WO2024099385A1 - 治疗计划系统、重叠自动检查方法及治疗计划的制定方法 - Google Patents

治疗计划系统、重叠自动检查方法及治疗计划的制定方法 Download PDF

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WO2024099385A1
WO2024099385A1 PCT/CN2023/130654 CN2023130654W WO2024099385A1 WO 2024099385 A1 WO2024099385 A1 WO 2024099385A1 CN 2023130654 W CN2023130654 W CN 2023130654W WO 2024099385 A1 WO2024099385 A1 WO 2024099385A1
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beam source
model
overlap
reference object
type
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English (en)
French (fr)
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钟万兵
陈江
邓逸樵
姜炳旭
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Neuboron Therapy System Ltd
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Neuboron Therapy System Ltd
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Priority to EP23888070.2A priority Critical patent/EP4491221A4/en
Priority to JP2025525075A priority patent/JP2026513118A/ja
Publication of WO2024099385A1 publication Critical patent/WO2024099385A1/zh
Priority to US18/941,359 priority patent/US20250065151A1/en
Anticipated expiration legal-status Critical
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N5/00—Radiation therapy
    • A61N5/10—X-ray therapy; Gamma-ray therapy; Particle-irradiation therapy
    • A61N5/1001—X-ray therapy; Gamma-ray therapy; Particle-irradiation therapy using radiation sources introduced into or applied onto the body; brachytherapy
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N5/00—Radiation therapy
    • A61N5/10—X-ray therapy; Gamma-ray therapy; Particle-irradiation therapy
    • A61N5/103—Treatment planning systems
    • A61N5/1039—Treatment planning systems using functional images, e.g. PET or MRI
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N5/00—Radiation therapy
    • A61N5/10—X-ray therapy; Gamma-ray therapy; Particle-irradiation therapy
    • A61N5/103—Treatment planning systems
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N5/00—Radiation therapy
    • A61N5/10—X-ray therapy; Gamma-ray therapy; Particle-irradiation therapy
    • A61N5/1048—Monitoring, verifying, controlling systems and methods
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00—Three-dimensional [3D] modelling for computer graphics
    • G06T17/20—Finite element generation, e.g. wire-frame surface description, tesselation
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0012—Biomedical image inspection
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/70—Determining position or orientation of objects or cameras
    • G06T7/73—Determining position or orientation of objects or cameras using feature-based methods
    • G06T7/75—Determining position or orientation of objects or cameras using feature-based methods involving models
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/40—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H30/00—ICT specially adapted for the handling or processing of medical images
    • G16H30/40—ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/50—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N5/00—Radiation therapy
    • A61N5/10—X-ray therapy; Gamma-ray therapy; Particle-irradiation therapy
    • A61N2005/1085—X-ray therapy; Gamma-ray therapy; Particle-irradiation therapy characterised by the type of particles applied to the patient
    • A61N2005/109—Neutrons
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2200/00—Indexing scheme for image data processing or generation, in general
    • G06T2200/04—Indexing scheme for image data processing or generation, in general involving 3D image data
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2210/00—Indexing scheme for image generation or computer graphics
    • G06T2210/41—Medical

Definitions

  • the present application relates to the technical field of treatment planning, and in particular to a treatment planning system, an automatic overlap checking method, and a method for formulating a treatment plan.
  • Radiotherapy is a local treatment method using radiation therapy and is also an important means of cancer treatment.
  • radiation therapy such as cobalt-60, linear accelerator, and electron beam has become one of the main means of cancer treatment.
  • traditional photon or electron therapy is limited by the physical conditions of the radiation itself. While killing tumor cells, it will also cause damage to a large number of normal tissues in the beam path; in addition, due to the different sensitivity of tumor cells to radiation, traditional radiotherapy is often not effective for malignant tumors that are more resistant to radiation (such as glioblastoma multiforme and melanoma).
  • neutron capture therapy is a combination of the above two concepts, such as Boron Neutron Capture Therapy (BNCT), which provides a better cancer treatment option than traditional radiation by specifically gathering boron-containing drugs in tumor cells and combining them with precise beam control.
  • BNCT Boron Neutron Capture Therapy
  • physicists need to estimate the treatment effect and determine the treatment process. This process is the process of formulating a radiotherapy treatment plan.
  • the collimator outlet is usually set close to the tumor.
  • the collimator can guide the radiation particles to move in the direction of the outlet, thereby ensuring that most of the radiation particles are shot at the tumor and protecting other normal human tissue.
  • human tissue and the collimator entity are not allowed to overlap, otherwise it is difficult to position the patient to the treatment parameter position. If the collimator only overlaps with the air part in the voxel grid, or the treatment part that is more prominent on the human surface can extend into the internal space of the collimator, these situations are acceptable.
  • the physicist needs to judge whether the human tissue overlaps with the collimator. If the overlap is found in the actual treatment, such as after the dose calculation is completed or even when the positioning is found, the treatment will not proceed smoothly.
  • the present invention provides a treatment planning system, comprising:
  • An image processing module used for acquiring medical image data of an irradiated body, and establishing a three-dimensional voxel model of the irradiated body based on the medical image data, wherein the three-dimensional voxel model of the irradiated body includes a plurality of voxel grids;
  • a data processing module used for acquiring a beam source model and determining position parameters of the beam source model and a three-dimensional voxel model of the irradiated body
  • An overlap detection module used to determine the positional relationship between the voxel grid and the beam source
  • the treatment plan generation module is used to generate a treatment plan.
  • the treatment planning system obtains information such as the voxel grid of the irradiated body three-dimensional voxel model, the beam source model and the position parameters of the irradiated body three-dimensional voxel model by setting an image processing module, a data processing module, an overlap detection module and a treatment plan generation module, and then uses the overlap detection module to determine whether the irradiated body three-dimensional voxel model and the beam source model overlap and are reasonable, thereby determining whether the collimator and the patient's tissue overlap and are reasonable under the treatment plan, and checking whether the treatment plan will cause the collimator and the patient's tissue to collide during positioning. All processes can be automatically checked and judged by the treatment planning system, thereby providing guidance to the physicist in advance, so that the physicist can correct the treatment plan more quickly, and the treatment planning system can automatically generate a corresponding treatment plan.
  • the overlap detection module determines the positional relationship between the voxel grid and the beam source based on the positional relationship between a reference object and the beam source model, wherein the reference object is selected from a plurality of the voxel grids.
  • the overlap detection module can be used to determine the positional relationship between the reference object and the beam source model, and between the reference object and the internal irradiation space of the beam source model.
  • the treatment part of the irradiated body cannot extend into the internal irradiation space of the beam source, that is, the tissue of the irradiated body cannot overlap with the beam source model or the internal irradiation space of the beam source model.
  • the overlap detection module will determine whether the three-dimensional voxel model of the irradiated body is allowed to extend into the internal irradiation space of the beam source model, and whether the three-dimensional voxel model of the irradiated body extending into the internal irradiation space overlaps with the beam source model.
  • the overlap detection module can be used to output an overlap prompt signal between the reference object and the beam source.
  • the overlap detection module outputs an overlap prompt signal for the user or physicist to determine whether the relative position relationship between the irradiated object and the beam source needs to be adjusted. If adjustment is required, the adjustment can be made according to the overlap prompt signal.
  • the overlap detection module can be used to determine the tissue type of the overlapping reference object.
  • the overlap detection module determines that the reference object overlaps with the beam source model, it can determine whether the three-dimensional voxel model of the irradiated volume extending into the internal irradiation space of the beam source model overlaps with the beam source model, and further determine the tissue type of the overlapping reference object, thereby further determining whether the overlapping tissue range needs to be adjusted.
  • the overlap detection module can be used to determine the adjustment range of the position parameter.
  • the system will provide a reasonable adjustment range of the position parameter for the reference of the physicist;
  • the overlap detection module will provide an overlapping or non-overlapping position parameter adjustment range based on the tissue type of the reference object for the reference of the physicist to make adjustments, thereby facilitating the formulation of treatment plans and effectively improving the work efficiency of physicists.
  • the overlap detection module can be used to adjust the position parameter.
  • the overlap detection module determines whether the reference object and the beam source model overlap according to the positional relationship between the reference object and the beam source model, and automatically adjusts the position parameter.
  • the overlap detection module may be used to determine the type of voxel grid.
  • the types of the voxel grid include a first type of grid and a second type of grid, the first type of grid is composed of tissue of the irradiated body, and the second type of grid is composed of air, wherein the reference object is selected from the first type of grid.
  • a reference object is selected in the grid or a subsequent overlap judgment is performed or an overlap detection module is made to perform a subsequent overlap judgment, and when the voxel grid is determined to be the second type of grid, a reference object is not selected in the grid and a subsequent judgment step is not performed.
  • the tissue types include a first type of tissue and a second type of tissue, the first type of tissue is a surface flexible tissue, and the second type of tissue is a non-deformable tissue.
  • the overlapping tissue type is the first type of tissue, that is, surface tissue such as skin or surface flexible tissue such as skin, muscle, and fat, determine whether the position parameters need to be adjusted based on the overlapping range; if the overlapping tissue type is the second type of tissue, that is, non-deformable tissue such as bones, then it is necessary to adjust the position of the irradiated object or the position of the beam source model.
  • the reference object can be selected from the second type of tissue.
  • tissue type of the irradiated body is the first type of tissue, it is not necessary to adjust the position parameters of the three-dimensional voxel model of the irradiated body or the beam source model, or an allowable adjustment range of the position parameters of the three-dimensional voxel model of the irradiated body or the beam source model is given; when the tissue type of the irradiated body is the second type of tissue, it is necessary to adjust the position parameters of the three-dimensional voxel model of the irradiated body or the beam source model, or give a corresponding adjustment signal for the reference of the physicist.
  • the reference object includes one, more or all of the vertices, face centers, random points, contours or outer surfaces of the voxel grid.
  • the random points can be randomly sampled points in the voxel grid to simulate enough random points as reference objects.
  • the position parameters include the relative distance, relative angle, and beam irradiation direction between the beam source model and the three-dimensional voxel model of the irradiated body.
  • the treatment planning system calculates and outputs the position parameters based on the medical imaging data.
  • the overlap prompt signal includes overlap position, overlap amplitude and overlap volume.
  • an overlap prompt signal including overlap position, overlap amplitude and overlap volume is output for reference by the user or physicist to adjust the relative position.
  • the beam source model is selected based on the medical image data of the irradiated body, wherein the data processing module can select a suitable beam source model through the 3D voxel model of the irradiated body or the medical image data.
  • the present invention provides an automatic overlap checking method, the method comprising:
  • Model acquisition step acquiring a three-dimensional voxel model of the irradiated body and a beam source model, wherein the three-dimensional voxel model of the irradiated body includes a plurality of voxel grids;
  • Position parameter acquisition step acquiring position parameters of the beam source model and the irradiated body three-dimensional voxel model
  • Overlap judgment step judging the positional relationship between the three-dimensional voxel model of the irradiated volume and the beam source model based on the positional relationship between the voxel grid and the beam source model.
  • a reference object selection step is included before the overlap judgment step: a reference object is selected from a plurality of voxel grids; in the overlap judgment step, the positional relationship between the irradiated volume three-dimensional voxel model and the beam source model is judged based on the positional relationship between the reference object and the beam source model.
  • a grid type determination step is also included:
  • the voxel grid is determined to be a first type of grid, a reference object is selected in the grid and the overlap determination step is performed; when the voxel grid is determined to be a second type of grid, no reference object is selected in the grid and the overlap determination step is not performed;
  • the types of voxel grids include first-type grids and second-type grids, the first-type grids are composed of tissues of the irradiated body, and the second-type grids are composed of air.
  • the overlap determination step includes a position adjustment step: when the reference object overlaps with the beam source model, the position parameters of the beam source model or the irradiated volume three-dimensional voxel model are automatically adjusted until the reference object and the beam source model do not overlap.
  • the overlap determination step further includes an overlap signal output step: when the reference object overlaps with the beam source model, an overlap prompt signal is output.
  • the overlap determination step further includes a space insertion determination step: determining whether the irradiated body three-dimensional voxel model inserts into the internal irradiation space of the beam source model, and adjusting position parameters of the irradiated body three-dimensional voxel model and the beam source model.
  • the space penetration determination step includes a positional relationship determination step: determining the positional relationship between the reference object and the internal irradiation space of the beam source model.
  • the position relationship judgment step can be performed in the model acquisition step.
  • the space penetration judgment step further includes a tissue type judgment step: judging the tissue type of the irradiated body that penetrates into the irradiation space, and adjusting the position parameters according to the tissue type of the irradiated body.
  • the tissue type in the tissue type determination step includes a first type of tissue and a second type of tissue, the first type of tissue is a surface flexible tissue, and the second type of tissue is a non-deformable tissue;
  • the tissue type of the irradiated body is the first type of tissue, it is not necessary to adjust the position parameters of the 3D voxel model of the irradiated body or the beam source model, or the adjustment range of the position parameters of the 3D voxel model of the irradiated body and the beam source model is given;
  • the position parameters of the three-dimensional voxel model of the irradiated body or the beam source model are adjusted, or an adjustment signal is given.
  • the reference is selected from the second type of tissue.
  • the position parameters in the position parameter acquisition step include the relative distance, relative angle, and beam irradiation direction between the beam source model and the three-dimensional voxel model of the irradiated body.
  • the reference object in the overlap determination step includes one, more or all of the vertices, center points, random points, contours or outer surfaces of the voxel grid.
  • the overlap prompt signal in the overlap signal output step includes overlap position, overlap amplitude and overlap volume.
  • the beam source model is selected based on medical image data of the irradiated body.
  • the present invention provides a method for formulating a treatment plan, characterized by comprising:
  • Model data acquisition step acquiring medical image data of the irradiated body, and establishing a three-dimensional voxel model of the irradiated body based on the medical image data, wherein the three-dimensional voxel model of the irradiated body includes a plurality of voxel grids;
  • Position parameter determination step determining position parameters of the beam source model and the irradiated body three-dimensional voxel model
  • Overlap judgment step judging the positional relationship between the voxel grid and the beam source and adjusting the position parameters
  • Treatment plan generation step Generate a treatment plan.
  • the overlap judgment step also includes a reference object selection step: selecting a reference object from a plurality of voxel grids; in the overlap judgment step, the positional relationship between the irradiated volume three-dimensional voxel model and the beam source model is judged based on the positional relationship between the reference object and the beam source model.
  • a grid type determination step is also included:
  • the voxel grid is determined to be a first type of grid, a reference object is selected in the grid and the overlap determination step is performed; when the voxel grid is determined to be a second type of grid, no reference object is selected in the grid and the overlap determination step is not performed;
  • the types of voxel grids include first-type grids and second-type grids, the first-type grids are composed of tissues of the irradiated body, and the second-type grids are composed of air.
  • the overlap determination step includes a position adjustment step: when the reference object overlaps with the beam source model, the position parameters of the beam source model or the irradiated volume three-dimensional voxel model are automatically adjusted until the reference object and the beam source model do not overlap.
  • the overlap determination step further includes an overlap signal output step: when the reference object overlaps with the beam source model, an overlap prompt signal is output.
  • the overlap determination step further includes a space insertion determination step: determining whether the irradiated body three-dimensional voxel model inserts into the internal irradiation space of the beam source model, and adjusting position parameters of the irradiated body three-dimensional voxel model and the beam source model.
  • the space penetration determination step includes a positional relationship determination step: determining the positional relationship between the reference object and the internal irradiation space of the beam source model.
  • the position relationship judgment step can be performed in the position parameter determination step.
  • the space penetration judgment step further includes a tissue type judgment step: judging the tissue type of the irradiated body that penetrates into the irradiation space, and adjusting the position parameters according to the tissue type of the irradiated body.
  • the tissue type in the tissue type determination step includes a first type of tissue and a second type of tissue, the first type of tissue is a surface flexible tissue, and the second type of tissue is a non-deformable tissue;
  • the tissue type of the irradiated body is the first type of tissue, it is not necessary to adjust the position parameters of the 3D voxel model of the irradiated body or the beam source model, or the adjustment range of the position parameters of the 3D voxel model of the irradiated body and the beam source model is given;
  • the position parameters of the three-dimensional voxel model of the irradiated body or the beam source model are adjusted, or an adjustment signal is given.
  • the reference is selected from the second type of tissue.
  • the position parameters in the position parameter determination step include the relative distance, relative angle, and beam irradiation direction between the beam source model and the three-dimensional voxel model of the irradiated body.
  • the reference objects in the overlap determination step include vertices, face centers, random One, more, or all of the following: points, contours, or exterior surfaces.
  • the overlap prompt signal in the overlap signal output step includes overlap position, overlap amplitude and overlap volume.
  • the beam source model is selected based on medical image data of the irradiated body.
  • the treatment planning system obtains information such as the voxel grid of the irradiated body three-dimensional voxel model, the beam source model and the position parameters of the irradiated body three-dimensional voxel model by setting an image processing module, a data processing module, an overlap detection module and a treatment plan generation module, and then uses the overlap detection module to determine whether the irradiated body three-dimensional voxel model and the beam source model overlap and are reasonable, thereby determining whether the collimator and the patient's tissue overlap and are reasonable under the treatment plan, and checking whether the treatment plan will cause the collimator and the patient's tissue to collide during positioning. All processes can be automatically checked and judged by the treatment planning system, thereby providing guidance to the physicist in advance, so that the physicist can correct the treatment plan more quickly, and the treatment planning system can automatically generate a corresponding treatment plan.
  • FIG1 is a schematic diagram of a treatment planning system according to an embodiment of the present invention.
  • FIG2 is a schematic diagram of a boron neutron capture reaction
  • Figure 3 is the 10 B(n, ⁇ ) 7 Li neutron capture nuclear reaction equation
  • FIG4 is a block diagram of a neutron capture therapy system according to an embodiment of the present invention.
  • FIG. 5 is a flow chart of an automatic overlap checking method according to an embodiment of the present invention.
  • FIG. 6 is a flow chart of an automatic overlap checking method according to another embodiment of the present invention.
  • FIG. 7 is a flow chart of a method for formulating a treatment plan according to an embodiment of the present invention.
  • 100 boron neutron capture therapy facility 10 neutron beam source; 20 treatment planning system; 30 control system; 1 image processing module; 2 data processing module; 3 overlap detection module; 4 treatment plan generation module.
  • the present invention provides a treatment planning system 20 that can determine whether an irradiated object and a beam source overlap and generate a corresponding treatment plan.
  • the treatment plan is a treatment plan for performing radiation therapy, preferably, a treatment plan for performing neutron capture therapy, and more preferably, a treatment plan for performing boron neutron capture therapy.
  • a treatment plan for performing radiation therapy preferably, a treatment plan for performing neutron capture therapy, and more preferably, a treatment plan for performing boron neutron capture therapy.
  • One embodiment of the present invention is briefly introduced using boron neutron capture therapy as an example.
  • boron neutron capture therapy uses the high capture cross section of boron ( 10B ) drugs for thermal neutrons to produce two heavily charged particles, 4He and 7Li , through 10B (n, ⁇ ) 7Li neutron capture and nuclear fission reactions.
  • FIG2 and FIG3 which respectively show a schematic diagram of a boron neutron capture reaction and a 10 B(n, ⁇ ) 7 Li neutron capture nuclear reaction equation, the average energy of the two charged particles is about 2.33 MeV, with high linear energy transfer (LET) and short range characteristics.
  • LET linear energy transfer
  • the linear energy transfer and range of ⁇ particles are 150 keV/ ⁇ m and 8 ⁇ m, respectively, while those of 7 Li heavy-charged particles are 175 keV/ ⁇ m and 5 ⁇ m.
  • the total range of the two particles is approximately equivalent to the size of a cell. Therefore, the radiation damage caused to the organism can be limited to the cellular level.
  • boron-containing drugs selectively accumulate in tumor cells and are combined with appropriate neutron radiation sources, the purpose of locally killing tumor cells can be achieved without causing too much damage to normal tissues.
  • Neutrons for BNCT can be supplied by nuclear reactors or accelerators.
  • accelerator BNCT is used as an example.
  • the accelerator accelerates charged particles (such as protons, deuterons, etc.), and the accelerated charged particles react with metal targets to produce neutrons.
  • the appropriate nuclear reaction is selected based on the required neutron yield and energy, the energy and current of the accelerated charged particles that can be provided, and the physical and chemical properties of the metal targets.
  • the commonly discussed nuclear reactions are 7 Li(p,n) 7 Be and 9 Be(p,n) 9 B, both of which are endothermic reactions.
  • the energy thresholds of the two nuclear reactions are 1.881MeV and 2.055MeV, respectively.
  • the ideal neutron source for BNCT is epithermal neutrons at the keV energy level, theoretically, if protons with energies just slightly above the threshold are used to bombard lithium metal targets, relatively low-energy neutrons can be produced, which can be used clinically without much slowing down.
  • the cross-sections of lithium metal (Li) and beryllium metal (Be) targets with protons of the threshold energy are not high. In order to produce a sufficiently large neutron flux, higher energy protons are usually used to initiate nuclear reactions.
  • the Monte Carlo method can accurately simulate the collision trajectory and energy distribution of nuclear particles in the three-dimensional space inside the irradiated target.
  • boron neutron capture therapy in order to simulate the absorbed dose of the human body under certain radiation conditions to help doctors formulate treatment plans, it is often necessary to use computer technology to process medical images in various ways to establish an accurate lattice model required by the Monte Carlo software, and combine the Monte Carlo software for simulation calculations.
  • Medical image data can be magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), PET-CT or X-ray imaging. In this embodiment, it will be explained based on the data of computed tomography (CT), and the file format of CT is usually DICOM.
  • a boron neutron capture therapy facility 100 includes a neutron beam source 10, a treatment planning system 20, and a control system 30.
  • the neutron beam source 10 includes a neutron generator and a treatment table.
  • the neutron generator generates a therapeutic neutron beam N and irradiates the irradiated part of the patient on the treatment table.
  • the treatment planning system 20 generates a treatment plan based on the medical imaging data of the patient, and the control system 30 controls the neutron beam source 10 to perform irradiation therapy based on the treatment plan.
  • the treatment planning system 20 stores a tissue model template library of the patient.
  • the treatment planning system 20 establishes a three-dimensional voxel prosthetic tissue model corresponding to the medical imaging data of the irradiated part based on the tissue model template library, and simulates and calculates the dose distribution of the patient during irradiation therapy through a Monte Carlo simulation program based on the three-dimensional voxel prosthetic tissue model and generates a treatment plan.
  • the tissue model template library is pre-set to prevent the inaccuracy of the established model and dose calculation due to the difference in personal experience of the operator such as the physician; at the same time, it avoids spending a lot of time and energy on the definition of the basic information of the organism in the lattice in the model.
  • the control system 30 retrieves the treatment plan corresponding to the current patient from the treatment planning system 20 and controls the irradiation of the neutron beam source 10 according to the treatment plan.
  • the neutron generating device includes a neutron generating unit, a beam shaping body and a collimator.
  • the neutron generating unit includes an accelerator and a target material.
  • the accelerator is used to accelerate charged particles (such as protons, deuterons, etc.) to generate charged particle lines such as proton lines.
  • the charged particle lines irradiate the target material and react with the target material to generate neutron lines (neutron beams).
  • the target material is preferably a metal target material.
  • the appropriate nuclear reaction is selected based on the required neutron yield and energy, the energy and current of the accelerated charged particles that can be provided, the physical and chemical properties of the metal target material, and other characteristics.
  • the nuclear reactions that are often discussed are 7 Li (p, n) 7 Be and 9 Be (p, n) 9 B, both of which are endothermic reactions.
  • a target material made of lithium metal is used.
  • the target material can also be made of metal materials other than lithium and beryllium, such as tantalum (Ta) or tungsten (W);
  • the target material can be in the shape of a disk, or other solid shapes, or a liquid (liquid metal);
  • the accelerator can be a linear accelerator, a cyclotron, a synchrotron, or a synchrocyclotron.
  • the neutron generator can be a nuclear reactor without an accelerator and a target material.
  • the neutron source of BNCT comes from a nuclear reactor or a nuclear reaction between accelerated charged particles and a target material
  • what is actually produced is a mixed radiation field, that is, the generated beam contains neutrons and photons ranging from low energy to high energy.
  • the more radiation content there is, except for epithermal neutrons the greater the proportion of non-selective dose deposition in normal tissues. Therefore, the radiation content that causes unnecessary dose deposition should be reduced as much as possible.
  • the beam shaper can adjust the beam quality of the neutron beam generated by the neutron generator and reduce unnecessary dose deposition.
  • the collimator is used to converge the neutron beam so that the neutron beam has a higher targeting during the treatment process.
  • the beam shaping body includes a reflector, a retarder, a thermal neutron absorber, a radiation shield and a beam outlet.
  • the retarder can adjust the fast neutron energy (>40keV) from the neutron generator to the epithermal neutron energy zone (0.5eV-40keV) and reduce the thermal neutron content ( ⁇ 0.5eV) as much as possible; the retarder is made of a material with a large cross section for fast neutrons and a small cross section for epithermal neutrons.
  • the retarder is made of at least one of D2O , AlF3 , FluentalTM, CaF2 , Li2CO3 , MgF2 and Al2O3 ; the reflector surrounds the retarder and reflects the neutrons that pass through the retarder and diffuse to the surroundings back to the A neutron beam is used to improve the utilization rate of neutrons. It is made of a material with strong neutron reflection ability. As a preferred embodiment, the reflector is made of at least one of Pb or Ni. On the transmission path of the neutron beam, a thermal neutron absorber is arranged at the rear of the retarder to absorb thermal neutrons passing through the retarder to reduce the content of thermal neutrons in the neutron beam.
  • the thermal neutron absorber is made of Li-6. In other embodiments, since the material of the retarder contains Li-6, the thermal neutron absorber may not be arranged separately, but the retarder is used as the thermal neutron absorber.
  • the radiation shielding body is used to shield neutrons and photons leaking from the part other than the beam outlet.
  • the material of the radiation shielding body includes at least one of a photon shielding material and a neutron shielding material.
  • the material of the radiation shielding body includes a photon shielding material lead (Pb) and a neutron shielding material polyethylene (PE).
  • the collimator is arranged at the rear of the beam exit, and the epithermal neutron beam coming out of the collimator is directed toward the irradiated body. After passing through the shallow normal tissue of the irradiated body, the epithermal neutron beam is slowed down into thermal neutrons to reach the tumor cells to achieve the purpose of treatment.
  • the treatment plan of the embodiment of the present invention includes the irradiation conditions required for implementing radiotherapy on the irradiated body.
  • the irradiation conditions include position parameters and dose parameters.
  • the position parameters include coordinate information that can represent the relative position of the irradiated body model and the beam source model, various coordinate information or relative position information of the irradiation source, and the angle or direction indicated by the above relative position. In the process of formulating the treatment plan, it is generally necessary to calculate the position parameters before calculating the dose parameters.
  • the beam source is located at the entrance or exit of the collimator (close to the irradiated body). In some cases, the irradiated body cannot extend into the collimator. From the perspective of computational efficiency, the beam source at the exit of the collimator is closer to the irradiated body. Therefore, choosing the exit of the collimator as the location of the beam source can calculate the dose distribution faster. In this case, the beam source information at the exit is based on the case where the collimator is air. In order to reasonably formulate the treatment position and calculate the accurate treatment dose, the irradiated body must not overlap with the collimator or the space inside the collimator.
  • the treatment part of the irradiated body can extend into the collimator, so the entrance of the collimator is selected as the location of the beam source to calculate the dose distribution.
  • the tissue of the irradiated body must not overlap with the collimator.
  • the user or physicist needs to make a treatment plan, and then judge whether there is overlap or whether the overlap is reasonable by naked eye observation or based on experience during simulation treatment or actual treatment, which makes the whole treatment process more cumbersome.
  • the treatment planning system 20 of this embodiment includes an image processing module 1 , a data processing module 2 , an overlap detection module 3 and a treatment plan generating module 4 .
  • the image processing module 1 is used to obtain medical image data of the irradiated body, which is generally obtained through an external scanning device.
  • the image processing module 1 establishes a three-dimensional voxel model of the irradiated body based on the medical image data.
  • the three-dimensional voxel model of the irradiated body includes a plurality of voxel grids.
  • the image processing module 1 establishes a voxel grid describing the three-dimensional voxel model of the irradiated body.
  • the data processing module 2 is used to obtain the beam source model and determine the position parameters of the beam source model and the three-dimensional voxel model of the irradiated body.
  • the data processing module 2 obtains the irradiated volume three-dimensional voxel model from the image processing module 1, and Obtaining the beam source model from the library:
  • the preset library may include beam source models of different shapes and sizes, so that the data processing module 2 can obtain the beam source model that is compatible with the three-dimensional voxel model of the irradiated body.
  • the data processing module 2 can also select a suitable beam source model through the irradiated body three-dimensional voxel model or medical image data.
  • the irradiated body three-dimensional voxel model can be input or selected by the user, and the data processing module 2 can call the corresponding beam source model through the user's input or selection.
  • the data processing module 2 calculates the position parameters through the irradiated body three-dimensional voxel model and the selected beam source model.
  • the position parameters include the relative distance, relative angle, and beam irradiation direction between the beam source model and the irradiated body three-dimensional voxel model.
  • the data processing module 2 can also calculate the irradiation parameters based on the image data or the irradiated body three-dimensional voxel model. It can be understood that the present invention may not have a collimator, and the beam directly irradiates the irradiated body after coming out of the beam outlet of the beam shaping body. For the convenience of description, when a collimator is provided, the outlet of the collimator is interpreted as the beam outlet, and the device constituting the beam outlet is collectively referred to as the beam source.
  • the beam source model in the present invention is the model of the device constituting the beam outlet.
  • the location of the beam source is determined while selecting the beam source model, that is, when selecting and formulating a treatment plan, whether the treatment part of the irradiated body will extend into the collimator.
  • an irradiation space is formed at the beam outlet of the beam source, and the irradiation space is surrounded by the periphery of the beam outlet.
  • the irradiation space may be a radial opening.
  • the overlap detection module 3 is used to determine the positional relationship between the voxel grid and the beam source.
  • the overlap detection module 3 determines the positional relationship between the voxel grid and the beam source model based on the positional relationship between the reference object and the beam source model, wherein the reference object is selected from at least part of the voxel grid, and the reference object includes one, more or all of the vertices, face centers, random points, contours or outer surfaces of the voxel grid.
  • the types of voxel grids include a first type of grid and a second type of grid, wherein the first type of grid is filled with tissues of the irradiated body, and the tissues of the first type of grid refer to the organic or inorganic components of the human body such as organs, blood vessels, bones, muscles, fat, skin, etc. of the irradiated body, and the second type of grid is filled with air, wherein the reference object is selected from the first type of grid.
  • the overlap detection module 3 can determine whether the positional relationship between the irradiated volume three-dimensional voxel model and the beam source model is reasonable. Specifically, the overlap detection module 3 or the data processing module 2 can determine whether the voxel grid belongs to the first type of grid or the second type of grid; when the voxel grid is determined to be the first type of grid, a reference object is selected in the grid, or a subsequent overlap judgment is performed, or the overlap detection module 3 is made to perform a subsequent overlap judgment; when the voxel grid is determined to be the second type of grid, a reference object is not selected in the grid and subsequent judgment steps are not performed. The overlap detection module 3 determines whether the reference object and the beam source model overlap based on the positional relationship between the reference object and the beam source model, and adjusts the position parameters.
  • the overlap detection module 3 determines that the reference object overlaps with the beam source model, it adjusts the position of the three-dimensional voxel model of the irradiated volume or the position of the beam source model, outputs a signal to the data processing module 2 to recalculate the position parameters, and obtains new position parameters to perform overlap judgment again until the reference object and the beam source model do not overlap.
  • the overlap detection module 3 determines that the reference object overlaps with the beam source model, it outputs a signal to the data processing module 2, the data processing module 2 adjusts and recalculates the position parameters of the three-dimensional voxel model of the irradiated volume or the position parameters of the beam source model, and the overlap detection module 3 obtains the new position parameters and makes another judgment until the reference object and the beam source model do not overlap.
  • the above embodiments are all based on the fact that the treatment part of the irradiated body cannot extend into the collimator, that is, the tissue of the irradiated body cannot overlap with the beam source model or the internal irradiation space of the beam source.
  • the overlap detection module 3 can also determine whether the positional relationship between the irradiated body three-dimensional voxel model and the internal irradiation space of the beam source is reasonable, that is, determine whether the irradiated body three-dimensional voxel model is allowed to extend into the internal irradiation space of the beam source, determine whether the irradiated body three-dimensional voxel model extending into the internal irradiation space of the beam source overlaps with the beam source model, and determine whether the treatment part of the irradiated body can extend into the internal irradiation space of the beam source when selecting the beam source model.
  • the overlap detection module 3 determines that the reference object overlaps with the beam source model, it can determine whether the irradiated body three-dimensional voxel model extending into the internal irradiation space of the beam source overlaps with the beam source model.
  • the overlap detection module 3 can also be used to determine the tissue type of the overlapping reference object, wherein the tissue type includes a first type of tissue and a second type of tissue, wherein the first type of tissue is a surface tissue such as skin or a surface flexible tissue such as skin, muscle, fat, etc.; the second type of tissue is a non-deformable tissue such as bone; and the reference object is selected from the second type of tissue.
  • the tissue type includes a first type of tissue and a second type of tissue, wherein the first type of tissue is a surface tissue such as skin or a surface flexible tissue such as skin, muscle, fat, etc.; the second type of tissue is a non-deformable tissue such as bone; and the reference object is selected from the second type of tissue.
  • the tissue type of the overlapping reference object is the first type of tissue
  • it is determined whether the position parameter needs to be adjusted according to the overlapping range or the adjustment range of the position parameter is given by the treatment planning system 20; if the tissue type of the overlapping reference object is the second type of tissue, it is necessary to adjust the position of the irradiated body or the position of the beam source model.
  • the position parameter is calculated by the data processing module 2 and then determined by the overlap detection module 3, or directly determined by the overlap detection module 3.
  • the position parameter at this time is output to the treatment plan generation module 4 for dose calculation, and then a treatment plan is formulated.
  • the overlap detection module 3 can also be used to output an overlap prompt signal between the reference object and the beam source, so that the user or physicist can determine whether the relative position relationship between the irradiated object and the beam source needs to be adjusted. If adjustment is required, the overlap detection module 3 can make a judgment after the adjustment is calculated by the data processing module 2, or the overlap detection module 3 can make a judgment directly.
  • the overlap prompt signal includes the overlap position, overlap amplitude, and overlap volume.
  • the embodiment of the present invention further includes an automatic overlapping inspection method based on a treatment plan.
  • the method includes:
  • model acquisition step acquiring a three-dimensional voxel model of the irradiated volume and a beam source model, wherein the three-dimensional voxel model of the irradiated volume includes a plurality of voxel grids;
  • position parameter acquisition step acquiring position parameters of the beam source model and the irradiated body three-dimensional voxel model
  • overlapping judgment step judging the positional relationship between the irradiated volume three-dimensional voxel model and the beam source model based on the positional relationship between the voxel grid and the beam source model.
  • the overlap judgment step Before the overlap judgment step, it also includes S400, a reference object selection step: selecting a reference object from a plurality of voxel grids; in S300, the overlap judgment step, the positional relationship between the irradiated volume three-dimensional voxel model and the beam source model is judged based on the positional relationship between the reference object and the beam source model.
  • the model acquisition step the acquired beam source model has been preset or imported into the treatment planning system 20 through other devices.
  • the beam source model includes multiple ones, which are pre-stored in the treatment planning system 20 and can be selected by the doctor based on the medical image data of the irradiated body.
  • the irradiated body three-dimensional voxel model is established based on the medical image data of the irradiated body, and the irradiated body three-dimensional voxel model includes a plurality of voxel grids.
  • the position parameter acquisition step, the position parameters of the beam source model and the irradiated volume 3D voxel model include at least the relative distance, relative angle and beam irradiation direction between the beam source model and the irradiated volume 3D voxel model.
  • the treatment planning system 20 calculates and outputs the position parameters according to the medical imaging data.
  • the method further includes S500, the grid type determination step:
  • the voxel grid is determined to be a first type of grid, a reference object is selected in the grid and the overlap determination step is performed; when the voxel grid is determined to be a second type of grid, no reference object is selected in the grid and the overlap determination step is not performed;
  • the types of voxel grids include first-class grids and second-class grids, the first-class grids are composed of tissues of the irradiated body, and the second-class grids are composed of air.
  • the tissues of the first-class grids refer to the organic or inorganic components of the human body such as organs, blood vessels, bones, muscles, fat, skin, etc. of the irradiated body.
  • the reference object selection step the reference object is selected from the first-class grid.
  • the voxel grid is generally a polyhedron.
  • the voxel grid is a hexahedron
  • the reference object is a point, line or surface of the voxel grid.
  • the point of the voxel grid is preferably used as the reference object.
  • the reference object is the vertex of the voxel grid.
  • it is determined whether the eight vertices of the first-class voxel grid overlap with the beam source model. If any vertex overlaps with the beam source model, it is determined that the three-dimensional voxel model of the irradiated body overlaps with the beam source model.
  • the reference object includes but is not limited to one, more or all of the center points, random points, contour lines or outer surfaces of the voxel grid.
  • the random point can be a randomly sampled point selected in the voxel grid to simulate enough random points as reference objects.
  • the overlapping determination step includes S310, the position adjustment step: when the reference object overlaps with the beam source model, automatically adjusting the position parameters of the beam source model or the irradiated volume three-dimensional voxel model until the reference object does not overlap with the beam source model.
  • the beam irradiation direction is not adjusted, that is, when adjusting the relative position of the beam source model and the irradiated body three-dimensional voxel model, the beam irradiation direction is translated to ensure that the adjustment has minimal impact on other parameter changes. All processes can be automatically checked, judged and adjusted using the treatment planning system 20, which improves the accuracy of the output treatment plan and avoids the problem of incompatibility with the actual positioning.
  • the overlapping judgment step also includes S320, an overlapping signal output step: when the reference object overlaps with the beam source model, an overlapping prompt signal is output for the user or physicist to determine whether the relative position relationship between the irradiated object and the beam source needs to be adjusted. If adjustment is required, the adjustment is performed according to the overlapping prompt signal, and after the adjustment, S300, the overlapping judgment step is repeated.
  • the overlapping prompt signal may include overlapping position, overlapping amplitude, overlapping volume, etc., for the user or physicist to refer to for adjusting the relative position.
  • the overlapping determination step further includes S330, a space extension determination step: determining whether the irradiated body three-dimensional voxel model extends into the internal irradiation space of the beam source model, and adjusting position parameters of the irradiated body three-dimensional voxel model and the beam source model.
  • the space penetration determination step may further include the following steps:
  • S331, position relationship judgment step judge the position relationship between the reference object and the internal irradiation space of the beam source model. Similar to the way of judging overlap in steps S300 and S400, in this step, a reference object is selected and the position relationship of the reference object is judged to judge whether the three-dimensional voxel model of the irradiated body is allowed to extend into the internal irradiation space of the beam source model and whether the three-dimensional voxel model of the irradiated body extends into the irradiation space. Furthermore, in this embodiment, S331, position relationship judgment step can also be performed in S100, model acquisition step.
  • the irradiated body When selecting the beam source model, it is judged whether the irradiated body can extend into the internal irradiation space according to the size of the internal irradiation space in the beam source model and the size of the irradiated body, especially whether the treatment part in the irradiated body can extend into the internal irradiation space.
  • tissue type determination step determine the tissue type of the irradiated body extending into the irradiation space, and adjust the position parameters according to the tissue type of the irradiated body.
  • the tissue type of the irradiated body is determined by determining the type of the voxel grid or the reference object.
  • the tissue type includes a first type of tissue and a second type of tissue.
  • the first type of tissue is a surface flexible tissue, including skin, muscle, fat, etc.
  • the second type of tissue is a non-deformable tissue, such as bones, etc.; further, when the tissue type of the irradiated body is the first type of tissue, it is not necessary to adjust the position parameters of the 3D voxel model of the irradiated body or the beam source model, or give an adjustment range of the position parameters of the 3D voxel model of the irradiated body and the beam source model; when the irradiated body is the second type of tissue, the position parameters of the 3D voxel model of the irradiated body or the beam source model are adjusted, or an adjustment signal is given.
  • the reference object can be selected from the second type of tissue.
  • step S331 position relationship determination step
  • step S332 tissue type determination step.
  • the type of the irradiated body may be determined first and then a reference object may be selected, or reference objects may be selected from all types of tissues and then the position relationship of reference objects that meet the requirements may be determined.
  • the treatment plan generation module 4 generates a treatment plan based on the adjusted position parameters.
  • the treatment plan generation module 4 will recalculate the irradiation parameters based on the irradiation parameters obtained by the data processing module 2 and the adjusted unknown parameters, and the generated treatment plan includes the adjusted position parameters and the new irradiation parameters.
  • the main adjustment is the relative position of the irradiated volume three-dimensional voxel model and the beam source model.
  • the direction parameters do not change, only the dose parameters can be recalculated when recalculating the irradiation parameters.
  • Each module in the above treatment planning system 20 can be implemented in whole or in part by software, hardware, or a combination thereof.
  • Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each module.
  • the treatment plan system 200 may also include a terminal, a communication module, a server, a data storage module, etc.
  • the terminal communicates with the server through the communication module.
  • the image processing module 1, the data processing module 2, the overlap detection module 3 and the treatment plan generation module 4 can be integrated in the terminal.
  • the terminal can be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, Internet of Things devices and portable wearable devices.
  • the Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart car-mounted devices, etc.
  • Portable wearable devices can be smart watches, smart bracelets, head-mounted devices, etc.
  • the data storage module can be integrated on the server 1, or it can be placed on the cloud or other network servers.
  • the data storage module includes a non-volatile storage medium and an internal memory.
  • the non-volatile storage medium stores programs and data related to the image processing module 1, the data processing module 2, the overlap detection module 3 and the treatment plan generation module 4, as well as an operating system and a computer program.
  • the internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium.
  • the server can be implemented as an independent server or a server cluster consisting of multiple servers.
  • the communication module is used to communicate with an external terminal in a wired or wireless manner. The wireless manner can be achieved through WIFI, mobile cellular network, NFC (near field communication) or other technologies.
  • the terminal also includes a display device and an input device.
  • the image processing module 1, the data processing module 2, the overlap detection module 3 and the treatment plan generation module 4 can present corresponding data and interfaces through the display device.
  • the image processing module 1, the data processing module 2, the overlap detection module 3 and the treatment plan generation module 4 can obtain the parameters input by the user through the input device.
  • the display device can be a display screen in particular, and the display screen can be a liquid crystal display screen or an electronic ink display screen.
  • the input device can be a touch layer covered on the display screen, or it can be a button, trackball or touchpad set on the terminal, or it can be an external keyboard, touchpad or mouse, etc.
  • the embodiment of the present invention further includes a treatment plan formulation method, which, as the operation mode of the treatment plan system 20, can determine the overlap and generate a corresponding treatment plan.
  • the parts that are the same or similar to the above content are not repeated.
  • the treatment plan formulation method includes the following steps:
  • model data acquisition step acquiring medical image data of the irradiated body, and establishing a three-dimensional voxel model of the irradiated body based on the medical image data, wherein the three-dimensional voxel model of the irradiated body includes a plurality of voxel grids;
  • A200, position parameter determination step determining position parameters of the beam source model and the irradiated body three-dimensional voxel model
  • overlapping determination step determining the positional relationship between the voxel grid and the beam source and adjusting the positional parameters
  • treatment plan generation steps generate a treatment plan.
  • the overlap judgment step before A300, it also includes A500, a reference object selection step: selecting a reference object from a plurality of voxel grids; in A300, the overlap judgment step, the positional relationship between the three-dimensional voxel model of the irradiated body and the beam source model is judged based on the positional relationship between the reference object and the beam source model.
  • the reference object selection step also includes:
  • A501 determining whether the voxel grid belongs to the first type of grid or the second type of grid
  • the overlap determination step further includes:
  • A301 Determine whether the reference object overlaps with the beam source model, or determine whether the reference object extends into the beam source model.
  • the generated treatment plan includes the position parameters determined in step A200.
  • steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with other steps or at least a part of the steps or stages in other steps.
  • any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory.
  • Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc.
  • Volatile memory can include random access memory (RAM) or external cache memory, etc.
  • RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). DRAM), etc.
  • SRAM static random access memory
  • DRAM dynamic random access memory
  • the database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database.
  • the non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto.
  • the processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

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Abstract

本发明涉及一种治疗计划系统、重叠自动检查方法及治疗计划的制定方法，治疗计划系统包括：影像处理模块，并基于医学影像数据建立被照射体模型，被照射体模型包括若干体素网格；数据处理模块，获取射束源模型，确定射束源模型和被照射体模型的位置参数；重叠检测模块，在若干体素网格中选取参考物，根据参考物与射束源模型的位置关系判断参考物与射束源模型是否重叠，并调整位置参数直到参考物与射束源模型不重叠；治疗计划生成模块，基于调整后的位置参数生成治疗计划。本发明不仅能够自动判断准直器与患者组织是否重叠，检验治疗方案是否会导致摆位时准直器与患者组织发生碰撞；还能够更快地修正放疗计划，且能够自动生成相应的治疗计划。

Description

治疗计划系统、重叠自动检查方法及治疗计划的制定方法 技术领域
本申请涉及治疗计划技术领域，特别是涉及一种治疗计划系统、重叠自动检查方法及治疗计划的制定方法。
背景技术
放射治疗是利用放射线治疗的一种局部治疗方法，也是癌症治疗的重要手段。随着原子科学的发展，例如钴六十、直线加速器、电子射束等放射线治疗已成为癌症治疗的主要手段之一。然而传统光子或电子治疗受到放射线本身物理条件的限制，在杀死肿瘤细胞的同时，也会对射束途径上大量的正常组织造成伤害；另外由于肿瘤细胞对放射线敏感程度的不同，传统放射治疗对于较具抗辐射性的恶性肿瘤(如：多行性胶质母细胞瘤(glioblastoma multiforme)、黑色素细胞瘤(melanoma))的治疗成效往往不佳。为了减少肿瘤周边正常组织的辐射伤害，化学治疗(chemotherapy)中的标靶治疗概念便被应用于放射线治疗中；而针对高抗辐射性的肿瘤细胞，目前也积极发展具有高相对生物效应(relative biological effectiveness,RBE)的辐射源，如质子治疗、重粒子治疗、中子捕获治疗等。其中，中子捕获治疗便是结合上述两种概念，如硼中子捕获治疗(Boron Neutron Capture Therapy,BNCT)，借由含硼药物在肿瘤细胞的特异性集聚，配合精准的射束调控，提供比传统放射线更好的癌症治疗选择。在进行放射治疗前，物理师需要预估治疗效果，确定治疗流程，这个过程就是制定放疗治疗计划的过程。
在制定治疗计划时，其中重要的步骤就是确定准直器相对于病人的照射角度和方向。为了保护正常人体组织不受过多辐射损伤，通常会将准直器出口设置在靠近肿瘤部分的位置，准直器能够引导射线粒子向出口方向运动，从而保证大部分射线粒子射向肿瘤并保护其它正常人体组织。大多数情况下，在实际治疗过程中，人体组织与准直器实体是不允许发生重叠的，否则难以将病人摆位至治疗参数位置。如果准直器只是和体素网格中的空气部分发生重叠，或者是人体表面比较突出的治疗部位是可以伸入进准直器内部空间，这些情况是可以接受的。物理师制定治疗计划时需要自己判断人体组织是否与准直器重叠，倘若在实际治疗中才发现有重叠，例如剂量计算完成后甚至摆位时才发现这个问题，将会导致治疗无法顺利进行。
发明内容
基于此，有必要针对上述技术问题，提供一种能够高效的、准确的治疗计划系统、治疗计划的重叠自动检查方法及治疗计划的制定方法。
第一方面，本发明提供了一种治疗计划系统，其包括：
影像处理模块，用于获取被照射体的医学影像数据，并基于所述医学影像数据建立被照射体三维体素模型，所述被照射体三维体素模型包括若干个体素网格；
数据处理模块，用于获取射束源模型以及确定所述射束源模型和所述被照射体三维体素模型的位置参数；
重叠检测模块，用于判断所述体素网格与所述射束源的位置关系；
治疗计划生成模块，用于生成治疗计划。
本发明提供的治疗计划系统，通过设置影像处理模块、数据处理模块、重叠检测模块和治疗计划生成模块，得到被照射体三维体素模型的体素网格、射束源模型和被照射体三维体素模型的位置参数等信息，再通过重叠检测模块来判断被照射体三维体素模型和射束源模型是否重叠及合理，从而判断在该治疗方案下准直器与患者组织是否重叠及合理，检验治疗方案是否会导致摆位时准直器与患者组织发生碰撞，且所有流程均能够通过治疗计划系统自动完成检查和判断，进而能够提前为物理师提供指导，使得物理师能够更快地修正治疗计划，且治疗计划系统能够自动生成相应的治疗计划。
在其中一个实施例中，所述重叠检测模块基于参考物与所述射束源模型的位置关系来判断所述体素网格与所述射束源的位置关系，其中，所述参考物由若干个所述体素网格中选取。
在其中一个实施例中，所述重叠检测模块可用于判断所述参考物与所述射束源模型、所述参考物与所述射束源模型的内部照射空间的位置关系。当被照射体的治疗部位不可以伸入射束源内部照射空间时，即被照射体的组织不仅不可以与射束源模型重叠，也不可以与射束源模型的内部照射空间重叠。并且，在选择射束源模型时就判断并确定被照射体的治疗部位能否伸入射束源模型的内部照射空间。重叠检测模块会对被照射体三维体素模型是否允许伸入射束源模型的内部照射空间、伸入内部照射空间的被照射体三维体素模型是否和射束源模型重叠进行判断。
在其中一个实施例中，所述重叠检测模块可用于输出所述参考物与所述射束源的重叠提示信号。当参考物与射束源模型重叠时，重叠检测模块输出重叠提示信号，供用户或物理师判断是否需要调整被照射体和射束源之间的相对位置关系，若需要调整，则可根据重叠提示信号进行调整。
在其中一个实施例中，所述重叠检测模块可用于判断重叠的所述参考物的组织类型。当 重叠检测模块判断参考物与射束源模型重叠时，即可判断伸入射束源模型的内部照射空间的被照射体三维体素模型与射束源模型是否重叠，并进一步地判断重叠的参考物的组织类型，从而进一步判断是否需要对重叠的组织范围进行调整。
在其中一个实施例中，所述重叠检测模块可用于判断所述位置参数的调整范围。当被照射体的治疗部位不可以伸入射束源内部照射空间时，确定参考物与射束源模型重叠后，系统会提供合理的位置参数的调整范围以供物理师参考；当被照射体的治疗部位可以伸入射束源内部照射空间时，重叠检测模块会根据参考物的组织类型给出重叠或不重叠的位置参数调整范围以供物理师参考进行调整与否，从而便于治疗计划制定的同时，还能够有效提高物理师的工作效率。
在其中一个实施例中，所述重叠检测模块可用于调整所述位置参数。重叠检测模块根据参考物与射束源模型的位置关系来判断参考物与射束源模型是否重叠，并自动调整位置参数。
在其中一个实施例中，所述重叠检测模块可用于判断体素网格的类型。
在其中一个实施例中，所述体素网格的类型包括第一类网格和第二类网格，所述第一类网格由所述被照射体的组织组成，所述第二类网格由空气组成，其中，所述参考物选取于所述第一类网格。当系统判断体素网格为第一类网格时，在该网格中选择参考物或执行后续的重叠判断或使重叠检测模块执行后续的重叠判断，当判断体素网格为第二类网格时，不在该网格中选择参考物且不执行后续的判断步骤。
在其中一个实施例中，所述组织类型包括第一类组织和第二类组织，所述第一类组织为表层柔性组织，所述第二类组织为不可形变组织。
在进一步判断重叠的参考物的组织类型时，如果重叠的组织类型为第一类组织时，即皮肤等表层组织或者是皮肤、肌肉、脂肪等表层柔性组织，根据重叠范围判断是否需要调整位置参数；如果重叠的组织类型为第二类组织时，即骨骼等不可形变的组织，此时则需要调整被照射体的位置或者射束源模型的位置。
在其中一个实施例中，所述参考物可由所述第二类组织中选取。
当被照射体的组织类型为第一类组织时，不需要调整被照射体三维体素模型或射束源模型的位置参数，或者给出被照射体三维体素模型或射束源模型的位置参数允许的调整范围；当被照射体的组织类型为第二类组织时，则需要调整被照射体三维体素模型或射束源模型的位置参数，或给出相应的调整信号以供物理师参考。
在其中一个实施例中，所述参考物包括所述体素网格的顶点、面心点、随机点、轮廓线或外表面中的一个、多个或全部。随机点可以是在体素网格中选取随机抽样点，模拟足够多的随机点作为参考物。
在其中一个实施例中，所述位置参数包括所述射束源模型和所述被照射体三维体素模型之间的相对距离、相对角度、射束照射方向。治疗计划系统根据医学影像数据计算并输出该位置参数。
在其中一个实施例中，所述重叠提示信号包括重叠位置、重叠幅度和重叠体积。当参考物与射束源模型重叠时，输出包括重叠的位置、重叠幅度和重叠体积等重叠提示信号，供用户或物理师参考进行相对位置的调整。
在其中一个实施例中，所述射束源模型基于所述被照射体的医学影像数据选择。其中，数据处理模块能够通过被照射体三维体素模型或医学影像数据选择合适的射束源模型。
第二方面，本发明提供了一种重叠自动检查方法，所述方法包括：
模型获取步骤：获取被照射体三维体素模型和射束源模型，被照射体三维体素模型包括若干个体素网格；
位置参数获取步骤：获取射束源模型和被照射体三维体素模型的位置参数；
重叠判断步骤：基于体素网格与射束源模型的位置关系判断被照射体三维体素模型与射束源模型的位置关系。
在其中一个实施例中，在所述重叠判断步骤之前还包括参考物选取步骤：在若干个体素网格中选取参考物；所述重叠判断步骤中基于参考物与射束源模型的位置关系来判断被照射体三维体素模型与射束源模型的位置关系。
在其中一个实施例中，在所述参考物选取步骤或所述重叠判断步骤之前或开始参考物选取步骤或所述重叠判断步骤时，还包括网格类型判断步骤：
当判断体素网格为第一类网格时，在该网格中选择参考物并执行所述重叠判断步骤，当判断体素网格为第二类网格时，不在该网格中选择参考物且不执行所述重叠判断步骤；
其中，体素网格的类型包括第一类网格和第二类网格，第一类网格由被照射体的组织组成，第二类网格由空气组成。
在其中一个实施例中，所述重叠判断步骤包括位置调整步骤：当参考物与射束源模型重叠时，自动调整射束源模型或被照射体三维体素模型的位置参数，直至参考物与射束源模型不重叠。
在其中一个实施例中，所述重叠判断步骤还包括重叠信号输出步骤：当参考物与射束源模型重叠时，输出重叠提示信号。
在其中一个实施例中，所述重叠判断步骤还包括空间伸入判断步骤：判断被照射体三维体素模型是否伸入射束源模型的内部照射空间，并调整被照射体三维体素模型与射束源模型的位置参数。
在其中一个实施例中，所述空间伸入判断步骤包括位置关系判断步骤：判断参考物与射束源模型的内部照射空间的位置关系。
在其中一个实施例中，所述位置关系判断步骤可在所述模型获取步骤中执行，在获取射束源模型时，根据射束源模型的内部照射空间的尺寸和被照射体的尺寸，判断被照射体是否可以伸入射束源模型的内部照射空间。
在其中一个实施例中，所述空间伸入判断步骤还包括组织类型判断步骤：判断伸入照射空间的被照射体的组织类型，根据被照射体的组织类型调整位置参数。
在其中一个实施例中，所述组织类型判断步骤中组织类型包括第一类组织和第二类组织，第一类组织为表层柔性组织，第二类组织为不可形变组织；
当被照射体的组织类型为第一类组织时，不需要调整被照射体三维体素模型或射束源模型的位置参数，或给出被照射体三维体素模型、射束源模型的位置参数的调整范围；
当被照射体为第二类组织时，调整被照射体三维体素模型或射束源模型的位置参数，或给出调整信号。
在其中一个实施例中，参考物由第二类组织中选取。
在其中一个实施例中，所述位置参数获取步骤中位置参数包括射束源模型和被照射体三维体素模型之间的相对距离、相对角度、射束照射方向。
在其中一个实施例中，所述重叠判断步骤中参考物包括体素网格的顶点、面心点、随机点、轮廓线或外表面中的一个、多个或全部。
在其中一个实施例中，所述重叠信号输出步骤中重叠提示信号包括重叠位置、重叠幅度和重叠体积。
在其中一个实施例中，所述模型获取步骤中射束源模型基于被照射体的医学影像数据选取。
第三方面，本发明提供了一种治疗计划的制定方法，其特征在于，包括：
模型数据获取步骤：获取被照射体的医学影像数据，并基于医学影像数据建立被照射体三维体素模型，被照射体三维体素模型包括若干个体素网格；
位置参数确定步骤：确定射束源模型和被照射体三维体素模型的位置参数；
重叠判断步骤：判断体素网格与射束源的位置关系并调整位置参数；
治疗计划生成步骤：生成治疗计划。
在其中一个实施例中，所述重叠判断步骤前还包括参考物选取步骤：在若干个体素网格中选取参考物；所述重叠判断步骤中基于参考物与射束源模型的位置关系来判断被照射体三维体素模型与射束源模型的位置关系。
在其中一个实施例中，在所述参考物选取步骤或所述重叠判断步骤之前或开始参考物选取步骤或所述重叠判断步骤时，还包括网格类型判断步骤：
当判断体素网格为第一类网格时，在该网格中选择参考物并执行所述重叠判断步骤，当判断体素网格为第二类网格时，不在该网格中选择参考物且不执行所述重叠判断步骤；
其中，体素网格的类型包括第一类网格和第二类网格，第一类网格由被照射体的组织组成，第二类网格由空气组成。
在其中一个实施例中，所述重叠判断步骤包括位置调整步骤：当参考物与射束源模型重叠时，自动调整射束源模型或被照射体三维体素模型的位置参数，直至参考物与射束源模型不重叠。
在其中一个实施例中，所述重叠判断步骤还包括重叠信号输出步骤：当参考物与射束源模型重叠时，输出重叠提示信号。
在其中一个实施例中，所述重叠判断步骤还包括空间伸入判断步骤：判断被照射体三维体素模型是否伸入射束源模型的内部照射空间，并调整被照射体三维体素模型与射束源模型的位置参数。
在其中一个实施例中，所述空间伸入判断步骤包括位置关系判断步骤：判断参考物与射束源模型的内部照射空间的位置关系。
在其中一个实施例中，所述位置关系判断步骤可在所述位置参数确定步骤中执行，在获取射束源模型时，根据射束源模型的内部照射空间的尺寸和被照射体的尺寸，判断被照射体是否可以伸入射束源模型的内部照射空间。
在其中一个实施例中，所述空间伸入判断步骤还包括组织类型判断步骤：判断伸入照射空间的被照射体的组织类型，根据被照射体的组织类型调整位置参数。
在其中一个实施例中，所述组织类型判断步骤中组织类型包括第一类组织和第二类组织，第一类组织为表层柔性组织，第二类组织为不可形变组织；
当被照射体的组织类型为第一类组织时，不需要调整被照射体三维体素模型或射束源模型的位置参数，或给出被照射体三维体素模型、射束源模型的位置参数的调整范围；
当被照射体为第二类组织时，调整被照射体三维体素模型或射束源模型的位置参数，或给出调整信号。
在其中一个实施例中，参考物由第二类组织中选取。
在其中一个实施例中，所述位置参数确定步骤中位置参数包括射束源模型和被照射体三维体素模型之间的相对距离、相对角度、射束照射方向。
在其中一个实施例中，所述重叠判断步骤中参考物包括体素网格的顶点、面心点、随机 点、轮廓线或外表面中的一个、多个或全部。
在其中一个实施例中，所述重叠信号输出步骤中重叠提示信号包括重叠位置、重叠幅度和重叠体积。
在其中一个实施例中，所述模型获取步骤中射束源模型基于被照射体的医学影像数据选取。
本发明提供的治疗计划系统，通过设置影像处理模块、数据处理模块、重叠检测模块和治疗计划生成模块，得到被照射体三维体素模型的体素网格、射束源模型和被照射体三维体素模型的位置参数等信息，再通过重叠检测模块来判断被照射体三维体素模型和射束源模型是否重叠及合理，从而判断在该治疗方案下准直器与患者组织是否重叠及合理，检验治疗方案是否会导致摆位时准直器与患者组织发生碰撞，且所有流程均能够通过治疗计划系统自动完成检查和判断，进而能够提前为物理师提供指导，使得物理师能够更快地修正治疗计划，且治疗计划系统能够自动生成相应的治疗计划。
附图说明
图1为本发明实施例的治疗计划系统的示意图；
图2为硼中子捕获反应示意图；
图3为10B(n,α)7Li中子捕获核反应方程式；
图4为本发明实施例的中子捕获治疗系统的框图；
图5为本发明实施例的重叠自动检查方法的流程图；
图6为本发明其他实施例的重叠自动检查方法的流程图；
图7为本发明实施例的治疗计划的制定方法的流程图。
附图标号说明：
100硼中子捕获治疗设施；10中子束射束源；20治疗计划系统；30控制系统；1影像处
理模块；2数据处理模块；3重叠检测模块；4治疗计划生成模块。
具体实施方式
为了使本申请的目的、技术方案及优点更加清楚明白，以下结合附图及实施例，对本申请进行进一步详细说明。应当理解，此处描述的具体实施例仅仅用以解释本申请，并不用于限定本申请。
如图1所示，本发明提供了一种治疗计划系统20，能够判断被照射体和射束源是否重叠并生成相应的治疗计划。
作为本实施例的一种实施方式，治疗计划为执行放射线治疗的治疗计划，优选的，为执行中子捕获治疗的治疗计划，更优选的，为执行硼中子捕获治疗的治疗计划，本发明一实施例以硼中子捕获治疗为例进行简单介绍。
中子捕获治疗作为一种有效的治疗癌症的手段近年来的应用逐渐增加，其中以硼中子捕获治疗最为常见。硼中子捕获治疗(Boron Neutron Capture Therapy,BNCT)是利用含硼(10B)药物对热中子具有高捕获截面的特性，借由10B(n,α)7Li中子捕获及核分裂反应产生4He和7Li两个重荷电粒子。参照图2和图3，其分别示出了硼中子捕获反应的示意图和10B(n,α)7Li中子捕获核反应方程式，两荷电粒子的平均能量约为2.33MeV，具有高线性转移(Linear Energy Transfer,LET)、短射程特征，α粒子的线性能量转移与射程分别为150keV/μm、8μm，而7Li重荷粒子则为175keV/μm、5μm，两粒子的总射程约相当于一个细胞大小，因此对于生物体造成的辐射伤害能局限在细胞层级，当含硼药物选择性地聚集在肿瘤细胞中，搭配适当的中子射源，便能在不对正常组织造成太大伤害的前提下，达到局部杀死肿瘤细胞的目的。
硼中子捕获治疗的中子可以由核反应堆或加速器供应。本发明一实施例以加速器硼中子捕获治疗为例，加速器对带电粒子(如质子、氘核等)进行加速，加速的带电粒子与金属靶材作用产生中子，依据所需的中子产率与能量、可提供的加速带电粒子能量与电流大小、金属靶材的物化性等特性来挑选合适的核反应，常被讨论的核反应有7Li(p,n)7Be及9Be(p,n)9B，这两种反应皆为吸热反应。两种核反应的能量阀值分别为1.881MeV和2.055MeV，由于硼中子捕获治疗的理想中子源为keV能量等级的超热中子，理论上若使用能量仅稍高于阀值的质子轰击金属锂靶材，可产生相对低能的中子，不须太多的缓速处理便可用于临床，然而锂金属(Li)和铍金属(Be)两种靶材与阀值能量的质子作用截面不高，为产生足够大的中子通量，通常选用较高能量的质子来引发核反应。
蒙特卡罗方法能够对辐照目标内部三维空间核粒子碰撞轨迹和能量分布进行精确模拟，在硼中子捕获治疗中，为了模拟人体在一定辐射条件下的吸收剂量以帮助医生制定治疗计划，常常需要利用计算机技术对医学影像进行各种处理建立精确的蒙特卡罗软件需要的晶格模型，并结合蒙特卡罗软件进行模拟计算。医学影像数据可以为核磁共振成像(Magnetic Resonance Imaging,MRI)、电子计算机断层扫描(Computed Tomography,CT)、正电子发射型计算机断层扫描(Positron Emission Tomography,PET)、PET-CT或X射线成像(X-Ray imaging)，本实施例中将基于电子计算机断层扫描(CT)的数据来阐述，CT的文件格式通常为DICOM。但本领域技术人员熟知地，还可以使用其他的医学影像数据，只要该医学影像数据能够被转换成三维体素假体组织模型，就能够应用于本发明揭示的模块化治疗计划系统及系统构建方法中。
参阅图4，硼中子捕获治疗设施100包括中子束射束源10、治疗计划系统20和控制系统30。中子束射束源10包括中子产生装置和治疗台，中子产生装置产生治疗用中子束N并照射到治疗台上的患者的被照射部位。治疗计划系统20根据患者的医学影像数据生成治疗计划，控制系统30基于治疗计划控制中子束射束源10执行照射治疗。在一实施例中，治疗计划系统20内存储有患者的组织模型模板库，治疗计划系统20根据组织模型模板库建立被照射部位的医学影像数据对应的三维体素假体组织模型，并基于三维体素假体组织模型通过蒙特卡罗模拟程序模拟计算患者进行照射治疗时的剂量分布并生成治疗计划。预先设定组织模型模板库，防止由于医师等操作者个人经验的差异，导致建立的模型及剂量计算不精确；同时，避免花费大量的时间精力在模型中晶格的生物体基本信息的定义上。控制系统30从治疗计划系统20调取当前患者对应的治疗计划，并根据治疗计划控制中子束射束源10的照射。
中子产生装置包括中子产生部、射束整形体及准直器。中子产生部包括加速器和靶材，加速器用于对带电粒子(如质子、氘核等)进行加速，产生如质子线的带电粒子线，带电粒子线照射到靶材并与靶材作用产生中子线(中子束)，靶材优选为金属靶材。依据所需的中子产率与能量、可提供的加速带电粒子能量与电流大小、金属靶材的物化性等特性来挑选合适的核反应，常被讨论的核反应有7Li(p,n)7Be及9Be(p,n)9B，这两种反应皆为吸热反应。本发明的实施例中采用锂金属制成的靶材。但是本领域技术人员熟知的，靶材的材料也可以由锂、铍之外的金属材料制成，例如由钽(Ta)或钨(W)等形成；靶材可以为圆板状，也可以为其他固体形状，也可以使用液状物(液体金属)；加速器可以是直线加速器、回旋加速器、同步加速器、同步回旋加速器。在其他实施方式在，中子产生部可以是核反应堆而不采用加速器和靶材。
无论硼中子捕获治疗的中子源来自核反应堆或加速带电粒子与靶材的核反应，产生的实际上皆为混合辐射场，即产生的射束包含了低能至高能的中子、光子。对于深部肿瘤的硼中子捕获治疗，除了超热中子外，其余的放射线含量越多，造成正常组织非选择性剂量沉积的比例越大，因此这些会造成不必要剂量沉积的放射线含量应尽量降低。射束整形体能够调整中子产生装置产生的中子束的射束品质，降低不必要的剂量沉积，准直器用以汇聚中子束，使中子束在进行治疗的过程中具有较高的靶向性。
射束整形体包括反射体、缓速体、热中子吸收体、辐射屏蔽体和射束出口。缓速体能够将从中子产生装置出来的快中子能量(＞40keV)调整到超热中子能区(0.5eV-40keV)并尽可能减少热中子(＜0.5eV)含量；缓速体由与快中子作用截面大、与超热中子作用截面小的材料制成，作为一种优选实施例，缓速体由D2O、AlF3、FluentalTM、CaF2、Li2CO3、MgF2和Al2O3中的至少一种制成；反射体包围缓速体，并将穿过缓速体向四周扩散的中子反射回 中子射束以提高中子的利用率，其由中子反射能力强的材料制成，作为一种优选实施例，反射体由Pb或Ni中的至少一种制成；在中子束的传输路径上，热中子吸收体设置于缓速体后部，用于吸收穿过缓速体的热中子以减少中子束中热中子的含量，其由与热中子作用截面大的材料制成，作为一种优选实施例，热中子吸收体由Li-6制成，在其他实施例中，由于缓速体的材料中含有Li-6，热中子吸收体可以不单独设置，而是以缓速体作为热中子吸收体；辐射屏蔽体用于屏蔽从出束口以外部分渗漏的中子和光子，辐射屏蔽体的材料包括光子屏蔽材料和中子屏蔽材料中的至少一种，作为一种优选实施例，辐射屏蔽体的材料包括光子屏蔽材料铅(Pb)和中子屏蔽材料聚乙烯(PE)。
准直器设置在射束出口后部，从准直器出来的超热中子束照向被照射体，超热中子束经被照射体的浅层正常组织后被缓速为热中子到达肿瘤细胞实现治疗目的。
本发明实施例的治疗计划包括对被照射体实施放射治疗所需要的照射条件。照射条件包括位置参数和剂量参数等。位置参数包括能够表示被照射体模型和射束源模型的相对位置的坐标信息、照射源的各种坐标信息或相对位置信息，以及上述相对位置所指示的角度或方向。在制定治疗计划过程中，进行剂量参数计算前，一般需要先计算位置参数。
通常射束源所在的位置位于准直器入口处或准直器出口处(靠近被照射体那边)。在某些情况下，被照射体无法伸入准直器内部，从计算效率上看，准直器出口处的射束源离被照射体更近，因而选择准直器出口作为射束源所在的位置能够更快地计算剂量分布，在这种情况下，出口处射束源信息是基于准直器内部为空气的情况下制作的，为了实现合理制定治疗位置及计算出准确的治疗剂量，被照射体不仅不可以与准直器重叠，也不可以与准直器内部的空间重叠。在另外一些情况下，被照射体的治疗部位可以伸入准直器，就选择准直器入口作为射束源所在的位置计算剂量分布，在这种情况下，照射体的组织不可以与准直器重叠。在传统方式中，用户或物理师需要治疗计划制定后，在模拟治疗或者实际治疗时，肉眼观察或者基于经验判断是否重叠，或者判断重叠是否合理，会导致整个治疗过程比较繁琐。
基于此，本实施例的治疗计划系统20包括影像处理模块1、数据处理模块2、重叠检测模块3和治疗计划生成模块4。
影像处理模块1用于获取被照射体的医学影像数据，医学影像数据一般通过外部的扫描设备获取。影像处理模块1基于医学影像数据建立被照射体三维体素模型，被照射体三维体素模型包括若干个体素网格，由影像处理模块1建立描述被照射体三维体素模型的体素网格。
数据处理模块2用于获取射束源模型以及确定射束源模型和被照射体三维体素模型的位置参数。
进一步地，数据处理模块2从影像处理模块1中获取被照射体三维体素模型，从预设的 库中获取射束源模型。预设的库中可以包括不同形状和尺寸的射束源模型，以供数据处理模块2获取与被照射体三维体素模型适配的射束源模型。
进一步地，数据处理模块2还能够通过被照射体三维体素模型或医学影像数据选择合适的射束源模型。在其他可选的实施方式中，被照射体三维体素模型可以由用户输入或选择，数据处理模块2可以通过用户的输入或选择调用相应的射束源模型。数据处理模块2通过被照射体三维体素模型和选取的射束源模型计算位置参数，位置参数包括射束源模型和被照射体三维体素模型之间的相对距离、相对角度、射束照射方向。应当知道的是，数据处理模块2还能根据影像数据或被照射体三维体素模型计算出照射参数。可以理解，本发明可以不具有准直器，射束从射束整形体的射束出口出来后直接照射向被照射体，为描述方便，当设置有准直器时，准直器的出口解释为射束出口，构成射束出口的装置统称为射束源，本发明中的射束源模型即构成射束出口的装置的模型。
进一步地，在其他可选的实施方式中，在选择射束源模型的同时也确定射束源所在的位置，也就是选择制定治疗计划时，被照射体的治疗部位是否会伸入准直器内。
进一步地，射束源的射束出口处形成有照射空间，照射空间由射束出口的外周包围而成，例如，照射空间可以是放射状的开口。
重叠检测模块3用于判断体素网格与射束源的位置关系。本实施例中重叠检测模块3基于参考物与射束源模型的位置关系来判断体素网格与射束源模型的位置关系，其中，参考物在至少部分体素网格中选取，参考物包括体素网格的顶点、面心点、随机点、轮廓线或外表面中的一个、多个或全部。具体地，体素网格的类型包括第一类网格和第二类网格，第一类网格填充被照射体的组织，第一类网格的组织指的是被照射体的器官、血管、骨骼、肌肉、脂肪、皮肤等组成人体的有机或无机的组分，第二类网格填充空气，其中，参考物选取于第一类网格。
进一步地，重叠检测模块3可以判断被照射体三维体素模型和射束源模型的位置关系是否合理。具体地，重叠检测模块3或数据处理模块2能够判断体素网格属于第一类网格或第二类网格；当判断体素网格为第一类网格时，在该网格中选择参考物，或执行后续的重叠判断，或使重叠检测模块3执行后续的重叠判断；当判断体素网格为第二类网格时，不在该网格中选择参考物且不执行后续的判断步骤。重叠检测模块3根据参考物与射束源模型的位置关系判断参考物与射束源模型是否重叠，并调整位置参数。
进一步地，作为一种实施方式，当重叠检测模块3判断参考物与射束源模型重叠时，调整被照射体三维体素模型的位置或者射束源模型的位置，输出信号至数据处理模块2使其重新计算位置参数，并获得新的位置参数再次进行重叠判断，直到参考物与射束源模型不重叠。
进一步地，作为另一种实施方式，当重叠检测模块3判断参考物与射束源模型重叠时，输出信号至数据处理模块2，数据处理模块2调整并重新计算被照射体三维体素模型的位置参数或者射束源模型的位置参数，重叠检测模块3获得新的位置参数再次进行判断，直到参考物与射束源模型不重叠。
值得注意的是，上述实施例均是基于被照射体的治疗部位不可以伸入准直器内部，即被照射体的组织不仅不可以与射束源模型重叠，也不可以与射束源的内部照射空间重叠。
进一步地，在其他可选的实施方式中，重叠检测模块3还可以判断被照射体三维体素模型和射束源的内部照射空间的位置关系是否合理，即判断被照射体三维体素模型是否允许伸入射束源的内部照射空间、判断伸入射束源的内部照射空间的被照射体三维体素模型是否和射束源模型重叠，并且在选择射束源模型时就判断并确定被照射体的治疗部位是否可以伸入射束源的内部照射空间内。当重叠检测模块3判断参考物与射束源模型重叠时，即可判断伸入射束源的内部照射空间的被照射体三维体素模型与射束源模型是否重叠。
进一步地，重叠检测模块3还可用于判断重叠的参考物的组织类型，其中，组织类型包括第一类组织和第二类组织，第一类组织为皮肤等表层组织或者是皮肤、肌肉、脂肪等表层柔性组织；第二类组织为骨骼等不可形变组织；参考物由第二类组织中选取。具体地，如果重叠的参考物的组织类型为第一类组织，根据重叠范围判断是否需要调整位置参数或由治疗计划系统20给出位置参数的调整范围；如果重叠的参考物的组织类型为第二类组织，则需要调整被照射体的位置或者射束源模型的位置。调整后再经由数据处理模块2计算位置参数后由重叠检测模块3判断，或经由重叠检测模块3直接进行判断。当参考物与射束源模型确认合理，输出此时的位置参数至治疗计划生成模块4，进行剂量计算，进而制定治疗计划。
进一步地，作为另一种实施方式，重叠检测模块3还可用于输出参考物与射束源的重叠提示信号，供用户或物理师判断是否需要调整被照射体和射束源之间的相对位置关系，若需要调整，调整后再经由数据处理模块2计算后由重叠检测模块3判断，或经由重叠检测模块3直接进行判断。具体地，本实施例中重叠提示信号包括重叠位置、重叠幅度和重叠体积等。当参考物与射束源模型确认位置关系合理，输出此时的位置参数至治疗计划生成模块4，进行剂量计算，进而制定治疗计划。
如图5所示，本发明实施例还包括一种基于治疗计划的重叠自动检查方法。所述方法包括：
S100、模型获取步骤：获取被照射体三维体素模型和射束源模型，被照射体三维体素模型包括若干个体素网格；
S200、位置参数获取步骤：获取射束源模型和被照射体三维体素模型的位置参数；
S300、重叠判断步骤：基于体素网格与射束源模型的位置关系判断被照射体三维体素模型与射束源模型的位置关系。
在重叠判断步骤之前还包括S400、参考物选取步骤：在若干个体素网格中选取参考物；在S300、重叠判断步骤中基于参考物与射束源模型的位置关系来判断被照射体三维体素模型与射束源模型的位置关系。
在S100、模型获取步骤中，所获取的射束源模型已经预设或通过其他装置导入在治疗计划系统20中。具体的，射束源模型包含多个，均预先存储在治疗计划系统20中，可供医生基于被照射体的医学影像数据进行选择。被照射体三维体素模型基于被照射体的医学影像数据建立，被照射体三维体素模型包括若干个体素网格。
在S200、位置参数获取步骤中，射束源模型和被照射体三维体素模型的位置参数至少包括射束源模型和被照射体三维体素模型之间的相对距离、相对角度和射束照射方向，治疗计划系统20根据医学影像数据计算并输出该位置参数。
在S400、参考物选取步骤或S300、重叠判断步骤之前或开始S400、参考物选取步骤或S300、重叠判断步骤时，还包括S500、网格类型判断步骤：
当判断体素网格为第一类网格时，在该网格中选择参考物并执行所述重叠判断步骤，当判断体素网格为第二类网格时，不在该网格中选择参考物且不执行所述重叠判断步骤；
其中，体素网格的类型包括第一类网格和第二类网格，第一类网格由被照射体的组织组成，第二类网格由空气组成。具体地，第一类网格的组织指的是被照射体的器官、血管、骨骼、肌肉、脂肪、皮肤等组成人体的有机或无机的组分。在S400、参考物选取步骤中，参考物从第一类网格中选取。体素网格一般为多面体，在本实施例中，体素网格为六面体，参考物为体素网格的点、线或面。为了简化计算过程便和减小计算对系统内存的占用，优选体素网格的点作为参考物，在本实施例中，参考物为体素网格的顶点，其中一个优选的实施方式，判断第一类体素网格的八个顶点是否与射束源模型重叠，有任意一个顶点与射束源模型重叠，则判定被照射体三维体素模型与射束源模型重叠。在其他实施例中，参考物包括但不限于体素网格的面心点、随机点、轮廓线或外表面中的一个、多个或全部，例如随机点可以是在体素网格中选取随机抽样点，模拟足够多的随机点作为参考物。
进一步地，S300、重叠判断步骤包括S310、位置调整步骤：当参考物与射束源模型重叠时，自动调整射束源模型或被照射体三维体素模型的位置参数，直至参考物与射束源模型不重叠。
进一步地，为了简化调整过程和减小计算对系统的内存占用，调整射束源模型或被照射体三维体素模型的位置参数时，可以只调整射束源模型和被照射体三维体素模型的相对位置， 不调整射束照射方向，即在调整射束源模型和被照射体三维体素模型的相对位置时，沿射束照射方向平移，保证调整后对其他参数变化影响最小。所有流程能够利用治疗计划系统20自动完成检查判断和调整，提高了所输出治疗计划的准确性，避免了不适配实际摆位的问题。
进一步地，S300、重叠判断步骤还包括S320、重叠信号输出步骤：当参考物与射束源模型重叠时，输出重叠提示信号，供用户或物理师判断是否需要调整被照射体和射束源之间的相对位置关系，若需要调整，根据重叠提示信号进行调整，调整后重复S300、重叠判断步骤。进一步的，重叠提示信号可以包括重叠位置、重叠幅度、重叠体积等等，供用户或物理师参考进行相对位置的调整。
进一步地，S300、重叠判断步骤还包括S330、空间伸入判断步骤：判断被照射体三维体素模型是否伸入射束源模型的内部照射空间，并调整被照射体三维体素模型与射束源模型的位置参数。
进一步地，S330、空间伸入判断步骤还可以包括以下步骤：
S331、位置关系判断步骤：判断参考物与射束源模型的内部照射空间的位置关系。与步骤S300、S400中判断重叠的方式相似，本步骤中通过选取参考物并判断参考物的位置关系来判断是否允许被照射体三维体素模型伸入射束源模型的内部照射空间以及被照射体三维体素模型是否伸入照射空间。进一步地，本实施例中S331、位置关系判断步骤也可以在S100、模型获取步骤中执行，在选择射束源模型时，根据射束源模型中内部照射空间的尺寸和被照射体尺寸，判断被照射体是否可以伸入内部照射空间内，尤其判断被照射体中的治疗部位是否可以伸入内部照射空间内。
S332、组织类型判断步骤：判断伸入照射空间的被照射体的组织类型，根据被照射体的组织类型调整位置参数。本实施例中通过判断体素网格或参考物的类型判断被照射体的组织类型，具体地，组织类型包括第一类组织和第二类组织，第一类组织为表层柔性组织，包括皮肤、肌肉、脂肪等，第二类组织为不可形变组织，例如骨骼等；进一步地，当被照射体的组织类型为第一类组织时，不需要调整被照射体三维体素模型或射束源模型的位置参数，或给出被照射体三维体素模型、射束源模型的位置参数的调整范围；当被照射体为第二类组织时，调整被照射体三维体素模型或射束源模型的位置参数，或给出调整信号。参考物可以从第二类组织中选取。
具体地，S331、位置关系判断步骤和S332、组织类型判断步骤无先后顺序的限定，可以先判断被照射体类型再选择参考物，也可以在所有类型组织中选择参考物后，再判断符合要求的参考物的位置关系。
治疗计划生成模块4基于调整后的位置参数生成治疗计划。当有重叠发生对位置参数重 新进行调整时，治疗计划生成模块4会基于数据处理模块2得到的照射参数和调整后的未知参数重新计算照射参数，所生成的治疗计划包含调整后的位置参数和新的照射参数。进一步的，当位置参数调整时，主要调整的是被照射体三维体素模型和射束源模型的相对位置，在方向参数不改变的情况下，重新计算照射参数时可以只重新计算剂量参数。
上述治疗计划系统20中的各个模块可全部或部分通过软件、硬件及其组合来实现。上述各模块可以硬件形式内嵌于或独立于计算机设备中的处理器中，也可以以软件形式存储于计算机设备中的存储器中，以便于处理器调用执行以上各个模块对应的操作。
其中，治疗计划系统200还可以包含终端、通信模块、服务器、数据存储模块等。终端通过通信模块与服务器进行通信。影像处理模块1、数据处理模块2、重叠检测模块3和治疗计划生成模块4可以集成在终端内。其中，终端可以但不限于是各种个人计算机、笔记本电脑、智能手机、平板电脑、物联网设备和便携式可穿戴设备，物联网设备可为智能音箱、智能电视、智能空调、智能车载设备等。便携式可穿戴设备可为智能手表、智能手环、头戴设备等。数据存储模块可以集成在服务器1上，也可以放在云上或其他网络服务器上。数据存储模块包括非易失性存储介质、内存储器。该非易失性存储介质存储有影像处理模块1、数据处理模块2、重叠检测模块3和治疗计划生成模块4涉及的程序和数据，以及存储有操作系统和计算机程序。该内存储器为非易失性存储介质中的操作系统和计算机程序的运行提供环境。服务器可以用独立的服务器或者是多个服务器组成的服务器集群来实现。通信模块用于与外部的终端进行有线或无线方式的通信，无线方式可通过WIFI、移动蜂窝网络、NFC(近场通信)或其他技术实现。
终端还包括显示设备和输入装置。影像处理模块1、数据处理模块2、重叠检测模块3和治疗计划生成模块4可以通过显示设备呈现相应的数据和界面。像处理模块1、数据处理模块2、重叠检测模块3和治疗计划生成模块4可以通过输入装置获取用户输入的参数。显示设备尤其可以是一种显示屏，显示屏可以是液晶显示屏或者电子墨水显示屏。输入装置可以是显示屏上覆盖的触摸层，也可以是终端上设置的按键、轨迹球或触控板，还可以是外接的键盘、触控板或鼠标等。
如图7所示，本发明实施例还包括一种治疗计划制定方法，作为上述治疗计划系统20的运行方式，能够判断重叠情况并生成相应的治疗计划，与前述内容相同或相似的部分不做赘述。治疗计划制定方法包括以下步骤：
A100、模型数据获取步骤：获取被照射体的医学影像数据，并基于医学影像数据建立被照射体三维体素模型，被照射体三维体素模型包括若干个体素网格；
A200、位置参数确定步骤：确定射束源模型和被照射体三维体素模型的位置参数；
A300、重叠判断步骤：判断体素网格与射束源的位置关系并调整位置参数；
A400、治疗计划生成步骤：生成治疗计划。
进一步地，本实施例中A300、重叠判断步骤前还包括A500、参考物选取步骤：在若干个体素网格中选取参考物；A300、重叠判断步骤中基于参考物与射束源模型的位置关系来判断被照射体三维体素模型与射束源模型的位置关系。
进一步地，本实施例中A500、参考物选取步骤还包括：
A501、判断体素网格属于第一类网格或是第二类网格；
A502、在第一类网格中选取参考物。
进一步地，本实施例中A300、重叠判断步骤还包括：
A301、判断参考物与射束源模型是否重叠，或判断参考物是否伸入射束源模型。
A302、当参考物与射束源模型重叠或伸入其中时，调整位置参数，并重复步骤A301；当参考物与射束源模型不重叠或不伸入其中时，执行步骤A400。当参考物与射束源从一开始就不存在重叠时，生成的治疗计划包括步骤A200中确定的位置参数。
应该理解的是，虽然如上所述的各实施例所涉及的流程图中的各个步骤按照编号、箭头或连接线的指示依次显示，但是这些步骤并不是必然按照编号指示的顺序依次执行。除非本文中有明确的说明，这些步骤的执行并没有严格的顺序限制，这些步骤可以以其它的顺序执行。而且，如上所述的各实施例所涉及的流程图中的至少一部分步骤可以包括多个步骤或者多个阶段，这些步骤或者阶段并不必然是在同一时刻执行完成，而是可以在不同的时刻执行，这些步骤或者阶段的执行顺序也不必然是依次进行，而是可以与其它步骤或者其它步骤中的步骤或者阶段的至少一部分轮流或者交替地执行。
本领域普通技术人员可以理解实现上述实施例方法中的全部或部分流程，是可以通过计算机程序来指令相关的硬件来完成，所述的计算机程序可存储于一非易失性计算机可读取存储介质中，该计算机程序在执行时，可包括如上述各方法的实施例的流程。其中，本申请所提供的各实施例中所使用的对存储器、数据库或其它介质的任何引用，均可包括非易失性和易失性存储器中的至少一种。非易失性存储器可包括只读存储器(Read-Only Memory，ROM)、磁带、软盘、闪存、光存储器、高密度嵌入式非易失性存储器、阻变存储器(ReRAM)、磁变存储器(Magnetoresistive Random Access Memory，MRAM)、铁电存储器(Ferroelectric Random Access Memory，FRAM)、相变存储器(Phase Change Memory，PCM)、石墨烯存储器等。易失性存储器可包括随机存取存储器(Random Access Memory，RAM)或外部高速缓冲存储器等。作为说明而非局限，RAM可以是多种形式，比如静态随机存取存储器(Static Random Access Memory，SRAM)或动态随机存取存储器(Dynamic Random Access Memory， DRAM)等。本申请所提供的各实施例中所涉及的数据库可包括关系型数据库和非关系型数据库中至少一种。非关系型数据库可包括基于区块链的分布式数据库等，不限于此。本申请所提供的各实施例中所涉及的处理器可为通用处理器、中央处理器、图形处理器、数字信号处理器、可编程逻辑器、基于量子计算的数据处理逻辑器等，不限于此。
以上实施例的各技术特征可以进行任意的组合，为使描述简洁，未对上述实施例中的各个技术特征所有可能的组合都进行描述，然而，只要这些技术特征的组合不存在矛盾，都应当认为是本说明书记载的范围。
以上所述实施例仅表达了本申请的几种实施方式，其描述较为具体和详细，但并不能因此而理解为对本申请专利范围的限制。应当指出的是，对于本领域的普通技术人员来说，在不脱离本申请构思的前提下，还可以做出若干变形和改进，这些都属于本申请的保护范围。因此，本申请的保护范围应以所附权利要求为准。
以上实施例的各技术特征可以进行任意的组合，为使描述简洁，未对上述实施例中的各个技术特征所有可能的组合都进行描述，然而，只要这些技术特征的组合不存在矛盾，都应当认为是本说明书记载的范围。
以上所述实施例仅表达了本申请的几种实施方式，其描述较为具体和详细，但并不能因此而理解为对本申请专利范围的限制。应当指出的是，对于本领域的普通技术人员来说，在不脱离本申请构思的前提下，还可以做出若干变形和改进，这些都属于本申请的保护范围。因此，本申请的保护范围应以所附权利要求为准。

Claims (16)

  1. 一种治疗计划系统，其特征在于，包括：
    影像处理模块，用于获取被照射体的医学影像数据，并基于所述医学影像数据建立被照射体三维体素模型，所述被照射体三维体素模型包括若干个体素网格；
    数据处理模块，用于获取射束源模型以及确定所述射束源模型和所述被照射体三维体素模型的位置参数；
    重叠检测模块，用于判断所述体素网格与所述射束源的位置关系；
    治疗计划生成模块，用于生成治疗计划。
  2. 根据权利要求1所述的治疗计划系统，其特征在于，所述重叠检测模块基于参考物与所述射束源模型的位置关系来判断所述体素网格与所述射束源模型的位置关系，其中，所述参考物由若干个所述体素网格中选取。
  3. 根据权利要求1所述的治疗计划系统，其特征在于，所述重叠检测模块可用于判断所述参考物与所述射束源、所述参考物与所述射束源的内部照射空间的位置关系。
  4. 根据权利要求2所述的治疗计划系统，其特征在于，所述重叠检测模块可用于判断体素网格的类型。
  5. 根据权利要求4所述的治疗计划系统，其特征在于，所述体素网格的类型包括第一类网格和第二类网格，所述第一类网格由所述被照射体的组织组成，所述第二类网格由空气组成，其中，所述参考物选取于所述第一类网格。
  6. 根据权利要求2所述的治疗计划系统，其特征在于，所述重叠检测模块可用于判断重叠的所述参考物的组织类型。
  7. 根据权利要求6所述的治疗计划系统，其特征在于，所述组织类型包括第一类组织和第二类组织，所述第一类组织为表层柔性组织，所述第二类组织为不可形变组织。
  8. 根据权利要求7所述的治疗计划系统，其特征在于，所述参考物由所述第二类组织中选取。
  9. 根据权利要求2所述的治疗计划系统，其特征在于，所述参考物包括所述体素网格的顶点、面心点、随机点、轮廓线或外表面中的一个、多个或全部。
  10. 根据权利要求1所述的治疗计划系统，其特征在于，所述位置参数包括所述射束源模型和所述被照射体三维体素模型之间的相对距离、相对角度、射束照射方向。
  11. 一种重叠自动检查方法，其特征在于，包括：
    模型获取步骤：获取被照射体三维体素模型和射束源模型，被照射体三维体素模型包括若干个体素网格；
    位置参数获取步骤：获取射束源模型和被照射体三维体素模型的位置参数；
    重叠判断步骤：基于体素网格与射束源模型的位置关系判断被照射体三维体素模型与射束源模型的位置关系。
  12. 根据权利要求11所述的重叠自动检查方法，其特征在于，在所述重叠判断步骤之前还包括参考物选取步骤：在若干个体素网格中选取参考物；所述重叠判断步骤中基于参考物与射束源模型的位置关系来判断被照射体三维体素模型与射束源模型的位置关系。
  13. 根据权利要求12所述的重叠自动检查方法，其特征在于，在所述参考物选取步骤或所述重叠判断步骤之前或开始参考物选取步骤或所述重叠判断步骤时，还包括网格类型判断步骤：
    当判断体素网格为第一类网格时，在该网格中选择参考物并执行所述重叠判断步骤，当判断体素网格为第二类网格时，不在该网格中选择参考物且不执行所述重叠判断步骤；
    其中，体素网格的类型包括第一类网格和第二类网格，第一类网格由被照射体的组织组成，第二类网格由空气组成。
  14. 根据权利要求12所述的重叠自动检查方法，其特征在于，所述重叠判断步骤包括位置调整步骤：当参考物与射束源模型重叠时，自动调整射束源模型或被照射体三维体素模型的位置参数，直至参考物与射束源模型不重叠。
  15. 根据权利要求12所述的重叠自动检查方法，其特征在于，所述重叠判断步骤还包括空间伸入判断步骤：判断被照射体三维体素模型是否伸入射束源模型的内部照射空间。
  16. 一种治疗计划的制定方法，其特征在于，包括：
    模型数据获取步骤：获取被照射体的医学影像数据，并基于医学影像数据建立被照射体三维体素模型，被照射体三维体素模型包括若干个体素网格；
    位置参数确定步骤：确定射束源模型和被照射体三维体素模型的位置参数；
    重叠判断步骤：判断体素网格与射束源的位置关系并调整位置参数；
    治疗计划生成步骤：生成治疗计划。
PCT/CN2023/130654 2022-11-11 2023-11-09 治疗计划系统、重叠自动检查方法及治疗计划的制定方法 Ceased WO2024099385A1 (zh)

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