JP6711675B2 - Interpretation support device - Google Patents

Description

The embodiment of the present invention relates to an image interpretation support device.

A medical image generated by a medical image capturing apparatus such as an X-ray CT (Computed Tomography) apparatus or an MRI (Magnetic Resonance Imaging) apparatus is interpreted by an image interpreting doctor. The radiologist interprets the medical image to create an image interpretation report, and attaches accompanying information such as annotations and measurement information to the medical image. Here, when interpreting a medical image, the radiologist interprets items according to request information (order information) requested by the clinician, but also interprets other items according to his/her own judgment. For example, the radiologist interprets a cerebral infarction or cerebral aneurysm with the MR image of the head, which is requested to interpret the brain metastasis of prostate cancer, just in case. Further, for example, an image interpretation doctor also reads a scoliosis that has been treated three years ago, just in case, with a chest CT image requested to read the main lesion of lung cancer.

JP, 2006-074416, A JP, 2015-095050, A JP, 2010-055130, A JP, 2010-128971, A JP, 2009-082442, A

The problem to be solved by the present invention is to provide an image interpretation support apparatus capable of improving the quality of image interpretation.

The image interpretation support apparatus according to the embodiment includes an extraction unit and a notification unit. The extraction unit extracts, from the medical images collected from the subject, target items that are different from the items of the image interpretation according to the contents of the examination on the subject and are the subject of the image interpretation. The notification unit notifies the target item extracted by the extraction unit.

FIG. 1 is a diagram showing an example of a configuration of an image interpretation terminal according to the first embodiment. FIG. 2 is a diagram for explaining an outline of processing by the image interpretation terminal according to the first embodiment. FIG. 3 is a diagram illustrating an example of the list master according to the first embodiment. FIG. 4A is a diagram showing an example of an addition rule according to the first embodiment. FIG. 4B is a diagram illustrating an example of the addition rule according to the first embodiment. FIG. 5 is a diagram for explaining an example of initial item extraction by the extraction function according to the first embodiment. FIG. 6 is a diagram for explaining an example of extraction of items based on biopsy information by the extraction function according to the first embodiment. FIG. 7 is a diagram for explaining an example of extraction of items based on past information by the extraction function according to the first embodiment. FIG. 8 is a diagram for explaining an example of selection of items based on information of medical image data by the extraction function according to the first embodiment. FIG. 9 is a diagram illustrating an example of display processing by the notification function according to the first embodiment. FIG. 10 is a diagram showing the process of updating the image interpretation target list by the notification function according to the first embodiment. FIG. 11 is a diagram illustrating an example of display of image interpretation results by the notification function according to the first embodiment. FIG. 12 is a diagram illustrating an example of generation of an image interpretation report by the generation function according to the first embodiment. FIG. 13 is a flowchart showing a processing procedure by the image interpretation terminal according to the first embodiment. FIG. 14 is a diagram showing an example of a list master according to the second embodiment.

An embodiment of an image interpretation support apparatus according to the present application will be described in detail below with reference to the accompanying drawings. The image interpretation support apparatus according to the present application is not limited to the embodiments described below.

(First embodiment)
First, the first embodiment will be described. In the first embodiment, an example in which the technology disclosed in the present application is applied to a radiogram interpretation terminal will be described. FIG. 1 is a diagram showing an example of a configuration of an image interpretation terminal according to the first embodiment. For example, as illustrated in FIG. 1, the image interpretation terminal 500 according to the first embodiment includes a medical image diagnostic apparatus 100, an image storage apparatus 200, a user terminal 300, and a management server 400 via a network 2. Connected. The respective devices illustrated in FIG. 1 are in a state of being able to communicate with each other directly or indirectly, for example, by an in-hospital LAN (Local Area Network) installed in the hospital.

Here, the medical information processing system 1 of FIG. 1 including the image interpretation terminal 500 can introduce, for example, a PACS (Picture Archiving and Communication System). Further, each device in the medical information processing system 1 shown in FIG. 1 can mutually transmit and receive medical images and the like in accordance with the DICOM (Digital Imaging and Communications in Medicine) standard. Further, in the medical information processing system 1, for example, HIS (Hospital Information System), RIS (Radiology Information System) and the like are introduced, and various information can be managed. 1 shows one each of the medical image diagnostic apparatus 100, the image storage apparatus 200, the user terminal 300, the management server 400, and the image interpretation terminal 500, the number of each apparatus is arbitrary.

The medical image diagnostic apparatus 100 includes an X-ray diagnostic apparatus, an X-ray CT (Computed Tomography) apparatus, an MRI (Magnetic Resonance Imaging) apparatus, an ultrasonic diagnostic apparatus, a SPECT (Single Photon Emission Computed Tomography) apparatus, and a PET (Positron Emission computed Tomography) apparatus. ) Device, a SPECT-CT device in which a SPECT device and an X-ray CT device are integrated, a PET-CT device in which a PET device and an X-ray CT device are integrated, or a group of these devices. Moreover, the medical image diagnostic apparatus 100 can generate three-dimensional medical image data (volume data). The medical image diagnostic apparatus 100 is also referred to as a modality apparatus.

For example, the medical image diagnostic apparatus 100 acquires the patient information from the order information received directly from the user terminal 300 or the patient list (modality work list) for each modality apparatus created by the management server 400 that received the order information. And collect medical image data for each patient. Then, the medical image diagnostic apparatus 100 transmits the collected medical image data to the image interpretation terminal 500, the management server 400, and the image storage apparatus 200. The medical image diagnostic apparatus 100 manages the image data generated by performing various image processes on the collected medical image data (for example, X-ray CT image data, MR image data, etc.) and the image interpretation terminal 500 and management. It can also be transmitted to the server 400 and the image storage device 200. Further, the medical image diagnostic apparatus 100, when transmitting the medical image data or the image data to the management server 400, includes, for example, a patient ID for identifying a patient, an examination ID for identifying a test, and the medical image diagnostic apparatus 100 as additional information. And the image series ID for identifying one imaging by the medical image diagnostic apparatus 100, etc. are transmitted.

The image storage device 200 stores image data collected by various medical image diagnostic devices. For example, the image storage device 200 stores medical image data collected by the medical image diagnostic device 100, image data generated by performing image processing on the medical image data, and the like. The image storage device 200 also stores the image data generated by the image interpretation terminal 500. The image storage device 200 is realized by computer equipment such as a server device.

The user terminal 300 is a device that is arranged in each medical department in the hospital and is operated by a doctor (clinician) working in each medical department, and is a PC (Personal Computer), a tablet PC, or a PDA (Personal Digital Assistant). , Mobile phones, etc. For example, the user terminal 300 performs various processes and displays image data according to the operation by the doctor of each medical department. For example, in the user terminal 300, medical chart information such as a symptom of a patient or a doctor's finding is input by a doctor. Further, the user terminal 300 is input with order information for requesting an examination by the medical image diagnostic apparatus 100, and transmits the input order information to the medical image diagnostic apparatus 100 and the management server 400. That is, the doctor in the medical department operates the user terminal 300 to read the reception information and the electronic medical record information of the patient who came to the hospital, examine the corresponding patient, and input the medical record information to the read electronic medical record. Then, the doctor in the medical department operates the user terminal 300 to transmit the order information according to the necessity of the examination by the medical image diagnostic apparatus 100.

In addition, the user terminal 300 acquires image data according to the operation of the doctor from the image storage device 200, and displays the acquired image data on a display unit such as a monitor. The medical image data and image data stored in the image storage device 200 are stored in association with the patient ID, examination ID, device ID, image series ID, and the like. Therefore, the user terminal 300 can acquire necessary medical image data and image data from the image storage device 200 by performing a search using the patient ID, the examination ID, the device ID, the image series ID, and the like.

The management server 400 manages various types of information regarding inspection. For example, the management server 400 receives a plurality of order information from the user terminals 300 arranged in each medical department, creates a patient list for each medical image diagnostic apparatus 100, and uses the created patient list for each medical image diagnostic. Send to the device 100. As an example, the management server 400 receives order information for performing the examination by the medical image diagnostic apparatus 100 from each of the user terminals 300 of each clinical department to create a patient list, and the created patient list is used as the medical image. It is transmitted to the diagnostic device 100.

The image interpretation terminal 500 is, for example, a device that is placed in the radiology department and is operated by an image interpretation doctor, and performs various types of image processing and display of image data according to the operation of the image interpretation doctor. The image interpretation doctor performs image interpretation using the image data displayed on the image interpretation terminal 5. As an example, the image interpretation terminal 500 acquires medical image data from the medical image diagnostic apparatus 100 or the image storage apparatus 200 in response to an operation by an image interpretation doctor. Then, the image interpretation terminal 500 executes various image processes on the acquired medical image data in accordance with an operation by the image interpretation doctor to generate image data. The image interpretation terminal 500 stores the generated image data in the image storage device 200. Further, the image interpretation terminal 500 generates report information after image interpretation according to the operation of the image interpretation doctor. For example, the image interpretation terminal 500 includes an I/F (interface) circuit 510, an input circuit 520, a display 530, a storage circuit 540, and a processing circuit 550, as shown in FIG.

The I/F circuit 510 is connected to the processing circuit 550, and stores various kinds of data between the medical image diagnostic apparatus 100, the image storage apparatus 200, the user terminal 300, and the management server 400 that are connected via the network. Control transmission and communication. For example, the I/F circuit 510 is realized by a network card, a network adapter, a NIC (Network Interface Controller), or the like.

The input circuit 520 includes a pointing device such as a mouse, a keyboard, and the like, receives inputs of various operations on the image interpretation terminal 500 from the image interpretation doctor, and transfers instructions and setting information received from the image interpretation doctor to the processing circuit 550. For example, the input circuit 520 receives an acquisition request for medical image data, image processing conditions, and the like from the image interpretation doctor. The input circuit 520 described in this embodiment is an example of the reception unit described in the claims.

The display 530 is a monitor referred to by the operator, and under the control of the processing circuit 550, displays image data to the operator and receives various instructions and various settings from the operator via the input circuit 520. GUI (Graphical User Interface) is displayed. Further, the display 530 displays, for example, information on items to be interpreted for each examination. Items to be interpreted will be described in detail later.

The storage circuit 540 is, for example, a semiconductor memory device such as a RAM (Random Access Memory) or a flash memory (Flash Memory), or a storage device such as a hard disk or an optical disk. The acquired medical image data and image data are stored. The storage circuit 540 also stores the processing result of the processing circuit 550. Further, the storage circuit 540 stores a list master 541, an additional rule 542, and the like, as shown in FIG. Details of the list master 541 and the additional rule 542 will be described later.

The processing circuit 550 controls the entire image interpretation terminal 500. Specifically, the processing circuit 550 executes medical image acquisition processing, image processing, image display, and the like according to the instruction transferred from the input circuit 520. For example, the processing circuit 550 executes the acquisition function 551, the extraction function 552, the generation function 553, and the notification function 554 as shown in FIG. Here, for example, each processing function executed by the acquisition function 551, the extraction function 552, the generation function 553, and the notification function 554, which are the components of the processing circuit 550 shown in FIG. 1, is stored in the form of a program executable by a computer. Recorded in circuit 540. The processing circuit 550 is a processor that realizes a function corresponding to each program by reading each program from the storage circuit 540 and executing the program. In other words, the processing circuit 550 in the state where each program is read out has the respective functions shown in the processing circuit 550 of FIG. The extraction function 552 described in the present embodiment is an example of the extraction unit described in the claims. The generation function 553 is an example of the generation unit described in the claims. Further, the notification function 554 is an example of the notification unit described in the claims.

The word "processor" used in the above description is, for example, a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), an application specific integrated circuit (ASIC), a programmable logic device ( For example, it means a circuit such as a Simple Programmable Logic Device (SPLD), a Complex Programmable Logic Device (CPLD), and a Field Programmable Gate Array (FPGA). The processor realizes the function by reading and executing the program stored in the memory circuit. Instead of storing the program in the memory circuit, the program may be directly incorporated in the circuit of the processor. In this case, the processor realizes the function by reading and executing the program incorporated in the circuit. It should be noted that each processor of the present embodiment is not limited to the case where each processor is configured as a single circuit, and a plurality of independent circuits may be combined and configured as one processor to realize its function. Good.

With such a configuration, the image interpretation terminal 500 according to the present embodiment enables the quality of image interpretation to be improved. Specifically, the image interpretation terminal 500 extracts items other than the image interpretation items corresponding to the order information of the examination based on the information of the collected medical image data, and extracts the items in addition to the image interpretation items corresponding to the order information. The quality of the image interpretation is improved by notifying the selected item as the item of the image interpretation target. The outline of this embodiment will be described below with reference to FIG. FIG. 2 is a diagram for explaining an outline of processing by the image interpretation terminal 500 according to the first embodiment.

For example, as shown in FIG. 2, the image interpretation terminal 500 is a list of items to be interpreted using "list master", "order information", "biopsy information", and "examination image". Generate the "interpretation target list". Here, the list master is information in which a modality device, a target part, an imaging method, and the like are associated with each item, and is stored by the storage circuit 540. FIG. 3 is a diagram illustrating an example of the list master 541 according to the first embodiment. For example, the list master 541 is information in which "item name" and "inspection condition" are associated with each other, as shown in FIG. Here, the “item name” indicates an item for image interpretation, and the “inspection condition” indicates an inspection condition when performing image interpretation for the “item name”. For example, as shown in FIG. 3, the list master 541 is information in which “item name: prostate cancer> main lesion” and “examination condition: examination type: MR, detailed site: prostate” are associated with each other. That is, the above information means that the examination of the “prostate” by the “MRI apparatus” is suitable for reading the “main lesion” of the “prostate cancer”.

Similarly, as shown in FIG. 3, the list master 541 associates “item name: prostate cancer> brain metastasis” with “test condition test type: MR, detailed site: head”, and “item”. The information includes information in which “name: prostate cancer>lung metastasis” and “test condition test type: CT, detailed site: lung” are associated with each other. In this way, the list master 541 is stored as information in which examination contents suitable for each image interpretation item are associated. Here, the list master 541 accumulates information based on the contents of the image interpretation performed so far and the contents of the examination performed at that time. That is, the list master 541 is accumulated based on the record information of what kind of image interpretation was performed using the medical image data of the predetermined region collected by the predetermined imaging method of the predetermined modality device. Therefore, the list master 541 is appropriately updated based on the record information for each hospital (interpretation doctor) and new knowledge advocated by academic societies.

As shown in FIG. 2, the image interpretation terminal 500 extracts the items to be interpreted from the list master 541 based on the biopsy information and the examination image in addition to the order information in each examination on the subject. Then, the interpretation target list is generated. Here, for example, as a list of image interpretation targets, “prostate cancer>main lesion”, “prostate cancer>lymph node metastasis”, “prostate cancer>brain metastasis”, “prostate cancer>bone metastasis”, “cerebral infarction” shown in FIG. And “brain tumor” are extracted, the image interpretation terminal 500 generates the image interpretation target list in the next examination of the same subject in the previous image interpretation target list (that is, “prostate cancer>main lesion”, “prostate cancer> Information on “lymph node metastasis”, “prostate cancer>brain metastasis”, “prostate cancer>bone metastasis”, “cerebral infarction” and “brain tumor”) is used.

As described above, the image interpretation terminal 500 according to the first embodiment, based on not only the image interpretation items obtained from the order information but also the examination image and biopsy information obtained by the examination and the examination history (history), The quality of image interpretation is improved by extracting items to be interpreted and notifying the image interpretation doctor. Hereinafter, the details of the processing by the image interpretation terminal 500 according to the first embodiment will be described.

The acquisition function 551 executed by the processing circuit 550 acquires a medical image to be interpreted from the medical image diagnostic apparatus 100 or the image storage apparatus 200 via the I/F circuit 510 and stores the medical image in the storage circuit 540. .. For example, the acquisition function 551 is generated from data such as projection data and MR signals, volume data reconstructed from them, and further from volume data, based on the information input by the operator via the input circuit 520. Image data and the like are acquired and stored in the storage circuit 540. Further, the acquisition function 551 acquires order information, biopsy information, etc. for each subject input from the user terminal 300.

The extraction function 552 is an item that is different from the image interpretation item according to the content of the examination on the subject and that is the subject item that is the subject of the image interpretation based on the medical image collected from the subject. Specifically, the extraction function 552 includes at least one of correspondence information in which examination conditions and image interpretation items are associated with each other, history information of the subject, and biopsy information of the subject, and attribute information and analysis of the medical image. The target item is extracted based on the comparison result with the image information including the information. That is, the extraction function 552 collects the order information, the history information of the subject, the interpretation items derived from the list master 541 based on the biopsy information, and the image information of the medical image data actually collected. Collate. Then, the extraction function 552 uses the actually collected medical image data among the interpretation items derived from the list master 541 based on the order information, the history information of the subject, and the biopsy information. The items that can be extracted are extracted as the items to be interpreted.

Here, the image information of the medical image data is the attribute information including the information of the modality device that has collected the medical image data, the information of the target site, and the type information of the medical image data, the analysis information of the medical image data, and the like. .. For example, the extraction function 552 identifies an item that can be interpreted using the collected medical image data based on the attribute information of the medical image data and the analysis information. Here, the extraction function 552 acquires the attribute information of the medical image data from the supplementary information of the medical image data and the order information, and extracts the target item based on the acquired attribute information.

In addition, the extraction function 552 acquires the site information included in the medical image data by executing the analysis process for extracting the site included in the medical image data, and extracts the target item based on the acquired site information. To do. For example, the extraction function 552 extracts three-dimensional medical image data (volume data), image data generated from the volume data, or a part such as an organ included in the two-dimensional medical image data collected. For example, the extraction function 552 detects a site such as an organ included in volume data or image data based on an anatomical feature point (Anatomical Landmark). Here, the anatomical characteristic point is a point indicating the characteristic of a site such as a specific bone, organ, blood vessel, nerve, or lumen. That is, the extraction function 552 extracts bones, organs, blood vessels, nerves, lumens, etc. included in the volume data and image data by detecting anatomical feature points such as specific organs and bones. The extraction function 552 can also detect the positions of the head, neck, chest, abdomen, legs, etc. included in the volume data by detecting characteristic feature points of the human body.

The generation function 553 generates information indicating an item to be an image interpretation target extracted by the extraction function 552. Specifically, the generation function 553 generates display information indicating the items extracted by the extraction function 552. For example, the generation function 553 generates the interpretation target list shown in FIG. In addition, the generation function 553 performs various processes on the data collected by the medical image diagnostic apparatus 100 to generate image data for display. For example, the generation function 553 reconstructs the volume data by using the data such as the projection data and the MR signal stored in the storage circuit 540. The generation function 553 also generates image data by performing various types of image processing on the volume data.

Further, the generation function 553 generates an image interpretation report in which the image interpretation result by the image interpretation doctor is reflected. Specifically, the generation function 553 generates an image interpretation report according to the contents input by the image interpretation doctor via the input circuit 520. Here, the generation function 553 generates an image interpretation report that reflects information on the implemented items in the image interpretation list. For example, the input circuit 520 accepts information on the implemented items in the image interpretation target list. The generation function 553 adds the template corresponding to the accepted item to the image interpretation report.

The notification function 554 notifies the target item extracted by the extraction function 552. Specifically, the notification function 554 causes the display 530, which displays the medical images collected from the subject, to display the item to be interpreted. That is, the notification function 554 is extracted based on the image interpretation item obtained from the order information, the medical image data, the biopsy information, and the examination history (history) on the display 530 where the image interpreting doctor observes and interprets the image data. A list of image interpretation targets including the items to be interpreted is displayed. Further, the notification function 554 causes the display 530 to display the image interpretation report generated by the generation function 553.

As described above, the image interpretation terminal 500 according to the first embodiment is based on the medical image data actually collected, biopsy information, and the examination history (history) in addition to the items of the image interpretation obtained from the order information. By extracting an item to be interpreted and notifying it to the interpreting doctor, it is possible to prompt interpretation of items other than the order information and improve the quality of the interpretation. Hereinafter, an example of processing by the image interpretation terminal 500 will be described. Here, a case will be described below in which the image interpretation items are provided with priorities and the image interpretation target list in which the information of the priority is shown for each item is displayed.

For example, in the image interpretation terminal 500 according to the first embodiment, the storage circuit 540 stores the additional rule 542. The additional rule 542 is information for setting the priority for the image interpretation item. 4A and 4B are diagrams illustrating an example of the additional rule 542 according to the first embodiment. Here, in FIG. 4A, an additional rule 542 for setting the priority to the item of the image interpretation based on the order information is shown. In addition, in FIG. 4B, an additional rule 542 for setting a priority for an item of image interpretation based on biopsy information is shown.

For example, as shown in FIG. 4A, the additional rule 542 for setting the priority for the image interpretation item based on the order information is “clinical disease name”, “examination purpose”, “list item No.”, and “list item number”. This is information associated with "priority". Here, “clinical disease name” indicates the disease name included in the order information for each subject, “test purpose” indicates the purpose of the test included in the order information for each subject, and “list item No.” is the list master. "No." of the item 541 is shown, and "priority" shows the priority of image interpretation. For example, as shown in FIG. 4A, the additional rule 542 for setting the priority for the image interpretation item based on the order information includes “clinical disease name: prostate cancer”, “examination purpose: detailed examination”, and “list item”. This is information in which "No.: 1" and "priority: 5" are associated with each other. That is, in the above-mentioned information, the item “clinical disease name” included in the order information is “prostate cancer”, the “examination purpose” is “detailed examination”, and the “No.” of the list master 541 is “1”. Is added to the image interpretation target list with “priority: 5”.

As described above, in the additional rule 542 for setting the priority for the interpretation item based on the order information, the “clinical disease name” and the “examination purpose” are associated with the respective interpretation items corresponding to the priority. Here, the “inspection purpose” includes, for example, “screening” and “follow-up” as shown in FIG. 4A, in addition to the “detailed inspection” described above. Even if the “clinical disease name” and the interpretation item (list item No.) are the same, the additional rule 542 is associated with different “priority” according to the “examination purpose”. For example, in the additional rule 542, even if the “clinical disease name” is “prostate cancer” and the “list item No.” is “1”, the “inspection purpose” is “detailed examination”, “screening”, “following”. In the case of “up”, the respective priorities are associated with each other. As an example, when the “inspection purpose” is “detailed inspection” or “follow-up” under the above conditions, the highest “priority” “5” is associated as shown in FIG. 4A. Be done. Further, under the above conditions, when the “inspection purpose” is “screening”, as shown in FIG. 4A, “3”, which is a medium “priority”, is associated. The “priority” included in the additional rule 542 for setting the priority for the image interpretation item based on the order information can be set arbitrarily.

Further, for example, as shown in FIG. 4B, the additional rule 542 for setting the priority for the image interpretation item based on the biopsy information includes “condition”, “list item No.”, and “priority”. Is information associated with. Here, “condition” indicates a condition provided in the biopsy result, “list item No.” indicates the item “No.” of the list master 541, and “priority” indicates the priority of the image interpretation. .. For example, as shown in FIG. 4B, the additional rule 542 for setting the priority for the image interpretation item based on the biopsy information is “condition: PSA (Prostate-Specific Antigen)>4.0 ng/ml”, and This is information in which "list item No.: 1" and "priority: 5" are associated with each other. Note that "PSA" is a "prostate-specific antigen", which is a protein increased by diseases such as prostate cancer, benign prostatic hyperplasia, and prostatitis. That is, in the above information, when the value exceeds "4.0 ng/ml" in the "PSA" test, the item "No." of the list master 541 is "1" and "Priority: 5". Means adding to the image interpretation list.

As described above, in the additional rule 542 for setting the priority for the image interpretation item based on the biopsy information, the “condition” is associated with the priority for each corresponding image interpretation item. Here, the biopsy information includes specimen information such as a tumor marker and physiological information such as various vital data. Therefore, in addition to the condition of "PSA" described above, the condition of the additional rule 542 for setting the priority to the item of the image interpretation based on the biopsy information is, for example, as shown in FIG. Conditions such as "blood pressure" and "systolic blood pressure" are also included. The "priority" included in the additional rule 542 for setting the priority for the image interpretation item based on the biopsy information can be arbitrarily set.

The extraction function 552 according to the first embodiment uses the above-mentioned additional rule 542 to extract an item to be an image interpretation target. For example, the extraction function 552 first extracts a base image interpretation item (initial item) based on the order information of the subject, the list master 541, and the addition rule 542. That is, the extraction function 552 extracts an initial item which is an item of image interpretation based on the order information requested for this examination. FIG. 5 is a diagram for explaining an example of initial item extraction by the extraction function 552 according to the first embodiment.

For example, as shown in FIG. 5, when the order information acquired by the acquisition function 551 is “clinical disease name: prostate cancer, examination purpose: detailed examination, requesting department comment:, medical history:... ”, extraction The function 552 refers to the list master 541 (for example, FIG. 3) and the additional rule 542 (for example, FIG. 4A) for setting the priority of the interpretation item based on the order information, and the initial item to be included in the interpretation target list. To extract. As an example, the extraction function 552 acquires “list item No.: 1 to 5” corresponding to “clinical disease name: prostate cancer, examination purpose: detailed examination” in the additional rule 542, and acquires the obtained “list item number”. .: 1 to 5” are extracted.

That is, as shown in the lower diagram of FIG. 5, the extraction function 552 displays “item name: prostate cancer>main lesion, examination condition examination type: MR, detailed site: prostate” from the list master 541 and “item name: Prostate cancer> Brain metastasis, Test condition Test type: MR, Detailed site: Head”, “Item name: Prostate cancer> Lung metastasis, Test condition Test type: CT, Detailed site: Lung”, “Item name: Prostate "Cancer> bone metastasis, examination condition examination type: CT, detailed site: whole body" and "item name: prostate cancer> bone metastasis, examination condition examination type: bone cinch, detailed site: whole body" are extracted. Here, "priority: 5" set in the additional rule 542 is associated with each item.

Next, the extraction function 552 extracts the image interpretation item to be added to the initial item based on the biopsy information of the subject, the list master 541, and the addition rule 542. That is, the extraction function 552 extracts the image interpretation item based on the biopsy information of the subject of this examination. FIG. 6 is a diagram for explaining an example of extraction of items based on biopsy information by the extraction function 552 according to the first embodiment.

For example, as shown in FIG. 6, when the biopsy information acquired by the acquisition function 551 is “PSA: 5.0 ng/ml, diastolic blood pressure: 100 mmHg, systolic blood pressure: 145 mmHg,... ”, extracted The function 552 refers to the list master 541 (for example, FIG. 3) and the additional rule 542 (for example, FIG. 4B) for setting the priority of the item of the image interpretation based on the biopsy information, and adds it to the interpretation target list. To extract the item. As an example, the extraction function 552 determines that “PSA” is “5.0 ng/ml” that satisfies “condition: PSA>4.0 ng/ml” in the acquired biopsy information of the subject. With reference to the addition rule 542, the item whose “list item No.” is “1” is added with “priority: 5”. That is, the extraction function 552 extracts “item name: prostate cancer>main lesion, examination condition examination type: MR, detailed site: prostate” with “priority: 5” for generation of the interpretation target list. Here, in the example of FIG. 6, since “item name: prostate cancer> main lesion, examination condition examination type: MR, detailed site: prostate” is already included in the initial items, the extraction function 552 is not included here. The additional processing of is omitted. Note that the extraction function 552, when the same item is extracted by the extraction of items based on order information and the extraction of items based on biopsy information as described above, the priority associated with each additional rule 542. Of these, the higher priority is set.

In addition, the extraction function 552 is “diastolic blood pressure: 100 mmHg, systolic blood pressure: 145 mmHg” in the acquired biopsy information of the subject, and satisfies “condition: diastolic blood pressure>90 mmHgor systolic blood pressure>140 mmHg”. Then, with reference to the addition rule 542, the items whose “list item No.” is “8” and “9” are added with “priority: 4”. That is, as shown in the lower diagram of FIG. 6, the extraction function 552 selects “item name: cerebral aneurysm, examination condition examination type: MR, detailed site: head” from the list master 541 and “item name: brain”. Aneurysm, examination conditions examination type: CT, detailed site: head” are extracted. Here, "priority: 4" set in the additional rule 542 is associated with each item.

Next, the extraction function 552 extracts the image interpretation item to be added to the initial item based on the past image interpretation target list of the subject to be examined this time. That is, the extraction function 552 acquires the image interpretation target list generated in the past for the subject of this examination, and adds the items included in the acquired image interpretation target list as items of the image interpretation target list of this time. Here, the extraction function 552 can extract, from the items included in the past image interpretation target list, the item to be added to the current image interpretation target list based on the past image interpretation result. That is, the extraction function 552 extracts an item that has “abnormal” in the past image interpretation as an item to be added to the image interpretation target list this time. Here, "abnormal" means that there is an interpretation result that "there is a suspicion of a tumor" based on the shadow in the image data. It should be noted that in the present embodiment, simply, image data having image features such as shadows is referred to as “with findings”. FIG. 7 is a diagram for explaining an example of extraction of items based on past information by the extraction function 552 according to the first embodiment.

For example, as shown in FIG. 7, “item name: cerebral infarction, test condition test type: MR, detailed site: head, priority: 5, result: abnormal” is added to the past interpretation target list acquired by the acquisition function 551. 7 is included, the extraction function 552 extracts “item name: cerebral infarction, examination condition examination type: MR, detailed site: head” from the list master 541 as shown in the lower diagram of FIG. 7. , "Priority: 5" are associated.

Next, the extraction function 552 selects the extracted items based on the medical image data actually collected in this examination. That is, the extraction function 552 selects only the items that can be interpreted using the medical image data collected this time among the items extracted by the above processing. Here, the extraction function 552 uses attribute information and analysis information of the medical image data in order to determine an item that can be interpreted using the medical image data collected this time. For example, the extraction function 552 identifies which part of the medical image data collected this time is targeted by referring to the supplementary information of the medical image data, and sets the item of image interpretation for the identified part as Judge as an item that can be interpreted. In addition, the extraction function 552 executes the analysis process of the part extraction on the medical image data to specify the detailed part included in the medical image data, and the image interpretation item for the specified part can be interpreted. Judge as an item.

FIG. 8 is a diagram for explaining an example of selection of items based on information of medical image data by the extraction function 552 according to the first embodiment. For example, as shown in FIG. 8, when the information of the inspection image is “examination type: MR, site: whole body, detailed site: head, lung, prostate,... ”, the extraction function 552 displays in FIG. Among the items shown, only the items that can be interpreted by the above-mentioned medical image data are selected. That is, as shown in the lower part of FIG. 8, the extraction function 552 selects “item name: prostate cancer> main lesion, test condition test type: MR, detailed site: prostate, priority: 5” from the items shown in FIG. , "Item name: prostate cancer> brain metastasis, examination condition examination type: MR, detailed site: head, priority: 5", and "item name: cerebral infarction, examination condition examination type: MR, detailed site: "Head" and "item name: cerebral aneurysm, examination condition examination type: MR, detailed site: head" are selected.

As described above, when the extraction function 552 extracts the image interpretation items to be included in the image interpretation target list, the generation function 553 generates the image interpretation target list including the extracted image interpretation items. For example, the generation function 553 includes “item name: prostate cancer> main lesion, examination condition examination type: MR, detailed site: prostate, priority: 5” and “item name: prostate cancer> brain” shown in the lower part of FIG. Metastasis, test conditions Test type: MR, detailed site: head, priority: 5”, “item name: cerebral infarction, test condition test type: MR, detailed site: head”, and “item name: cerebral artery” An interpretation target list including a bump, an inspection condition, an inspection type: MR, a detailed part: a head” is generated.

The notification function 554 causes the display 530 to display the image interpretation target list generated by the generation function 553. FIG. 9 is a diagram illustrating an example of display processing by the notification function 554 according to the first embodiment. For example, as shown in FIG. 9, the notification function 554 displays order information “clinical disease name: prostate cancer, examination purpose: detailed examination, requesting department comment:, medical history:... ”, and an examination image. The display 530 displays the interpretation target list generated by the generation function 553. Here, the notification function 554 causes the items included in the image interpretation target list to be displayed such that the priorities of the items can be identified. For example, the notification function 554 changes the notification of the item according to the priority of the item. As an example, the notification function 554 displays items with high priority on the upper side and items with low priority on the lower side, as shown in the image interpretation target list in FIG. 9. In the case where the priorities are the same, for example, when the notification function 554 displays the items based on the order information of this examination on the uppermost side and displays the items based on the medical history and biopsy information on the lower side. May be

Here, the image interpretation terminal 500 according to the first embodiment can edit the image interpretation target list generated and displayed by the processing circuit 550. Specifically, when the input circuit 520 receives an input operation for adding an item or deleting an item from the image interpretation doctor, the generation function 553 generates an image interpretation target list in which the item for which the input operation is received is added (or deleted). To do. The notification function 554 updates the display of the image interpretation target list so that the generated image interpretation target list is displayed. FIG. 10 is a diagram showing the process of updating the interpretation target list by the notification function 554 according to the first embodiment.

For example, the input circuit 520 receives an operation of adding the items “item name: prostate cancer> lymph node metastasis” and “item name: prostate cancer> bone metastasis”. The generation function 553 creates an interpretation target list in which “item name: prostate cancer> lymph node metastasis” and “item name: prostate cancer> bone metastasis” that have received an item addition operation are added to the interpretation target list shown in FIG. To generate. As shown in FIG. 10, the notifying function 554 includes the image interpretation target list displayed on the display 530 in which “item name: prostate cancer> lymph node metastasis” and “item name: prostate cancer> bone metastasis” are added. Update to the target list.

Further, the image interpretation terminal 500 according to the first embodiment can input the image interpretation result to the image interpretation target list. Specifically, the input circuit 520 receives the input operation of the image interpretation result, and the notification function 554 displays the information indicating the image interpretation result in the image interpretation target list. Here, the image interpretation result includes whether or not image interpretation is performed, whether there is an abnormality, whether there is a finding, and the like. That is, the notification function 554 displays the image interpretation target list showing these image interpretation results. FIG. 11 is a diagram showing an example of display of image interpretation results by the notification function 554 according to the first embodiment.

For example, as shown in FIG. 11, the notification function 554 displays an image interpretation target list indicating whether or not image interpretation is performed depending on whether or not the check box corresponding to each image interpretation item is checked. In addition, as shown in FIG. 11, the notification function 554 indicates that the check boxes are checked with different colors for “no abnormality, no observation”, “no abnormality, observation”, and “abnormality, observation”. By displaying by, the image interpretation target list indicating whether there is an abnormality and whether there is a finding is displayed. For example, the image interpretation doctor performs image interpretation while referring to the image interpretation target list shown in FIG. 11, and adds a check indicating the image interpretation result to each check box.

Here, in the image interpretation terminal 500 according to the first embodiment, it is possible to display image data in conjunction with the displayed image interpretation target list. For example, when the input circuit 520 receives a designation operation of an item to be interpreted, the generation function 553 generates image data suitable for the designated item. Then, the notification function 554 updates the image data displayed on the display 530 with the generated image data. For example, when the image interpretation doctor selects an item included in the image interpretation target list via the input circuit 520, the generation function 553 generates image data suitable for the selected item. Then, the notification function 554 updates the display image with the generated image, as shown in FIG. 11.

Further, the image interpretation terminal 500 according to the first embodiment can generate an image interpretation report according to the image interpretation result so that the image interpretation result is reflected in the image interpretation report. Specifically, the generation function 553 inputs the template corresponding to the item for which “there is a finding” into the image interpretation report. FIG. 12 is a diagram showing an example of generation of an image interpretation report by the generation function 553 according to the first embodiment. For example, when the input circuit 520 receives an input of “with findings” for the item “prostate cancer>brain metastasis”, the generation function 553 causes the “brain” in the interpretation report in this examination, as shown in FIG. Generate a template for entering findings regarding "transition". Further, the generation function 553 inserts the interpreted image data into the template as a key image.

In the present embodiment, the image interpretation target list includes not only the image interpretation items based on the order information of the examination but also the image history items based on the medical history and biopsy information. Therefore, by automatically generating the image interpretation report according to the image interpretation result, it is possible to easily create the image interpretation report and prevent forgetting to reflect the image interpretation result.

As described above, the image interpretation terminal 500 according to the first embodiment displays an image interpretation target list including a history and an item of image interpretation based on biopsy information, in addition to the item of image interpretation based on order information, It is possible to accept an operation of adding an arbitrary image interpretation item from the image interpretation doctor. That is, when a veteran image interpretation doctor performs image interpretation, it is possible to appropriately add image interpretation items based on his/her own experience. Therefore, in the image interpretation terminal 500 according to the first embodiment, by adding the items thus added to the list master 541, it is possible to improve the accuracy of the displayed image interpretation target list. For example, the generation function 553 updates the list master 541 so as to add an item newly added when a veteran radiologist interprets predetermined image data, and updates the addition rule 542. Here, the priority set in the additional rule 542 can be set arbitrarily, but it is also possible to update the priority according to the past interpretation result. For example, there may be a case where the interpretation frequency for each item is calculated based on the inspection information and the actual interpretation information, and the priority is updated based on the calculated interpretation frequency.

Next, a procedure of processing by the image interpretation terminal 500 according to the first embodiment will be described. FIG. 13 is a flowchart showing a processing procedure by the image interpretation terminal 500 according to the first embodiment. Here, step S101 in FIG. 13 is realized, for example, by the processing circuit 550 calling a program corresponding to the acquisition function 551 from the storage circuit 540 and executing the program. Further, step S102, step S106, step S108, and step S109 are realized, for example, by the processing circuit 550 calling a program corresponding to the generation function 553 from the storage circuit 540 and executing the program. Further, steps S103 to S105 are realized, for example, by the processing circuit 550 calling a program corresponding to the extraction function 552 from the storage circuit 540 and executing the program. Further, step S107 is realized by, for example, the processing circuit 550 calling a program corresponding to the notification function 554 from the storage circuit 540 and executing the program.

In the image interpretation terminal 500 according to this embodiment, first, the processing circuit 550 acquires subject information, order information, biopsy information, and image information (step S101). Then, the processing circuit 550 generates an initial item based on the order information (step S102). Subsequently, the processing circuit 550 adds a list item based on the biopsy information (step S103), and adds a list item based on the past image interpretation target list (step S104). Further, the processing circuit 550 extracts a part included in the medical image data based on the image attribute information and the analysis information (step S105).

Then, the processing circuit 550 narrows down the list items based on the extracted region and examination type to generate an image interpretation target list (step S106), and displays the image data and the image interpretation target list on the display 530 (step S107). After that, the processing circuit 550 generates an image interpretation report that reflects the image interpretation result (step S108), and updates the list master 541 and the additional rule 542 based on the image interpretation result (step S109).

As described above, according to the first embodiment, the extraction function 552 selects the target items that are different from the interpretation items according to the content of the examination on the subject and that are the subject of the interpretation. Extract based on the medical image collected from the specimen. The notification function 554 notifies the target item extracted by the extraction function 552. Therefore, the image interpretation terminal 500 according to the first embodiment can present the image interpretation items to the image interpretation doctor other than the items based on the order information, and the image interpretation possible items are displayed regardless of the ability of the image interpretation doctor. Allows you to notice and improve the quality of interpretation.

Further, according to the first embodiment, the extraction function 552 includes at least one of the list master 541, the history information of the subject and the biopsy information of the subject, and the attribute information and the analysis information of the medical image. The target item is extracted based on the comparison result with the image information. Therefore, the image interpretation terminal 500 according to the first embodiment can accurately extract an item that can be interpreted in the medical image data actually collected.

Further, according to the first embodiment, the extraction function 552 acquires the part information included in the medical image by executing the analysis process for extracting the part included in the medical image, and the acquired part information. The target item is extracted based on. Therefore, the image interpretation terminal 500 according to the first embodiment can acquire detailed site information included in the medical image data, and can improve the accuracy of determining an item that can be interpreted.

Further, according to the first embodiment, the list master 541 is updated based on the information of the image interpretation performed on the medical image collected under each examination condition. Therefore, the image interpretation terminal 500 according to the first embodiment makes it possible to generate a list master that reflects an image interpretation result by an experienced image interpretation doctor. As a result, the image interpretation terminal 500 can display a more accurate image interpretation target list.

Further, according to the first embodiment, the extraction function 552 extracts the target item based on the priority set for each image interpretation item. The notification function 554 changes the notification of the target item according to the priority of the target item. Therefore, the image interpretation terminal 500 according to the first embodiment enables the image interpretation doctor to clearly indicate the items to be interpreted with priority.

Further, according to the first embodiment, the notification function 554 displays the target item on the display 530 that displays the medical images collected from the subject. Therefore, the image interpretation terminal 500 according to the first embodiment enables efficient image interpretation.

Further, according to the first embodiment, the input circuit 520 receives information on the implemented item among the target items notified by the notification function 554. The generation function 553 generates an image interpretation report that reflects the information on the items received by the input circuit 520. Therefore, the image interpretation terminal 500 according to the first embodiment makes it possible to efficiently generate an image interpretation report.

(Second embodiment)
Now, the first embodiment has been described so far, but it may be implemented in various different forms other than the first embodiment described above.

In the above-described embodiment, a case has been described in which the image-interpretable item is determined based on the information about the part included in the medical image data. However, the embodiment is not limited to this, and may be determined by the image type, for example. For example, when the medical image data is collected by the X-ray CT apparatus, the image interpretation terminal 500 collects whether the medical image data is a “ThinSlice image”, whether the collected medical image data is a contrast image, or not. Items that can be interpreted are determined according to whether a virtual endoscopic image can be generated from the obtained medical image data. Further, for example, when the medical image data is collected by the MRI apparatus, the image interpretation terminal 500 can perform image interpretation according to whether there is an MRA image, whether the collected medical image data is a contrast image, and the like. To judge. For example, if there is an MRA image, it is possible to interpret a fine cerebral infarction, and therefore the extraction function 552 extracts an interpretation item for interpreting a fine cerebral infarction.

As described above, when determining an item that can be interpreted based on the image type, the image interpretation terminal 500 stores, for example, the list master 541 including information on the image type. FIG. 14 is a diagram showing an example of the list master 541 according to the second embodiment. For example, the list master 541 is information in which "item name" and "inspection condition" are associated with each other, as shown in FIG. Here, in the list master 541 according to the second embodiment, the inspection condition includes “image type”. That is, in the list master 541 according to the second embodiment, in addition to the “examination type” indicating the information of the modality device that collects the medical image data and the “detailed portion” indicating the examination target portion, This information is associated with an “image type” indicating the type of image to be displayed. For example, the extraction function 552 acquires information regarding the “image type” from the incidental information of the medical image data acquired by the acquisition function 551, and determines an image-interpretable item based on the acquired information.

Further, in the above-described embodiment, an example is given in which initial items are generated, items are added using biopsy information or a past image interpretation target list, and then items that can be interpreted using medical image data are determined. I explained it. However, the embodiment is not limited to this, and the determination of the diagnosable item using the medical image data can be executed at any time. For example, it may be a case where the interpretation-enabled item is determined using the medical image data before the initial item is extracted. In this case, the items added as the initial items and the items added by using the biopsy information and the past image interpretation target list are items that have already been determined to be readable.

Moreover, in the above-mentioned embodiment, the case where the image interpretation terminal 500 executes various processes has been described. However, the embodiment is not limited to this, and may be a case where various processes are executed in the management server 400, for example. In such a case, the management server 400 has a processing circuit similar to the processing circuit 550 and executes the above-described processing.

In addition, each constituent element of each device illustrated in the first embodiment is functionally conceptual, and does not necessarily have to be physically configured as illustrated. That is, the specific form of distribution/integration of each device is not limited to that shown in the figure, and all or a part of the device may be functionally or physically distributed/arranged in arbitrary units according to various loads or usage conditions. It can be integrated and configured. Further, each processing function performed by each device may be implemented in whole or in part by a CPU and a program that is analyzed and executed by the CPU, or may be implemented as hardware by a wired logic.

The display method described in the above embodiments can be realized by executing a display program prepared in advance on a computer such as a personal computer or a workstation. This display program can be distributed via a network such as the Internet. The display program can also be executed by being recorded in a computer-readable recording medium such as a hard disk, a flexible disk (FD), a CD-ROM, an MO, or a DVD, and being read from the recording medium by the computer.

According to at least one embodiment described above, the quality of image interpretation can be improved.

Although some embodiments of the present invention 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, replacements, and changes can be made without departing from the spirit of the invention. The embodiments and their modifications are included in the scope of the invention and the scope thereof, and are included in the invention described in the claims and the scope of equivalents thereof.

500 Interpretation terminal 520 Input circuit 552 Extraction function 553 Generation function 554 Notification function

Claims (8)

The items of the interpretation that corresponds to the examination order information of the subject by the imaging of medical images are different items, and the target item is interpretation possible items on the basis of the medical image, the image before Symbol Medical image An extraction unit that extracts based on information ,
A notification unit that notifies the target item extracted by the extraction unit,
An image interpretation support device comprising: The extraction unit is a device that captures a medical image and correspondence information that associates an inspection condition including information about an imaging target site with an item that can be interpreted by an inspection under the inspection condition , which is already performed for the subject. Regarding the examination by the imaging of the medical image, it is derived based on the medical history information of the subject including the imaged device and the target site of the imaging, and the items of the image interpretation performed , and the biopsy information of the subject. that at least one of the examination of information by capturing the medical image, based on the collation result between the image information including the attribute information and the analysis information of the medical image, and extracts the target item, according to claim 1 Image interpretation support device. Attribute information of the medical image, the medical image equipment of the captured, including information about the type of the target portion position及 beauty the medical image imaging, interpretation support apparatus according to claim 2. The extraction unit acquires the part information included in the medical image by executing an analysis process for extracting the part included in the medical image, and extracts the target item based on the acquired part information. The image interpretation support apparatus according to claim 2 or 3. Correspondence information that associates the items of the interpretation and the test conditions are updated based on the information of interpretation conducted on medical images acquired by each test condition, any one of claims 2-4 The image interpretation support apparatus according to one item. The extraction unit extracts the target item based on the priority set for each image interpretation item,
The image interpretation support apparatus according to claim 1, wherein the notification unit changes notification of the target item according to the priority of the target item. The image interpretation support apparatus according to claim 1, wherein the notification unit displays the target item on a display unit that displays a medical image collected from the subject. Of the target items notified by the notification unit, a reception unit that receives information on the implemented items,
A generation unit that generates an image interpretation report that reflects the information of the items received by the reception unit,
The image interpretation support apparatus according to claim 1, further comprising:

Images