JP2024000182A - Treatment plan support device, treatment plan support method, and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To make a treatment plan suitable for a patient.

SOLUTION: A treatment plan support device of an embodiment has an acquisition unit, a first estimation unit, a first generation unit, a second estimation unit, and a presentation unit. The acquisition unit acquires a treatment plan including patient information on a patient, first treatment for the patient, and second treatment for the patient performed after the first treatment. The first estimation unit estimates a first effect of treatment brought about by the first treatment based on the patient information. The second estimation unit estimates a second effect of treatment brought about by the second treatment based on the first effect of treatment. The first generation unit generates reference information on the treatment plan based on the second effect of treatment. The presentation unit presents the treatment plan and the reference information.

SELECTED DRAWING: Figure 2

COPYRIGHT: (C)2024,JPO&INPIT

Description

Embodiments disclosed in this specification and the drawings relate to a treatment planning support device, a treatment planning support method, and a program.

For example, a patient's treatment may be performed in accordance with a treatment plan. A treatment plan is made, for example, based on the results of simulating treatment effect prediction. Additionally, multiple treatments may be administered to a patient in succession. In such a case, for example, a simulation is performed for each of a plurality of treatments, and a treatment plan is created based on the results of the simulation.

In this way, there is no interdependence among the multiple simulations performed when creating a treatment plan for consecutively administering multiple treatments to a patient. For this reason, it is difficult to feed back the therapeutic effects and risk prediction results after a series of treatments based on a treatment plan to each of a plurality of treatments. Further, in a simulation in which a plurality of treatments are performed on a patient in succession, a simulation is performed based on values that do not take into account the effects of previous treatments. For this reason, the simulation may not be rational and may be wasted.

Japanese Patent Application Publication No. 2006-318162 Japanese Patent Application Publication No. 2017-84350

The problem to be solved by the embodiments disclosed in this specification and the drawings is to make it possible to formulate a treatment plan suitable for a patient. However, the problems to be solved by the embodiments disclosed in this specification and the drawings are not limited to the above problems. Problems corresponding to the effects of each configuration shown in the embodiments described later can also be positioned as other problems.

The treatment planning support device of the embodiment includes an acquisition unit, a first estimation unit, a second estimation unit, a first creation unit, and a presentation unit. The acquisition unit acquires patient information regarding the patient and a treatment plan including each of a first treatment for the patient and a second treatment for the patient to be performed after the first treatment. The first estimation unit estimates a first treatment effect of the first treatment based on the patient information. The second estimation unit estimates a second treatment effect of the second treatment based on the first treatment effect. The first creation unit creates reference information regarding the treatment plan based on the second treatment effect. The presentation unit presents the treatment plan and the reference information.

FIG. 1 is a block diagram showing an example of the configuration of an in-hospital system 1 according to an embodiment. FIG. 1 is a block diagram showing an example of the configuration of a treatment planning support device 100 according to an embodiment. The figure explaining an example of the outline of the procedure by which a user treats a patient according to a treatment plan. 5 is a flowchart showing a first example of processing in the treatment planning support device 100. FIG. 7 is a flowchart showing a second example of processing in the treatment planning support device 100. 7 is a flowchart showing a third example of processing in the treatment planning support device 100. 10 is a flowchart showing a fourth example of processing in the treatment planning support device 100.

Hereinafter, a treatment planning support device, a treatment planning support method, and a program according to an embodiment will be described with reference to the drawings.

The treatment planning support device of the embodiment is included in, for example, an in-hospital system provided within a hospital. For example, a patient is treated using a combination of multiple treatment methods. For example, a test is performed on the patient before and after implementing the treatment method. The treatment planning support device supports creation of a treatment plan when multiple treatments are performed in succession.

FIG. 1 is a block diagram showing an example of the configuration of an in-hospital system 1 according to an embodiment. The in-hospital system 1 of the embodiment includes, for example, a hospital information system (hereinafter referred to as HIS) 10, a radiology information system (hereinafter referred to as RIS) 20, and a medical image diagnostic apparatus (modality) 30. , a picture archiving and communication system (PACS) 40, and a treatment planning support device 100.

The HIS 10 is a computer system that provides business support within the hospital. Specifically, the HIS 10 has various subsystems. Various subsystems include, for example, an electronic medical record system, a medical accounting system, a medical reservation system, a hospital visit reception system, and an admission/discharge management system.

The HIS 10 is, for example, a computer such as a server device or a client terminal equipped with a processor such as a CPU (Central Processing Unit), a memory such as a ROM (Read Only Memory) or a RAM (Random Access Memory), a display, an input interface, and a communication interface. include.

A user such as a doctor uses the electronic medical record system included in the HIS 10 to input or refer to information regarding a patient (hereinafter referred to as patient information). A user issues an image inspection order to the HIS 10. The HIS 10 transfers order information corresponding to the image inspection order to other systems such as the RIS 20.

RIS20 is a computer system that provides operational support in the image diagnosis department. The RIS 20 performs reservation management of image test orders in cooperation with the HIS 10, as well as coordination of reservation information with examination equipment and management of examination information. The RIS 20 includes, for example, a computer such as a server device or a client terminal that includes a processor such as a CPU, a memory such as a ROM or a RAM, a display, an input interface, and a communication interface.

The modality 30 executes imaging (photography) according to imaging conditions (imaging protocol) determined based on, for example, an image examination instruction. Examples of the modality 30 include an X-ray computed tomography device, an X-ray diagnostic device, a magnetic resonance imaging device, an ultrasound diagnostic device, a nuclear medicine diagnostic device, and the like. The modality 30 is operated by, for example, an operator such as a doctor (radiologist) or a medical radiology technician. Medical images (image data) generated by imaging by the modality 30 are transmitted to the PACS 40.

PACS 40 is a computer system that receives medical images transmitted by modality 30 and stores them in a database. The PACS 40 transmits (transfers) medical images stored in the database in response to requests from clients. The PACS 40 includes a server computer including a processor such as a CPU, a memory such as ROM and RAM, a display, an input interface, and a communication interface. The medical images stored in the PACS 40 are accompanied by information regarding the patient to be photographed and the photographing as additional information. The supplementary information includes information such as a patient ID, an examination ID, and imaging conditions (imaging protocol) in a format that complies with the DICOM (Digital Imaging and Communication in Medicine) standard, for example.

The configuration of the in-hospital system 1 is not limited to the above. The in-hospital system 1 may include, for example, an image interpretation report creation device. Moreover, some elements of the in-hospital system 1 may be integrated. For example, the HIS 10 and the RIS 20 may be integrated into one system.

FIG. 2 is a block diagram showing an example of the configuration of the treatment planning support device 100 according to the embodiment. The treatment planning support device 100 includes, for example, a communication interface 110, an input interface 120, a display 130, a processing circuit 140, and a memory 150.

The communication interface 110 communicates with external devices such as the HIS 10, the RIS 20, the modality 30, and the PACS 40 via a network NW such as a LAN (Local Area Network). The communication interface 110 includes, for example, a communication interface such as a NIC (Network Interface Card). The network NW may include the Internet, a cellular network, a Wi-Fi network, a WAN (Wide Area Network), etc. instead of or in addition to a LAN.

The input interface 120 receives various input operations from a treating doctor and the like, converts the received input operations into electrical signals, and outputs the electrical signals to the processing circuit 140. For example, when an input operation is performed by a doctor or the like, the input interface 120 generates information according to the input operation. Input operations to the input interface 120 may include, for example, input operations of information such as the purpose of the test, patient's symptoms, past medical history, and the like. Information such as the purpose of the test, the patient's symptoms, and past medical history is useful information that can estimate the body structure of the target patient, which is different from that of a healthy person.

Input operations include, for example, operations related to generating order information, selecting reference image candidates, attaching edited images, and editing edited images. When the input operations in these cases are executed, the input interface 120 generates generation instruction information, attachment request information, selection information, and image editing information, respectively. The input interface 120 outputs information corresponding to the generated input operation to the processing circuit 140.

The input interface 120 includes, for example, a mouse, a keyboard, a trackball, a switch, a button, a joystick, a touch panel, and the like. The input interface 120 may be, for example, a user interface that accepts voice input such as a microphone. When the input interface 120 is a touch panel, the input interface 120 may also have the display function of the display 130.

Note that in this specification, the input interface is not limited to one that includes physical operation parts such as a mouse and a keyboard. For example, examples of the input interface include an electrical signal processing circuit that receives an electrical signal corresponding to an input operation from an external input device provided separately from the device and outputs this electrical signal to a control circuit.

Display 130 displays various information. For example, the display 130 displays images generated by the processing circuit 140, a GUI (Graphical User Interface) for accepting various input operations from an operator, and the like. For example, the display 130 is an LCD (Liquid Crystal Display), a CRT (Cathode Ray Tube) display, an organic EL (Electro Luminescence) display, or the like.

The processing circuit 140 includes, for example, an acquisition function 141, an estimation function 142, a first creation function 143, a second creation function 144, and a presentation function 145. The processing circuit 140 realizes these functions by, for example, a hardware processor (computer) executing a program stored in a memory (storage circuit) 150.

A hardware processor is, for example, a CPU, a GPU (Graphics Processing Unit), an Application Specific Integrated Circuit (ASIC), a programmable logic device (for example, a Simple Programmable Logic Device (SPLD), or Refers to circuits such as complex programmable logic devices (CPLDs) and field programmable gate arrays (FPGAs).

Instead of storing the program in the memory 150, the program may be directly incorporated into the circuit of the hardware processor. In this case, the hardware processor realizes its functions by reading and executing a program built into the circuit. The above program may be stored in advance in the memory 150 or in a non-temporary storage medium such as a DVD or CD-ROM, and the non-temporary storage medium is the drive device ( (not shown) may be installed in the memory 150 from a non-transitory storage medium.

The hardware processor is not limited to being configured as a single circuit, but may be configured as one hardware processor by combining a plurality of independent circuits to realize each function. Further, a plurality of components may be integrated into one hardware processor to realize each function. Although the hardware processor, memory, etc. in the treatment planning support device 100 are provided separately from the hardware processor, memory, etc. of the HIS 10, they may be common.

The memory 150 stores, for example, a treatment method database (hereinafter referred to as DB) 151 and a treatment effect prediction model 152. The treatment method DB 151 includes a plurality of data regarding treatment methods to be performed on patients. The treatment effect prediction model 152 is a model that predicts the treatment effect based on the treatment method stored in the treatment method DB 151. The treatment effect prediction model 152 is created for each treatment method included in the treatment method DB 151.

The treatment effect prediction model 152 is, for example, a trained model that has been trained by machine learning with the patient's test values before treatment, treatment method, treatment risk, etc. as input and the test values and treatment risk after treatment as output. be. The treatment method includes not only a medical treatment method but also an exercise therapy method performed before treatment. Regarding treatment methods as a medical practice, examples of cancer treatment include radiation therapy, anticancer drug treatment, surgical treatment, and immunotherapy. The treatment effect prediction model 152 is learned by, for example, logistic regression or deep learning. Instead of the output from the treatment effect prediction model 152, results obtained from a rule base may be used.

The acquisition function 141 acquires patient information presented by the HIS 10 or the like. The acquisition function 141 acquires test values (hereinafter referred to as pre-treatment test values) of a test performed before starting treatment of a patient (hereinafter referred to as pre-treatment test). The pre-treatment test values may be presented by a testing facility inside or outside the hospital where the in-hospital system 1 is installed, or may be presented by being output from the input interface 120 in response to a user's input operation.

The acquisition function 141 acquires executable treatment methods. A treatment plan for treating the patient is acquired based on the acquired patient information and pre-treatment test values. The treatment plan includes patient information, treatment methods, and associated information. The accompanying information includes, for example, information such as date and time, location, surgeon, and required facilities when the treatment method is surgery. The acquisition function 141 automatically selects and acquires a treatment plan from a plurality of predetermined templates using, for example, disease name and severity. In this case, the disease name and severity are output by the input interface 120 in response to the user's input operation, for example.

The acquisition function 141 may acquire a treatment plan based on information output by the input interface 120 in response to a user's input operation. The treatment plan includes, for example, each of a first treatment and a second treatment. The first treatment is, for example, the first treatment performed on a patient in a treatment plan. The second treatment is a treatment performed after the first treatment. The first treatment may be a treatment other than the first treatment given to the patient.

The acquisition function 141 acquires, for example, a provisional treatment plan (hereinafter referred to as a provisional treatment plan) for generating a treatment plan. The provisional treatment plan is created on the input interface 120, for example, based on an input operation on the input interface 120 by the user. The input interface 120 transmits the created interim treatment plan to the processing circuit 140, and the acquisition function 141 in the processing circuit 140 acquires the transmitted interim treatment plan. The acquisition function 141 is an example of an acquisition unit.

The estimation function 142 includes, for example, a first estimation function 147 and a second estimation function 148. The first estimation function 147 estimates the first treatment effect and first treatment risk of the first treatment based on patient information. The second estimation function 148 estimates the second treatment effect and second treatment risk of the second treatment based on the patient information and the first treatment effect estimated by the first estimation function 147. The first estimation function 147 is an example of a first estimation section. The second estimation function 148 is an example of a second estimation section.

The first creation function 143 generates "reference information for changing (improving) treatment plan" based on the first treatment effect, first treatment risk, and second treatment effect and second treatment risk estimated by the estimation function 142. ”. The "reference information for changing (improving) the treatment plan" includes the first treatment effect, the first treatment risk, the second treatment effect, and the second treatment risk. The second creation function 144 creates a treatment plan based on the "reference information for changing (improving) treatment plan" created by the first creation function 143. The first creation function 143 is an example of a first creation section. The second creation function 144 is an example of a second creation section.

The presentation function 145 uses part or all of the contents of the treatment plan created by the second creation function 144 and the "reference information for changing (improving) treatment plan" created by the first creation function 143 as reference information. present. The presentation function 145 presents reference information by transmitting it to an external device such as the HIS 10 or outputting it to be displayed on the display 130, for example. The presentation function 145 is an example of a presentation section. The presentation function 145 also functions as a transmitting unit or an output unit depending on the mode of presentation.

The reference information presented by the presentation function 145 includes information to be fed back to create a treatment plan, such as the first treatment effect, first treatment risk, second treatment effect, and second treatment effect estimated by the treatment method and estimation function 142. 2 Contains some or all information on treatment risks. The reference information may include information that expected test values and acceptable risks can be achieved with this treatment method, and information that expected test values and acceptable risks cannot be achieved with this treatment method. The reference information may include other information. The reference information may include, for example, treatment methods other than those included in the treatment plan, information regarding patient contraindications, patient name, patient severity, test values from pre-treatment tests and therapeutic tests, and the like.

Prior to explaining the processing in the treatment planning support device 100, an overview of the procedure by which a user treats a patient will be explained. FIG. 3 is a diagram illustrating an example of an outline of a procedure in which a user treats a patient according to a treatment plan. When treating a patient, a user first performs a test on the patient (hereinafter referred to as a pre-treatment test) and measures test values. The contents of the pre-treatment test include, for example, a blood test and a cardiopulmonary function test.

After performing a pre-treatment test, the user performs the first treatment, followed by the second treatment. At respective timings after performing the first treatment and the second treatment, the user performs tests with the same contents as the pre-treatment test (first treatment test and second treatment test), and performs the first treatment test and second treatment test, respectively. Measure the test values after the treatment test. Then, by completing the second treatment, the treatment based on the treatment plan is completed.

Hereinafter, the procedure of the process executed by the treatment planning support device 100 will be explained using several examples.

First, a first example will be explained. FIG. 4 is a flowchart showing a first example of processing in the treatment planning support device 100. Here, for example, an example will be described in which a treatment plan for cancer treatment is generated in which the first treatment is surgery and the second treatment is postoperative adjuvant chemotherapy. Adjuvant chemotherapy is generally used to eradicate small, invisible cancer cells that may be left behind after surgery.

Before formulating a treatment plan using the treatment planning support device 100, the user requests a testing institution or the like to complete a pre-treatment test on the patient. The testing period may be, for example, a testing department within a hospital, or a specialized testing institution outside the hospital. The contents of the pre-treatment examination are determined by, for example, the patient's medical condition and the contents of the treatment. The pre-treatment test may be a general test that does not depend on the patient's symptoms.

Furthermore, the user inputs the disease name, severity, expected test values after treatment according to the treatment plan (hereinafter referred to as expected test values), and tolerable treatment risk (hereinafter referred to as acceptable risk). , the input interface 120 accepts input operations from the user. The input interface 120 outputs the received expected test values and acceptable risks to the processing circuit 140. Expected test values and acceptable risks are examples of criteria.

Expected test values include, for example, values of FEV1 (Forced Expiratory Volume in one second) and DLco (diffusing capacity of lung for carbon monoxide) related to respiratory function are X or more. Acceptable risks include, for example, a post-treatment complication rate of less than Y%, a 5-year survival rate, a recurrence rate of less than Z%, and the like.

When creating a treatment plan, the treatment plan support device 100 uses the acquisition function 141 to acquire the patient's pre-treatment test values presented by a testing organization or the like (step S101). The patient's pre-treatment laboratory values indicate the patient's current physical condition. Subsequently, the acquisition function 141 acquires the expected test value and allowable risk output by the input interface 120 (step S103).

Subsequently, the acquisition function 141 acquires executable treatment methods from among the treatment methods stored in the treatment method DB 151 (step S105). The treatment methods that can be implemented here include, for example, surgical procedures, types of radiation therapy, and the like. The acquisition function 141 acquires, for example, the treatment methods available at the facility where the treatment is performed, and if there is a treatment method contraindicated for the patient, acquires the treatment methods excluding the treatment method contraindicated for the patient.

Subsequently, the acquisition function 141 acquires a provisional treatment plan based on the acquired disease name and patient severity (step S107). An interim treatment plan is an interim treatment plan prescribed to a patient. The interim treatment plan includes, for example, a first treatment and a second treatment.

Next, the first estimation function 147 calculates the test value after the first treatment (hereinafter referred to as the first test estimate) based on the pre-treatment test value acquired by the acquisition function 141 and the first treatment included in the provisional treatment plan. value) and treatment risk (hereinafter referred to as first treatment risk) are estimated as the first treatment effect (step S109). The first estimation function 147 executes, for example, a treatment effect prediction model 152 that inputs pre-treatment test values and surgical information (excision range, surgical method, etc.) and outputs post-surgical test values and treatment risks. do. For example, when performing preoperative exercise therapy before surgery, predicted values of test values after implementation of preoperative exercise therapy may be input instead of pretreatment test values.

Subsequently, the second estimation function 148 calculates the test value after the second treatment (hereinafter referred to as , second test estimated value) and treatment risk (hereinafter referred to as second treatment risk) are estimated as the second treatment effect (step S111). A treatment effect that outputs the test values and treatment risks after postoperative adjuvant chemotherapy by inputting predicted test values after surgery and information on postoperative adjuvant chemotherapy (type, amount, duration, etc. of drugs). Predictive model 152 is executed.

Next, the second creation function 144 compares the second test estimate and the expected test value, and the second treatment risk and the acceptable risk, so that the second test estimate and the second treatment risk are the expected test value. It is determined whether or not the and allowable risks have been achieved (step S113). It is an example of meeting the criteria that the second test estimate and second treatment risk achieve the expected test value and acceptable risk, respectively.

If it is determined that the second test estimated value and the second treatment risk have achieved the expected test value and acceptable risk, respectively, the second creation function 144 determines the provisional treatment plan acquired by the acquisition function 141 as the treatment plan. (Step S115). Subsequently, the presentation function 145 presents the treatment plan created by the second creation function 144 (step S117).

The presentation function 145 presents the treatment plan by displaying it on the display 130, for example. The presentation function 145 presents the treatment plan by transmitting it to an external device such as a client terminal of the HIS 10 or the RIS 20, for example. The presentation function 145 may present reference information other than the treatment plan. In this way, the treatment planning support device 100 ends the process shown in FIG. 4.

If it is determined that the second test estimated value and the second treatment risk do not achieve the expected test value and acceptable risk, respectively, the second creation function 144 increments the number of times N of revisions of the treatment plan (N=N+1) ( Step S119). Subsequently, the second creation function 144 determines whether the number N of revisions to the treatment plan exceeds a threshold (step S121). The threshold value here may be determined in advance, for example, or may be arbitrarily set by the user.

If it is determined that the number of revisions of the treatment plan does not exceed the threshold, the first creation function 143 generates the first treatment effect and first treatment risk, and the second treatment effect and second treatment risk estimated by the estimation function 142. Based on the above, "reference information for changing (improving) treatment plans" will be created. The presentation function 145 presents the "reference information for changing (improving) the treatment plan" created by the first creation function 143. The presentation function 145 does not need to present "reference information for changing (improving) the treatment plan." The second creation function 144 modifies the treatment plan based on the "reference information for changing (improving) treatment plan" created by the first creation function 143 (step S123), and returns the process to step S109. When modifying the treatment plan, the second creation function 144 modifies the treatment plan by, for example, changing the type and period of each treatment in the acquired first treatment and second treatment, and creates a revised treatment plan. do. The second creation function 144 stores the created treatment modification plan in the memory 150.

At this time, the second creation function 144 stores in the memory 150 a combination of "differences in treatment plan changes" and "changes in test values/risk predicted values due to treatment plan changes." The first creation function 143 uses this information stored in the memory 150 when modifying the treatment plan from the second time onwards, and feeds it back as a guideline for changing the type and period of each treatment. The first creation function 143 creates "reference information for changing (improving) the treatment plan" with reference to the fed-back information.

If it is determined that the number of revisions of the treatment plan exceeds the threshold, the second creation function 144 selects the expected test values for the second test estimate and the second treatment risk from among the N provisional treatment plans or revised treatment plans. Then, a provisional treatment plan or a revised treatment plan close to the acceptable risk is determined as the treatment plan (step S125).

For example, in determining whether the second test estimate is close to the expected test value, the second creation function 144 calculates, for example, the average or weighted average of the excess of the second test estimate with respect to the expected test value. May be used. When using a weighted average, the second creation function 144 may set the priority of the test estimate in advance. The second creation function 144 may be used to determine the second treatment risk and acceptable risk in the same manner as the relationship between the second test estimate and expected test value.

After that, the presentation function 145 presents the treatment plan created by the second creation function 144 (step S117). At this time, the presentation function 145 also presents reference information such as "reference information for changing (improving) treatment plan". In this way, the treatment planning support device 100 ends the process shown in FIG. 4.

In the treatment planning support device 100 of the embodiment, in the first processing procedure, post-treatment test estimated values and treatment risks of the first treatment and the second treatment are continuously estimated. Therefore, it is possible to efficiently formulate an effective treatment plan suitable for the conditions of the patient and the medical facility from among a huge number of possible combinations of treatment plans. Therefore, when administering multiple treatments to a patient in succession, a treatment plan suitable for the patient can be created.

Next, the second processing procedure will be explained. In the description of the second processing procedure, steps similar to those of the first processing procedure may be given the same step numbers and the description thereof may be omitted or simplified. FIG. 5 is a flowchart showing a second example of processing in the treatment planning support device 100. The second example is, for example, an example in which a plurality of non-treatment periods are set after preoperative exercise therapy is performed and until a surgical operation is performed as a treatment for cancer. By setting a plurality of non-treatment periods, for example, it becomes a material for considering the date of surgical operation.

In the second example, the treatment planning support device 100 first uses the acquisition function 141 to acquire the patient's pre-treatment test values (step S101), and then acquires the expected test values and acceptable risk (step S103). . Subsequently, the acquisition function 141 acquires an executable treatment method (step S105) and acquires a provisional treatment plan (step S107). The steps up to this point are the same as in the first example, but in step S105, one treatment method (surgery) is acquired.

Subsequently, the first estimation function 147 sets a plurality of periods during which the patient is not treated (hereinafter referred to as non-treatment periods) after performing the pre-treatment exercise therapy and before performing the surgical operation (step S201). The first estimation function 147 sets a plurality of periods, such as 0 days, 1 day, 3 days, and 1 week, as non-treatment periods. The non-treatment period may be a period after treatment. Furthermore, when a plurality of treatments are included in the treatment plan, the non-treatment period may be a part or all of the period before and after each treatment.

Subsequently, the estimation function 142 estimates the treatment effect after each non-treatment period (step S203). The treatment effect prediction model 152 used to estimate the treatment effect is learned by machine learning, for example, using the patient's test values, treatment method, non-treatment period, etc. as input, and outputting the test values after treatment and treatment risk. This is a trained model.

Subsequently, the estimation function 142 determines whether estimation of the treatment effect (test estimate and treatment risk) for each non-treatment period has been completed for all non-treatment periods set in step S201. (Step S205).

If it is determined that the estimation of the treatment effect for each non-treatment period has not been completed, the estimation function 142 returns the process to step S203 and estimates the treatment effect for each non-treatment period for which the estimation of the treatment effect has not been completed. Estimate treatment effects. When the estimation function 142 determines that the estimation of the treatment effect for each non-treatment period has been completed, the second creation function 144 includes the estimated test value and the treatment risk in the estimated treatment effect. It is determined whether there is a non-treatment period in which the therapeutic effect achieved the value and the acceptable risk, respectively (step S207).

If it is determined that there is a treatment effect in which the estimated test value and treatment risk achieve the expected test value and acceptable risk, respectively, the second creation function 144 generates a treatment plan with the best expected test value and acceptable risk. (Step S209). Subsequently, the presentation function 145 presents the treatment plan created by the second creation function 144 (step S211), and the treatment plan support device 100 ends the process shown in FIG. 5. For example, when presenting a treatment plan, the presentation function 145 may display the treatment plan, estimated test values, and treatment risks in chronological order.

If it is determined that there is no treatment effect in which the estimated test value and treatment risk have achieved the expected test value and acceptable risk, respectively, the second creation function 144 increments the number of corrections N of the treatment plan (step S119). Subsequently, the second creation function 144 determines whether the number N of revisions to the treatment plan exceeds a threshold (step S121). If it is determined that the number of corrections N of the treatment plan does not exceed the threshold, the first creation function 143 creates "reference information for changing (improving) the treatment plan", and the presentation function 145 Presents "reference information for changing (improving) treatment plans" created by The presentation function 145 does not need to present "reference information for changing (improving) the treatment plan." The second creation function 144 modifies the treatment plan based on the "reference information for changing (improving) treatment plan" created by the first creation function 143 (step S123), and returns the process to step S201.

If it is determined that the number of revisions to the treatment plan exceeds the threshold, the second creation function 144 selects the second test estimate and the second treatment risk from among the provisional treatment plan or revised treatment plan that includes multiple treatment periods. A provisional treatment plan or a revised treatment plan that is close to the expected test values and acceptable risk, respectively, is determined as the treatment plan (step S125). The presentation function 145 presents the treatment plan created by the second creation function 144 together with reference information (step S211). In this way, the treatment planning support device 100 ends the process shown in FIG. 5.

In the second example, after implementing preoperative exercise therapy, a plurality of non-treatment periods are set before treatment, and the treatment effect is estimated according to each of the plurality of non-treatment periods. Therefore, it is possible to efficiently create an effective treatment plan that is suitable for the patient, the conditions of the medical facility, the preoperative non-treatment period, etc. from a huge number of treatment plans that can be combined with non-treatment periods. . Therefore, a treatment plan suitable for the patient can be formulated.

Next, the third processing procedure will be explained. In the description of the third processing procedure, steps similar to those of the first processing procedure may be given the same step numbers and the description thereof may be omitted or simplified. FIG. 6 is a flowchart showing a third example of processing in the treatment planning support device 100. A third example is an example in which a part of the treatment plan, for example, the date on which surgery is to be performed, is fixed.

In the third example, the treatment planning support device 100 first uses the acquisition function 141 to acquire the patient's pre-treatment test values (step S101), and then acquires the expected test values and acceptable risk (step S103). . Subsequently, the acquisition function 141 acquires an executable treatment method (step S105) and acquires a provisional treatment plan (step S107). The steps up to this point are the same as the first example.

Subsequently, the acquisition function 141 fixes a part of the acquired provisional treatment plan (step S301). The item of the interim treatment plan to be fixed may be any item included in the treatment plan. The item to be fixed in the provisional treatment plan is, for example, the implementation date of the surgery included in the treatment plan.

Subsequently, similarly to the first example, the first estimation function 147 estimates the first treatment effect (step S109), and the second estimation function 148 estimates the second treatment effect (step S111). Thereafter, the second creation function 144 determines a treatment plan when the estimated test value and treatment risk achieve the expected test value and acceptable risk, respectively (step S115), and the presentation function 145 presents the treatment plan ( Step S117).

Furthermore, if the estimated test value and treatment risk do not achieve the expected test value and allowable risk, respectively, the treatment plan is revised until the number of revisions N of the treatment plan exceeds the threshold (steps S119 to S125). When modifying the treatment plan, the treatment plan is modified while maintaining a part of the treatment plan fixed in step S301, in this example, the date on which the surgery is to be performed. Thereafter, the first creation function 143 creates "reference information for changing (improving) the treatment plan." Subsequently, the second creation function 144 determines a treatment plan based on "reference information for changing (improving) treatment plan", and the presentation function 145 uses the treatment plan created by the second creation function 144 as reference information. By presenting the same, the treatment planning support device 100 ends the process shown in FIG. 6 .

In a third example, the user fixes a portion of the treatment plan. Therefore, it is possible to create a treatment plan that secures the information necessary for the treatment plan, such as the date on which the surgery will be performed and the facilities and equipment necessary for the treatment. Furthermore, since candidates for a treatment plan are narrowed down, a treatment plan suitable for the patient can be created more efficiently.

Next, the fourth processing procedure will be explained. In the explanation of the fourth processing procedure, the same step numbers may be given to the same steps as the first processing procedure, and the explanation thereof may be omitted or simplified. FIG. 7 is a flowchart showing a fourth example of processing in the treatment planning support device 100. The fourth example is an example in which the user manually instructs to change (revise) the treatment plan and use the in-hospital system 1 interactively.

In the fourth example, the treatment planning support device 100 first obtains the patient's pre-treatment test value in the estimation function 142 (step S101), and then obtains the expected test value and acceptable risk (step S103). . Subsequently, the acquisition function 141 acquires an executable treatment method (step S105) and acquires a provisional treatment plan (step S107). Subsequently, the first estimation function 147 estimates the first treatment effect (step S109), and the second estimation function 148 estimates the second treatment effect (step S111). The steps up to this point are the same as the first example.

Next, the first creation function 143 creates "reference information for changing (improving) the treatment plan" including the first treatment effect and treatment risk estimated by the estimation function 142, and the second treatment effect and treatment risk. do. Subsequently, the presentation function 145 presents the "reference information for changing (improving) treatment plan" created by the first creation function 143 together with the treatment plan, here a provisional treatment plan (step S401). The presentation function 145 may present expected test values and acceptable risks along with the treatment plan.

Next, the user selects the treatment effects (first treatment effect and second treatment effect) and treatment risks included in the "reference information for changing (improving) treatment plan" created by the first creation function 143 that was presented. (1st treatment risk and 2nd treatment risk) etc. will be confirmed. When changing the treatment plan, the user performs an input operation on the input interface 120 to input and instruct the changes to the treatment plan. The user confirms the presented treatment effect and, if the treatment plan is not to be changed, performs an input operation on the input interface 120 to instruct acceptance of the treatment plan decision.

The input interface 120 that receives the instruction of the change content through the user's input operation creates change content information. The input interface 120, which accepts the treatment plan through the user's input operation, creates plan determination information. The input interface 120 outputs the created change content information and plan decision information to the processing circuit 140.

When the input interface 120 outputs change content information or plan decision information, the processing circuit 140 uses an acquisition function 141 to acquire the output change content information and plan decision information. Following step S401, the acquisition function 141 determines whether change content information has been acquired (step S403).

If change content information has not been acquired, the acquisition function 141 determines whether plan determination information has been acquired (step S405). If it is determined that the plan determination information has not been acquired, the acquisition function 141 returns the process to step S403. If the acquisition function 141 determines that plan determination information has been acquired, the second creation function 144 determines the treatment plan presented in step S401 (step S407), presents the treatment plan and reference information again if necessary, The treatment planning support device 100 ends the process shown in FIG. 6 .

If it is determined in step S403 that the acquisition function 141 has acquired the change content information, the second creation function 144 changes the treatment plan according to the change content included in the change content information (step S409). Subsequently, the second creation function 144 returns the process to step S109, and the treatment plan support device 100 executes the subsequent process.

In a fourth example, the user himself changes or accepts the treatment plan. Therefore, an experienced user can generate a treatment plan based on his or her own experience. Therefore, it is possible to easily formulate a treatment plan suitable for treatment. Furthermore, since the user can generate a treatment plan suitable for his or her skill, the treatment can proceed smoothly.

In the above embodiment, there are two treatment methods, the first treatment and the second treatment, but there may be three or more treatment methods. Specifically, for example, the first treatment may be preoperative exercise therapy, the second treatment may be surgery, and the third treatment may be postoperative adjuvant chemotherapy. Preoperative exercise therapy is generally performed in anticipation of a decline in cardiorespiratory function and physical strength after surgery, and the aim is to reduce the risk of postoperative complications such as pneumonia by training in advance. It is a therapy that will help you.

In the above embodiment, the disease name and severity are input, but the treatment plan may be generated by inputting only patient information and pre-treatment test values without inputting the disease name or severity. . In this case, for example, the disease name may be estimated and a treatment plan generated based on pre-treatment test values, or the treatment plan generation may proceed while the disease name is undetermined, and the treatment plan generation stage may be The disease name may be estimated by

According to at least one embodiment described above, an acquisition unit that acquires patient information regarding a patient and a treatment plan including each of a first treatment for the patient and a second treatment for the patient to be performed after the first treatment. a first estimation unit that estimates a first treatment effect of the first treatment based on the patient information; and a second estimation unit that estimates a second treatment effect of the second treatment based on the first treatment effect. By having an estimation unit, a first creation unit that creates reference information regarding the treatment plan based on the second treatment effect, and a presentation unit that presents the treatment plan and the reference information, it is possible to A treatment plan can be developed.

Although several embodiments have been described, these embodiments are presented by way of example and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, substitutions, and changes can be made without departing from the gist of the invention. These embodiments and their modifications are included within the scope and gist of the invention as well as within the scope of the invention described in the claims and its equivalents.

1...Hospital system 10...HIS
20...RIS
30...Modality 40...PACS
100...Treatment planning support device 110...Communication interface 120...Input interface 130...Display 140...Processing circuit 141...Acquisition function 142...Estimation function 143...First creation function 144...Second creation function 145...Presentation function 147...First estimation Function 148...Second estimation function 150...Memory 151...Treatment method DB
152...Treatment effect prediction model N...Number of corrections NW...Network

Claims (13)

an acquisition unit that acquires patient information regarding the patient and a treatment plan including each of a first treatment for the patient and a second treatment for the patient performed after the first treatment;
a first estimation unit that estimates a first treatment effect of the first treatment based on the patient information;
a second estimation unit that estimates a second treatment effect of the second treatment based on the first treatment effect;
a first creation unit that creates reference information regarding the treatment plan based on the second treatment effect;
a presentation unit that presents the treatment plan and the reference information;
Treatment planning support device. an acquisition unit that acquires patient information regarding a patient and a treatment plan including treatment for the patient;
an estimation unit that estimates the therapeutic effect of the treatment based on the patient information and a non-treatment period related to the period in which the treatment is not performed;
a first creation unit that creates reference information regarding the treatment plan based on the treatment effect;
a presentation unit that presents the treatment plan and the reference information;
Treatment planning support device. further comprising a second creation unit that creates a treatment plan for the patient based on the first treatment effect and the second treatment effect;
The treatment planning support device according to claim 1. the second creation unit determines a treatment plan that satisfies predetermined criteria;
The treatment planning support device according to claim 3. The second creation unit corrects the treatment plan when the created treatment plan does not meet predetermined criteria.
The treatment planning support device according to claim 4. The second creation unit determines a treatment plan closest to the determination criterion when the number of revisions of the treatment plan exceeds a threshold.
The treatment planning support device according to claim 5. The second creation unit fixes a part of the treatment plan and corrects the treatment plan.
The treatment planning support device according to claim 5. the second creation unit determines the treatment plan based on a user's instructions;
The treatment planning support device according to claim 3. The presentation unit presents the reference information to the user when the second creation unit creates the treatment plan.
The treatment planning support device according to claim 8. The reference information includes part or all of the content of the first therapeutic effect and the second therapeutic effect,
The treatment planning support device according to claim 1. At least one of the first treatment effect and the second treatment effect is a machine whose input is a patient's pre-treatment test value, treatment method, and treatment risk, and whose output is a post-treatment test value and treatment risk. This is a trained model learned by learning,
The treatment planning support device according to claim 1. The computer is
obtaining patient information regarding the patient and a treatment plan including each of a first treatment for the patient and a second treatment for the patient to be performed after the first treatment;
a first estimation unit that estimates a first treatment effect of the first treatment based on the patient information;
Estimating a second therapeutic effect of the second treatment based on the first treatment effect,
creating reference information regarding the treatment plan based on the second treatment effect;
presenting the treatment plan and the reference information;
Treatment planning support method. to the computer,
obtaining patient information regarding the patient and a treatment plan including each of a first treatment for the patient and a second treatment for the patient to be performed after the first treatment;
a first estimation unit that estimates a first treatment effect of the first treatment based on the patient information;
Estimating a second therapeutic effect of the second treatment based on the first treatment effect,
creating reference information regarding the treatment plan based on the second treatment effect;
presenting the treatment plan and the reference information;
program.

Images