JP2023157681A - Treatment planning system, treatment planning method, and treatment planning program - Google Patents

Abstract

To understand a light quantity distribution of near-infrared light within a living body.SOLUTION: A treatment planning system 1 includes a computing unit 13 that computes and outputs a near-infrared light quantity distribution, a near-infrared light quantity distribution within a living body, based on calculations of behavior of radiated near-infrared light within the living body. The computing unit 13 may compute the near-infrared light quantity distribution based on calculations using the Monte Carlo method. At least part of the calculations may be executed by a GPU (Graphics Processing Unit). The treatment planning system 1 also includes a setting unit 12 to define an area of interest within the living body. The computing unit 13 may calculate a near-infrared light quantity distribution within the area of interest set by the setting unit 12 in the living body.SELECTED DRAWING: Figure 1

Description

One aspect of the present disclosure relates to a treatment planning system, a treatment planning method, and a treatment planning program that output a near-infrared light amount distribution that is a light amount distribution of irradiated near-infrared light in a living body.

Patent Document 1 listed below discloses a tumor monitoring system for evaluating the effects of radiation therapy.

Special Publication No. 2002-525153

Radiation used in radiotherapy penetrates living bodies. On the other hand, near-infrared light used in photoimmunotherapy is repeatedly scattered within a living body, so it is not possible to understand, for example, the light intensity distribution of near-infrared light within a living body. Therefore, it is desired to understand the light intensity distribution of near-infrared light in living organisms.

A treatment planning system according to one aspect of the present disclosure calculates a near-infrared light amount distribution, which is a light amount distribution of near-infrared light in a living body, based on calculation of the behavior of irradiated near-infrared light in the living body. It is equipped with an arithmetic unit that outputs In such an aspect, the light amount distribution of near-infrared light in the living body is output. This makes it possible to understand the light intensity distribution of near-infrared light within the living body.

A treatment planning method according to another aspect of the present disclosure is a treatment planning method executed by an apparatus, and the treatment planning method is a treatment planning method that is executed by an apparatus, and is based on calculation of the behavior of irradiated near-infrared light in the living body. It includes a calculation step of calculating and outputting a near-infrared light amount distribution, which is a light amount distribution. In such an aspect, the light amount distribution of near-infrared light in the living body is output. This makes it possible to understand the light intensity distribution of near-infrared light within the living body.

A treatment planning program according to another aspect of the present disclosure calculates a near-infrared light amount distribution, which is a light amount distribution of near-infrared light in a living body, based on calculation of the behavior of irradiated near-infrared light in the living body. Make the computer execute the calculation step of calculating and outputting. In such an aspect, the light amount distribution of near-infrared light in the living body is output. This makes it possible to understand the light intensity distribution of near-infrared light within the living body.

According to one aspect of the present disclosure, it is possible to understand the light amount distribution of near-infrared light in a living body.

1 is a diagram illustrating an example of a functional configuration of a treatment planning system according to an embodiment. It is a diagram showing an example of the hardware configuration of a computer used in the treatment planning system according to the embodiment. 1 is a flowchart illustrating an example of processing executed by the treatment planning system according to the embodiment. FIG. 2 is a diagram showing the configuration of a treatment planning program according to an embodiment together with a storage medium. It is a flowchart of an example of near-infrared light behavior calculation by Monte Carlo method. It is a flow chart of an example of burn risk assessment. It is a flowchart of an example of a treatment plan quality determination. 3 is a flowchart of an example of optical parameter distribution setting. It is a figure which shows an example of a volume dose histogram. It is a figure which shows an example of a volume light amount histogram.

Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. In addition, in the description of the drawings, the same elements are denoted by the same reference numerals, and redundant description will be omitted. In addition, the embodiments of the present disclosure in the following description are specific examples of the present invention, and unless there is a statement that specifically limits the present invention, the present invention is not limited to these embodiments.

FIG. 1 is a diagram showing an example of the functional configuration of a treatment planning system 1 according to an embodiment. The treatment planning system 1 is a computer system that outputs a near-infrared light amount distribution that is a light amount distribution of irradiated near-infrared light in a living body.

As shown in FIG. 1, the treatment planning system 1 (treatment planning system) includes a storage section 10, an acquisition section 11, a setting section 12, a calculation section 13 (calculation section), and an evaluation section 14.

Although each functional block of the treatment planning system 1 is assumed to function within the treatment planning system 1, the present invention is not limited to this. For example, some of the functional blocks of the treatment planning system 1 are computer devices different from the treatment planning system 1, and are capable of transmitting and receiving information to and from the treatment planning system 1 as appropriate within the computer device connected to the treatment planning system 1 through a network. It is possible to function while doing so. Furthermore, some functional blocks of the treatment planning system 1 may be omitted, multiple functional blocks may be integrated into one functional block, or one functional block may be decomposed into multiple functional blocks. good.

FIG. 2 is a diagram showing an example of the hardware configuration of a computer used in the treatment planning system 1. Physically, the treatment planning system 1, as shown in FIG. The computer system is configured as a computer system including an input/output device 103 such as a keyboard, microphone, and display, a communication module 104 that is a data transmission/reception device, and an auxiliary storage device 105 such as a hard disk and SSD (Solid State Drive). . Each of the CPU 100, RAM 101 and ROM 102, input/output device 103, communication module 104, and auxiliary storage device 105 may be configured in plural numbers. The functions of each functional block shown in FIG. 1 operate by loading predetermined computer software onto hardware such as the CPU 100 and RAM 101 shown in FIG. This is realized by operating the memory and reading and writing data in the RAM 101 and the auxiliary storage device 105.

Each function of the treatment planning system 1 shown in FIG. 1 will be explained below.

The storage unit 10 stores arbitrary information that is used or output in processing of the treatment planning system 1 and the like. The storage unit 10 may store information calculated by each function of the treatment planning system 1. The information stored by the storage unit 10 may be appropriately referenced by each function of the treatment planning system 1.

The capture unit 11 captures images related to a living body such as a patient. The capture unit 11 may output the captured image to the setting unit 12 , calculation unit 13 , and evaluation unit 14 , or may store it in the storage unit 10 .

The setting unit 12 performs various settings related to calculation by the calculation unit 13 or evaluation by the evaluation unit 14. The setting unit 12 may set a region of interest (ROI) in the living body. The setting unit 12 may set optical parameters related to optics. The setting unit 12 may change settings related to behavior calculation (described later) based on the calculation result by the calculation unit 13. The settings made by the setting section 12 are referred to and used by the setting section 12 itself, the calculation section 13, and the evaluation section 14. The settings made by the setting unit 12 may be output as setting information to the setting unit 12 itself, the calculation unit 13, and the evaluation unit 14, or may be stored in the storage unit 10.

The calculation unit 13 calculates and outputs a near-infrared light amount distribution, which is a light amount distribution of near-infrared light in the living body, based on a behavior calculation that is a calculation of the behavior of the irradiated near-infrared light in the living body. . The calculation unit 13 may output the calculated near-infrared light intensity distribution to the evaluation unit 14, display it on a display or the like that is the input/output device 103, or display it on a network via the communication module 104. It may be transmitted to another device or may be stored in the storage unit 10.

The calculation unit 13 may calculate the near-infrared light amount distribution based on behavior calculation using the Monte Carlo method. At least a portion of the behavior calculation may be executed by a GPU (Graphics Processing Unit). The calculation unit 13 may calculate the near-infrared light intensity distribution in the region of interest set by the setting unit 12 in the living body. The calculation unit 13 may calculate the near-infrared light amount distribution based on behavior calculation using the optical parameters set by the setting unit 12. The calculation unit 13 may display information regarding the near-infrared light amount distribution superimposed on the morphological image of the living body (captured by the capture unit 11). The calculation unit 13 may further calculate and output a histogram based on the near-infrared light amount distribution. The calculation unit 13 may perform behavior calculations based on the settings changed by the setting unit 12. The calculation unit 13 may further calculate and output the heat distribution in the living body based on the behavior calculation. The calculation unit 13 may further calculate and output the risk related to burns based on the behavior calculation.

The calculation unit 13 may output the calculated near-infrared light amount distribution to the image captured by the capture unit 11. The calculation unit 13 may calculate the near-infrared light amount distribution based on the settings made by the setting unit 12.

The evaluation unit 14 evaluates the near-infrared light amount distribution calculated or output by the calculation unit 13 or information based on the near-infrared light amount distribution. The calculation unit 13 may output the evaluation results to the setting unit 12, the calculation unit 13, and the evaluation unit 14 themselves, may display them on a display that is the input/output device 103, or may output them via the communication module 104. The information may be transmitted to another device via a network, or may be stored in the storage unit 10.

FIG. 3 is a flowchart illustrating an example of a process (treatment planning method) executed by the treatment planning system 1. First, the capturing unit 11 captures an image (step S1). Next, the setting unit 12 performs various settings (step S2). Next, the calculation unit 13 calculates and outputs the near-infrared light amount distribution in the living body (step S3, calculation step). Next, the evaluation unit 14 evaluates the near-infrared light amount distribution calculated or output in S3 (step S4). In addition, in S3, the calculation unit 13 may output the image captured in S1, or may calculate the near-infrared light amount distribution based on the settings made in S2.

Next, a treatment planning program 300 for causing a computer to execute a series of processes by the treatment planning system 1 will be explained. As shown in FIG. 4, the treatment planning program 300 is accessed by being inserted into a computer, or is stored in a program storage area 201 formed in a storage medium 200 included in the computer. More specifically, the treatment planning program 300 is stored in a program storage area 201 formed in a storage medium 200 included in the treatment planning system 1.

The treatment planning program 300 includes an acquisition module 301, a setting module 302, a calculation module 303, and an evaluation module 304. The functions realized by executing the import module 301, setting module 302, calculation module 303, and evaluation module 304 are the import section 11, setting section 12, calculation section 13, and evaluation section 14 of the treatment planning system 1 described above. The functions are similar to each other.

The treatment planning program 300 includes (one or more CPUs of) the treatment planning system 1, an acquisition unit 11 that takes in images, a setting unit 12 that makes various settings, and calculates and outputs near-infrared light intensity distribution in the living body. This is a program for functioning as the calculation unit 13 and the evaluation unit 14 that performs evaluation regarding near-infrared light amount distribution.

Note that a part or all of the treatment planning program 300 may be transmitted via a transmission medium such as a communication line, and may be received and stored (including installation) by another device. Furthermore, each module of the treatment planning program 300 may be installed on any of a plurality of computers instead of one computer. In that case, a series of processes of the treatment planning program 300 described above are performed by the computer system made up of the plurality of computers.

Hereinafter, details of the treatment planning system 1 and each function included in the treatment planning system 1 will be explained based on various viewpoints 1 to 4. Part or all of the content of one or more other viewpoints can be incorporated or merged into the content of each viewpoint as appropriate.

<Viewpoint 1>
In the treatment planning system 1 (treatment planning device), a CT image is captured in the capture unit 11 (clinical image capture unit) in order to perform a treatment plan using patient morphology information. In addition, it is assumed that MRI images and PET images will be used to understand the position of the tumor and the shape of normal tissue, so the position and tilt of the MRI image and PET image will be adjusted with respect to the base CT image. It may also have a function of superimposing (fused positioning).

The setting section 12 (region of interest drawing section) sets a target region and a risk organ region as a region of interest (ROI) using the fused and aligned MRI image/PET image. By setting the region of interest, it becomes possible to calculate the amount of light and heat in the target and risk organs. Furthermore, since the skin/mucosal region is the region most intensely irradiated by the Frontal light diffuser (described later), and there is a risk of burns, heat amount prediction may be performed by setting a separate region.

The setting section 12 (light source setting section) sets the reference coordinates of the light source and the irradiation direction vector (in the case of a cylindrical light diffuser), depending on the type of light source used (Frontal light diffuser or Cylindrical light diffuser (described later)). Set the vector connecting both ends of the light source), the irradiated range (diameter for Frontal light diffuser, length for Cylindrical light diffuser), and irradiation time.

The setting section 12 (calculation condition setting section) has a function that allows setting the optical parameters (refractive index, absorption coefficient, scattering coefficient, etc.) necessary for calculating the behavior of near-infrared light for each region (soft tissue, bone, air, etc.). has. Setting the calculation area, calculation resolution, and number of generated photons affect calculation accuracy and calculation time, so consideration is given to ensuring that calculations can be performed with the minimum necessary area and resolution. Furthermore, since the number of generated photons directly affects the statistical calculation accuracy, it becomes possible to calculate the estimated calculation accuracy.

The calculation unit 13 (near-infrared light behavior calculation unit) calculates the behavior of near-infrared light that reproduces physical processes. Using the optical parameters set for each region, the near-infrared light intensity distribution is calculated, taking into account the processes of reflection, refraction, scattering, and absorption. The Monte Carlo method may be used for calculations in complex systems within the human body. Furthermore, since near-infrared light is converted into heat at the corresponding location through the absorption process, the heat absorption distribution may be calculated.

The evaluation unit 14 (treatment plan evaluation unit) displays the near-infrared light amount distribution superimposed on the CT image, and qualitatively confirms that the target region is appropriately irradiated with near-infrared light. Also, while checking the near-infrared light intensity distribution, adjust the position (coordinates), direction vector, and irradiation time of each light source. In addition, by setting the minimum prescribed light amount necessary for treatment and calculating a photons volume histogram (PVH) of the region of interest, it is possible to check whether the prescribed light amount is being delivered to the target area or whether excessive amounts are being delivered to risk organs. Check that near-infrared light is not being irradiated. Note that a reaction volume histogram (RVH) that takes into account the accumulated amount of a drug (such as IR-700) that reacts with near-infrared light may be used. Concerning the drug distribution, calculations that incorporate the distribution of drugs that respond to near-infrared light may be included. Furthermore, the presence or absence of burn risk is determined from the calculated maximum temperature of the skin and mucous membranes. Calculation accuracy may affect the quality of the treatment plan, so if the estimated calculation accuracy is insufficient, calculations are performed with increased statistical accuracy by increasing the number of generated photons.

FIG. 5 is a flowchart of an example of near-infrared light behavior calculation using the Monte Carlo method. First, the importing unit 11 reads a morphological image (step S10). The importing unit 11 or the setting unit 12 defines the shape of the calculation system using three-dimensional voxels using the loaded morphological image (CT image). Next, the setting unit 12 sets optical parameters (step S11). Specifically, the setting unit 12 sets optical parameters such as refractive index, absorption coefficient, and scattering coefficient for each voxel of the three-dimensional voxel calculation system. The setting unit 12 may normally set common parameters for each region, such as biological soft tissue, bone, and air. Next, the calculation unit 13 generates photons at the light source position (step S12). Frontal light diffuser generates photons as a point light source. In the case of a cylindrical light diffuser, a random number is used as a line light source to generate photons with equal probability on a line.

Next, the setting unit 12 or the calculation unit 13 sets the light source (or photon) direction vector (step S13). In the case of a Frontal light diffuser, the vector of each photon is set using random numbers with respect to the irradiation direction vector so that the light intensity distribution is uniform in a cone shape or a hexagonal pyramid shape. In the case of a cylindrical light diffuser, the vector of each photon is set isotropically using random numbers. Note that the shape of the direction vector distribution may be changed depending on the characteristics of the diffuser. Next, the setting unit 12 or the calculation unit 13 determines the reaction position (step S14). Specifically, we create a probability distribution function that matches the mean free path (distance at which a photon is attenuated to 1/e due to scattering, absorption, etc.) calculated from the absorption coefficient and scattering coefficient, and use random numbers to calculate the probability distribution function. Determine the reaction point.

Next, the calculation unit 13 determines deviation from the calculation system (step S15). If it is determined in S15 that the determined reaction position deviates from the calculation system (S15: Yes), photon tracking is ended (Step S16). On the other hand, if it is determined in S15 that the determined reaction position does not deviate from the calculation system (S15: No), the calculation unit 13 determines a boundary where the refractive index differs (Step S17).

If it is determined in S17 that the reaction position is a boundary between regions with different refractive indexes (S17: Yes), the setting unit 12 or the calculation unit 13 sets a new direction vector as reflection or refraction depending on the incident angle. settings (step S18). On the other hand, if it is determined in S17 that the reaction position is not a boundary between regions with different refractive indexes (S17: No), the calculation unit 13 performs behavior selection using random numbers (Step S19). Specifically, scattering or absorption is selected by random numbers using a probability distribution function calculated from the absorption coefficient and the scattering coefficient.

Following S18, or when scattering is selected in S19 (S19: Scattering), the setting unit 12 or calculation unit 13 adds the light amount to the photon passing voxel (Step S20). Specifically, the passage length through the voxel is calculated, and the amount of light corresponding to the passage length is added to the voxel. Next, the process returns to S13.

On the other hand, if absorption is selected in S19 (S19: Absorption), the calculation unit 13 adds the amount of heat to the reaction position (Step S21). Specifically, when near-infrared light is absorbed, it is converted into heat, so the heat is added to the absorbed voxel. Next, the process advances to S16.

FIG. 6 is a flowchart of an example of burn risk assessment. First, the calculation unit 13 performs near-infrared light behavior calculation (step S31) using the light source information in the initial setting (step S30), and calculates the near-infrared light absorption distribution (step S32). Next, the calculation unit 13 calculates the temperature of the skin and mucous membranes from the near-infrared light absorption distribution (step S33), and calculates the maximum temperature of the skin and mucous membranes at a permissible temperature (for example, 50°C as a risk of burn injury). 5 minutes of irradiation, etc.) (step S34), and if the allowable temperature is exceeded (S34: No), it is determined that there is a risk of burn injury (step S35), and the light source setting is changed (step S36). ), return to S31. On the other hand, if the temperature does not exceed the allowable temperature (S34: Yes), it is determined that there is no risk of burn injury (Step S37).

FIG. 7 is a flowchart of an example of determining the quality of the treatment plan. First, the calculation unit 13 performs near-infrared light behavior calculation (step S41) using the initially set light source information (step S40), and calculates the near-infrared light amount distribution (step S42). Next, the calculation unit 13 calculates the PVH or RVH for the target region and the risk organ (step S43), and determines whether the prescribed light amount is being delivered to the target region (step S44), and whether the risk organ is irradiated with an excessive amount of light. It is checked whether it has been done (step S45). Furthermore, the calculation unit 13 checks whether there is any risk of burns to the skin and mucous membranes (step S46). If there is a problem with these (S44: No, S45: No, or S46: Yes), change the light source settings (Step S48) and calculate the near-infrared light behavior again (return to S41). Repeat the checking process until the problem is resolved. If all the conditions are met (S44: Yes, S45: Yes, and S46: No), the treatment plan ends (Step S47).

FIG. 8 is a flowchart of an example of optical parameter distribution setting. First, the setting unit 12 defines the shape of the calculation system using three-dimensional voxels from the morphological image (CT image) (step S50). Next, the setting unit 12 defines biological soft tissues, bones, air, etc. as regions of interest (step S51). Next, the setting unit 12 defines optical parameters such as refractive index, absorption coefficient, and scattering coefficient for each region of interest (step S52), and defines optical parameters such as refractive index, absorption coefficient, and scattering coefficient for each voxel within the region of interest. Optical parameters such as coefficients are set as a three-dimensional optical parameter distribution (step S53). Next, the calculation unit 13 uses the three-dimensional optical parameter distribution to calculate near-infrared light behavior in a complex system (step S54).

The above is the explanation of viewpoint 1.

<Viewpoint 2>
Photoimmunotherapy involves intravenously administering a drug containing an anti-EGFR antibody such as Cetuximab and a light-reactive reagent (IRDye-700DX), and irradiating near-infrared light near the affected area, which targets only tumor cells with immunogen. This is a new cancer treatment that can induce sexual cell death. In photoimmunotherapy, therapeutic effects can be obtained by irradiating tumor cells with an appropriate amount of near-infrared light, but until now there has been no device that can visualize the distribution of near-infrared light within the body. Furthermore, conventionally, the range and position of near-infrared light irradiation have been determined based on the operator's experience.

The treatment planning system 1 includes a near-infrared light visualization device (computation unit 13) that simulates the behavior of near-infrared light in the body using the Monte Carlo method and visualizes the distribution of near-infrared light emitted from a light source in the body. The treatment planning device may include a light source placement optimization device (computation unit 13) for calculating a light source position for delivering an appropriate amount of near-infrared light to a tumor.

[Overview of treatment planning device]
Similar to a treatment planning device in radiation therapy, (the importing unit 11) reads a morphological image such as a CT image as a base, and (the setting unit 12) sets the light source position on the CT image. 13) Display the near-infrared light amount distribution on the CT image. Further, by setting a region of interest (ROI) (by the setting unit 12), detailed near-infrared light intensity distribution information within the ROI is acquired, and it is determined whether a sufficient amount of light is being administered for treatment. For calculating the behavior of near-infrared light (by the calculation unit 13), a highly accurate calculation algorithm based on a theoretical physical process such as the Monte Carlo method is used.

[Near-infrared light behavior calculation unit using Monte Carlo method (treatment planning system 1)]
The near-infrared light behavior calculation system (treatment planning system 1) using the Monte Carlo method is capable of calculating behavior for any light source. By calculating the behavior of each photon (by the calculation unit 13), it is possible to compile the near-infrared light amount distribution in any system. For example, (the calculation unit 13) may calculate the behavior of near-infrared rays by optical simulation, and calculate the spread of near-infrared rays as the intensity distribution of near-infrared rays.

[Near-infrared light intensity distribution display section (treatment planning system 1)]
In the treatment planning of photoimmunotherapy, it is very important to understand the near-infrared light intensity distribution in the body. There may also be a function (calculating unit 13) for superimposing and displaying near-infrared light intensity distributions.

[ROI drawing section (treatment planning system 1)]
In the treatment plan, a region of interest (ROI) is set on a morphological image such as a CT image (by the setting unit 12), and the treatment effect is predicted by analyzing the information within the ROI (by the calculation unit 13). . Further, it may have a function (calculation unit 13) that can highlight a tumor lesion using a functional image such as PET/MRI, and create an ROI by superimposing it on a CT image.

[Volume light intensity histogram calculation unit (treatment planning system 1)]
In order to quantitatively predict the therapeutic effect on a tumor, the near-infrared light intensity distribution within the tumor ROI may be converted into a histogram (by the calculation unit 13). Quantitative analysis becomes possible by calculating (by the calculation unit 13) a photon volume histogram (PVH) similar to the dose volume histogram (DVH) used in the radiation therapy field.

[Calorie distribution display section (treatment planning system 1)]
Near-infrared light is converted into heat when absorbed within the body. In photoimmunotherapy, irradiation is performed at an energy density of 50 J/cm ² with a Frontal diffuser and 100 J/cm ² with a Cylindrical diffuser, but there are concerns about burns due to temperature rise in areas that are directly irradiated with near-infrared light. Ru. In the Monte Carlo simulation (by the calculation unit 13), it is possible to calculate not only the near-infrared light intensity distribution but also the absorption distribution of near-infrared light, so a function to display the temperature rise distribution in the body is implemented. Good too.

[Burn Prediction Department (Treatment Planning System 1)]
By calculating the risk of occurrence of burns (by the calculation unit 13) from the temperature increase distribution calculated by the heat distribution display device (calculation unit 13), it is possible to avoid burns.

[Treatment planning system GUI]
The treatment planning device may be broadly divided into five functions.
(1) CT/PET/MRI image reading and positioning function (Fusion) (importing unit 11)
(2) Region of interest (ROI) drawing function (setting section 12 and calculation section 13)
(3) Light source setting function (setting section 12 and calculation section 13)
(4) Calculation condition setting and optimization function (setting section 12 and calculation section 13)
(5) Treatment plan evaluation function (calculation unit 13 and evaluation unit 14)

(1) CT/PET/MRI image reading and positioning function (Fusion)
(The importing unit 11) may read in a CT image as a base morphological image, and may additionally read in functional images such as PET and MRI in order to obtain tumor position information. Since CT images and PET/MRI images are usually captured by different devices, (the capture unit 11) may be equipped with a function of aligning the CT images with the CT images.

(2) Region of interest (ROI) drawing function (The setting unit 12) is equipped with a function to set a region of interest not only for the tumor, which is the treatment target site, but also for the skin surface and mucous membrane tissues where burns and the like are concerned. Good too. The region of interest setting information may also be used for setting optical parameters and evaluating treatment plans.

(3) Light source setting function In photoimmunotherapy, two types of light sources, Frontal diffuser and Cylindrical diffuser, can be used, so there may be a function (setting unit 12 or calculation unit 13) to set the position of each light source. . These light source positions may also be displayed (by the setting unit 12 or the calculation unit 13) on the CT image and the rendered 3D image of the patient's skin surface.

(4) Calculation condition setting and optimization function Because it takes a certain amount of time to calculate the near-infrared light intensity distribution, (the setting unit 12) may be able to set the calculation range and resolution in advance so that the calculation can be executed efficiently. good. Further, since the optical parameters of the living tissue greatly affect the accuracy of near-infrared light behavior calculation, the setting unit (the setting unit 12 or the calculation unit 13) may be able to be set for each patient. In addition, there is an optimization function that automatically calculates each irradiation time for the set light source position, and an optimization function that automatically fine-tunes the light source position itself to enable appropriate irradiation of the tumor. (setting section 12 or calculation section 13) may be provided.

(5) Treatment plan evaluation function (the calculation unit 13 or the evaluation unit 14) calculates a volumetric light intensity histogram within the region of interest from the near-infrared light distribution, and confirms that the light intensity necessary for treatment is delivered throughout the tumor. You may implement a function that allows confirmation. Further, (the calculation unit 13 or the evaluation unit 14) may enable efficient treatment planning by changing the histogram in real time when changing the intensity (irradiation time) of each light source. Furthermore, (the calculation unit 13 or the evaluation unit 14) may calculate the amount of heat due to absorption of near-infrared light, predict the temperature rise of the skin and mucous membrane surfaces, and prevent burns.

The above is the explanation of viewpoint 2.

<Viewpoint 3>
Photoimmunotherapy can induce immunogenic cell death only in tumor cells by intravenously administering a drug containing an anti-EGFR antibody and a light-reactive reagent and irradiating near-infrared light near the affected area. It is a possible new cancer treatment. Problems with current procedures include the inability to accurately determine the irradiation area, the amount of irradiation, and the inability to accurately control the irradiation location. The treatment planning system 1 is a system that can accurately calculate the behavior of near-infrared light emitted from a light source (treatment planning device) and can realize highly accurate photoimmunotherapy.

The treatment planning system 1 has a function (setting unit 12) for setting a tumor ROI (region of interest) on a CT image, a function (calculating unit 13) for calculating the light intensity distribution of irradiated near-infrared light, and a function (operating unit 13) for setting a tumor ROI (region of interest) on a CT image. A function for calculating the light intensity distribution as a light intensity volume histogram (calculation unit 13), a function for optimizing the light source position for uniform irradiation of the tumor ROI (setting unit 12 or calculation unit 13), and the like are implemented.

In order to reproduce the behavior of near-infrared light, the treatment planning system 1 (computation unit 13) implements a high-speed Monte Carlo optical transport calculation algorithm using a GPU, and visualizes the near-infrared light distribution in the body.

The treatment planning system 1 (treatment planning device) (the calculation unit 13) is mainly divided into a Monte Carlo calculation for calculating the behavior of near-infrared light and a GUI (Graphical User Interface). Monte Carlo calculation for near-infrared light allows (the calculation unit 13) to calculate the light amount distribution in the body for any light source. If the optical parameters are literature values for biological soft tissues, the values may be different in actual patients. Therefore, for example, optical parameters for near-infrared light may be measured for each patient. Further, the GUI may include functions such as CT image capture, ROI setting function, light amount volume histogram, etc. (capture unit 11, setting unit 12, or calculation unit 13).

Because near-infrared light travels through repeated scattering and absorption within a living body, these optical parameters greatly affect calculation accuracy. In order to confirm the validity of the optical parameters, a verification experiment using laboratory animals or the like may be conducted. In addition, in the Monte Carlo method, the number of photons to be tracked has a large effect on calculation accuracy, so it may require a large amount of calculation time. In photoimmunotherapy, it is necessary to plan a treatment using a patient's morphological image such as a CT image taken at the surgical site, so it is desirable that the time required for the treatment plan be as short as possible. Since parallel calculation is effective as a method of shortening the time for calculating the light amount distribution, a GPU (for the calculation unit 13) may be used.

[Photoimmunotherapy (head and neck Illuminox treatment)]
This is a treatment method in which a drug that reacts to light is administered, and once the drug has sufficiently concentrated on the cancer, the cancer is treated with a laser beam. Photoimmunotherapy drugs combine light-reactive substances (e.g., IRDye 700 DX) with proteins (e.g., anti-EGFR antibodies such as Cetuximab) that attach to markers (antigens) that are abundant on the surface of cancer cells. It is labeled. Due to the drug's tumor selectivity, it does not attach to normal cells. As for its action, when a photoimmunotherapy drug is administered intravenously (infusion), it gradually accumulates in cancer cells, and its adhesion to cancer cells is saturated in about one day. By irradiating them with near-infrared laser light, a photochemical reaction is induced, causing the cancer cells to burst and die. The advantage is that unlike anticancer drugs, there are no side effects outside the treatment area, and there is no damage outside the cancer cells. In addition to its ability to directly kill cells, it can also activate immunity against cancer, leading to prevention of cancer recurrence. There are two irradiation methods: ``irradiation from inside the body through a catheter'' and ``irradiation from outside the body.''

According to the treatment planning system 1, it is possible to visually confirm the reach range of near-infrared light and to confirm that sufficient near-infrared light is being delivered to the tumor.

The treatment planning procedure for "irradiation from within the body through a catheter" is as follows.
(1) Identify the location of the tumor using PET images taken before surgery.
(2) Puncture multiple needle catheters so that the tumor is irradiated with sufficient near-infrared light.
(3) CT imaging is performed, and the ROI of the tumor is set on the CT image (by the setting unit 12).
(4) (The calculation unit 13) calculates the behavior of near-infrared light from a light source placed in the needle catheter, and obtains the near-infrared light intensity distribution inside the body.
(5) (The evaluation unit 14) quantitatively evaluates the amount of near-infrared light delivered to the tumor, and if the delivered amount is insufficient, puncture points are added as appropriate.
(6) Confirm that the prescribed amount of light is being delivered to the tumor and actually irradiate it.
In the "irradiation from outside the body" method, a similar treatment plan is performed by adjusting the irradiation position, irradiation direction, number of light sources used, etc.

For current radiation therapy, established treatment planning devices are commercially available, so radiation distribution can be predicted through simulation. Therefore, radiation treatment plans can also be made. On the other hand, for photoimmunotherapy, no established treatment planning device is commercially available. According to the treatment planning system 1, the behavior of near-infrared rays is simulated, and the location of the catheter, the distribution of light, the irradiation time, the expected therapeutic effect, etc. can be predicted in advance. In order to reproduce the behavior of near-infrared light, the treatment planning system 1 may implement a high-speed Monte Carlo optical transport calculation algorithm using a GPU or the like to visualize the light intensity distribution in the body.

[Optical simulation]
Ray tracing is a method of simulating an image observed at a certain point by tracing light rays. For example, in the case of light rays, it is possible to obtain images that minutely reflect the reflectance, transparency, refractive index, etc. of the object's surface, and because the path of the light ray is calculated pixel by pixel, it is possible to draw realistically. On the other hand, the amount of calculation becomes extremely large. GPUs for ray tracing are being developed.

The Monte Carlo method is a method of tracking each light beam, and among ray tracing methods, it is a method that reduces the amount of calculation to a realistic amount by limiting it to only directions randomly selected using random numbers. be. Since it is easy to incorporate differences in optical parameters such as bone, tumor, and non-tumor in the body as a structure, it may be employed in the simulation (by the calculation unit 13) of the treatment planning system 1. Note that the ray tracing (by the calculation unit 13) of the treatment planning system 1 may employ any other ray tracing.

Ray tracing on GPU can be accelerated. Because the scattering is large and the distance that light travels is short, faster processing is possible than with radiation treatment planning devices. For example, a CPU-based simulation takes about 1 minute to calculate 10 ⁶ photons, but a GPU-based simulation can speed up the calculation by more than 1000 times.

The treatment planning system 1 may create a database of scattering and absorption conditions in the body (stored in the storage unit 10 or the like) in advance and use the database as appropriate. These may be set with reference to literature values, or, since these parameters may vary greatly depending on the individual, optical parameters of the individual patient may be measured in advance and set.

The most important conditions in the simulation are whether a sufficient amount of light is delivered to the tumor (no omissions) and whether serious side effects will occur.

[light source]
The wavelength of the light source used in photoimmunotherapy is in the near-infrared region. The wavelength used in radiation therapy is X-rays. Radiation therapy uses different wavelengths and has a different range within the body (about 1 cm). Simulation is important because near-infrared light scatters so much that it hardly reaches inside, and even if you try to focus it, you can't. For example, near-infrared light at 690 nm may be used in photoimmunotherapy. This is the result of considering the limit wavelength at which energy can be imparted through photochemical reactions within the wavelength range that easily passes through living organisms, known as the ``biological window.'' Since it is practical to limit the wavelength within the window of the living body, the wavelength range may be 650 to 1000 nm. Although simulation results vary depending on the wavelength, a monochromatic light source may usually be used. (The setting unit 12) may change optical parameters such as scattering and absorption according to the wavelength of the light source used. Radiation passes straight through the body, whereas near-infrared light is frequently scattered inside the body and hardly passes through (absorbed at the surface), so the physical processes are completely different, so radiation simulation and Near-infrared light simulation is a completely different matter. Near-infrared light is converted into heat when absorbed within the body. There is a concern about burns due to temperature rise near the light source. In photoimmunotherapy, near-infrared light irradiation is performed for 4 to 5 minutes, so the threshold may be about 50 to 51°C.

[Irradiation method]
The irradiation method is external irradiation (using a Frontal diffuser) or internal irradiating (using a Cylindrical diffuser). The irradiation method may be continuous irradiation or intensity modulation irradiation. The intensity may be changed between the center and the edges. The uniformity of the amount of light on the target may be improved by changing the irradiation intensity in the irradiation range. Points to be aware of when using near-infrared irradiation include burns and the possibility of drug (Akyalx) accumulation. In that case, effects on specific organs (including skin and blood vessels) may also be considered.

[Burns]
Consideration may be given to the location of the burn. Basically, there is a risk of burns to tissues near the light source, but in the case of a cylindrical diffuser, it penetrates into the tumor, so there is little effect on other organs. The intensity of the light source may be increased to take into account burn injuries (use a point light source, etc.). Intratissue burn prediction may also be performed. This can be done by creating an endothermic distribution map at the same time as the light intensity distribution map, issuing a warning for areas where the temperature exceeds 50°C, or creating a treatment plan to prevent the temperature from exceeding 50°C. The endothermic distribution map may be created based on absorption coefficients and scattering coefficients. The threshold value may be set for each organ using temperature.

As a treatment plan of the treatment planning system 1, the operator sets the position and intensity of the light source (via the setting unit 12), the calculation unit 13 calculates the near-infrared light amount distribution, and the evaluation unit 14 calculates the near-infrared light intensity distribution. ) Steps may be taken to evaluate the suitability of the treatment plan.

The volumetric dose histogram (PVH) is an analysis means devised based on the volumetric dose histogram (DVH) used in radiation therapy. In order to predict the therapeutic effect quantitatively, the near-infrared light intensity distribution within the tumor ROI is converted into a histogram (by the calculation unit 13).

FIG. 9 is a diagram showing an example of a volume dose histogram. In FIG. 9, the horizontal axis represents the radiation dose, and the vertical axis represents the proportion of the organ volume that is exposed to radiation. Histograms A and B are volume dose histograms of normal tissue. Histogram C is a volume dose histogram of the tumor area. The closer the cancer target is to the upper right of the volume dose histogram, the better the plan, but it is necessary to plan so that normal tissues are not irradiated as much as possible.

FIG. 10 is a diagram showing an example of a volumetric light amount histogram. In FIG. 10, the horizontal axis indicates the amount of near-infrared light, and the vertical axis indicates the proportion of the organ volume that is irradiated with near-infrared light. Histogram Tumor, histogram PTV, histogram Skin, and histogram Mucosa are volumetric light intensity histograms of the tumor, posterior tibial vein, skin, and mucosa, respectively. Histogram Skin and Histogram Mucosa are the parts that are most irradiated with near-infrared light, so it cannot be said that there is no damage, and the higher the amount of light, the more near-infrared light is absorbed, so they are the same from the perspective of burns. It may also be displayed on a graph.

[How to judge quality]
The therapeutic effect of the tumor is determined (by the evaluation unit 14) based on the PVH (or RVH) as to whether the minimum amount of light that reaches the tumor (calculated by the calculation unit 13) exceeds the amount of light necessary for treatment. The reason why PVH or RVH is used here is that although the treatment planning device can calculate the light intensity distribution, the amount of drug taken into the tumor needs to be evaluated separately, so if this is taken into account, it is calculated as RVH. Because it will be. Regarding the determination of burn injuries, if the heat absorption distribution is calculated (by the calculation unit 13) and the threshold temperature is exceeded, measures are taken such as lowering the intensity of the light source. Furthermore, the temperature of the skin surface may be monitored in real time by thermography.

According to the treatment planning system 1, it becomes possible to visualize what was previously unknown about how near-infrared light behaves outside and inside the body. In addition, it is possible to optimize the irradiation position, area, light intensity, distance, and angle depending on the positional relationship between the probe and the tumor.

The above is the explanation of viewpoint 3.

<Viewpoint 4>
The treatment planning system 1 is a treatment planning system for photoimmunotherapy. The treatment planning system 1 relates to a simulation system for pre-planning (prediction of optimal irradiation time/light source position) for treatment with photoimmunotherapy.

Photoimmunotherapy is a treatment method in which a drug that responds to light is administered, and once the drug has sufficiently concentrated on the cancer, the cancer is treated with laser light. The advantage is that unlike anticancer drugs, there are no side effects outside the treatment area, and there is no damage outside the cancer cells. In addition to its ability to directly kill cells, it can also activate immunity against cancer, leading to prevention of cancer recurrence. Applicable cancer types include, but are not limited to, head and neck, chest, liver/gallbladder/spleen, digestive system, urinary system, and gynecological system.

Photoimmunotherapy drugs (drugs that react to light) are drugs that react to light (e.g., proteins that attach to markers (antigens) that are abundant on the surface of cancer cells (e.g., anti-EGFR antibodies such as Cetuximab). : IRDye 700 DX). It hardly sticks to normal cells. The drug itself does not damage cells.

First, a photoimmunotherapy drug is administered by drip. Then, after about a day, the drug binds to the cancer. By irradiating with laser light, substances (cancer antigens) released from cancer cells activate immunity against cancer.

Irradiation methods include a method in which a catheter is inserted into the body for irradiation, and a method in which irradiation is performed from outside the body.

According to the treatment planning system 1, it is possible to understand how and how much light will be applied, and where to apply the light to achieve highly accurate irradiation.

In the treatment planning system 1, CT/PET/MRI images are read (by the import unit 11), fusion is performed, and a region of interest (ROI) is drawn (by the setting unit 12 or calculation unit 13). (ROI setting according to purpose such as tumor, skin surface, mucous tissue, etc.), light source setting (Frontal diffuser or cylindrical diffuser) (by setting unit 12), and calculation condition setting (by setting unit 12) Range, resolution, Default change for each patient setting, setting of irradiation time and light source position) are performed (by calculation unit 13 or evaluation unit 14) and treatment plan evaluation (including pass/fail judgment) (light intensity distribution display and endothermic distribution display) , calculation of volumetric light intensity histogram (PVH), tumor treatment effect determination, burn injury determination).

According to the treatment planning system 1, optical simulation using the Monte Carlo method (by the calculation unit 13), endothermic distribution/burn prediction judgment (by the calculation unit 13 or evaluation unit 14), and tumor treatment effect judgment can be executed. . Optical simulation using the Monte Carlo method makes it possible to investigate how the amount of light is distributed in the tumor area. In the endothermic distribution/burn prediction judgment, because near-infrared light generates more heat than radiation, the endothermic distribution is calculated from the near-infrared light intensity distribution (absorption coefficient and scattering coefficient), and the risk of burn occurrence is calculated. This allows you to investigate the effects of heat generation. In determining the therapeutic effect of a tumor, the optimal light amount can be determined by calculating the volume of the tumor, PTV (irradiation target area including the tumor), skin, and mucous membrane according to the irradiation amount and determining the optimal light amount.

The above is the explanation of viewpoint 4.

Next, the effects of the treatment planning system 1 will be explained.

According to the treatment planning system 1, the near-infrared light amount distribution, which is the light amount distribution of near-infrared light in the living body, is calculated based on the calculation of the behavior of the irradiated near-infrared light in the living body (behavior calculation). and an arithmetic unit 13 that outputs the calculated values. In such a treatment planning system 1, the light intensity distribution of near-infrared light in the living body is output. This makes it possible to understand the light intensity distribution of near-infrared light within the living body.

The calculation unit 13 of the treatment planning system 1 may calculate the near-infrared light amount distribution based on calculation (behavior calculation) using the Monte Carlo method. In such a treatment planning system 1, behavior calculation can be performed more reliably.

In the treatment planning system 1, at least part of the calculation (behavior calculation) may be executed by a GPU (Graphics Processing Unit). In such a treatment planning system 1, behavior calculation can be performed faster.

The treatment planning system 1 may further include a setting section 12 that sets a region of interest in the living body, and the calculation section 13 may calculate the near-infrared light intensity distribution in the region of interest set by the setting section 12 in the living body. In such a treatment planning system 1, it is possible to calculate the near-infrared light intensity distribution in the region of interest. Further, for example, by calculating only the near-infrared light intensity distribution in the region of interest, calculation can be made faster.

The treatment planning system 1 further includes a setting unit 12 that sets optical parameters related to optics, and a calculation unit 13 calculates the near-infrared light intensity distribution based on calculations (behavior calculations) using the optical parameters set by the setting unit 12. It may be calculated. In such a treatment planning system 1, it is possible to calculate a more detailed and accurate near-infrared light intensity distribution based on optical parameters.

The calculation unit 13 of the treatment planning system 1 may display information regarding the near-infrared light amount distribution superimposed on the morphological image of the living body. In such a treatment planning system 1, for example, a user can confirm information regarding near-infrared light intensity distribution on a morphological image of a living body.

The calculation unit 13 of the treatment planning system 1 may further calculate and output a histogram based on the near-infrared light amount distribution. In such a treatment planning system 1, for example, the user can check a histogram based on the near-infrared light amount distribution.

The treatment planning system 1 further includes a setting unit 12 that changes settings related to calculation (behavior calculation) based on the calculation result by the calculation unit 13; behavior calculation) may also be performed. In such a treatment planning system 1, for example, each time the calculation unit 13 performs calculation, behavior calculation can be performed based on more appropriate settings based on the previous calculation result. That is, each time the calculation unit 13 performs a calculation, more appropriate behavior calculation can be performed.

The calculation unit 13 of the treatment planning system 1 may further calculate and output the heat distribution in the living body based on the calculation (behavior calculation). In such a treatment planning system 1, for example, the user can check the heat distribution in the living body.

The calculation unit 13 of the treatment planning system 1 may further calculate and output the risk related to burns based on the calculation (behavior calculation). In such a treatment planning system 1, for example, the user can confirm the risk of burn injury.

In photoimmunotherapy, a type of cancer treatment that uses near-infrared light, it has been thought that near-infrared light can reach as deep as 1 cm, but clinical results show that the reaching distance is shorter than expected. It has been pointed out that According to the treatment planning system 1, it is possible to formulate an effective treatment plan by quantitatively evaluating the light intensity distribution of near-infrared light in the living body. Moreover, according to the treatment planning system 1, an effective treatment plan can be formulated by understanding the light intensity distribution of near-infrared light in the living body and performing quantitative evaluation. Furthermore, according to the treatment planning system 1, it is possible to quantitatively evaluate the amount of near-infrared light delivered to the tumor and predict the therapeutic effect.

The treatment planning system 1 can also be regarded as a device of items 1 to 10 below.

[Item 1]
a calculation unit that calculates and outputs a near-infrared light amount distribution that is a light amount distribution of the near-infrared light in the living body based on calculation of the behavior of the irradiated near-infrared light in the living body;
Treatment planning system.

[Item 2]
The calculation unit calculates the near-infrared light amount distribution based on the calculation using the Monte Carlo method.
The treatment planning system described in item 1.

[Item 3]
At least a part of the calculation is executed by a GPU (Graphics Processing Unit).
The treatment planning system according to item 1 or 2.

[Item 4]
further comprising a setting unit that sets a region of interest in the living body,
The calculation unit calculates the near-infrared light amount distribution in the region of interest set by the setting unit in the living body.
The treatment planning system according to any one of items 1 to 3.

[Item 5]
It further includes a setting section for setting optical parameters related to optics,
The calculation unit calculates the near-infrared light amount distribution based on the calculation using the optical parameters set by the setting unit.
The treatment planning system according to any one of items 1 to 4.

[Item 6]
The calculation unit displays information regarding the near-infrared light amount distribution superimposed on the morphological image of the living body.
The treatment planning system according to any one of items 1 to 5.

[Item 7]
The calculation unit further calculates and outputs a histogram based on the near-infrared light amount distribution.
The treatment planning system according to any one of items 1 to 6.

[Item 8]
further comprising a setting section that changes settings related to the calculation based on the calculation result by the calculation section,
The calculation unit performs the calculation based on the settings changed by the setting unit.
The treatment planning system according to any one of items 1 to 7.

[Item 9]
The calculation unit further calculates and outputs the heat distribution in the living body based on the calculation.
The treatment planning system according to any one of items 1 to 8.

[Item 10]
The calculation unit further calculates and outputs a risk related to burn injury based on the calculation.
The treatment planning system according to any one of items 1 to 9.

The treatment planning system 1 can also be regarded as a system of the following items 1A to 11A.

[Item 1A]
A treatment planning system for photoimmunotherapy, comprising:
A display device that visualizes the distribution of near-infrared light in the body by calculating the behavior of near-infrared light;
A treatment planning system that quantitatively analyzes the amount of near-infrared light irradiated to a tumor based on the near-infrared light amount distribution of the display device.

[Item 2A]
The treatment planning system according to item 1A,
A treatment planning system characterized in that the display device displays a near-infrared light amount distribution superimposed on a patient morphology image such as an X-ray tomography image (X-ray CT).

[Item 3A]
The treatment planning system according to item 2A,
A treatment planning system having a function of setting optical parameters for near-infrared light as a distribution for patient's morphological information obtained from the X-ray tomography image (X-ray CT) or the like.

[Item 4A]
The treatment planning system according to item 3A,
A treatment planning system that uses a Monte Carlo method to calculate the behavior of the near-infrared light and includes a near-infrared light behavior calculation device that calculates the behavior of the near-infrared light in a complex system.

[Item 5A]
The treatment planning system described in item 4A,
A treatment planning system including a near-infrared light behavior calculation device that calculates an accurate near-infrared light amount distribution using the optical parameter distribution.

[Item 6A]
The treatment planning system according to item 4A or 5A,
A treatment planning system having a high-speed parallel computing device using a GPU (Graphics Processing Unit) or the like to perform calculations using the Monte Carlo method of near-infrared light.

[Item 7A]
The treatment planning system according to item 6A,
A treatment planning system that includes a drawing device that draws the range of a tumor as a region of interest (ROI) in order to quantitatively analyze the amount of near-infrared light irradiated to the tumor.

[Item 8A]
The treatment planning system according to item 7A,
A treatment planning system that includes a photons volume histogram calculation device that aggregates the amount of near-infrared light irradiated onto a region of interest for each specific location in the region of interest and quantitatively analyzes it as a histogram.

[Item 9A]
The treatment planning system according to item 8A,
A treatment planning system that adjusts the position and angle of a light source based on the volumetric light amount histogram to search for conditions necessary for treatment.

[Item 10A]
The treatment planning system according to item 9A,
A treatment planning system that includes a heat distribution display device that calculates the heat distribution within the body caused by absorption of near-infrared light into the body.

[Item 11A]
The treatment planning system according to item 10A,
A treatment planning system including a burn prediction device that predicts side reactions such as burns based on the calculation results of the heat distribution display device.

DESCRIPTION OF SYMBOLS 1...Treatment planning system, 10...Storage part, 11...Intake part, 12...Setting part, 13...Calculation part, 14...Evaluation part, 100...CPU, 101...RAM, 102...ROM, 103...I/O device, 104...Communication module, 105...Auxiliary storage device, 200...Storage medium, 201...Program storage area, 300...Treatment plan program, 301...Intake module, 302...Setting module, 303...Calculation module, 304...Evaluation module.

Claims (12)

a calculation unit that calculates and outputs a near-infrared light amount distribution that is a light amount distribution of the near-infrared light in the living body based on calculation of the behavior of the irradiated near-infrared light in the living body;
Treatment planning system. The calculation unit calculates the near-infrared light amount distribution based on the calculation using the Monte Carlo method.
The treatment planning system according to claim 1. At least a part of the calculation is executed by a GPU (Graphics Processing Unit).
The treatment planning system according to claim 1 or 2. further comprising a setting unit that sets a region of interest in the living body,
The calculation unit calculates the near-infrared light amount distribution in the region of interest set by the setting unit in the living body.
The treatment planning system according to claim 1. It further includes a setting section for setting optical parameters related to optics,
The calculation unit calculates the near-infrared light amount distribution based on the calculation using the optical parameters set by the setting unit.
The treatment planning system according to claim 1. The calculation unit displays information regarding the near-infrared light amount distribution superimposed on the morphological image of the living body.
The treatment planning system according to claim 1. The calculation unit further calculates and outputs a histogram based on the near-infrared light amount distribution.
The treatment planning system according to claim 1. further comprising a setting section that changes settings related to the calculation based on the calculation result by the calculation section,
The calculation unit performs the calculation based on the settings changed by the setting unit.
The treatment planning system according to claim 1. The calculation unit further calculates and outputs the heat distribution in the living body based on the calculation.
The treatment planning system according to claim 1. The calculation unit further calculates and outputs a risk related to burn injury based on the calculation.
The treatment planning system according to claim 1 or 9. A treatment planning method performed by a device, the method comprising:
a calculation step of calculating and outputting a near-infrared light amount distribution, which is a light amount distribution of the near-infrared light in the living body, based on calculation of the behavior of the irradiated near-infrared light in the living body;
Treatment planning methods. causing a computer to execute a calculation step of calculating and outputting a near-infrared light amount distribution, which is a light amount distribution of the near-infrared light in the living body, based on calculation of the behavior of the irradiated near-infrared light in the living body; ,
Treatment planning program.

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