Medical information processing device, medical information processing method, and medical information processing program

Abstract

To detect early changes in the characteristics of disease-related tissues within the subject's body. [Solution] The medical information processing device according to this embodiment includes an acquisition unit, a comparison unit, a tissue change estimation unit, and a display control unit. The acquisition unit acquires tissue information indicating the state of tissues related to diseases in the body of a subject, and surface information indicating the state of the body surface of the subject. The comparison unit compares the tissue information and the surface information and calculates the comparison result between the tissue information and the surface information. The tissue change estimation unit estimates the change in the characteristics of the tissue based on the change in the comparison result over time. The display control unit displays the estimated result of the change in the characteristics of the tissue on a terminal.

Description

[Technical Field]

[0001] Embodiments disclosed herein and in the drawings relate to medical information processing devices, medical information processing methods, and medical information processing programs. [Background technology]

[0002] As a patient's disease develops, progresses, or recurs, the characteristics of the lesional tissue (or surrounding tissue) may change (hardness, fluid retention, etc.). For this reason, depending on the patient's disease, it is crucial to detect changes in the tissue characteristics of the lesional area at an early stage.

[0003] However, the conventional procedure of detecting diseases through X-ray imaging followed by X-ray CT (Computed Tomography) scans, which relies on the manifestation of symptoms in the subject, presents a problem in detecting diseases in a subject before symptoms appear. For example, in various follow-up examinations such as post-operative care, early detection of symptoms before they appear is desirable in order to improve the subject's quality of life (QOL). [Prior art documents] [Patent Documents]

[0004] [Patent Document 1] Japanese Patent Publication No. 2009-165842 [Overview of the project] [Problems that the invention aims to solve]

[0005] One of the problems that the embodiments disclosed herein and in the drawings aim to solve is to detect early changes in the characteristics of disease-related tissues within a subject's body. However, the problems that the embodiments disclosed herein and in the drawings aim to solve are not limited to the above problem. Problems corresponding to the effects of each configuration shown in the embodiments described later can also be positioned as other problems. [Means for solving the problem]

[0006] The medical information processing device according to this embodiment includes an acquisition unit, a comparison unit, a tissue change estimation unit, and a display control unit. The acquisition unit acquires tissue information indicating the state of tissues related to diseases in the subject's body and surface information indicating the state of the subject's body surface. The comparison unit compares the tissue information and the surface information and calculates the comparison result between the tissue information and the surface information. The tissue change estimation unit estimates the change in the tissue characteristics based on the change in the comparison result over time. The display control unit displays the estimated result of the change in the tissue characteristics on a terminal. [Brief explanation of the drawing]

[0007] [Figure 1] Figure 1 is a block diagram showing an example of the configuration of a medical information processing system including a medical information processing device according to an embodiment. [Figure 2] Figure 2 is a diagram illustrating an example of the positional relationship between an internal device and an external device in an embodiment. [Figure 3] Figure 3 is a diagram illustrating an example of tissue information and body surface information related to an embodiment. [Figure 4] Figure 4 is a diagram illustrating an example of the matching results between tissue information and body surface information shown in Figure 3, relating to an embodiment. [Figure 5] Figure 5 is a diagram illustrating an example of the difference with respect to the acquisition date and time, relating to an embodiment. [Figure 6] Figure 6 is a diagram illustrating an example of the difference and trend value relative to the acquisition date and time, relating to an embodiment. [Figure 7] Figure 7 shows an example of the difference and trend value in the case where the subject's condition is pleural effusion, relating to an embodiment. [Figure 8] Figure 8 shows an example of the estimation results displayed on the terminal's display according to the embodiment. [Figure 9] Figure 9 shows an example of a graph showing tumor size over time in a comparative example and a graph showing tumor size over time in an embodiment. [Figure 10]FIG. 10 is a diagram showing an example of an estimation result regarding a tumor displayed on a display of a terminal according to an embodiment. [Figure 11] FIG. 11 is a diagram showing an example of an estimation result regarding pleural effusion displayed on a display of a terminal according to an embodiment. [Figure 12] FIG. 12 is a flowchart showing an example of a procedure of characteristic change estimation processing according to an embodiment. [Figure 13] FIG. 13 is a diagram showing an example in which an estimation result is displayed on a display of an electrocardiogram monitor when the body movement detection device is the electrocardiogram monitor according to a second application example of the embodiment.

Embodiment for Carrying out the Invention

[0008] Hereinafter, embodiments of a medical information processing apparatus, a medical information processing method, and a medical information processing program will be described with reference to the drawings. In the following embodiments, parts denoted by the same reference numerals perform the same operations, and overlapping descriptions will be omitted as appropriate.

[0009] (Embodiment) FIG. 1 is a block diagram showing an example of a configuration of a medical information processing system 1 including a medical information processing apparatus 30 according to an embodiment. As shown in FIG. 1, the medical information processing system 1 according to the embodiment includes an in-vivo device 10, an extracorporeal device 20, a medical information processing apparatus 30, and a terminal 40. The in-vivo device 10, the extracorporeal device 20, and the terminal 40 are connected to the medical information processing apparatus 30 by wire or wirelessly via a network such as the Internet and / or an intranet. Note that the connection destination to the medical information processing apparatus 30 is not limited to the in-vivo device 10 and the extracorporeal device 20, and other servers and / or other databases may be connected.

[0010] The in-vivo device 10 is a device to be placed inside a subject's body, corresponding to, for example, an implantable wireless device. The in-vivo device 10 is placed at a site corresponding to the subject's disease (hereinafter referred to as the lesion site). For example, the in-vivo device 10 is placed in a region related to tissue regarding the subject's disease (hereinafter referred to as the lesion tissue) at the lesion site. The region related to the lesion tissue corresponds to, for example, the lesion tissue itself or the tissue around the lesion tissue (hereinafter referred to as the surrounding tissue). The in-vivo device 10 is placed in the lesion tissue when performing surgical treatment, puncture, biopsy, etc. on the lesion tissue.

[0011] Note that the in-vivo device 10 may be adapted from an existing implanted device such as a pacemaker. Also, the in-vivo device 10 may be covered by, for example, a film attached to the surface of damaged tissue or a biomimetic surface using a surfactant polymer. Thereby, adhesion between the subject and the in-vivo device 10 in the subject's body can be reduced, and the influence of the in-vivo device 10 on the subject can be reduced.

[0012] When the lesion is cancer, the lesion tissue is the region of cancer tissue, and the in-vivo device 10 is placed in the region indicating cancer. Also, when the lesion is osteoporosis, the lesion site is the bone part with reduced bone density, and the in-vivo device 10 is placed in the bone part with reduced bone density. Also, when the lesion is pleural effusion, cardiac tamponade, malignant pericardial effusion, etc. accumulated in the thoracic cavity (between the lung and the chest wall), the lesion site is the chest, and the in-vivo device 10 is placed in the chest. Also, when the lesion is ascites such as malignant ascites, the lesion site is the abdomen, and the in-vivo device 10 is placed in the abdomen.

[0013] Furthermore, if the lesion is dementia or chronic subdural hematoma, the lesion site is the brain, and the in-vivo device 10 is positioned in the brain. Furthermore, if the lesion is obese, the lesion site is a fatty region, and the in-vivo device 10 is positioned in a fatty region. Furthermore, if the lesion is obese, the lesion site is a fatty region, and the in-vivo device 10 is positioned in a fatty region. Furthermore, if the lesion is cirrhosis, the lesion site is the liver, and the in-vivo device 10 is positioned in the liver. Furthermore, if the lesion is related to muscle, the lesion site is muscle, and the in-vivo device 10 is positioned in muscle.

[0014] The in-vivo device 10 includes a first sensor 11 and a first transmitter 12. The first sensor 11 detects tissue information indicating the state of tissue related to a disease in the subject's body. The first sensor 11 corresponds to, for example, a sensor that detects the mechanical properties of diseased tissue or surrounding tissue. Specifically, the first sensor 11 can be implemented as an acceleration sensor that detects the acceleration of diseased tissue or surrounding tissue, a temperature sensor that detects the temperature of diseased tissue or surrounding tissue, or a pressure sensor that detects the pressure of diseased tissue or surrounding tissue. To make the explanation more specific, the first sensor 11 will be described as an acceleration sensor. In this case, the tissue information corresponds to the acceleration (in-vivo acceleration) of diseased tissue or surrounding tissue.

[0015] The first transmitter 12 transmits tissue information, including the date and time of acquisition of the tissue information, to the medical information processing device 30. Since known wireless communication technologies such as proximity communication can be applied to the first transmitter 12, a detailed explanation is omitted. If the in-vivo device 10 and the medical information processing device 30 can be connected by a wire, the first transmitter 12 transmits the tissue information to the medical information processing device 30 via a cable electrically connecting the in-vivo device 10 and the medical information processing device 30.

[0016] An example of the internal device 10 has been described above, but the internal device 10 is not limited to that. For example, the internal device 10 may be realized by a magnetic material. This magnetic material corresponds to a specific marker placed inside the body of subject P at the site of surgical treatment or puncture. The specific marker corresponds to, for example, a metal marker placed in the breast of subject P in preparation for the disappearance of lesions during chemotherapy in neoadjuvant chemotherapy for breast cancer. In this case, the metal marker may be placed in the breast of subject P during mammography. The acquisition of tissue information will be described in the acquisition function 34a.

[0017] The extracorporeal device 20 is a device placed outside the body of the subject, for example, by being attached to the body surface of the subject. For example, the extracorporeal device 20 is attached to the body surface of the subject closest to the internal device 10 or the lesion site. The extracorporeal device 20 is not limited to a device that is constantly attached to the body surface of the subject when various processes according to this embodiment are performed, and may be implemented by, for example, a device installed on a chair when the subject is seated, or a device installed separately when the subject is sleeping.

[0018] Furthermore, the external device 20 is not limited to the type attached to the subject, but may be implemented as a non-contact device for the subject (a device capable of photographing the subject (e.g., an optical camera), or a device that transmits and receives radio waves using a wireless LAN (Local Area Network) or millimeter-wave radar). The external device 20 may also be incorporated into, for example, a sensor that measures the subject's electrocardiogram (e.g., an electrocardiogram sensor). For the purposes of this explanation, the external device 20 will be assumed to be a device attached to the subject.

[0019] The external device 20 includes a second sensor 21 and a second transmitter 22. The second sensor 21 detects body surface information indicating the state of the subject's body surface. The second sensor 21 corresponds to, for example, a sensor that detects the mechanical properties of the subject's body surface. Specifically, the second sensor 21 can be an acceleration sensor that detects the acceleration (external acceleration) of the subject's body surface, a temperature sensor that detects the temperature of the subject's body surface, or a pressure sensor that detects the pressure of the subject's body surface. To make the explanation more specific, the second sensor 21 will be described as an acceleration sensor. In this case, the body surface information corresponds to the acceleration of the subject's body surface.

[0020] The second transmitter 22 transmits body surface information, including the date and time of acquisition of the body surface information, to the medical information processing device 30. Since known wireless communication technology can be applied to the second transmitter 22, its description is omitted. If the external device 20 and the medical information processing device 30 can be connected by wire, the second transmitter 22 transmits the body surface information to the medical information processing device 30 via a cable electrically connecting the external device 20 and the medical information processing device 30.

[0021] Figure 2 shows an example of the positional relationship between the internal device 10 and the external device 20. In Figure 2, the internal device 10 is located in the chest area inside the body of subject P. In this case, as shown in Figure 2, the external device 20 is located in front of the internal device 10, that is, on the body surface of subject P facing and in closest contact with the internal device 10.

[0022] Furthermore, if the external device 20 is continuously attached to the subject P, the internal device 10 and the external device 20 may have a schedule timer. In this case, the internal device 10 and the external device 20 may operate at pre-planned (set) times using the schedule timer. Pre-set times include, for example, 2:00-3:00, 8:00-9:00, 16:00-17:00, etc.

[0023] Terminal 40 has a display 41, an input interface (not shown), a processing circuit (not shown), and a memory (not shown). Terminal 40 is compatible with a client device, viewer device, and / or a subject P's smartphone with a health support app, sleep analysis app, etc. installed in an electronic medical record system and / or medical information system.

[0024] The processing circuit in terminal 40 is implemented by, for example, a processor. The term "processor" refers to circuits such as CPUs, GPUs (Graphics Processing Units), Application Specific Integrated Circuits (ASICs), and programmable logic devices (e.g., Simple Programmable Logic Devices (SPLDs), Complex Programmable Logic Devices (CPLDs), and Field Programmable Gate Arrays (FPGAs)). The processing circuit in terminal 40 is stored in memory (not shown) and controls the entire terminal 40 according to the program.

[0025] The memory in terminal 40 stores data to be displayed by the display control function 34d. The memory 33 is implemented by, for example, semiconductor memory elements such as RAM (Random Access Memory) and flash memory, a hard disk, or an optical disc. Furthermore, the memory in terminal 40 stores programs for each circuit included in terminal 40 to perform its function. The memory is an example of a terminal memory unit.

[0026] If terminal 40 is a client device, the input interface is implemented by a trackball, switches, buttons, mouse, keyboard, touchpad for input operations by touching the operating surface, touchscreen with integrated display screen and touchpad, non-contact input circuit using optical sensors, and audio input circuit (microphone, etc.) for various instructions and settings. If terminal 40 is a smartphone, the input interface is implemented by switches, buttons, touchpad, touchscreen, and audio input circuit for various instructions and settings. The input interface converts the input operations received from the user into electrical signals and outputs them to the processing circuit within terminal 40.

[0027] Furthermore, the input interface in terminal 40 is not limited to those equipped with physical operating components such as a mouse or keyboard. For example, an electrical signal processing circuit that receives electrical signals corresponding to input operations from an external input device located separately from terminal 40 and outputs these electrical signals to the processing circuit of terminal 40 is also included as an example of an input interface. An input interface is just one example of an input unit and may also be called an operation unit.

[0028] Display 41 displays various information under the control of the processing circuit of terminal 40 and / or the display control function 34d. For example, display 32 displays a GUI (Graphical User Interface) for receiving user instructions. For example, display 41 is a liquid crystal display, a CRT (Cathode Ray Tube) display, or an organic EL (Electro Luminescence) display. Display 41 is an example of a display unit. Display 41 also displays estimation results estimated by the tissue change estimation function 34c under the control of the display control function 34d. The content displayed on display 41 will be explained later.

[0029] The medical information processing device 30 can be implemented, for example, as a server device. Alternatively, the medical information processing device 30 may be implemented as various medical servers, such as a picture archiving and communication system (PACS). As shown in Figure 1, the medical information processing device 30 includes an input interface 31, a display 32, a memory 33, and a processing circuit 34.

[0030] The input interface 31 is implemented by a trackball, switches, buttons, mouse, keyboard, touchpad for input operations by touching the operating surface, touchscreen with integrated display screen and touchpad, non-contact input circuit using optical sensors, audio input circuit (microphone, etc.), etc. The input interface 31 converts the input operations received from the user into electrical signals and outputs them to the processing circuit 34.

[0031] Furthermore, the input interface 31 is not limited to those equipped with physical operating components such as a mouse or keyboard. For example, an electrical signal processing circuit that receives electrical signals corresponding to input operations from an external input device provided separately from the medical information processing device 30 and outputs these electrical signals to the processing circuit 34 is also included as an example of an input interface 31. The input interface 31 is an example of an input unit and may also be called an operation unit.

[0032] The display 32 displays various types of information under the control of the display control function 34f. For example, the display 32 displays a GUI for receiving user instructions, estimation results estimated by the organizational change estimation function 34c, etc. For example, the display 32 may be a liquid crystal display or an organic EL display. The display 32 is an example of a display unit.

[0033] Memory 33 can be implemented using, for example, semiconductor memory elements such as RAM or flash memory, a hard disk, or an optical disc. For example, memory 33 stores various data generated by various processes performed by the processing circuit 34 described later. Memory 33 also stores estimation results estimated by the tissue change estimation function 34c. Furthermore, memory 33 stores programs for each circuit included in the medical information processing device 30 to realize its function. Memory 33 is an example of a storage unit.

[0034] The processing circuit 34 is implemented by the processor. The processing circuit 34 controls the operation of the entire medical information processing device 30 by executing the acquisition function 34a, the comparison function 34b, the tissue change estimation function 34c, and the display control function 34d. The processing circuit 34 that implements the acquisition function 34a corresponds to the acquisition unit. The processing circuit 34 that implements the comparison function 34b corresponds to the comparison unit. The processing circuit 34 that implements the tissue change estimation function 34c corresponds to the tissue change estimation unit. The processing circuit 34 that implements the display control function 34d corresponds to the display control unit.

[0035] The processing circuit 34 reads and executes a program corresponding to the acquisition function 34a from the memory 33. As a result, the acquisition function 34a acquires tissue information indicating the state of disease-related tissues within the subject P's body, and surface information indicating the state of the subject P's body surface. For example, the acquisition function 34a acquires tissue information from the internal device 10. The acquisition function 34a stores the acquired tissue information in the memory 33. If the internal device 10 is made of a magnetic material, the acquisition function 34a has a function capable of detecting the movement of the magnetic material. In this case, the acquisition function 34a functions as a magnetic transmitter capable of detecting the position of the magnetic material. By detecting the position of the magnetic material over time, the acquisition function 34a acquires the acceleration indicating the movement of the magnetic material within the body as internal acceleration in the tissue information.

[0036] Furthermore, the acquisition function 34a acquires body surface information from the extracorporeal device 20. The acquisition function 34a stores the acquired body surface information in the memory 33. As a modification of this embodiment, the acquisition function 34a may acquire body surface information from a trained model by inputting tissue information into the trained model. In this case, the trained model is pre-trained and stored in the memory 33. Alternatively, the acquisition function 34a may acquire body surface information from tissue information using statistical analysis processing instead of the trained model. In this case, the program that implements the statistical analysis processing is pre-stored in the memory 33.

[0037] Furthermore, if the external device 20 is implemented by a non-contact device to the subject P, the acquisition function 34a may acquire body surface information based on the output from the non-contact device. For example, if an optical camera is used as the non-contact device, the acquisition function 34a acquires body surface information, including the acceleration of the body surface, by performing image analysis on multiple images acquired by the optical camera in a time series. Since known image processing methods such as alignment processing and difference processing can be applied to this image analysis, a detailed explanation is omitted.

[0038] Furthermore, when a wireless LAN or millimeter-wave radar (e.g., LiDAR: Light Detection and Ranging) is used as a non-contact device, the acquisition function 34a acquires body surface information, including body surface acceleration, by performing various data processing operations on the data acquired by the wireless LAN or millimeter-wave radar. Since known data processing methods can be applied to this data processing, a detailed explanation is omitted.

[0039] Figure 3 shows an example of tissue information TI and body surface information BS. When both the first sensor 11 and the second sensor 21 are implemented as acceleration sensors (3-axis acceleration sensors) corresponding to three orthogonal axes (X axis, Y axis, Z axis), the output from the first sensor 11 (internal acceleration in tissue information) and the output from the second sensor 21 (external acceleration in body surface information) have the acceleration corresponding to each of the three orthogonal axes (X axis, Y axis, Z axis) and the date and time of acquisition of said acceleration.

[0040] Furthermore, if the external device 20 is constantly attached to the subject P, and both the internal device 10 and the external device 20 have schedule timers, the acquisition function 34a acquires tissue information and body surface information according to the operation of the internal device 10 and the external device 20 at the scheduled time. Also, although Figure 3 shows an example in which tissue information TI and body surface information BS are acquired at regular time intervals, it is not limited to this, and tissue information TI and body surface information BS may be acquired according to signals from outside the subject P. The processing details for acquiring tissue information TI and body surface information BS according to signals from outside the subject P will be explained in the application example of this embodiment.

[0041] The processing circuit 34 reads and executes a program corresponding to the comparison function 34b from memory 33. This allows the comparison function 34b to compare tissue information with body surface information. The comparison function 34b then calculates the comparison result. For example, the comparison function 34b matches the acquisition dates and times of the tissue information and body surface information. By comparing the acquisition dates and times of the tissue information and body surface information, the comparison function 34b identifies the corresponding acceleration in units of, for example, 1 / 10th of a second.

[0042] Figure 4 shows an example of the matching result BR between the tissue information TI and body surface information BS shown in Figure 3. The matching result BR shown in Figure 4 shows the intracellular and extracellular accelerations matched in units of 1 / 10th of a second. The comparison function 34b stores the matching result BR in the memory 33.

[0043] The comparison function 34b uses the matched tissue information TI and body surface information BS to calculate the difference (which may also be called difference data) between the tissue information TI and the body surface information as a comparison result for each acquisition date and time. The formula for calculating the difference Δ for each acquisition date and time is given, for example, by the following formula (1) or (2). Note that the formula for calculating the difference Δ is not limited to formulas (1) and (2), and may be expressed by other formulas as long as they can express the difference between the acceleration of the matched tissue and the acceleration of the body surface.

[0044] Difference Δ = |(X 内 - X 外 ) + (Y 内 - Y 外 ) + (Z 内 - Z 外 )| ··· (1) Difference Δ = {(X 内 - X 外 )(Y 内 - Y 外 )(Z 内 - Z 外 )}^(1 / 2) ··· (2)

[0045] In equations (1) and (2), the subscript "in" indicates the inside (tissue) of the subject P, and the subscript "out" indicates the outside (body surface) of the subject P. Also, in equations (1) and (2), X 内 represents the acceleration of the X-axis in the tissue inside the subject P, Y 内 represents the acceleration of the Y-axis in the tissue inside the subject P, Z 内 represents the acceleration of the Z-axis in the tissue inside the subject P. Also, in equations (1) and (2), X 外 represents the acceleration of the X-axis on the body surface of the subject P, Y 外 represents the acceleration of the Y-axis on the body surface of the subject P, Z 外 represents the acceleration of the Z-axis on the body surface of the subject P. As shown in equations (1) and (2), the difference Δ is based on the acceleration outside the body.

[0046] The comparison function 34b stores the difference Δ calculated for each acquisition date and time in memory 33 as a comparison result, associating it with the acquisition date and time. Figure 5 shows an example of the difference Δ with respect to the acquisition date and time. The vertical axis in Figure 5 shows the magnitude of the difference Δ. The horizontal axis in Figure 5 shows the acquisition date and time (e.g., on the order of seconds). As shown in Figure 5, the magnitude of the difference fluctuates greatly. When the tissue surrounding the internal device 10 is soft, there is a discrepancy in the way the acceleration detected by the internal device 10 and the acceleration detected by the external device 20 vibrate (the difference between the devices is large). In other words, when the tissue surrounding the internal device 10 is soft, or when there is a lot of liquid such as water around the tissue, the difference between the acceleration of the tissue and the acceleration of the body surface becomes large.

[0047] On the other hand, if the tissue surrounding the internal device 10 is rigid, the internal device 10 and the external device 20 vibrate in the same way (the difference between the devices is small). In other words, if the tissue surrounding the internal device 10 is rigid, or if there is little liquid such as water around the tissue, the difference between the acceleration of the tissue and the acceleration of the body surface becomes small.

[0048] The processing circuit 34 estimates changes in tissue characteristics based on the time-dependent changes in the comparison results using the tissue change estimation function 34c. Tissue characteristics include, for example, the stiffness of the tissue in relation to the placement of the in-vivo device 10, and the accumulation of water and air around the tissue. For example, the tissue change estimation function 34c calculates the trend of the difference Δ (hereinafter referred to as the trend value (tendency value)) by applying a moving average of the difference Δ with respect to the acquisition date and time.

[0049] Specifically, the organizational change estimation function 34c calculates the trend value by using each of the multiple acquisition dates and times as a reference and averaging the difference Δ over a predetermined past period from that reference acquisition date and time. The predetermined past period is, for example, 10 seconds. In this way, the organizational change estimation function 34c calculates the trend value for each of the multiple acquisition dates and times by calculating the average of the difference over the most recent past period. The fluctuation (variance) of the difference Δ is reduced by calculating the trend value.

[0050] Next, the tissue change estimation function 34c compares the trend value with a predetermined threshold. The predetermined threshold is pre-set as a table corresponding to, for example, the location of the subject P's medical condition, the location where the internal device 10 is placed (implanted), the subject P's disease name, organ, and test order, and stored in memory 33. The predetermined threshold may also be set as the trend value at a time when the subject P's medical condition worsened in the past. The tissue change estimation function 34c stores the comparison result between the trend value and the predetermined threshold in memory 33 as an estimated result of changes in tissue characteristics.

[0051] If the trend value exceeds a predetermined threshold, the tissue change estimation function 34c estimates that the tissue is soft. On the other hand, if the trend value is below the predetermined threshold, the tissue change estimation function 34c estimates that the tissue is hard. The estimation of the softness / hardness (hardness / softness) of the tissue described above is explained by comparing a threshold with the trend value, but is not limited to this. For example, the tissue change estimation function 34c may estimate the softness / hardness (hardness / softness) of the tissue by inputting the trend value into a trained model that outputs the softness / hardness (hardness / softness) of the tissue as input.

[0052] Figure 6 shows an example of the difference Δ with respect to the acquisition date and time and the trend value. The vertical axis in Figure 6 shows the magnitude of the difference Δ. The horizontal axis in Figure 6 shows the acquisition date and time (e.g., on the order of seconds). As shown in Figure 6, the fluctuation of the trend value is smaller than the fluctuation of the difference. As shown in Figure 6, if the tissue surrounding the in-vivo device 10 is soft, or if there is a lot of fluid such as water around the tissue, the trend value will be large (the difference between devices will be large).

[0053] On the other hand, if the tissue surrounding the internal device 10 is rigid, or if there is little fluid such as water around the tissue, the trend value will be small. The horizontal line TH shown in Figure 6 indicates a predetermined threshold. In this case, the tissue change estimation function 34c estimates that the tissue is soft if the trend value exceeds the predetermined threshold.

[0054] For example, as a tumor shrinks (cancer cells die) due to chemotherapy or radiation therapy, the tissue surrounding the tumor becomes softer. At this time, the in-vivo device 10 becomes more mobile compared to when the tumor is larger. As the in-vivo device 10 becomes more mobile, the trend value decreases, and at this time, the tissue change estimation function 34c uses the trend value to determine the therapeutic effect on the tumor as a state corresponding to the disease in the tissue.

[0055] On the other hand, when a benign tumor transforms into a malignant tumor (cancerous transformation), the surrounding tissue hardens due to the enlargement of the cancer. At this time, the in-vivo device 10 becomes less mobile compared to the benign tumor. As the in-vivo device 10 becomes less mobile, the trend value increases, and the tissue change estimation function 34c uses the trend value to determine the degree of malignancy of the tumor as a disease-appropriate state in the tissue.

[0056] Figure 7 shows an example of the difference Δ and trend value when the patient P's condition is pleural effusion. As shown in Figure 7, the trends in the difference and trend value differ depending on the degree of pleural effusion. Therefore, the tissue change estimation function 34c can estimate the degree of fluid accumulation by appropriately setting the threshold TH and comparing it with the trend value.

[0057] In other words, the tissue change estimation function 34c further estimates the disease-specific state (pathological condition) of the tissue based on the estimation results of changes in tissue characteristics (comparison results between threshold TH and trend value). In the example shown in Figure 7, the tissue change estimation function 34c estimates the degree of pleural effusion based on the comparison results between threshold TH and trend value.

[0058] Furthermore, the degree of fluid accumulation, which indicates the disease-related state in the tissue, is not limited to the large, medium, or small levels of accumulation as defined by the multiple thresholds shown in Figure 7. For example, the tissue change estimation function 34c may use the trend value from the time when subject P's condition worsened in the past as a reference value, and calculate the ratio of the current trend value based on that reference value as the pleural effusion index indicating the state of pleural effusion. Alternatively, the tissue change estimation function 34c may calculate the difference between the previous pleural effusion index and the pleural effusion index calculated this time.

[0059] The processing circuit 34 and the display control function 34d cause the estimated results of changes in tissue characteristics to be displayed on the terminal 40. The display control function 34d also causes the estimated disease state to be displayed on the terminal 40, for example. Specifically, the display control function 34d causes the estimated results of changes in tissue characteristics and / or the estimated disease state to be displayed on the display 41 of the terminal 40. The display control function 34d may also display the estimated results of changes in tissue characteristics and / or the estimated disease state on the display 32.

[0060] Figure 8 shows an example of the estimation results displayed on the display 41 of terminal 40. In Figure 8, terminal 40 corresponds to a terminal for medical professionals, such as a client device and / or viewer device in an electronic medical record system. In Figure 8, the mobility of the tumor is shown as an example of the estimation results. In this case, the tissue change estimation function 34c may estimate the size of the tumor based on the previous estimation result and the current estimation result.

[0061] For example, the tissue change estimation function 34c estimates the size of the tumor (such as malignancy) based on the correlation between the tumor's mobility and its size, which has been analyzed in advance. Specifically, when the in-vivo device 10 is implanted in tumor tissue, if the trend value decreases, the tissue change estimation function 34c estimates that the tumor has grown because the tumor tissue has become less mobile.

[0062] Figure 9 shows an example of graph CE, which shows the size of the tumor over time in the comparative example, and graph EM, which shows the size of the tumor over time in this embodiment. As shown in Figure 9, in this embodiment, compared to the comparative example, the size of the tumor can be displayed on the terminal 40 at time AR, before the tumor grows larger.

[0063] In other words, in the comparative example graph CE, which displays the size of a tumor estimated from imaging tests (such as X-rays and X-ray CT scans), there are limitations on the frequency of imaging tests due to radiation exposure, etc., which can make it difficult to detect tumor enlargement early, for example. On the other hand, in the graph EM of this embodiment, trend values ​​can be obtained at a much higher frequency than in the comparative example, so users can notice signs of changes in tumor size earlier than in the comparative example.

[0064] Figure 10 shows an example of the estimated results regarding a tumor displayed on the display 41 of terminal 40. The display 41 in Figure 10 corresponds to terminal 40 for medical professionals such as attending physicians. The estimated results shown in Figure 10 include, for example, the ratio of the trend value in the previous estimation result and the trend value in the current estimation result, the ratio of the tumor size in the previous estimation result and the tumor size in the current estimation result, and recommendations for further examination based on the estimation of malignancy due to the difference between the tumor stiffness in the previous estimation result and the tumor stiffness in the current estimation result. The display control function 34d displays the above ratio and the recommendation for further examination on the display 41.

[0065] Figure 11 shows an example of the estimated results regarding pleural effusion displayed on the display 41 of terminal 40. The display 41 in Figure 11 corresponds to terminal 40 for medical professionals such as attending physicians, as in Figure 10. The pleural effusion index shown in the estimated results in Figure 11 is estimated by the tissue change estimation function 34c based, for example, on the trend value in the previous estimation result and the trend value in the current estimation result.

[0066] Furthermore, the tissue change estimation function 34c may calculate the difference between the current trend value and the pleural effusion index corresponding to the current trend value, based on the trend value at the time of implantation of the in-vivo device 10. In this case, the display control function 34d may display the resulting effusion index on the display 41, as shown in Figure 11. In addition, the display control function 34d may display recommendations for further examinations, etc., on the display 41 based on this difference, as shown in Figure 11.

[0067] The overall configuration of the medical information processing system 1 according to this embodiment has been described above. Next, the process of estimating changes in tissue characteristics using the medical information processing device 30 and displaying them on the terminal 40 (hereinafter referred to as the characteristic change estimation process) will be described.

[0068] Figure 12 is a flowchart showing an example of the procedure for characteristic change estimation processing. Prior to performing the characteristic change estimation processing, the in-vivo device 10 is assumed to be pre-placed in the tissue related to the disease condition of the subject P, as shown in Figure 2. Also, prior to performing the characteristic change estimation processing, the extracorporeal device 20 is assumed to be pre-attached to the body surface of the subject P near the tissue where the in-vivo device 10 is placed, as shown in Figure 2.

[0069] (Characteristic change estimation process) (Step S121) The processing circuit 34 acquires tissue information TI, which indicates the state of disease-related tissues within the subject P's body, and surface information BS, which indicates the state of the subject P's body surface, using the acquisition function 34a. For example, the acquisition function 34a acquires tissue information TI from the internal device 10, which includes acceleration related to the internal tissues of the subject P and the date and time the acceleration was acquired. The acquisition function 34a also acquires surface information BS from the external device 20, which includes acceleration on the subject P's body surface and the date and time the acceleration was acquired. The acquisition function 34a stores the acquired tissue information TI and surface information BS in the memory 33.

[0070] (Step S122) The processing circuit 34 uses the comparison function 34b to match the tissue information TI and the body surface information BS based on the acquisition date and time of the tissue information TI and the body surface information BS. Specifically, the comparison function 34b generates a matching result BR as shown in Figure 4 by matching the tissue information TI and the body surface information BS using the acquisition date and time. The comparison function 34b stores the matching result BR in the memory 33.

[0071] (Step S123) The processing circuit 34 compares the matched tissue information TI and body surface information BS using the comparison function 34b and generates differential data having multiple differences Δ for each acquisition date and time. For example, the comparison function 34b applies the acceleration of the tissue information TI and the acceleration of the body surface information BS to equation (1) or equation (2) for each of the multiple acquisition dates and times to generate differential data. The comparison function 34b stores the generated differential data in the memory 33.

[0072] (Step S124) The processing circuit 34 calculates trend values ​​along the time series based on the differential data using the tissue change estimation function 34c. Specifically, the tissue change estimation function 34c calculates multiple trend values ​​corresponding to multiple acquisition dates and times by applying a moving average to each acquisition date and time in the differential data. The tissue change estimation function 34c stores the generated multiple trend values ​​in the memory 33.

[0073] (Step S125) The processing circuit 34 estimates changes in the characteristics of the subject P's tissue based on multiple trend values ​​using the tissue change estimation function 34c. For example, the tissue change estimation function 34c estimates tissue changes by comparing each of the multiple trend values ​​with a specified threshold. Furthermore, the tissue change estimation function 34c estimates the disease-specific state (pathological condition) of the subject P's tissue based on the estimation results of changes in tissue characteristics.

[0074] For example, the tissue change estimation function 34c estimates the condition of subject P based on past trend values, such as the trend value at the time when subject P's condition worsened, and the current trend value. Specifically, the tissue change estimation function 34c estimates the condition of subject P using a correspondence table of disease conditions to the difference or ratio between past trend values ​​and current trend values. The tissue change estimation function 34c stores the estimation results, including the above various estimations, in the memory 33.

[0075] (Step S126) The processing circuit 34, using the display control function 34d, causes the estimation results to be displayed on the display 41 of the terminal 40. The display control function 34d also displays the estimated disease state on the display 41. Alternatively, the display control function 34d may also cause the estimation results to be displayed on the display 32 of the medical information processing device 30.

[0076] For example, the display control function 34d causes the estimated results to be displayed on the display 41 of the terminal 40 of a medical professional display system (such as an electronic medical record or integrated viewer). The display control function 34d also causes the estimated results to be displayed in health support apps, sleep analysis apps, etc., installed on the terminal 40 owned by the subject P.

[0077] As a modification of this embodiment, if the subject P's condition is pleural effusion, the acquisition function 34a may acquire tissue information TI and body surface information BS when the subject P is performing strenuous exercise. In this case, the tissue change estimation function 34c determines the degree of fluid accumulation in the subject P by detecting that the internal device 10 is not moving much, even though the subject P's heart should be beating vigorously. Alternatively, the acquisition function 34a may acquire tissue information TI and body surface information BS when the subject P is not performing strenuous exercise. In this case, the tissue change estimation function 34c determines the degree of fluid accumulation in the subject P by detecting that the internal device 10 is moving, even though the subject P's heart should not be beating vigorously.

[0078] The medical information processing device 30 according to the embodiment described above acquires tissue information TI indicating the state of disease-related tissues within the subject P's body and surface information BS indicating the state of the subject P's body surface. It compares the tissue information TI with the surface information BS, calculates the comparison result between the tissue information TI and the surface information BS, estimates the change in the tissue's characteristics based on the change in the comparison result over time, and displays the estimated change in the tissue's characteristics on the terminal 40. In the medical information processing device 30 according to the embodiment, the tissue characteristic is the hardness of the tissue. Furthermore, the medical information processing device 30 according to the embodiment acquires tissue information TI from an internal device 10 located in a region related to the subject P's tissue, acquires surface information BS from an external device 20 located outside the subject P's body, or acquires surface information BS by inputting tissue information TI into a trained model.

[0079] Furthermore, in the medical information processing device 30 according to the embodiment, tissue information TI and body surface information BS have acquisition dates and times for tissue information TI and body surface information BS, and the medical information processing device 30 according to the embodiment matches the acquisition dates and times of tissue information TI and body surface information BS, and uses the matched tissue information and body surface information to calculate the difference between tissue information TI and body surface information BS as a comparison result for each acquisition date and time.

[0080] Based on these findings, the medical information processing device 30 according to the embodiment can easily and frequently acquire the difference in movement (acceleration) between the internal device 10 and the external device 20, and the change in that difference over time, without performing image diagnosis on the subject P. This allows for the estimation of changes in the characteristics of the tissue surrounding the internal device 10. As a result, the medical information processing device 30 according to the embodiment can detect changes in the characteristics of the tissue at the lesion site of the subject P at an early stage and present the estimation results to medical professionals (users) such as the attending physician, the subject P, etc. According to the medical information processing device 30 according to the embodiment, for example, as shown in Figures 7 and 9, the user can notice signs of changes in tumor size at an earlier stage compared to graph CE in the comparative example.

[0081] In addition, the medical information processing device 30 according to the embodiment further estimates the disease-dependent state in the tissue of the subject P based on the estimation results, and further displays the estimated disease state on the terminal 40. Thus, according to the medical information processing device 30 according to the embodiment, in addition to presenting the user with changes in the characteristics of the tissue at the lesion site of the subject P, it is possible to present the user with a response based on the estimated changes in the disease state, for example, as shown in Figures 10 and 11.

[0082] Based on the above, the medical information processing device 30 according to the embodiment can detect changes in tissue characteristics due to disease at an early stage, which leads to earlier intervention for lesions and improves the quality of life (QOL) of the subject P.

[0083] (First application example) This application example involves correcting tissue information by acquiring body movement information indicating the body movement of subject P from a body movement detection device that detects the body movement of subject P. Examples of body movement detection devices include electrocardiogram monitors, respiratory monitors, and heart rate monitors. The processing circuit 34 acquires body movement information from the body movement detection device using the acquisition function 34a. The body movement information includes body movement data indicating the body movement of subject P and the date and time of acquisition of the body movement data. The acquisition function 34a stores the body movement information in the memory 33.

[0084] The processing circuit 34 corrects (modifies) the tissue information TI using the acquired body movement information via the comparison function 34b. For example, the comparison function 34b corrects the tissue acceleration (tissue information) using tissue information TI and body movement information acquired at the same time. In the corrected acceleration, noise caused by the subject P's body movement is reduced. In other words, the corrected tissue information is less affected by noise caused by the subject P's body movement. The comparison function 34b compares the corrected tissue information with the body surface information and calculates the comparison result.

[0085] According to the medical information processing device 30 in this application example, the accuracy of trend values ​​can be improved by modifying tissue information using body movement information indicating the body movements of the subject P. As a result, the medical information processing device 30 in this application example can present the estimated results to the user with improved accuracy. Therefore, the medical information processing device 30 in this application example can detect changes in tissue characteristics due to disease at an early stage by improving accuracy, thereby enabling accurate treatment of lesions. For the above reasons, the medical information processing device 30 in this application example can further improve the quality of life (QOL) of the subject P. Other effects are the same as in the embodiment, so their explanation is omitted.

[0086] (Second application example) This application example involves acquiring body movement information from a body movement detection device and, based on that information, acquiring tissue information TI and body surface information BS at predetermined timings when body movement decreases. To make the explanation more concrete, the body movement detection device will be described as an electrocardiogram monitor. In this case, the body movement information corresponds to the electrocardiogram waveform. The body movement detection device may also function as an external device 20.

[0087] The processing circuit 34 acquires the electrocardiogram waveform of subject P from the electrocardiogram monitor using the acquisition function 34a. The acquisition function 34a acquires tissue information and body surface information during periods in the electrocardiogram waveform when the body movement of subject P is smaller than other periods (hereinafter referred to as the minimum body movement period). The minimum body movement period is a predetermined period including, for example, the end of diastole and / or the end of systole, and corresponds to a predetermined timing. At this time, the acquisition function 34a acquires tissue information and body surface information at the same timing each time. Even when the body movement detection device is a heart rate monitor or blood pressure monitor, the acquisition function 34a acquires tissue information and body surface information at the same timing each time, according to the set value.

[0088] The processing circuit 34 may, by means of the display control function 34d, display the estimation results estimated by the tissue change estimation function 34c on the monitor of the body movement detection device. Figure 13 shows an example in which the estimation results are displayed on the display MD of the electrocardiogram monitor when the body movement detection device is an electrocardiogram monitor. As shown in Figure 13, the user can check the estimation results displayed by the display control function 34d on the electrocardiogram of the subject P, along with the electrocardiogram waveform.

[0089] According to the medical information processing device 30 in this application example, tissue information TI and body surface information BS can be acquired at a predetermined timing (minimum body movement period) when the body movement is small, using body movement information indicating the body movement of the subject P. As a result, according to the medical information processing device 30 in this application example, noise caused by the body movement of the subject P can be reduced, and the accuracy of the trend value can be improved. Other effects are the same as in the embodiments, so their explanation will be omitted.

[0090] When the technical concept of this embodiment is realized by a medical information processing method, the medical information processing method acquires tissue information indicating the state of disease-related tissues within the subject P's body and surface information indicating the state of the subject P's body surface, compares the acquired tissue information and surface information, calculates the comparison result between the acquired tissue information and surface information, estimates the change in the tissue's characteristics based on the change in the calculated comparison result over time, and displays the estimated result of the change in the tissue's characteristics on the terminal 40. The processing procedure for the characteristic change estimation process realized by the medical information processing method is in accordance with the embodiment. Furthermore, the effects of the medical information processing method are the same as in the embodiment. For these reasons, a description of the processing procedure and effects of the characteristic change estimation process in the medical information processing method is omitted.

[0091] When the technical concept of this embodiment is realized in a medical information processing program, the medical information processing program enables a computer to perform the following medical information processing method: acquire tissue information indicating the state of disease-related tissues within the subject P's body and surface information indicating the state of the subject P's body surface; compare the acquired tissue information and surface information; calculate the comparison result between the acquired tissue information and surface information; estimate the change in the characteristics of the tissue based on the change in the calculated comparison result over time; and display the estimated result of the change in the characteristics of the tissue on the terminal 40. For example, the characteristic change estimation process can also be realized by installing the medical information processing program on a computer such as the medical information processing device 30 shown in Figure 1 and loading them into memory. In this case, the program that can cause a computer to execute this process can also be stored and distributed on a storage medium such as a magnetic disk (hard disk, etc.), optical disk (CD-ROM, DVD, etc.), or semiconductor memory.

[0092] Furthermore, the distribution of the medical information processing program is not limited to the above-mentioned media; it may also be distributed using telecommunications functions, such as downloading via the Internet. The processing procedure in the medical information processing program conforms to the characteristic change estimation process. The effects of the medical information processing program are the same as those in the embodiment. For these reasons, a detailed explanation of the processing procedure and effects of the characteristic change estimation process in the medical information processing program is omitted.

[0093] According to at least the embodiments, modifications, and applications described above, it is possible to detect changes in the characteristics of disease-related tissues within the subject P's body at an early stage. This can improve the subject P's quality of life (QOL).

[0094] While several embodiments have been described, these embodiments are presented as examples only and are not intended to limit the scope of the invention. These embodiments can be implemented in a variety of other forms, and various omissions, substitutions, modifications, and combinations of embodiments are possible without departing from the spirit of the invention. These embodiments and their variations are included in the scope and spirit of the invention, as well as in the claims and their equivalents. [Explanation of Symbols]

[0095] 1. Medical Information Processing System 10 Intravascular Devices 11. First Sensor 12. First Transmitter 20 In vitro devices 21 Second Sensor 22 Second Transmitter 30 Medical Information Processing Devices 31 Input Interfaces 32 displays 33 memory 34 Processing Circuits 34a Acquisition function 34b Comparison function 34c Tissue change estimation function 34d Display Control Function 40 devices 41 displays

Claims

1. An acquisition unit that acquires tissue information indicating the state of tissues related to diseases inside the subject's body and surface information indicating the state of the subject's body surface, A comparison unit that compares the tissue information with the body surface information and calculates the comparison result between the tissue information and the body surface information, A tissue change estimation unit estimates changes in the characteristics of the tissue based on the changes in the comparison results over time, A display control unit that displays the estimated results of changes in the characteristics of the aforementioned organization on a terminal, A medical information processing device equipped with [a specific feature].

2. The aforementioned characteristics are the hardness of the tissue and the retention of water and air around the tissue. The medical information processing device according to claim 1.

3. The tissue information and the body surface information have the acquisition date and time of the tissue information and the acquisition date and time of the body surface information, The comparison unit is, The acquisition dates and times of the aforementioned tissue information and the aforementioned body surface information are compared, Using the matched tissue information and the body surface information, the difference between the tissue information and the body surface information is calculated as the comparison result for each acquisition date and time. The medical information processing device according to claim 1.

4. The acquisition unit is, The aforementioned tissue information is obtained from an in-vivo device placed in a region related to the tissue, The body surface information is acquired from an extracorporeal device placed outside the body of the subject, or the body surface information is acquired by inputting the tissue information into a trained model. The medical information processing device according to claim 1.

5. The acquisition unit acquires motion information indicating the subject's motion from a motion detection device that detects the subject's motion, The comparison unit is, The aforementioned organizational information is corrected using the aforementioned body movement information, The corrected tissue information and the body surface information are compared to calculate the comparison result. The medical information processing device according to claim 1.

6. The tissue change estimation unit further estimates the state of the tissue corresponding to the disease based on the estimation result, The display control unit further displays the disease state on the terminal. The medical information processing device according to claim 1.

7. The acquisition unit is, From the body movement detection device that detects the body movements of the subject, further body movement information indicating the body movements of the subject is acquired. Based on the aforementioned body movement information, the tissue information and the body surface information are acquired at a predetermined timing when the body movement becomes smaller. A medical information processing device according to any one of claims 1 to 6.

8. Tissue information indicating the state of tissues related to diseases within the subject's body, and surface information indicating the state of the subject's body surface are obtained. The tissue information and the body surface information are compared, and the comparison result between the tissue information and the body surface information is calculated. Based on the changes in the comparison results over time, the changes in the characteristics of the tissue are estimated. To display the estimated results of changes in the characteristics of the aforementioned organization on the terminal. A medical information processing method comprising the following.

9. to the computer Tissue information indicating the state of tissues related to diseases within the subject's body, and surface information indicating the state of the subject's body surface are obtained. The tissue information and the body surface information are compared, and the comparison result between the tissue information and the body surface information is calculated. Based on the changes in the comparison results over time, the changes in the characteristics of the tissue are estimated. To display the estimated results of changes in the characteristics of the aforementioned organization on the terminal. A medical information processing program that makes this possible.

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