Medical support system and medical support method

Abstract

A lesion information acquisition unit 42 acquires lesion information associated with a lesion detected from an endoscopic image by an image analysis device 3. A skill evaluation criteria setting unit 62 sets skill evaluation criteria associated with a processing to be performed with respect to the detected lesion on the basis of the lesion information.

Description

[Technical field]

[0001] The present disclosure relates to a medical support system and a medical support method for supporting evaluation of treatment skills. [Background technology]

[0002] Due to the recent shortage of doctors, there are fewer opportunities for experienced doctors to spend time educating junior doctors, making it difficult to properly evaluate the skills of junior doctors. In particular, to evaluate procedural skills in endoscopic examinations, experienced doctors need to actually observe the situation in which the junior doctor is performing the procedure, but the current situation is that busy experienced doctors cannot find the time to train junior doctors.

[0003] Patent Document 1 discloses a technology that detects drugs and treatment tools used in an endoscopic examination from frame images included in an endoscopic video by image recognition, and records the spraying of drugs and the implementation of treatment. The technology disclosed in Patent Document 1 aims to objectively evaluate the quality of an endoscopic examination by grasping the time and number of times required to spray drugs and implement treatment. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2017-86685 A Summary of the Invention [Problem to be solved by the invention]

[0005] Being able to accurately evaluate the treatment skills of doctors is important not only from the perspective of training young doctors, but also from the perspective of risk management in medical facilities. Therefore, there is a need for the development of technology to support the evaluation of treatment skills.

[0006] The present disclosure has been made in light of these circumstances, and has a purpose to provide a technique for supporting the evaluation of a doctor's treatment skills. [Means for solving the problem]

[0007] In order to solve the above problems, a medical support system of one embodiment of the present invention includes one or more processors having hardware, and the one or more processors acquire lesion information regarding a lesion detected by a computer from an endoscopic image, and set skill evaluation criteria for treatment to be performed on the detected lesion based on the lesion information.

[0008] Another aspect of the present invention is a medical support method, in which a computer acquires lesion information regarding a lesion detected from an endoscopic image, and sets skill evaluation standards for treatment to be performed on the detected lesion based on the lesion information.

[0009] Any combination of the above components, and conversion of the present disclosure into a method, device, system, recording medium, computer program, etc. are also valid aspects of the present disclosure. [Brief description of the drawings]

[0010] [Figure 1] FIG. 1 is a diagram showing a configuration of a medical support system according to an embodiment. [Diagram 2] FIG. 2 is a diagram illustrating functional blocks of the server device. [Diagram 3] FIG. 13 is a diagram showing an example of an endoscopic image. [Figure 4] FIG. 11 is a sequence diagram showing a procedure for setting skill evaluation standards. [Diagram 5] FIG. 13 is a diagram illustrating an example of a table. [Figure 6] FIG. 13 is a diagram illustrating an example of a table. [Figure 7] FIG. 13 is a diagram illustrating an example of a table. [Figure 8] FIG. 11 is a diagram showing an example of past implementation information. [Figure 9] FIG. 11 is a diagram showing an example of displayed information. [Figure 10] FIG. 13 is a diagram showing an example of an endoscopic image in which a treatment tool is captured. [Figure 11] FIG. 11 is a diagram showing an example of displayed information. [Figure 12] 13 is a diagram showing an example of information displayed on the display unit 100. FIG. [Figure 13] FIG. 13 is a diagram illustrating an example of a table. [Figure 14] FIG. 13 is a diagram illustrating an example of a table. [Figure 15] FIG. 13 is a diagram illustrating an example of a table. [Figure 16] FIG. 13 is a diagram showing an example of a displayed screen. [Figure 17] FIG. 13 is a diagram showing another example of a displayed screen. [Figure 18] FIG. 13 is a diagram showing another example of a displayed screen. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] FIG. 1 shows a configuration of a medical support system 1 according to an embodiment. The medical support system 1 is provided in a medical facility such as a hospital where endoscopic examinations are performed. In the medical support system 1, a server device 2, an image analysis device 3, an image storage device 8, an endoscope system 9, and a terminal device 10b are communicatively connected via a network 4 such as a LAN (local area network). The endoscope system 9 is provided in an examination room, and has an endoscopic observation device 5 and a terminal device 10a. In the medical support system 1, the server device 2, the image analysis device 3, and the image storage device 8 may be provided outside the medical facility, for example, as a cloud server.

[0012] An endoscope 7 inserted into the digestive tract of a patient is connected to the endoscopic observation device 5. The endoscope 7 has a light guide for transmitting illumination light supplied from the endoscopic observation device 5 to illuminate the inside of the digestive tract, and is provided at its tip with an illumination window for emitting the illumination light transmitted by the light guide to biological tissue, and an imaging section for capturing images of the biological tissue at a predetermined period and outputting an imaging signal to the endoscopic observation device 5. The imaging section includes a solid-state imaging element (e.g., a CCD image sensor or a CMOS image sensor) that converts incident light into an electrical signal.

[0013] The endoscopic observation device 5 performs image processing on the image signal photoelectrically converted by the solid-state image sensor of the endoscope 7 to generate an endoscopic image, which is displayed on the display device 6 in real time. The endoscopic observation device 5 may have a function of performing special image processing for the purpose of highlighting, etc., in addition to normal image processing such as A / D conversion and noise removal. The endoscopic observation device 5 generates an endoscopic image at a predetermined period (for example, 1 / 60 seconds). The endoscopic observation device 5 may be configured with one or more processors having dedicated hardware, but may also be configured with one or more processors having general-purpose hardware. The endoscope 7 of the embodiment is a flexible endoscope and has a forceps channel for inserting an endoscopic treatment tool. A doctor can perform various endoscopic treatments during an endoscopic examination by inserting a treatment tool into the forceps channel and operating it.

[0014] The doctor observes the endoscopic image displayed on the display device 6 according to the examination procedure. The doctor observes the endoscopic image while moving the endoscope 7, and operates the release switch of the endoscope 7 when a lesion is displayed on the display device 6. When the release switch is operated, the endoscopic observation device 5 captures (saves) the endoscopic image at the timing when the release switch is operated, and transmits the captured endoscopic image to the image storage device 8 together with information (image ID) that identifies the endoscopic image. Note that the endoscopic observation device 5 may transmit a plurality of captured endoscopic images together to the image storage device 8 after the examination is completed. The image storage device 8 records the endoscopic image transmitted from the endoscopic observation device 5 by linking it to an examination ID that identifies the endoscopic examination. The endoscopic images stored in the image storage device 8 are used by the doctor to create an examination report.

[0015] The terminal device 10a includes an information processing device 11a and a display device 12a, and is installed in an examination room. The terminal device 10a is used by doctors, nurses, etc. to check information on treatment and information on lesions in real time during an endoscopic examination. The information processing device 11a acquires information on treatment and information on lesions from the server device 2 and / or the image analysis device 3 during an endoscopic examination, and displays the information on the display device 12a.

[0016] The terminal device 10b includes an information processing device 11b and a display device 12b, and is installed in a room other than the examination room. The terminal device 10b may be used, for example, when an experienced doctor checks the treatment skills of a junior doctor. The terminal devices 10a and 10b are configured by one or more processors having general-purpose hardware.

[0017] The image analysis device 3 is an electronic calculator (computer) that analyzes an endoscopic image, detects a lesion contained in the endoscopic image, and performs a differential diagnosis of the detected lesion. In the medical support system 1 of the embodiment, the endoscopic observation device 5 displays the endoscopic image on the display device 6 in real time, and also supplies the endoscopic image to the image analysis device 3 in real time. The image analysis device 3 has an AI (artificial intelligence) diagnostic function, and may be configured by one or more processors having dedicated hardware, or may be configured by one or more processors having general-purpose hardware.

[0018] The image analysis device 3 uses a trained model generated by machine learning using an endoscopic image for learning and information on a lesion area included in the endoscopic image as teacher data. Annotation of the endoscopic image is performed by an annotator with specialized knowledge such as a doctor, and machine learning may use CNN, RNN, LSTM, etc., which are types of deep learning. When an endoscopic image is input, this trained model detects and outputs information on a lesion (lesion information). The lesion information detected by the image analysis device 3 may include the position of the lesion contour (contour coordinates), the size of the lesion, the depth of invasion of the lesion, and the result of a differential diagnosis of the lesion. During an endoscopic examination, the image analysis device 3 receives an endoscopic image from the endoscopic observation device 5 in real time, and supplies the detected lesion information to the server device 2 in real time.

[0019] The image analysis device 3 of the embodiment also has a function of detecting the contents of the treatment performed by the doctor (hereinafter sometimes referred to as "user") on the lesion by image analysis, and outputting implementation information indicating the contents of the treatment. For example, with respect to the time (treatment time) that the user performed the treatment, when the treatment tool frames in on the endoscopic image, the image analysis device 3 determines the start of the treatment and starts timing the treatment time, and when the treatment tool frames out of the endoscopic image, determines the end of the treatment and ends timing the treatment time. Note that the image analysis device 3 may determine the end of the treatment when the treatment tool frames out of the endoscopic image, the treatment site is washed with water, and the doctor operates the release switch. In this case, the operation information of the release switch is provided from the endoscopic observation device 5 to the image analysis device 3 and is used to determine the end of the treatment. In this way, the image analysis device 3 may measure the treatment time and output the implementation information including the treatment time to the server device 2.

[0020] When a treatment tool is framed in an endoscopic image, the image analysis device 3 identifies the type of the treatment tool by image analysis. The treatment tool includes high-frequency treatment tools used to remove a lesion, such as a high-frequency snare, dissection forceps, and high-frequency knife. For example, a high-frequency snare is used for EMR (Endoscopic Mucosal Resection), and a high-frequency knife is used for ESD (Endoscopic Submucosal Dissection). The treatment tool may include forceps such as biopsy forceps, grasping forceps, and hot biopsy forceps, and injection needles such as a biopsy needle and a local injection needle. When the image analysis device 3 identifies the type of the photographed treatment tool, it outputs information indicating the identified type of treatment tool to the server device 2 as implementation information.

[0021] The image analyzing device 3 detects the outline (cutting edge) of the area actually excised by the user with the treatment tool. When the user excises the lesion, the image analyzing device 3 detects the position where the lesion is excised with the treatment tool in real time, and outputs implementation information including cutting edge information indicating the position of the cutting edge to the server device 2 in real time. Note that the image analyzing device 3 may output the cutting edge information indicating the position of the cutting edge to the server device 2 after the excision with the treatment tool is completed.

[0022] The image analysis device 3 also has a function of detecting events that occur during the treatment (lesion resection) as the treatment contents. Specifically, the image analysis device 3 may detect the degree of bleeding during the treatment and output implementation information including information indicating the degree of bleeding to the server device 2 after the treatment is completed. The image analysis device 3 may also monitor the occurrence of perforation during the treatment and output implementation information including information indicating whether or not perforation has occurred to the server device 2 after the treatment is completed. In this way, the image analysis device 3 of the embodiment not only outputs lesion information detected by the AI ​​diagnosis function to the server device 2, but also has a function of outputting implementation information indicating the treatment contents performed by the user on the lesion to the server device 2. In the image analysis device 3, the function of outputting lesion information and the function of outputting implementation information may be realized by separate processors.

[0023] 2 shows a functional block of the server device 2. The server device 2 has a function of supporting the evaluation of treatment skills in endoscopic examination, and includes a communication unit 20, a processing unit 30, and a storage device 80. The communication unit 20 transmits and receives information such as data and instructions between the image analysis device 3, the endoscopic observation device 5, the image storage device 8, the terminal device 10a, and the terminal device 10b via the network 4. The processing unit 30 includes an acquisition unit 40, a treatment tool estimation unit 60, a skill evaluation standard setting unit 62, an evaluation unit 64, and an output processing unit 66, and the acquisition unit 40 includes a lesion information acquisition unit 42, an implementation information acquisition unit 44, a patient information acquisition unit 46, and a performance information acquisition unit 48. The storage device 80 includes a patient information storage unit 82, an implementation information storage unit 84, a skill evaluation information storage unit 86, and a master DB 88.

[0024] The server device 2 includes a computer, which executes a program to realize various functions shown in Fig. 2. The computer includes hardware such as a memory into which the program is loaded, one or more processors that execute the loaded program, an auxiliary storage device, and other LSIs. The processor is composed of multiple electronic circuits including a semiconductor integrated circuit and an LSI, and the multiple electronic circuits may be mounted on one chip or multiple chips. The functional blocks shown in Fig. 2 are realized by cooperation between hardware and software, and therefore, it will be understood by those skilled in the art that these functional blocks can be realized in various forms by hardware alone, software alone, or a combination thereof.

[0025] The endoscopic observation device 5 of the embodiment supplies an endoscopic image to the image analysis device 3, and the image analysis device 3 performs image analysis of the supplied endoscopic image in real time to detect a lesion. Upon detecting a lesion, the image analysis device 3 generates lesion information related to the lesion and outputs it to the server device 2. The lesion information detected by the image analysis device 3 may include the following information. Lesion location (contour information) Size of the lesion Depth of lesion Differential diagnosis of lesions

[0026] In an embodiment, the information indicating the position of the lesion may be the position coordinates of a contour surrounding the bottom surface of the lesion having a three-dimensional shape, and the information indicating the size of the lesion may be the longest diameter of the bottom surface of the lesion. The information indicating the depth of invasion of the lesion may be expressed by a sequence code of Tis, T1, T2, T3, T4a, or T4b using the TNM classification. The differential diagnosis result of the lesion may be information indicating whether the lesion is non-neoplastic or neoplastic.

[0027] 3 shows an example of an endoscopic image displayed on the display device 6. In this endoscopic image, a raised portion is a lesion, and when the image analysis device 3 detects a lesion contained in the endoscopic image, it outputs lesion information to the server device 2. In the medical support system 1 of the embodiment, the server device 2 sets a standard (hereinafter referred to as a "skill evaluation standard") for evaluating a user's lesion treatment skill based on the information output from the image analysis device 3, and evaluates the user's treatment skill based on the set skill evaluation standard and implementation information indicating the content of the treatment actually performed by the user. The procedure for setting the skill evaluation standard will be described below.

[0028] FIG. 4 is a sequence diagram showing the procedure for setting the skill evaluation standard. When the image analysis device 3 detects a lesion from an endoscopic image (S10), it outputs information about the lesion (lesion information) to the server device 2 (S12). In the server device 2, the lesion information acquisition unit 42 acquires the lesion information output from the image analysis device 3 (S14). During an endoscopic examination, the image analysis device 3 executes a lesion detection process for each endoscopic image. Therefore, if the same lesion is included in a plurality of consecutive endoscopic images, the same lesion will be detected from all of the endoscopic images. Therefore, if the lesion detected this time is the same as the lesion detected last time, it is preferable that the image analysis device 3 does not output the lesion information about the same lesion to the server device 2. In other words, the image analysis device 3 may be controlled so that when it detects one lesion from an endoscopic image for the first time, it outputs the lesion information about the lesion to the server device 2, and even if the same lesion is detected from a subsequent endoscopic image, it does not output the lesion information to the server device 2.

[0029] The skill evaluation standard setting unit 62 sets a skill evaluation standard for a treatment to be performed on a detected lesion based on the lesion information acquired by the lesion information acquisition unit 42. In the embodiment, the skill evaluation standard includes an appropriate time for performing a treatment on a lesion and an incision line for excising the lesion, and the skill evaluation standard setting unit 62 may set the appropriate time and the incision line as the skill evaluation standard based on the lesion information. In the sequence diagram shown in FIG. 4, the skill evaluation standard setting unit 62 derives an appropriate time for performing a treatment on a lesion based on the lesion information (S20). Note that steps S16 and S18 will be described later.

[0030] As described above, the lesion information provided by the image analysis device 3 includes the position of the lesion (contour coordinates), the size of the lesion, the depth of invasion of the lesion, and the result of the differential diagnosis of the lesion. The skill evaluation standard setting unit 62 may set the skill evaluation standard based on at least one of the position of the lesion (contour coordinates), the size of the lesion, the depth of invasion of the lesion, and the result of the differential diagnosis of the lesion. Note that the skill evaluation standard setting unit 62 may set the skill evaluation standard based on at least two or more of the position of the lesion (contour coordinates), the size of the lesion, the depth of invasion of the lesion, and the result of the differential diagnosis of the lesion.

[0031] The skill evaluation standard setting unit 62 derives an appropriate time for performing lesion treatment based on the lesion information (S20). In the embodiment, the skill evaluation standard setting unit 62 derives the appropriate time by adding a time corresponding to a weighted score according to the lesion information to a reference time (BT) for performing lesion treatment. The master DB 88 records the weighted score according to the lesion information.

[0032] 5(a) shows an example of a table associating lesion sizes with weighting scores Sa. In this table, a weighting score of 0 is assigned to lesion sizes less than 5 mm, a weighting score of 1 is assigned to lesion sizes 5 mm or more and less than 10 mm, a weighting score of 2 is assigned to lesion sizes 10 mm or more and less than 20 mm, and a weighting score of 3 is assigned to lesion sizes 20 mm or more.

[0033] 5(b) shows an example of a table associating the invasion depth of a lesion with a weighting score Sb. In this table, a weighting score of 0 is assigned to the invasion depth Ts, a weighting score of 1 is assigned to the invasion depth T1, a weighting score of 2 is assigned to the invasion depth T2, a weighting score of 3 is assigned to the invasion depth T3, a weighting score of 4 is assigned to the invasion depth T4a, and a weighting score of 5 is assigned to the invasion depth T4b.

[0034] 5(c) shows an example of a table that associates differential diagnosis results with weighting scores Sc, in which a weighting score of 0 is assigned to a non-neoplastic differential diagnosis and a weighting score of 3 is assigned to a neoplastic differential diagnosis.

[0035] The skill evaluation standard setting unit 62 may calculate the appropriate time required to perform lesion treatment using the following calculation formula (1). Optimal time = Reference time (BT) + Sa × Ta + Sb × Tb + Sc × Tc (1) Here, Sa is a weighted score corresponding to the lesion size, Sb is a weighted score corresponding to the depth of invasion, Sc is a weighted score corresponding to the differential diagnosis result, Ta is the summation time for the lesion size, Tb is the summation time for the depth of invasion, and Tc is the summation time for the differential diagnosis result.

[0036] In the embodiment, the reference time (BT) is 8 minutes, Ta is 30 seconds, Tb is 30 seconds, and Tc is 30 seconds. Note that Ta, Tb, and Tc may be different times. In the embodiment, it is assumed that the lesion information acquisition unit 42 has acquired lesion information including the following lesion size, invasion depth, and differential diagnosis result. Lesion size: 15mm Depth of invasion: T2 Differential diagnosis: Non-neoplastic

[0037] The skill evaluation standard setting unit 62 refers to the master DB 88 and derives the following weighted scores. Weight score Sa: 2 Weight score Sb: 2 Weight score Sc: 0

[0038] In this case, the skill evaluation standard setting unit 62 calculates the appropriate time for the treatment from the formula (1) as follows: Optimal time = 8 minutes + 2 x 30 seconds + 2 x 30 seconds + 0 x 30 seconds = 10 minutes In this manner, the skill evaluation standard setting unit 62 may calculate an appropriate time required to perform treatment for a lesion based on the lesion information.

[0039] The skill evaluation standard setting unit 62 may calculate the appropriate time by taking into account not only the lesion information but also the information of the patient undergoing the endoscopic examination. In this case, the master DB 88 records a weighted score according to the patient information.

[0040] 6 shows an example of a table associating patient information with weighting scores Sd. In this table, a weighting score of 0 is assigned to patient information of "no residue", a weighting score of 1 is assigned to patient information of "residue", a weighting score of 0 is assigned to patient information of "no inflammation", a weighting score of 1 is assigned to patient information of "inflammation", a weighting score of 0 is assigned to patient information of "under 65 years old", and a weighting score of 1 is assigned to patient information of "65 years old or older".

[0041] Before the start of the endoscopic examination, the patient information acquisition unit 46 acquires patient information by referring to the examination order information transmitted from the hospital information system (HIS) (S16). The skill evaluation standard setting unit 62 may calculate the appropriate time based on the lesion information and the patient information. In the example shown in Fig. 6, a weight score Sd is assigned to each of the information on residue, the information on inflammation, and the information on age, but it is not necessary to assign a weight score Sd to all of these three pieces of information, and it is sufficient that a weight score Sd is assigned to at least one of the pieces of information.

[0042] In the embodiment, the patient information acquiring unit 46 acquires patient information including at least one of information on residue, information on inflammation, and information on age, and the skill evaluation standard setting unit 62 derives the appropriate time based on the lesion information and the patient information acquired by the patient information acquiring unit 46 (S20). At this time, the skill evaluation standard setting unit 62 may calculate the appropriate time required to perform lesion treatment using the following calculation formula (2). Appropriate time = Reference time (BT) + Sa x Ta + Sb x Tb + Sc x Tc + Sd x Td (2) Here, Sa is a weighted score corresponding to the lesion size, Sb is a weighted score corresponding to the depth of invasion, Sc is a weighted score corresponding to the differential diagnosis result, Sd is a weighted score corresponding to the patient information, Ta is the addition time for the lesion size, Tb is the addition time for the depth of invasion, Tc is the addition time for the differential diagnosis result, and Td is the addition time for the patient information.

[0043] The skill evaluation standard setting unit 62 may also calculate the appropriate time taking into account the type of treatment tool used. In this case, the master DB 88 records weighted scores according to the type of treatment tool.

[0044] 7 shows an example of a table associating the treatment tool type with the weighting score Se. In this table, a weighting score of 0 is assigned to a high frequency snare (type 1), a weighting score of 1 is assigned to a high frequency snare (type 2), and a weighting score of 2 is assigned to a high frequency snare (type 3). Note that the master DB 88 may have a table associating all types of treatment tools that may be used in treatment with the weighting score Se.

[0045] The treatment tool estimation unit 60 estimates and acquires the type of treatment tool to be used to treat the lesion based on the lesion information (S18). For example, the treatment tool estimation unit 60 may estimate the type of treatment tool to be used based on data obtained by statistically processing information on treatments performed in the past. The skill evaluation standard setting unit 62 derives an appropriate time based on the lesion information and treatment tool information related to the estimated type of treatment tool (S20). At this time, the skill evaluation standard setting unit 62 may calculate the appropriate time required to perform the lesion treatment using the following calculation formula (3). Appropriate time = Reference time (BT) + Sa x Ta + Sb x Tb + Sc x Tc + Sd × Td + Se × Te (3) Here, Sa is a weighted score corresponding to the lesion size, Sb is a weighted score corresponding to the invasion depth, Sc is a weighted score corresponding to the differential diagnosis result, Sd is a weighted score corresponding to the patient information, Se is a weighted score corresponding to the treatment tool type, Ta is an addition time related to the lesion size, Tb is an addition time related to the invasion depth, Tc is an addition time related to the differential diagnosis result, Td is an addition time related to the patient information, and Te is an addition time related to the treatment tool type. Note that the treatment tool estimation unit 60 may exclude a parameter related to the patient information (Sd×Td) from the calculation formula (3).

[0046] In this way, the skill evaluation standard setting unit 62 calculates the appropriate time required to perform the treatment. In Fig. 4, step S14 must be executed before step S20 is executed, but steps S16 and S18 may be executed as necessary.

[0047] When the treatment tool estimation unit 60 estimates that the treatment tool to be used is a high-frequency snare (type 1), the weighted score Se is set to “0.” Below, a case where the skill evaluation standard setting unit 62 calculates the appropriate time to be “10 minutes” using the calculation formula (3) will be described.

[0048] The implementation information storage unit 84 stores implementation information indicating the contents of past treatments performed in the hospital facilities. The implementation information stored in the implementation information storage unit 84 includes at least the type of treatment tool used and the duration of the treatment. The skill evaluation standard setting unit 62 may determine whether the calculated appropriate time is appropriate by comparing it with the past results stored in the implementation information storage unit 84 (S22). The performance information acquisition unit 48 acquires information indicating the contents of past treatments in which the same type of treatment tool as the treatment tool estimated by the treatment tool estimation unit 60 was used from the implementation information storage unit 84, and provides the information to the skill evaluation standard setting unit 62.

[0049] FIG. 8 shows an example of past implementation information read from the implementation information storage unit 84. FIG. 8 shows a list of past implementation information using a high-frequency snare (type 1). The skill evaluation standard setting unit 62 judges whether the calculated appropriate time (10 minutes) is appropriate based on the implementation time of past treatments using the same type of treatment tool (S22). Here, the average of the three implementation times shown in FIG. 8 is 9 minutes 53 seconds, which is almost equal to 10 minutes. Therefore, the skill evaluation standard setting unit 62 judges that the calculated appropriate time is appropriate compared to past performances (Y in S22). Note that if the calculated appropriate time is different from the past performance value (average value) by a predetermined time (for example, 5 minutes) or more, the skill evaluation standard setting unit 62 judges that the calculated appropriate time is not appropriate compared to past performances (N in S22) and preferably corrects the appropriate time to be an appropriate time (S24). In this way, the skill evaluation standard setting unit 62 may re-derive the appropriate time based on information indicating the past treatment contents. When the skill evaluation standard setting unit 62 sets the appropriate time, the output processing unit 66 provides information indicating the appropriate time to the endoscope system 9 (S26). At this time, the output processing unit 66 may also provide lesion information to the endoscope system 9.

[0050] 9 shows an example of information displayed on the display device 6. The endoscopic observation device 5 displays information indicating the appropriate treatment time on the display device 6 (S28). In the endoscopic system 9, the information indicating the appropriate treatment time may be displayed on the display device 12a by the information processing device 11a. In either case, it is preferable that the information indicating the appropriate treatment time is displayed on a display device that can be seen by the user who is about to perform the treatment, and is presented as reference information when performing the treatment. In this way, the endoscopic observation device 5 or the information processing device 11a in the endoscopic system 9 displays on the display device the appropriate treatment time derived based on the type of treatment tool estimated to be used before the user starts treatment of the lesion.

[0051] The endoscopic observation device 5 displays information indicating the invasion depth on the display device 6 based on the lesion information provided by the server device 2. When the server device 2 provides the position coordinates of the line along which the lesion should be excised, the endoscopic observation device 5 may display a cut line 100 indicating the position of the line on the display device 6. As will be described later, in the server device 2, the skill evaluation standard setting unit 62 sets the cut line 100 based on the lesion position (contour coordinates) included in the lesion information as one of the skill evaluation standards. The cut line 100 is an ideal line when a user cuts out a lesion using a treatment tool, and the endoscopic observation device 5 superimposes the cut line 100 on an endoscopic image, so that the user can recognize that the lesion should be excised along the cut line 100. Note that the cut line 100 is preferably superimposed on an endoscopic image as shown in FIG. 9 to support the user in excising the lesion, but the cut line 100 may not be superimposed on an endoscopic image in the medical support system 1 as long as it can be used as one of the skill evaluation standards.

[0052] 10 shows an example of an endoscopic image in which a treatment tool is captured. When a treatment tool 102 comes into the frame of the endoscopic image, the image analyzing device 3 detects the treatment tool 102 included in the endoscopic image and identifies the type of treatment tool by image analysis (S30). When the image analyzing device 3 detects the treatment tool 102, it determines the start of treatment and starts timing the treatment time. The image analyzing device 3 provides the server device 2 with treatment tool information related to the identified type of treatment tool and implementation information including the start time of the treatment (S32). Here, the start time of the treatment is 13:08:22.

[0053] In the server device 2, the implementation information acquisition unit 44 acquires implementation information including the treatment tool information and the start time of the treatment. The skill evaluation standard setting unit 62 judges whether or not the type of treatment tool estimated by the treatment tool estimation unit 60 matches the type of treatment tool 102 identified by the image analysis device 3 (S34). If the type of treatment tool estimated here matches the type of the treatment tool 102 identified (Y in S34), the skill evaluation standard setting unit 62 recognizes that it is not necessary to change the appropriate treatment time derived before the start of the treatment. On the other hand, if the estimated type of treatment tool does not match the type of treatment tool 102 actually used (N in S34), the skill evaluation standard setting unit 62 re-derives the appropriate time based on the type of treatment tool 102 actually used (S36). For example, if the estimated treatment tool is a high-frequency snare (type 1) and the actually identified treatment tool is a high-frequency snare (type 2), the skill evaluation standard setting unit 62 uses the formula (3) to derive the appropriate time again, and the output processing unit 66 provides information indicating the corrected appropriate time to the endoscope system 9 (S38). Here, it is assumed that the skill evaluation standard setting unit 62 corrects the appropriate time to "12 minutes" using the formula (3). Note that the output processing unit 66 provides the treatment start time (13:08:22) to the endoscope system 9, regardless of whether the appropriate time is corrected or not, and starts timing the treatment time in the endoscope system 9.

[0054] FIG. 11 shows an example of information displayed on the display device 6. The endoscopic observation device 5 displays on the display device 6 information indicating the appropriate treatment time set based on the type of treatment tool actually used (S40). As described above, the information indicating the appropriate treatment time may be displayed on the display device 12a by the information processing device 11a. The display device 6 may display the planned treatment end time obtained by adding the appropriate treatment time to the treatment start time, together with information indicating the treatment start time. After the treatment start time (13:08:22), the endoscopic observation device 5 displays the elapsed time since the treatment of the lesion started as the "elapsed treatment time." The user performs the treatment with the goal of keeping the elapsed treatment time within the appropriate treatment time.

[0055] The above is an explanation of the procedure for setting the appropriate treatment time, which is one of the skill evaluation criteria. As described above, the skill evaluation criteria setting unit 62 sets the incision line 100 for resecting a lesion as another skill evaluation criterion. The skill evaluation criteria setting unit 62 sets the incision line 100 for reliably resecting the lesion and not cutting out any excess, based on the contour information of the lesion contained in the lesion information. The incision line 100 is set to cut out only the portion necessary for lesion resection, and if the line (incision edge) actually cut by the user is along the incision line 100, the treatment skill is evaluated high. On the other hand, if the incision edge is inside or outside the incision line 100, the treatment skill is evaluated low.

[0056] When the user starts treatment, the image analysis device 3 detects the treatment contents performed by the user on the lesion by image analysis, and outputs implementation information indicating the treatment contents to the server device 2. The image analysis device 3 detects the position (cutting edge) where the user actually excised with the treatment tool 102. The image analysis device 3 may detect the cutting position in real time, and output cutting edge information indicating the detected cutting position to the server device 2 in real time as implementation information, or may output cutting edge information indicating all cutting positions to the server device 2 after the cutting is completed.

[0057] In the server device 2, the implementation information acquisition unit 44 acquires the implementation information output from the image analysis device 3. The evaluation unit 64 judges whether the lesion has been appropriately excised based on the skill evaluation standard set by the skill evaluation standard setting unit 62 and the implementation information acquired by the implementation information acquisition unit 44. Here, the evaluation unit 64 compares the position coordinates of the incision line 100 with the position coordinates of the incision edge actually cut by the user to detect the deviation between the incision line 100 and the incision edge by the user in real time. When the user is incising the inside of the incision line 100, that is, when the incision edge by the user is located inside the incision line 100 and a part to be incised remains, the evaluation unit 64 generates a warning and causes the output processing unit 66 to transmit the warning to the endoscope system 9. In the endoscope system 9, it is preferable that the endoscopic observation device 5 or the information processing device 11a outputs a warning by voice or image indicating that the user is incising the inside of the incision line 100, and prompts the user to perform additional incision. At this time, the evaluation unit 64 stores the fact that the user has been warned in the implementation information storage unit 84 as implementation information.

[0058] The image analyzing device 3 detects events that occur during the treatment as the treatment contents. Specifically, the image analyzing device 3 detects the degree of bleeding, and outputs implementation information including information indicating the degree of bleeding to the server device 2 after the treatment is completed. The image analyzing device 3 also monitors the occurrence of perforation, and outputs implementation information including information indicating whether or not perforation has occurred to the server device 2 after the treatment is completed. In the server device 2, the implementation information acquiring unit 44 stores the implementation information acquired from the start to the completion of the treatment in the implementation information storage unit 84, linking it to the examination ID of the endoscopic examination and the treatment ID that identifies the treatment.

[0059] When the treatment tool frames out of the endoscopic image, the image analysis device 3 determines that the treatment has ended and ends the measurement of the treatment time. Note that the image analysis device 3 may determine that the treatment has ended and end the measurement of the treatment time when the treatment area is washed with water and the doctor operates the release switch after the treatment tool 102 frames out of the endoscopic image. In this case, the treatment end time is 13:19:52. When the image analysis device 3 determines that the treatment has ended, it provides the server device 2 with the treatment information including the treatment end time and the measured treatment time (the treatment end time minus the treatment start time).

[0060] In the server device 2, the implementation information acquisition unit 44 acquires implementation information including the treatment time and the treatment end time, and stores the information in the implementation information storage unit 84. The output processing unit 66 provides the treatment end time to the endoscope system 9, and causes the endoscope system 9 to end the measurement of the treatment time.

[0061] 12 shows an example of information displayed on the display device 6. When the endoscopic observation device 5 acquires the treatment end time from the output processing unit 66, it stops timing the treatment elapsed time. In this example, the time required for the treatment by the user is 11 minutes and 30 seconds, which is within the appropriate treatment time of 12 minutes. This means that the user completed the treatment within the appropriate time and cleared the skill evaluation standard regarding the treatment time.

[0062] When the treatment is completed, the evaluation unit 64 generates skill evaluation information that evaluates the skill of the user who performed the treatment based on the skill evaluation criteria set by the skill evaluation criteria setting unit 62 and the implementation information acquired by the implementation information acquisition unit 44. The evaluation unit 64 may generate the skill evaluation information based on the appropriate time included in the skill evaluation criteria and the treatment time included in the implementation information. The evaluation unit 64 may also generate the skill evaluation information based on the skill evaluation criteria regarding the incision line 100 and the incision edge information indicating the position of the incision edge where the user excised the lesion. The evaluation unit 64 of the embodiment may score the user's treatment skill using a deduction system from a full score (for example, 50 points). The master DB 88 records the deduction scores according to the implementation information.

[0063] 13(a) shows an example of a table that associates treatment time with deduction points. In this table, the time over the appropriate time, i.e. (treatment time - appropriate time), is associated with deduction points, and specifically, 0 deduction points are assigned to "no overtime", 3 deduction points are assigned to "less than 3 minutes overtime", 5 deduction points are assigned to "3 minutes or more but less than 10 minutes overtime", 10 deduction points are assigned to "10 minutes or more but less than 15 minutes overtime", and 15 deduction points are assigned to "15 minutes or more overtime".

[0064] 13(b) shows an example of a table associating the number of warnings with penalty points. As described above, a warning is output when the user is cutting inside the cut line 100. In this table, a penalty point of 0 is assigned to "no warning," a penalty point of 3 is assigned to "one warning," a penalty point of 5 is assigned to "two warnings," and a penalty point of 10 is assigned to "three or more warnings."

[0065] 13(c) shows an example of a table associating deviation amounts and deduction points when the outside of the incision line 100 is resected. This situation corresponds to a case where the user resects more biological tissue than necessary, and the deviation amount indicates the maximum distance from the incision line 100. In this table, a deduction point of 0 is assigned to a "deviation of less than 3 mm," a deduction point of 5 is assigned to a "deviation of 3 mm or more but less than 6 mm," a deduction point of 7 is assigned to a "deviation of 6 mm or more but less than 9 mm," and a deduction point of 10 is assigned to a "deviation of 9 mm or more."

[0066] The evaluation unit 64 performs the following steps (1)-(3) to derive deduction points for the skill evaluation criteria.

[0067] (1) The evaluation unit 64 calculates (treatment time - appropriate time) by referring to the implementation information stored in the implementation information storage unit 84, and identifies the deduction points P1 corresponding to (treatment time - appropriate time) from the table shown in Figure 13 (a).

[0068] (2) The evaluation unit 64 refers to the implementation information stored in the implementation information storage unit 84 to identify the number of times the warning has been issued, and identifies the deduction points P2 corresponding to the number of times the warning has been issued from the table shown in FIG. 13(b).

[0069] (3) The evaluation unit 64 refers to the implementation information stored in the implementation information storage unit 84 and determines whether the cut edge with which the user excised the lesion is located outside the cut line 100. When the cut edge is located outside the cut line 100, the evaluation unit 64 identifies the maximum deviation between the cut edge and the cut line 100 from the position coordinates of the cut edge and the position coordinates of the cut line 100, and identifies the deduction points P3 corresponding to the deviation from the table shown in FIG.

[0070] After identifying the deduction points P1 to P3, the evaluation unit 64 calculates the skill score for lesion treatment using the following calculation formula (4). Skill score = 50 - (P1 + P2 + P3) (4) The evaluation unit 64 generates skill evaluation information from the calculated skill scores.

[0071] 14 shows an example of a table associating skill evaluations with skill scores. In the embodiment, the evaluation unit 64 evaluates the skill of a procedure on a five-level scale, from rank A to E, based on the skill score calculated for the procedure. Note that in the embodiment, the ranks A to E are called skill evaluation information, but the skill score itself may also be called skill evaluation information.

[0072] The evaluation unit 64 may generate skill evaluation information based on the information regarding bleeding and / or the information regarding perforation. 15(a) shows an example of a table in which the presence or absence of heavy bleeding is associated with a penalty point. In this table, a penalty point of 0 is assigned to "no heavy bleeding" and a penalty point of 10 is assigned to "heavy bleeding." 15B shows an example of a table that associates the presence or absence of punching with a penalty point. In this table, a penalty point of 0 is assigned to "no punching" and a penalty point of 20 is assigned to "punching."

[0073] The evaluation unit 64 performs the following steps (4)-(5) to derive deduction points for the bleeding status and the occurrence status of perforation. (4) The evaluation unit 64 refers to the implementation information stored in the implementation information storage unit 84 to determine whether or not heavy bleeding has occurred, and identifies the deduction points P4 from the table shown in FIG. 15(a). (5) The evaluation unit 64 refers to the implementation information stored in the implementation information storage unit 84 to determine whether or not a perforation has occurred, and identifies the deduction points P5 from the table shown in FIG. 15(b).

[0074] After identifying the deduction points P1 to P5, the evaluation unit 64 calculates the skill score for lesion treatment using the following calculation formula (5). Skill score = 50 - (P1 + P2 + P3 + P4 + P5) (5) The evaluation unit 64 generates skill evaluation information from the calculated skill score by referring to the table shown in FIG.

[0075] Where: Penalty P1: 0 Penalty P2: 3 Penalty P3: 7 Penalty P4: 0 Penalty P5:20 If so, the evaluation unit 64 calculates a skill score=20, and therefore generates skill evaluation information of rank D.

[0076] As described above, the evaluation unit 64 generates skill evaluation information that evaluates the user's skills based on the skill evaluation criteria and the implementation information stored in the implementation information storage unit 84. The evaluation unit 64 links the generated skill evaluation information to a user ID, an examination ID, and a procedure ID, and stores it in the skill evaluation information storage unit 86. In the storage device 80, the skill evaluation information may be associated with the implementation information so that, for example, when an experienced doctor operates the terminal device 10b to check the skill evaluation information generated for a junior doctor, the experienced doctor can also refer to the implementation information.

[0077] FIG. 16 shows an example of a screen displayed on the display device 12b. The screen shown in FIG. 16 includes information about procedures performed in one endoscopic examination. When an experienced doctor operates the information processing device 11b and inputs the examination ID of an endoscopic examination as a search condition, the output processing unit 66 in the server device 2 reads out the skill evaluation information and implementation information linked to the examination ID from the storage device 80 and provides them to the information processing device 11b. In this example, Doctor A performs three procedures in an endoscopic examination, and the skill evaluation information for each of the three procedures is displayed in the form of a rank. By looking at the screen shown in FIG. 16, an experienced doctor can check the skill evaluation for multiple procedures performed in an endoscopic examination.

[0078] FIG. 17 shows another example of a screen displayed on the display device 12b. The screen shown in FIG. 17 includes information on the treatment results of users who meet the search criteria. When an experienced doctor operates the information processing device 11b to input information on the user as a search criterion, the output processing unit 66 accepts the search criterion and reads out all the implementation information and skill evaluation information of the corresponding user from the storage device 80 based on the search criterion. The output processing unit 66 statistically processes the read implementation information and skill evaluation information, and provides the statistical processing result to the information processing device 11b. In this example, the average value of the skill evaluation information of the users who meet the search criteria is displayed as the "average rank". By looking at the screen shown in FIG. 17, an experienced doctor can simultaneously check the skill evaluation information associated with each of multiple users.

[0079] Fig. 18 shows another example of a screen displayed on the display device 12b. The screen shown in Fig. 18 includes information on the treatment records of two users, Doctor B and Doctor C. When an experienced doctor operates the information processing device 11b to specify two users, the output processing unit 66 reads out the implementation information and skill evaluation information of the two users from the storage device 80, performs statistical processing, and provides the results of the statistical processing to the information processing device 11b. By looking at the screen shown in Fig. 18, the experienced doctor can simultaneously check and compare the skill evaluation information linked to Doctor B and Doctor C.

[0080] The present disclosure has been described above based on a number of examples. These examples are merely illustrative, and those skilled in the art will understand that various modifications are possible in the combination of each component and each processing process, and that such modifications are also within the scope of the present disclosure. In the examples, the terminal device 10a is provided with various information from the server device 2, but the information may be provided from the image analysis device 3. [Industrial Applicability]

[0081] The present disclosure can be applied to the technical field of supporting the evaluation of doctor skills. [Explanation of symbols]

[0082] 1 Medical support system, 2 Server device, 3 Image analysis device, 4 Network, 5 Endoscopic observation device, 6 Display device, 7 Endoscope, 8 Image storage device, 9 Endoscopic system, 10a, 10b Terminal device, 11a, 11b Information processing device, 12a, 12b Display device, 20 Communication unit, 30 Processing unit, 40 Acquisition unit, 42 Lesion Information acquisition unit, 44... implementation information acquisition unit, 46... patient information acquisition unit, 48... performance information acquisition unit, 60... treatment tool estimation unit, 62... skill evaluation standard setting unit, 64... evaluation unit, 66... ​​output processing unit, 80... storage device, 82... patient information storage unit, 84... implementation information storage unit, 86... skill evaluation information storage unit, 88... master DB, 100... cutting line, 102... treatment tool.

Claims

1. 1. A medical support system, comprising: one or more processors having hardware; The one or more processors: The computer acquires lesion information including at least one of the size of the lesion detected from the endoscopic image and the depth of invasion of the lesion; setting a skill evaluation standard for a treatment to be performed on the detected lesion based on the lesion information; A medical support system comprising:

2. The one or more processors: Setting the skill evaluation criteria including an appropriate time required to perform the treatment of the lesion; 2. The medical support system according to claim 1.

3. The one or more processors: Setting the skill evaluation criteria including a cut line for removing the lesion; 2. The medical support system according to claim 1.

4. The one or more processors: obtaining implementation information indicating the contents of a treatment performed by a user on the lesion; generating skill evaluation information that evaluates the skill of the user who performed the procedure based on the set skill evaluation standard and the implementation information; 2. The medical support system according to claim 1.

5. The one or more processors: obtaining the lesion information including a differential diagnosis result of the lesion; Setting the skill evaluation criteria based on the differential diagnosis results of the lesions; 2. The medical support system according to claim 1.

6. The one or more processors: Obtaining treatment tool information regarding the type of treatment tool to be used; setting the skill evaluation standard based on the lesion information and the treatment tool information; 2. The medical support system according to claim 1.

7. The one or more processors: Acquire information indicating the contents of past treatments in which the same type of treatment tool as the treatment tool was used; Setting the skill evaluation standard based on information indicating past treatment contents; 7. The medical support system according to claim 6.

8. The one or more processors: acquiring patient information including at least one of information regarding residue, information regarding inflammation, and information regarding age; The skill evaluation standard is set based on the lesion information and the patient information.

2. The medical support system according to claim 1.

9. The one or more processors: Setting the skill evaluation criteria including an appropriate time required to perform the treatment of the lesion; obtaining performance information including a treatment time taken by a user to treat the lesion; generating the skill evaluation information based on the appropriate time included in the skill evaluation standard and the treatment time included in the implementation information; 5. The medical support system according to claim 4.

10. The one or more processors: acquiring the lesion information including a size of the lesion, a depth of invasion of the lesion, and a differential diagnosis result of the lesion; Obtaining treatment tool information regarding the type of treatment tool to be used; setting the skill evaluation standard including the appropriate time based on the lesion information and the treatment tool information; generating the skill evaluation information based on the appropriate time included in the skill evaluation standard and the treatment time included in the implementation information; The medical support system according to claim 9 .

11. The one or more processors: During the treatment of the lesion, an image captured by the endoscopic examination, information indicating the appropriate time, and the time since the treatment of the lesion was started are displayed on one or more display devices. The medical support system according to claim 9 .

12. The one or more processors: before the treatment of the lesion is started, displaying on a display device information indicating an appropriate time set based on the type of treatment tool estimated to be used; When the type of the treatment tool to be used differs from the type of the treatment tool to be estimated, information indicating the appropriate time set based on the type of the treatment tool to be used is displayed on the display device.

7. The medical support system according to claim 6.

13. The one or more processors: acquiring the lesion information including contour information indicating a position of a contour of the lesion; setting the skill evaluation standard for the incision line of the lesion based on the contour information of the lesion; obtaining implementation information including cut edge information indicating a location of a cut edge along which a user excised the lesion; generating skill evaluation information that evaluates the skill of the user who excised the lesion based on the skill evaluation criterion and the excision edge information; 4. The medical support system according to claim 3.

14. The one or more processors: outputting a warning when the cut edge at which the user cuts a lesion is inside the cut line; generating the skill evaluation information based on the number of times the warning is output; The medical support system according to claim 13 .

15. The one or more processors: generating the skill evaluation information based on a distance between the cutting edge and the cutting line when the cutting edge used by the user to cut the lesion is located outside the cutting line; The medical support system according to claim 13 .

16. The one or more processors: obtaining the implementation information including information regarding bleeding during resection of the lesion; generating the skill evaluation information based on the information regarding the bleeding; 5. The medical support system according to claim 4.

17. The one or more processors: obtaining the implementation information including information regarding perforation during resection of the lesion; generating the skill evaluation information based on the information regarding the drilling; 5. The medical support system according to claim 4.

18. A storage device is provided for storing the skill evaluation information in association with the user.

5. The medical support system according to claim 4.

19. The one or more processors: Displaying the skill evaluation information associated with the user on a display device.

20. The medical support system according to claim 18.

20. The one or more processors: Accepts information about the user as search criteria, displaying the skill evaluation information searched based on the search conditions on the display device; 20. The medical support system according to claim 19.

21. The one or more processors: The skill evaluation information associated with each of the multiple users is simultaneously displayed on the display device.

20. The medical support system according to claim 19.

22. The procedure is an endoscopic procedure in an examination using a flexible endoscope; 2. The medical support system according to claim 1.

23. A medical support method, comprising: The computer acquires lesion information including at least one of the size of the lesion detected from the endoscopic image and the depth of invasion of the lesion; setting a skill evaluation standard for a treatment to be performed on the detected lesion based on the lesion information; A medical support method comprising:

24. On the computer, A function of acquiring lesion information including at least one of the size of a lesion detected from an endoscopic image by a separate computer and the depth of invasion of the lesion; and a program for realizing a function of setting a skill evaluation standard for treatment to be performed on the detected lesion based on the lesion information.

Images