JP2621112B2 - Treatment plan optimization method for radiation therapy system - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method for optimizing a treatment plan in a radiotherapy system, that is, a treatment plan that minimizes exposure to normal tissues and effectively supplies a dose to a treatment target site such as a tumor. A method to support the planning work when planning a treatment (hereinafter referred to as “treatment plan optimization method”)
About.

[0002]

2. Description of the Related Art In radiotherapy, prior to treatment, a method of irradiation that minimizes exposure to normal tissues of the human body to be treated and gives a therapeutically effective dose to tumors and the like at lesions. Ask for. This process is commonly referred to as "treatment planning." Conventionally, after a dose distribution for a certain irradiation method is obtained by numerical calculation, for example, a DVH (Dose Volume Histogra) showing a relationship of a tissue volume to each dose value is obtained.
m) Alternatively, the irradiation method is evaluated using a kind of evaluation characteristic diagram called cumulative DVH, which shows the relationship between each dose value and the total volume of tissue that exceeds the dose, and if the results are satisfactory, The treatment method was mainly designed by a trial and error method in which the irradiation method was adopted for treatment, and otherwise the same treatment was performed by another irradiation method. Instead of using such a trial and error method, there is an idea of treating a treatment plan as a kind of mathematical optimization problem. For example,
"A Study on Optimization of Intracavitary Irradiation Therapy" (Etsuko Kumamoto et al., Proceedings of JAMIT Study Group, pp.96-101, 1993.1), or "Dose-Volume Considerations with Line"
ar Programming Optiza-tion ”(SM Morrill, et
al., Med. Phys. 18 (6), pp. 1201-1210, 1991) make a treatment plan by optimization by linear programming that minimizes an objective function under certain constraints.

[0003]

Unlike these papers, when irradiating a narrow radiation beam from a source, the number of restriction points that impose restrictions on the beam from a certain source such as a lethal dose or less than a useful dose is given. There is not enough, for example, optimization can be achieved without irradiation from a certain source, or the dispersion of irradiation such that the irradiation intensity from a certain source becomes infinite becomes the optimal solution. Undesirable results may be obtained from a chemical viewpoint. Increasing the number of constraint points can prevent such an inappropriate optimal solution from occurring, but this leads to an increase in constraint conditions and an increase in the processing time of the optimization calculation. The present invention has been made in view of the above circumstances, and an object of the present invention is to solve the above-described problems in the conventional technology and to reduce the number of constraints in a linear programming method without excessively increasing the number of constraints. It is an object of the present invention to provide a method for deriving an optimal solution for realizing.

[0004]

SUMMARY OF THE INVENTION The above objects of the present invention are as follows.
An input device that inputs image data and an external command, a computer that processes the input image data according to an external command, a display device that displays a processing result,
A treatment planning device having a storage device for storing processing results,
A radiation treatment system comprising a radiation treatment device having means for controlling the position and direction of a gantry, an irradiation head, a treatment couch, and energy of an accelerator based on the processing result of the treatment planning device, When the intensity of the radiation source spatially distributed with respect to the lesion in the treatment target is determined to be the optimum value at which the treatment effect is maximized by solving the linear programming problem, the variable for adjustment and the variable A function is set, the constraint value of the constraint condition in the linear programming problem is designated by the value of the function, and the intensity distribution of the radiation source is obtained by repeatedly solving the linear programming problem while sequentially changing the value of the function. This is achieved by a method for optimizing a treatment plan, which has a process of determining an optimum value.

[0005]

In the method for optimizing a treatment plan according to the present invention,
At the constrained point in the human body to be treated, which imposes restrictions such as a lethal dose, a useful dose or less, or a specified dose phase, etc., specifies the respective dose values of the lethal dose, the useful dose, or the specified dose from a function using a variable for adjustment. The optimal spatial distribution of the radiation source intensity around the human body is found by repeatedly solving the linear programming problem while sequentially changing the values of the above-mentioned adjustment variables using possible constraints. In the case where a constraint that specifies a lethal dose, a useful dose or a dose value of a specified dose from a function using a variable for adjustment and a conventional constraint that directly specifies a dose value are mixed in a linear programming problem, The present invention is applicable. However,
When specifying the dose value from the function using the variable for adjustment, the position of the constraint point is within the range where each radiation beam irradiates the human body using a human tomographic image, and two or more radiation beams intersect. At least one point is set in a range excluding a portion to be performed. This makes it possible to derive an optimal solution for realizing decentralized irradiation in the linear programming method without excessively increasing the number of constraint points that increase the calculation time.

For example, the following function is used as a function based on a variable for adjustment. dose (α) = (LD / n) × α where dose (α): dose value (Gy) LD: lethal dose (Gy) n: number of portals α: variable for adjustment This is the lethal dose per gate To find out how much
The value multiplied by α is used as a lethal dose, a useful dose or a specified dose at a certain restriction point. Not only the above functions can be applied, but other functions may be applied. In the treatment plan optimizing method according to the present invention, there is also provided a method of displaying the position of a restriction point on a tomographic image of a human body in order to confirm the position of the restriction point. Indicate the value of the lethal dose, the useful dose, the specified dose phase, etc., and the dose value of the lethal dose, the useful dose or the specified dose from the function using the variable for adjustment, or specify the dose value directly. It is performed so that restriction points can be distinguished for each type of designation.

Hereinafter, the principle of the present invention will be described more specifically. 1. Irradiation method In radiotherapy, a treatment method is used in which the tumor is necrotic by the tissue destruction effect of radiation. For the treatment, a treatment device as shown in FIG. 2 is used. The patient is laid on the treatment couch 201, and the gantry 202 and the treatment couch 201 are rotated to irradiate a tumor in a human body to be treated from various directions with radiation. Radiation is applied to a source 203 in a gantry 202.
From the irradiation head 204 to form a beam and irradiate the tumor. Irradiation methods are broadly classified into two types: multi-port irradiation and rotary irradiation. 1.1. By rotating the gantry 202 and the treatment bed 201, the radiation source 203 is moved in a certain direction with respect to the tumor in the body, and irradiation is performed with the radiation source 203 fixed in that direction.
Multiport irradiation is a method in which the irradiation is performed again by moving the radiation source 203 in another direction, and such a process is performed a plurality of times to give a dose to the tumor. Although multiport irradiation is not simultaneous irradiation from multiple sources, the effect is the same as simultaneous irradiation since the total amount of absorbed dose to the tissue is the sum of the absorbed doses from irradiation from each direction. The number of portals, which means the number of sources, is equal to the number of directions in which the sources are fixed relative to the tumor.

[0008] 1.2. Rotational irradiation While maintaining the treatment bed 201 at an angle, the gantry 2
02 is rotated over a range of a constant rotation speed, so that a continuous irradiation is performed from a source 203 moving at a constant speed on an arc trajectory centered on the tumor in the body to give a dose to the tumor. It is. Usually, since the treatment couch 201 is fixed at several places, it is general to irradiate several arc trajectories. 2. Numerical calculation of absorbed dose distribution Since it is not possible to directly measure the absorbed dose distribution of tissues inside the human body, a physical model is assumed based on the tissue distribution obtained from an image diagnostic device such as an X-ray CT device before treatment. The calculated processing is applied to this data to determine the absorbed dose distribution of the tissue. Numerical calculation method, for example, as in "Radiation Therapy Planning System" (Seiya Inamura, Shinohara Publishing, 1992)
Various algorithms such as the first to third generation algorithms and the Monte Carlo method have been devised depending on the physical model. The Monte Carlo method is currently considered the most accurate calculation method, but it is not used for actual treatment planning due to the enormous calculation time. The calculation methods used in the actual treatment plan are first and second generation algorithms. As the generation progresses, the physical model becomes more sophisticated and accurate, but requires more calculation time. The second generation algorithm seems to be the current limit in practical terms. However, even the second generation algorithm takes a considerable amount of computation time, so it is common to use the first generation algorithm for treatment planning. Since the present invention does not depend on the numerical calculation method, the content of the numerical calculation method will not be described below.

3. Dose Volume Histogram (DVH) FIG. 3A shows an example of the DVH 301. The DVH 301 displays the tissue volume for each absorbed dose in a graph, with the horizontal axis representing the absorbed dose and the vertical axis representing the volume, using the absorbed dose distribution obtained by numerical calculation, for the target tissue or the entire irradiation site. . In the treatment plan, a high dose is given to the tumor, and the dose to normal tissue is minimized according to the irradiation conditions.
Since the absorbed dose distribution is obtained by numerical calculation, a tissue having a volume in the low dose range of the DVH301 is considered to be a normal tissue. A large volume in the low-dose area is a desirable treatment plan. The DVH 301 can also be used to evaluate the irradiation conditions for the tumor, but rather it is used to evaluate the irradiation conditions for the normal tissue from the volume in the low dose range. There is also a cumulative DVH 302. This example is shown in FIG.
It is shown in (b). This focuses on a certain absorbed dose in the DVH301, and calculates the total volume of the tissue that has exceeded that value,
This total volume is displayed corresponding to each absorbed dose of interest. If the volume in the DVH 301 is V (D) and the volume in the cumulative DVH 302 is Vc (D),

(Equation 1) Can be expressed as The cumulative DVH 302 is also used mainly for evaluating irradiation conditions for normal tissues.

[0010] 4. Linear Programming Linear programming is a mathematical technique that finds, as a solution, the value of a variable that minimizes or maximizes a linear objective function under certain linear constraints. An example of formulating a treatment plan by linear programming is described below. This is to determine the weight of each source that minimizes the total output dose by setting the absorbed dose of normal tissue below the tolerable dose, the absorbed dose of the tumor above the lethal dose, and the absorbed dose at the point of interest at the designated dose.

(Equation 2) This is a description assuming multi-port irradiation with a large number of sources, but in the case of rotary irradiation, it is considered to be a formulation in which one orbit is regarded as one long source and the weight for each orbit is determined as a solution. There is no essential difference between multi-port irradiation and rotary irradiation, and both irradiation methods can be treated uniformly by the above-mentioned formulation.

5. How to Display Tissue Absorption Dose Distribution Isodose maps are often used to display the absorbed dose to tissues obtained by numerical calculations. If the 3D absorbed dose distribution of the tissue is used, the absorbed dose distribution on a certain slice plane is used, and if the 2D absorbed dose distribution is used, it is used as it is, and several Points with equal values for each absorbed dose are connected by a line. The result is similar to a contour map, but is called a contour map.
Normally, an isodose map is superimposed on the tissue distribution so that the absorbed dose distribution with respect to the tissue distribution can be evaluated using the isodose map. There is also a display method in which a two-dimensional isodose map is expanded to three-dimensional. In this case, points having the same absorbed dose in the three-dimensional absorbed dose distribution of the tissue are connected to form a surface. This is called the isodosimetric map. There is a problem that the inner surface cannot be seen in the three-dimensional isodosimetric view. For this reason,
It is common to display isodosimetric maps translucently.

[0012] The superposition of the tissue distribution and the isodosimetric view is superimposed and displayed as they are, and they become shadows of each other, making it difficult to observe the internal structure. In addition, there is a display method in which the isodose surface is superimposed on the semi-transparent display. Since an invisible portion still occurs, a method of rotating the three-dimensional image and observing it from the back side, or cutting out a suitable cut surface and observing the inside is adopted. Constraints that impose constraints such as greater than lethal dose, less than useful dose, or specified dose phase are specified for each constraint and the dose value of lethal dose, tolerable dose, or specified dose is specified from a function using a variable for adjustment, or To make it possible to specify the dose value directly or to distinguish it by type,
The position is indicated by a mark or the like determined by being superimposed on the two-dimensional or three-dimensional dose distribution. The details of image processing such as composite display such as superimposition of images and rotation processing and cutting processing of a three-dimensional image are not particularly described below because they do not directly affect the present invention.

[0013]

Embodiments of the present invention will be described below in detail with reference to the drawings. First, an example of a radiotherapy system to which the treatment plan optimization method according to the present invention can be applied,
1 shows an example of a flowchart of the entire radiation treatment plan to which the present invention is applied. Finally, some specific embodiments of the present invention will be described. FIG. 4 shows an example of the radiotherapy system. A human tomographic image obtained from the X-ray CT apparatus 401 is input to the treatment planning apparatus 402. In the treatment planning device 402, the irradiation condition of the radiation is determined by the input of the planner 403 or by an automatic calculation process in the treatment planning device 402. The irradiation conditions of the radiation are input to the control device 405 in the treatment device 404, and the energy of the electron accelerator 406, the rotation angle and the rotation orbital position of the gantry 407, the size of the irradiation field of the irradiation head 408, and the treatment in accordance with the irradiation conditions. The control device 405 controls the horizontal / vertical parallel movement position and the rotation angle of the bed 409.

The treatment planning device 402 refers to a computer system as shown in FIG. This system includes an input device 1002 for inputting data and a display device 100 for displaying a result, in addition to the main body of the computer 1001.
3 and a storage device 1004 for storing the result. FIG. 11 shows an example of the contents of the treatment planning device 402. In the treatment planning device 402, the tissue extraction 11
02, optimization calculation 1103, constraint condition setting / change 110
4, objective function setting / change 1105, dose distribution calculation 110
6, image data 11 via an interface 1101 which is a calculation processing part such as a display calculation 1107 as an input / output unit.
08, extracted data 1109, constraint conditions 1110, parameters 1111, result display 1112, irradiation conditions 1113, etc., are connected to input / output data in a storage device or a display device.

In the treatment plan, first, image data 1108
Is input, and a range to be extracted according to the process of tissue extraction 1102 is input as a parameter 1111 to obtain an extraction result. The result is stored in the storage device as extracted data 1109. Next, inputting the initial value of the irradiation condition 1113 and inputting the parameter 1111 as appropriate according to the processing of the optimization calculation 1103, the constraint condition setting / change 110 is performed.
4, objective function setting / change 1105, dose distribution calculation 110
6 is repeated to determine the optimum irradiation condition 1113, and this is stored in the storage device. Display calculation 1
107, for example, the result display state of the dose distribution 11
Output as 12 is also performed. This processing will be specifically described below with reference to a flowchart.

FIG. 1 shows an example of a flowchart of the entire radiation treatment plan based on the above-mentioned radiation treatment system. Each step will be described. Step 101: A CT image of a human tomographic image is input. Step 102: The planner 403 looks at the CT image displayed on the screen of the treatment planning device 402, specifies a target tissue such as a tumor and a normal tissue, and inputs the positions thereof, or Automatically extracts and calculates the locations of the target and normal tissues. Step 103: The planner 403 inputs parameters relating to irradiation conditions. Step 104: The planner 403 sets the constraint point position and the dose constraint value at that point (lethal dose, usable dose, designated dose)
Enter The system obtains the absorbed dose at the position of the constraint point, and generates constraint conditions (more than lethal dose, less than usable dose, designated dose phase, etc.) for linear programming by associating the constraint value at that point.

Step 105: The planner 403 selects an optimization formula determined in advance, that is, what objective function is to be minimized or maximized, and solves an optimization problem by a linear programming method. . Step 106: If a solution is found, proceed to the next step; otherwise, return to step 104. Step 107: Obtain the absorbed dose distribution by numerical calculation. Step 108: Using the absorbed dose distribution, create respective characteristic diagrams of DVH, cumulative DVH, isodose map, and isodose area map,
Display on the screen. Step 109: If it is desired to change the dose value of the constraint condition, return to step 104; otherwise, proceed to the next step. Step 110: If the shape of each characteristic diagram is desirable, proceed to the next step; otherwise, return to step 104.

Step 111: Output parameters related to irradiation conditions to the control device 405 in the treatment device 404.
There are several existing methods for the extraction calculation in step 102, and the extraction can be realized using them. The extraction result is used when selecting an organization to be changed in restriction or an organization to be displayed in the present invention. Hereinafter, some specific examples of the present invention will be described. These are details of steps 104 to 106 described above. In the following examples, for the sake of simplicity, when setting constraints such as a lethal dose or more, a useful dose or less, or a specified dose phase at a constraint point, the dose value is specified from a function using a variable for adjustment. In this case, the case in which the dose value is directly specified is referred to as the "non-control point method".

1. Embodiment 1 FIG. 5 shows a flowchart. This is an example in which either the objective function that minimizes the total output dose or the objective function that maximizes the dose at a certain point can be selected regardless of the restrictions of the control point method and the restrictions of the non-control point method. The required functionality is the most basic example that is complete. Step 501: If a constraint of the control point method is imposed, the process proceeds to the next step. If a constraint of the non-control point method is imposed, the process proceeds to step 503. Step 502: Input a restriction point position of the control point method. However, whether or not the condition that at least one point exists corresponding to each beam within the range where the radiation beam passes through the inside of the human body and excluding the portion where two or more beams intersect Is input while checking interactively or is automatically specified. In the case of automatic designation, for example, a point on the skin surface where the beam first enters the human body is set as a restriction point of the control point method. After that, input the variable value for adjustment and the type of constraint (more than lethal dose, less than the tolerable dose, or specified dose phase, etc.) and set the constraint condition of the control point method.

Step 503: Input the restriction point position of the non-control point method. However, it is set at an arbitrary position by manual operation, or is automatically set by a random distribution or a distribution on grid points. After that, the dose value and the type of constraint (more than lethal dose, less than useful dose or designated dose phase, etc.)
To set the non-control point constraint. Step 504: Select an objective function that minimizes the total output dose or an objective function that maximizes the dose at a certain point. Step 505: Solve the linear programming problem corresponding to the selected objective function, and obtain the intensity weight of each source (each gate) and orbit. Step 506: If a solution to the linear programming problem is obtained, proceed to the next step; otherwise, return to step 501.

2. Embodiment 2 FIG. 6 shows a flowchart. This is because the objective function that minimizes the total output dose is automatically selected when there is a restriction on the control point method, and the objective function that minimizes the total output dose when there is no restriction on the control point method, or This is an embodiment in which any of the objective functions that maximize the dose at a certain point can be selected. If the control point method is restricted, the objective function that minimizes the total output dose is set, so that the intensity of the source through which the beam passes through the point where the control point method is restricted is less likely to be zero. The intensity of the source through which the beam passes through a point where the restriction of the non-control point method is likely to be zero. The present embodiment forcibly creates a state in which the intensity of the above-mentioned radiation source hardly becomes 0, and is suitable for a case where a treatment plan for irradiating from a distribution direction of points having restrictions of the control point method is made.

Step 601: If the constraint of the control point method is imposed, go to the next step. If the constraint of the non-control point method is imposed, go to step 603. Step 602: Input a constraint point position of the control point method. However, whether or not the condition that at least one point exists corresponding to each beam within the range where the radiation beam passes through the inside of the human body and excluding the portion where two or more beams intersect Is input while checking interactively or is automatically specified. In the case of automatic designation, for example, a point on the skin surface where the beam first enters the human body is set as a restriction point of the control point method. After that, input the variable value for adjustment and the type of constraint (more than lethal dose, less than the tolerable dose, or specified dose phase, etc.) and set the constraint condition of the control point method. Step 603: Set an objective function that minimizes the total output dose.

Step 604: Input the restriction point position of the non-control point method. However, it is set at an arbitrary position by manual operation, or is automatically set by a random distribution or a distribution on grid points. Then the dose value and the type of constraint
(More than lethal dose, less than useful dose, or designated dose phase, etc.) and set the non-control point method constraint. Step 605: Select an objective function that minimizes the total output dose or an objective function that maximizes the dose at a certain point. Step 606: Solving the linear programming problem based on the selected formulation to obtain the intensity weight of each source (each gate) and orbit. Step 607: If a solution to the linear programming problem is obtained, proceed to the next step; otherwise, return to step 601.

3. Third Embodiment FIG. 7 shows a flowchart. This means that if there is a control point constraint, the objective function that maximizes the dose at a certain point is automatically selected, and if there is no control point constraint, the objective function that minimizes the total output dose, or This is an embodiment in which any of the objective functions for maximizing the dose at a certain point can be selected. If there is a restriction on the control point method, an objective function that maximizes the dose at a certain point is set. Is hardly reduced to zero. In this embodiment,
Since this state is forcibly created, it is suitable for the case where a treatment plan for irradiating with diverging directions is made.

Step 701: If the restriction of the control point method is imposed, go to the next step. If the restriction of the non-control point method is imposed, go to step 704. Step 702: Input the restriction point position of the control point method. However, whether or not the condition that at least one point exists corresponding to each beam within the range where the radiation beam passes through the inside of the human body and excluding the portion where two or more beams intersect Is input while checking interactively or is automatically specified. In the case of automatic designation, for example, a point on the skin surface where the beam first enters the human body is set as a restriction point of the control point method. After that, input the variable value for adjustment and the type of constraint (more than lethal dose, less than the tolerable dose, or specified dose phase, etc.) and set the constraint condition of the control point method.

Step 703: An objective function for maximizing the dose at a certain point is set. Step 704: Input the restriction point position of the non-control point method. However, it is set at an arbitrary position by manual operation, or is automatically set by a random distribution or a distribution on grid points. After that, the user inputs the dose value and the type of constraint (more than lethal dose, less than useful dose, or specified dose phase, etc.), and sets the non-control point type constraint condition. Step 705: If there is a restriction on the control point method, select an objective function that maximizes the dose at a certain point. Step 706: Solving the linear programming problem based on the selected formulation to obtain the intensity weight of each source (each gate) and orbit. Step 707: If a solution to the linear programming problem is obtained, proceed to the next step; otherwise, return to step 701.

4. Embodiment 4 FIG. 8 shows a flowchart. This is an embodiment in which a part of the restrictions of the control point method can be changed to the restrictions of the non-control point method in the second and subsequent repetition processes. In the control point method, since the dose value to be imposed as a constraint cannot be determined theoretically, it may be difficult to obtain a solution if the distribution of the points to be constrained becomes complicated during the iterative process. When the user wants to get out of that state, the change as in this embodiment is an effective means. Step 801: If the restriction of the control point method is imposed, go to the next step. If the restriction of the non-control point method is imposed, go to step 803.

Step 802: Input a restriction point position in the control point system. However, whether or not the condition that at least one point exists corresponding to each beam within the range where the radiation beam passes through the inside of the human body and excluding the portion where two or more beams intersect Is input while checking interactively or is automatically designated, for example, a point on the skin surface where the beam first enters the human body is set as a control point type constraint point.
After that, the variable values for adjustment and the types of constraints (more than lethal dose,
(Dose below the durable dose or specified dose phase) and set the control point system constraints. Step 803: If a constraint of the non-control point method is imposed, proceed to step 805. If a part of the constraint of the control point method is changed to a constraint of the non-control point method, proceed to the next step.

Step 804: Change part of the restrictions of the control point method to the restrictions of the non-control point method. That is, some of the restrictions of the control point method are deleted, and they are set as new restrictions of the non-control point method. The setting method is the same as step 805. Step 805: Input the restriction point position of the non-control point method. However, it is set at an arbitrary position by manual operation, or is automatically set by a random distribution or a distribution on grid points. After that, the user inputs the dose value and the type of constraint (more than lethal dose, less than useful dose, or specified dose phase, etc.), and sets the non-control point type constraint condition. Step 806: Select an objective function that minimizes the total output dose or an objective function that maximizes the dose at a certain point,
By solving the linear programming problem based on the formulation, the intensity weight of each radiation source (each gate) and orbit is obtained. Step 807: If a solution to the linear programming problem is obtained, proceed to the next step; otherwise, return to step 801.

5. Embodiment 5 FIG. 9 shows a flowchart. This is an embodiment in which a part of the restrictions of the non-control point method can be changed to the restrictions of the control point method in the second and subsequent repetition processes. In the case of a treatment plan with a simple distribution of points that impose constraints, it may be desirable to actively adopt the control point method in the middle of the iterative process to find more effective irradiation conditions. In that case, the change as in the present embodiment is an effective means. Step 901: If a control point type constraint is imposed, proceed to the next step. If a non-control point type constraint is imposed, proceed to step 905. Step 902: If a constraint of the control point method is imposed, proceed to Step 904. If a part of the constraint of the non-control point method is changed to a constraint of the control point method,
Proceed to the next step.

Step 903: A part of the restriction of the non-control point method is changed to the restriction of the control point method. In other words, some of the restrictions of the non-control point method were removed,
Set them as constraints for the new control point scheme. The setting method is the same as step 904. Step 904: Input a constraint point position of the control point method. However, whether or not the condition that at least one point exists corresponding to each beam within the range where the radiation beam passes through the inside of the human body and excluding the portion where two or more beams intersect Is input while checking interactively or is automatically designated, for example, a point on the skin surface where the beam first enters the human body is set as a control point type constraint point. After that, input the variable value for adjustment and the type of constraint (more than lethal dose, less than the tolerable dose, or the designated dose phase), and set the constraint condition of the control point method.

Step 905: Input the restriction point position of the non-control point method. However, it is set at an arbitrary position by manual operation, or is automatically set by a random distribution or a distribution on grid points. After that, the dose value and the type of constraint (more than lethal dose, less than useful dose or designated dose phase, etc.)
To set the non-control point constraint. Step 906: Select an objective function that minimizes the total output dose or an objective function that maximizes the dose at a certain point,
By solving the linear programming problem based on the formulation, the intensity weight of each radiation source (each gate) and orbit is obtained. Step 907: If a solution to the linear programming problem is obtained, proceed to the next step; otherwise, return to step 901.

The above embodiment is merely an example of the present invention, and it goes without saying that the present invention is not limited to this. For example, as a numerical calculation method used when obtaining the absorbed dose distribution of the internal tissue of the human body by a calculation process assuming a certain physical model using the tissue distribution obtained from an image diagnostic apparatus such as an X-ray CT apparatus as basic data, Various algorithms such as the first to third generation algorithms and the Monte Carlo method have been devised depending on the physical model, but any of these may be used.

[0034]

As described above in detail, according to the present invention, the irradiation directions can be decentralized in the optimization of the radiation treatment plan without excessively increasing the number of constraint points causing an increase in the calculation time. This has a remarkable effect that a treatment plan optimizing method that can derive the irradiation condition as an optimal solution can be realized.

[Brief description of the drawings]

FIG. 1 is an operation flowchart illustrating a treatment plan.

FIG. 2 is a diagram showing a specific configuration example of a radiotherapy apparatus.

FIG. 3 is a diagram illustrating DVH and cumulative DVH.

FIG. 4 is a block diagram illustrating a configuration of a radiotherapy system according to an embodiment;

FIG. 5 is an operation flowchart of the first embodiment.

FIG. 6 is an operation flowchart of the second embodiment.

FIG. 7 is an operation flowchart of the third embodiment.

FIG. 8 is an operation flowchart of the fourth embodiment.

FIG. 9 is an operation flowchart of the fifth embodiment.

FIG. 10 is a diagram illustrating a hardware configuration of a treatment planning device according to an embodiment.

FIG. 11 is a diagram illustrating a functional configuration of a treatment planning device according to an embodiment.

[Explanation of symbols]

 201,409 Treatment bed 202,407 Gantry 203 Source 204,408 Irradiation head 301 DVH 302 Cumulative DVH 401 X-ray CT apparatus 402 Treatment planning apparatus 403 Planner 404 Treatment apparatus 405 Control apparatus 406 Electronic accelerator

Claims (5)

(57) [Claims] 1. An input device for inputting image data and an external command, a computer for processing the input image data according to an external command, a display device for displaying a processing result, and a storage for storing the processing result. Radiation therapy comprising a treatment planning device having a device, and a radiation treatment device having means for controlling the position and direction of the gantry, irradiation head, treatment bed, and energy of the accelerator based on the processing results of the treatment planning device. In the system, when using the treatment planning device to determine the intensity of the radiation source spatially distributed with respect to the lesion in the treatment target to an optimal value that maximizes the treatment effect by solving a linear programming problem, A variable for adjustment and a function based on the variable are set, and a constraint value of a constraint condition in the linear programming problem is designated by a value of the function,
A method of optimizing a treatment plan in a radiotherapy system, comprising a step of repeatedly solving the linear programming problem while sequentially changing the value of the function to determine an intensity distribution of a radiation source to an optimum value. 2. The processing for determining the optimum value includes the following steps: lethal dose, tolerable dose, and designated dose at a constrained point in the body to be treated, which imposes constraints such as a lethal dose, a dose below, or a designated dose phase. 2. A process for determining a radiation source intensity to an optimum value by solving a linear programming problem using a constraint condition in which the intensity of the radiation source can be specified from a function by a variable for adjustment. Method of Optimizing Treatment Plan for Radiation Therapy System in Japan 3. The process of determining an optimal value includes directly calculating a lethal dose, a useful dose, or a dose value of a designated dose at a point of interest in a treatment target body that imposes restrictions such as a lethal dose or more, a useful dose or less, or a specified dose phase. Solving a linear programming problem using constraints that specify the dose value from a function with variables for adjustment in addition to the specified constraints, and has a process of determining the intensity of the radiation source to an optimum value. The method for optimizing a treatment plan in a radiotherapy system according to claim 1, wherein 4. The processing for determining the optimum value is performed when a dose value of a lethal dose, a working dose, or a designated dose is specified from a function using a variable for adjustment. At least one point is located in a range where each radiation beam irradiates the inside of the treatment target using the tomographic image of the treatment target body, and excluding a portion where two or more radiation beams intersect. The method of optimizing a treatment plan in a radiation treatment system according to claim 1, further comprising a process of determining the intensity of the radiation source to an optimum value by setting. 5. The processing for determining the optimum value includes the steps of: setting the position of the constraint point for each constraint such as a lethal dose or more, a dose less than a useful dose, or a designated dose phase, and a dose value of a lethal dose, a useful dose or a designated dose. The intensity of the radiation source can be set to the optimal value by displaying it on the tomographic image of the treatment target so that it can be distinguished for each type, whether it is specified from a function using adjustment variables or the dose value is directly specified. 2. The method for optimizing a treatment plan in a radiotherapy system according to claim 1, further comprising the step of: