Radiation therapy planning support system, radiation therapy planning support program, and radiation therapy planning support method

Abstract

The aim is to provide a radiation therapy planning support system that can efficiently realize a dose distribution close to the ideal dose distribution created by the radiation therapy device, and that can stabilize the quality of treatment planning by ensuring that the realized dose distribution does not vary significantly even when different types of radiation therapy devices are used. [Solution] The system includes a dose distribution storage unit 21b that stores an ideal radiation dose distribution created based on information about the position and cross-sectional contour of the affected area to be irradiated with radiation, a regionization processing unit 20c that divides the cross-section into two or more regions for each predetermined dose range based on the dose distribution information, and a dose parameter setting unit 30a that associates predetermined parameter values ​​for radiation doses suitable for realizing the dose distribution with the radiation therapy device used for each region.

Description

Technical Field

[0001] The present invention relates to a radiotherapy planning support system, a radiotherapy planning support program, and a radiotherapy planning support method.

Background Art

[0002] In general, before irradiating a tumor with radiation using a radiotherapy device, medical staff usually use dedicated software for the radiotherapy device in advance to plan and determine the dose distribution to be irradiated based on information in the patient's body obtained from CT images or the like. There are usually normal tissues around the tumor to be irradiated with radiation, and there are risk organs (Organ at Risk: OAR) that need to be avoided from radiation irradiation as much as possible. Therefore, the dose distribution is planned to give the maximum dose to the target tumor while preventing damage to the OAR.

[0003] An increase in the radiation dose to be irradiated to the target also leads to an increase in the dose to the OAR. Therefore, the planning of the dose distribution is not easy. Parameters related to radiation irradiation are input using the dedicated planning software for the radiotherapy device, and the dose distribution is optimized and calculated. After confirming the result, the parameters are adjusted and recalculated and reconfirmed repeatedly until finally a distribution that can efficiently give more dose to the target without causing damage to the OAR is determined. A lot of time and labor are required to reach this determination.

[0004] In particular, in recent years, intensity-modulated radiotherapy (IMRT), volumetric-modulated radiotherapy (VMRT), etc. have become popular and their functions have been advanced. It has become possible to concentrate radiation on the tumor more efficiently and reduce the irradiation to surrounding normal tissues. On the other hand, the calculation of the dose distribution and the work of determining the optimal dose distribution have become more difficult, and the time required for each calculation by the planning software tends to be longer. Therefore, at present, more time and labor are required until medical staff actually determine the dose distribution considered to be optimal.

[0005] In response to this, the present applicant has already proposed a system that obtains an ideal dose distribution based on target affected area information and learning results pre-trained by predetermined deep learning (Patent Document 1). According to this system, a high-quality ideal dose distribution can be created in a short time using AI.

[0006] However, even if an ideal dose distribution can be created in a short time using AI technology, it is not calculated using the dedicated software of the radiation therapy device actually used. Therefore, when importing and implementing that dose distribution into the device, the calculations become complex, and there are limitations to the device's mechanical operation, making it difficult to directly implement the created ideal dose distribution on the device side. In addition, multiple types of radiation therapy devices are in use, each with different mechanisms and characteristics. Therefore, even if a dose distribution close to the ideal can be achieved with one type of device, it does not necessarily mean that it can be achieved with other types of devices. This has led to the problem that the dose distribution (and consequently the quality of treatment planning) achieved varies greatly depending on the type of device. [Prior art documents] [Patent Documents]

[0007] [Patent Document 1] Japanese Patent Publication No. 2020-178935 [Overview of the project] [Problems that the invention aims to solve]

[0008] Therefore, in view of the above-mentioned circumstances, the present invention aims to provide a radiation therapy planning support system that can efficiently realize a dose distribution close to the ideal dose distribution created in the radiation therapy device, and that can stabilize the quality of the treatment plan by ensuring that the realized dose distribution does not vary greatly even if the type of radiation therapy device is different. [Means for solving the problem]

[0009] In light of the current situation, the inventors conducted thorough research and found that the software specifically designed for radiation therapy devices has an optimization calculation function for calculating the dose distribution by setting the parameters as described above. They then conceived the idea of ​​dividing the created ideal dose distribution into two or more regions for each predetermined dose range and simplifying it into data for each region.

[0010] In other words, by simplifying the data to separate data for multiple regions having predetermined dose ranges, it becomes possible to efficiently realize a dose distribution close to the ideal dose distribution in the radiotherapy device without placing a heavy load on the device. At the same time, we have discovered that even if the type of device is different, by simply setting predetermined parameter values ​​for radiation dose appropriate for each device in each region, it is possible to realize a dose distribution close to the ideal dose distribution without causing large variations between devices, and thus completed the present invention.

[0011] Furthermore, the inventors have found that by dividing the OAR or a nearby area around it into predetermined dose ranges that are finer than other areas, and setting predetermined parameter values ​​for radiation dose, a dose distribution close to the ideal dose distribution can be achieved with any type of radiation therapy device. They have also found that if the characteristics of each type of radiation therapy device are known, the way the area is divided can be changed for each type, thereby further suppressing the variation in dose distribution due to differences in type.

[0012] In other words, the present invention encompasses the following inventions. (1) A radiation therapy planning support system comprising: a dose distribution storage unit that stores an ideal radiation dose distribution created based on information of the location and cross-sectional contour of the affected area to be irradiated with radiation; a regionization processing unit that divides the cross-section into two or more regions for each predetermined dose range based on the dose distribution information; and a dose parameter setting unit that associates predetermined parameter values ​​for radiation doses suitable for realizing the dose distribution with the radiation therapy device to be used for each region.

[0013] (2) The radiation therapy planning support system according to (1), wherein the dose parameter setting unit includes an input field display unit that displays input fields for predetermined parameter values ​​relating to the radiation dose for each region.

[0014] (3) A radiotherapy planning support system according to (1) or (2), comprising a regionized image display unit that generates and displays a contour-like regionized image consisting of the contour of the cross section and the boundaries of the plurality of regions, in which each region is distinguishable from other regions.

[0015] (4) The radiotherapy planning support system according to (1) or (2), wherein the regionization processing unit performs a process to divide the portion of an organ at risk (OAR) or its vicinity into a region subdivided into a finer dose range compared to other portions. (5) The radiotherapy planning support system according to (1) or (2), wherein the regionization processing unit has two or more templates with different division methods, and performs processing based on the selected template.

[0016] (6) The radiotherapy planning support system according to (1) or (2), wherein the predetermined parameter values ​​for radiation dose include one or more predetermined parameter values ​​for radiation dose among the radiation irradiation volume for each region, the target dose, and the priority compared to other regions.

[0017] (7) A radiotherapy planning support program that causes a computer to function as a regionization processing unit that divides the cross-section into two or more regions for each predetermined dose range based on information of an ideal radiation dose distribution created based on information of the location and cross-sectional contour of the affected area to be irradiated with radiation, and a dose parameter setting unit that associates predetermined parameter values ​​for radiation dose suitable for realizing the dose distribution with the radiotherapy device to be used for each region.

[0018] (8) A radiation therapy planning support method, wherein a computer divides the cross-section into two or more regions for each predetermined dose range based on information on the ideal dose distribution of radiation created based on the position and cross-sectional contour information of the affected part to be irradiated with radiation, and for each region, sets a predetermined parameter value related to the radiation dose suitable for realizing the dose distribution with the radiation therapy apparatus to be used, and calculates an optimal dose distribution to be realized with the radiation therapy apparatus to be used based on the predetermined parameter value related to the radiation dose of each set region.

Advantages of the Invention

[0019] According to the radiation therapy planning support system according to the present invention configured as described above, it is possible to efficiently realize a dose distribution close to the created ideal dose distribution with a radiation therapy apparatus, and even if the types of radiation therapy apparatuses are different, there is no significant variation in the dose distribution to be realized, and the quality of the treatment plan can be stabilized.

Brief Description of the Drawings

[0020] [Figure 1] A block diagram showing an overview of the entire radiation therapy system having a radiation therapy planning support system according to a representative embodiment of the present invention. ​​​​​​​​​​​​​​​​​​​​​ [Figure 9] Figure 8 is an explanatory diagram showing a specific example of regionization processing using a template. [Figure 10] A conceptual diagram illustrating the domainization process using other templates. [Figure 11] Figure 10 is an explanatory diagram showing a specific example of area creation processing using a template. [Figure 12] A conceptual diagram illustrating the domainization process using other templates. [Figure 13] A block diagram showing the configuration of the planning computer in a radiation therapy planning support system. [Figure 14] This block diagram also shows the configuration of the dose parameter setting unit included in the planning computer. [Figure 15] An explanatory diagram showing an example of an input field (already filled in) for predetermined parameter values ​​related to radiation dose. [Figure 16] An explanatory diagram illustrating the process of defining an ideal dose distribution as a region. [Figure 17] A flowchart illustrating the processing procedure using the radiation therapy planning support system. [Modes for carrying out the invention]

[0021] Hereinafter, typical embodiments of the present invention will be described in detail with reference to the attached drawings.

[0022] As shown in Figure 1, the radiation therapy planning support system 1 according to this embodiment consists of a support computer 2 and a planning computer 3 dedicated to the radiation therapy device 10. The planning computer 3 can be a conventionally known radiation therapy planning system (TPS) computer that plans and determines the dose distribution to be irradiated by the radiation therapy device 10.

[0023] As shown in Figure 2, the support computer 2 is centered around a processing unit 20 and includes storage means 21, input means 22 such as a pointing device, keyboard, or touch panel, display means 23 such as a display, and a communication control unit 24. The processing unit 20 is mainly composed of a CPU such as a microprocessor and has a storage unit consisting of RAM and ROM (not shown) where programs and processing data that define the procedures for various processing operations are stored. The support computer 2 may be a computer configured specifically for this purpose, or a general-purpose personal computer can be used. The support computer 2 may be composed of a single computer device, but is not limited to that, and can of course be composed of multiple computer devices.

[0024] Functionally, the processing unit 20 includes a contour creation unit 20a that creates the contours of tumors and organs, a dose distribution creation unit 20b that creates the ideal radiation dose distribution desired by medical professionals, a regionization processing unit 20c that divides the cross section into two or more regions divided according to predetermined dose ranges, a regionization image display unit 20d that generates and displays contour-like regionization images consisting of the contour of the cross section and the boundaries of the multiple regions, in which each region is displayed in a way that allows it to be distinguished from other regions, and a region information output unit 20e that outputs information of the two or more regions created by the regionization processing unit 20c (including information about the dose range of each region) and the regionization image. These processing functions are realized by the above program.

[0025] The storage means 21 consists of memory or hard disks inside or outside the computer 2. The contents of some or all of the storage units may be stored in the memory or hard disks of other computers connected to the support computer 2. Specifically, the storage means 21 includes at least a contour information storage unit 21a that stores information on the contours of tumors and organs created by the contour creation unit 20a, a dose distribution storage unit 21b that stores the dose distribution created by the dose distribution creation unit 20b, and a region information storage unit 21c that stores information on the regions divided by the region processing unit 20c.

[0026] The contour creation unit 20a creates contours of tumors and organs based on information indicating the position and contours of multiple cross-sections of the same target area captured by the CT scanner 11, and stores them in the contour information storage unit 21a. Contour creation may be performed by recognizing contours drawn by a medical professional using an input means 22 such as a mouse on the images of each cross-section, or by automatically recognizing contours using an image recognition mechanism and a machine learning mechanism. Figure 4(a) shows an example of a contour 50 created for cross-section 5A.

[0027] The dose distribution creation unit 20b creates an ideal radiation dose distribution for medical professionals based on the location of the affected area and the information of the cross-sectional contour created by the contour creation unit 20a, and stores it in the dose distribution storage unit 21b. As shown in Figure 3, the dose distribution creation unit 20b has a machine learning mechanism 201, and determines the ideal dose distribution by referring to the learning results of the machine learning mechanism 201. Any method such as deep learning using a neural network can be used as the learning method for the machine learning mechanism 201. Preferably, the dose distribution generation system described in Japanese Patent Application Publication No. 2020-178935 and Japanese Patent Application No. 2024-30369, which have already been filed by the applicant of this application, can be used.

[0028] More specifically, this is deep learning using training data with affected area information, which indicates the location and cross-sectional contour of the affected area, as explanatory variables, and dose distribution information as the objective variable. The ideal dose distribution is generated based on the above information on the location and cross-sectional contour of the affected area, as well as the learning results learned in advance by a predetermined deep learning method, and specified information such as the protocol to be used, the irradiation technique, the name of the radiotherapy device to be used, and the plan policy. Figure 5 shows the input screen 6 in which the specified information is entered. Since this specified information is also entered in the training data, the dose distribution creation unit 20b uses the machine learning mechanism 201 to determine the optimal dose distribution for the specified information.

[0029] A protocol refers to a standardized set of procedures and guidelines followed when performing radiation therapy, including the dose administered to the target, the prescribed volume, the dose limits for normal organs used as indicators for managing side effects, the frequency of treatment, and the duration of treatment. Irradiation techniques include, for example, fixed multi-field IMRT and intensity-modulated rotational irradiation (VMAT).

[0030] A plan policy is a policy that sets priorities for each case, referring to priorities such as dose delivery to tumors and dose reduction to normal organs. For example, in addition to the standard model, which is a standard approach, there are multiple plan policy models that can be selected, such as a PTV-priority model that ensures radiation is delivered by using the planning target volume (PTV), and an OAR-priority model that further reduces radiation delivery to the orthostatic regulating area (OAR).

[0031] Figure 4(b) shows an example of the created ideal dose distribution 51. While this example describes how to create a dose distribution using a machine learning mechanism, the dose distribution of the present invention is not limited to those created using a machine learning mechanism; it may be created by other methods. Furthermore, it may include dose distributions created outside of the support computer 2 and input into the support computer 2.

[0032] The regionization processing unit 20c divides the cross-section into two or more regions for each predetermined dose range based on the dose distribution information created by the dose distribution creation unit 20b, and stores them in the region information storage unit 21c. For example, as shown in Figure 6, the cross-section is divided into three regions with doses of 100%, 50%, and 0% as boundaries: region R1 for doses of 100% or more, region R2 for doses of 50% to 100%, and region R3 for doses of 0% to 50%. Specifically, the cross-section is divided into three regions as shown in Figures 7(a) and (b).

[0033] By simplifying the dose distribution, which is a detailed distribution of doses, into data divided into regions based on predetermined dose ranges such as the region of 100% or more dose, the region of 50-100% dose, and the region of 0-50% dose, it becomes possible to efficiently realize a dose distribution close to the ideal dose distribution on the radiotherapy device without placing a heavy load on the device. Furthermore, even if the type of device is different, a dose distribution close to the ideal dose distribution can be realized without causing large variations between devices. Figure 16 shows an example of the process of dividing the ideal dose distribution into three regions (the region of 0-30% dose, the region of 30-60% dose, and the region of 60-90% dose).

[0034] There are no particular limitations on how many regions are divided into based on the dose range. One or more patterns (regionalization templates) can be set in advance for how these regions are divided, and it is preferable to have multiple templates available that are suitable for different protocols, irradiation techniques, names of radiation therapy devices used, and plan policies selected by medical professionals, as described above.

[0035] As a template for regionalization, in addition to the basic forms (methods of division) exemplified in Figures 6 and 7, it is preferable to have a template that divides the area of ​​an organ at risk (OAR) or its surrounding area (R4), which should be avoided from radiation exposure, into more detailed regions based on predetermined dose ranges compared to the areas of other non-risk organs (R1 to R3). For example, as exemplified in Figures 8 and 9, this would involve dividing the area into four regions: R401 for doses of 75-100%, R402 for doses of 50-75%, R403 for doses of 25-50%, and R404 for doses of 0-25%. This makes it possible to more reliably suppress radiation exposure to organs at risk (OAR). It is preferable that such a template be automatically selected, for example, when the OAR-prioritizing model is selected as the plan policy, or to be selected separately by a medical professional.

[0036] Furthermore, it is also preferable to have other templates available, such as those exemplified in Figures 10 and 11, which designate the organ at risk (OAR) and the region (R5) at a predetermined distance from the OAR as special areas for reducing radiation dose. This makes it possible to more reliably reduce radiation exposure to the organ at risk (OAR).

[0037] Furthermore, as another template, as illustrated in Figure 12, it is also preferable to have a template that separates the region (R6) between planned target volumes (PTVs), where high-dose regions are likely to occur ("dose bridge"), into a special region independent of the others. This ensures that each PTV is irradiated with a stronger dose. It is also preferable to further divide such region R6 into multiple regions for each predetermined dose range (for example, three regions: R601 for doses of 40-80%, R602 for doses of 0-40%, and R603 for doses of 40-80%).

[0038] Furthermore, it is also preferable to have a template that divides the region into areas where the planned target volume (PTV) and the area up to a predetermined distance from the PTV are defined as areas with a predetermined dose percentage or higher, and other areas are defined as areas where the dose is kept below this level. Such areas may be regions that extend a predetermined distance in a specific direction from the PTV. This makes it easier to, for example, restrict the dose on the organ at risk (OAR) side. Multiple predetermined distances may be set. For example, it may be possible to limit the dose to 60% in the area up to 5 cm from the PTV and to 30% in the area up to 10 cm from the PTV.

[0039] When multiple templates are available for regionization, the regionization processing unit 20c may automatically select a template according to the information specified by the medical professional and perform regionization according to that template, or the medical professional may select one in advance. Two or more templates may also be selected in combination. The regionization processing unit 20c stores information on multiple regions created according to the templates in the region information storage unit 21c.

[0040] The regionized image display unit 20d generates contour-like regionized images 4 for the multiple regions created by the regionization processing unit 20c, as shown in Figure 4(c), consisting of the cross-sectional contour and the boundary lines of the multiple regions, with each region displayed in a way that allows it to be distinguished from other regions. These images are displayed on the display means 23 and also stored in the region information storage unit 21c.

[0041] The region information output unit 20e exports the information of the multiple regions that have been created in a format usable by the planning computer 3. If the system is connected to the planning computer 3 online via the communication control unit 24, as in this example, the data may be transmitted online, or it may be output to a storage medium such as a USB drive and input to the planning computer 3.

[0042] As shown in Figure 13, the planning computer 3 is centered around a processing unit 30 and includes storage means 31, input means 32 such as a pointing device, keyboard, or touch panel, display means 33 such as a display, and a communication control unit 34. The processing unit 30 is mainly composed of a CPU such as a microprocessor and has a storage unit consisting of RAM and ROM (not shown) where programs and processing data that define the procedures for various processing operations are stored. The planning computer 2 is not limited to being composed of a single computer device, and of course can be composed of multiple computer devices.

[0043] Functionally, the processing unit 30 comprises a dose parameter setting unit 30a that associates predetermined parameter values ​​related to radiation dose for each region, a regionized image display unit 30b that displays regionized images, and a treatment plan creation unit 30c that creates a treatment plan using the radiation therapy device to be used. The storage means 31 comprises at least a region information storage unit 31a that stores the imported (input) region information and regionized image data, and a treatment plan storage unit 31b that stores the created treatment plan.

[0044] The dose parameter setting unit 30a associates predetermined parameter values ​​for radiation dose suitable for achieving the ideal dose distribution described above with the radiotherapy device 10 used with each region. The predetermined parameter values ​​for radiation dose are not particularly limited, but preferably include information such as the radiation irradiation volume for each region, the target dose, and the priority compared to other regions. These parameter values ​​are predetermined as optimal initial values ​​for each template used, based on information such as the protocol selected by the medical professional, the irradiation technique, the name of the radiotherapy device used, and the plan policy, as described above.

[0045] In this example, as shown in Figure 14, the dose parameter setting unit 30a is equipped with an input field display unit 301 that displays input fields on the display unit 33 for inputting the parameter values ​​using the input means 32 for each region, and medical professionals input predetermined parameter values ​​into the displayed input fields. Figure 15 is an example of an input screen 7 consisting of input fields (already entered) for predetermined parameter values ​​related to radiation dose, where reference numeral 35a is an input field for inputting the parameter value of irradiation volume for each region, reference numeral 35b is an input field for inputting the parameter value of target dose for each region, and reference numeral 35c is an input field for inputting the parameter value of priority for each region. "CTV", "preDose 0-30%", etc. written in the "Target" column in the figure are names assigned to each region of multiple cross-sections.

[0046] Instead of medical professionals entering these parameter values, they may be pre-entered and stored (registered) in the support computer 2 for each template, and then automatically set for each region created by the support computer 2 (such as the regionization processing unit 20c).

[0047] The regionized image display unit 30b displays the regionized image 4 received from the support computer 2 on the display means 33, and as shown in the lower part of Figure 16, each region can be identified and displayed. Each region can be displayed in correspondence with the region selected in the input field, and when medical professionals input parameters in each region or confirm the input content, they can input or confirm which region each parameter value belongs to by looking at the region image displayed for each selected region.

[0048] The dose parameter setting unit 30a and the regionalized image display unit 30b described above can, of course, be installed in the support computer 2 instead of the planning computer 3, or they can be installed in both computers.

[0049] The treatment planning unit 30c creates a treatment plan using the radiotherapy device, based on the parameter values ​​set in the dose parameter setting unit 30a, using these values ​​as initial values. In other words, the parameter values ​​set in the dose parameter setting unit 30a are parameters for reproducing the ideal dose distribution created by the support computer 2 through optimization calculations by the dedicated planning computer 3 for the specific radiotherapy device 10, and are created as a plan that can be irradiated by the actual radiotherapy device 10. By transmitting the machine parameters that realize this plan to the radiotherapy device 10, the radiotherapy device 10 becomes ready for irradiation. Figure 4(d) shows an example of a dose distribution 52 created as a treatment plan.

[0050] The treatment planning unit 30c can directly use the functions (optimization calculation software) provided by known radiotherapy planning devices. It is difficult and time-consuming to input the ideal dose distribution directly and have the planning computer 3 calculate it, and it is not possible to create an ideal irradiation plan. However, as in the present invention, by first converting the information into information for a simple region and then setting the above parameter values, it is possible to efficiently reproduce the ideal dose distribution (a distribution that hits the tumor in the ideal way and suppresses irradiation to organs at risk in the ideal way), and to operate the ideal plan on the radiotherapy device 10 that will actually be used.

[0051] The following describes the processing procedures performed by the radiation therapy planning support system 1, based on Figure 17.

[0052] First, the contour creation unit 20a of the support computer 2 creates the contours of the tumor and organs based on information indicating the position and contours of multiple cross-sections of the same target affected area captured by the CT scanning device 11, and stores them in the contour information storage unit 21a (S101).

[0053] Next, the medical professional inputs the protocol to be used, the irradiation technique, the name of the radiotherapy device to be used, and the plan policy into the support computer 2 (S102). At this stage, it is preferable for the medical professional to select a regionization template to be created by the regionization processing unit 20c, which will be described later.

[0054] Next, the dose distribution creation unit 20b of the support computer 2 creates an ideal radiation dose distribution based on the location of the affected area and the information of the cross-sectional contour created by the contour creation unit 20a, and stores it in the dose distribution storage unit 21b (S103).

[0055] Next, the region division processing unit 20c of the support computer 2 divides the cross-section into two or more regions for each predetermined dose range based on the created dose distribution information and template, and stores the information of these multiple regions in the region information storage unit 21c (S104).

[0056] Next, the area information output unit 20e of the support computer 2 exports the information of the multiple created areas in a format usable by the planning computer 3, and imports it into the planning computer 3 either online or via a storage medium (S105).

[0057] Next, based on the input from the medical personnel, the dose parameter setting unit 30a of the planning computer 3 associates predetermined parameter values ​​related to radiation dose for each region (S106).

[0058] Next, the treatment plan creation unit 30c of the planning computer 3 creates a treatment plan using the radiotherapy device, based on the parameter values ​​set by the dose parameter setting unit 30a, and using these as initial values ​​(S107). Then, the created treatment plan is transferred to the radiotherapy device 10 (S108).

[0059] Although embodiments of the present invention have been described above, the present invention is not limited in any way to these embodiments, and can of course be implemented in various forms without departing from the spirit of the invention. For example, in the embodiments described above, an example was described in which the radiation therapy planning support system 1 is composed of at least two computers, a support computer 2 and a planning computer 3, but the present invention is not limited in any way to such examples, and it is of course possible to compose it with only one computer (for example, only the support computer 2 or the planning computer 3).

[0060] Even when using a single computer, regardless of the type of radiation therapy device, the same effect can be achieved by first creating or inputting and storing an ideal dose distribution, and then, based on this, providing the aforementioned regionalization processing unit and dose parameter setting unit when creating a treatment plan suitable for the radiation therapy device. This allows the radiation therapy device to efficiently realize a dose distribution close to the created ideal dose distribution, and also stabilizes the quality of the treatment plan. [Explanation of symbols]

[0061] 1. Radiation Therapy Planning Support System 2. Support Computers 3. Planning computer 4. Regionized image 5A cross section 6. Input screen 7 Input screen 10 Radiation therapy equipment 11 CT scanner 20 Processing Units 20a Contour creation unit 20b Dose distribution creation section 20c Regionization processing unit 20d Regional image display section 20e Area information output section 21 Memory means 21a Contour information storage unit 21b Dose distribution memory unit 21c Area information storage unit 22 Input means 23 Display means 24 Communication Control Unit 30 Processing Unit 30a Dose parameter setting section 30b Regionalized image display section 30c Treatment Planning Department 31 Memory means 31a Area information storage unit 31b Treatment planning memory unit 32 Input means 33 Display means 34 Communication Control Unit 35a, 35b, 35c Input fields 50 contours 51. Dose Distribution 52. Dose Distribution 201 Machine Learning Mechanism 301 Input field display section

Claims

1. A dose distribution storage unit that stores the ideal radiation dose distribution created based on information about the location and cross-sectional contour of the affected area to be irradiated with radiation, A regionization processing unit that divides the cross-section into two or more regions for each predetermined dose range based on the dose distribution information, A dose parameter setting unit that associates predetermined parameter values ​​for radiation dose suitable for achieving the dose distribution in each region with the radiation therapy device used, A radiation therapy planning support system equipped with the following features.

2. The radiation therapy planning support system according to claim 1, wherein the dose parameter setting unit includes an input field display unit that displays input fields for predetermined parameter values ​​for each region.

3. A radiotherapy planning support system according to claim 1 or 2, comprising a regionized image display unit that generates and displays a contour-like regionized image consisting of the contour of the cross-section and the boundaries of the plurality of regions, wherein each region is displayed in a manner that allows it to be distinguished from other regions.

4. The radiation therapy planning support system according to claim 1 or 2, wherein the regionization processing unit performs a process to divide the portion of an organ at risk (OAR) or its surrounding area into regions with finer predetermined dose ranges compared to other parts.

5. The radiotherapy planning support system according to claim 1 or 2, wherein the regionization processing unit has two or more regionization templates with different division methods, and performs processing based on the selected template.

6. The radiation therapy planning support system according to claim 1 or 2, wherein the predetermined parameter values ​​relating to the radiation dose include one or more parameter values ​​from among the radiation irradiation volume for each region, the target dose, and the priority compared to other regions.

7. Computers, A regionization processing unit divides the cross-section into two or more regions according to predetermined dose ranges, based on information about the ideal radiation dose distribution, which is created based on information about the location and cross-sectional contour of the affected area to be irradiated with radiation. Furthermore, a radiation therapy planning support program that functions as a dose parameter setting unit that associates predetermined parameter values ​​for radiation doses suitable for achieving the aforementioned dose distribution with the radiation therapy device used in each region.

8. Based on information about the ideal radiation dose distribution, which is created based on the location and cross-sectional contour of the affected area to be irradiated, the computer divides the cross-section into two or more regions according to predetermined dose ranges. For each region, a predetermined parameter value for the radiation dose suitable for achieving the aforementioned dose distribution with the radiation therapy device used is set. Based on predetermined parameter values ​​for radiation dose in each set region, the optimal dose distribution to be achieved with the radiation therapy device used is calculated. Methods for supporting radiation therapy planning.

Images