Radiation therapy support device and radiation therapy support method

Abstract

To provide a radiation therapy support device and radiation therapy support method capable of performing an appropriate radiation therapy that takes into account individual differences of patients.SOLUTION: A computation processing device 201 adjusts internal parameters of an absolute lymphocyte count (ALC) prediction simulator 210 on the basis of actual measured values of a plurality of second feature quantities measured at mutually-different time points during a period in which radiation therapy is performed so that a three-dimensional dose distribution determined to be acceptable on the basis of the time transition of the second feature quantity output from the ALC prediction simulator 210 is formed in the body of a subject. The computation processing device 201 executes the ALC prediction simulator 210 with the adjusted internal parameters, displays the time transition output from the simulator, and adjusts a target value of a first feature quantity according to an operation from an operator.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present disclosure relates to a radiotherapy support device and a radiotherapy support method.

Background Art

[0002] In radiotherapy, the temporal change in a feature quantity related to cells having high radiosensitivity may affect the prognosis of a patient. For example, lymphocytes including killer T cells and helper T cells involved in cellular immunity are cells responsible for the human immune system and are known to have high radiosensitivity. Among patient groups who have received radiotherapy, it has been reported that a group with a small decrease in the absolute lymphocyte count (ALC) in the blood has a higher probability of a good prognosis (see Non-Patent Document 1).

[0003] The above research results suggest the possibility that the therapeutic effect of radiotherapy can be improved by formulating a treatment plan for radiotherapy so as to suppress the decrease in ALC.

[0004] On the other hand, Patent Document 1 discloses a treatment planning method for suppressing a decrease in ALC by defining a site affected by radiation exposure as a lymphocyte-related organ at risk (LOAR) and giving a dose constraint thereto in the same manner as other general organs at risk (OAR).

[0005] In addition, Non-Patent Document 2 discloses a simulation method for predicting the increase or decrease of ALC by using the dose index of LOAR (such as Dose-Volume Histogram (DVH), etc.) obtained from the treatment plan as an input. Such a simulation method is useful for determining appropriate dose constraints for LOAR. In the technique described in Non-Patent Document 2, based on the measured values of ALC obtained from the treatment results of dozens of patients, the internal parameters of the simulation are adjusted so that the time course of ALC is reproduced on average. The internal parameters include the radiation sensitivity of lymphocytes and the amount of recovery per unit time.

Prior Art Documents

Patent Documents

[0006]

Patent Document 1

[0007]

Non-Patent Document 1

Non-Patent Document 2

Summary of the Invention

Problems to be Solved by the Invention

[0008] There are individual differences in the radiosensitivity of lymphocytes and the amount of recovery per unit time. However, in the technique described in Non-Patent Document 2, these individual differences are not considered, so it may not be possible to accurately predict the increase or decrease of ALC. For this reason, it is difficult to determine appropriate dose constraints for LOAR and treatment plans considering them for individual patients, and it is difficult to perform appropriate radiation therapy considering the individual differences of patients.

[0009] An object of the present disclosure is to provide a radiation therapy support device and a radiation therapy support method capable of performing appropriate radiation therapy considering individual differences of patients.

Means for Solving the Problems

[0010] A radiation therapy support device according to an aspect of the present disclosure is a radiation therapy support device that supports radiation therapy for irradiating a subject with radiation, and includes a recording unit and a control unit. The recording unit stores a simulator that predicts and outputs the time transition of a second feature amount for determining the prognosis of the subject, with the target value of the first feature amount representing the characteristics of the three-dimensional dose distribution formed in the subject's body by radiation irradiation as an input. The control unit adjusts internal parameters of the simulator based on measured values of a plurality of the second feature amounts measured at a plurality of different time points during the period in which the radiation therapy is performed so that the three-dimensional dose distribution determined to be qualified based on the time transition is formed in the subject's body, executes the simulator with the adjusted internal parameters, displays the time transition output from the simulator, and adjusts the three-dimensional dose distribution according to an operation from an operator.

Effects of the Invention

[0011] According to the present invention, it becomes possible to perform appropriate radiation therapy considering individual differences of patients.

Brief Description of the Drawings

[0012]

Figure 1

Figure 2

Figure 3

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Figure 8

Figure 9

Mode for Carrying Out the Invention

[0013] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings.

Example

[0014] FIG. 1 is a schematic configuration diagram showing a configuration example of an adaptive radiation therapy system according to the present embodiment. The adaptive radiation therapy system 100 shown in FIG. 1 is a group of devices for performing radiation therapy for irradiating a patient, who is a subject, with radiation to treat a tumor or the like of the patient, and includes a treatment planning device 200, a radiation irradiation device 300, an inspection device 400, and a database 500.

[0015] The treatment planning device 200 is a radiation therapy support device that supports radiation therapy and is configured by an information processing device (for example, an information processing device such as a computer device) capable of various information processing. As shown in FIG. 1, the treatment planning device 200 includes an arithmetic processing unit 201, an input device 202, a display device 203, a memory 204, and a communication device 205. The arithmetic processing unit 201 is connected to the input device 202, the display device 203, the memory 204, and the communication device 205. This connection method is not particularly limited, and a connection method via a LAN (Local Area Network) or a WAN (Wide Area Network) such as the Internet may be used.

[0016] The arithmetic processing unit 201 is a processor such as a CPU (Central Processing Unit), a GPU (Graphic Processing Unit), and an FPGA (Field-Programmable Gate Array), and constitutes a control unit that controls the entire treatment planning device 200. The input device 202 is a device that receives various information according to an operation from an operator who operates the treatment planning device 200, and is, for example, a mouse and a keyboard. The display device 203 is a device that displays various information such as a treatment plan, and is, for example, a display.

[0017] The memory 204 is composed of a single or a plurality of recording media, and is a recording unit that records a program (computer program) that defines the operation of the arithmetic processing unit 201 and various information used and generated by the arithmetic processing unit 201. The recording media are, for example, a magnetic storage medium such as an HDD (Hard Disk Drive), a semiconductor storage medium such as a RAM (Random Access Memory), a ROM (Read Only Memory), and an SSD (Solid State Drive), a combination of an optical disk such as a DVD (Digital Versatile Disk) and an optical disk drive. The communication device 205 is a communication interface that is communicably connected to an external device. In the example of FIG. 1, the communication device 205 is connected to a radiation irradiation device 300, an inspection device 400, and a database 500.

[0018] At the start of operation of the treatment planning device 200 (for example, when power is turned on), the arithmetic processing device 201 reads a program from the memory 204, executes the read program, and executes various processes related to support for radiotherapy such as creation of a treatment plan, thereby controlling the entire treatment planning device 200.

[0019] Also, in this embodiment, the memory 204 records, as a program, an ALC prediction simulator 210 that is a simulator that takes, as an input, a target value of a first feature quantity representing characteristics of a three-dimensional dose distribution formed in a patient's body by radiation irradiation, and predicts and outputs the time transition of a second feature quantity for determining the patient's prognosis. In this embodiment, the first feature quantity is a dose index based on a dose volume histogram of the LOAR, which is a site that affects the ALC by radiation exposure, and the second feature quantity is the ALC.

[0020] The radiation irradiation device 300 is a device that irradiates a patient with radiation. In this embodiment, the radiation irradiation device 300 irradiates a patient with a particle beam as radiation using a spot scanning method. The spot scanning method is a method in which points (spots) are three-dimensionally arranged inside and around a target region to be irradiated with radiation, such as a tumor, in a patient's body, and a thin beam is irradiated to each spot. In the spot scanning method, a prescribed irradiation dose is determined for each spot. When a prescribed dose is irradiated to a certain spot, the beam is deflected to the next spot to be irradiated and irradiated again. By applying the prescribed dose to all spots, a desired dose distribution is formed in the target region.

[0021] In this embodiment, a radiation irradiation apparatus 300 corresponding to particle beam therapy using a spot scanning method will be described. However, the radiation irradiation apparatus 300 is not limited to this example, and may be an X-ray irradiation apparatus corresponding to intensity modulated radiation therapy (IMRT) or volumetric modulated arc therapy (VMAT) using X-rays. In an X-ray irradiation apparatus corresponding to IMRT or VMAT, X-rays are irradiated from a plurality of directions onto a target region. The dose distribution formed by the X-rays irradiated from each direction within the target region is non-uniform, but a uniform dose distribution that matches the three-dimensional shape of the target region is imparted to the patient's body by superimposing the doses from all directions. At this time, the fluence distribution of the X-rays irradiated from each direction is obtained by solving an inverse problem using the treatment planning apparatus 200. Further, a multi-leaf collimator may be installed between the X-ray source and the isocenter in order to realize an arbitrary fluence distribution of the X-rays.

[0022] The inspection apparatus 400 is an acquisition unit that acquires the patient's ALC as a second feature amount for predicting the patient's prognosis. In this embodiment, the inspection apparatus 400 analyzes the blood collected from the patient to acquire the ALC, but may also receive the ALC measured by another apparatus. The patient's ALC is stored in the database 500.

[0023] FIG. 2 is a flowchart for explaining an example of an adaptive radiation therapy process using the adaptive radiation therapy system 100 of Embodiment 1. Hereinafter, the particle beam may also be referred to as radiation.

[0024] First, the operator collects blood from the patient and inputs it into the inspection apparatus 400. The inspection apparatus 400 analyzes the input blood to acquire the measured value of the patient's ALC and stores it in the database 500 (step S1). Thereafter, a treatment plan creation process for creating a treatment plan is executed.

[0025] In the treatment plan creation process, first, the arithmetic processing unit 201 of the treatment planning apparatus 200 sets a region of interest (ROI) for a CT (Computed Tomography) image, which is a fluoroscopic image of a patient, and records the set ROI in the memory 204 or the database 500 as three-dimensional position information (step S2). The ROI includes a target region (e.g., a tumor, etc.) to which radiation is to be irradiated and an exclusion region where radiation irradiation is to be avoided as much as possible. Also, in this embodiment, the exclusion region includes a LOAR, which is a site that affects the ALC due to radiation exposure, and other general OARs. The LOAR is, for example, a site with a large amount of blood such as the heart, aorta, and lungs. The arithmetic processing unit 201, for example, displays each slice of the CT image of the patient on the display device 203, receives information indicating the target region and the exclusion region for each slice image from the operator via the input device 202, and sets the region of interest based on the information. Note that the arithmetic processing unit 201 may automatically set the region of interest by analyzing the CT image. Also, for one patient, there may be two or more target regions, OARs, and LOARs respectively.

[0026] Furthermore, the arithmetic processing unit 201 sets a dose constraint, which is a constraint regarding the dose of radiation irradiated to the ROI set in step S2, and a weight value for the dose constraint, and stores the set dose constraint and weight value in the memory 204 or the database 500 (step S3).

[0027] In this embodiment, the dose constraint is the target dose D of the dose to be irradiated to the target region, which is the target value. (j) Target The maximum allowable value of the dose irradiated to the OAR is the OAR maximum dose D. (j) max-OAR The maximum allowable value of the dose irradiated to the LOAR is the LOAR maximum dose D. (j) max-LOAR The maximum allowable value per unit volume of the dose irradiated to the OAR is the OAR maximum dose volume ratio V. (j) max-OARand the maximum value of the tolerance per unit volume of the dose irradiated to the LOAR, i.e., the LOAR maximum dose volume ratio V (j) max-LOAR are included. Hereinafter, the OAR maximum dose D (j) max-OAR and the LOAR maximum dose D (j) max-LOAR are collectively referred to as the maximum dose D (j) max and the OAR maximum dose volume ratio V (j) max-OAR and the LOAR maximum dose volume ratio V (j) max-LOAR are collectively referred to as the maximum dose volume ratio V (j) max sometimes.

[0028] The weight values are the target target dose D (j) Target , the OAR maximum dose D (j) max-OAR , the LOAR maximum dose D (j) max-LOAR , the OAR maximum dose volume ratio V (j) max-OAR , and the LOAR maximum dose volume ratio V (j) max-LOAR corresponding weight values w (j) Target , w (j) OAR-Dmax , w (j) LOAR-Dmax , w (j) OAR-Vmax , and w (j) LOAR-Vmax are included.

[0029] Note that the subscript j is an identification number for identifying the target, OAR, and LOAR when there are two or more of each.

[0030] Subsequently, the arithmetic processing unit 201 sets an objective function F(x) for the three-dimensional dose distribution of the entire ROI based on the information (ROI, dose constraint, and weight value) recorded in the memory 204 or the database 500 (step S4). x is a parameter to be optimized, which will be described later, and is a vector with the irradiation dose for each spot as an element. Hereinafter, x may also be referred to as the spot irradiation dose x. In this embodiment, the objective function F(x) is expressed by the following equation. [Equation]

[0031] Here, the subscript i indicates the number of the voxel included in each ROI. Also, d i,j is the dose of the radiation irradiated to the i-th voxel of the j-th ROI. Note that the vector d with the dose of each voxel as an element is obtained as d = Ax from the vector x with the irradiation dose of each spot as an element and the dose matrix A. The dose matrix A represents the dose given to each voxel by the particle beam irradiated to each spot.

[0032] The function θ(y) is a step function, which is 1 when y is positive and 0 otherwise. Also, the function C [a,b] is an interval constraint function and is defined by the following equation. [[ID=•21]][Equation]

[0033] Also, the parameter ΔD that defines the interval of the function C [0,ΔD] in Equation 1 is the difference between the dose D(V (j) max ) at which the maximum dose volume ratio V (j) max is obtained in the DVH curve and the maximum dose D (j) max . FIG. 3 is a diagram showing an example of the parameter ΔD, the DCH curve of the j-th ROI, and the dose D(V (j) max ) at which the corresponding maximum dose volume ratio V (j) max ) is obtained, and the maximum dose D(j) max and parameter ΔD are shown.

[0034] Returning to the description of FIG. 2, when the objective function F(x) is generated in step S4, the arithmetic processing unit 201 calculates the spot irradiation dose x that minimizes the objective function F(x) by optimization calculation (iterative search) (step S5). Specifically, the arithmetic processing unit 201 calculates the dose matrix A by the arithmetic processing unit 201 based on the three-dimensional in-vivo information of the patient obtained from the CT image and the beam irradiation angle of the radiation irradiation device 300 set by the operator, and records it in the memory 204 or the database 500. Subsequently, the arithmetic processing unit 201 obtains the spot irradiation dose x that minimizes the objective function using the dose matrix A by iterative calculation as a treatment plan. The end condition of the iterative calculation can be determined according to indexes such as, for example, the calculation time of the entire iterative calculation, the number of iterations, or the change amount of the objective function per iterative calculation. [[ID=*8]]

[0035] Next, the arithmetic processing unit 201 calculates the three-dimensional dose distribution (vector d having the dose of each voxel as an element) formed in the patient's body based on the spot irradiation dose x calculated in step S5. Further, the arithmetic processing unit 201 calculates the DVH curve and dose index of the LOAR based on the three-dimensional dose distribution and displays them on the display device 203 (step S6).

[0036] FIG. 4 is a diagram showing an example of a display screen for displaying the DVH curve of the LOAR. The display screen 410 shown in FIG. 4 includes the DVH curve 401 of the j-th LOAR and the dose index 402 of the LOAR calculated from the DVH curve 401. The dose index 402 is the first feature amount that becomes the input value of the ALC prediction simulator 210. In the present embodiment, the dose index 402 is the dose-volume ratio V(D (j) max-LOAR when it is the maximum dose D of the LOAR set as the dose constraint in step S3. (j) max-LOAR )

[0037] Return to the description of FIG. 2. The arithmetic processing unit 201 executes the ALC prediction simulator 210 recorded in the memory 204, and uses the dose volume ratio V(D (j) max-LOAR ), which is the dose index calculated in step S6, as the input value of the ALC prediction simulator 210 to predict the time course of the patient's ALC, and displays the prediction result on the display device 203 (step S7).

[0038] In the ALC prediction simulator 210, in addition to the dose index, the initial value of the actually measured value of ALC acquired in step S1 is used. The ALC prediction simulator 210 has internal parameters such as the radiation sensitivity and recovery rate of lymphocytes, and it is necessary to set the values of the internal parameters. In this embodiment, the ALC prediction simulator 210 has the radiation sensitivity and recovery rate of lymphocytes as internal parameters, and predetermined values are used for their initial values. The initial values are, for example, the average radiation sensitivity and recovery rate determined based on past treatment results, and are stored in the database 500 in advance by the operator. The radiation sensitivity is, for example, the reduction rate of ALC when irradiated with a predetermined dose (such as 2 Gy), and the recovery rate is, for example, the recovery amount of ALC during a certain period (about 1 hour to 1 day) after irradiation with a predetermined dose.

[0039] The arithmetic processing unit 201 determines the pass / fail of the treatment plan (more specifically, the spot irradiation dose x) based on the prediction result of the temporal change of ALC by the ALC prediction simulator 210, and displays the pass / fail determination result on the display device 203 (step S8). For example, the arithmetic processing unit 201 determines whether the temporal change of ALC satisfies a predetermined reference condition, and performs the pass / fail determination of the treatment plan. In this embodiment, the reference condition is that the ALC decrease period, which is the period during which ALC is less than the threshold value, does not exceed the reference value. In this case, when the ALC decrease period does not exceed the reference value, the arithmetic processing unit 201 determines that the treatment plan is passed, and when the ALC decrease period is greater than or equal to the reference value, the arithmetic processing unit 201 determines that the treatment plan is failed. However, even when the ALC decrease period is greater than or equal to the reference value, the treatment plan may be determined to be passed based on a comprehensive judgment by an operator such as a doctor. The threshold value and the reference value are set in advance based on clinical experience and the like. Note that the ALC decrease period is represented by the number of days in this embodiment, but is not limited thereto.

[0040] FIG. 5 and FIG. 6 are diagrams showing an example of a display screen for displaying the prediction result of the temporal change of ALC and the pass / fail determination result of the treatment plan.

[0041] The display screen 510 shown in FIGS. 5 and 6 includes the prediction result 501 of the temporal change of ALC, the threshold value 502 for ALC for performing the pass / fail determination of the treatment plan, and the pass / fail determination result 503 of the treatment plan. Further, in the display screen 510, in the prediction result 501 of the temporal change of ALC, a region 504 where ALC is less than the threshold value 502 is highlighted. In the example of FIG. 5, the period during which ALC is less than the threshold value 502 is 5 days, which is shorter than the reference value (16 days in the example of the figure), and therefore, the pass / fail determination result 503 indicates "OK (passed)". On the other hand, in the example of FIG. 6, the period during which ALC is less than the threshold value 502 is 18 days, which is longer than the reference value, and therefore, the pass / fail determination result 503 indicates "NG (failed)".

[0042] Return to the description of FIG. 2. If the treatment plan is unqualified, the arithmetic processing unit 201 checks whether the internal parameters (radiosensitivity and recovery rate) of the ALC prediction simulator 210 have been adjusted in step S14 described later (step S9). Here, the internal parameters of the ALC prediction simulator 210 have not been adjusted yet. In that case, the arithmetic processing unit 201 returns to the process of step S3 and adjusts (re-sets) the weight values for each ROI according to the operation on the input device 202 from the operator, thereby adjusting the treatment plan. At this time, the arithmetic processing unit 201 may display an alert notifying that the treatment plan is unqualified on the display device 203.

[0043] On the other hand, if the treatment plan is qualified, the arithmetic processing unit 201 ends the treatment plan creation process, and the adaptive radiation therapy system 100 irradiates the patient with radiation according to the treatment plan (spot irradiation dose x) created in the treatment plan creation process (step S10). The radiation irradiation is performed in multiple fractions. In this embodiment, one fraction of irradiation is performed per day. Note that the number of fractions is set as part of the treatment plan, for example, but since the setting method and the like are not directly related to the present disclosure, the description thereof is omitted.

[0044] When the radiation irradiation for one fraction is completed by the process of step S10, the adaptive radiation therapy system 100 determines whether the radiation irradiation for all fractions is completed (step S11).

[0045] If the radiation irradiation for all fractions is completed, the process ends. On the other hand, if the radiation irradiation for all fractions is not completed, the operator collects blood from the patient again and inputs it into the inspection device 400. The inspection device 400 analyzes the input blood to re-acquire the measured value of the patient's ALC and stores it in the database 500 together with the date and time of the re-acquisition (step S12).

[0046] Then, the arithmetic processing unit 201 determines whether the measured value of the ALC re-acquired in step S12 is equal to or greater than a predetermined number (step S13). The predetermined number is, for example, 3.

[0047] When the measured value of the ALC is less than a predetermined number, the process of step S10 is executed again. On the other hand, when the measured value of the ALC is equal to or more than the predetermined number, the arithmetic processing unit 201 adjusts the internal parameters of the ALC prediction simulator 210 based on the measured value of the ALC in order to perform adaptive radiation therapy, and stores the adjusted internal parameters in the memory 204 or the database 500 (step S14). As a method for adjusting the internal parameters, for example, a method of adjusting the internal parameters of the ALC prediction simulator so that the time transition of the ALC predicted by the ALC prediction simulator 210 reproduces the measured values of a plurality of ALCs can be mentioned. The measured values of the ALC used for adjusting the parameters may be all the measured values stored in the database 500, or may be a predetermined number or more of measured values selected from those measured values by an arbitrary or predetermined method.

[0048] Thereafter, the process returns to step S7, and the arithmetic processing unit 201 uses the ALC prediction simulator 210 whose internal parameters were adjusted in step S14 with the dose index V(D (j) max-LOAR ) obtained in step S6 as an input to re-predict the time transition of the ALC, and further in step S8, based on the re-predicted time transition of the ALC, the pass / fail determination of the treatment plan is performed again.

[0049] When the treatment plan is passed, the adaptive radiation therapy system 100 proceeds to the process of step S10. On the other hand, when the treatment plan fails, the process proceeds to step S9, and the arithmetic processing unit 201 checks whether the internal parameters of the ALC prediction simulator 210 have been adjusted. Here, the internal parameters of the ALC prediction simulator 210 have been adjusted. In this case, the arithmetic processing unit 201 displays an operation screen for adjusting the dose index set in step S6 on the display device 203, and adjusts the dose index according to the operation on the operation screen (step S15). In this embodiment, the dose volume ratio V(D (j) max-LOAR ) which is the dose index is the target LOAR maximum dose volume ratio V‘ (j) max-LOARAssume that it is adjusted to.

[0050] FIG. 7 is a diagram showing an example of an operation screen. The operation screen 700 shown in FIG. 7 shows the DVH curve 701 of the j-th LOAR and the interface 702 for adjusting the dose constraint. In the example of FIG. 7, the interface 702 is represented by an arrow-shaped symbol and is operated by an operator using the input device 202.

[0051] Returning to the description of FIG. 2. The arithmetic processing unit 201 executes the ALC prediction simulator 210, and as the input value of the ALC prediction simulator 210, instead of the dose index V(D (j) max-LOAR ) obtained in step S6, the target LOAR maximum dose volume ratio V' newly set by adjusting in step S13 (j) max-LOAR is used to re-predict the time course of the patient's ALC, and the re-prediction result is displayed on the display device 203 (step S16).

[0052] FIG. 8 is a diagram showing an example of a display screen for displaying the re-prediction result of the time course of the patient's ALC. In the display screen 800 shown in FIG. 8, the time course 801 of the ALC predicted with the dose index V(D (j) max-LOAR ) obtained in step S6 as the input and the time course 802 of the ALC predicted with the target LOAR maximum dose volume ratio V' newly set in step S13 (j) max-LOAR as the input are superimposed and displayed. Thereby, the operator can confirm the time course of the ALC based on the measured value of the ALC after the start of radiotherapy.

[0053] Return to the description of FIG. 2. The arithmetic processing unit 201 determines whether the treatment plan is acceptable based on the re-prediction result of the time transition of the ALC, and displays the acceptability determination result on the display device 203 (step S17). For example, similar to the processing in step S8, the arithmetic processing unit 201 determines whether the period during which the ALC is less than the threshold exceeds the reference value. If the period does not exceed the reference value, the treatment plan is determined to be acceptable. If the period exceeds the reference value, the treatment plan is determined to be unacceptable. Note that the display screen 800 shown in FIG. 8 includes the threshold value 502 and the acceptability determination result 503 of the treatment plan, similar to the examples in FIGS. 5 and 6.

[0054] When the treatment plan is acceptable, the arithmetic processing unit 201 proceeds to step S3 and updates the LOAR maximum dose volume ratio V (j) max-LOAR to the target LOAR maximum dose volume ratio V' (j) max-LOAR . As a result, the dose index is adjusted according to the operation on the operation screen in step S6, and thus the treatment plan is adjusted. In this embodiment, the dose volume ratio V(D (j) max-LOAR ), which is the dose index, is adjusted to the target LOAR maximum dose volume ratio V' (j) max-LOAR . On the other hand, when the treatment plan is unacceptable, the arithmetic processing unit 201 returns to the processing in step S15 and adjusts the LOAR maximum dose volume ratio V (j) max-LOAR again. At this time, the arithmetic processing unit 201 may display an alert on the display device 203.

[0055] As described above, according to this embodiment, the memory 204 stores an ALC prediction simulator 210, which is a simulator that takes, as an input, a target value of a first feature amount representing the characteristics of the three-dimensional dose distribution formed in the patient's body by radiation irradiation, and predicts and outputs the time course of a second feature amount for determining the patient's prognosis. The arithmetic processing unit 201 adjusts the internal parameters of the ALC prediction simulator 210 based on the measured values of a plurality of second feature amounts measured at different time points during the period when radiation therapy was performed so that a three-dimensional dose distribution determined to be qualified based on the time course of the second feature amount output from the ALC prediction simulator 210 is formed in the subject's body. The arithmetic processing unit 201 executes the ALC prediction simulator 210 with adjusted internal parameters, displays the time course output from the simulator, and adjusts the target value of the first feature amount according to an operation from the operator.

[0056] Therefore, in radiation therapy considering the second feature amount for determining the prognosis, it is possible to adjust the three-dimensional dose distribution formed in the patient's body so as to reflect the measured value of the second feature amount. Accordingly, it becomes possible to perform appropriate radiation therapy considering the individual differences of the patients.

[0057] Further, in this embodiment, the arithmetic processing unit 201 adjusts the internal parameters of the ALC prediction simulator 210 so that the time course of the second feature amount predicted by the ALC prediction simulator 210 reproduces the measured values of the plurality of second feature amounts. For this reason, it is possible to adjust the internal parameters while more appropriately considering the individual differences of the patients.

[0058] Further, in this embodiment, the first feature amount is a dose index based on the dose-volume histogram of the LOAR, which is a site that affects the ALC by radiation exposure. The second feature amount is the ALC. The internal parameters of the ALC prediction simulator 210 include the radiation sensitivity and recovery rate of lymphocytes. For this reason, it becomes possible to more appropriately consider the individual differences of the patients in radiation therapy.

[0059] In addition, in this embodiment, the arithmetic processing unit 201 further displays information indicating whether or not the temporal change of the second feature amount satisfies a predetermined reference condition. In this case, since it becomes possible to easily confirm the validity of the temporal change of the second feature amount, it becomes possible to easily determine the appropriateness of the three-dimensional dose distribution formed in the patient's body.

[0060] In addition, in this embodiment, the reference condition is that the period during which the ALC is less than a predetermined threshold does not exceed the reference value. In this case, it becomes possible to more appropriately determine the appropriateness of the three-dimensional dose distribution formed in the patient's body.

Embodiment

[0061] In this embodiment, the objective function is different from that in Embodiment 1. In the following, mainly the differences from Embodiment 1 will be described.

[0062] FIG. 9 is a flowchart for explaining an example of an adaptive radiation therapy process using the adaptive radiation therapy system 100 of Embodiment 2.

[0063] First, as in Embodiment 1, the operator first collects blood from the patient and inputs it into the inspection device 400. The inspection device 400 analyzes the input blood to obtain the patient's ALC and stores it in the database 500 as the actually measured ALC value (step S21). Thereafter, a treatment plan creation process for creating a treatment plan is executed.

[0064] In the treatment plan creation process, first, the arithmetic processing unit 201 of the treatment planning device 200 sets an ROI for the CT image of the patient and records the set ROI in the memory 204 or the database 500 as three-dimensional position information (step S22).

[0065] Furthermore, the arithmetic processing unit 201 sets a dose constraint and its weight value for the ROI set in step S22, and stores the set dose constraint and weight value in the memory 204 or the database 500 (step S23).

[0066] In this embodiment, the dose constraint is the target dose D (j) Target , the maximum dose D (j) max-OAR of the OAR, the maximum dose volume ratio V (j) max-OAR of the OAR, and the maximum number of days T max of the maximum allowable value of the number of days when the ALC is less than the threshold. The weight values are the target dose D (j) Target , the maximum dose D (j) max-OAR of the OAR, the maximum dose volume ratio V (j) max-OAR of the OAR, and the maximum number of days T max of the maximum ALC reduction, and the corresponding weight values w (j) Target , w (j) OAR-Dmax , w (j) OAR-Vmax , and w (j) T-max .

[0067] Subsequently, the arithmetic processing unit 201 sets the objective function F(x) based on the information (ROI, dose constraint, and weight value) recorded in the memory 204 or the database 500 (step S24). In this embodiment, the objective function F(x) is represented by the following equation.

Equation

[0068] Here, t is the number of days when the ALC calculated by the ALC prediction simulator 210 is less than the threshold. The last term on the right side of the objective function F(x) is a penalty term that increases in the direction away from the optimal value as the period during which the ALC is less than the threshold is longer. In this embodiment, since the objective function F(x) is optimized to be minimized, the penalty term increases as the period during which the ALC is less than the threshold is longer. Note that when the objective function F(x) is optimized to be maximized, the penalty term decreases as the period during which the ALC is less than the threshold is longer.

[0069] When the objective function F(x) is generated in step S24, the arithmetic processing unit 201 calculates the spot irradiation dose x that minimizes the objective function F(x) by optimization calculation (iterative search) (step S25).

[0070] Next, the arithmetic processing unit 201 calculates the three-dimensional dose distribution in the patient's body based on the spot irradiation dose x calculated in step S25. Further, the arithmetic processing unit 201 calculates the DVH curve and dose index of the LOAR based on the three-dimensional dose distribution and displays them on the display device 203 (step S26). The dose index is, as in Example 1, the dose volume ratio V(D (j) max-LOAR at which it becomes (j) max-LOAR ).

[0071] The arithmetic processing unit 201 executes the ALC prediction simulator 210 recorded in the memory 204, and uses the dose volume ratio V(D (j) max-LOAR ), which is the dose index calculated in step S26, as the input value of the ALC prediction simulator 210 to predict the time course of the patient's ALC and display the prediction result on the display device 203 (step S27). The arithmetic processing unit 201 determines the pass / fail of the treatment plan based on the prediction result of the time course of the ALC, and displays the pass / fail determination result on the display device 203 (step S28).

[0072] If the treatment plan fails, the arithmetic processing unit 201 returns to the process of step S23 and adjusts (reset) the weight values for each ROI according to the operation on the input device 202 from the operator to adjust the treatment plan. At this time, the arithmetic processing unit 201 may display an alert on the display device 203 notifying that the treatment plan has failed.

[0073] On the other hand, if the treatment plan passes, the arithmetic processing unit 201 ends the treatment plan formulation process, and the adaptive radiation therapy system 100 irradiates the patient with radiation according to the treatment plan (step S29).

[0074] When the radiation irradiation for one fraction is completed by the process of step S29, the adaptive radiation therapy system 100 determines whether the radiation irradiation for all fractions has been completed (step S30).

[0075] If the radiation irradiation for all fractions has been completed, the process ends. On the other hand, if the radiation irradiation for all fractions has not been completed, the operator collects blood from the patient again and inputs it into the inspection device 400. The inspection device 400 analyzes the input blood, re-acquires the measured value of the patient's ALC, and stores it in the database 500 together with the date and time of the re-acquisition (step S31).

[0076] Then, the arithmetic processing unit 201 determines whether the measured value of ALC re-acquired in step S12 is equal to or greater than a predetermined number (step S32).

[0077] If the measured value of ALC is less than the predetermined number, the process of step S29 is executed again. On the other hand, if the measured value of ALC is equal to or greater than the predetermined number, the arithmetic processing unit 201 adjusts the internal parameters (radiation sensitivity and recovery rate of lymphocytes) of the ALC prediction simulator 210 based on the measured value of ALC in order to perform adaptive radiation therapy, and stores the adjusted internal parameters in the memory 204 or the database 500 (step S33).

[0078] Thereafter, returning to the process of step S27, the arithmetic processing unit 201 uses the ALC prediction simulator 210 after adjusting the internal parameters in step S28 with the dose index V(D (j) max-LOAR ) as an input to re-predict the time course of ALC, and further in step S8, based on the re-predicted time course of ALC, the pass / fail determination of the treatment plan is performed again.

[0079] In this embodiment, the objective function F(x) includes a penalty term that increases in a direction deviating from the optimal value as the period during which the ALC is less than the threshold becomes longer. Therefore, it becomes possible to form a three-dimensional dose distribution considering the period during which the ALC is less than the threshold for the patient.

[0080] The above-described embodiments of the present disclosure are examples for explaining the present disclosure, and are not intended to limit the scope of the present disclosure only to those embodiments. A person skilled in the art can implement the present disclosure in various other ways without departing from the scope of the present disclosure.

[0081] For example, the configurations and processes of the respective embodiments can be applied to other embodiments as long as they do not conflict with each other.

[0082] Also, the second feature amount is not limited to the ALC, and may be the number of killer T cells in the blood, or the number of killer T cells in tumor cells, etc. In the latter case, instead of collecting blood, the number of killer T cells is measured by collecting tumor cells.

Description of Reference Numerals

[0083] 100: Adaptive Radiation Therapy System 200: Treatment Planning Device 201: Arithmetic Processing Device 202: Input Device 203: Display Device 204: Memory 205: Communication Device 210: ALC Prediction Simulator 300: Radiation Irradiation Device 400: Inspection Device 500: Database

Claims

1. A radiotherapy support device for supporting radiotherapy that irradiates a subject with radiation, comprising a recording unit and a control unit, wherein the recording unit stores a simulator that predicts and outputs the time course of a second feature quantity for determining the prognosis of the subject, with the target value of the first feature quantity representing the characteristics of the three-dimensional dose distribution formed in the subject's body by radiation irradiation as an input, and the control unit adjusts the internal parameters of the simulator based on the measured values of the plurality of second feature quantities measured at a plurality of different time points during the period when the radiotherapy is being performed such that the three-dimensional dose distribution determined to be qualified based on the time course is formed in the subject's body, executes the simulator with the adjusted internal parameters, displays the time course output from the simulator, and adjusts the three-dimensional dose distribution according to an operation from an operator.

2. The radiotherapy support device according to claim 1, wherein the control unit adjusts the internal parameters such that the time course reproduces the measured values.

3. The radiotherapy support device according to claim 1, wherein the first feature quantity is a dose index based on a dose volume histogram of lymphocyte-related risk organs, which are sites that affect the number of blood lymphocytes due to radiation exposure.

4. The radiotherapy support device according to claim 1, wherein the second feature quantity is the number of blood lymphocytes.

5. The radiotherapy support device according to claim 1, wherein the internal parameters include the radiation sensitivity and recovery rate of lymphocytes.

6. The radiotherapy support device according to claim 1, wherein the control unit further displays information indicating whether the time course satisfies a predetermined reference condition.

7. The radiotherapy support device according to claim 6, wherein the second feature quantity is the number of blood lymphocytes, and the reference condition is that the period during which the number of blood lymphocytes is less than a predetermined threshold does not exceed the reference value in the time course.

8. The radiotherapy support device according to claim 1, wherein the three-dimensional dose distribution is defined in the treatment plan of the radiotherapy.

9. The radiotherapy support device according to claim 1, wherein the control unit generates the treatment plan by optimizing the objective function targeted by the three-dimensional dose distribution. ​ ​ ​ ​ ​ ​ ​ The radiation therapy support apparatus according to claim 8, wherein the objective function includes a penalty term that increases in a direction deviating from the optimum value as the period during which the second feature amount deviates from a predetermined standard is longer.

10. A radiation therapy support method by a radiation therapy support apparatus that supports radiation therapy for irradiating a subject with radiation, storing a simulator that predicts and outputs the time evolution of a second feature amount for determining the prognosis of the subject, with the target value of the first feature amount representing the characteristics of the three-dimensional dose distribution formed in the subject's body by the irradiation of radiation as an input, adjusting internal parameters of the simulator based on measured values of the plurality of second feature amounts measured at a plurality of different time points during the period in which the radiation therapy is performed so that the three-dimensional dose distribution determined to be qualified based on the time evolution is formed in the subject's body, executing the simulator with the internal parameters adjusted, displaying the time evolution output from the simulator, and adjusting the three-dimensional dose distribution according to an operation from an operator. A radiation therapy support method.

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