal to the beam axis and symmetrically distributed with the first high-voltage electrode along the Z axis to form a closed electric field confinement structure.

[0017] Preferably, the electrode parameters of the strip type position sensor are determined by the resolution and charge collection efficiency required for position measurement, and the electrode parameters include the strip electrode width and the spacing between strips;

[0018] The distance between two adjacent planes is determined by the electric field strength required for the drift of positive and negative ion pairs, the composite effect of positive and negative ion pairs, the high voltage tolerance of the high voltage electrode, and the collection efficiency of positive and negative ion pairs; the planes include a bias plane, a position measurement plane, and a charge measurement plane.

[0019] Preferably, the signal acquisition and processing module adopts a dual-mode switching measurement method to cope with high instantaneous saturation current intensity; wherein the dual mode includes a current mode and an integration mode;

[0020] If the beam intensity is greater than the intensity threshold and the rate of change is greater than the change threshold, the current mode is selected;

[0021] When the beam intensity is less than or equal to the intensity threshold, or the rate of change thereof is less than or equal to the change threshold, the integration mode is selected.

[0022] Preferably, the dual-mode switching implementation method includes:

[0023] By connecting optocoupler solid-state relays and ultra-low capacitance MOSFET arrays in parallel, a lossless switching channel with on-before-off switching is constructed.

[0024] Based on the real-time rate of change of beam intensity, the mode switching threshold is adjusted by a dynamic hysteresis algorithm, and the threshold is dynamically scaled with the beam parameters;

[0025] Use the time series prediction model to analyze historical beam current data and predict the beam current trend within the first time range in the future. When the predicted value exceeds the threshold, trigger the mode switch in advance.

[0026] In the switching time window, the output signals of the two modes are dynamically weighted and fused, and the weight function changes continuously with the switching time;

[0027] Compensation charges matching the parasitic capacitance characteristics are injected at the switching instant to eliminate baseline offset errors.

[0028] Preferably, the signal acquisition and processing module uses a high-speed operational amplifier and a high-speed analog-to-digital converter to quickly convert the weak electrical signal generated by the detector into a digital signal and process it; and by connecting a charge-sensitive preamplifier to the signal output end of the detector, accurate measurement of the charge amount is achieved.

[0029] In a second aspect, the present invention provides a beam parameter quality control method for controlling the quality of the beam parameters of the device of the present invention, the method comprising:

[0030] Measure the beam parameters at the scanning point at different gantry rotation angles to obtain the beam parameters at each angle;

[0031] The beam parameters at different angles are corrected using the gantry deformation and beam parameter correction model.

[0032] Collecting multimodal operating data from the equipment and constructing an adaptive feature set, inputting the feature set into a multi-objective dynamic optimization model to solve for the optimal quality control trigger interval and perform feedback adjustment based on real-time parameter deviations and cumulative dose thresholds;

[0033] When the cumulative dose deviation is greater than the deviation threshold, online recalibration is triggered to update the correction model weight coefficient.

[0034] Preferably, a gantry deformation and beam parameter correction model is established using a machine learning algorithm based on the collected gantry bending moment distribution, temperature deformation tensor, and corresponding beam parameters.

[0035] Preferably, the method includes collecting multimodal operation data of the equipment and constructing an adaptive feature set, inputting the feature set into a multi-objective dynamic optimization model, solving the optimal quality control trigger interval, and performing feedback adjustment based on real-time parameter deviation and cumulative dose threshold; comprising:

[0036] Collect multimodal operating data of devices in real time and build a dynamic optimization feature set through time series alignment and statistical modeling;

[0037] Inputting the feature set into a pre-trained LSTM network to predict the probability value of the beam parameter deviation exceeding a preset threshold in a future time window;

[0038] Using the constructed features as input, a multi-objective dynamic optimization model is used to construct an objective function integrating risk, cost, and equipment loss, and a genetic algorithm is used to solve the optimal quality control interval.

[0039] Dynamically adjust quality control intervals based on real-time deviations and dose accumulation levels.

[0040] In a third aspect, the present invention provides a particle radiotherapy system comprising:

[0041] The treatment head has a built-in deflection magnet to control the beam direction and realize pencil beam scanning along a preset path;

[0042] The integrated measurement device described in the embodiment of the present invention is used for real-time measurement of beam parameters emitted from a treatment head and applied to a pencil beam scanning point in arc proton therapy.

[0043] In a fourth aspect, the present invention provides an electronic device comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the functions of any device described in the present invention or performs the steps of any method described in the present invention when executing the computer program.

[0044] In a fifth aspect, the present invention provides a computer-readable storage medium, which stores computer instructions. When a computer reads the computer instructions, the computer implements the functions of any device described in the present invention or executes the steps of any method described in the present invention.

[0045] Compared with the prior art, the beneficial effects of the present invention include at least the following: the integrated measurement device of the present application, through the multiple measurement units arranged at periodic intervals along the beam transmission direction to form a two-dimensional orthogonal sampling grid in the signal acquisition and processing module, can synchronously obtain the spatiotemporal distribution data of the beam cross section during a beam emission; compared with traditional measurement methods, it greatly improves the efficiency and comprehensiveness of data acquisition, provides a rich and timely data foundation for subsequent precise analysis of beam characteristics, and helps radiotherapy physicians more accurately understand the real-time status of the proton beam in the patient's body, thereby optimizing treatment plans. The analysis module can process a variety of beam parameters including scanning point position, beam spot size, charge, and range in real time; making the dose calculation and control during radiotherapy more accurate, effectively reducing the dose deviation caused by beam parameter measurement errors, improving the accuracy of the tumor target dose, and better protecting surrounding normal tissues. The suspension adapter ensures that the device and the treatment machine are precisely fixed and installed, so that the beam axis passes orthogonally through the detector array, ensuring the accuracy and consistency of the measurement; the high-voltage power supply module with a distributed topology provides a gradient bias voltage for each measurement unit, improving the stability and reliability of the power supply, ensuring that the measurement unit can operate stably under different working conditions, and thus improving the stability and measurement accuracy of the entire measurement device. The unique structural design inside the measurement unit, such as the closed electric field confinement structure formed by the first high-voltage electrode and the second high-voltage electrode, combined with the strip position sensor and charge measurement sensor, can not only effectively confine the beam, but also accurately measure the lateral position distribution and charge amount of the beam; at the same time, by reasonably determining the electrode parameters and the spacing between each plane, the position measurement resolution and charge collection efficiency are further improved, enhancing the accuracy and reliability of the device's beam parameter measurement. The signal acquisition and processing module utilizes a dual-mode switching measurement method that intelligently selects between current mode and integration mode based on beam intensity and rate of change. Under conditions of high instantaneous saturation current, it rapidly switches to the appropriate mode, avoiding data distortion and ensuring accurate beam parameter measurement under a variety of complex beam conditions. This significantly improves the adaptability of the measurement device and the accuracy of the results. The beam parameter quality control method measures beam parameters at scan points at different gantry rotation angles and corrects them using a gantry deformation and beam parameter correction model. This method fully accounts for the impact of gantry deformation on beam parameters at different angles, effectively improving beam parameter accuracy at all angles and ensuring uniformity and accuracy of dose distribution throughout the entire arc proton therapy process. A measurement interval optimization function is constructed to determine an appropriate quality control interval based on the actual operation of the radiotherapy equipment, improving both measurement and system efficiency. When the cumulative dose deviation exceeds a threshold, an online recalibration mechanism is triggered to promptly update the correction model weight coefficients, further ensuring the real-time and effectiveness of beam parameter quality control and enhancing the safety and stability of arc proton therapy. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 1 is a schematic structural diagram of an integrated measurement device according to an embodiment of the present invention;

[0047] Figure 2 Schematic diagram of a beam parameter quality control method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0048] In view of the deficiencies in the prior art, the applicant of this case has proposed the technical solution of this application after long-term research and extensive practice. The following will further explain the technical solution, its implementation process and principles, etc. in conjunction with the drawings in the embodiments of this application and specific implementation cases.

[0049] It should be noted that the embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain this application, and should not be understood as limiting this application. The embodiments described are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, this application covers any replacement, modification, equivalent method and scheme made within the spirit, principle and scope of this application defined by the claims. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0050] In the description of this application, "first", "second", "third" and similar words do not indicate any order, quantity or importance, but are only used to distinguish different components. Similarly, "a" or "an" and other similar words do not indicate a quantity limitation, but rather indicate the existence of at least one. "Include" or "comprising" and other similar words mean that the elements or objects appearing before "include" or "comprising" include the elements or objects listed after "include" or "comprising" and their equivalents, and do not exclude other elements or objects. "Connected" or "connected" and other similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect.

[0051] In the description of this application, the terms "center," "up," "down," "front," "back," "left," "right," "vertical," "horizontal," "top," "bottom," "inside," "outside," and the like, indicating directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings and are intended only to facilitate the description of this application and simplify the description. They are not intended to indicate or imply that the devices or components referred to must have a specific direction, be constructed, or operate in a specific direction. Therefore, they should not be construed as limitations on this application. Furthermore, when positional terms such as "both sides," "outside," "upper," and "lower" are used, they should be understood to be used solely to facilitate understanding and description, taking into account that the structure may be oriented in other directions.

[0052] In the description of this application, unless otherwise clearly specified and limited, the technical or scientific terms used should have the usual meanings understood by persons with ordinary skills in the field to which this application belongs. Terms such as "install", "connect", and "connect" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, a conflicting connection, or an integrated connection. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0053] Furthermore, in order to provide the public with a better understanding of the present application, some specific details are described in detail in the detailed description of the present application below. A person skilled in the art can fully understand the present application without the description of these details.

[0054] Example 1: See attached Figure 1 This embodiment provides an integrated measurement device for real-time and rapid measurement of beam parameters at a pencil beam scanning point in arc proton therapy, the device comprising:

[0055] Signal acquisition and processing module; including multiple measurement units spaced apart along the beam propagation direction. The multiple measurement units are periodically and repeatedly arranged to form a two-dimensional orthogonal sampling grid, and the spatiotemporal distribution data of the beam cross section is synchronously acquired through a single beam output;

[0056] The analysis module is used to process the beam parameters output by the signal acquisition and processing module in real time, wherein the beam parameters include scanning point position, beam spot size, charge amount and range.

[0057] The working principle of this technical solution is as follows: During arc proton therapy, a pencil beam travels along the beam propagation direction. Multiple measurement units, spaced and periodically arranged along this direction, form a two-dimensional orthogonal sampling grid within the signal acquisition and processing module. As the proton beam passes through, various sensors within the measurement units (such as position sensors and charge sensors) synchronously sample the beam, acquiring data related to the beam's cross-section at a specific moment, such as its position and charge, thereby generating data on the spatiotemporal distribution of the beam's cross-section.

[0058] The collected data on the spatiotemporal distribution of the beam cross section is transmitted to the signal acquisition and processing module for preliminary processing before being passed to the analysis module. Based on the received data, the analysis module applies a specific algorithm to perform real-time calculations and analysis of beam parameters such as scanning point position, beam spot size, charge, and range, yielding the final result.

[0059] The effects of the above technical solution are: through the two-dimensional orthogonal sampling grid structure, the spatiotemporal distribution data of the beam cross section can be synchronously obtained in one beam emission. Compared with traditional measurement methods, it greatly shortens the measurement time, improves the measurement efficiency, meets the needs of real-time and rapid measurement, and can provide timely feedback on beam parameters during arc proton therapy; it can measure multiple key beam parameters such as scanning point position, beam spot size, charge and range, providing more comprehensive and rich data support for proton therapy, making it easier for doctors and technicians to understand the beam status more accurately and optimize treatment plans; the integrated integrated design integrates signal acquisition, processing and analysis functions, reduces the connection and complexity between devices, reduces system errors, improves the stability and reliability of the equipment, and also facilitates installation, debugging and maintenance.

[0060] In a possible implementation, the apparatus further includes:

[0061] a hanging adapter for mounting the device in a fixed position on the treatment machine, ensuring that the beam axis passes orthogonally through the detector array;

[0062] The high-voltage power supply module adopts a distributed topology to provide a gradient bias voltage for each measurement unit.

[0063] The working principle of the above technical solution is:

[0064] The suspension adapter serves as a connection and positioning mechanism; during installation, it securely connects the integrated measurement device to the treatment machine. Through precise mechanical design and installation positioning, the detector array of the measurement device establishes an accurate spatial relationship with the beam axis of the treatment machine, ensuring that the beam axis passes perpendicularly (orthogonally) through the detector array. During proton beam emission, the beam enters the measurement unit of the measurement device along the correct path, ensuring the accuracy and validity of the measurement data.

[0065] The high-voltage power supply module adopts a distributed topology and is connected to each measurement unit in the entire measurement device. This topology enables independent and precise voltage distribution based on the needs of different measurement units. A gradient bias voltage is provided to each measurement unit, that is, different levels of interrelated bias voltage are provided based on factors such as the function and location of the measurement unit. For example, different sensors (such as high-voltage electrodes) in a measurement unit require different voltage conditions to generate the appropriate electric field to achieve functions such as confinement and detection of the proton beam. The high-voltage power supply module can provide power on demand.

[0066] The effects of the above technical solution are: the hanging adapter ensures the accurate installation and positioning of the measuring device and the treatment machine, so that the beam can enter the measuring device according to the expected path, avoiding measurement data errors due to installation deviations, and improving the reliability of the measurement results; it can be adapted to different types of treatment machines, enhance the versatility of the measuring device, and facilitate use on different proton therapy equipment.

[0067] The high-voltage power supply module provides a suitable gradient bias voltage for the measurement unit, helping to optimize the electric field distribution within the measurement unit, enabling the position sensor and charge measurement sensor to function better and improving the accuracy of beam parameter measurements. The distributed topology reduces the risk of a single power supply failure impacting the entire device, improving the reliability and stability of the high-voltage power supply system and ensuring the overall stable operation of the measurement device.

[0068] In a possible implementation, the measuring unit includes, in sequence along the beam transmission direction:

[0069] The first high-voltage electrode is arranged at the starting end of the measurement unit, with its bias plane being orthogonal to the beam axis, generating a transverse confinement electric field;

[0070] A strip-type position sensor, comprising an X-direction position sensor (position sensor 1) and a Y-direction position sensor (position sensor 2); the position measurement plane formed by the strip electrodes of the strip-type position sensor is parallel to the beam cross section, and is used to synchronously obtain the beam transverse position distribution; wherein the X-direction position sensor and the Y-direction position sensor are respectively located on two sides of a thin plate, and the two sides are strip collection electrodes in two directions, wherein the thickness of the thin plate is less than, for example, 2 mm;

[0071] a charge measurement sensor having a charge measurement plane coplanar with a position measurement plane;

[0072] The second high-voltage electrode is arranged at the end of the measuring unit, with its bias plane being orthogonal to the beam axis and symmetrically distributed with the first high-voltage electrode along the Z axis to form a closed electric field confinement structure.

[0073] The working principle of the above technical solution is as follows: the first high-voltage electrode is set at the starting end of the measurement unit, and the bias plane is orthogonal to the beam axis. After power is turned on, a transverse confinement electric field is generated to preliminarily constrain the proton beam entering the measurement unit, so that the beam maintains a relatively concentrated path in the transverse direction (X and Y directions); the proton beam continues to move forward, and the second high-voltage electrode is set at the end of the measurement unit. Its bias plane is orthogonal to the beam axis and is symmetrically distributed with the first high-voltage electrode along the Z axis. It works together with the first high-voltage electrode to form a closed electric field confinement structure, further constraining the proton beam, preventing the beam from diverging, and ensuring that the beam can pass through the measurement unit in a relatively stable state.

[0074] The strip position sensor includes position sensors for the X direction (position sensor 1) and the Y direction (position sensor 2), located on both sides of the thin plate. The position measurement plane formed by its strip electrodes is parallel to the beam cross section. When the proton beam passes through, it interacts with the strip electrodes to generate electrical signals. By analyzing these electrical signals, the lateral position distribution information of the beam in the X and Y directions can be synchronously obtained, thereby determining the specific position of the beam on the cross section.

[0075] The charge measurement plane of the charge measurement sensor is coplanar with the position measurement plane. When the proton beam passes through, the charge measurement sensor senses the charge carried by the beam and converts it into an electrical signal. By processing and analyzing the electrical signal, the charge quantity information of the beam is obtained.

[0076] The effects of the above technical solution are:

[0077] Through high-voltage electrodes and the closed electric field collected and formed, the positive and negative particle pairs generated by the proton beam ionization are effectively detected; the strip position sensor and charge measurement sensor can more accurately obtain the position and charge information of the beam, improving the measurement accuracy of the beam parameters; the X and Y direction sensors of the strip position sensor are integrated on both sides of the thin plate, and the charge measurement plane is coplanar with the position measurement plane. This compact structural design integrates multiple measurement functions in a limited space, reducing the volume of the measurement unit while ensuring the integrity and synchronization of the measurement functions and improving measurement efficiency; within a single measurement unit, both the beam lateral position distribution measurement and charge measurement can be realized, and a variety of key beam parameters can be obtained, providing strong support for the comprehensive evaluation of the beam status in proton therapy.

[0078] In one possible implementation, the strip position sensor electrode parameters are determined by the resolution required for position measurement and the charge collection efficiency. The electrode parameters include the width of the strip electrodes and the spacing between the strips; for example, the electrode width is 2 mm and the electrode spacing is 0.5 mm.

[0079] The distance between two adjacent planes is determined by the electric field strength required for the drift of positive and negative ion pairs, the composite effect of positive and negative ion pairs, the high voltage tolerance of the high voltage electrode, and the collection efficiency of positive and negative ion pairs; the planes include a bias plane, a position measurement plane, and a charge measurement plane. For example, the distance between two adjacent planes is about 5 mm.

[0080] The working principle of the above technical solution is:

[0081] The width and spacing of the strip electrodes determine the distribution of the electric field; the electric field strength between the electrodes is inversely proportional to the electrode spacing and is related to the electrode width; the smaller the electrode spacing, the higher the electric field strength, which helps to improve the charge collection efficiency; when charged particles or radiation pass through the sensor, they will induce charges between the electrode strips. By analyzing the signal strength on different electrodes, the position of the particle on the sensor can be calculated; usually involves weighted averaging of the signal or other algorithms to improve the resolution of position measurement.

[0082] The parameters of the strip electrodes also affect the charge collection efficiency. The strip electrode width and spacing must ensure that the charges generated by the proton beam can be effectively collected and converted into detectable electrical signals when it passes through. If the electrode width is too narrow or the spacing is too large, some charges may not be collected in time, reducing the charge collection efficiency and affecting the accurate measurement of the beam charge. If the electrodes are too wide or the spacing is too small, although the charge collection efficiency may be improved, the resolution of the position measurement will be reduced. Therefore, the appropriate strip electrode width and spacing are determined by comprehensively balancing the resolution required for position measurement and the charge collection efficiency. For example, when the electrode width is 2mm and the electrode spacing is 0.5mm, a measurement range larger than 20cm*20cm can be achieved.

[0083] Within the measurement cell, the interaction between the proton beam and the surrounding medium generates positive and negative ion pairs. To effectively collect these pairs and use them to measure relevant parameters (such as inferring beam characteristics by measuring ion current), a suitable electric field is required to induce the drift of the pairs. The spacing between two adjacent planes (the bias plane, the position measurement plane, and the charge measurement plane) affects the distribution of the electric field strength. If the spacing is too large, the electric field strength may be insufficient, causing the positive and negative ion pairs to drift too slowly or even be unable to be effectively collected. If the spacing is too small, the electric field strength may be too strong, causing other adverse effects (such as electrical breakdown). Therefore, it is necessary to determine the appropriate plane spacing based on the electric field strength required for the drift of the positive and negative ion pairs, for example, about 5mm, to ensure that the electric field strength meets the requirements for effective drift of the positive and negative ion pairs.

[0084] During drift, positive and negative ion pairs may recombine—that is, recombine and disappear—which can affect the accurate measurement of beam-related parameters. An appropriate interplanar spacing can reduce the probability of recombination. A larger spacing may increase the chances of recombination during drift, while a smaller spacing allows the pairs to be captured by the collector electrode more quickly, reducing the time window for recombination. By studying the relationship between the recombination effect of positive and negative ion pairs and the interplanar spacing, we can select a spacing value that effectively reduces the recombination probability and improves measurement accuracy.

[0085] High-voltage electrodes are used to generate a confining electric field and operate at a high voltage. A too small spacing between adjacent planes can lead to excessive electric field concentration between the electrodes, exceeding their tolerances and causing electrical breakdown and other faults, impacting the normal operation of the measurement device. Therefore, when determining the spacing between adjacent planes, it is necessary to fully consider the high-voltage electrodes' high-voltage tolerance to ensure that the spacing setting does not subject them to excessive electric field stress, thus ensuring the long-term stable operation of the device.

[0086] The interplanar spacing directly impacts the collection efficiency of positive and negative ion pairs. A suitable spacing enables the generated positive and negative ion pairs to drift efficiently to their corresponding collection electrodes under the influence of the electric field. An inappropriate spacing may prevent some positive and negative ion pairs from reaching the collection electrodes, reducing collection efficiency and, in turn, affecting the accuracy of beam parameter measurements. Through research and optimization of the collection efficiency of positive and negative ion pairs, a spacing of 5 mm between adjacent planes has been determined to achieve high collection efficiency.

[0087] The effects of the above technical solution are:

[0088] The electrode parameters are determined by comprehensively considering the position measurement resolution and charge collection efficiency, achieving a balance between the two key measurement performances. This avoids sacrificing charge collection efficiency for the sole pursuit of high resolution, or reducing position measurement accuracy due to excessive focus on charge collection. This allows the strip position sensor to perform well in both position and charge measurement.

[0089] The approximately 5mm spacing between adjacent planes is determined based on the electric field strength required for the drift of positive and negative ion pairs, ensuring an appropriate electric field strength. This allows positive and negative ion pairs to drift at an appropriate speed under the action of the electric field and efficiently reach the collector electrode, providing a stable and effective ion flow for ion-pair-based beam parameter measurement and improving the reliability of measurement results. A reasonable plane spacing effectively reduces the recombination of positive and negative ion pairs during drift, shortening the time and space for ion pair recombination. This allows more ion pairs to be successfully collected for measurement, improving the accuracy of measurement data and facilitating more precise analysis of beam characteristics. The plane spacing is determined based on the high-voltage electrode's high-voltage tolerance to prevent breakdown of the high-voltage electrode due to excessive electric field concentration caused by too small a spacing. This extends the life of the measurement device, improves its operational stability and reliability, and reduces the risk of treatment interruption caused by equipment failure. The plane spacing is optimized based on the collection efficiency of positive and negative ion pairs to maximize ion pair collection efficiency. More ion pairs can be captured by the collector electrode, providing more sufficient data for beam parameter measurement, facilitating more comprehensive and accurate assessment of beam status, and providing strong support for the precise implementation of proton therapy.

[0090] In a possible implementation, the electrode parameters of the strip-type position sensor are determined by the following steps:

[0091] Establishing constraints, the constraints including target spatial resolution, charge collection efficiency, and high voltage electrode withstand voltage;

[0092] Establish a finite element model that includes electric field distribution, ion migration and composite effects to simulate the kinetic process of ion transport;

[0093]

[0094] in, is the change in ion concentration, n ± is the positive / negative ion concentration, D is the diffusion coefficient, μ is the mobility; k rec is the recombination coefficient, which is used to measure the rate at which positive and negative ions recombine with each other; is the gradient operator; E is the electric field intensity;

[0095] The strip width and spacing are iteratively adjusted by genetic algorithm to minimize the first objective function F:

[0096]

[0097] Among them, F is the first objective function, δ actual is the actual spatial resolution; η actual is the actual charge collection efficiency; V applied is the actual applied voltage; V max is the high voltage electrode withstand voltage; δ target is the target spatial resolution; η req is the target charge collection efficiency, and α, β, and γ are weights.

[0098] As can be understood, in the finite element model, the ion concentration distribution is closely related to the beam's position. Strip position sensors determine beam position by detecting changes in ion concentration. As the beam passes through the sensor, ion concentrations at different locations vary due to the effects of the beam current. The strip width and spacing affect the electric field's ion confinement and detection. By analyzing the ion concentration distribution across the sensor strips, the minimum discernible position difference, or spatial resolution, can be calculated. For example, if the ion concentration changes too gradually between adjacent strips, it becomes difficult to distinguish finer differences in the beam's position, resulting in low spatial resolution. Conversely, if the concentration changes significantly and can be accurately measured, high spatial resolution can be achieved. Based on the ion concentration distribution data obtained from the finite element model, specific algorithms (such as those based on concentration gradients or signal intensity differences) are used to calculate the actual spatial resolution. The calculated result is compared with the target spatial resolution and used as part of the objective function F.

[0099] Charge collection efficiency is determined by the ratio of the amount of ion charge that the sensor can effectively collect to the theoretically collected charge. In the finite element model, changes in ion concentration reflect the processes of ion generation, migration, and recombination. If the recombination effect is strong, a large number of ions recombine and disappear before reaching the sensor electrodes, resulting in less collected charge and lower charge collection efficiency. Conversely, if the electric field is properly designed, ion migration is smooth and recombination is minimized, improving charge collection efficiency. Strip width and spacing influence the electric field distribution, which in turn affects ion migration paths and recombination probability. Based on the temporal and spatial variations in ion concentration in the finite element model, combined with information such as the ion generation rate, the actual collected ion charge is calculated and compared with the theoretical charge to obtain the actual charge collection efficiency. This is then compared with the target charge collection efficiency and used to calculate the objective function F.

[0100] The finite element model simulates the electric field conditions in the entire measuring device, including the electric field generated by the high-voltage electrode. The strip width and spacing will change the electric field distribution in the sensor area, thereby affecting the actual applied voltage required to achieve the desired electric field effect (such as meeting ion migration requirements, avoiding breakdown, etc.). For example, if the strip spacing is too small, the electric field may be too concentrated, and the applied voltage needs to be reduced to prevent breakdown; if the spacing is too large, the voltage may need to be increased to ensure effective ion migration. By solving the electric field-related equations and combining parameters such as the dielectric properties of the material, the actual applied voltage that meets the measurement requirements (such as appropriate ion migration speed, electric field strength range, etc.) at the current strip width and spacing is obtained. Compare it with the high-voltage electrode withstand voltage and participate in the calculation of the objective function F. Relationship with parameter iteration

[0101] During the iterative parameter optimization process, the stripe width and spacing are continuously modified using a genetic algorithm. After each modification, the finite element model is rerun to obtain new results, such as the change in ion concentration. Parameters such as spatial resolution, charge collection efficiency, and actual applied voltage are then recalculated. These new parameters are then substituted into the objective function F to determine whether F is moving toward a smaller value. If so, the parameters are further adjusted in that direction; if not, other parameter combinations are tried. Through continuous iteration, the optimal electrode parameters that satisfy the objective function F are gradually found.

[0102] By establishing constraints including the target spatial resolution, charge collection efficiency, and high-voltage electrode withstand voltage, the key performance factors of the strip position sensor were comprehensively considered. Based on these constraints, a finite element model was used to simulate the dynamics of ion transport, accurately analyzing the movement, diffusion, and recombination of ions in the electric field, providing a scientific basis for the determination of electrode parameters. This ensures that the final electrode parameters can achieve high accuracy in terms of spatial resolution and charge collection efficiency, meeting the demand for precise measurement of beam parameters in arc proton therapy.

[0103] The stripe width and spacing are iteratively adjusted using a genetic algorithm, guided by minimizing the objective function F. This objective function comprehensively considers the differences between actual and target spatial resolution, charge collection efficiency, and the relationship between the actual applied voltage and the withstand voltage of the high-voltage electrode. It is able to find an optimal balance between multiple key performance indicators, avoiding excessive emphasis on one indicator at the expense of others. This significantly optimizes the overall performance of the stripe position sensor and improves the comprehensive effectiveness of proton beam position and charge measurement.

[0104] This method takes the withstand voltage of the high-voltage electrode into account. It can rationally adjust electrode parameters based on the actual withstand voltage of the high-voltage electrode in different measurement devices, ensuring that the entire measurement system operates within a safe voltage range and enhancing the sensor's adaptability to diverse hardware conditions. Furthermore, by optimizing metrics such as charge collection efficiency, it can better adapt to measurement requirements in diverse beam current environments, improving the reliability and stability of the measurement device in complex proton therapy scenarios.

[0105] In one possible implementation, the distance between adjacent measurement planes is determined by the following method:

[0106] The initial spacing range d is set by the manufacturing process limit and the electric field uniformity threshold constraint. min ≤d≤d max ; where d min Determined by manufacturing process limits, d min Constrained by the electric field uniformity threshold;

[0107] Electric field distribution and ion transport obtained through multi-physics coupling modeling;

[0108] Limit the recombination rate; determine the minimum allowable spacing by adjusting the electric field strength;

[0109] Design the second objective function to comprehensively evaluate the electric field strength, collection efficiency and voltage resistance;

[0110]

[0111] Where F(d) is the second objective function; d is the distance between adjacent planes; E max is the maximum electric field intensity calculated by the electric field distribution model; E safe is the safety electric field strength; η is the ion collection efficiency, that is, the ratio of the number of ions actually collected to the total number of ions; V applied is the actual applied voltage; V max is the high voltage electrode withstand voltage; w1, w2, w3 are weights;

[0112] The spacing is iteratively adjusted using a genetic algorithm.

[0113] Among them, the electric field distribution and ion transport conditions obtained through multi-physics field coupling modeling include:

[0114] Establish an electric field distribution model and solve the Poisson equation; calculate the electric field intensity at each point in the calculation area:

[0115]

[0116] Where V is the electric potential, ρ is the space charge density, ε is the dielectric constant, and ε0 is the vacuum dielectric constant.

[0117] Construct an ion transport model that combines continuity and drift-diffusion equations;

[0118]

[0119] The minimum spacing is determined based on manufacturing process limits, taking into account the minimum distance achievable during actual manufacturing. The maximum spacing is determined based on the electric field uniformity threshold constraint, ensuring that the electric field uniformity meets the requirements within this spacing range, thereby setting the initial spacing range. Through multi-physics coupled modeling, an electric field distribution model is established, solving the Poisson equation to calculate the electric field intensity at each point within the region and clarify the electric field distribution. Furthermore, an ion transport model is constructed, combining the continuity and drift-diffusion equations to analyze the transport processes of ions in the electric field, including diffusion, migration, and recombination. The minimum allowable spacing is determined by adjusting the electric field intensity to ensure that ion recombination is within an acceptable range and the electric field intensity is appropriate. An objective function is designed, comprehensively considering factors such as electric field intensity and safety field intensity, ion collection efficiency, and voltage resistance. A genetic algorithm is used to iteratively adjust the spacing d between adjacent planes within the initially set spacing range, using the objective function as the optimization target, to continuously find the spacing value that optimizes the objective function.

[0120] Setting the initial spacing range based on manufacturing process limits and electric field uniformity thresholds ensures that the spacing between adjacent measurement planes is achievable in actual manufacturing and that the electric field uniformity meets measurement requirements. This fundamentally avoids manufacturing difficulties and poor electric field performance caused by unreasonable spacing, laying the foundation for reliable manufacturing and stable operation of the measurement device. Through multi-physics field coupling modeling, in-depth analysis of the electric field distribution and ion transport allows for precise understanding of the motion patterns of ions between measurement planes. On this basis, key parameters are determined and an objective function is constructed, effectively optimizing key factors affecting measurement accuracy, such as electric field strength and ion collection efficiency. This reduces interference such as ion recombination, improves the accuracy of beam parameter measurements, and provides more reliable data support for proton therapy. By incorporating voltage withstand capability into the objective function and iteratively adjusting the spacing using a genetic algorithm, the spacing between adjacent measurement planes is aligned with the withstand voltage of the high-voltage electrode. This avoids safety issues such as breakdown caused by excessive electric field strength or actual applied voltage exceeding the withstand value, enhancing the safety and stability of the measurement device and extending its service life.

[0121] In one possible implementation, the signal acquisition and processing module adopts a dual-mode switching measurement method to cope with high instantaneous saturation current intensity; wherein the dual mode includes a current mode and an integration mode;

[0122] If the beam intensity is greater than the intensity threshold and the rate of change is greater than the change threshold, the current mode is selected;

[0123] When the beam intensity is less than or equal to the intensity threshold, or the rate of change thereof is less than or equal to the change threshold, the integration mode is selected.

[0124] In one possible implementation, the dual-mode switching method includes:

[0125] By connecting optocoupler solid-state relays and ultra-low capacitance MOSFET arrays in parallel, a lossless switching channel with on-before-off switching is constructed.

[0126] Based on the real-time rate of change of beam intensity, the mode switching threshold is adjusted by a dynamic hysteresis algorithm, and the threshold is dynamically scaled with the beam parameters;

[0127] Use the time series prediction model to analyze historical beam current data and predict the beam current trend within the first time range in the future. When the predicted value exceeds the threshold, trigger the mode switch in advance.

[0128] In the switching time window, the output signals of the two modes are dynamically weighted and fused, and the weight function changes continuously with the switching time;

[0129] Compensation charges matching the parasitic capacitance characteristics are injected at the switching instant to eliminate baseline offset errors.

[0130] The working principle and effects of the above technical solution are as follows:

[0131] When the monitored beam intensity exceeds the preset intensity threshold and its rate of change exceeds the variation threshold, it indicates that the beam is at a high instantaneous saturation intensity and is volatile. In this case, the current mode is selected because it can quickly respond to such high-intensity, high-rate-of-change beam conditions, promptly acquiring and processing beam signals to avoid signal loss or distortion. If the beam intensity is less than or equal to the intensity threshold, or its rate of change is less than or equal to the variation threshold, the beam is relatively stable, with low intensity and low variability. In this case, the integral mode is more suitable, as it can accumulate and process weaker beam signals, improving signal detection accuracy.

[0132] The switching channel is constructed by connecting an optocoupler solid-state relay and an ultra-low capacitance MOSFET array in parallel. During the switching process, the optocoupler solid-state relay is turned on first, allowing current to flow smoothly. Then the ultra-low capacitance MOSFET array is turned on again, and the optocoupler solid-state relay is gradually turned off. This achieves lossless switching with a first-on, then-off behavior, avoiding interference with signal acquisition caused by current interruption or surge at the moment of mode switching.

[0133] A dynamic hysteresis algorithm adjusts the mode switching threshold based on the real-time rate of change of the beam intensity. As beam parameters (such as intensity and rate of change) change dynamically, the threshold scales accordingly. For example, when beam intensity fluctuates frequently, the threshold adaptively adjusts, making mode switching more efficient and avoiding frequent, unnecessary, or untimely switching caused by a fixed threshold.

[0134] By collecting and analyzing historical beam current data, a time series prediction model is used to predict the beam current trend within the first timeframe. When the predicted value exceeds a set threshold, a mode switch is triggered in advance. This allows for early preparation before a significant change in beam current conditions is imminent, necessitating a mode switch, ensuring the continuity and accuracy of signal acquisition and processing.

[0135] Within the switching time window, the output signals of the current mode and the integration mode are dynamically weighted and combined. The weighting function changes continuously with the switching time. In the initial switching phase, the signal weight of the current mode is given greater weight. As the switching time progresses, the signal weight of the upcoming mode is gradually increased. This method ensures a smooth transition between the signal outputs of the two modes, avoiding sudden changes or discontinuities in the signal caused by mode switching.

[0136] At the moment of mode switching, baseline offset errors may occur due to factors such as parasitic capacitance. To eliminate this error, compensation charges that match the characteristics of the parasitic capacitance are injected. The interaction between the compensation charges and the parasitic capacitance offsets the baseline offset caused by the parasitic capacitance, ensuring accurate signal acquisition.

[0137] In one possible implementation, the signal acquisition and processing module uses a high-speed operational amplifier and a high-speed analog-to-digital converter to quickly convert the weak electrical signal generated by the detector into a digital signal and process it; by connecting a charge-sensitive preamplifier to the detector signal output end, accurate measurement of the charge amount can be achieved.

[0138] After detecting the proton beam-related signal, the detector generates a weak electrical signal. A high-speed operational amplifier first amplifies this weak signal, increasing its amplitude for more accurate processing and identification. Next, a high-speed analog-to-digital converter rapidly converts the amplified analog signal into a digital signal. During this process, the high-speed analog-to-digital converter samples, quantizes, and encodes the analog signal, converting the continuous analog quantity into a discrete digital quantity, enabling the signal to be received and processed by the digital processing system.

[0139] The high-speed operational amplifier and analog-to-digital converter work together to significantly increase signal processing speed. They rapidly convert the weak electrical signals generated by the detector into digital signals, enabling timely capture of changes in the proton beam signal and meeting the stringent real-time measurement requirements of arc proton therapy. Furthermore, the rapid signal processing reduces delays in signal transmission and processing, improving the overall measurement system's responsiveness and providing more accurate, real-time data support for physicians to promptly adjust treatment plans.

[0140] A charge-sensitive preamplifier is connected to the detector signal output. When the detector detects the charge signal generated by the proton beam, the charge-sensitive preamplifier can detect and amplify the charge quantity. By converting the input charge signal into a voltage signal and amplifying the voltage signal, accurate measurement of the charge quantity can be achieved. The characteristics of the charge-sensitive preamplifier make it very sensitive to changes in the input charge and can accurately convert changes in the charge quantity into measurable voltage changes. Through the charge-sensitive preamplifier, accurate measurement of the charge quantity is achieved. In proton therapy, charge quantity is an important beam parameter. Accurate measurement of charge quantity helps doctors more accurately understand the energy distribution and treatment effect of the proton beam. Accurate charge quantity measurement data can provide a key basis for optimizing treatment plans and improve the accuracy and effectiveness of treatment.

[0141] In a possible implementation, backup is designed for important electrical components in the circuit.

[0142] The measurement device's circuitry incorporates backup components for critical electrical components. While the primary component is functioning normally, the backup component remains on standby. Should the primary component fail due to aging, overload, or other factors, the system automatically detects the fault and quickly switches to the backup component, which then takes over and continues operation, ensuring the entire measurement device's signal acquisition and processing capabilities remain unaffected, thus enhancing the device's reliability.

[0143] In a possible implementation, the electronic components of the apparatus have radiation resistance.

[0144] Proton therapy environments are subject to significant amounts of radiation. Radiation-resistant electronic devices, through specialized material selection and structural design, are able to withstand the effects of radiation on their internal circuits and functions. In a radiation environment, the atomic structure and electronic properties of these electronic devices remain resistant to the impact of radiation particles, ensuring the normal operation of the devices and continued execution of functions such as signal acquisition and processing. The radiation resistance of these electronic devices ensures the stable operation of the measurement device in the radiation environment of proton therapy, extending the device's service life and ensuring accurate measurement of beam parameters throughout the treatment process, safeguarding the safety and effectiveness of proton therapy.

[0145] Example 2: See attached Figure 2 A beam parameter quality control method is used to control the quality of the beam parameters in Example 1, the method comprising:

[0146] Measure the beam parameters at the scanning point at different gantry rotation angles to obtain the beam parameters at each angle;

[0147] The beam parameters at different angles are corrected using the gantry deformation and beam parameter correction model.

[0148] Collecting multimodal operating data from the equipment and constructing an adaptive feature set, inputting the feature set into a multi-objective dynamic optimization model to solve for the optimal quality control trigger interval and perform feedback adjustment based on real-time parameter deviations and cumulative dose thresholds;

[0149] When the cumulative dose deviation is greater than the deviation threshold, online recalibration is triggered; and the correction model weight coefficient is updated; wherein the correction model weight coefficient can be updated by a particle swarm optimization algorithm.

[0150] The working principle of the above technical solution is:

[0151] In arc proton therapy, the gantry operates at different rotation angles. By measuring beam parameters (such as scanning point position, beam spot size, charge, and range) at various angles, comprehensive information on the actual state of the beam under different treatment conditions can be obtained, providing a data basis for subsequent parameter correction and quality control.

[0152] Since the gantry may deform at different angles, this deformation will affect the beam parameters, resulting in deviations in the measured beam parameters. A gantry deformation and beam parameter correction model is used, which pre-establishes the relationship between gantry deformation and beam parameter deviation. By inputting the beam parameters measured at different angles into the model, the parameters are corrected according to the existing relationship in the model to compensate for deviations caused by factors such as gantry deformation, bringing the beam parameters closer to the actual values ​​and improving the accuracy of the beam parameters.

[0153] Multimodal data is collected in real time during radiotherapy equipment operation, including gantry angle, beam parameter set, cumulative equipment operation time, effective absorbed dose, and patient target characteristics. Feature extraction is performed on this data to construct features such as the mean and standard deviation of historical gantry angle quality control deviations, adjacent angle gradients, key component aging coefficients, normalized effective absorbed doses, logarithmically transformed target volume values, and the interaction term between target shape complexity and the shortest distance to sensitive organs. These features are then input into a multi-objective dynamic optimization model, which constructs an objective function that integrates risk, cost, and equipment wear. The risk term reflects the probability of beam parameter deviations from reference values, the cost term encompasses the time and downtime costs associated with quality control operations, and the wear term reflects the aging and wear of key equipment components. A genetic algorithm is used to solve the objective function and search for the optimal quality control interval. Furthermore, this method dynamically adjusts the quality control interval based on real-time monitored beam parameter deviations and dose accumulation levels. If the deviation or dose accumulation reaches a certain level, it indicates that the equipment operating status or beam parameter stability has changed. At this time, the quality control interval should be shortened; otherwise, it can be appropriately extended to achieve a dynamic balance between risk, cost and equipment stability.

[0154] Cumulative dose deviation is an important indicator for measuring the impact of beam parameter accuracy on treatment efficacy. When the cumulative dose deviation exceeds a pre-set deviation threshold, it indicates that the beam parameters may have significantly changed, affecting the accuracy of the treatment dose. This triggers online recalibration. Online recalibration restores the beam parameters to their correct state by re-measuring and adjusting them. Simultaneously, the particle swarm optimization algorithm is used to update the correction model weight coefficients. The particle swarm optimization algorithm simulates the foraging behavior of bird flocks, searching for the optimal solution in the solution space and continuously adjusting the weights of various factors in the correction model. This allows the correction model to better adapt to the current state of the device and changes in beam parameters, further improving the accuracy of beam parameter correction and the effectiveness of quality control.

[0155] In one possible implementation, a gantry deformation and beam parameter correction model is established using a machine learning algorithm based on the collected gantry bending moment distribution, temperature deformation tensor, and corresponding beam parameters.

[0156] The working principle of the above technical solution is:

[0157] First, the gantry bending moment distribution data is collected. This distribution reflects the torque applied to different parts of the gantry, which is closely related to the gantry's stress state. Simultaneously, the temperature deformation tensor data is collected. Temperature changes cause the gantry material to expand and contract, resulting in deformation. The temperature deformation tensor accurately describes the extent and direction of this deformation. Furthermore, corresponding beam parameters, such as scanning point position, beam spot size, charge, and range, must be collected. These parameters are critical physical quantities during treatment and are affected by gantry deformation.

[0158] Feature extraction is performed on the collected rack bending moment distribution, temperature deformation tensor and beam parameter data; key force characteristics, such as the maximum bending moment position and bending moment change trend, are extracted from the bending moment distribution data; main deformation characteristics, such as deformation direction and quantitative indicators of deformation degree, are extracted from the temperature deformation tensor data; beam parameter data are standardized to facilitate analysis at the same scale; and these features are then integrated to form a data set that can be processed by machine learning algorithms.

[0159] Machine learning algorithms (such as neural networks and decision trees) are used as input for the integrated dataset. The algorithm continuously adjusts the model's internal parameters (such as the neural network's weights and biases) to identify the intrinsic mapping relationship between the gantry bending moment distribution, the temperature deformation tensor, and the beam parameters. During training, the model predicts the beam parameters based on the input data, then compares them with the actual acquired beam parameters to calculate the prediction error. Through optimization algorithms such as backpropagation, the error is continuously reduced, enabling the model to accurately establish a corrective relationship between the gantry deformation (represented by the bending moment distribution and temperature deformation tensor) and the beam parameters, ultimately resulting in a gantry deformation and beam parameter correction model.

[0160] By establishing this model, it is possible to quantitatively analyze the impact of gantry deformation on beam parameters, and to correct the beam parameters according to the actual gantry deformation, compensating for parameter deviations caused by gantry deformation, making the beam parameters more consistent with actual treatment needs and improving the accuracy, safety, and effectiveness of treatment. Various factors affecting gantry deformation, such as gantry bending moment distribution and temperature deformation tensor, are taken into account, enabling the model to adapt to different working conditions. Regardless of whether the gantry is subjected to uneven force or has large temperature variations, the model can accurately correct the beam parameters based on the corresponding deformation data, enhancing the model's generalization and robustness and improving the reliability of the measurement device in complex environments.

[0161] In one possible implementation, the method includes collecting multimodal operating data of the device and constructing an adaptive feature set, inputting the feature set into a multi-objective dynamic optimization model, solving for the optimal quality control trigger interval, and performing feedback adjustment based on real-time parameter deviation and cumulative dose threshold; including:

[0162] Real-time acquisition of multimodal data during device operation, including gantry angle, beam parameter set, cumulative device operation time, effective absorbed dose, and patient target characteristics. For example, the beam parameter set includes beam position, spot size, charge, and range parameters; patient target characteristics include target volume, three-dimensional coordinates, and shape complexity indicators; environmental data can include treatment room temperature, humidity, and vibration level;

[0163] The minimum angular difference between adjacent gantry positions can be determined by the rotation interval supported by the accelerator hardware, for example, 3°-5°. The angular difference between adjacent gantry positions during treatment is determined by optimizing clinical needs.

[0164] Clean the collected data, remove obvious outliers, and fill in missing values;

[0165] Based on the acquired data, multiple features are constructed, including historical gantry angle quality control values ​​(including the mean and standard deviation of the historical gantry angle deviation and the gradient of adjacent angles), key component aging coefficients, normalized effective absorbed dose values, logarithmic transformation values ​​of the target volume, and the interaction term between the target shape complexity and the shortest distance to sensitive organs.

[0166] Inputting the feature set into a pre-trained LSTM network to predict the probability of beam parameter deviation exceeding a preset threshold within a future time window; wherein the input features of the LSTM network include the mean and standard deviation of historical quality control deviations of gantry angles, adjacent angle gradients, key component aging coefficients, logarithmic transformation values ​​of target volume, and the interaction term between target shape complexity and the shortest distance to sensitive organs;

[0167] The constructed features are used as input to a multi-objective dynamic optimization model. An objective function integrating risk, cost, and equipment loss is constructed. A genetic algorithm is used to solve the optimal quality control interval through the multi-objective dynamic optimization model.

[0168] The objective function includes the weighted sum of risk, cost, and loss terms. The risk term is the probability that the deviation between the predicted beam parameters and the reference value is greater than the maximum allowable deviation. The cost term includes the quality control time cost and downtime loss cost, which are related to the quality control interval. The loss term is the time integral of the aging coefficient of the key components.

[0169] Dynamically adjust quality control intervals based on real-time deviations and dose accumulation levels.

[0170] Among them, the quality control interval is dynamically adjusted according to the real-time deviation and dose accumulation level, including:

[0171] When the deviation between the actual value of the beam parameter monitored in real time and the predicted value reaches a first threshold (e.g., 0.5 times the maximum allowable deviation), or the accumulated effective absorbed dose reaches a second threshold (e.g., 0.7 times the dose upper limit), immediate quality control is triggered. Once triggered, the current treatment beam is immediately paused, and quality control measurements are completed within a preset time. If the measured correction exceeds a third threshold (e.g., 0.1 times the reference beam parameter value), the magnet recalibration process is automatically initiated.

[0172] The working principle of this technical solution is to obtain real-time data on the operating radiotherapy equipment, including gantry angle, beam parameters (position, spot size, etc.), cumulative equipment operation time, effective absorbed dose, patient target characteristics (volume, shape complexity, etc.), and environmental data (temperature, humidity, etc.). This data is then cleaned to remove outliers and fill in missing values, providing a reliable data foundation for subsequent analysis.

[0173] Based on the preprocessed data, various features are constructed, such as gantry angle-related statistics and component aging coefficients. These features are then fed into the LSTM network, which leverages its ability to process time series data to predict the probability of parameter deviations exceeding preset deviations within future time windows and assess the risk of beam parameter deviation.

[0174] The construction features are used as inputs to a multi-objective dynamic optimization model, constructing an objective function that includes a weighted sum of risk (parameter deviation probability), cost (quality control time and downtime losses), and loss (component aging integral). A genetic algorithm is used to search for the optimal solution under these multiple objectives, determining the optimal quality control interval and balancing risk, cost, and loss.

[0175] Real-time monitoring of the deviation between actual and predicted beam parameters and the accumulated effective absorbed dose. When the deviation reaches the first threshold or the accumulated dose reaches the second threshold, immediate quality control is triggered, pausing beam measurement. If the correction exceeds the third threshold, magnet recalibration is initiated, and the quality control interval is dynamically adjusted based on the results.

[0176] The above technical solution achieves the following: Long quality control cycles can reduce device measurement accuracy, impacting treatment outcomes; while short quality control cycles require frequent quality control, reducing equipment operating efficiency. By integrating multimodal data and multiple model algorithms, factors influencing beam parameters are comprehensively considered to accurately determine quality control intervals, promptly detect and correct parameter deviations, ensure radiotherapy dose accuracy, and improve treatment efficacy and safety. A multi-objective optimization model balances risk, cost, and equipment wear and tear to avoid over- or under-quality control, thereby reducing equipment wear and downtime while managing risk and achieving a cost-benefit balance. Quality control intervals are dynamically adjusted based on real-time deviations and dose accumulation levels. This allows the quality control strategy to adapt to changes in equipment operating status and beam parameters, enhancing the flexibility and robustness of radiotherapy equipment quality control. Real-time quality control is triggered when beam parameter deviations or dose accumulation reach certain thresholds. This dynamic adjustment allows the quality control interval to be flexibly adjusted based on the actual equipment operating status, avoiding the problems associated with fixed, excessively long or short quality control cycles. For example, when the parameter deviation of the equipment increases significantly after running for a period of time, the quality control cycle is shortened to ensure measurement accuracy and treatment effect; if the equipment runs stably, the quality control cycle can be appropriately extended to improve operating efficiency.

[0177] Embodiment 3: A particle radiotherapy system, comprising:

[0178] The treatment head has a built-in deflection magnet to control the beam direction and realize pencil beam scanning along a preset path;

[0179] The aforementioned integrated measurement device is used to measure in real time the beam parameters of the pencil beam scanning point emitted from the treatment head and used in arc proton therapy.

[0180] An embodiment of the present invention also provides an electronic device, which includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, it implements the functions of the device described in any one of the embodiments of the present application or the steps of the method described in the embodiments of the application.

[0181] The present application also provides a computer-readable storage medium for storing a computer program that, when executed, implements the functions of any of the apparatuses described in the present application or the steps of any of the methods described in the present application. The specific implementation methods and technical effects achieved are consistent with those described in the above-mentioned method embodiments, and some details are not further described.

[0182] In the present application, a readable storage medium can be any tangible medium that contains or stores a program that can be used by or in combination with an instruction execution system, device or device. A program product can use any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared or semiconductor system, device or device, or any combination of the above. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0183] A computer-readable storage medium may include a data signal propagated in baseband or as part of a carrier wave, carrying readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The readable storage medium may also be any readable medium that can transmit, propagate, or transfer a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the readable storage medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical cable, RF, or any suitable combination thereof. The program code for performing the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar programming languages. The program code may be executed entirely on the user computing device, partially on an associated device, as a standalone software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. Where a remote computing device is involved, the remote computing device may 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 may be connected to an external computing device (e.g., through the Internet using an Internet service provider).

[0184] Although the embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are illustrative and are not to be construed as limiting the present invention. A person skilled in the art may change, modify, replace and modify the above embodiments within the scope of the invention without departing from the principles and purpose of the present invention. All such changes shall fall within the scope of protection of the claims of the present invention.

Claims

1. An integrated measurement device for real-time and rapid measurement of beam parameters at pencil beam scanning points in arc proton therapy, characterized in that: The device comprises: Signal acquisition and processing module; including multiple measurement units spaced apart along the beam propagation direction. The multiple measurement units are periodically and repeatedly arranged to form a two-dimensional orthogonal sampling grid, and the spatiotemporal distribution data of the beam cross section is synchronously acquired through a single beam output; The analysis module is used to process the beam parameters output by the signal acquisition and processing module in real time, wherein the beam parameters include scanning point position, beam spot size, charge amount and range.

2. The integrated measuring device according to claim 1, characterized in that: The device further comprises: a hanging adapter for mounting the device in a fixed position on the treatment machine, ensuring that the beam axis passes orthogonally through the detector array; The high-voltage power supply module adopts a distributed topology to provide a gradient bias voltage for each measurement unit.

3. The integrated measuring device according to claim 1, characterized in that: The measuring unit includes, in sequence along the beam transmission direction: The first high-voltage electrode is arranged at the starting end of the measurement unit, with its bias plane being orthogonal to the beam axis, generating a transverse confinement electric field; A strip-type position sensor, comprising an X-direction position sensor and a Y-direction position sensor; the position measurement plane formed by the strip electrodes of the strip-type position sensor is parallel to the beam cross section, and is used to synchronously obtain the beam transverse position distribution; a charge measurement sensor having a charge measurement plane coplanar with a position measurement plane; The second high-voltage electrode is arranged at the end of the measuring unit, with its bias plane being orthogonal to the beam axis and symmetrically distributed with the first high-voltage electrode along the Z axis to form a closed electric field confinement structure.

4. The integrated measuring device according to claim 3, characterized in that: Determining electrode parameters of the strip type position sensor by the resolution and charge collection efficiency required for position measurement, wherein the electrode parameters include strip electrode width and spacing between strips; The distance between two adjacent planes is determined by the electric field strength required for the drift of positive and negative ion pairs, the composite effect of positive and negative ion pairs, the high voltage tolerance of the high voltage electrode, and the collection efficiency of positive and negative ion pairs; the planes include a bias plane, a position measurement plane, and a charge measurement plane.

5. The integrated measuring device according to claim 1, characterized in that: The signal acquisition and processing module adopts a dual-mode switching measurement method to cope with high instantaneous saturation current intensity; wherein the dual mode includes current mode and integration mode; If the beam intensity is greater than the intensity threshold and the rate of change is greater than the change threshold, the current mode is selected; When the beam intensity is less than or equal to the intensity threshold, or the rate of change thereof is less than or equal to the change threshold, the integration mode is selected.

6. The integrated measuring device according to claim 5, characterized in that: The dual-mode switching implementation method includes: By connecting optocoupler solid-state relays and ultra-low capacitance MOSFET arrays in parallel, a lossless switching channel with on-before-off switching is constructed. Based on the real-time rate of change of beam intensity, the mode switching threshold is adjusted by a dynamic hysteresis algorithm, and the threshold is dynamically scaled with the beam parameters; Use the time series prediction model to analyze historical beam current data and predict the beam current trend within the first time range in the future. When the predicted value exceeds the threshold, trigger the mode switch in advance. In the switching time window, the output signals of the two modes are dynamically weighted and fused, and the weight function changes continuously with the switching time; Compensation charges matching the parasitic capacitance characteristics are injected at the switching instant to eliminate baseline offset errors.

7. The integrated measuring device according to claim 1, characterized in that: The signal acquisition and processing module uses a high-speed operational amplifier and a high-speed analog-to-digital converter to quickly convert the weak electrical signals generated by the detector into digital signals and process them; by connecting a charge-sensitive preamplifier to the detector signal output end, accurate measurement of the charge amount is achieved.

8. A beam parameter quality control method for controlling the quality of the beam parameters in claim 1, characterized in that: The method comprises: Measure the beam parameters at the scanning point at different gantry rotation angles to obtain the beam parameters at each angle; The beam parameters at different angles are corrected using the gantry deformation and beam parameter correction model. Collecting multimodal operating data from the equipment and constructing an adaptive feature set, inputting the feature set into a multi-objective dynamic optimization model to solve for the optimal quality control trigger interval and perform feedback adjustment based on real-time parameter deviations and cumulative dose thresholds; When the cumulative dose deviation is greater than the deviation threshold, online recalibration is triggered to update the correction model weight coefficient.

9. The beam parameter quality control method according to claim 8, characterized in that: Based on the collected gantry bending moment distribution, temperature deformation tensor and corresponding beam parameters, a gantry deformation and beam parameter correction model is established using a machine learning algorithm.

10. The beam parameter quality control method according to claim 8, characterized in that: Collect multimodal operating data of the equipment and construct an adaptive feature set, input the feature set into a multi-objective dynamic optimization model, solve the optimal quality control trigger interval, and perform feedback adjustment based on real-time parameter deviation and cumulative dose threshold; including: Collect multimodal operating data of devices in real time and build a dynamic optimization feature set through time series alignment and statistical modeling; Inputting the feature set into a pre-trained LSTM network to predict the probability value of the beam parameter deviation exceeding a preset threshold in a future time window; Using the constructed features as input, a multi-objective dynamic optimization model is used to construct an objective function integrating risk, cost, and equipment loss, and a genetic algorithm is used to solve the optimal quality control interval. Dynamically adjust quality control intervals based on real-time deviations and dose accumulation levels.

11. A particle radiotherapy system, characterized in that: include: The treatment head has a built-in deflection magnet to control the beam direction and realize pencil beam scanning along a preset path; The integrated measurement device described in claim 1 is used for real-time measurement of beam parameters emitted from a treatment head and applied to a pencil beam scanning point in arc proton therapy.

12. An electronic device, characterized in that: The electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the functions of the device according to any one of claims 1 to 7 or performs the steps of the method according to claim 8 when executing the computer program.

13. A computer-readable storage medium, characterized in that The storage medium stores computer instructions. When a computer reads the computer instructions, the computer implements the functions of the device according to any one of claims 1 to 7 or executes the steps of the method according to claim 8.

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