Dosage calculation program, treatment device and dosage calculation method

Abstract

To provide a dosage calculation program, a treatment device, and a dosage calculation method capable of accelerating the calculation speed of the Monte Carlo simulation for radiation compared to a conventional technique.SOLUTION: A QA dosage calculation program (106c1) is a program executed by a treatment planning and quality assurance dosage calculation PC (106) that calculates the radiation dosage or dosage distribution irradiated to an irradiation target and causes the treatment planning and quality assurance dosage calculation PC (106) to execute a division procedure which divides the radiation passage region including the irradiation target region into multiple divided regions, and a calculation procedure which calculates the radiation dosage or dosage distribution using the same calculation condition within the divided regions divided in the division procedure. In the division procedure, the number and shape of the divided regions are determined by estimating an objective function.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present invention relates to a radiation dose calculation program, a treatment device, and a dose calculation method in a treatment device, a diagnostic device, or a nuclear facility that uses radiation. [Background technology]

[0002] As an example of a method for forming a three-dimensional model of a subject from a captured image containing voxels of different sizes, Patent Document 1 describes the following steps: (1) dividing slice data of the captured image into multiple regions such that each region contains a predetermined number of pixels; (2) when the pixels contained in one divided region all represent tissues or substances having the same characteristics, combining the pixels to replace them with one voxel data; (3) when one divided region contains pixels representing tissues or substances having different characteristics, defining the pixel data in the one region as mixed voxel data; (4) repeating steps (2) and (3) to obtain slice data including the replaced voxel data and the mixed voxel data; and (5) stacking the multiple slice data obtained by step (4) in multiple stages.

[0003] Non-Patent Document 1 describes a new variance reduction technique called Supervoxel Woodcock, which combines the Woodcock tracking technique with the supervoxel concept used in computer graphics. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2012-088771 A [Non-patent literature]

[0005] [Non-Patent Document 1] A. Behlouli, et al., “Improved Woodcock tracking on Monte Carlo simulations for medical applications”, 2019 Phys. Med. Biol. 63 225005 Summary of the Invention [Problem to be solved by the invention]

[0006] Radiation therapy includes treatment methods using X-rays (photons), treatment methods using charged particle beams or neutron beams, brachytherapy, etc. What they have in common is that they use the energy of radiation to cut the DNA of cancer cells, thereby killing them or suppressing their activity.

[0007] In X-ray therapy, electrons accelerated by an electric field are irradiated onto a metal target, and X-rays are emitted using the bremsstrahlung phenomenon. In particle beam therapy using charged particles such as protons or carbon, a charged particle beam accelerated by an accelerator called a synchrotron or cyclotron is transported to the treatment room by a beam transport system. Cancer treatment is carried out by irradiating the affected area of ​​a patient lying on a bed in the treatment room with this radiation.

[0008] Before radiation therapy, it is necessary to create an appropriate treatment plan for each patient using treatment planning software. In the treatment plan, the affected area is irradiated with the dose prescribed by the doctor, and the dose is reduced for important organs that should not be exposed to the radiation. The location and dose of radiation to be irradiated are determined. In the case of particle beam therapy, the energy of the particle beam must also be determined.

[0009] The method of determination involves modeling the inside of the patient's body, taking the sum of the residual between the radiation dose absorbed by each minute volume and the target dose as an evaluation function, and determining the above energy, irradiation position, and irradiation amount using an iterative calculation algorithm such as the gradient method or Newton's method so as to minimize this evaluation function. After the above irradiation position and irradiation amount have been determined, the treatment plan also includes a step of calculating the dose inside the patient's body and confirming whether the desired dose distribution is formed inside the patient's body.

[0010] After the treatment plan has been decided, quality assurance (QA) is carried out. Conventionally, quality assurance for radiation therapy is carried out outside of clinic hours, such as early in the morning, by using a water phantom and a small ion chamber to measure the radiation dose specified in the treatment plan, and it is confirmed that the irradiation position and dose match those in the plan.

[0011] In recent years, adaptive treatment has been used, which modifies the treatment plan according to the patient's condition on the day of treatment. The patient's condition on the day refers to the state of the patient's internal environment that affects the dose distribution, such as the state of a tumor swelling or shrinking during previous treatment, or the presence or absence of a runny nose in the head and neck area, or the presence or absence of air pockets in the digestive organs.

[0012] QA for adaptive therapy is performed within the treatment time, so it is not measured, but rather is performed using a dose calculation program separate from the treatment planning system. Monte Carlo simulation calculations are often used for this QA. In simulation calculations using the Monte Carlo method, radiation is considered as particles or rays, and tracking is performed within a three-dimensional model that reflects the density and chemical composition of internal tissues. During tracking, a certain time or space step is advanced, and the presence or absence and type of reaction are determined using random numbers, and the absorbed dose and secondary particles due to the reaction are calculated.

[0013] In radiation therapy such as that described above, when Monte Carlo calculations are performed in treatment planning (irradiation dose optimization step, dose distribution calculation step) or QA, the problem of long calculation times needs to be solved.

[0014] The length of the time or space step in the above Monte Carlo calculation (hereinafter referred to as the step length) generally does not span a microscopic volume. The reason is that the step length is generally expressed as the product of the mean free path of radiation and a random number, and the mean free path is determined by the type of radiation, energy, and the properties of the substance through which it passes.

[0015] Therefore, when the properties of the next microscopic volume are different, it is necessary to recalculate the mean free path.

[0016] For example, when tracking X-rays from an arbitrary point P1 to a point belonging to a voxel different from P1, if the mean free path distance in the microscopic volume A is L, the distance that can proceed without reaction is L. When the distance from the position of the particle to the boundary of the microscopic volume A is X1, if L>X1, an extra distance X2 (=L - X1) occurs, and this distance X2 will proceed in the next microscopic volume B. Here, let the reaction point, which is the end point of X2 at this time, be P3.

[0017] However, in this case, when the density of the microscopic volume B is higher than that of the microscopic volume A, if the recalculated mean free path (the distance that can proceed without reaction) is X3 and the reaction point in this case is P3', then X3 < X2 should hold. That is, when trying to track beyond the boundary of the microscopic volume to the end of the step length L, the reaction point shifts from P3' to P3, which corresponds to a decrease in the reaction rate.

[0018] Therefore, even when the step length is larger than the size of the microscopic volume, it is common practice to stop tracking at the boundary and resume tracking in the next microscopic volume with the same energy, the same propagation direction, and the recalculated mean free path.

[0019] The scale of the above-mentioned microvolume is about the resolution of a CT image, and with the recent progress of imaging diagnostic equipment, a resolution of less than 1 mm has become possible, and it is expected to become even smaller in the future. However, the smaller the scale of the microdeposition, the longer the calculation time, so in order to actually reduce the calculation time, it is sometimes made larger than the resolution of a CT image. In that case, it is generally about 1 mm to 3 mm.

[0020] Even so, the number of microvolumes in just one slice (a CT image in the XY plane) is 10 4 pcs to 10 6 One of the reasons why Monte Carlo calculations of radiation are slow is that tracking must be stopped at the boundary of a small volume to determine whether a reaction has occurred or not and to recalculate the free path.

[0021] To avoid this, a method that does not stop tracking at the boundary of the microvolume can be considered. For example, en is the largest (μ max ) A fixed step length is calculated according to the material. This fixed step length is the free path for heavy materials, and since it is guaranteed that the distance traveled without reaction is not too long when crossing the boundary of a small volume, recalculation of the free path is not required. The increase in reaction rate due to matching the step to the heavy material is solved by introducing a virtual reaction. The reaction rate of the virtual reaction is P=1-μ local / μ max Here, μ max is the largest energy absorption coefficient, μ local is the energy absorption coefficient of the tracking arrival position.

[0022] However, actual medical CT images always have regions where the air is the main component and regions where there is bone, and can be said to be a system with a large density difference. When tracking with the fixed step method described above, calculations are performed on the free path inside the bone, so the calculation time inside the air or soft tissue may be long, and the effect of speeding up may be reduced.

[0023] The present invention provides a dose calculation program, a treatment apparatus, and a dose calculation method that can increase the calculation speed of a Monte Carlo simulation of radiation compared to the conventional methods. [Means for solving the problem]

[0024] The present invention includes a number of means for solving the above-mentioned problems. One example is a program to be executed by a dose calculation system for calculating an exposure dose or dose distribution of radiation irradiated to an irradiation object, the program causing the dose calculation system to execute a division procedure for dividing an area through which the radiation passes, including the area of ​​the irradiation object, into a number of divided areas, and a calculation procedure for calculating the exposure dose or the dose distribution within the divided areas divided by the division procedure using the same calculation conditions, and in the division procedure, the number and shape of the divided areas are determined by estimating an objective function. Effect of the Invention

[0025] According to the present invention, the calculation speed of the Monte Carlo simulation of radiation can be increased as compared with the conventional art. Problems, configurations and effects other than those described above will become apparent from the following description of the embodiments. [Brief description of the drawings]

[0026] [Figure 1] 1 is a diagram showing an outline of the overall configuration of a radiotherapy apparatus using X-rays, in which a dose calculation program and a dose calculation method according to a first embodiment are suitably executed. [Diagram 2] FIG. 2 is a diagram showing an example of the configuration of a treatment planning system and a quality assurance system in the radiotherapy apparatus according to the first embodiment. [Diagram 3] 4 is a flowchart illustrating the flow of a dose calculation method according to the first embodiment. [Figure 4] 13 is a diagram showing details of a model division process in the dose calculation program and the dose calculation method according to the second embodiment. FIG. [Diagram 5] 13 is a diagram showing details of a model division process in the dose calculation program and the dose calculation method according to the third embodiment. [Figure 6]13 is a diagram showing details of a model division process in the dose calculation program and the dose calculation method according to the fifth embodiment. FIG. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0027] The following describes the embodiments of the dose calculation program, the treatment device, and the dose calculation method of the present invention with reference to the drawings. In the drawings used in this specification, the same or similar reference numerals are used for the same or corresponding components, and the repeated description of these components may be omitted.

[0028] <Example 1> A dose calculation program, a treatment apparatus, and a dose calculation method according to a first embodiment of the present invention will be described with reference to FIGS. 1 to 3. FIG.

[0029] First, as an example of a radiotherapy device, the overall configuration of a radiotherapy device using X-rays will be described with reference to Fig. 1. Fig. 1 is a diagram showing an outline of the overall configuration of a radiotherapy device using X-rays, in which a dose calculation program and a dose calculation method according to the first embodiment are suitably executed.

[0030] The radiation therapy device is composed of a movable treatment table (102), a linear accelerator (LINAC) (103), a gantry (104), a control PC (105), a treatment plan and quality assurance dose calculation PC (106), and a communication device (107), etc. Among these, the irradiation device that irradiates radiation to an irradiation target based on an irradiation dose or dose distribution is composed of the movable treatment table (102), the linear accelerator (103), the gantry (104), the control PC (105), and the communication device (107).

[0031] The movable treatment table (102) is a bed installed in the treatment room and is configured to allow the patient (101) to lie down on it.

[0032] The linear accelerator (103) is configured to generate therapeutic X-rays to be irradiated onto the affected area of ​​the patient (101). The linear accelerator (103) is attached to a C-arm gantry (104) that can rotate 360 ​​degrees or 180 degrees.

[0033] In the radiation therapy device, the rotation of the gantry (104) allows for the Intensity Modulated Radiation Therapy (IMRT) mode, which irradiates from a specific angle, and the Intensity Modulated Rotational Amplification (VMAT) mode, which distributes the dose 360 ​​degrees. This allows for increased dose concentration and avoidance of healthy tissue and organs at risk (OAR), which are susceptible to radiation.

[0034] The radiation used in the treatment may be not only X-rays, but also particle beams such as protons, helium, carbon, etc. In that case, a synchrotron accelerator, a cyclotron accelerator, a synchrocyclotron accelerator, etc. may be provided as appropriate instead of or in addition to the linear accelerator (103).

[0035] The control PC (105) is installed in a control room where the treatment room can be observed, and the treatment planning and quality assurance dose calculation PC (106) is installed in a doctor's examination room or a dedicated treatment planning room. These control PC (105) and treatment planning and quality assurance dose calculation PC (106) are connected to the movable treatment table (102), linear accelerator (103), gantry (104), etc. by wire or wireless connection via a communication device (107) such as a router or firewall.

[0036] FIG. 2 is a diagram showing an example of the configuration of the treatment plan and quality assurance dose calculation PC (106) in the radiotherapy apparatus according to the first embodiment.

[0037] 2, the treatment planning and quality assurance dose calculation PC (106) includes a CPU (106a), a memory (106b), a storage device (106c), a display device (106d), and a user input / output device (106e) such as a keyboard and a mouse. A treatment planning program (106c2) and a QA dose calculation program (106c1) are implemented in the storage device (106c), and are executed by the CPU (106a) of the treatment planning and quality assurance dose calculation PC (106).

[0038] Similarly to the treatment planning and quality assurance dose calculation PC (106), the control PC (105) also has a central processing unit (CPU) and a memory connected to the CPU.

[0039] The control processes for the operations executed by the control PC (105) and the treatment planning and quality assurance dose calculation PC (106) may be integrated into one program, or each may be divided into multiple programs, or may be a combination of these.

[0040] Some or all of the programs held by each device may be implemented by dedicated hardware or may be modularized. Furthermore, various programs may be installed in each device via a program distribution server or external storage media, or may be used to update existing devices.

[0041] Furthermore, each device may be an independent device connected to a wired or wireless network, or two or more devices may be integrated together.

[0042] Next, the QA dose calculation program (106c1) executed in the treatment plan and quality assurance dose calculation PC (106) of this embodiment will be described in detail.

[0043] The QA dose calculation program (106c1) of this embodiment is a program executed by the treatment plan and quality assurance dose calculation PC (106) for calculating the dose or dose distribution of radiation irradiated to an irradiation target as described above, and causes the treatment plan and quality assurance dose calculation PC (106) to execute a division procedure for dividing the radiation passing area, including the irradiation target area, into multiple divided areas, and a calculation procedure for calculating the dose or dose distribution using the same calculation conditions within the divided areas divided by the division procedure. Of these, in the division procedure, the number and shape of the divided areas are determined by estimating an objective function.

[0044] In this embodiment, an example will be described in which calculation time is used as the objective function, and the number and shape of the divided regions are determined in the division procedure by repeated calculations that maximize or minimize the objective function.

[0045] Next, each step will be described in detail. In the segmentation step of segmenting a passing region such as air, including the region to be irradiated, into a plurality of segmented regions, in order to solve the above-mentioned problems, a CT or a three-dimensional model generated based on the CT is segmented into one or more regions such as bones and soft tissues.

[0046] Each of the divided regions may have the following characteristics: (a) it contains a large number of minute volumes, (b) the density difference between the minute volumes is small, and (c) it has a simple shape.

[0047] Furthermore, the division method is optimized after estimating the calculation time as the objective function. The calculation time is estimated quickly with less memory access. For example, the following formula (1) can be used as the objective function, but it is not limited to this. Calculation time = (number of area decisions × decision cost + calculation time for one step) × average number of steps … (1)

[0048] Each parameter in the above equation (1) is determined as follows: Number of area judgments ≒ Number of faces that define the area × Constant Decision cost: A constant that depends on computer performance Calculation time for one step: A constant that depends on computer performance and simulation algorithm. Average number of steps ≒ scale of area ÷ μ max Step length determined by

[0049] As described above, it is possible to quickly find an objective function that reflects the calculation time by performing arithmetic operations on constants or parameters that depend on the region division method (number of faces of the region, scale of the region). As a result, the initial state of the divided regions is stored in a database for each part to be treated, and an optimization problem can be created in which the objective function is minimized while changing the vertices of the region for each patient.

[0050] In addition, in this division procedure, it is desirable that the user be able to specify and change the priority, such as the weighting of each term (parameter) of the objective function.

[0051] Specifically, during step S302 in FIG. 3 described below, the user can modify and / or specify the priority of each term in the objective function on the screen of the display device (106d) by operating the user input / output device (106e).

[0052] Next, a calculation procedure for calculating the irradiation amount or dose distribution using the same calculation conditions within the divided regions divided by the division procedure will be described.

[0053] In this calculation procedure, the "same calculation conditions" refer to the same calculation conditions for each divided area after the divided areas are determined. max , and calculate with the same fixed step length. Here, the virtual reaction is P=1-σ local / σ max The probability of occurrence is σ max is the largest energy absorption coefficient μ max The reaction cross section or reaction rate corresponding to σ local is the energy absorption coefficient μ of the tracking arrival position local is the reaction cross section or reaction rate corresponding to

[0054] Next, the flow of the dose calculation method of the embodiment 1 will be described with reference to Fig. 3. Fig. 3 is a flowchart illustrating the flow of the dose calculation method of the embodiment 1. The CPU (106a) of the treatment plan and quality assurance dose calculation PC (106) executes each of the following steps.

[0055] First, the CPU (106a) of the PC (106) for calculating the treatment plan and the quality assurance dose reads the QA dose calculation program (106c1), reads the CT image of the patient (S301), and divides it into one or more divided regions having the above-mentioned characteristics (a)-(c) by the model division process (S302). At this time, the above-mentioned formula (1) can be used as the objective function, but it is not limited to this.

[0056] Next, the CPU (106a) executes a process for generating incident beam data (S303). Here, M particles (or rays, hereafter omitted and simply referred to as particles) are generated as the number of particles designated by the user (S303), and temporarily recorded in the memory (106b).

[0057] The information generated in step S303 may be, but is not limited to, the type of particle, initial coordinates, velocity vector, energy, and weight. The generation method may be a method of calculating by Monte Carlo calculation, a method of generating random numbers according to a predetermined distribution, or a method of reading the information as a file from the storage device (106c) of the PC (106) for calculating treatment plans and quality assurance doses to the memory (106b). The amount of particles to be generated may be a method of calculating and reading M particles at once, or a method of generating the particles in multiple batches to save memory usage.

[0058] Next, in order to loop from N=0 to N=M-1 and calculate each radiation particle and the secondary particles generated by the reaction thereof, the CPU (106a) initializes the particle number N to 0 (S304).

[0059] Next, the CPU (106a) calculates the energy, the maximum energy absorption coefficient μ max or the maximum reaction cross section σmax The step length L is calculated by the above (S305).

[0060] Thereafter, the CPU (106a) determines whether or not to leave the divided region when moving a distance L from the corresponding position with the corresponding velocity vector (S306). If it is determined that the object will leave the divided region, tracking is performed up to the boundary of the divided region (S307), and the process proceeds to the next step S308. On the other hand, if it is determined that the object will not leave the corresponding divided region, the process proceeds to the next step S308.

[0061] Next, the CPU (106a) first determines whether or not a hypothetical reaction occurs at the end of the step (S308). The probability that a hypothetical reaction occurs is P=1-σ local / σ max Here, σ max is the largest energy absorption coefficient μ max The reaction cross section or reaction rate corresponding to σ local is the energy absorption coefficient μ of the tracking arrival position local is the reaction cross section or reaction rate corresponding to

[0062] If it is determined in step S308 that a virtual reaction occurs, it is assumed that there is no change in the radiation particles, and the process proceeds to step S310. On the other hand, if it is determined that a virtual reaction does not occur, the reaction that occurs is determined based on the reaction cross sections and random numbers of various reactions at the corresponding energy, as in the conventional Monte Carlo calculation, and information such as the radiation energy loss, velocity vector change, and secondary particles is calculated and recorded in memory (S309).

[0063] Next, the CPU (106a) determines whether the particle number N satisfies N < M in order to check whether the above calculations have been performed for all of the particle number M specified by the user in the previous step S303 (S310). When it is determined that the condition is satisfied, N is incremented by N = N + 1 (S311), and then the process returns to step S305 to repeat the calculation. On the other hand, when it is determined that the condition is not satisfied, since the calculations for all particles have been completed, the process proceeds to step S312, where the result of the dose distribution is displayed and recorded (S312), and the calculation process ends (S313).

[0064] Next, the effects of this embodiment will be described.

[0065] The QA dose calculation program (106c1) of the first embodiment of the present invention described above is a program for causing a treatment planning and quality assurance dose calculation PC (106) that calculates the radiation dose or dose distribution irradiated to an irradiation target to execute a division procedure for dividing a radiation passage region including the region of the irradiation target into a plurality of divided regions, and a calculation procedure for calculating the irradiation dose or dose distribution using the same calculation conditions within the divided regions divided by the division procedure. The treatment planning and quality assurance dose calculation PC (106) is caused to execute the division procedure, and in the division procedure, the number and shape of the divided regions are determined by estimating the objective function.

[0066] As a result, Monte Carlo calculation of radiation becomes possible without stopping tracking at the boundary of the microvolume. In addition, since the density difference between the microvolumes within each divided region is small, the step length becomes an appropriate length, and the effect of speeding up the calculation can be obtained.

[0067] Here, in the acceleration of the calculation according to this embodiment, since it is realized by omitting the boundary processing for each microvolume, the step length within the region does not become longer than normal, and thus there is an advantage that the accuracy is not decreased.

[0068] Conventional simulation calculations involve methods of increasing the microvolume size or mesh size, or increasing the step length, for parts that are not of interest or have a low priority. However, these methods have the problem that increasing the size reduces the calculation accuracy.

[0069] In addition, in Patent Document 1 and other documents, it is said that a high-speed effect can be achieved by combining micro-volumes of the same density, but the details of the method are such that by increasing the size of the micro-volumes by combining them, the occurrence of tracking stopping at the boundaries is reduced, thereby contributing to the high-speed effect.

[0070] In contrast, in this embodiment, the calculation of a fixed step length does not reduce accuracy, and there is no need to stop tracking at the boundary of a minute volume.

[0071] In this embodiment, the tracking is not stopped at the boundary of the minute volume, but the maximum energy absorption coefficient μ max Since the time required to stop tracking and recalculate the step length changes, tracking must be stopped and the step length must be recalculated. However, as shown in equation (1), optimization that estimates and determines the objective function has the effect of making it easier for the division regions to converge to shapes with fewer vertices and faces, and to a smaller number of division regions, so the time required to stop tracking at the boundaries of the division regions and recalculate the step length can be made negligible compared to the conventional method.

[0072] For example, in the case of head and neck cancer treatment, the device is divided into three hexahedrons, as shown in Figure 5 below, so the number of microvolumes is 10 of the conventional number. 4 pcs to 10 6 Compared to the individual units, the processing time is so short that it can be almost ignored.

[0073] <Example 2> A dose calculation program, a treatment apparatus, and a dose calculation method according to a second embodiment of the present invention will be described with reference to Fig. 4. Fig. 4 is a diagram showing details of a model division process in the dose calculation program and the dose calculation method according to the second embodiment.

[0074] In this embodiment, the division procedure involves determining the number and shape of divided regions for each treatment area by starting from a pre-prepared pattern and repeating calculations to maximize or minimize an objective function while changing the vertices of the region.

[0075] Although Fig. 4 is two-dimensional, in reality a three-dimensional volume is divided. Since it is desirable for the divided regions to have a small density difference within the region and a small number of faces and vertices in the division procedure, as shown in Fig. 4, in step S302 shown in Fig. 3 described above, rather than creating and optimizing a divided region (401) as a very small volume of, for example, 512 x 512 size, a conceivable method is to first create an initial division including divided regions (402) that have been combined at regular intervals, such as 5 x 5 or 10 x 10, and then optimize the combination and division in units of the initial division.

[0076] The other configurations and operations are substantially the same as those of the dose calculation program, treatment apparatus, and dose calculation method of the first embodiment described above, and the details are omitted.

[0077] The dose calculation program, treatment apparatus, and dose calculation method of the second embodiment of the present invention also provide substantially the same effects as the dose calculation program, treatment apparatus, and dose calculation method of the first embodiment described above, and further improves the execution speed of the region division processing.

[0078] <Example 3> A dose calculation program, a treatment apparatus, and a dose calculation method according to a third embodiment of the present invention will be described with reference to Fig. 5. Fig. 5 is a diagram showing details of a model division process in the dose calculation program and the dose calculation method according to the third embodiment, and is a schematic diagram showing a CT scan of the head and neck.

[0079] In Fig. 5, region (511) is an air portion, region (512) is a bone portion, and region (513) is a soft tissue portion. As shown in Fig. 5, the optimal division method is to mainly use soft tissue, so that region (503) that does not contain bone is taken as one division region, and rectangular region (502) having four vertices (504) that includes all of the bone portion and surrounds region (503) is taken as another division region. The rest can be divided into three regions, including region (501) that is only air.

[0080] Here, in the dose calculation program of this embodiment, the treatment plan and quality assurance dose calculation PC (106) can further execute a display procedure for displaying and explaining the divided regions on the display device (106d) to the user. More specifically, in step S302 of Fig. 3, a screen such as that shown in Fig. 5 can be displayed on the screen of the display device (106d).

[0081] In addition, in the dose calculation program of this embodiment, the treatment plan and quality assurance dose calculation PC (106) can further execute a correction procedure for displaying on the user input / output device (106e) a correction screen for correcting the number and shape of the divided regions determined in the division procedure. More specifically, in step S302 in Fig. 3, the user can correct and specify the vertices (504) in Fig. 5 by operating the user input / output device (106e) on a screen such as that in Fig. 5 displayed on the display device (106d).

[0082] The other configurations and operations are substantially the same as those of the dose calculation program, treatment apparatus, and dose calculation method of the first embodiment described above, and the details are omitted.

[0083] The dose calculation program, treatment apparatus, and dose calculation method of the third embodiment of the present invention can obtain substantially the same effects as the dose calculation program, treatment apparatus, and dose calculation method of the first embodiment described above, and can calculate the optimal division method for each patient by determining a desired pattern in advance for the treatment area and minimizing or maximizing an objective function while changing the positions of the vertices (504, etc.) of each region.

[0084] <Example 4> A dose calculation program, a treatment apparatus, and a dose calculation method according to a fourth embodiment of the present invention will be described.

[0085] In the above-mentioned first to third embodiments, the division procedure uses the calculation time as the objective function when determining the number and shape of the divided regions by estimating the objective function, but as in the division procedure of this embodiment, the objective function can be a material property, for example, a density difference or a maximum energy absorption coefficient, or the relative relationship between each divided region, for example, a density difference, an electron density difference, or a difference in energy absorption coefficient within each region. Furthermore, it is also possible to create an objective function based on a comparative relationship between regions, such as increasing the difference in the maximum energy absorption coefficient between a region and an adjacent region.

[0086] Here, the attenuation coefficient μ is the ratio of the intensity of radiation that travels a distance x inside a substance to the intensity of radiation in the substance according to the following formula (2): I 0 When the attenuation coefficient is from to I, it is the constant μ. This attenuation coefficient has the dimension of the reciprocal of the length, so it is also called the linear attenuation coefficient.

[0087]

number

[0088] In addition, the Hounsfield unit (HU value) is a value obtained by linearly converting the linear attenuation coefficient so that the HU value of water is 0 and the HU value of air is -1000.

[0089]

number

[0090] Furthermore, the energy absorption coefficient μ enWhen the intensity of photons (X-rays, gamma rays) is attenuated by the attenuation coefficient μ above, not all of the lost energy is absorbed by the substance. In fact, the photons of radiation undergo Compton scattering, the photoelectric effect, and electron pair creation reactions, transferring energy to charged particles. When the electrons decelerate, some of the energy escapes as bremsstrahlung and is not absorbed. Energy absorption coefficient μ en is a coefficient that evaluates the amount of photon energy absorbed by a charged particle, taking into account bremsstrahlung.

[0091] Electron density is the number of electrons present in a unit volume, and its value is 10 23 Since this is a large value, for convenience it is sometimes used as the relative electron density using distilled water as a standard.

[0092] The other configurations and operations are substantially the same as those of the dose calculation program, treatment apparatus, and dose calculation method of the first embodiment described above, and the details are omitted.

[0093] The dose calculation program, treatment apparatus, and dose calculation method according to the fourth embodiment of the present invention also provide substantially the same effects as those of the dose calculation program, treatment apparatus, and dose calculation method according to the first embodiment described above.

[0094] <Example 5> A dose calculation program, a treatment apparatus, and a dose calculation method according to a fifth embodiment of the present invention will be described with reference to Fig. 6. Fig. 6 is a diagram showing details of a model division process in the dose calculation program and the dose calculation method according to the fifth embodiment.

[0095] In Example 5, the division procedure involves determining the number and shape of division regions after learning from past successful cases using a learning device, and the system learns the division method from past successful cases using a learning device such as a machine learning model or a deep neural network, and then proposes an appropriate division method for each patient.

[0096] The flow of the process will be described below with reference to Fig. 6. The CPU (106a) of the treatment plan and quality assurance dose calculation PC (106) executes each of the following steps.

[0097] First, the CPU (106a) of the treatment plan and quality assurance dose calculation PC (106) reads the QA dose calculation program (106c1) and reads the CT image of the patient (S301), and checks for the presence or absence of a learning model, for example, from the storage device (106c) (S601). If it is determined that a learning model exists, the process proceeds to step S302, and if it is determined that a learning model does not exist, the process proceeds to step S602.

[0098] Next, the CPU (106a) reads past successful cases from the storage device (106c) etc. (S602), learns them (S603), and stores the model in the storage device (106c) etc. (S604). After that, the process proceeds to step S302.

[0099] The CPU (106a) also outputs the dose distribution result (S312), and then asks the user whether to add a case (S606). If the user instructs to add a case, the process proceeds to step S607, where the case is added (S607), and the process returns to step S602. On the other hand, if it is determined not to add a case, the process proceeds to step S313, where the process ends.

[0100] In addition, in this embodiment, the basis for the machine learning selection result in step S601 can be displayed on the display device (106d).

[0101] The other configurations and operations are substantially the same as those of the dose calculation program, treatment apparatus, and dose calculation method of the first embodiment described above, and the details are omitted.

[0102] The dose calculation program, treatment apparatus, and dose calculation method according to the fifth embodiment of the present invention also provide substantially the same effects as those of the dose calculation program, treatment apparatus, and dose calculation method according to the first embodiment described above.

[0103] Furthermore, in the division procedure, the number and shape of the division regions are determined after learning from past successful cases using a learning device, thereby enabling calculation of the radiation exposure dose or dose distribution with high accuracy in a shorter time.

[0104] <Other> The present invention is not limited to the above-mentioned embodiment, but includes various modified examples. The above-mentioned embodiment has been described in detail to explain the present invention in an easily understandable manner, and the present invention is not necessarily limited to the embodiment having all of the described configurations.

[0105] It is also possible to replace a part of the configuration of one embodiment with the configuration of another embodiment, or to add the configuration of another embodiment to the configuration of one embodiment. It is also possible to add, delete, or replace part of the configuration of each embodiment with the configuration of another embodiment.

[0106] For example, the embodiment of the present invention may be in the following form.

[0107] (1) A program to be executed by a dose calculation system for calculating an exposure dose or dose distribution of radiation irradiated to an irradiation object, the dose calculation system executing a division step of dividing an area through which the radiation passes, including the area of ​​the irradiation object, into a plurality of divided areas, and a calculation step of calculating the exposure dose or the dose distribution within the divided areas divided by the division step using the same calculation conditions, wherein in the division step, the number and shape of the divided areas are determined by estimating an objective function.

[0108] (2) In the dose calculation program described in (1), calculation time is used as the objective function.

[0109] (3) In the dose calculation program described in (1), the objective function is a property of a material.

[0110] (4) In the dose calculation program described in (3), the material characteristic is determined to be either a density difference or a maximum energy absorption coefficient.

[0111] (5) In the dose calculation program described in (1), the relative relationship between each of the divided regions is used as the objective function.

[0112] (6) In the dose calculation program according to any one of (1) to (5), in the division step, the number and shape of the divided regions are determined by repeated calculations that maximize or minimize the objective function.

[0113] (7) In the dose calculation program described in any one of (1) to (6), in the division procedure, the number and shape of the divided regions are determined for each treatment site by repeating calculations that start from a previously prepared pattern and maximize or minimize the objective function while changing the vertices of the region.

[0114] (8) In the dose calculation program according to any one of (1) to (7), in the division step, the number and shape of the divided regions are determined after learning from past successful cases using a learning device.

[0115] (9) In the dose calculation program according to any one of (1) to (8), the dose calculation system is further made to execute a correction procedure for displaying on an operation device a correction screen for correcting the number and shape of the divided areas determined in the division procedure.

[0116] (10) In the dose calculation program according to any one of (1) to (9), in the division step, a user can specify and change the priority of each term of the objective function.

[0117] (11) In the dose calculation program according to any one of (1) to (10), the dose calculation system is further made to execute a display procedure for displaying and explaining the divided regions to a user on an output device. [Explanation of symbols]

[0118] 101:Patient 102: Movable treatment table (irradiation device) 103: Linear accelerator (irradiation device) 104: Gantry (irradiation device) 105: Control PC (irradiation device) 106: PC for treatment planning and quality assurance dose calculation (dose calculation system) 106a:CPU 106b:Memory 106c: Storage device 106c1: Dose calculation program 106c2: Treatment planning program 106d: Display device 106e: User input / output devices (operating devices) 107: Communication device (irradiation device) 401: Initial division area 402: Split area where merging has been performed 501: Range of division area 1 502: Range of division area 2 503: Range of division area 3 504: Vertex of the divided area 511: Air 512:Bone 513: Soft tissue

Claims

1. A program to be executed by a dose calculation system for calculating an exposure dose or a dose distribution of radiation irradiated to an irradiation target, a division step of dividing a region through which the radiation passes, the region including the region to be irradiated, into a plurality of divided regions; a calculation procedure for calculating the irradiation amount or the dose distribution using the same calculation conditions within the divided regions divided by the division procedure; In the division step, the number and shape of the divided regions are determined by estimating an objective function. Dose calculation program.

2. 2. The dose calculation program according to claim 1, The calculation time is used as the objective function. Dose calculation program.

3. 2. The dose calculation program according to claim 1, The objective function is the property of the material. Dose calculation program.

4. 4. The dose calculation program according to claim 3, The material characteristic is either density difference or maximum energy absorption coefficient. Dose calculation program.

5. 2. The dose calculation program according to claim 1, The objective function is to use the relative relationship between each of the divided regions. Dose calculation program.

6. 2. The dose calculation program according to claim 1, In the division procedure, the number and shape of the divided regions are determined by repeated calculations that maximize or minimize the objective function. Dose calculation program.

7. 7. The dose calculation program according to claim 6, In the division procedure, the number and shape of the divided regions are determined for each treatment site by repeating calculations that maximize or minimize the objective function while changing the vertices of the regions, starting from a previously prepared pattern. Dose calculation program.

8. 2. The dose calculation program according to claim 1, In the division step, the number and shape of the divided regions are determined after learning past successful cases using a learning device. Dose calculation program.

9. 2. The dose calculation program according to claim 1, and further causing the dose calculation system to execute a correction procedure for displaying a correction screen on an operation device for correcting the number and shape of the divided regions determined in the division procedure. Dose calculation program.

10. 2. The dose calculation program according to claim 1, In the division procedure, the user can specify and change the priority of each term in the objective function. Dose calculation program.

11. 2. The dose calculation program according to claim 1, The dose calculation system further executes a display procedure for displaying and explaining the divided regions on an output device to a user. Dose calculation program.

12. A dose calculation system that executes a dose calculation program according to any one of claims 1 to 11; an irradiation device that irradiates the irradiation target with the radiation based on the irradiation amount or the dose distribution; Radiation therapy equipment.

13. A dose calculation method for calculating an exposure dose or a dose distribution of radiation irradiated to an irradiation target, comprising: a dividing step of dividing a region through which the radiation passes, the region including the region to be irradiated, into a plurality of divided regions; A calculation step of calculating the irradiation amount or the dose distribution using the same calculation conditions within the divided regions divided in the division step, In the dividing step, the number and shape of the divided regions are determined by estimating an objective function. Dose calculation methods.

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