Image reading support device and operation method of image reading support device

Abstract

To improve quality of an examination.SOLUTION: An image reading support device includes a judgement part, a determination part, and an acquisition part. The judgement part judges a state of a test object on the basis of secular change of a level of a tumor marker. The determination part determines the level of the comparable tumor marker from among the levels of the plurality of tumor marker, which are acquired with time, depending on the state of the test object. The acquisition part acquires a medical image corresponding to the level of the comparable tumor marker.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The embodiments disclosed in the present specification and the drawings include an image interpretation support device and an image interpretation support Operation of the device It concerns the method. [Background technology]

[0002] In recent years, regular testing using tumor markers has become widely used as a means of checking the progression of cancer in cancer patients. For example, blood tests using microRNA (ribonucleic acid) as a tumor marker (such as breast cancer marker tests) are known to be able to detect cancer early. Tests using such tumor markers are useful for finding out whether cancer has recurred, the progression of the disease, and the presence of cancer that has not been completely removed by surgery or is too small to be seen by diagnostic imaging.

[0003] For example, after surgical removal of a cancer with a high tumor marker level, the tumor marker level often decreases and improves. On the other hand, if the cancer recurs, the tumor marker level increases again, so tumor marker testing may be used for postoperative follow-up.

[0004] Here, in tests using tumor markers, it is difficult to identify the affected area with a single type of marker, and the affected area is identified by a combination of multiple types. Also, since the tumor marker value itself does not accurately reflect the movement of cancer, it is difficult to understand the state of cancer from the tumor marker value alone. For example, in tests using tumor markers, there are cases where the tumor marker value increases even when there is no cancer (false positive), and cases where the tumor marker value shows a low value even when the cancer is progressing (false negative).

[0005] Thus, since the presence or absence of cancer and the progression of cancer cannot be determined by the value of tumor markers alone, generally, in addition to tests using tumor markers, tests using medical images are performed, and diagnosis is made based on a combination of the medical images. Therefore, in order to make diagnosis efficiently, cooperation between blood tests, medical information viewers, medical image diagnostic devices, etc. is required. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] JP 2017-188000 A Summary of the Invention [Problem to be solved by the invention]

[0007] One of the problems to be solved by the embodiments disclosed in this specification and the drawings is to improve the quality of the inspection. However, the problems to be solved by the embodiments disclosed in this specification and the drawings 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]

[0008] An image interpretation support device according to an embodiment includes a judging unit, a deciding unit, and an acquiring unit. The judging unit judges a state of a subject based on a change in a tumor marker value over time. The deciding unit decides a tumor marker value to be compared from among a plurality of tumor marker values ​​acquired over time according to the state of the subject. The acquiring unit acquires a medical image corresponding to the tumor marker value to be compared. [Brief description of the drawings]

[0009] [Figure 1] FIG. 1 is a block diagram showing an example of the configuration of an image reading apparatus according to the first embodiment. [Diagram 2] FIG. 2 is a diagram for explaining an example of a workflow of an examination using a tumor marker. [Diagram 3] FIG. 3 is a diagram for explaining an example of processing of the image reading apparatus according to the first embodiment. [Figure 4] FIG. 4 is a diagram for explaining an example of a process related to image selection by the image reading apparatus according to the first embodiment. [Diagram 5]FIG. 5 is a diagram for explaining an example of a process by the decision function according to the first modification. [Figure 6] FIG. 6 is a diagram illustrating an example of a process performed by a control function according to the second modification. [Figure 7] FIG. 7 is a diagram for explaining an example of a process performed by a control function according to the third modification. [Figure 8] FIG. 8 is a flowchart showing a procedure of processing by the image reading apparatus according to the first embodiment. [Figure 9] FIG. 9 is a diagram for explaining an example of processing of the image reading apparatus according to the second embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Hereinafter, the embodiments of the image reading support device and image reading support method will be described in detail with reference to the drawings. Note that in the following embodiments, the image reading support device of the present application will be described as an example in which it is applied to an image reading device, but the image reading support device and image reading support method according to the present application are not limited to the following embodiments. In addition, the embodiments can be combined with other embodiments or conventional techniques as long as no inconsistency occurs in the processing content.

[0011] (First embodiment) An example of the configuration of an image reading device according to the first embodiment will be described. Fig. 1 is a block diagram showing an example of the configuration of an image reading device 5 according to the first embodiment. The image reading device 5 is connected to an in-vitro diagnostic device 1, an electronic medical record system 2, a PACS (Picture Archiving and Communication Systems) 3, and a medical image diagnostic device 4 via a network. Note that other systems such as an HIS (Hospital Information System) and a RIS (Radiology Information System) may also be included in the network, and these systems may be connected to the image reading device 5.

[0012] The in-vitro diagnostic apparatus 1 performs various tests on samples such as blood and tissue collected from a subject. For example, the in-vitro diagnostic apparatus 1 performs a blood test using microRNA as a tumor marker and obtains the tumor marker value of each tumor marker. The in-vitro diagnostic apparatus 1 then transmits the test results (e.g., tumor marker values, etc.) to each device on the network.

[0013] The electronic medical record system 2 stores various medical data related to the medical records of subjects and patient information. Specifically, the electronic medical record system 2 generates medical data related to subjects or acquires the medical data from other devices via a network, and stores the medical data in a memory circuit within the system. For example, the electronic medical record system 2 is realized by a computer device such as a server or a workstation.

[0014] The PACS 3 receives, stores, and manages medical image data collected by the medical image diagnostic device 4 via a network. For example, the PACS 3 stores and manages CT image data, ultrasound image data, MRI image data, and the like collected from the same subject.

[0015] The medical image diagnostic device 4 captures an image of a subject to generate medical image data. Then, the medical image diagnostic device 4 transmits the generated medical image data to various devices on the network. For example, the medical image diagnostic device 4 is an X-ray diagnostic device, an X-ray CT (Computed Tomography) device, an MRI (Magnetic Resonance Imaging) device, an ultrasound diagnostic device, a SPECT (Single Photon Emission Computed Tomography) device, a PET (Positron Emission computed Tomography) device, etc.

[0016] The image reading device 5 displays medical images acquired via a network. An operator, such as an image reading doctor, who operates the image reading device 5 performs image reading on the medical images displayed on the display of the image reading device 5. For example, as shown in Fig. 1, the image reading device 5 has a communication interface 51, an input interface 52, a display 53, a storage circuitry 54, and a processing circuitry 55. The image reading device 5 is connected to each device on the network via the network so as to be able to communicate with each device on the network.

[0017] The communication interface 51 is connected to the processing circuit 55, and controls communication between each device on the network. Specifically, the communication interface 51 receives various information from each device, and outputs the received information to the processing circuit 55. For example, the communication interface 51 is realized by a network card, a network adapter, a NIC (Network Interface Controller), or the like.

[0018] The input interface 52 is connected to the processing circuit 55 and accepts various instructions and information input operations from an operator. Specifically, the input interface 52 converts the input operation accepted from the operator into an electric signal and outputs it to the processing circuit 55. For example, the input interface 52 is realized by a trackball, a switch button, a mouse, a keyboard, a touch pad that performs an input operation by touching the operation surface, a touch screen in which a display screen and a touch pad are integrated, a non-contact input circuit using an optical sensor, and a voice input circuit. Note that in this specification, the input interface 52 is not limited to only those that have physical operation parts such as a mouse and a keyboard. For example, an electric signal processing circuit that receives an electric signal corresponding to an input operation from an external input device provided separately from the device and outputs the electric signal to the processing circuit is also included as an example of the input interface 52.

[0019] The display 53 is connected to the processing circuit 55 and displays various information and images. Specifically, the display 53 converts the information and image data sent from the processing circuit 55 into an electric signal for display and outputs it. For example, the display 53 is realized by a liquid crystal display, a CRT (Cathode Ray Tube) display, an organic EL (Electro Luminescence) display, a plasma display, a touch panel, or the like.

[0020] The memory circuitry 54 is connected to the processing circuitry 55 and stores various data. For example, the memory circuitry 54 stores various data received from each device arranged on a network (not shown) and the processing result of the image reading device 5. The memory circuitry 54 also stores various programs that the processing circuitry 55 reads and executes to realize various functions. As shown in FIG. 1, the memory circuitry 54 also stores a judgment condition 541 and corresponding information 542. The judgment condition 541 and the corresponding information 542 will be described in detail later. For example, the memory circuitry 54 is realized by a semiconductor memory element such as a random access memory (RAM) or a flash memory, a hard disk, an optical disk, or the like.

[0021] The processing circuitry 55 controls the operation of the image reading device 5 in response to an input operation received from an operator via the input interface 52. Specifically, as shown in FIG. 1, the processing circuitry 55 controls the operation of the image reading device 5 by executing a control function 551, a judgment function 552, a decision function 553, an acquisition function 554, and a generation function 555. Here, the control function 551 is an example of a display control unit. Also, the judgment function 552 is an example of a judgment unit. Also, the decision function 553 is an example of a decision unit. The acquisition function 554 is an example of an acquisition unit. For example, the processing circuitry 55 is realized by a processor.

[0022] The control function 551 controls the execution of processes according to various requests input via the input interface 52. For example, the control function 551 controls the transmission and reception of various information via the communication interface 51, the storage of information in the memory circuit 54, and the display of various information on the display 53. The control function 551 controls the display of the display information generated by the generation function 555, which will be described in detail later.

[0023] The judgment function 552 judges the state of the subject based on the change over time of the tumor marker. The decision function 553 decides the value of a tumor marker to be compared from among the values ​​of a plurality of tumor markers acquired over time according to the state of the subject. The acquisition function 554 acquires a medical image corresponding to the value of the tumor marker to be compared. The processing of the judgment function 552, decision function 553, and acquisition function 554 will be described in detail later.

[0024] The generating function 555 generates various display information. Specifically, the generating function 555 generates display information for supporting interpretation. For example, the generating function 555 generates information showing changes in tumor markers over time, various medical images, and the like. To give one example, the generating function 555 generates a graph showing tumor marker values ​​for each date on which a blood test using a tumor marker was performed. The generating function 555 also generates medical images of various parts of the subject by performing various image processing on medical image data acquired via a network.

[0025] The above describes the overall configuration of the image reading device 5. With this configuration, the image reading device 5 improves the quality of examinations. Specifically, the image reading device 5 automatically searches for and acquires medical images suitable for comparative image reading, thereby reducing the workflow of image selection work and improving the quality of examinations.

[0026] For example, when a tumor marker test is performed for follow-up observation, it is necessary to select medical images for comparative reading based on the tumor marker values ​​of the current test and the tumor marker values ​​of previous tests, and the workflow for selecting images suitable for comparative reading is lengthy and time-consuming. Therefore, if there is not enough time to complete the work, sufficient image selection may not be performed, which may result in a decline in the quality of the test.

[0027] Fig. 2 is a diagram for explaining an example of a workflow of an examination using a tumor marker, in which Fig. 2 shows an example of a workflow of an examination using a tumor marker in follow-up observation after cancer treatment.

[0028] For example, the flow of cancer treatment is as follows: first, a test subject undergoes a medical examination and diagnosis, as shown in Figure 2. If a patient is diagnosed with cancer, treatment is then administered and the patient is monitored. If recurrence or metastasis occurs, treatment will be administered again.

[0029] In this embodiment, the quality of the examination using a tumor marker is improved in the above-mentioned follow-up. For example, in the examination using a tumor marker in the follow-up after cancer treatment shown in Fig. 2, a tumor marker examination using various tumor markers is performed. In this examination, for example, the effect of chemotherapy or radiation therapy is confirmed, and the progress of cancer is confirmed by periodically measuring tumor markers.

[0030] As mentioned above, in tumor marker tests, medical images are collected because a diagnosis cannot be made based on tumor marker values ​​alone. For example, for follow-up observation, ultrasound images are collected using an ultrasound diagnostic device to examine the size of the cancer, the location of blood vessels, and the presence or absence of ascites or nodules in the liver. In addition, for detailed examinations, such as when abnormalities are found in tumor markers, CT images and MR images are collected using an X-ray CT device or an MRI device to examine the nature, distribution, and metastasis state of the cancer.

[0031] An operator, such as a radiologist, who operates the image reading device 5, compares the medical images collected by the various medical image diagnostic devices described above with past images, and makes a diagnosis by combining the tumor marker values ​​and the image reading results. In comparative image reading of medical images, as shown in FIG. 2, the radiologist first (1) checks the current marker value, and then (2) checks the past marker values ​​and considers their progress. From the results, the radiologist (3) determines a tumor marker value to be compared (the best time for comparison) from among the past tumor marker values, and (4) determines a medical image that corresponds to the determined tumor marker value to be compared. The radiologist then performs comparative image reading of the determined medical image with the medical image collected this time.

[0032] Thus, in image interpretation accompanying an examination using a tumor marker in follow-up observation, it is necessary to select a medical image to be compared based on the tumor marker value of the previous examination, and the image interpretation physician will follow the steps (1) to (4) above. Therefore, it takes time to search for a medical image suitable for comparison. Therefore, when there is no time to search for images and it is difficult to consider an image suitable for comparison, a medical image collected during the previous examination may be selected as the image to be compared.

[0033] Therefore, the image reading device 5 according to the first embodiment automatically searches and acquires medical images suitable for comparative image reading, thereby reducing the workflow of image selection work and improving the quality of examination. Details of the processing by the image reading device 5 will be described below.

[0034] The control function 551 acquires the tumor marker values ​​of the subject in response to an operation via the input interface 52. Specifically, the control function 551 acquires the test results of the tumor marker tests that the subject to be interpreted has previously undergone in response to an operation via the input interface 52. For example, the control function 551 acquires the past tumor marker values ​​and the tumor marker values ​​at the time of the subject to be interpreted for all tumor markers that have been tested for the subject. The control function 551 may acquire the tumor marker values ​​directly from the in-vitro diagnostic apparatus 1 via the network, or may acquire the tumor marker values ​​from the electronic medical record system 2.

[0035] The determination function 552 determines the state of the subject based on the change over time of the tumor marker value. Specifically, the determination function 552 determines the state of the subject at the time of determination based on the change in the tumor marker value from a time point prior to the time of determination to the time of determination for which the state of the subject is to be determined. For example, the determination function 552 determines the state of the subject based on the change in the tumor marker value at the time of interpretation for past tumor marker values.

[0036] Here, the judgment function 552 judges the state of the subject based on the judgment conditions 541 stored in the memory circuitry 54. The judgment conditions 541 include information for judging the state of the subject for each type of tumor marker. Specifically, the judgment conditions 541 include a threshold value for each tumor marker for suggesting the presence of cancer.

[0037] In the test using a tumor marker, various tumor markers are used according to the type of cancer. Here, examples of tumor markers used in the tumor marker test include "AFP", "PIVKA-II", "CA-125", "CA15-3", "CEA", and "NCC-ST-439". In the tumor marker test, various tumor markers are used according to the type of cancer to be tested, such as hepatocellular carcinoma, breast cancer, esophageal cancer, lung cancer, biliary tract cancer, prostate cancer, neuroblastoma, medullary thyroid cancer, gastric cancer, pancreatic cancer, colon cancer, cervical cancer, uterine body cancer, and ovarian cancer.

[0038] The judgment condition 541 includes a threshold value for suggesting the presence of cancer for each type of tumor marker described above. For example, the judgment function 552 judges the subject's condition to be "worsened" when the tumor marker value at the time of the image interpretation increases from the past tumor marker value and exceeds the above threshold value.

[0039] Furthermore, the determination function 552 determines the degree of "worsening" based on the degree of increase in the tumor marker value. For example, when the increase from the past (previous) tumor marker value exceeds the threshold, the determination function 552 determines the subject's condition as "rapid deterioration." On the other hand, when the increase from the past (previous) tumor marker value does not exceed the threshold, the determination function 552 determines the subject's condition as "tending to worsening." The threshold for comparing the increased tumor marker value is set appropriately for each type of tumor marker, and is stored in the memory circuitry 54 as the determination condition 541.

[0040] Similarly, the determination function 552 determines the subject's condition as "recovery" when the tumor marker value at the time of the image interpretation falls from the past tumor marker value and falls below the threshold value. Furthermore, the determination function 552 determines the degree of "recovery" based on the degree of fall in the tumor marker value. For example, the determination function 552 determines the subject's condition as "rapid recovery" when the value that has fallen from the past (previous) tumor marker value exceeds the threshold value. On the other hand, when the value that has fallen from the past (previous) tumor marker value does not exceed the threshold value, the determination function 552 determines the subject's condition as "tending to recovery." The threshold value to be compared with the fallen value of the tumor marker value is appropriately set for each type of tumor marker and stored in the memory circuitry 54 as the determination condition 541.

[0041] The determination function 553 determines a tumor marker value to be compared from among a plurality of tumor marker values ​​acquired over time, depending on the state of the subject. Specifically, the determination function 553 determines a tumor marker value to be compared with the tumor marker at the time to be determined, from among a plurality of tumor marker values ​​acquired at a time prior to the time to be determined, depending on the state of the subject at the time to be determined. For example, the determination function 553 determines a past tumor marker value to be compared with the time to be interpreted, depending on the state of the subject determined by the determination function 552.

[0042] Here, the determination function 553 determines the value of the tumor marker to be compared based on the correspondence information 542 stored in the memory circuitry 54. The correspondence information 542 includes information in which the state of the tumor marker value to be compared is associated with each state of the subject. For example, the correspondence information 542 includes information in which the state of the subject "worsening" is associated with "stable", which indicates a low value in the transition of the past tumor marker value. When based on such information, when the state of the subject is judged to be "worsening", the determination function 553 determines the tumor marker value indicating the low value from among the past tumor marker values ​​as the comparison target. Note that the correspondence information 542 can also include, in addition to the above information, information in which the state of the tumor marker value is associated with the state of the subject "sudden deterioration" or "tending to worsening", for example.

[0043] Furthermore, the correspondence information 542 includes information in which a "high value" indicating a high value after treatment in the transition of past tumor marker values ​​is associated with the subject's condition of "recovery." When based on such information, when the subject's condition is judged to be "recovered," the determination function 553 determines, as a comparison target, a tumor marker value indicating a high value from among the past tumor marker values. Note that, in addition to the above information, the correspondence information 542 can also include information in which, for example, a tumor marker value state is associated with a subject's condition such as "rapid recovery" or "tending to recovery."

[0044] The determination function 553 determines a tumor marker value to be compared with the time point to be interpreted, based on the above-mentioned correspondence information 542. That is, the determination function 553 determines a tumor marker value to be compared using the correspondence information 542, thereby determining a past time point to be compared with the time point to be interpreted.

[0045] The acquisition function 554 acquires a medical image corresponding to the tumor marker value of the comparison target determined by the determination function 553. Specifically, the acquisition function 554 acquires a medical image corresponding to the time point at which the tumor marker value of the comparison target was acquired. The acquisition function 554 also acquires a medical image corresponding to the time point that is the subject of interpretation. Here, the acquisition function 554 can acquire the medical image corresponding to the determined tumor marker value from the PACS 3 or the medical image diagnostic device 4.

[0046] For example, the acquisition function 554 acquires medical images acquired on the same day as the day the tumor marker value at the time of the image interpretation was acquired (or within a predetermined period from the day the tumor marker value was acquired). The acquisition function 554 also acquires medical images acquired on the same day as the day the tumor marker value determined by the determination function 553 was acquired (or within a predetermined period from the day the tumor marker value was acquired).

[0047] The generating function 555 generates various display information for displaying the medical image acquired by the acquiring function 554 on the display 53. Specifically, the generating function 555 generates various information for comparative interpretation between the medical image at the time point to be interpreted and the medical image corresponding to the time point when the tumor marker value determined by the determining function 553 was acquired.

[0048] The control function 551 causes the display 53 to display the medical images acquired by the acquisition function 554 and the display information generated by the generation function 555. An operator such as an image interpretation doctor performs image interpretation on the medical images displayed by the display 53. As described above, the image interpretation device 5 can automatically search for, acquire, and display medical images suitable for comparison with the medical image at the time of the image interpretation, thereby reducing the workflow of image selection work and enabling improvement in the quality of examinations.

[0049] An example of the processing by the image reading device 5 according to this embodiment will be described below. Fig. 3 is a diagram for explaining an example of the processing by the image reading device 5 according to the first embodiment. Here, Fig. 3 shows an example in which a tumor marker value increases during follow-up.

[0050] For example, the flow of cancer treatment is as follows: first, a patient undergoes a medical examination and diagnosis, as shown in Figure 3. If a patient is diagnosed with cancer, treatment is then administered and the patient is monitored. If recurrence or metastasis occurs, treatment will be administered again.

[0051] Here, in a follow-up observation, it is assumed that in a tumor marker test using a tumor marker, the tumor marker value has increased from the previous test value and exceeded the threshold value.

[0052] In such a case, since the tumor marker value result indicates high urgency, for example, collection of CT images by CT scan is performed and interpretation is performed. Then, diagnosis is made by integrating the tumor marker value and the interpretation result. In the first embodiment, medical images are automatically selected in the interpretation in the above-mentioned process.

[0053] That is, as shown in FIG. 3, image reading device 5 first (1) judges the current marker value as "the tumor marker value exceeds the threshold value." Then, image reading device 5 (2) judges the subject's condition as "worsening" because a comparison with past marker values ​​shows an "increase" from a "low value" to a "high value." Furthermore, image reading device 5 determines the optimum marker value for comparison (the optimum time for comparison) based on the judgment result and correspondence information 542. That is, image reading device 5 (3) determines the (post-treatment) tumor marker value that showed "stable" as a comparison target for the tumor marker value that showed "worsening."

[0054] Then, the image reading device 5 (4) determines and acquires a medical image corresponding to the tumor marker value indicating "stable." For example, the image reading device 5 narrows down the target examination (date and time) based on the result of the tumor marker value indicating "stable," and determines that the image is one in which the patient is stable based on the diagnosis result and examination information of the target examination, and determines the image. If there is no target image, the image reading device 5 performs image reconstruction, clinical analysis again, transition to another examination, etc. Then, the image reading device 5 acquires a medical image, and (5) displays the acquired medical image and the medical image collected this time. This allows the image reading doctor to perform comparative interpretation and, for example, make a judgment such as "there is no recurrence, but metastasis to other tissues has been confirmed" based on the difference result of the displayed medical images.

[0055] In this way, the image reading device 5 automatically performs the above-mentioned steps (1) to (4). The following describes the detailed processing of the automatic procedure. FIG. 4 is a diagram for explaining an example of processing related to image selection by the image reading device 5 according to the first embodiment. Here, FIG. 4 shows the acquisition status of tumor markers and medical images, and a graph showing the transition of tumor marker values. Specifically, FIG. 4 shows the acquisition status of "tumor marker i" and "tumor marker ii" from "2019 / 1 / 1" to "2020 / 7 / 1", and the acquisition status of "ultrasound image (ultrasound in the figure)" and "CT image (CT in the figure)" from "2019 / 1 / 1" to "2020 / 7 / 1" in the upper part of the figure.

[0056] In addition, in the lower part of Figure 4, a graph showing the values ​​of "tumor marker i" and "tumor marker ii" from "2019 / 1 / 1" to "2020 / 7 / 1" is shown. Here, curve L1 in Figure 4 shows the graph of "tumor marker i", and curve L2 shows the graph of "tumor marker ii".

[0057] For example, in reading after an examination using a tumor marker on "2020 / 7 / 1," the control function 551 obtains the tumor marker values ​​of "tumor marker i" and "tumor marker ii" on "2020 / 7 / 1" as well as the previously obtained values ​​of each tumor marker.

[0058] The determination function 552 determines the state of the subject on "2020 / 7 / 1" based on the tumor marker values ​​of "tumor marker i" and "tumor marker II" on "2020 / 7 / 1" and the past values ​​of each tumor marker. That is, the determination function 552 determines the state of the subject's cancer based on the transition state of "tumor marker i" and the transition state of "tumor marker II."

[0059] For example, the determination function 552 determines that the value of "tumor marker i" has risen to the same level as the threshold value of "tumor marker i" as of "2020 / 4 / 1" and has maintained that value on "2020 / 7 / 1" based on the transition of the value of "tumor marker i" shown on curve L1 in Fig. 4. The determination function 552 also determines that the value of "tumor marker II" on "2020 / 7 / 1" has risen from the value on "2020 / 4 / 1" and indicates a high value that exceeds the threshold value of "tumor marker II" based on the transition of the value of "tumor marker II" shown on curve L2 in Fig. 4.

[0060] Then, the judgment function 552 compares the degree of increase in each tumor marker value (for example, the change in the value of tumor marker II from 4 / 1 to 7 / 1) with a threshold value and judges that the subject's cancer state is "worsening."

[0061] Since the judgment result by the judgment function 552 is "worsening", the decision function 553 decides on the tumor marker value indicating "stable" as the tumor marker value to be compared. For example, the decision function 553 decides on the value of "2019 / 10 / 1" indicating low values ​​of "tumor marker i" and "tumor marker ii" based on the transition of the value of "tumor marker i" (curve L1) and the transition of the value of "tumor marker ii" (curve L2) in Fig. 4 as the value to be compared.

[0062] Here, in the transition of the values ​​of "tumor marker i" and "tumor marker ii" shown in FIG. 4, both marker values ​​are below the threshold even on "2020 / 1 / 1". As shown in FIG. 4, when there are tumor marker values ​​that can be compared at multiple time points, the determination function 553 can determine the tumor marker value to be compared based on arbitrarily set conditions. For example, the determination function 553 can compare the tumor marker values ​​and determine the tumor marker value to be compared based on the comparison result. As an example, the determination function 553 determines the tumor marker value (time point) showing the lowest or highest value as the comparison target.

[0063] Furthermore, for example, the determination function 553 can determine a tumor marker value to be compared based on the date on which the tumor marker value was acquired. As one example, the determination function 553 can determine, as a comparison target, a tumor marker value of a date closest to "2020 / 7 / 1" that is the subject of image interpretation, or a date furthest from "2020 / 7 / 1" that is the subject of image interpretation, among multiple time points.

[0064] Also, for example, the determination function 553 can determine a tumor marker value to be compared based on the acquired medical image. As an example, the determination function 553 can determine, as a comparison target, a tumor marker value at a time point when a medical image of the same type as that acquired at the time point to be interpreted was acquired among a plurality of time points. For example, as shown in FIG. 4, the determination function 553 determines, as a comparison target, a tumor marker value on "2019 / 10 / 1" on which a CT image identical to that acquired on "2020 / 7 / 1" to be interpreted was acquired among "2019 / 10 / 1" and "2020 / 1 / 1" on which the tumor marker value is stable.

[0065] The acquisition function 554 acquires medical images at the time determined by the determination function 553. Specifically, the acquisition function 554 acquires medical images of the same type as the medical images acquired at the time of interpretation from among the medical images acquired at the time determined by the determination function 553. For example, the acquisition function 554 acquires CT images acquired at a time corresponding to "2019 / 10 / 1". Also, the acquisition function 554 acquires CT images corresponding to the time "2020 / 7 / 1" that is the subject of interpretation.

[0066] The control function 551 displays the medical image acquired by the acquisition function 554 on the display 53. For example, the control function 551 displays a CT image acquired at a time corresponding to "2019 / 10 / 1" and a CT image corresponding to "2020 / 7 / 1" on the display 53. This allows the image interpretation doctor to compare the CT image of "2020 / 7 / 1" suggesting that the condition of the subject has deteriorated and the CT image of "2019 / 10 / 1" in which the condition of the subject is stable, without taking the time to select an image. As a result, the quality of the examination is improved. In the example shown in FIG. 4, the case where two types of tumor markers (tumor marker i and tumor marker ii) are used is described, but the embodiment is not limited to this. For example, an image for comparative reading may be selected from the examination results using one type or three or more types of tumor markers.

[0067] Here, the judgment function 552 judges the condition of each part of the subject based on the type of tumor marker, the determination function 553 determines the value of the tumor marker to be compared for each type of tumor marker, and the acquisition function 554 acquires a medical image corresponding to the value of the tumor marker to be compared for each part of the subject based on the type of tumor marker.

[0068] In tests using tumor markers, tumor markers targeting various sites can be used in one test. That is, tests for tumor markers other than the above-mentioned "tumor marker I" and "tumor marker II" can be performed. In addition, the same type of tumor marker suggests the presence of cancer in different sites. In other words, the same type of tumor marker is used in tests for cancer in different sites.

[0069] Therefore, the determination function 552 extracts all target sites according to the type of tumor marker used. The acquisition function 554 acquires medical images of the sites extracted by the determination function 552 for the time points to be interpreted and the time points determined by the determination function 553.

[0070] Here, when there is no medical image of the extracted part, the acquisition function 554 can generate a new medical image by various image processing. When a CT image or the like is acquired in association with an examination using a tumor marker, medical image data of a wide range (e.g., the whole body) of the subject is often collected. Therefore, the acquisition function 554 reconstructs a medical image of the extracted part, for example, using medical image data collected over a wide range. Also, for example, the acquisition function 554 acquires medical images of each part by applying a clinical analysis app for each part to the medical image data collected from the subject.

[0071] Furthermore, when medical image data of a wide range has not been collected and medical image data including the extracted region has not been saved, the acquisition function 554 can also control the control function 551 to display information prompting the collection of medical image data of the extracted region on the display 53. In other words, the acquisition function 554 can also control to collect medical images of the region from the subject.

[0072] As described above, the image reading device 5 according to this embodiment can select and display an appropriate medical image from past medical images according to the condition of the subject in reading a medical image accompanying an examination using a tumor marker. Here, the image reading device 5 can execute various processes in addition to the above-mentioned processes. Below, modified examples of the image reading device 5 will be described.

[0073] (Variation 1) In the above-described embodiment, when there are tumor marker values ​​that can be compared at multiple points in time, the tumor marker values ​​to be compared are determined based on arbitrarily set conditions (conditions based on dates, conditions based on acquired medical images). The image interpretation device 5 can further determine the tumor marker values ​​to be compared based on the characteristics of the medical images.

[0074] In such a case, the determination function 553 extracts multiple candidates for the tumor marker value to be compared from among the multiple tumor marker values ​​acquired over time based on the tumor marker value, and determines the tumor marker value to be compared from among the multiple candidates based on the characteristics of each medical image corresponding to the multiple candidates. Specifically, the determination function 553 extracts multiple candidates based on the tumor marker value, and determines the candidate associated with the medical image having characteristics in line with the determination result by the determination function 552 from among the multiple extracted candidates as the tumor marker value to be compared.

[0075] Fig. 5 is a diagram for explaining an example of processing by the determination function 553 according to the modified example 1. Here, Fig. 5 shows a graph in which the vertical axis indicates tumor marker values ​​and the horizontal axis indicates time. Fig. 5 also shows processing by the determination function 553 when performing image interpretation at time t4.

[0076] For example, as shown in Fig. 5, the tumor marker value at time t4 is in a state that greatly exceeds the threshold value. Therefore, the judgment function 552 judges that the condition of the subject at time t4 is in a "worsened" state. In response to this judgment result, the decision function 553 first extracts times t1, t2, and t3, at which the tumor marker value is low, as candidates for comparison in order to determine the time point of the stable state.

[0077] Then, the determination function 553 acquires a medical image I1 corresponding to time t1, a medical image I2 corresponding to time t2, and a medical image I3 corresponding to time t3, compares the medical images I1 to I3, and determines the image that is considered to have been collected under a more stable condition as the comparison target. For example, the determination function 553 extracts tumors in the medical images I1 to I3, and measures the size of the extracted tumors. Then, the determination function 553 determines the medical image with the smallest measured tumor size as the one that was collected under a more stable condition as the comparison target for time t4.

[0078] Also, for example, the determination function 553 extracts multiple candidates for a comparison tumor marker value from multiple tumor marker values ​​acquired over time based on the tumor marker value, and determines a comparison tumor marker value from the multiple candidates based on the similarity between each medical image corresponding to the multiple candidates and the medical image at the time of determination when the subject's condition was determined.

[0079] As an example, the determination function 553 calculates the similarity between the medical image I4 corresponding to the time t4 in Fig. 5 and the medical image I1, the similarity between the medical image I4 and the medical image I2, and the similarity between the medical image I4 and the medical image I3, and determines the time point of the medical image with the lowest calculated similarity as the comparison target. In other words, the determination function 553 determines the time point at which the medical image with the lowest similarity to the medical image I4 collected at the time t4 that suggested the subject's condition was "worsening" to be collected as the more stable state.

[0080] In the above example, a case was described in which the subject's condition "worsens" and a point in time when the subject's condition is stable is determined as a point of comparison. However, the determination function 553 can also perform similar processing in the case in which the subject's condition "recovers" and a point in time when the subject's condition is worsened is determined as a point of comparison.

[0081] (Variation 2) In the above embodiment, the control function 551 has been described as displaying a medical image at a time point to be interpreted and a medical image at a time point determined as a comparison target on the display 53. However, the control function 551 can also display various other information on the display 53.

[0082] Fig. 6 is a diagram showing an example of processing by the control function 551 according to Modification 2. For example, the control function 551 can display a medical image together with a graph showing the tumor marker value on the vertical axis and the date on the horizontal axis, as shown in Fig. 6. In such a case, the generation function 555 generates the graph L4 shown in Fig. 6 based on the multiple tumor marker values ​​acquired by the control function 551 (the tumor marker value at the time of the image interpretation and past tumor marker values).

[0083] Then, the control function 551 causes the display 53 to display display information in which the medical images are associated with the graph L4 generated by the generation function 555. For example, the control function 551 causes the display 53 to display, in addition to the medical image I7 at the time point that is the subject of interpretation, a medical image I6 at the time point that is the subject of comparison (5 / 1) and a medical image I5 at the time point that is the subject of C treatment (3 / 1) in association with the graph.

[0084] Furthermore, the control function 551 can further display various information useful for diagnosing the subject. In such a case, the acquisition function 554 acquires information useful for diagnosing the subject. Specifically, the acquisition function 554 acquires various information useful for diagnosis from the electronic medical record system 2 via the network. For example, the acquisition function 554 acquires the subject's treatment history, the doctor's findings on the subject, and the like as information useful for diagnosis.

[0085] The control function 551 can display information showing the change in tumor marker over time, the treatment history of the subject, and the findings of the subject, in association with a medical image corresponding to the value of the tumor marker to be compared and a medical image at the time of the subject's condition being determined. For example, as shown in FIG. 6, the control function 551 can display display information that allows the relationship between each treatment and the tumor marker value to be understood at a glance by displaying the time when treatment A was performed and the time when treatment B was performed in association with a graph. Furthermore, the control function 551 can display the doctor's findings at that time in association with the information, as shown in "Recovery" on "5 / 1" in FIG. 6.

[0086] (Variation 3) In the above-described embodiment, a case has been described in which a previous medical image of the same specimen is acquired as a medical image to be compared. However, the image reading device 5 can display information of a different specimen as a comparison object. Specifically, the image reading device 5 can display, as comparative information, information of a specimen whose tumor marker value changes over time similarly to that of the specimen to be read and whose diagnosis has been confirmed by a doctor.

[0087] In such a case, the control function 551 extracts, from the subject information of a subject different from the subject and for which a diagnosis has been confirmed, subject information in which the change over time in the tumor marker is similar to the change over time in the tumor marker of the subject, and controls the display 53 to display the extracted subject information.

[0088] Fig. 7 is a diagram for explaining an example of processing by the control function 551 according to Modification 3. For example, as shown in Fig. 7, the control function 551 compares the transitions of the tumor marker value of patient A with the transitions of the tumor marker value stored in the medical network database 6. Then, the control function 551 acquires from the medical network database 6 medical information of patient X that shows the same transitions of the tumor marker value as the transitions of the tumor marker value of patient A.

[0089] Then, the control function 551 displays the acquired medical information of patient X on the display 53 as information to be compared with that of patient A. The medical network database 6 is connected to the network of Fig. 1, and the control function 551 accesses the medical network database 6 via the network to compare the transitions of the tumor marker values ​​and acquire medical information.

[0090] Next, the procedure of the process by the image reading device 5 will be described. FIG. 8 is a flowchart showing the procedure of the process by the image reading device 5 according to the first embodiment. Here, step S101 and step S105 in FIG. 8 are realized by the processing circuitry 55 reading a program corresponding to the control function 551 from the storage circuitry 54 and executing it. Also, step S102 is realized by the processing circuitry 55 reading a program corresponding to the determination function 552 from the storage circuitry 54 and executing it. Also, step S103 is realized by the processing circuitry 55 reading a program corresponding to the decision function 553 from the storage circuitry 54 and executing it. Also, step S104 is realized by the processing circuitry 55 reading a program corresponding to the acquisition function 554 from the storage circuitry 54 and executing it.

[0091] 8, the processing circuitry 55 acquires a tumor marker value (step S101), and determines the state of the subject based on the change over time in the tumor marker value (step S102).Then, the processing circuitry 55 determines the tumor marker value to be compared (the time point to be compared) based on the state of the subject (step S103).

[0092] Thereafter, the processing circuitry 55 extracts medical images corresponding to the tumor marker values ​​to be compared (step S104), and displays the extracted medical images for comparison (step S105).

[0093] As described above, according to the first embodiment, the judgment function 552 judges the state of the subject based on the change over time in the tumor marker value. The decision function 553 decides a tumor marker value to be compared from among a plurality of tumor marker values ​​acquired over time according to the state of the subject. The acquisition function 554 acquires a medical image corresponding to the tumor marker value to be compared. Therefore, the image reading device 5 according to the first embodiment can automatically select and display an appropriate medical image according to the state of the subject, reducing the effort of an operator such as an image reading doctor and enabling the quality of the examination to be improved.

[0094] According to the first embodiment, the judgment function 552 judges the state of the subject at the time of the judgment based on the change in the tumor marker value from a time before the time of the judgment to the time of the judgment. The determination function 553 determines a comparison tumor marker value to be compared with the tumor marker at the time of the judgment from among a plurality of tumor marker values ​​acquired at a time before the time of the judgment, according to the state of the subject at the time of the judgment. The acquisition function 554 acquires a medical image corresponding to the time when the comparison tumor marker value was acquired. Therefore, the image reading device 5 according to the first embodiment makes it possible to automatically acquire an optimal past image when performing comparative image reading in follow-up observation.

[0095] Furthermore, according to the first embodiment, the judgment function 552 judges the condition of each part of the subject based on the type of tumor marker. The decision function 553 decides a tumor marker value to be compared for each type of tumor marker. The acquisition function 554 acquires a medical image corresponding to the tumor marker value to be compared for each part of the subject based on the type of tumor marker. Therefore, the image reading device 5 according to the first embodiment can automatically acquire appropriate medical images for each part targeted by the tumor marker used, making it possible to further improve the quality of the examination.

[0096] According to the first embodiment, the acquisition function 554 acquires a medical image of a region by executing a reconstruction process on medical image data collected from a subject. Therefore, the image interpretation device 5 according to the first embodiment makes it possible to generate and display an appropriate medical image.

[0097] According to the first embodiment, the acquisition function 554 acquires a medical image of a region by re-executing a clinical analysis application on medical image data collected from a subject. Therefore, the image reading device 5 according to the first embodiment makes it possible to generate a medical image suitable for a region.

[0098] According to the first embodiment, the acquisition function 554 acquires a medical image of a region by controlling to collect an image of the region from the subject. Therefore, the image reading device 5 according to the first embodiment makes it possible to prompt to newly collect a medical image of the target region even if there is no medical image of the target region.

[0099] Moreover, according to the first embodiment, the acquisition function 554 further acquires information that is effective for diagnosing the subject. Therefore, the image reading device 5 according to the first embodiment makes it possible to obtain information that contributes to diagnosis, in addition to medical images.

[0100] Furthermore, according to the first embodiment, the determination function 553 determines a tumor marker value to be compared from among a plurality of tumor marker values ​​acquired over time, based on the tumor marker value. Therefore, the image reading device 5 according to the first embodiment makes it possible to determine a comparison target based on the tumor marker value.

[0101] Furthermore, according to the first embodiment, the determination function 553 extracts multiple candidates for a tumor marker value to be compared from multiple tumor marker values ​​acquired over time based on the tumor marker value, and determines a tumor marker value to be compared from the multiple candidates based on the features of each medical image corresponding to the multiple candidates. Therefore, the image interpretation device 5 according to the first embodiment makes it possible to determine a more optimal time point from multiple time points showing similar tumor marker values.

[0102] According to the first embodiment, the determination function 553 determines a tumor marker value to be compared from among a plurality of tumor marker values ​​acquired over time, based on the tumor marker value and the type of the corresponding medical image. Therefore, the image reading device 5 according to the first embodiment makes it possible to acquire medical images of the same type as the comparison target.

[0103] Furthermore, according to the first embodiment, the determination function 553 extracts multiple candidates for a comparison target tumor marker value from multiple tumor marker values ​​acquired over time based on the tumor marker value, and determines a comparison target tumor marker value from the multiple candidates based on the similarity between each medical image corresponding to the multiple candidates and the medical image at the time of the determination target when the subject's condition was determined. Therefore, the image interpretation device 5 according to the first embodiment makes it possible to obtain a comparison target medical image based on the similarity of the images.

[0104] Furthermore, according to the first embodiment, the control function 551 controls so as to display a medical image corresponding to the tumor marker value to be compared and a medical image at the time of the subject's condition to be determined on the display 53. Therefore, the image interpretation device 5 according to the first embodiment makes it possible to automatically display the medical image to be compared.

[0105] Furthermore, according to the first embodiment, the control function 551 displays information indicating the time-dependent change of the tumor marker and information effective for diagnosing the subject, in association with a medical image corresponding to the tumor marker value to be compared and a medical image at the time of judgment when the subject's condition was judged. Therefore, the image interpretation device 5 according to the first embodiment can display various information in addition to medical images, making it possible to further improve the quality of examinations.

[0106] Moreover, according to the first embodiment, the control function 551 extracts subject information that is of a subject different from the subject and in which a time-dependent change in a tumor marker is similar to that of the subject from among subject information in which a diagnosis has been confirmed, and controls the display 53 to display the extracted subject information. Therefore, the image reading device 5 according to the first embodiment can display information on a subject in which a diagnosis has been confirmed in a similar state to that of the subject to be image-read, making it possible to improve the accuracy of the diagnosis.

[0107] Second embodiment In the above-mentioned first embodiment, an example in which the tumor marker level increases during follow-up has been described. In the second embodiment, an example in which the tumor marker level decreases during follow-up will be described.

[0108] Fig. 9 is a diagram for explaining an example of the processing of the image reading device 5 according to the second embodiment. Here, Fig. 9 shows an example in which the tumor marker value decreases and stabilizes during follow-up observation.

[0109] For example, the flow of cancer treatment is as follows: first, a test subject undergoes a medical examination and diagnosis, as shown in Figure 9. If a cancer is diagnosed, treatment is then administered and the patient is monitored. If recurrence or metastasis occurs, treatment will be administered again.

[0110] Here, in a follow-up observation, it is assumed that in a tumor marker test using a tumor marker, the value has decreased over the past several tests and fallen below the threshold value.

[0111] In such a case, for example, X-ray images are collected by mammography as follow-up observation based on the tumor marker value results, and interpretation is performed. Then, a diagnosis is made by integrating the tumor marker value and the interpretation result. In the second embodiment, medical images are automatically selected during interpretation in the above-mentioned process.

[0112] That is, as shown in FIG. 9, the judgment function 552 first (1) judges the current marker value as "the tumor marker value is below the threshold value". Then, the judgment function 552 (2) judges the subject's condition as "recovered" since a comparison with the past marker value shows a "stable decline" from a "high value" to a "low value (reference value)". Furthermore, the decision function 553 determines the optimum marker value for comparison (the optimum time for comparison) based on the judgment result and the correspondence information 542. That is, the decision function 553 (3) determines the (post-treatment) tumor marker value that showed a "high value" as a comparison target for the tumor marker value that showed "recovery".

[0113] Thereafter, the acquisition function 554 (4) determines and acquires a medical image corresponding to the tumor marker value that indicates a "high value." That is, the acquisition function 554 narrows down the target examination (date and time) based on the result of the tumor marker value that indicates a "high value," and determines that the image is one in which the patient is deteriorating based on the diagnosis result and examination information of the target examination, and determines the image. Here, if there is no target image, the acquisition function 554 executes image reconstruction, clinical analysis again, transition to another examination, etc. Then, the control function 551 acquires the medical image, and (5) displays the acquired medical image and the medical image collected this time. This allows the image interpretation doctor to perform comparative interpretation and, for example, make a judgment such as "there is no recurrence and no metastasis to other tissues" based on the difference result of the displayed medical images.

[0114] In this way, the image reading device 5 according to the second embodiment also automatically performs the above-mentioned steps (1) to (4). This enables the image reading device 5 to improve the quality of examinations using tumor markers for various cancers.

[0115] (Other embodiments) Although the first and second embodiments have been described above, the present invention may be embodied in various different forms other than the first and second embodiments described above.

[0116] In the above-described embodiment, the case where the image interpretation support device according to the present application is applied to the image interpretation device 5 has been described. However, the embodiment is not limited to this, and may be applied to, for example, any of the devices in the network shown in Fig. 1. In such a case, the processing circuit of the applied device executes processes similar to those of the control function 551, the determination function 552, the decision function 553, the acquisition function 554, and the generation function 555 described above.

[0117] In the image reading device 5 described in each embodiment, each processing function is stored in the storage circuitry 54 in the form of a program executable by a computer. The processing circuitry 55 is a processor that realizes a function corresponding to each program by reading the program from the storage circuitry 54 and executing it. In other words, the processing circuitry 55 in a state in which each program is read has a function corresponding to the read program. In the above-mentioned embodiments, the case where each processing function is realized by a single processing circuitry 55 has been shown, but the embodiment is not limited to this. For example, the processing circuitry 55 may be configured by combining multiple independent processors, and each processor may realize each processing function by executing each program. In addition, each processing function possessed by the processing circuitry 55 may be realized by being appropriately distributed or integrated into a single or multiple processing circuits.

[0118] The term "processor" used in the above description means a circuit such as a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), an Application Specific Integrated Circuit (ASIC), a programmable logic device (e.g., a Simple Programmable Logic Device (SPLD), a Complex Programmable Logic Device (CPLD), and a Field Programmable Gate Array (FPGA)). The processor realizes its function by reading and executing a program stored in the memory circuits 12 and 12a.

[0119] In the above-described embodiments, the storage circuitry 54 has been described as storing a program corresponding to each processing function. However, a configuration may be adopted in which a plurality of storage circuits are distributed and the processing circuitry 55 reads out the corresponding program from each storage circuit. Also, instead of storing the program in the storage circuitry, the program may be directly built into the circuitry of the processor. In this case, the processor realizes the function by reading and executing the program built into the circuitry.

[0120] Each component of each device according to the above-mentioned embodiment is a functional concept, and does not necessarily have to be physically configured as shown in the figure. In other words, the specific form of distribution and integration of each device is not limited to that shown in the figure, and all or a part of them can be functionally or physically distributed and integrated in any unit according to various loads, usage conditions, etc. Furthermore, each processing function performed by each device can be realized in whole or in any part by a CPU and a program analyzed and executed by the CPU, or can be realized as hardware using wired logic.

[0121] The image interpretation support method described in the above-mentioned embodiment can be realized by executing a processing program prepared in advance on a computer such as a personal computer or a workstation. This medical information processing program can be distributed via a network such as the Internet. The medical information processing program can also be recorded on a non-transitory recording medium readable by a computer such as a hard disk, a flexible disk (FD), a CD-ROM, an MO, or a DVD, and executed by being read from the recording medium by a computer.

[0122] According to at least one of the embodiments described above, the quality of the examination can be improved.

[0123] Although some embodiments have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, substitutions, modifications, and combinations of embodiments can be made without departing from the spirit of the invention. These embodiments and their modifications are included in the scope of the invention and its equivalents as described in the claims, as well as in the scope and spirit of the invention. [Explanation of symbols]

[0124] 5. Image Reading Device 551 Control Functions 552 Judgment function 553 Decision Function 554 Acquisition Function 555 Generation function

Claims

1. a determination unit for determining a state of the subject based on a change in the value of the tumor marker over time; A determination unit that determines a tumor marker value to be compared from among a plurality of tumor marker values ​​acquired over time in accordance with the condition of the subject; an acquisition unit for acquiring a medical image corresponding to the value of the tumor marker to be compared; An image reading support device comprising:

2. The determination unit determines a state of the subject at a time point to be determined based on a change in the value of the tumor marker from a time point prior to the time point to be determined, the determination unit determines, according to the state of the subject at the time to be determined, a comparison tumor marker value to be compared with the tumor marker at the time to be determined from among a plurality of tumor marker values ​​acquired at a time point prior to the time to be determined; The image interpretation support device according to claim 1 , wherein the acquisition unit acquires a medical image corresponding to a time point at which the value of the tumor marker to be compared was acquired.

3. The determination unit determines a condition of each site of the subject based on the type of the tumor marker, The determination unit determines the value of the tumor marker to be compared for each type of tumor marker, The image interpretation support device according to claim 1 , wherein the acquisition unit acquires a medical image corresponding to a value of the tumor marker to be compared for each part of the subject based on the type of the tumor marker.

4. The image interpretation support apparatus according to claim 3 , wherein the acquisition unit acquires a medical image of the region by executing a reconstruction process on medical image data collected from the subject.

5. The image interpretation support device according to claim 3 , wherein the acquisition unit acquires the medical image of the region by re-executing a clinical analysis on the medical image data collected from the subject.

6. The image interpretation support apparatus according to claim 3 , wherein the acquisition unit acquires a medical image of the region by controlling to collect an image of the region from the subject.

7. 7. The image interpretation support apparatus according to claim 1, wherein the acquisition unit further acquires information useful for diagnosing the subject.

8. The reading support device according to any one of claims 1 to 7, wherein the determination unit determines the value of the tumor marker to be compared from among the values ​​of the multiple tumor markers acquired over time based on the value of the tumor marker.

9. The image interpretation support device according to any one of claims 1 to 7, wherein the determination unit extracts multiple candidates for the value of the tumor marker to be compared from the multiple tumor marker values ​​acquired over time based on the value of the tumor marker, and determines the value of the tumor marker to be compared from the multiple candidates based on the characteristics of each medical image corresponding to the multiple candidates.

10. The reading support device according to any one of claims 1 to 7, wherein the determination unit determines the value of the tumor marker to be compared from among the multiple tumor marker values ​​acquired over time based on the value of the tumor marker and the type of the corresponding medical image.

11. The image interpretation support device according to any one of claims 1 to 7, wherein the determination unit extracts multiple candidates for the value of the tumor marker to be compared from the multiple tumor marker values ​​acquired over time based on the value of the tumor marker, and determines the value of the tumor marker to be compared from the multiple candidates based on the similarity between each medical image corresponding to the multiple candidates and a medical image at the time of determination at which the condition of the subject was determined.

12. The image interpretation support device according to any one of claims 1 to 11, further comprising a display control unit that controls the display unit to display a medical image corresponding to the value of the tumor marker to be compared and a medical image at the time of judgment at which the state of the subject is judged.

13. The image interpretation support device of claim 12, wherein the display control unit displays display information indicating the change in the tumor marker over time and information useful for diagnosing the subject, in association with a medical image corresponding to the value of the tumor marker to be compared and a medical image at the time of judgment when the condition of the subject was judged.

14. 14. The image interpretation support device according to claim 12, wherein the display control unit extracts subject information from subject information of a subject different from the subject and for which a diagnosis has been confirmed, the subject information having a change over time in a tumor marker similar to the change over time in the tumor marker of the subject, and controls the display unit to display the extracted subject information.

15. A method for operating an image interpretation support device for supporting image interpretation of medical images, comprising: The image interpretation support apparatus includes a determination unit, a decision unit, and an acquisition unit, a determination step in which the determination unit determines a state of the subject based on a change over time in the value of the tumor marker; a determination step in which the determination unit determines a tumor marker value to be compared from among a plurality of tumor marker values ​​acquired over time in accordance with a state of the subject; an acquisition step in which the acquisition unit acquires a medical image corresponding to the value of the tumor marker to be compared; A method for operating an image interpretation support device, comprising:

Images