Biomarker calculation device, particle beam therapy system, and biomarker calculation method

Abstract

To support determination on the necessity of intervention to radiotherapy.SOLUTION: A biomarker calculation device retains radiotherapy plan information, immune cell number information obtained by recording an influence of irradiation of radiation on the number of immune cells of a patient, and definition information of a prediction model for predicting the temporal transition of the number of immune cells. The prediction model includes internal parameters on the physical characteristics of the patient. The biomarker calculation device determines the internal parameters of the prediction model by using the immune cell number information, predicts the temporal transition of the number of the immune cells of the patient with the radiotherapy by using the radiotherapy plan information and the prediction model, and calculates a biomarker correlated with convalescence based on a result of the prediction.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to a technique for calculating a biomarker for evaluating the prognosis of radiation therapy. [Background technology]

[0002] Lymphocytes, including killer T cells and helper T cells, are responsible for the immune system of the human body and are known to have high radiosensitivity. Several reports have shown that patients who have undergone radiation therapy and have a significant decrease in the absolute lymphocyte count (ALC) in their blood have a poor prognosis (see, for example, Non-Patent Document 1).

[0003] These research results suggest that it may be possible to improve the efficacy of radiation therapy by formulating a radiation therapy plan that does not reduce ALC. Patent Document 1 discloses a treatment planning method that defines the area affected by radiation exposure that affects ALC as lymphocyte-related organ at risk (LOAR) and imposes dose restrictions in the same way as other organs at risk (OAR), with the aim of suppressing lymphocyte count reduction (see, for example, Patent Document 1).

[0004] Non-Patent Document 2 discloses a method for determining parameters such as the radiation sensitivity and recovery rate of lymphocyte count, which differ from patient to patient, using a dose index obtained by a treatment plan, such as a dose-volume histogram (DVH), as an input. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] US Patent Application Publication No. 2023 / 0094681 [Non-patent literature]

[0006] [Non-Patent Document 1] Houat YE. Meta-analysis and Critical Review: Association Between Radio-induced Lymphopenia and Overall Survival in Solid Cancers. Advances in Radiation Oncology. Published online 2023. [Non-Patent Document 2] Jin JY, Mereniuk, et at., A framework for modeling radiation induced lymphopenia in radiotherapy. Radiother Oncol. 2020 Mar;144:105-113. Summary of the Invention [Problem to be solved by the invention]

[0007] Since the radiosensitivity of lymphocytes varies from person to person, even if the radiation dose is the same, the degree of decrease in the number of lymphocytes (survival rate of lymphocytes) varies. In other words, the dose constraint of the LOAR obtained in Patent Document 1 may not necessarily be optimal for each individual patient. Therefore, there is a demand for radiation therapy that can adapt to individual differences in biological responses, such as the radiosensitivity of lymphocytes.

[0008] Furthermore, the technology of Patent Document 1 does not evaluate the extent to which the effect of suppressing the decrease in lymphocyte count affects the prognosis of the patient, making it difficult for doctors to determine whether or not therapeutic intervention is necessary. [Means for solving the problem]

[0009] A representative example of the invention disclosed in the present application is as follows: A biomarker calculation device includes an arithmetic unit and a storage device connected to the arithmetic unit, the storage device stores radiation therapy planning information, immune cell count information recording the effect of radiation exposure on the patient's immune cell count, and definition information of a prediction model for predicting the time transition of the immune cell count, the prediction model including internal parameters related to the patient's physical characteristics, the biomarker calculation device determines the internal parameters of the prediction model using the immune cell count information, predicts the time transition of the patient's immune cell count associated with radiation therapy using the radiation therapy planning information and the prediction model, and calculates a biomarker correlated with prognosis based on the result of the prediction. Effect of the Invention

[0010] According to the present invention, a biomarker correlated with a patient's prognosis can be presented as information for determining whether or not therapeutic intervention is required. Objects, configurations, and effects other than those described above will become apparent from the following description of the embodiments. [Brief description of the drawings]

[0011] [Figure 1] 1 is a diagram illustrating an example of the configuration of a particle beam therapy system according to a first embodiment. [Diagram 2] FIG. 1 is a diagram illustrating an example of the configuration of a biomarker calculation device according to a first embodiment. [Diagram 3] 4 is a flowchart illustrating an example of a biomarker calculation process executed by the biomarker calculation device of the first embodiment. [Figure 4] 2 shows an example of a prediction model used by the biomarker calculation device of the first embodiment. [Diagram 5] FIG. 1 is a diagram showing the predicted results of the time transition of lymphocyte counts output by the biomarker calculation device of Example 1. [Figure 6] FIG. 4 is a diagram showing an example of a processing result of the biomarker calculation device of the first embodiment. [Figure 7] FIG. 2 is a diagram showing an example of a screen displayed by the biomarker calculation device of the first embodiment via a display device. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] Hereinafter, an embodiment of the present invention will be described with reference to the accompanying drawings. However, the present invention is not limited to the description of the embodiment shown below. It is easily understood by those skilled in the art that the specific configuration can be changed without departing from the concept or purpose of the present invention.

[0013] In the configurations of the invention described below, the same or similar configurations or functions are given the same reference numerals, and duplicated explanations are omitted.

[0014] In this specification, the terms "first," "second," "third," and the like are used to distinguish components and do not necessarily limit the number or order.

[0015] In order to facilitate understanding of the invention, the position, size, shape, range, etc. of each component shown in the drawings, etc. may not represent the actual position, size, shape, range, etc. Therefore, the present invention is not limited to the position, size, shape, range, etc. disclosed in the drawings, etc. EXAMPLES

[0016] FIG. 1 is a diagram showing an example of the configuration of a particle beam therapy system 10 according to a first embodiment.

[0017] 1, a particle beam therapy system 10 is a system for performing therapy using a particle beam. The particle beam is, for example, a heavy particle beam such as a carbon beam, or a proton beam. Note that the present invention is not limited to the type of particle beam used.

[0018] The particle beam therapy system 10 includes a particle beam therapy device 100, a treatment planning device 110, a biomarker calculation device 120, an inspection device 130, and a display device 140. Each device is connected via a network 150 such as a wide area network (WAN) or a local area network (LAN). The connection method of the network 150 may be either wired or wireless. Note that the connection method of each device is not limited to a network.

[0019] The testing device 130 is a device for testing the physical condition of the patient 11, such as the number of immune cells. The test is performed at any timing. The testing device 130 of the first embodiment measures the number of lymphocytes contained in blood collected from the patient 11. The testing device 130 manages the test results as lymphocyte count information 221 (see FIG. 2). The test is performed multiple times, and the lymphocyte count information 221 stores multiple pieces of test data including the test results and the test dates and times. The testing device 130 that measures lymphocytes as immune cells may be, for example, an electrical resistance blood cell counter.

[0020] The present invention is not limited to the lymphocyte count, and the white blood cell count, neutrophil count, red blood cell count, or platelet count in the blood may be used. It is known that these cells, like lymphocytes, are reduced by radiation exposure. In addition, if the neutrophil count is significantly reduced during radiation therapy, the risk of infection increases, and treatment may be interrupted, which is related to the prognosis of the patient. The testing device 130 may perform tests on multiple immune cells.

[0021] The treatment planning device 110 is a device for setting a radiation therapy plan for the patient 11 using the particle beam therapy device 100. The treatment planning device 110 manages the set radiation therapy plan as radiation therapy plan information 220 (see FIG. 2). The biomarker calculation device 120 calculates a biomarker correlated with prognosis using information on the physical condition of the patient 11 following treatment. The display device 140 displays various information.

[0022] The particle beam therapy apparatus 100 irradiates a diseased part 12 of a patient 11 in accordance with a radiation treatment plan. The particle beam therapy apparatus 100 includes an accelerator 101, a beam transport device 102, a particle beam irradiation device 103, and a treatment table 104.

[0023] The treatment table 104 is a table for placing the patient 11 and can move the diseased part 12 of the patient 11 to a predetermined position. The accelerator 101 accelerates charged particles and emits them as a particle beam (charged particle beam). The type of the accelerator 101 is not particularly limited, and examples thereof include a synchrotron type accelerator, a cyclotron type accelerator, or a synchrocyclotron type accelerator. The beam transport device 102 transports the particle beam emitted from the accelerator 101 to the particle beam irradiation device 103.

[0024] The particle beam irradiation device 103 irradiates the diseased part 12 of the patient 11 placed on the treatment table 104 with the particle beam transported by the beam transport device 102. The particle beam irradiation device 103 includes, for example, two pairs of scanning electromagnets, a dose monitor, and a position monitor (all are not shown). The two pairs of scanning electromagnets are installed in directions perpendicular to each other and deflect the particle beam so that the particle beam reaches a desired position in a plane perpendicular to the beam axis of the particle beam at the position of the diseased part 12. The dose monitor measures the amount of the irradiated particle beam. The position monitor detects the position through which the particle beam has passed.

[0025] The method of irradiating the particle beam by the particle beam irradiation device 103 is not particularly limited. For example, a scanning method or a line scanning method in which dose distributions formed by thin particle beams are arranged to match the shape of the diseased part 12 can be used. The irradiation method may be a wobbler method, or may be a collimator after spreading the distribution of the particle beam such as a double scatterer method, or an irradiation method of forming a dose distribution matching the shape of the diseased part 12 using a bolus.

[0026] Note that the configuration of the particle beam therapy system 10 shown in FIG. 1 is an example and is not limited thereto. For example, it may be composed only of the particle beam therapy apparatus 100, the biomarker calculation apparatus 120, and the display apparatus 140.

[0027] FIG. 2 is a diagram illustrating an example of the configuration of the biomarker calculation device 120 according to the first embodiment.

[0028] The biomarker calculation device 120 includes an arithmetic unit 200, a storage device 201, a communication device 202, an input device 203, and a display device 204. Each hardware element is connected via an internal bus 205.

[0029] The arithmetic device 200 is, for example, a processor, and executes various calculations. The arithmetic device 200 operates as a functional unit (module) that realizes a specific function by executing processing according to a program stored in the storage device 201. In the following description, when a process is described with the functional unit as the subject, it indicates that the arithmetic device 200 is executing a program that realizes the functional unit. In this embodiment, the arithmetic device 200 functions as a lymphocyte count prediction unit 210 and a biomarker calculation unit 211.

[0030] The storage device 201 is, for example, a semiconductor storage device such as a RAM (Random Access Memory) and a ROM (Read Only Memory), and stores the programs executed by the arithmetic device 200 and various information. The storage device 201 of the first embodiment stores radiation therapy planning information 220 managed by the treatment planning device 110, lymphocyte count information 221 managed by the inspection device 130, and prediction model information 222. The prediction model information 222 is information for managing a prediction model for predicting the time transition of the lymphocyte count. The prediction model will be described later.

[0031] The biomarker calculation device 120 may have a magnetic storage medium such as a hard disk drive (HDD) or a semiconductor storage medium such as a solid state drive (SSD). The programs and information stored in the storage device 201 may be installed via an optical disk such as a digital versatile disk (DVD), a USB memory, or a network.

[0032] The communication device 202 is a device for communicating with an external device via a network. The input device 203 is a device that receives various information from an operator, such as a mouse and a keyboard. The display device 204 is a device that displays various information, such as a display.

[0033] The lymphocyte count prediction unit 210 uses the radiotherapy plan information 220, lymphocyte count information 221, and prediction model information 222 stored in the storage device 201 to predict the temporal change in the lymphocyte count of the patient 11 accompanying radiotherapy, and stores the result of the prediction in the storage device 201.

[0034] The biomarker calculation unit 211 uses the result of the prediction stored in the storage device 201 to calculate a biomarker correlated with the prognosis of the patient 11, and stores the calculated biomarker in the storage device 201.

[0035] Note that the functional units of the biomarker calculation device 120 may be combined into one functional unit or one functional unit may be divided into a plurality of functional units.

[0036] Note that the functional unit may be realized using a virtual computer, a computer system, or a dedicated circuit such as an FPGA (Field-Programmable Gate Array) and an ASIC (Application Specific Integrated Circuit).

[0037] Next, the operation and processing of the particle beam therapy system 10 will be described.

[0038] First, the operator formulates a radiotherapy plan using the treatment planning device 110. The formulation of the radiotherapy plan is carried out, for example, as follows.

[0039] First, the operator operates the treatment planning device 110 to set a region of interest (ROI), i.e., a target region to be irradiated with radiation (e.g., a tumor), and an exclusion area (OAR) to avoid irradiation with radiation, in three-dimensional data of the patient 11 generated using a CT image of the patient 11, or the like.

[0040] Next, the operator operates the treatment planning system 110 to set a dose constraint for the ROI. The dose constraint is, for example, a target dose D (j) _Traget, OAR Maximum Dose D (j) The operator further assigns a weight w (j) _Traget, w (j) Set _(OAR-D_max).

[0041] Here, the subscript j represents an identification number when there are two or more targets and OARs. Next, the treatment planning system 110 determines the radiation dose that minimizes the objective function number F(x) shown in formula (1). Here, x is a parameter to be optimized, and is a vector whose elements are the radiation doses. Note that the arrow of x is omitted due to notation constraints.

[0042]

number

[0043] The subscript i indicates the number of the voxel included in each ROI. d_(i,j) is the dose of the i-th voxel. The function θ(x) is a step function that is 1 if x is positive and 0 otherwise.

[0044] The method of formulating the radiation therapy plan information is not limited to the above-mentioned method.

[0045] FIG. 3 is a flowchart illustrating an example of a biomarker calculation process executed by the biomarker calculation device 120 according to the first embodiment.

[0046] After radiation therapy has started according to the radiation therapy planning information 220, the operator instructs the biomarker calculation device 120 to execute processing. It is assumed that during radiation therapy, the number of lymphocytes contained in the blood of the patient 11 is examined by the examination device 130 at any timing.

[0047] The biomarker calculation device 120 acquires the radiation therapy planning information 220 and the lymphocyte count information 221, and stores them in the storage device 201 (step S301).

[0048] Next, the biomarker calculation device 120 constructs a prediction model using the lymphocyte count information 221 and the prediction model information 222 (step S302).

[0049] As a prediction model for predicting the time course of lymphocyte count, for example, the compartment model described in Non-Patent Document 2 can be used.

[0050] Lymphocytes are abundant in organs such as bone marrow, spleen, and lymph nodes, and are further supplied to the whole body through blood circulation. In the compartment model, the circulation of lymphocytes between these organs is divided into areas called compartments, and modeled as the exchange of lymphocytes between the compartments. The compartment model can further model the decrease in lymphocyte numbers according to the radiation dose irradiated to each compartment, and the decrease due to lymphocyte circulation in the body.

[0051] FIG. 4 shows an example of a prediction model used by the biomarker calculation device 120 of the first embodiment.

[0052] The prediction model shown in Figure 4 consists of five compartments, namely bone marrow, spleen, lymph nodes, lungs, and other organs, and circulating blood connecting each compartment. Each compartment is divided into a non-circulating component that continuously retains lymphocytes, and a circulating component that exchanges lymphocytes through the circulating blood. Lymphocytes are constantly produced in the bone marrow, spleen, and lymph nodes. On the other hand, lymphocytes are consumed in the lungs and other organs. The lightning bolt symbol represents particle beam irradiation.

[0053] The internal parameters such as the number of lymphocytes contained in each compartment and the circulation rate can be determined from literature values ​​or equilibrium conditions that do not change when radiation is not irradiated. In addition, the number of lymphocytes contained in each compartment is reduced according to the dose value of each compartment. A Linear-model or a Linear-Quadratic model can be used for the amount of reduction in lymphocytes. The prediction model includes an internal parameter for reflecting the characteristics of the patient 11 regarding the amount of reduction in the number of lymphocytes due to radiation exposure as an internal parameter related to the physical characteristics of the patient 11. Specifically, it includes an internal parameter representing the radiation sensitivity of lymphocytes (survival rate of lymphocytes for a unit radiation dose). The production rate (recovery rate) of lymphocytes in the bone marrow, spleen, etc. may also be included as an internal parameter.

[0054] The prediction model is not limited to the compartment model shown in Fig. 4. For example, a model in which the blood dose is calculated from the radiation therapy planning information 220 and the lymphocyte count is reduced accordingly may be used. This prediction model also includes internal parameters for reflecting the characteristics of the amount of reduction in the lymphocyte count due to the irradiation of the patient 11 with radiation.

[0055] Here, a method for determining an internal parameter for reflecting the characteristic of the patient 11 regarding the amount of decrease in lymphocyte count due to radiation exposure will be described.

[0056] (Step 1) The biomarker calculation device 120 sets initial values ​​for the internal parameters. The initial values ​​may be set randomly or may be preset.

[0057] (Step 2) The biomarker calculation device 120 acquires test data (first test data) indicating the number of lymphocytes contained in non-irradiated blood and data (second test data) indicating the number of lymphocytes contained in irradiated blood from the lymphocyte count information 221. The lymphocyte count information 221 may include one piece of first test data and one or more pieces of second test data.

[0058] (Step 3) The biomarker calculation device 120 updates internal parameters so as to minimize the error between the lymphocyte count at the dates and times corresponding to the first test data and the second test data in the time progression of the lymphocyte count output by the prediction model and the lymphocyte count contained in the first test data and the second test data.

[0059] The biomarker calculation device 120 repeatedly executes steps 2 and 3 until the error becomes smaller than a predetermined value.

[0060] Note that test results during treatment do not have to be used. For example, the results of a radiation irradiation test using blood collected from the patient 11 before treatment may be used. Specifically, by measuring the change in lymphocyte count while changing the dose of irradiation to the blood, the relationship between the decrease in lymphocyte count and the radiation dose can be evaluated and the radiation sensitivity of lymphocytes can be determined. The recovery rate of lymphocytes may be a statistical value (e.g., average value) obtained by statistically processing past test data or a literature value. Note that the internal parameters may be input by the operator.

[0061] Next, the biomarker calculation device 120 predicts the time transition of the lymphocyte count using the radiation therapy planning information 220 and the prediction model (step S303).

[0062] Next, the biomarker calculation device 120 calculates a biomarker correlated with the prognosis of the patient 11 using the predicted result of the time transition of the lymphocyte count (step S304).

[0063] Various biomarkers are conceivable. For example, the minimum value of the lymphocyte count during treatment may be considered as the biomarker. Alternatively, the number of days during which the lymphocyte count is lower than a preset threshold may be considered as the biomarker. In the present invention, any biomarker may be used as long as it can be calculated using the predicted results of the time course of the lymphocyte count.

[0064] The biomarker calculation device 120 displays the biomarker calculation results on the display device 140 (step S305).

[0065] FIG. 5 is a diagram showing the predicted results of the time transition of the lymphocyte count output by the biomarker calculation device 120 of the first embodiment.

[0066] 5 shows the output of a prediction model in which internal parameters have been determined using four pieces of measurement data included in a period 501. Note that period 501 is the period from the start date of treatment (day 0) to the 23rd day. Graph 502 shows the time progression of the lymphocyte count generated from the measurement data. Graph 503 shows the time progression of the prediction model output by the prediction model.

[0067] FIG. 6 is a diagram showing an example of a processing result of the biomarker calculation device 120 of the first embodiment.

[0068] FIG. 6 shows the results of biomarker calculations when the present invention was applied to 40 cases of patients suffering from lung cancer who underwent chemoradiotherapy.

[0069] In this example, the biomarker calculated is whether the number of days the lymphocyte count (ALC) is 500 counts / μL is more than or less than 16 days. This is because previous research results confirmed that when the number of days the lymphocyte count (ALC) is 500 counts / μL is less than 16 days, the prognosis is good, and when the number of days the lymphocyte count (ALC) is 500 counts / μL is 16 days or more, the prognosis is poor.

[0070] When the biomarkers calculated by the biomarker calculation device 120 were compared with the biomarkers calculated from blood tests, it was possible to predict whether the number of days until the lymphocyte count (ALC) reached 500 counts / μL would be 16 days or longer in 32 of the 40 cases.

[0071] In this example, the internal parameters are determined using lymphocyte count test data obtained at four points during the early stages of treatment, meaning that the patient's prognosis can be predicted with an 80% accuracy rate at roughly half the time during the entire treatment course, which takes 40-50 days. Based on the calculation results, doctors can determine whether or not to take action, such as modifying the treatment plan.

[0072] FIG. 7 is a diagram showing an example of a screen displayed by the biomarker calculation device 120 of the first embodiment via the display device 140. As shown in FIG.

[0073] The screen 700 displays the predicted results of the time course of lymphocyte counts and the calculated results of biomarkers.

[0074] The predicted results of the time transition of lymphocyte count are displayed, for example, as a graph with the number of days elapsed since the start of radiation therapy on the horizontal axis and the number of lymphocytes on the vertical axis. The graph may be displayed with the actual values ​​used to determine the internal parameters superimposed. When the number of days until the lymphocyte count is below a threshold is adopted as a biomarker, the number of days is displayed on the screen 700.

[0075] Note that the screen 700 may display a preset threshold value, a reference value for determining whether the prognosis is good or bad, and the like.

[0076] The operator can check the predicted prognosis of the patient 11 as visual information by referring to the screen 700. This can assist the doctor in determining whether or not treatment intervention is required.

[0077] The present invention is not limited to the above-mentioned embodiment, but includes various modified examples. For example, the above-mentioned embodiment describes the configuration in detail to easily explain the present invention, and the present invention is not necessarily limited to the configuration including all the described configurations. Also, it is possible to add, delete, or replace a part of the configuration of each embodiment with another configuration.

[0078] In addition, the above-mentioned configurations, functions, processing units, processing means, etc. may be realized in part or in whole by hardware, for example, by designing them as integrated circuits. The present invention can also be realized by software program code that realizes the functions of the embodiments. In this case, a storage medium on which the program code is recorded is provided to a computer, and a processor included in the computer reads the program code stored in the storage medium. In this case, the program code itself read from the storage medium realizes the functions of the above-mentioned embodiments, and the program code itself and the storage medium storing it constitute the present invention. Examples of storage media for supplying such program code include flexible disks, CD-ROMs, DVD-ROMs, hard disks, SSDs (Solid State Drives), optical disks, magneto-optical disks, CD-Rs, magnetic tapes, non-volatile memory cards, ROMs, etc.

[0079] Furthermore, the program code for realizing the functions described in this embodiment can be implemented in a wide range of program or script languages, such as assembler, C / C++, perl, Shell, PHP, Python, Java (registered trademark), etc.

[0080] Furthermore, the program code of the software that realizes the functions of the embodiments may be distributed over a network and stored in a storage means such as a computer's hard disk or memory, or in a storage medium such as a CD-RW or CD-R, and the processor of the computer may read out and execute the program code stored in the storage means or storage medium.

[0081] In the above-mentioned embodiment, the control lines and information lines are shown as those considered necessary for the explanation, and not all the control lines and information lines are shown in the product. All the components may be connected to each other. [Explanation of symbols]

[0082] 10 Particle Therapy System 11 patients 12 Affected area 100 Particle beam therapy equipment 101 Accelerator 102 Beam Transport Device 103 Particle beam irradiation device 104 Treatment table 110 Treatment planning device 120 Biomarker Calculation Device 130 Inspection Equipment 140 Display device 150 Network 200 Computing equipment 201 Storage device 202 Communication equipment 203 Input Device 204 Display device 205 Internal Bus 210 Lymphocyte Count Prediction Department 211 Biomarker Calculation Unit 220 Radiation Therapy Planning Information 221 Lymphocyte count information 222 Prediction Model Information 700 screens

Claims

1. A biomarker calculation device, comprising: A computing device and a storage device connected to the computing device, The storage device stores radiation therapy planning information, immune cell count information that records the effect of radiation exposure on the number of immune cells of a patient, and definition information of a prediction model for predicting the time transition of the number of immune cells; the predictive model includes internal parameters relating to physical characteristics of the patient; The biomarker calculation device comprises: Using the immune cell count information, the internal parameters of the prediction model are determined; Using the radiation therapy planning information and the prediction model, predicting a time course of the number of the immune cells of the patient associated with radiation therapy; A biomarker calculation device, characterized in that a biomarker correlated with prognosis is calculated based on the result of the prediction.

2. The biomarker calculation device according to claim 1, A biomarker calculation device characterized in that the internal parameters include a parameter related to radiation sensitivity that represents the survival rate of the immune cells relative to the radiation exposure dose.

3. The biomarker calculation device according to claim 2, A biomarker calculation device characterized in that the internal parameters include parameters related to the generation rate of the immune cells.

4. The biomarker calculation device according to claim 2, A biomarker calculation device characterized in that the immune cell count information includes test data including the number of at least one of lymphocytes, white blood cells, neutrophils, red blood cells, and platelets contained in the blood, and the test date and time.

5. The biomarker calculation device according to claim 1, A biomarker calculation device, comprising: a processor for processing the biomarkers; a processor for processing the biomarkers;

6. 1. A particle beam therapy system, comprising: The present invention includes a particle beam therapy device for irradiating a patient with radiation, a biomarker calculation device, and a display device, The biomarker calculation device holds radiation therapy planning information, immune cell count information that records the effect of radiation exposure on the number of immune cells of the patient, and definition information of a prediction model for predicting the time transition of the number of immune cells, the predictive model includes internal parameters relating to physical characteristics of the patient; The biomarker calculation device comprises: Using the immune cell count information, the internal parameters of the prediction model are determined; Using the radiation therapy planning information and the prediction model, predicting a time course of the number of the immune cells of the patient associated with radiation therapy; Calculating a biomarker correlated with prognosis based on the result of the prediction; The particle beam therapy system according to claim 1, wherein the display device displays the calculation results of the biomarkers.

7. A biomarker calculation method executed by a biomarker calculation device, comprising: The biomarker calculation device includes a calculation device and a storage device connected to the calculation device, The storage device stores radiation therapy planning information, immune cell count information that records the effect of radiation exposure on the number of immune cells of a patient, and definition information of a prediction model for predicting the time transition of the number of immune cells; the predictive model includes internal parameters relating to physical characteristics of the patient; The biomarker calculation method includes: The biomarker calculation device determines the internal parameters of the prediction model using the immune cell count information; a step of the biomarker calculation device predicting a time transition of the number of the immune cells of the patient associated with radiation therapy using the radiation therapy planning information and the prediction model; A biomarker calculation method comprising the steps of: the biomarker calculation device calculating a biomarker correlated with prognosis based on a result of the prediction.

8. The biomarker calculation method according to claim 7, A biomarker calculation method, characterized in that the internal parameters include a parameter related to radiation sensitivity that represents the survival rate of the immune cells relative to the radiation exposure dose.

9. 9. The biomarker calculation method according to claim 8, A biomarker calculation method, characterized in that the internal parameters include parameters related to the generation rate of the immune cells.

10. The biomarker calculation device according to claim 8, A biomarker calculation method characterized in that the immune cell count information includes test data including the number of at least one of lymphocytes, white blood cells, neutrophils, red blood cells, and platelets contained in the blood, and the test date and time.

11. The biomarker calculation method according to claim 7, A biomarker calculation method, comprising a step in which the biomarker calculation device presents the result of the prediction and the calculated biomarker.

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