Ion beam irradiation configuration optimization method, system, and computer storage medium

Abstract

Provided in the present invention is a computer storage medium-based ion beam irradiation configuration optimization method, aiming at improving the precision and effectiveness of treatment. According to the method, image data of a target area is acquired by means of three-dimensional scanning, and three-dimensional discretization processing is performed to construct a voxel angle range matrix. A preference value function is employed to quantify the preference of each voxel for different ion beam energies, and the energy layer at each angle is dynamically calculated and allocated in combination with the optimization of the irradiation angle. The system can automatically adjust the energy configuration and the irradiation angle by means of monitoring feedback data in real time, thereby ensuring optimal energy coverage of the target area. The method not only improves the therapeutic effect, but also reduces damage to normal tissues by means of precisely controlling the transfer of energy, thereby improving the safety and efficiency of treatment. By means of such optimization and dynamic adjustment mechanism, the present invention can provide a personalized treatment plan for each patient, thereby achieving efficient and precise treatment of complex target areas.

Description

Ion beam irradiation configuration optimization method, system and computer storage medium TECHNICAL FIELD

[0001] The present application relates to an irradiation configuration optimization method for ion beam therapy, in particular to a technical method for obtaining target region data by three-dimensional scanning, setting multiple irradiation angles and optimizing energy parameters, applying a preference value function for optimization and selecting the optimal ion beam energy configuration. BACKGROUND

[0002] With the continuous progress of radiotherapy technology, ion beam therapy as a high-precision and high-efficiency cancer treatment method has been widely used in clinical practice. Ion beam therapy uses proton beams and heavy ion beams (such as carbon ions, etc.), which have precise dose distribution and high biological effect, and shows significant advantages in tumor treatment. However, the complexity and high requirements of ion beam therapy make how to optimize the ion beam irradiation configuration an important research topic.

[0003] Ion beam therapy system is an advanced radiotherapy device, mainly including the following core components. First, the ion source is used to generate high-energy ion beams, such as proton sources and heavy ion sources (such as carbon ion sources), which are accelerated by accelerators to form high-energy charged particles. The accelerator is a key device that accelerates the ion beam generated by the ion source to the required high energy level by electromagnetic field. Next, the beam transport system transmits the high-energy ion beam from the accelerator to the treatment room, using a series of magnets and optical devices to accurately control the direction and intensity of the ion beam. Then, the treatment head guides the ion beam to a specific location in the patient's body, and can also be equipped with a collimator and a scatterer to adjust the shape and dose distribution of the ion beam, achieving precise irradiation.

[0004] During treatment, the image-guided system monitors the patient's position and tumor position changes in real time to ensure that the ion beam accurately irradiates the tumor target area. Common image-guided techniques include X-ray, CT and MRI. These techniques improve the accuracy of treatment by precisely positioning the tumor location. Finally, the treatment planning system develops a personalized treatment plan based on patient image data and tumor conditions. The system calculates the optimal ion beam irradiation angle, energy and dose distribution, simulates the treatment process, predicts the treatment effect, and makes real-time adjustments to ensure maximum treatment effect.

[0005] Each component of the ion beam therapy system works together to achieve efficient treatment of tumors through precise control and optimization, but the complexity of this process also brings high requirements for the optimization of ion beam irradiation configuration.

[0006] In the prior art, the dose control and energy optimization of ion beam therapy mainly rely on several methods, but these methods still have some technical problems and challenges in practical application.

[0007] In the patent document CN105609397A, an ion beam irradiation device and an ion beam current uniformization method are disclosed. The device extracts an ion beam with a rectangular cross-sectional surface from an ion source and moves the substrate back and forth in the short direction to process within the ion beam irradiation area. However, this method has a significant problem that the substrate needs to be moved outside the ion beam irradiation area each time it moves back and forth, which results in low processing efficiency and long processing time. In addition, since the substrate needs to be moved frequently outside the ion beam irradiation area, each rotation must also be performed outside the irradiation area, which further increases the time and complexity of substrate processing.

[0008] In the patent document CN115845279A, an ion beam rapid scanning irradiation system is disclosed. The system performs ion beam irradiation through rapid scanning to improve processing speed and efficiency. However, when processing complex target area morphology and multi-angle irradiation, the system still has problems of low calculation efficiency and insufficient accuracy. This is mainly because it is quite difficult to achieve uniform distribution of target area dose and optimal irradiation effect under multi-angle and multi-energy configuration. In addition, the system lacks dynamic adjustment of ion beam energy and angle during irradiation, resulting in unsatisfactory irradiation effect and possible uneven dose, which affects the treatment effect.

[0009] In the patent document CN110412639A, a method for obtaining an ion beam irradiation scheme based on nanodosimetry is disclosed. The method obtains calibrated nanodosimetry quantities under calibration conditions and quantifies radiation effects to determine radiation effect parameters, calculates corresponding nanodosimetry quantities, and applies radiation effect parameters to optimize the irradiation scheme. Although this method improves the accuracy of the irradiation scheme to some extent, it still faces problems of complex calculation and time-consuming under multi-angle and multi-energy configuration. In addition, this method has certain limitations when dealing with different radiation qualities and complex target area morphology.

[0010] In the patent document US10553395B2, an ion beam irradiation device and an ion beam irradiation method are disclosed. The device controls the rotation mechanism and reciprocating motion mechanism to make the substrate move back and forth within the ion beam irradiation range and continuously rotate. Although this device improves the uniformity of ion beam irradiation to some extent by combining rotation and reciprocating motion, it still has some problems in practical application. For example, in the edge part of the ion beam irradiation area, the current density of the ion beam is not uniform, making it difficult to achieve uniform irradiation. In addition, the device has a complex structure and requires the cooperation of multiple precision components, resulting in high production cost and difficult maintenance. These problems limit the widespread use of the device in practical application.

[0011] The applicant proposes an ion beam energy optimization method based on a preference value function after in-depth research. This method can dynamically adjust the energy and angle of the ion beam by setting and optimizing the preference value function to maximize the increase in the preference value of all voxels in the target area. A voxel is a basic unit in three-dimensional space used to represent and process three-dimensional image data. Similar to a pixel in a two-dimensional image, a voxel represents a specific volume in a three-dimensional image and is commonly used in medical imaging and computer graphics. In ion beam therapy, voxels are used to represent the three-dimensional structure of tumor regions and surrounding tissues and are the basis for developing and optimizing treatment plans. Specific applications include three-dimensional reconstruction, dose distribution calculation, and image analysis. The preference value is a quantitative indicator that measures the sensitivity of each voxel in the tumor tissue to the selection of ion beam energy. In other words, the preference value represents the energy requirement of a voxel to achieve the best treatment effect. The higher the preference value, the more "preferred" the selected ion energy is for the voxel, i.e., the selected energy can better cover the voxel and achieve the desired treatment effect.

[0012] The application proposes setting and optimizing the preference value function to ensure that each voxel can receive the most suitable energy, thereby improving the uniformity of the dose distribution, reducing the unevenness of high and low dose regions, and avoiding excessive damage to surrounding normal tissues.

[0013] SUMMARY

[0014] The purpose of the invention is to provide an ion beam energy optimization method based on a preference value function to overcome the problems of uneven dose distribution, low calculation efficiency, and insufficient dynamic adjustment in the prior art, achieve efficient and precise irradiation of tumor regions, and enhance the effectiveness of ion beam therapy.

[0015] To achieve one of the above-mentioned purposes, the application adopts the following technical solutions:

[0016] An ion beam irradiation configuration optimization method,

[0017] By performing three-dimensional scanning on the target area, three-dimensional image data of the target area is obtained;

[0018] According to the three-dimensional image data, a target area is defined for the area that needs to be irradiated by the ion beam;

[0019] Set multiple irradiation angles for the target area;

[0020] For each set of irradiation angles, the energy parameters are evaluated and selected to maximize the increase in the preference value of all voxels within the target volume, wherein the preference value is derived based on a function between the ion beam energy required for each voxel and its water equivalent range, to determine the energy of the ion beam required to be emitted at each irradiation angle.

[0021] This step utilizes imaging techniques such as CT (Computed Tomography) or MRI (Magnetic Resonance Imaging) to obtain detailed three-dimensional structural information of the target region, providing basic data for subsequent target definition and irradiation optimization. By analyzing the three-dimensional image data, the treatment target region, i.e., the target volume, is determined. This step can use image processing software combined with the professional knowledge of doctors to accurately mark the lesion area that needs to be irradiated.

[0022] A plurality of irradiation angles for the target volume are set. In order to ensure that the ion beam energy can fully cover the target volume, the target volume is irradiated from different angles. Setting multiple irradiation angles helps to evenly distribute the energy and reduce the side effects that may be caused by single direction irradiation.

[0023] Further, the function between the ion beam energy required for each voxel and its water equivalent range is:

[0024] Obtain the water equivalent range of the target volume voxels: Perform three-dimensional discretization processing on the target region to be processed, divide the target region to be processed into a plurality of cubic voxels; for each predetermined irradiation angle, the rays from the ion beam emission source to the center of each voxel are calculated to obtain the path from the ray source to the center of each voxel;

[0025] Calculate the relative stopping power: for each point on the ray path, calculate the relative stopping power of the ion rays at the point according to the material composition and density at the point compared with water;

[0026] Construct the voxel angle range matrix: calculate the sum of the relative stopping power on each ray path by line integral method to determine the water equivalent range of each voxel, and collect the water equivalent ranges of each voxel under different irradiation angles to form a voxel angle range matrix.

[0027] The three-dimensional discretization process refers to dividing a continuous three-dimensional space into a series of finite and discrete units or voxels, each of which represents a specific volume unit. Although a cube is the most common voxel shape, other shapes such as hexahedron and tetrahedron can also be used according to actual needs. For example, when dealing with objects with complex geometric shapes, irregularly shaped voxels can better adapt to the contours of the object. The size of the voxel is usually reasonably set according to the needs, considering factors such as spatial resolution and computing resources. This process is widely used in scientific computing, computer graphics, and medical imaging, especially in applications involving spatial analysis and simulation.

[0028] In the ion beam irradiation configuration optimization process, when calculating the required ion beam energy for each voxel, first, the ray path from the ion beam emission source to the center of each voxel is calculated, and the material composition and density of each point on the path are determined, usually through CT scan data acquisition. The relative stopping power refers to the relative value of the material's attenuation ability to the ion beam compared to water, which depends on the material's electron density and atomic number. The relative stopping power (RSP) of each point on the path is a parameter that measures the material's ability to attenuate ion rays, usually defined relative to the stopping power of water. By integrating the total attenuation on the path, the energy attenuation of the ion beam on different paths is determined, and the water equivalent range of each voxel is calculated.

[0029] For each set irradiation angle, the energy parameter is evaluated and selected to maximize the increase in the preference value of all voxels in the target region. The preference value is derived based on a function relationship between the required ion beam energy for each voxel and its water equivalent range, which determines the required ion beam energy for each irradiation angle.

[0030] Based on the water equivalent range information of the voxels, a preference value function is set for each voxel, which describes the preference degree of the voxel to different ion beam energies. The ion beam energy for each irradiation angle is optimized to maximize the increase in the preference value of the overall target region voxels, and the specific method is as follows:

[0031] Preference value calculation: based on the preference value function and the preset ion beam incident energy, the preference value of each target region voxel is calculated;

[0032] Historical maximum preference value initialization: set the historical maximum preference value of all voxels to the initial value;

[0033] Preference value update: For each irradiation angle, calculate the current preference value for each voxel using the preference value function and the selected incident energy. Compare the current preference value with the previously recorded historical maximum preference value for the voxel. If the current calculated value is greater, update this value as the new historical maximum preference value, and calculate the increase value;

[0034] Energy selection and optimization: Traverse all potential ion beam energy settings and select a specific energy configuration that maximizes the preference value increase for all target region voxels;

[0035] Iterative optimization: Repeat the above calculation and update steps until the optimal ion beam energy configuration is selected for all irradiation angles, thereby maximizing the preference value increase for all target region voxels.

[0036] where the water equivalent range represents the equivalent relationship between the range of the ion beam in water and in actual tissue. This information is obtained by three-dimensional discretization processing of the target region and relative stopping power calculation. The preference value function describes the preference degree of each voxel for different ion beam energies, i.e., which energy level is most suitable for the treatment needs of the voxel. This preference degree reflects the relationship between ion beam energy and voxel position and properties. Different voxels have different energy requirements due to their location and the type of tissue they are in. The preference value function is usually a continuous function that describes the response of the voxel to different energy levels. By calculating the preference value at different energy levels, a preference value curve can be drawn to show the preference degree of the voxel at various energy levels.

[0037] For example, for a specific voxel, its preference values at low, medium, and high energy levels can be calculated, and a complete preference value function can be obtained through interpolation or fitting methods. The preference value function can have various forms, depending on the properties and treatment needs of the voxel. Common forms include linear functions, polynomial functions, exponential functions, etc. For example, the preference value function of a certain voxel can be represented as a Gaussian distribution, with the central energy corresponding to the optimal treatment energy of the voxel, and the distribution width reflecting the sensitivity of the voxel to energy changes.

[0038] This step determines the most suitable energy configuration by calculating the preference value of each voxel and iteratively optimizes the overall target region voxel preference value increase. This process ensures that each voxel receives the best treatment while minimizing damage to surrounding normal tissue, thereby achieving more efficient and precise ion beam therapy.

[0039] Further, the irradiation optimization using the discrete preference value function includes the following steps:

[0040] Obtain voxel characteristic information: According to the voxel angle range matrix, obtain the water equivalent range WETv of each voxel.

[0041] Bragg peak coverage area judgment: For any energy E, determine the Bragg peak coverage area of the ion beam at this energy;

[0042] Define discrete preference value function: define a discrete preference value function fav(E) for each voxel, which takes the value 1 when the water equivalent range WETv of the voxel is within the Bragg peak coverage area of the ion beam at energy E, otherwise 0;

[0043] Maximum value of preference value and update: for each voxel, in the case of multi-angle irradiation, calculate the maximum value of its preference value fav max (E), which takes the maximum value of the preference value as 1 in the calculated angles;

[0044] Energy selection and optimization: use the discrete preference value function to optimize the required ion beam energy configuration at each irradiation angle to ensure that the increase value of the preference value of all target region voxels reaches the maximum.

[0045] Through three-dimensional image data and calculation model, generate the voxel angle range matrix of the target region. This matrix records the water equivalent range of each voxel at different irradiation angles. Water equivalent range is an important parameter, which represents the equivalent relationship between the range of ion beam in water and in actual tissue. After obtaining this information, the specific water equivalent range of each voxel can be determined. Bragg peak is the peak area of energy deposition of ion beam in matter, where the energy is maximized. The key of this step is to identify the Bragg peak position at different energy levels, and to judge whether the water equivalent range of each voxel is within the Bragg peak coverage area. If the range of the voxel matches the position of the Bragg peak, the preference value of the voxel is set to 1, indicating that this energy has the best effect on the voxel; otherwise, the preference value is set to 0. At different irradiation angles, the preference value of each voxel may be different. By calculating the preference value at each angle and selecting the maximum value, the best treatment effect of each voxel in energy configuration is ensured. This step determines the maximum preference value of each voxel through comparison and update.

[0046] In this step, by traversing and calculating all potential ion beam energy settings, a specific energy configuration is selected to maximize the preference value increment of the entire target region voxels. The core of this step is to use the discrete preference value function to optimize the energy parameters of each irradiation angle, so as to achieve the best treatment effect.

[0047] Further, the continuous preference value function is used for irradiation optimization, which includes the following steps:

[0048] Obtaining voxel feature information: obtaining water equivalent range WETv of each voxel according to the voxel angle range matrix;

[0049] Obtaining ion beam energy and depth dose distribution: obtaining the integral depth dose curve of the ion beam at any energy E in water medium;

[0050] Defining a continuous favor value function; for each voxel, a continuous favor value function fav(E) is defined according to the depth dose curve, which represents the energy acceptance degree of the specific voxel, and the value range is 0 to 1, and the continuous favor value function is based on the water equivalent range of the voxel and the depth dose distribution of the ion beam energy, and the acceptance degree of the voxel at different energies is calculated;

[0051] Cumulative and update of favor value: for each voxel, the cumulative favor value fav accum (E) is calculated under multi-angle irradiation, and the specific calculation method is as follows:

[0052] Wherein, fav'(E) is the favor value function of the voxel in the calculated angles, n represents the number of calculated angles, and if the current angle fav(E) is greater than fav accum (E), the maximum favor value is updated to fav(E);

[0053] Energy selection and optimization: using the continuous favor value function to optimize the required ion beam energy configuration under each irradiation angle, so as to ensure that the increase value of the favor value of all target region voxels reaches the maximum.

[0054] The voxel angle range matrix of the target region is generated by three-dimensional image data and a calculation model. This matrix records the water equivalent range of each voxel at different irradiation angles. The water equivalent range is a key parameter that represents the equivalent relationship between the range of the ion beam in water and the range in actual tissue. After obtaining this information, the specific water equivalent range of each voxel can be determined. The depth dose distribution curve reflects the energy deposition of the ion beam at different depths. This step obtains the dose distribution curve of the ion beam in water at different energy levels through calculation or experimental measurement. The continuous preference value function describes the acceptance of the voxel at different energy levels based on the water equivalent range of the voxel and the depth dose distribution of the ion beam energy. Through this function, the preference of each voxel to different energy levels can be quantified, and the higher the preference value, the better the treatment effect of the voxel at that energy level. The cumulative preference value reflects the comprehensive acceptance of the voxel at multiple irradiation angles. By calculating the preference value at each irradiation angle and accumulating it, the total preference value of the voxel at all irradiation angles can be obtained. By comparing and updating the preference value of each voxel at different angles, the optimal energy configuration is selected to maximize the preference value increment of each voxel. This process iteratively optimizes all potential energy settings to ultimately determine the optimal ion beam energy configuration, ensuring the best treatment effect.

[0055] In this step, the method of ion beam irradiation configuration optimization using the continuous preference value function, by obtaining the water equivalent range of the voxel and the energy depth dose distribution, defining the continuous preference value function representing the energy acceptance of the voxel, and calculating and updating the cumulative preference value under multi-angle irradiation, selecting the energy configuration that maximizes the preference value increment, to optimize the ion beam energy setting at each irradiation angle, to ensure that the preference value increment of all target region voxels reaches the maximum.

[0056] Further, it also includes the steps of quality assessment and weighting of the irradiation angle, the specific steps are as follows:

[0057] Three-dimensional reconstruction and boundary determination: first, three-dimensional reconstruction of the target region is performed, and the boundary surface is determined based on its shape and position;

[0058] Ion beam extension: the ion beam is directed to the target region and extends backward to form a column of equivalent water range at an additional depth;

[0059] Protection coefficient assignment: in the column, a protection coefficient p is assigned to the protection region overlapping with the target region i , where 0 i < 1;

[0060] Projection area calculation: calculate the projection of the protection region and the target region in the column cross-section, and obtain the effective projection area A j of each irradiation angle,

[0061] where T is the projected area of the target volume, Q i is the projected area of the overlap between the protection region i and the target volume, p i is the protection factor of the protection region i, and n is the number of protection regions overlapping with the target volume in the cylinder;

[0062] Distribution of irradiation weights: based on the irradiation quality indicator A j for each irradiation angle, the irradiation weights are distributed using the formula where n is the total number of irradiation angles.

[0063] The target volume is reconstructed in three dimensions using three-dimensional image data and a computational model to accurately represent its shape and position. The boundary surface is determined to accurately assess the impact of irradiation angles on the target volume and protection regions in subsequent steps. The ion beam continues to extend after irradiating the target volume, forming a cylindrical body with a depth equivalent to the water range. The purpose of this step is to simulate the further impact area of the ion beam after passing through the target volume in order to assess its impact on surrounding tissues. In order to quantify the impact of the ion beam on protection regions outside the target volume, a protection factor p i is assigned to each overlapping protection region. The protection factor has a value between 0 and 1, indicating the importance and sensitivity of the region, with a value closer to 1 indicating a higher protection requirement. By calculating the projected area of the protection regions and the target volume in the cylinder cross-section for each irradiation angle, the coverage of different irradiation angles on the target volume and protection regions can be quantified. Using the above formula, the effective projected area of each irradiation angle is converted into an irradiation weight W j . The higher the weight, the better the coverage of the angle on the target volume and the smaller the impact on the protection regions.

[0064] This step evaluates and weights each angle of ion beam irradiation, optimizing the irradiation configuration. This process not only considers the effective coverage of the target volume, but also takes into account the safety of the protection regions. Ultimately, based on these weight information, the best irradiation angle and energy configuration are selected to achieve high efficiency and accuracy of ion beam therapy while minimizing damage to surrounding normal tissues.

[0065] Further, according to the irradiation weight of each irradiation angle, the number of energy layers of the ion beam emitted at each irradiation angle is determined, so that the irradiation angle with a higher irradiation weight has more energy layers; wherein the step of determining the number of energy layers of the ion beam emitted at each irradiation angle comprises: for each irradiation angle, calculating the proportion of the total number of energy layers occupied according to its irradiation weight; for each irradiation angle, according to the proportion of the total number of energy layers occupied, the number of energy layers of the ion beam emitted is allocated, so that the total number of energy layers does not exceed the preset maximum value.

[0066] The irradiation weight reflects the coverage effect of each irradiation angle on the target region and the impact on the protection area. The higher the weight, the better the coverage of the target region and the smaller the impact on the protection area. In order to fairly allocate the number of energy layers, the proportion of the weight of each irradiation angle needs to be calculated. For each irradiation angle, according to the proportion of the total number of energy layers it occupies, the number of energy layers of the ion beam it emits is allocated, so that the total number of energy layers does not exceed the preset maximum value.

[0067] Further, the step of discretizing the irradiation angle includes the following specific steps: the entire range of available irradiation angles is evenly divided into multiple equally spaced subintervals in the horizontal and / or vertical direction; in each subinterval, the center point of the interval is selected as a candidate irradiation angle; for each candidate irradiation angle, based on the number of intersection points of the angle and the path distance of the ion beam to the target region, the irradiation priority is calculated; from all candidate irradiation angles, according to the calculated priority, the highest priority angle is selected as the irradiation angle to be used in the actual irradiation plan.

[0068] In order to systematically select the best irradiation angle, the range of available irradiation angles needs to be discretized. For example, the variable range of gantry angle and treatment bed angle is evenly divided into multiple equally spaced subintervals. This ensures that all possible irradiation angles are covered and provides a basis for subsequent priority calculation. Each subinterval represents a specific angle range. By selecting the center point of these intervals as a candidate irradiation angle, the calculation process can be simplified while ensuring the representativeness of each angle. For example, if a subinterval is between 0 and 10 degrees in the horizontal angle, the center point is 5 degrees, which will be used as the candidate irradiation angle. The irradiation priority is a comprehensive indicator that evaluates the effectiveness of each candidate irradiation angle. When calculating the priority, the following factors need to be considered:

[0069] Intersection points: the number of intersection points of the ion beam path with the key points inside the target region. The more intersection points, the more comprehensive the coverage of the target region by the angle.

[0070] Path distance: the path distance of the ion beam from the emission source to the target region. Shorter path distance usually means less energy loss and higher precision.

[0071] In this step, among all candidate irradiation angles, the angle with the most comprehensive coverage of the target region and the optimal path distance can be selected through priority calculation. The angle with the highest priority will be selected as the irradiation angle to be used in the actual irradiation plan. This selection process ensures that the irradiation effect of the ion beam is maximized while optimizing the treatment efficiency.

[0072] Further, a plurality of key voxels are found by a discretization method, wherein the step of finding the plurality of key voxels by the discretization method comprises:

[0073] Three-dimensional discretization processing: performing three-dimensional discretization on the treatment target region, dividing it into a plurality of cubic voxels;

[0074] Energy matrix calculation: for each voxel, at each predetermined irradiation angle, based on its water equivalent range, the energy size of the required ion beam is calculated, and an energy matrix is constructed;

[0075] Preference value matrix determination: using the data in the energy matrix, a preference value is set for each voxel, and a preference value matrix is generated;

[0076] Influence degree evaluation: analyzing the numerical value of each voxel in the preference value matrix to evaluate its influence degree on the overall irradiation plan, and assigning an influence degree value to it;

[0077] Key voxel selection: according to the influence degree value, a plurality of voxels with the highest influence degree are selected, which are identified as key voxels.

[0078] Discretize the continuous three-dimensional space and divide the entire treatment target region into a plurality of cubic voxels. Each voxel represents a specific volume unit, which makes the calculation and analysis more precise and accurate. For each voxel, at different predetermined irradiation angles, the required ion beam energy is calculated. Water equivalent range is a key parameter for determining the energy distribution of the ion beam within the voxel. Through these calculations, an energy matrix is generated, which records the energy values required by each voxel at each angle. According to the data in the energy matrix, a preference value is set for each voxel. The preference value reflects the degree of preference of the voxel for different energy levels, and through these values, a preference value matrix is generated. The preference value matrix can intuitively show the response of each voxel at different irradiation angles and energy levels. By analyzing the data in the preference value matrix, the influence degree of each voxel on the overall irradiation plan is evaluated. The influence degree value is a comprehensive indicator that reflects the sensitivity and importance of the voxel to ion beam energy configuration. The higher the value, the greater the influence of the voxel on the overall plan. According to the influence degree value calculated in the previous step, a plurality of voxels with the highest influence degree are selected. These voxels are identified as key voxels because they have the greatest influence on the overall irradiation plan. The selection of key voxels is to prioritize these voxels that are crucial to the treatment effect when optimizing the irradiation configuration.

[0079] This step, through the discretization processing and the influence degree evaluation, identifies the key voxels of the whole irradiation planning. The identification of the key voxels ensures that, in the optimization of the irradiation configuration, the voxels which are crucial to the treatment effect are given priority, thereby improving the accuracy and effectiveness of the treatment and reducing the damage to the surrounding normal tissues.

[0080] An ion beam emitting system applying the ion beam irradiation configuration optimization method, comprising: a vertically up-and-down lifting and rotatable seat device, which can be up-and-down fluctuated in height according to a sinusoidal curve and can complete at least two rotations during operation, wherein the height sinusoidal phase of the starting position of the second rotation is different from the height sinusoidal phase of the starting position of the first rotation by 180 degrees; an ion beam emitting unit equipped with a magnetic field deflection device, which is used to deflect the ion beam directly to the target area through the magnetic field when the target area deviates from the isocenter, so as to realize the non-coplanar irradiation; the system realizes the multi-angle and multi-level irradiation of the target area by adjusting the rotation angle and height of the rotating seat and the ion beam deflection direction of the ion beam emitting unit, optimizes the irradiation effect, and reduces the influence on the surrounding normal tissues; the ion treatment system further comprises the following modules: a. a three-dimensional scanning acquisition module for acquiring three-dimensional image data of the target area and defining the target area to be processed; b. an irradiation angle setting module for setting a plurality of irradiation angles according to different treatment requirements; c. an energy parameter evaluation and selection module for evaluating and selecting the energy parameters based on the maximum preference value increase value of all voxels in the target area; d. a voxel feature information acquisition module for acquiring the water equivalent range of the voxels in the target area and performing three-dimensional discretization processing on the region to be processed; e. a relative stopping power calculation module for calculating the stopping power of the ray path from the ion beam emitting source to the center of each voxel at each predetermined irradiation angle; f. a voxel angle range matrix construction module for calculating and summarizing the water equivalent range of each voxel at different irradiation angles based on the line integral method to form a voxel angle range matrix; g. a preference value function setting and optimization module for setting the preference value function for each voxel and performing optimization calculation using the discrete preference value function to determine the optimal ion beam energy configuration at each irradiation angle.

[0081] A computer storage medium having instructions stored thereon, the instructions being used to make a computer execute the ion beam irradiation configuration optimization method.

[0082] The ion beam irradiation configuration optimization method of the present application has the beneficial effects that:

[0083] Improving treatment accuracy: The present application ensures that the ion beam can irradiate the target area from multiple optimal angles by optimizing the irradiation angle and the energy parameter, and calculates the required ion beam energy for each voxel, achieving optimal energy coverage for all voxels in the target area, reducing the possibility of missed irradiation and over-irradiation, and improving the accuracy and effectiveness of treatment. Three-dimensional discretization processing and voxel angle range matrix construction further refine the irradiation plan and ensure the targeting of treatment.

[0084] Optimizing energy configuration: By setting a preference value function, the preference degree of each voxel to different ion beam energies is quantified, and the optimization calculation of energy configuration is carried out based on these preferences. The application of the preference value function makes the optimization of energy configuration more scientific, ensuring that the ion beam energy can effectively cover the target area and improve the treatment effect. At the same time, according to the irradiation weight of each irradiation angle, the number of energy layers is dynamically allocated, so that the irradiation angle with higher weight is allocated more energy layers, avoiding energy waste and over-irradiation.

[0085] Reducing damage to normal tissues: The present application significantly reduces damage to normal tissues through non-coplanar multi-angle irradiation and optimization of the protection area. The application of the rotating chair device and the magnetic field deflection device realizes non-coplanar multi-angle irradiation of the ion beam, which can effectively disperse energy and avoid damage to normal tissues caused by high-dose irradiation in a single direction. At the same time, a protection coefficient is assigned to the protection area overlapping the target area, and its projected area during irradiation is calculated to minimize the impact on normal tissues and improve the safety of treatment.

[0086] Improving treatment efficiency: By performing three-dimensional scanning on the target area to obtain accurate three-dimensional image data, and performing three-dimensional discretization processing on the area to be processed, detailed voxel feature information is obtained and processed, providing a basis for optimizing the treatment plan. By identifying key voxels and prioritizing irradiation based on these key voxels, the present application ensures that voxels critical to treatment effectiveness are given priority in optimizing irradiation configuration, further improving the accuracy and effectiveness of treatment, while reducing damage to normal tissues.

[0087] Flexible and personalized treatment plan: The present application realizes multi-angle and multi-level irradiation of the target area by dynamically adjusting the irradiation angle and energy configuration, improving treatment efficiency. Flexible irradiation configuration makes the treatment process more efficient, shortening the treatment time. Personalized treatment plan ensures that each patient can receive the most suitable treatment by accurately scanning and analyzing the specific situation of each patient, improving the accuracy and effectiveness of treatment, and ensuring that each patient receives the best treatment effect. Real-time adjustment of the treatment plan makes the treatment more flexible, allowing timely adjustments according to actual conditions to ensure the best implementation of treatment effect.

[0088] The ion beam emission system of the present application has the following beneficial effects:

[0089] Multi-angle and multi-level irradiation: The system achieves multi-angle and multi-level irradiation of the ion beam through a seat device that can rotate and rise and fall, and a magnetic field deflection device. The rotation and height adjustment of the seat enable the ion beam to irradiate the target area from different heights and angles, ensuring that the ion beam covers every part of the target area, avoiding the risk of missed irradiation and excessive irradiation, and improving the comprehensiveness and accuracy of treatment.

[0090] Flexibility of non-coplanar irradiation: Through the magnetic field deflection device, the ion beam can perform non-coplanar irradiation when deviating from the isocenter in the target area, increasing the flexibility and accuracy of irradiation. This non-coplanar irradiation method can optimize the energy delivery path, reduce the radiation exposure of normal tissues, improve the safety and effectiveness of treatment, and adapt to complex-shaped target areas, improving the applicability of treatment.

[0091] Precise three-dimensional scanning and target area definition: The system is equipped with a three-dimensional scanning acquisition module that can accurately acquire three-dimensional image data of the target area and define the target area. This process ensures that the ion beam can accurately aim at the target area, avoiding errors and improving the targeting of treatment. The three-dimensional reconstruction and boundary determination process enables the treatment plan to be designed based on the real anatomical structure, further improving the accuracy of treatment.

[0092] Optimized energy parameter selection: The system includes an energy parameter evaluation and selection module that evaluates and selects energy parameters based on the maximum preference value increase value of all voxels in the target area. Through this optimization method, the system can select the best energy configuration for each irradiation angle, ensuring that each voxel receives the best treatment energy, improving treatment effectiveness, and reducing unnecessary energy waste.

[0093] Reducing the impact on normal tissues: The system performs quality assessment and weighting on the irradiation angles, calculates the effective projection area and protection coefficient of each irradiation angle, and ensures that the impact on normal tissues is minimized. By optimizing the irradiation weight and energy layer quantity distribution, the system can preferentially select irradiation angles that have good coverage of the target area and have little impact on normal tissues, reducing the radiation exposure of normal tissues, improving the safety of treatment, and improving the comfort of patients. BRIEF DESCRIPTION OF DRAWINGS

[0094] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, a brief introduction to the drawings needed to be used in the embodiment or prior art description will be given below.

[0095] Figure 1 is a flowchart of the ion beam irradiation configuration optimization method of the present application.

[0096] Figure 2 is a schematic diagram of the energy optimization process based on the preference value function.

[0097] FIG. 3 is a flow chart of an ion beam irradiation configuration optimization method based on a continuous preference value function. DETAILED DESCRIPTION

[0098] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application.

[0099] Embodiment 1: Ion beam irradiation configuration optimization method

[0100] As shown in FIGS. 1 and 2, the present embodiment describes in detail an ion beam irradiation configuration optimization method, which aims to achieve efficient and accurate irradiation of the tumor target area through multi-angle and multi-level optimization configuration. The entire process covers the acquisition of three-dimensional image data, the accurate definition of the target area, the setting of multiple irradiation angles, and the optimization calculation of energy parameters at each angle. The following specific implementation steps will detail how to use advanced imaging technologies such as CT or MRI for three-dimensional scanning to obtain detailed three-dimensional image data of the target area, and based on these data, a series of optimization calculations are performed to ensure that each voxel can obtain the best treatment effect.

[0101] Step S1: Obtain three-dimensional image data. Choose imaging method: according to the target tissue and clinical needs, choose CT or MRI scanning. Set scanning parameters: adjust scanning mode, layer thickness, speed and other parameters to ensure image quality and patient comfort. Preparation: patient positioning, contrast agent use, patient guidance. Perform scanning: follow the procedure to perform scanning and obtain raw image data. Data processing: reconstruct images, denoise, correct, and store the processed three-dimensional image data in the hospital's PACS (Picture Archiving and Communication System) for subsequent target area definition and irradiation optimization.

[0102] Step S2: Target area definition. Based on the obtained three-dimensional image data, use image processing software and doctors' professional knowledge to accurately mark the target area that needs to be irradiated. This step determines the target area for treatment by analyzing the image data. Import the three-dimensional image data into professional medical image processing software such as MIM, Velocity, etc. Use the segmentation tool of the software to preliminarily segment the tumor and related tissues according to the different densities and contrasts of the image. The professional marking of the doctor is reviewed and modified by a professional radiation oncologist to ensure the accuracy of the target area. Manually mark complex areas, combine multi-angle and multi-slice image data to improve the accuracy of the marking. Confirm and save the target area to save the final confirmed target area as a three-dimensional data file for subsequent irradiation optimization.

[0103] Step S3: Set multiple irradiation angles. In order to ensure that the ion beam energy can fully cover the target area and reduce damage to the surrounding normal tissues, this step needs to set multiple irradiation angles to achieve the optimization of energy distribution through the optimization of angle combinations.

[0104] Irradiation angle range division: Uniformly divide the horizontal angle range (e.g., 360 degrees) and the vertical angle range (e.g., 180 degrees) into several sub-intervals. For example, divide the horizontal plane into 36 sub-intervals, each 10 degrees; divide the vertical plane into 18 sub-intervals, each 10 degrees.

[0105] Candidate irradiation angle selection: Select candidate angles from the center points of each sub-interval. By combining horizontal and vertical angles, a series of candidate irradiation angles are generated, ensuring uniform distribution of angles.

[0106] Angle selection:

[0107] Calculate the priority of all candidate angles, sort them according to the results and select the optimal angle combination. The final irradiation angle combination will optimize the treatment effect while minimizing damage to normal tissues.

[0108] Step S4: Calculate the energy parameters under each irradiation angle

[0109] After setting multiple irradiation angles, detailed energy parameter evaluation and selection need to be performed for each angle. The goal of this step is to maximize the preference value of all voxels in the target area by optimizing energy distribution, thereby improving treatment effect and reducing damage to normal tissues.

[0110] The energy optimization process based on the preference value function includes the following specific steps:

[0111] Step S4.1: Obtain the water equivalent range of the target area voxels

[0112] Three-dimensional discretization processing is performed on the target area, dividing the area to be processed into multiple cubic voxels (Voxel). The rays emitted from the ion beam emission source to the center of each voxel are calculated to obtain the path from the ray source to the center of each voxel.

[0113] This step specifically includes the following:

[0114] Three-dimensional discretization processing:

[0115] First, perform three-dimensional discretization processing on the target area. This is the process of dividing a continuous three-dimensional space into a series of finite and discrete units or voxels (Voxel). Each voxel represents a specific volume unit, usually a cube.

[0116] Three-dimensional discretization processing process:

[0117] Image Acquisition: The target region is scanned using imaging equipment such as CT or MRI, obtaining high-resolution three-dimensional image data of the region. These data are usually stored in the form of two-dimensional slices, each representing a two-dimensional planar image.

[0118] Image Reconstruction: The two-dimensional slice data is reconstructed into a complete three-dimensional image. This process is completed through image processing software, such as using Fourier transform or other reconstruction algorithms, to splice two-dimensional slices into three-dimensional volume data.

[0119] Three-dimensional discretization processing: High-resolution three-dimensional image data obtained in the above steps is subjected to three-dimensional discretization processing.

[0120] The specific steps are as follows:

[0121] a. Determine the size of the voxel: Select the size of the voxel according to the needs, the edge length of the voxel is usually determined according to the resolution of the imaging equipment and the limitation of the computing resources. For example, in order to realize high-precision planning in radiotherapy, the edge length of the voxel can be set to 1 millimeter.

[0122] b. Divide the space: Divide the entire target region into multiple three-dimensional grids, each grid unit is a voxel. Each voxel represents a fixed volume unit, usually a cube.

[0123] For example, the entire region to be processed is divided into multiple cubic voxels with an edge length of 1 millimeter. Through such detailed division, the fineness and accuracy of subsequent calculations can be ensured. Example: Suppose we have a 10 cubic centimeter target region that needs to be subjected to three-dimensional discretization processing. We choose 1 millimeter as the edge length of the voxel, so the entire target region will be divided into 1000 voxels (10×10×10 cubes). Each voxel occupies a volume of 1 cubic millimeter, covering the entire target region. This division makes the specific position and volume of each voxel clear, facilitating subsequent calculations and processing.

[0124] c. Generate voxel data: Map high-resolution three-dimensional image data to the generated voxel grid. The data value of each voxel is usually calculated by averaging or interpolating the pixels it covers to reflect the physical properties of its location.

[0125] For example, if a voxel contains multiple pixel points, the value of the voxel can be determined by averaging the values of these pixel points. Path calculation:

[0126] Next, for each predetermined irradiation angle, the rays from the ion beam emission source to the center of each voxel are calculated. This step involves the following specific content:

[0127] Determine the coordinates of the emission source and voxel centers: First, determine the position of the ion beam emission source and the coordinates of each voxel center. The position of the emission source is usually fixed, while the coordinates of the voxel centers depend on their specific positions after the three-dimensional discretization process.

[0128] Calculate the ray path: The ray path from the emission source to each voxel center needs to be accurately calculated. The position of every point on this path must be clearly defined to accurately assess the propagation of the ray in different media in subsequent steps.

[0129] Path segmentation and integration: Divide the ray path into small segments, each located in a specific medium. Accurately calculate the total length of the ray path and the attenuation effect of each segment of medium by integrating step by step.

[0130] Step S4.2: Calculate the relative stopping power

[0131] For each point on each ray path, compare the material composition and density at that point with the standard of water to calculate the relative stopping power of that point on the ion beam. The specific process is as follows:

[0132] Determine the material composition and density:

[0133] For each point on the ray path, first determine the material composition and density at that point. These information can be obtained through previous three-dimensional scanning data and related image processing techniques.

[0134] For example, CT scanning can provide density information of voxels, and these density information can be further converted into stopping power data. Definition of relative stopping power:

[0135] Relative stopping power (RSP) is a parameter that measures the ability of a material to attenuate ion beams, usually defined relative to the stopping power of water.

[0136] Relative stopping power calculation step Ray path determination:

[0137] First, calculate the ray path from the ion beam emission source to each voxel center. The ray path is the path of the ion beam through the target region, which can be considered as a straight line, and the relative stopping power needs to be calculated for each point along this path.

[0138] Obtain the material composition and density: For each point on the ray path, determine the material composition and density at that point. Usually, image data obtained by CT scanning can provide these information. The gray value in CT image can be converted into the material density information at the corresponding position.

[0139] Calculation of Relative Stopping Power:

[0140] Relative Stopping Power (RSP) refers to the relative value of the material's attenuation ability compared to water. Specifically, RSP is the ratio of the stopping power of the material at that point to the stopping power of water under the same conditions.

[0141] Formula: RSP can be calculated by the following formula:

[0142] Where S1 is the stopping power of the material at that point, and S2 is the stopping power of water for the same ion beam. Material Stopping Power: The stopping power of a material for an ion beam depends on the electron density and atomic number of the material. Materials with high atomic number and high electron density generally have higher stopping power.

[0143] Stopping Power of Water: The stopping power of water as a standard reference material is a known constant value.

[0144] Calculation of RSP values requires consideration of the electron density and atomic number of the material, which directly affect the weakening effect of ion beams. Calculation method: For each point's RSP value, compare its material composition and density with the standard value of water to determine the relative stopping power. The specific calculation formula can be determined according to the physical properties of the material and empirical formula. For example, use the Bethe formula to calculate the stopping power, and then convert it to RSP value by ratio. Data processing: Collect the RSP values of all points on the ray path to form a complete path RSP data. These data will be used for subsequent water equivalent range calculation to ensure accurate energy calculation for each voxel.

[0145] Example

[0146] Suppose a point on the ion beam path is in bone tissue, and another point is in soft tissue. The electron density and atomic number of bone tissue are higher than those of soft tissue, so its relative stopping power is also higher. Through CT image data, the material density information of the two points can be obtained, and their respective relative stopping powers can be calculated by the formula:

[0147] Bone tissue point: Suppose the stopping power S bone of bone tissue is 1.8 times that of water, then the RSP of this point is 1.8.

[0148] Soft tissue point: Suppose the stopping power S soft of soft tissue is 1.05 times that of water, then the RSP of this point is 1.05.

[0149] By integrating these relative stopping powers along the ray paths, the total attenuation of the ion beam along the path can be obtained, thus determining the water equivalent range of each voxel.

[0150] Step S4.3: Constructing the voxel angle range matrix

[0151] In this step, we will calculate the sum of relative stopping powers along each ray path using the line integral method to determine the water equivalent range of each voxel. Then, we will compile the water equivalent range data of each voxel at different irradiation angles to form a voxel line integral calculation of the sum of relative stopping powers:

[0152] For each irradiation angle, the path from the ion beam emission source to the center of each voxel has been calculated in step S4.1.

[0153] Along each ray path, the relative stopping power (RSP) is line integrated. Line integration is the cumulative sum of RSP values at all points along the path, which can be calculated by the following formula:

[0154] L eff =∫ path RSP(x)dx

[0155] where L eff represents the effective path length, RSP(x) represents the relative stopping power of a point on the path, and dx is a small distance element on the path.

[0156] Determine the water equivalent range:

[0157] The water equivalent range refers to the equivalent range length of the ion beam in water, which is used to represent the penetration ability of the ion beam in different media. The effective path length obtained by line integration can reflect the attenuation of the ion beam in actual tissue.

[0158] According to the calculated effective path length, determine the water equivalent range of each voxel. The water equivalent range calculation formula is as follows:

[0159] where R water represents the water equivalent range, L eff is the effective path length, and RSP water is the relative stopping power of water, usually taking a value of 1.

[0160] Compile the water equivalent range at different irradiation angles:

[0161] For each voxel, repeat the above line integral and water equivalent range calculation at all predetermined irradiation angles.

[0162] Each voxel will have multiple water equivalent range values corresponding to different irradiation angles.

[0163] Constructing the voxel-angle range matrix:

[0164] The water equivalent range values of each voxel at all irradiation angles are aggregated to form a multi-dimensional matrix, known as the voxel-angle range matrix. Each element in the matrix represents the water equivalent range of a certain voxel at a certain irradiation angle.

[0165] For example, if a target region is divided into m x n x p voxels and q irradiation angles are set, the dimension of the voxel-angle range matrix is m x n x p x q.

[0166] Data storage and processing:

[0167] The calculated voxel-angle range matrix is stored for subsequent steps.

[0168] Further processing of the voxel-angle range matrix can be performed using matrix operations and analysis tools to analyze the impact of different irradiation angles on the voxels.

[0169] Example illustration: Suppose there is a target region divided into 10 x 10 x 10 voxels and there are 5 predetermined irradiation angles. Through the above steps, the water equivalent range of each voxel at these 5 irradiation angles is calculated, forming a 10 x 10 x 10 x 5 voxel-angle range matrix. Each element of this matrix reflects the water equivalent range length of a specific voxel at a specific irradiation angle. The data in the matrix will be used in the subsequent preference value function setting and energy optimization process.

[0170] Step S4.4: Set the preference value function

[0171] In this step, we set a discrete preference value function for each voxel based on the water equivalent range information of the voxel. This function describes the preference degree of the voxel for different ion beam energies. The specific steps are as follows:

[0172] Read the voxel-angle range matrix: First, read the data from the voxel-angle range matrix constructed in step S4.3. This matrix contains the water equivalent range information of each voxel at different irradiation angles. The dimension of this matrix is m x n x p x q, where m, n, p represent the number of voxels in the target region in three dimensions, and q represents the number of predetermined irradiation angles.

[0173] Extract the water equivalent range information of each voxel: First, determine the position of the target voxel in the voxel-angle range matrix. For example, for voxel V ijk , the position in the matrix is (i, j, k). For each voxel V ijk , we need to extract its water equivalent range at all predetermined irradiation angles θ1, θ2, …, θ qwater equivalent range values at each of the irradiation angles. Specifically, the water equivalent range value of the voxel at each irradiation angle is extracted from the matrix to form a vector containing these values. For example, voxel V ijk The water equivalent range value at irradiation angle θ1is R ijkθ1 The water equivalent range value at irradiation angle θ2is R ijkθ2 and so on, until the last irradiation angle θ q All the extracted water equivalent range values are combined into a vector representing the water equivalent range R ijkθ1 R ijkθ2 …, R ijkθq of the voxel at all irradiation angles. For example, voxel V ijk The water equivalent range vector of voxel V ijkθ1 at all irradiation angles is [R ijkθ2 , R ijkθq ].

[0174] Example:

[0175] Suppose the target region is divided into 10x10x10 voxels and 5 predetermined irradiation angles are set. The dimension of the voxel angle range matrix is 10x10x10x5. For voxel V 555 we need to extract its water equivalent range values at the 5 irradiation angles. Suppose the 5 irradiation angles are θ1, θ2, θ3, θ4, θ5, respectively, then the water equivalent range values of voxel V 555 at these irradiation angles are R 555θ1 , R 555θ2 , R 555θ3 , R 555θ4 , R 555θ5 Finally, the water equivalent range vector of voxel V 555 can be represented as: [R 555θ1 , R 555θ2 , R 555θ3 , R 555θ4 , R 555θ5 By extracting and constructing such data vectors, we can comprehensively understand the water equivalent range of each voxel at different irradiation angles, providing accurate data support for subsequent preference value calculation and energy optimization.

[0176] Bragg peak coverage area judgment:

[0177] For any energy E, determine the Bragg peak coverage area for ions of that energy. The Bragg peak refers to the peak region of energy deposition of the ion beam in the material. The ion beam gradually slows down as it passes through the material, and the energy is released concentrated at the end of the penetration depth, forming the Bragg peak. This peak region is crucial for treatment effectiveness, as it can precisely deliver the maximum energy to the target area, maximizing tumor cell killing while minimizing damage to surrounding normal tissue.

[0178] For example, the water equivalent range range of the Bragg peak coverage area for energy E can be determined through experimental data or computational models.

[0179] Through experimental methods, the depth dose distribution curves of ion beams of different energies in water medium can be measured. The specific steps are as follows:

[0180] Use a water phantom experimental device to emit ion beams of different energies.

[0181] Arrange multiple detectors in the water to record the energy deposition of the ion beam at different depths.

[0182] Generate depth dose distribution curves to determine the location and coverage of the Bragg peak.

[0183] For example, experimental measurements show that the Bragg peak coverage area of ion beams of energy E1 in water is 20-25 cm, the Bragg peak coverage area of energy E2 is 30-35 cm, and so on.

[0184] Through computational models, the energy deposition of ion beams of different energies in water medium can also be simulated. The specific steps are as follows: Use Monte Carlo simulation or other physical simulation software, input the ion beam energy, initial position and direction, etc. Run the simulation to calculate the energy deposition distribution of the ion beam in water. Analyze the simulation results to determine the location and coverage of the Bragg peak. Computational models can provide more detailed results than experimental data, as they can take into account various complex factors such as different tissue types, density variations, etc. After determining the Bragg peak coverage area, it can be applied to ion beam treatment planning. For example, when setting the preference value function, it can be determined whether the water equivalent range of each voxel is within the Bragg peak coverage area of energy E, thereby determining the preference value of the voxel for that energy.

[0185] Example:

[0186] Suppose the following Bragg peak coverage areas are determined through experimental data and computational models:

[0187] Energy E1: Bragg peak coverage area 20-25 cm

[0188] Energy E2: Bragg peak coverage area 30-35 cm

[0189] Energy E3: Bragg peak coverage area is 40-45 cm

[0190] For voxel V ijk , its water equivalent range R ijk，water is 22 cm. By judgment, it is found that R ijk，water is located in the Bragg peak coverage area of energy E1, so the preference value of this voxel for energy E1 is set to 1, and the preference value for other energies is set to 0.

[0191] The Bragg peak coverage area is determined by experimental data or a calculation model, which can accurately guide the development of ion beam treatment plans, ensure the effective deposition of energy in the target area, and improve treatment effectiveness.

[0192] Define a discrete preference value function:

[0193] In the ion beam irradiation configuration optimization process, in order to quantify the preference degree of each voxel for different energy levels, we define a discrete preference value function fav(E) for each voxel. The specific process is as follows:

[0194] Define the form of the discrete preference value function:

[0195] For each voxel V i , we define a discrete preference value function fav i (E) to describe the preference value of the voxel at a specific energy E.

[0196] The form of the function is as follows:

[0197] Where fav i (E) represents the preference value of the i-th voxel at energy E, and R i，water is the water equivalent range of the i-th voxel. Through experimental data or a calculation model, the Bragg peak coverage area at different energies E can be determined. For example, for energy E, its Bragg peak coverage area can be a certain specific water equivalent range, such as 20-25 cm.

[0198] According to the water equivalent range R i，water of each voxel, it is determined whether the voxel is located in the Bragg peak coverage area of a specific energy E.

[0199] If R i，water is located in the Bragg peak coverage area of energy E, the value of fav i (E) is 1, indicating that the preference value of the voxel at energy E is 1.

[0200] If R i，water is not located in the Bragg peak coverage area of energy E, favi (E) is 0, meaning the voxel has a favorability value of 0 at energy E.

[0201] Specific example: Assume the i-th voxel V i has a water-equivalent range R i，water of 22 cm. Through experimental data or a computational model, it is determined that the Bragg peak coverage region for energy E1 is 20-25 cm, and the Bragg peak coverage region for energy E2 is 30-35 cm.

[0202] For energy E1, because R i，water is within its Bragg peak coverage region, fav i (E1) = 1.

[0203] For energy E2, because R i，water is within its Bragg peak coverage region, fav i (E2) = 0.

[0204] For voxel V i , its favorability values need to be calculated at all irradiation angles.

[0205] For example, assume there are q predetermined irradiation angles, θ1, θ2, …, θ q at which the favorability values of voxel V i are calculated as fav i (E1), fav i (E2), …, fav i (Eq).

[0206] For each voxel, the maximum of its favorability values is calculated under multi-angle irradiation. The specific method is as follows: compare the favorability values of voxel V i at all calculated irradiation angles, and take the maximum value as the maximum favorability value of the voxel. The specific method is as follows: initialize a variable max_fav i to 0, which is used to store the maximum favorability value of voxel V i . For each irradiation angle θ j : max_fav i = max(max_fav i , fav i (Ej)) This process ensures that for each voxel V i , we can find its maximum favorability value at all irradiation angles.

[0207] Example explanation: Assume there are 3 predetermined irradiation angles θ1, θ2, θ3 and corresponding energies E1, E2, E3. The favorability values of voxel V i at these angles are:

[0208] fav i (E1) = 0 (because R i，water is not in the Bragg peak coverage region of E1)

[0209] fav i (E2) = 1 (because R i，water is in the Bragg peak coverage region of E2)

[0210] fav i (E3) = 0 (because R i，water is not in the Bragg peak coverage region of E3)

[0211] By comparing the favorability values of these three angles, we get the maximum favorability value of voxel V i :

[0212] ma_fav i = max(0, 1, 0) = 1

[0213] Step S4.5: Energy selection and optimization

[0214] In the ion beam irradiation configuration optimization process, in order to ensure that each voxel can obtain the best energy coverage, we use the discrete favorability function to optimize the required ion beam energy configuration under each irradiation angle. The specific steps are as follows: traverse all potential ion beam energy settings: first, list all possible ion beam energy settings. These energy settings can cover the entire energy range required for treatment, from the lowest energy to the highest energy. Calculate the overall favorability increase value under each energy configuration: for each irradiation angle θ j , traverse all energy settings E k , calculate the favorability of the voxel under this energy configuration. Use the previously defined discrete favorability function fav i (Ek) to determine the favorability of each voxel under energy E k . Accumulate the favorability increase value of all voxels in the target region under this energy configuration:

[0215] where m is the total number of voxels in the target region, and current_favi is the current favorability of voxel V i .

[0216] Select the optimal energy configuration:

[0217] Compare the overall favorability increase value of all energy settings under each irradiation angle, and select the energy configuration that can maximize the favorability increase value of all target region voxels as the final energy setting.

[0218] The specific method is as follows:

[0219] Initialize a variable max_fav_increase to store the current maximum favorite value increase of energy.

[0220] Initialize a variable optimal_energy_setting to store the corresponding optimal energy setting.

[0221] For each energy setting E k : max_fav_increase = max(max_fav_increase, Δfavθj(Ek))

[0222] If Δfavθj(Ek) > max_fav_increase, update optimal_energy_setting to E k .

[0223] Final energy configuration determination: Through the above steps, the optimal energy configuration for each irradiation angle is determined, making the favorite value increase of all voxels in the target region reach the maximum. Record the optimal energy configuration for each irradiation angle as the final energy setting for use in actual treatment planning.

[0224] Through the above steps, the ion beam energy configuration for each irradiation angle can be optimized to ensure that the favorite value increase of all voxels in the target region reaches the maximum, thereby achieving high efficiency of treatment effect.

[0225] Step S4.6: Iterative optimization

[0226] In the process of ion beam irradiation configuration optimization, the optimal ion beam energy configuration for all irradiation angles is finally selected through continuous calculation and update to maximize the favorite value increase of all voxels in the target region. The specific steps are as follows:

[0227] Initialization settings:

[0228] Set the initial energy configuration and irradiation angle.

[0229] Initialize the favorite value of each voxel to the initial value (usually zero).

[0230] Initial calculation:

[0231] According to the initial energy configuration and irradiation angle, calculate the favorite value of each voxel.

[0232] Record the current favorite value and increase value of each voxel.

[0233] Iterative calculation:

[0234] For each predetermined irradiation angle, traverse all potential energy settings Ek.

[0235] Calculate the increase in the preference value for all voxels in the target region at each energy configuration Ek.

[0236] Select the configuration with the maximum increase in the preference value as the temporary optimal configuration for that angle in the current energy configuration.

[0237] Update the preference value:

[0238] For each voxel, compare its preference value in the current energy configuration with the previously recorded historical maximum preference value.

[0239] If the current preference value is greater than the historical maximum preference value, update the historical maximum preference value and record the corresponding energy configuration.

[0240] Check the convergence condition:

[0241] Determine whether the preference values of all voxels have reached a stable state, i.e., whether the changes in the preference values are less than a pre-set threshold after multiple iterations.

[0242] If the convergence condition is met, end the iteration and the current configuration is the optimal configuration.

[0243] If the convergence condition is not met, continue the iteration.

[0244] Output the optimal configuration:

[0245] After reaching the convergence condition, output the optimal energy configuration for each irradiation angle.

[0246] Record the final preference values of all voxels and the corresponding energy configurations.

[0247] Through the continuous iteration of the above steps, the optimization of energy configuration and irradiation angle is ensured, which maximizes the increase in the preference value of all voxels in the target region, and finally achieves the best treatment effect. This process not only improves the accuracy and effectiveness of treatment, but also reduces the damage to surrounding normal tissues, ensuring the safety and efficiency of ion beam therapy.

[0248] Example 2: Ion beam irradiation configuration optimization method based on continuous preference value function

[0249] In this embodiment, the method of continuous preference value function is used to optimize ion beam irradiation. Compared with Example 1, this embodiment is the same as Example 1 in the steps of obtaining voxel feature information and final irradiation angle optimization. However, in order to further improve the accuracy of irradiation, this embodiment introduces the continuous preference value function to optimize the energy configuration more meticulously.

[0250] Step S4.1`: Obtain water equivalent range of target voxels. This step is consistent with Example 1. First, by discretizing the target region in three dimensions, the water equivalent range of each voxel is obtained. These information is used to guide the subsequent favor value calculation and energy optimization. In the final irradiation angle optimization step, by adjusting the irradiation angle, it is ensured that the increase value of the favor value of all target region voxels is maximized.

[0251] Step S4.2`: Obtain ion beam energy and depth dose distribution. For any energy E, obtain the integral depth dose curve of the ion beam at this energy in the water medium. This curve represents the energy deposition of ion beams at different energies in water, and is used to determine the energy acceptance of each voxel. In order to obtain the integral depth dose curve under different energy E, we usually use the following two methods: experimental measurement: using ion beam treatment system, ion beam is shot into a water phantom (usually called water tank) under simulated conditions. By setting ion beams of different energies, the energy deposition of ion beams at different depth positions in the water tank is measured using a detector. Through multiple measurements, the depth dose curve of different energies can be obtained. Or simulation calculation: using Monte Carlo simulation and other calculation methods, based on the interaction model of ion beam and matter, the energy deposition distribution of ion beam in water medium is calculated. Simulation calculation method can quickly obtain the depth dose curve under different energy, and can flexibly adjust the parameters under different conditions (such as different ion species or medium).

[0252] Step S4.3`: Define continuous favor value function. Based on the depth dose curve obtained in step S4.2`, a continuous favor value function fav(E) is defined for each voxel. This function is used to represent the acceptance of the voxel at different energy levels, with a value range of 0 to 1, and is defined as follows: fav(E), represents the energy acceptance of a specific voxel, with a value range of 0 to 1, the continuous favor value function is based on the water equivalent range of the voxel and the depth dose distribution of the ion beam energy, to calculate the acceptance of the voxel at different energies. The specific value depends on the relationship between the water equivalent range (WETv) of the voxel and the depth dose distribution of the ion beam energy E. When the water equivalent range (WETv) of the voxel coincides with the Bragg peak position of the ion beam at this energy, the favor value fav(E) is close to 1, indicating that the voxel can maximize the energy acceptance at this energy. If WETv does not coincide with the Bragg peak position, the favor value fav(E) will be lower, even close to 0, indicating that the energy acceptance of the voxel at this energy is low.

[0253] Step S4.4`: Accumulation and update of favor value. In the case of multi-angle irradiation, the cumulative favor value of each voxel is calculated

[0254] Where n: represents the number of irradiation angles that have been calculated. fav i (E): represents the favorability value function of the voxel at the i-th irradiation angle.

[0255] If the favorability value fav i (E) of the current angle is greater than the cumulative favorability value fav accum (E), then update the favorability value maximum as fav i (E) ensures that under the condition of multi-angle irradiation, the favorability value of the voxel can be effectively accumulated, and can reflect the comprehensive influence under multiple angles.

[0256] Here is a specific example to show how to accumulate and update the favorability value in actual operation.

[0257] Suppose we have a target voxel that receives ion beam treatment at three different irradiation angles. We use the favorability value functions at the three different angles to calculate the cumulative favorability value of the voxel.

[0258] Water equivalent range (WETv) of the voxel: 5 centimeters

[0259] Three irradiation angles of the ion beam: A1, A2, and A3

[0260] Favorability value functions at these angles:

[0261] fav1(E) (angle A1): 0.7

[0262] fav2(E) (angle A2): 0.5

[0263] fav3(E) (angle A3): 0.9

[0264] Step 1: Favorability value calculation in initial state

[0265] We start from the first angle to calculate the favorability value: the first angle A1: favorability value fav1(E) = 0.7 At this time, the cumulative favorability value is initially: fav accum (E) = fav1(E) = 0.7

[0266] Step 2: Favorability value accumulation at the second angle: the second angle A2: favorability value fav2(E) = 0.5 Use the formula to calculate the cumulative favorability value:

[0267] fav accum (E) = 1 - ((1 - 0.7) x (1 - 0.5)) = 0.85, which is higher than the previous favorability value fav1(E) = 0.7, so we will update the favorability value, maximum: fav accum (E) = 0.85.

[0268] Step 3: Accumulation and updating of the third angle's favor value: Third angle A3: Favor value fav3(E) = 0.9 is calculated using the formula to accumulate the favor value:

[0269] fav accum (E) = 1 - ((1 - 0.7) x (1 - 0.5) x (1 - 0.9)) = 0.985, which is higher than the current accumulated value of 0.9, we will update the favor value to 0.985: fav accum (E) = 0.985.

[0270] From this example, we can see how the favor value of a voxel is gradually accumulated and updated under multi-angle irradiation. In this case, although the accumulated value from the second angle's favor value calculation is low, by considering the third angle, we can update the accumulated favor value of the voxel to a higher value of 0.985. This process reflects the continuous optimization of the energy acceptance of the voxel through the updating mechanism during multi-angle irradiation, ultimately ensuring the best effect of the treatment.

[0271] Step S4.5`: Energy selection and optimization

[0272] 1. Setting of initial energy configuration

[0273] Before energy selection and optimization, an initial energy configuration needs to be set. This initial configuration can be based on the following sources: Experience value: Based on past treatment experience, a preliminary energy configuration that may be optimal is set. Previous optimization results: In repeated treatment processes, the energy configuration optimized previously can be used as the initial value. Random setting: In the absence of prior knowledge, a random energy configuration can be selected as the starting point.

[0274] 2. Definition and calculation of favor value increment Δfav(E) to measure the impact of the energy configuration on all voxels in the target region. Its formula is:

[0275] m: Total number of voxels in the target region. fav i (E)): Favor value of voxel i under new energy configuration E. currentfav i (E): Favor value of voxel i under the current energy configuration.

[0276] 3. Traversal and selection of energy configuration: In order to find the optimal energy configuration, all possible energy settings need to be traversed and the favor value increment Δfav(E) under each setting needs to be calculated.

[0277] 4. Iterative optimization process: In order to ensure that the selected energy configuration is globally optimal, not just locally optimal, an iterative optimization process is needed. The specific process is as follows:

[0278] Update energy configuration:

[0279] Using the optimal energy configuration found in the previous step, update the cumulative favor value for each voxel. Recalculate the favor increment for each voxel using the new cumulative favor value.

[0280] Repeat traversal and selection: Take the updated energy configuration as the new initial configuration and traverse all possible energy settings again to find a new optimal configuration.

[0281] Check termination condition: If the increment change of Δfav(E) is less than a preset threshold (e.g., 0.001) or the maximum number of iterations is reached, terminate the optimization process.

[0282] Otherwise, continue iteration until the globally optimal energy configuration is found.

[0283] Here's a specific example: Suppose we have a simple target region consisting of 3 voxels. We consider three possible energy configurations (E1, E2, E3) and have an initial energy configuration during the current treatment. Our goal is to maximize the favor increment for each voxel by selecting the optimal energy configuration.

[0284] Number of target region voxels: 3 voxels (V1, V2, V3)

[0285] Possible energy configurations: E1 = 100 MeV, E2 = 120 MeV, E3 = 140 MeV

[0286] Favor values under current energy configuration:

[0287] V1: 0.6

[0288] V2: 0.4

[0289] V3: 0.5

[0290] Step 1: Calculate favor increment for each energy configuration

[0291] We will calculate the favor increment for each voxel under energy configurations E1, E2, and E3, respectively, relative to the current configuration.

[0292] Energy configuration E1 = 100 MeV

[0293] V1: New favor value is 0.7, increment Δfav1(E1) = 0.7 - 0.6 = 0.1

[0294] V2: New favor value is 0.5, increment Δfav2(E1) = 0.5 - 0.4 = 0.1

[0295] V3: New favor value is 0.6, increment Δfav3(E1) = 0.6 - 0.5 = 0.1V3: new favour value is 0.6, increment Δfav3(E1) = 0.6 - 0.5 = 0.1

[0296] Total increment Δfav(E1) = Δfav1(E1) + Δfav2(E1) + Δfav3(E1) = 0.1 + 0.1 + 0.1 = 0.3

[0297] Energy configuration E2 = 120 MeV

[0298] V1: new favour value is 0.8, increment Δfav1(E2) = 0.8 - 0.6 = 0.2

[0299] V2: new favour value is 0.6, increment Δfav1(E2) = 0.6 - 0.4 = 0.2

[0300] V3: new favour value is 0.7, increment Δfav1(E2) = 0.7 - 0.5 = 0.2

[0301] Total increment Δfav(E2) = Δfav1(E2) + Δfav2(E2) + Δfav3(E2) = 0.2 + 0.2 + 0.2 = 0.6

[0302] Energy configuration E3 = 140 MeV

[0303] V1: new favour value is 0.75, increment Δfav1(E3) = 0.75 - 0.6 = 0.15

[0304] V2: new favour value is 0.55, increment Δfav2(E3) = 0.55 - 0.4 = 0.15

[0305] V3: new favour value is 0.65, increment Δfav3(E3) = 0.65 - 0.5 = 0.15

[0306] Total increment Δfav1(E3) = Δfav1(E3) + Δfav2(E3) + Δfav3(E3) = 0.15 + 0.15 + 0.15 = 0.45

[0307] Select optimal energy configuration

[0308] Δfav(E1) = 0.3 Δfav(E2) = 0.6 Δfav(E3) = 0.45

[0309] The total favour value increment is largest for energy configuration E2 = 120 MeV (Δfav(E2) = 0.6). Therefore, we select E2 as the current optimal energy configuration.

[0310] Step S4.6`: Iterative optimisation

[0311] Iterative optimization finds the optimal energy configuration for each irradiation angle by repeating calculation and updating, maximizing the preference value increment of voxels within the target region. The specific steps are as follows:

[0312] Initialization settings:

[0313] Set the initial energy configuration and irradiation angle.

[0314] Set the initial preference value of each voxel to zero.

[0315] Initial calculation:

[0316] Calculate the preference value of each voxel according to the initial settings.

[0317] Record the current preference value and increment.

[0318] Iterative calculation:

[0319] For each irradiation angle, traverse all potential energy configurations.

[0320] Select the energy configuration that maximizes the preference value increment as the temporary optimal configuration.

[0321] Update the preference value:

[0322] Compare the current preference value of each voxel with the historical maximum value, and update the maximum preference value and the corresponding configuration.

[0323] Check the convergence condition:

[0324] If the preference value change is less than the preset threshold, end the iteration and determine the optimal configuration.

[0325] If the condition is not met, continue the iteration.

[0326] Output the optimal configuration:

[0327] Output the optimal energy configuration of each irradiation angle and the final preference value of the voxel.

[0328] Example 3: Method of quality assessment and weighting of irradiation angles

[0329] In Example 1, step S3 sets multiple irradiation angles to cover different regions of the target region. By evaluating the irradiation quality of each angle and assigning weights to each angle based on factors such as effective projection area and protection coefficient, the selection of these angles can be more accurately optimized, making the final energy configuration more reasonable and ensuring maximum treatment effect.

[0330] 1. Quality assessment of irradiation angles

[0331] To scientifically select the optimal irradiation angle, it is necessary to first evaluate the quality of each set irradiation angle. The core of quality evaluation is to calculate the effective projection area under each irradiation angle. The specific steps are as follows:

[0332] Three-dimensional reconstruction and boundary determination:

[0333] Accurate three-dimensional reconstruction of the target area, based on three-dimensional image data to construct a three-dimensional model of the target area. Through the model, the shape, size and position of the target area in the patient's body can be accurately determined. According to the three-dimensional model, the boundary surface of the target area is determined. Ion beam extension and protection coefficient distribution:

[0334] After determining the three-dimensional model and boundary of the target area, simulate the ion beam along each predetermined irradiation angle to the target area. The ion beam continues to extend backward after passing through the target area, forming a column with an equivalent water range. In order to protect the healthy tissue around the target area, the protection area overlapping with the target area in the column needs to be assigned a protection coefficient p i , where 0 i < 1, where 0 i < 1. The protection coefficient p i reflects the sensitivity of each protection area to the ion beam and the need for protection. The greater the protection coefficient, the more protection is needed in that area, and the energy configuration of the ion beam at that angle should be reduced accordingly.

[0335] Projection area calculation:

[0336] For each irradiation angle, calculate the projection area T of the target area, which is the area of the target area projected onto the column cross section at that angle. At the same time, calculate the projection area Q i of each protection area overlapping with the target area. These projection areas are calculated according to the geometric overlapping relationship between the protection area and the target area in the column. Combined with the protection coefficient p i , calculate the effective projection area of each irradiation angle. The effective projection area reflects the actual benefit area of the target area at that angle after considering the protection area. The calculation formula is as follows: effective projection area A j , where n is the number of protection areas overlapping with the target area in the column.

[0337] 2. Distribution of irradiation weight

[0338] After obtaining the effective projection area of each irradiation angle, the next step is to assign the corresponding irradiation weight to each angle. The irradiation weight reflects the relative importance of each angle in the overall treatment plan and directly affects the energy layer distribution at that angle. The specific steps are as follows:

[0339] Weight calculation:

[0340] For each irradiation angle, its irradiation weight is calculated according to its effective projection area. The formula for calculating the irradiation weight is:

[0341] The irradiation weight is assigned according to the irradiation quality index Aj of each irradiation angle, where n is the total number of irradiation angles. The calculation of the irradiation weight ensures that in the overall treatment plan, the contribution of each angle matches its quality. The higher the weight of an angle, the better its irradiation effect in the target area, and more energy layers should be allocated.

[0342] Energy layer allocation:

[0343] Based on the weight of each irradiation angle, the number of energy layers required at that angle is determined. Specifically, the higher the weight of an angle, the more energy layers it will be allocated to, to ensure that high-quality irradiation at that angle is fully utilized.

[0344] When allocating energy layers, it is also necessary to ensure that the total number of energy layers does not exceed the preset maximum value, so as to balance the treatment effect and the protection needs of healthy tissues.

[0345] Here is a specific example: Suppose there is a simple target area that needs to be treated by ion beam. After three-dimensional reconstruction and boundary determination, we set three main irradiation angles (angle A, angle B and angle C), which cover the target area from different directions. In order to ensure the treatment effect and the protection of healthy tissues, we need to evaluate the quality of these angles and assign irradiation weights.

[0346] Step 1: Three-dimensional reconstruction and boundary determination

[0347] Suppose through three-dimensional scanning and reconstruction, the shape and boundary of the target area have been determined. We set three main irradiation angles: A, B, C.

[0348] Step 2: Ion beam extension and protection coefficient allocationSimulate the ion beam from the three angles to the target area, and form a column with an equivalent water range at each angle.

[0349] In the column, the protection areas overlapping with the target area are set with protection coefficients p1, p2, p3, respectively, assuming the protection coefficients are 0.2, 0.5 and 0.8. The larger the protection coefficient, the more sensitive the area and the higher the protection demand.

[0350] Step 3: Projection area calculation

[0351] For angle A, suppose the projection area of the target area TA=100 square millimeters, and the projection areas of the protection areas are Q1=20 square millimeters, Q2=15 square millimeters, Q3=10 square millimeters. The formula for calculating the effective projection area is:

[0352] Effective projection area A = TA - (Q1 x p1 + Q2 x p2 + Q3 x p3) After substituting the data: Effective projection area A = 100 - (20 x 0.2 + 15 x 0.5 + 10 x 0.8) = 80.5 square millimeters. Similarly, for angle B and angle C, assuming the calculated effective projection areas are effective projection area B = 70.0 square millimeters and effective projection area C = 60.0 square millimeters, respectively.

[0353] Step 4: Distribution of irradiation weight

[0354] Calculate the irradiation weight of each angle. The total effective projection area is 80.5 + 70.0 + 60.0 = 210.5 square millimeters.

[0355] The irradiation weight of angle A is: 80.5 ÷ 210.5 ≈ 0.383; the irradiation weight of angle B is: 70.0 ÷ 210.5 ≈ 0.333; and the irradiation weight of angle C is: 60.0 ÷ 210.5 ≈ 0.28. Assuming the total number of energy layers is 100, then the number of energy layers allocated to angle A is: energy layers A = 100 x 0.383 ≈ 38 layers. Similarly, the number of energy layers for angles B and C are 33 layers and 29 layers, respectively.

[0356] Example 4: Irradiation angle discretization and priority calculation method

[0357] In step S3 of Example 1, in order to ensure that the ion beam energy can fully cover the target area and reduce damage to normal tissues, we set multiple irradiation angles. Through the preliminary setting of multiple angles, we can achieve reasonable distribution of energy in different areas of the target area. However, in order to further optimize the selection of these angles and ensure the best treatment effect, this embodiment proposes a method of irradiation angle discretization and priority calculation. This method further improves the setting effect in step S3 by scientifically analyzing and selecting the combination of irradiation angles.

[0358] 1. Range division of irradiation angles

[0359] First, we uniformly divide the available irradiation angle range. Irradiation angles usually expand in the horizontal and vertical directions. In order to ensure the uniformity and coverage of irradiation, these angle ranges are divided into several subintervals. Horizontal angle range division: In the horizontal plane, the variable angle range (such as 360 degrees) is uniformly divided into 36 equally spaced subintervals, each with a 10-degree interval. Vertical angle range division: In the vertical plane, the variable angle range (such as 180 degrees) is uniformly divided into 18 equally spaced subintervals, each with a 10-degree interval.

[0360] 2. Selection of candidate irradiation angles

[0361] In each divided sub-interval, the center point of the interval is selected as the candidate irradiation angle. The selection of these center points ensures the uniform distribution of angles.

[0362] Determination of candidate angles: For example, in the horizontal angle [10°, 20°] sub-interval, 15° is selected as the candidate angle of the interval; in the vertical angle [10°, 20°] sub-interval, 15° is also selected as the candidate angle. Through this division and selection, a number of candidate irradiation angles in three-dimensional space are generated.

[0363] 3. Calculation of irradiation priority

[0364] In order to select the optimal angle combination from these candidate angles, we next perform priority calculation for each candidate irradiation angle. The priority calculation is based on the following evaluation factors:

[0365] Target area coverage (C) Target area coverage (Coverage, C) is an evaluation of the coverage of the target area by the candidate irradiation angle. The higher the value of C, the more comprehensive the coverage of the target area by the irradiation angle. The value of C ranges from 0 to 1, with 1 representing complete coverage and 0 representing no coverage.

[0366] Normal tissue impact (N) Normal tissue impact (Normal tissue impact, N) is an evaluation of the impact of the candidate irradiation angle on the surrounding normal tissue. The higher the value of N, the greater the impact of the irradiation angle on the normal tissue. In order to optimize treatment effectiveness and protect normal tissue, we use (1-N) in the formula, i.e. the larger N is, the smaller (1-N) is, thereby reducing the priority of the angle. The value of N ranges from 0 to 1, with 1 representing maximum impact and 0 representing minimum impact.

[0367] Path length (L) Path length (Length, L) is an evaluation of the path length of the ion beam from the emission source to the target area. The higher the value of L, the longer the path, and the greater the possible energy loss and deviation. In order to optimize energy delivery, we use (1-L) in the formula, i.e. the larger L is, the smaller (1-L) is, thereby reducing the priority of the angle. The value of L ranges from 0 to 1, with 1 representing the longest path and 0 representing the shortest path.

[0368] Normalization In order to ensure the comparability of the evaluation factors in different ranges, the values of C, N, and L need to be normalized to the [0, 1] interval. The purpose of normalization is to make the value ranges of different evaluation factors consistent, thereby enabling fair comparison and weighted calculation.

[0369] w1xC: represents the contribution of target area coverage to the priority score, with the weight w1 adjusting its importance.

[0370] w2 x (1 - N): represents the inverse contribution of normal tissue impact to the priority score, with weight w2 adjusting its importance. The larger N is, the smaller (1 - N) is, and the lower the priority score is, reflecting the importance of normal tissue protection.

[0371] W3 x (1 - L): represents the inverse contribution of path length to the priority score, with weight w3 adjusting its importance. The larger L is, the smaller (1 - L) is, and the lower the priority score is, reflecting the importance of shorter path for energy delivery optimization.

[0372] The formula for calculating the priority score is: Score = w1 x C + w2 x (1 - N) + w3 x (1 - L) where the weight coefficients w1, w2, w3 are used to adjust the relative importance of each evaluation factor in the total priority score. C, N, L are all normalized to the [0, 1] interval to ensure the comparability of different factors.

[0373] 4. Angle selection

[0374] After calculating the priority scores of all candidate angles, we sort them from high to low according to the scores and select the top priority angle combination as the final irradiation angle combination. This combination optimization process aims to maximize the treatment effect while minimizing the damage to normal tissue.

[0375] Here is a specific example: suppose the target area needs to be treated with ion beam therapy, and the treatment range involves a horizontal angle of 360 degrees and a vertical angle of 180 degrees. We evenly divide these angles into subintervals of 10 degrees each:

[0376] Horizontal angle range: [0°, 360°], a total of 36 subintervals, each 10°.

[0377] Vertical angle range: [0°, 180°], a total of 18 subintervals, each 10°.

[0378] Candidate angle selection selects the center point of each subinterval as the candidate angle. For example, the combination of horizontal angle [10°, 20°] and vertical angle [10°, 20°], the candidate angle is (15°, 15°).

[0379] Priority calculation

[0380] Suppose the evaluation results of a certain candidate angle (15°, 15°) are as follows:

[0381] Target area coverage C: 0.85, weight w1 is 0.5

[0382] Normal tissue impact N: 0.4, weight w 2 is 0.3

[0383] Path length L: 0.2, weight w3 0.2

[0384] The formula for calculating the priority score is:

[0385] Score = 0.5 x 0.85 + 0.3 x (1-0.4) + 0.2 x (1-0.2) = 0.765

[0386] Angle selection

[0387] After calculating the priority scores for all candidate angles, we select the top priority angles as the final irradiation angle combination for treatment planning.

[0388] Example 5: Identification of key voxels and energy optimization method

[0389] Based on step S4 of Example 1, different voxels within the target region contribute differently to the overall treatment effect. Some voxels may play a more critical role in the treatment effect, so optimizing the energy allocation for these voxels can further improve the accuracy and effectiveness of treatment.

[0390] 1. Three-dimensional discretization processing: First, perform three-dimensional discretization processing on the target region. Assume that the target region is divided into 1000 voxels, each representing a cubic unit with a size of 1 cubic millimeter. These voxels form a three-dimensional grid covering the entire tumor area.

[0391] 2. Calculation of energy matrix: For each voxel, calculate the water equivalent range and required ion beam energy at the preset 5 irradiation angles (e.g., 0°, 45°, 90°, 135°, 180°). Assume that we calculate the energy matrix for a certain voxel (voxel number 123) as follows:

[0392] 3. Determination of preference value matrix: Based on the energy matrix, calculate the preference value for each voxel. Assume that the calculation of the preference value takes into account the energy requirements of the voxel at different angles and its position within the target region. The preference value matrix for voxel 123 may be as follows:

[0393] The higher the preference value, the better the voxel's acceptance of energy at that angle.

[0394] 4. Impact degree assessment By analyzing the preference value of each voxel, assess its impact on the overall irradiation planning. Assume that the comprehensive impact degree of voxel 123 at all angles is 0.9, which means it has an important impact on the treatment effect and should be identified as a key voxel.

[0395] 5. Selection of key voxels: From the 1000 voxels, the 50 voxels with the highest impact degree values are selected as key voxels. Suppose voxel 123 is one of them.

[0396] 6. Energy optimization of key voxels: Energy optimization is performed on the selected key voxels. Specifically, for voxel 123, the preference value at the irradiation angle of 180° is the highest, so more energy layers are allocated to this angle to ensure that voxel 123 can obtain the best energy coverage.

[0397] Before optimization: The energy allocated to each angle is 150 MeV, distributed uniformly.

[0398] After optimization: The energy at angle 180° is increased to 180 MeV, while the energy at other angles is correspondingly reduced to optimize the treatment effect of voxel 123.

[0399] 7. Result analysis: By identifying and optimizing key voxels, the entire treatment plan is significantly optimized. Key voxel 123 obtains better energy coverage, thereby improving the treatment effect of the target area while minimizing the impact on healthy tissues.

[0400] Example 6: Structure and function of ion beam emission system

[0401] During the ion beam treatment process, the structure and function of the ion beam emission system are crucial for achieving efficient and precise treatment. This embodiment describes an ion beam emission system that integrates multiple functional modules, which can achieve multi-angle and multi-level precise irradiation in the target area, thereby optimizing the treatment effect and maximizing the protection of healthy tissues.

[0402] 1. Design and operation of a liftable and rotatable chair device

[0403] This system includes a liftable and rotatable chair device. During operation, the device follows a set sinusoidal curve to rise and fall vertically, and can rotate at least two circles.

[0404] Lifting function of the chair: Through the electric lifting device, the chair can be accurately adjusted in the vertical direction to adjust the height of the patient's body, ensuring that the ion beam can be precisely irradiated from different angles.

[0405] Rotating function of the chair: The chair can rotate multiple circles, and the second circle starting position is designed to have a 180-degree phase difference in height from the first circle starting position. This design ensures that the ion beam can be irradiated at different angles to the target area without moving the patient, achieving omnidirectional irradiation.

[0406] 2. Ion beam emission unit and its magnetic field deflection device

[0407] The system is equipped with an ion beam emitting unit, which contains a magnetic field deflection device. This device is used to deflect the ion beam directly towards the target area through the magnetic field when the target area deviates from the isocenter, thereby achieving non-coplanar irradiation.

[0408] Magnetic field deflection function: The magnetic field deflection device can accurately control the direction of the ion beam, allowing flexible adjustment of the irradiation angle, especially suitable for non-coplanar irradiation requirements of complex target areas.

[0409] Configuration of the emitting unit: The ion beam emitting unit can emit appropriate ion beam energy according to the preset irradiation angle and energy parameters, thereby achieving accurate irradiation of the target area.

[0410] 3. Functions and interactions of system modules

[0411] The system contains multiple functional modules, which work together to ensure the efficiency and accuracy of ion beam therapy.

[0412] Three-dimensional scanning acquisition module: This module is used to acquire three-dimensional image data of the target area and define the target area to be processed. The accurate acquisition of data provides a basis for subsequent irradiation angle setting and energy optimization.

[0413] Irradiation angle setting module: Set multiple irradiation angles according to different treatment needs, combined with the angle discretization method in embodiment 8, ensure that the angle selection can cover the target area and reduce damage to normal tissues.

[0414] Energy parameter evaluation and selection module: Based on the maximum preference value increase of all voxels in the target area, the energy parameters are evaluated and selected to ensure the optimal energy allocation for each irradiation angle.

[0415] Voxel feature information acquisition module: This module acquires the water equivalent range of the voxels in the target area and performs three-dimensional discretization processing on the region to be processed, providing data support for subsequent preference value and energy matrix calculation.

[0416] Relative stopping power calculation module: For each predetermined irradiation angle, the stopping power of the ray path from the ion beam emitting source to the center of each voxel is calculated to help determine the optimal energy configuration.

[0417] Voxel angle range matrix construction module: Based on the line integral method, the water equivalent range of each voxel under different irradiation angles is calculated and summarized to form a voxel angle range matrix, providing a basis for energy optimization.

[0418] Preference value function setting and optimization module: Set the preference value function for each voxel and use the discrete preference value function for optimization calculation to determine the optimal ion beam energy configuration under each irradiation angle.

[0419] Embodiment 7: Implementation of computer storage medium

[0420] During the ion beam treatment process, the control and management of the computer system are crucial to ensure the accuracy and efficiency of the treatment. This embodiment describes an implementation of a computer storage medium, which stores instructions for performing an ion beam irradiation configuration optimization method, capable of automating and intelligently completing the entire treatment process.

[0421] 1. Types and characteristics of computer storage medium

[0422] The computer storage medium can be various types of physical media for storing computer program instructions. Common storage media include, but are not limited to: Hard Disk Drive (HDD): used for storing large amounts of data, suitable for long-term storage and high-frequency read-write operations. Solid State Drive (SSD): fast, suitable for scenarios requiring efficient data access. Optical disc (CD / DVD): suitable for storing standardized data that needs to be stored for a long time. Flash drive (USB): portable, suitable for data transfer and temporary storage. Cloud storage: network-based storage solution, convenient for cross-platform access and data sharing.

[0423] 2. Storage and execution of instructions

[0424] The storage medium stores a series of instructions that enable the computer system to perform the ion beam irradiation configuration optimization method. These instructions typically include the functions of the following modules:

[0425] Three-dimensional scanning and data processing instructions: obtain three-dimensional image data of the target area and process these data to generate accurate three-dimensional models. These models will serve as the basis for subsequent calculations.

[0426] Irradiation angle setting instructions: automatically generate and optimize multiple irradiation angle combinations based on input treatment requirements. These instructions will combine the irradiation angle discretization and priority calculation methods in Embodiment 8 to ensure the scientificity and rationality of angle selection.

[0427] Energy parameter calculation and optimization instructions: automatically calculate and optimize energy distribution at each irradiation angle. Instructions will combine the key voxel identification and energy optimization methods in Embodiment 9 to ensure that the most important areas within the target area receive optimal energy coverage.

[0428] Preference value and energy matrix construction instructions: set preference value functions for each voxel, construct energy matrices, and determine the optimal ion beam energy configuration through calculations.

[0429] Ion beam emission system control instructions: control various modules of the ion beam emission system, including the liftable rotating chair, magnetic field deflection device, etc., to ensure that the ion beam can accurately hit the target area according to the set scheme.

[0430] 3. System implementation and execution process

[0431] Once the computer system is started and the instructions on the storage medium are loaded, the entire treatment process will be automatically executed, with the following specific steps:

[0432] Data acquisition and model establishment: Through the three-dimensional scanning module, image data of the target area is acquired, and a three-dimensional model is generated.

[0433] Irradiation angle setting: The system generates a preliminary combination of irradiation angles according to preset rules and input parameters, and optimizes the angle selection through priority calculation.

[0434] Energy optimization and configuration: Combined with the preference value and the analysis results of key voxels, the system calculates the energy configuration under each irradiation angle and optimizes the adjustment.

[0435] System control and execution: Finally, the system accurately executes the set irradiation scheme through the emission control module, ensuring that the energy distribution in the target area achieves the best effect.

[0436] 4. Result monitoring and feedback

[0437] During the entire treatment process, the system also monitors various parameters in real time and fine-tunes the irradiation scheme according to actual conditions. This function ensures the flexibility and safety of treatment, and also records treatment data in the computer storage medium for subsequent analysis and reference.

[0438] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, and are not limited thereto; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or make equivalent replacements to some technical features; and these modifications or replacements do not cause the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

The application discloses an ion beam irradiation configuration optimization method. Three-dimensional image data of the target region is obtained by three-dimensional scanning of the target region. A target area definition is performed on the region needing to be irradiated by an ion beam according to the three-dimensional image data. A plurality of irradiation angles for the target area are set. For each set irradiation angle, an energy parameter is evaluated and selected to maximize the increase of the preference value of all voxels in the target area, wherein the preference value is obtained based on a function relationship between the required ion beam energy of each voxel and the water equivalent range thereof, so as to determine the required energy of the ion beam emitted at each irradiation angle. According to the ion beam irradiation configuration optimization method of claim 1, wherein the function relationship between the required ion beam energy of each voxel and the water equivalent range thereof comprises: The water equivalent range of the target area voxel is obtained by three-dimensional discretization processing of the target region to be processed, and the target region to be processed is divided into a plurality of cubic voxels; and for each predetermined irradiation angle, a ray emitted from an ion beam emission source to the center of each voxel is calculated to obtain the path from the ray source to the center of each voxel. The relative stopping power is calculated by comparing the material composition and density of the position of each point on the ray path with water to calculate the relative stopping power of the ion beam at the point. The voxel angle range matrix is constructed by calculating the total relative stopping power on each ray path by the line integral method to determine the water equivalent range of each voxel, and the water equivalent ranges of the voxels under different irradiation angles are summarized to form the voxel angle range matrix. Based on the water equivalent range information of the voxels, a preference value function is set for each voxel, which describes the preference degree of the voxel to different ion beam energies, and the ion beam energy under each irradiation angle is optimized to maximize the increase of the preference value of the whole target area voxel, and the specific method comprises: The ion beam irradiation configuration optimization method according to claim 2, characterized in that: The preference value is calculated based on the preference value function and the preset ion beam incident energy to calculate the preference value of each target area voxel; The historical maximum preference value of all voxels is set as an initial value; The current preference value of each voxel is calculated by using the preference value function and the selected incident energy for each irradiation angle, and the current preference value is compared with the historical maximum preference value recorded by the voxel, if the current calculated value is greater, the value is updated as the new historical maximum preference value, and the increase value is calculated; The energy selection and optimization are performed by traversing all potential ion beam energy settings to select an energy configuration which can maximize the increase of the preference value of all target area voxels; The iteration optimization is repeated until the maximization of the increase of the preference value of all voxels is realized. The irradiation optimization is performed by using the discrete preference value function, and the specific steps comprise the following steps: The ion beam irradiation configuration optimization method according to claim 3, characterized in that: The voxel feature information is obtained according to the voxel angle range matrix, and the water equivalent range WETv of each voxel is obtained. ​ Bragg peak coverage area determination: for any energy E, determine the Bragg peak coverage area of the ion beam at this energy; define a discrete favorability function: define a discrete favorability function fav(E) for each voxel, fav(E) takes value 1 when the water equivalent range WETv of the voxel is within the Bragg peak coverage area of the ion beam at energy E, otherwise fav(E) takes value 0; Maximum of the favorability values and update: for each voxel, in the case of multiple angles of illumination, the maximum of its favorability values, fav max (E) is calculated, this value taking the maximum of the favorability values equal to 1 among the calculated angles; Energy selection and optimization: use the discrete favorability function to optimize the required ion beam energy configuration at each irradiation angle to ensure that the increase in favorability value of all target region voxels reaches the maximum. The ion beam irradiation configuration optimization method according to claim 3, characterized in that: The irradiation optimization using the continuous favorability function includes the following steps: Obtain voxel feature information: obtain the water equivalent range WETv of each voxel according to the voxel angle range matrix; obtain the ion beam energy and depth dose distribution: obtain the integral depth dose curve of the ion beam in the water medium at any energy E; Define a continuous favorability function: define a continuous favorability function fav(E) for each voxel according to the depth dose curve, which represents the energy acceptance degree of a specific voxel, with a value range of 0 to 1. The continuous favorability function is based on the water equivalent range of the voxel and the depth dose distribution of the ion beam energy to calculate the acceptance degree of the voxel at different energies; Cumulative and update of favorability: for each voxel, under the condition of multi-angle irradiation, calculate its cumulative favorability, fav accum (E), in particular as follows: where fav'(E) is the favor value function of the voxel in the calculated angles, n represents the number of calculated angles, and if the current angle fav(E) is greater than fav accum (E), the maximum favor value is updated to fav(E); Energy selection and optimization: use the continuous favorability function to optimize the required ion beam energy configuration at each irradiation angle to ensure that the increase in favorability value of all target region voxels reaches the maximum. The ion beam irradiation configuration optimization method according to claim 1, characterized in that: Further comprising the steps of quality assessment and weighting of irradiation angles, the specific steps are as follows: Three-dimensional reconstruction and boundary determination: first, three-dimensional reconstruction is performed on the target region, and the boundary surface is determined based on its shape and position; Ion beam extension: the ion beam is directed to the target region and extends backward to form a column of equivalent water range with an additional depth; Protection coefficient assignment: In the cylinder, a protection coefficient p is assigned to each protection region which overlaps with the target region i where 0 < p i < 1; Projection area calculation: The projection of the protected area and the target volume in the cross section of the cylinder is calculated and from this the effective projection area A for each irradiation angle is derived j , where T is the projected area of the target volume, Q i is the projected area of the overlap of the protection region i with the target volume, p i is the protection coefficient of the protection region i, and n is the number of protection regions in the cylinder that overlap with the target volume. Distribution of the illumination weight: according to the illumination quality indicator A for each illumination angle j Using the formula Assign irradiation weight, where n is the total number of irradiation angles. The ion beam irradiation configuration optimization method according to claim 6, characterized in that: According to the irradiation weight of each irradiation angle, determine the number of energy layers of the ion beam emitted at each irradiation angle, so that the irradiation angle with higher irradiation weight has more energy layers; wherein, the step of determining the number of energy layers of the ion beam emitted at each irradiation angle includes: for each irradiation angle, according to its irradiation weight, calculate the proportion of the total number of energy layers it occupies; for each irradiation angle, according to the proportion of the total number of energy layers it occupies, allocate the number of energy layers of the ion beam it emits, so that the total number of energy layers does not exceed the preset maximum value. The ion beam irradiation configuration optimization method according to claim 6, characterized in that: The step of discretizing the irradiation angles, specifically includes the following steps: Divide the entire available irradiation angle range into multiple equally spaced subintervals in the horizontal and / or vertical directions; In each subinterval, select the center point of the interval as a candidate irradiation angle; For each candidate irradiation angle, calculate its irradiation priority based on the number of intersection points at that angle and the path distance of the ion beam to the target region; From all candidate irradiation angles, the angle with the highest priority is selected as the irradiation angle to be used in the actual irradiation plan according to the calculated priority. The ion beam irradiation configuration optimization method according to claim 1, wherein: The step of finding a plurality of key voxels by a discretization method comprises: Three-dimensional discretization processing: performing three-dimensional discretization on the target region to be treated to divide the target region into a plurality of cubic voxels; Energy matrix calculation: for each voxel, the energy of the required ion beam is calculated based on the water equivalent range thereof at each predetermined irradiation angle, and an energy matrix is constructed; Preference value matrix determination: using the data in the energy matrix, a preference value is set for each voxel to generate a preference value matrix; Influence degree evaluation: analyzing the numerical value of each voxel in the preference value matrix to evaluate the influence degree of the voxel on the overall irradiation plan and assigning an influence degree value to the voxel; Key voxel selection: selecting a plurality of voxels with the highest influence degree according to the influence degree values, and identifying these voxels as key voxels. Ion beam emission system using the ion beam irradiation configuration optimization method according to any one of claims 1 to 9, characterized in that It comprises: A seat device capable of vertical up-and-down lifting and rotation, which can be lifted up and down in a sinusoidal manner during operation and can complete at least two rotations, wherein the height sinusoidal phase of the starting position of the second rotation is 180 degrees different from that of the first rotation; An ion beam emitting unit equipped with a magnetic field deflection device for deflecting the ion beam directly to the target area when the target area deviates from the isocenter, thereby realizing non-coplanar irradiation; The system realizes multi-angle and multi-level irradiation of the target area by adjusting the rotation angle and height of the rotating seat and the ion beam deflection direction of the ion beam emitting unit, optimizes the irradiation effect, and reduces the impact on the surrounding normal tissues; The ion therapy system further comprises the following modules: a. A three-dimensional scanning acquisition module for acquiring three-dimensional image data of the target region and defining the target area to be processed; b. An irradiation angle setting module for setting a plurality of irradiation angles according to different treatment requirements; c. An energy parameter evaluation and selection module for evaluating and selecting energy parameters based on the maximum preference value increase of all voxels in the target area; d. A voxel feature information acquisition module for acquiring the water equivalent range of the voxels in the target area and performing three-dimensional discretization processing on the target area to be processed; e. A relative stopping power calculation module for calculating the stopping power of the ray path from the ion beam emitting source to the center of each voxel at each predetermined irradiation angle; f. A voxel angle range matrix construction module for calculating and summarizing the water equivalent ranges of each voxel at different irradiation angles based on the line integral method to form a voxel angle range matrix; g. A preference value function setting and optimization module for setting a preference value function for each voxel and performing optimization calculation using the discrete preference value function to determine the optimal ion beam energy configuration at each irradiation angle. The instructions are used to enable the computer to perform the ion beam irradiation configuration optimization method of any one of claims 1 to 9. A computer storage medium having stored thereon instructions, characterized in that, ​

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