WO2017179635A1 - Blood flow analysis system, analysis request accepting system, blood flow analysis method and program - Google Patents

Blood flow analysis system, analysis request accepting system, blood flow analysis method and program Download PDF

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Publication number
WO2017179635A1
WO2017179635A1 PCT/JP2017/015039 JP2017015039W WO2017179635A1 WO 2017179635 A1 WO2017179635 A1 WO 2017179635A1 JP 2017015039 W JP2017015039 W JP 2017015039W WO 2017179635 A1 WO2017179635 A1 WO 2017179635A1
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Prior art keywords
analysis
blood flow
request
simulation
unit
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PCT/JP2017/015039
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French (fr)
Japanese (ja)
Inventor
豊樹 古澤
周一 松井
輝泰 西野
慶一 板谷
翔平 宮崎
匡 山本
進 中嶋
真治 後藤
Original Assignee
Necソリューションイノベータ株式会社
株式会社Cardio Flow Design
社会医療法人北海道循環器病院
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Publication of WO2017179635A1 publication Critical patent/WO2017179635A1/en

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    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/02Arrangements for diagnosis sequentially in different planes; Stereoscopic radiation diagnosis
    • A61B6/03Computed tomography [CT]
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/05Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves 
    • A61B5/055Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves  involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging

Definitions

  • the present invention relates to a blood flow analysis system, an analysis request reception system, a blood flow analysis method, and a program.
  • Patent Literature 1 describes a method of creating a three-dimensional model representing at least a part of a patient's heart and identifying a coronary flow reserve ratio in the patient's heart based on the created three-dimensional model. ing.
  • An object of the present invention is to provide a blood flow analysis system, an analysis request reception system, a blood flow analysis method, and a program that can solve the above-described problems.
  • the blood flow analysis system includes an analysis request receiving unit that receives an analysis request including a two-dimensional tomographic image to be analyzed for blood flow via a communication network, and an analysis target from the analysis request.
  • An anonymization processing unit that deletes information for identifying a person and assigns a management number for identifying the analysis subject, a model generation unit that generates a three-dimensional model of a blood vessel shape based on the two-dimensional tomographic image,
  • a condition setting unit for setting a finite volume method condition used for blood flow simulation based on a three-dimensional model, a simulation request including the three-dimensional model, the condition set by the condition setting unit, and the management number
  • the blood flow simulation is performed by the fluid analysis method using the finite volume method. It comprises a analyzing unit for performing an analysis result generation unit that generates an analysis result based on the simulation result by the analyzing unit, and a analysis result transmitting unit that transmits to the requester on the basis
  • an analysis request receiving system includes an analysis request receiving unit that receives an analysis request including a two-dimensional tomographic image to be analyzed for blood flow via a communication network, and an analysis target from the analysis request.
  • An anonymization processing unit that deletes information for identifying a person and assigns a management number for identifying the analysis subject, a model generation unit that generates a three-dimensional model of a blood vessel shape based on the two-dimensional tomographic image, A condition setting unit for setting a finite volume method condition used for blood flow simulation based on a three-dimensional model, a simulation request including the three-dimensional model, the condition set by the condition setting unit, and the management number A simulation request processing unit to be generated; and a blood flow stain performed by a fluid analysis method using the finite volume method based on the simulation request.
  • Comprising an analysis result generation unit that generates an analysis result based on the result of the translation, and the analysis result transmitting unit that transmits to the request source based on the analysis result to the management number
  • the blood flow analysis method includes an analysis request receiving step for receiving an analysis request including a two-dimensional tomographic image to be analyzed for blood flow via a communication network, and an analysis target from the analysis request. Delete the information that identifies the person, a connectable anonymization step that assigns a management number that identifies the analysis subject, a model generation step that generates a three-dimensional model of the blood vessel shape based on the two-dimensional tomographic image, A condition setting step for setting a finite volume method condition used for blood flow simulation based on the three-dimensional model, a simulation request including the three-dimensional model, the condition set by the condition setting step, and the management number And a simulation request processing step for generating a fluid analysis method using the finite volume method based on the simulation request.
  • An analysis execution step for performing simulation of the blood flow an analysis result generation step for generating an analysis result based on the simulation result by the analysis execution step, and an analysis result for transmitting the analysis result to the request source based on the management
  • the program causes the computer to receive an analysis request including a two-dimensional tomographic image to be analyzed for blood flow via a communication network, and to analyze the analysis request from the analysis request. Delete the information that identifies the person, a connectable anonymization step that assigns a management number that identifies the analysis subject, a model generation step that generates a three-dimensional model of the blood vessel shape based on the two-dimensional tomographic image, A condition setting step for setting a finite volume method condition used for blood flow simulation based on the three-dimensional model, a simulation request including the three-dimensional model, the condition set by the condition setting step, and the management number And a simulation request processing step for generating the finite volume method based on the simulation request.
  • An analysis result generation step for generating an analysis result based on the result of the blood flow simulation performed by the fluid analysis method, and an analysis result transmission step for transmitting the analysis result to the request source based on the management number.
  • blood flow analysis can be requested in consideration of patient privacy.
  • FIG. 1 is a schematic block diagram showing a functional configuration of a user terminal device according to an embodiment of the present invention.
  • the blood flow analysis system 200 includes an analysis request reception system 210 and an analysis server device 240.
  • the analysis request reception system 210 includes a reception server device 211, an item management server device 212, a user authentication database device 221, a medical data file database device 222, an analysis file database device 223, and an analysis result file database device. 224, an operation terminal device 231, and a diagnostic report creation terminal device 232.
  • the reception server device 211 communicates with one or more user terminal devices 100 via the communication network 900.
  • the user terminal device 100 transmits a blood flow analysis request to the blood flow analysis system 200. Specifically, the user terminal device 100 generates an analysis request file in response to a user operation by a doctor in charge of requesting blood flow analysis, and an image of CT (Computed Tomography) or MRI (Magnetic Resonance Imaging), etc. A two-dimensional tomographic image of the analysis target portion is included in the analysis request and transmitted to the reception server device 211.
  • CT Computer Tomography
  • MRI Magnetic Resonance Imaging
  • a two-dimensional tomographic image of the analysis target portion is included in the analysis request and transmitted to the reception server device 211.
  • a general data format such as DICOM (Digital Imaging and Communication in Medicine) data can be used.
  • DICOM Digital Imaging and Communication in Medicine
  • the communication network 900 is a communication network that mediates communication between the user terminal device 100 and the reception server device 211.
  • the communication network 900 may be a general-purpose communication network such as the Internet, or may be a dedicated communication network for the blood flow analysis system 200.
  • the communication network 900 is the Internet will be described as an example.
  • the blood flow analysis system 200 performs a simulation for analyzing the blood flow of a patient in response to an analysis request from a doctor, and returns a diagnosis report based on the simulation result.
  • the patient here is a person to be analyzed, and it is not always necessary to have a medical condition.
  • it is necessary to grasp not only the state of the plaque attached to the blood vessel and the size of the heart but also the state of the blood flow. There is a case.
  • CFD computational Fluid Dynamics
  • blood flow analysis requires advanced technology. For this reason, it is not realistic for doctors who want to know the state of blood flow to analyze blood flow using CFD. Further, high-performance CFD software generally has a high license cost.
  • the CFD referred to here is a simulation in which the motion of the fluid is expressed by an equation.
  • the blood flow analysis system 200 shown in FIG. 1 receives a diagnosis request from a doctor, performs a simulation by CFD, and returns an analysis result.
  • the blood flow analysis system 200 performs a blood flow analysis in a short period of about 1 or 2 days using a high-performance computer and returns the analysis result.
  • the doctor who requested the diagnosis can obtain the analysis results without burdens such as acquiring CFD technology, obtaining a CFD software license, and securing a high-performance computer.
  • the blood flow analysis system 200 performs blood flow analysis on various parts related to blood flow, such as coronary arteries (coronary arteries), aorta, cerebral arteries, and heart. For example, the blood flow analysis system 200 performs coronary blood flow analysis for angina pectoris. In addition, the blood flow analysis system 200 performs blood flow analysis of the aorta for aortic aneurysm and aortic dissection. In addition, the blood flow analysis system 200 performs blood flow analysis of the cerebral artery for cerebral aneurysm and subarachnoid hemorrhage. In addition, the blood flow analysis system 200 performs blood flow analysis of the blood circulation including the heart for heart deformities such as congenital heart diseases.
  • the blood flow analysis system 200 also predicts information for evaluating the current state of the blood flow, information for predicting the future state of the blood flow, and the state of the blood flow after surgery when performing surgery. Providing information.
  • information for evaluating the current state of blood flow will be described.
  • the blood flow analysis system 200 evaluates the current state of the blood flow, for example, an evaluation index value of the severity of blood vessel stenosis and an evaluation index value indicating the risk of aneurysm rupture. To calculate various evaluation index values.
  • the blood flow analysis system 200 includes a WSS (Wall Shear Stress) indicating the strength of the force exerted on the blood vessel wall, a blood flow energy loss indicating energy efficiency for circulating the blood flow, and the like.
  • WSS is an index value for evaluating the risk of stenosis and rupture of blood vessels. In a portion where WSS is large, a large load is applied to the blood vessel. On the other hand, there is a possibility that plaque is likely to accumulate in a portion where WSS is small.
  • the blood flow energy loss is an index value for evaluating the burden on the heart.
  • the greater the blood flow energy loss the greater the burden on the heart.
  • blood flow analysis system 200 calculates blood flow by simulation, so that blood pressure and blood flow information can be obtained even for portions that are not actually measured. Thereby, the frequency
  • the current evaluation of blood flow is referred to as preoperative evaluation.
  • the blood flow analysis system 200 includes case data (a three-dimensional model such as a tomographic image, a blood vessel, etc. Analysis result data etc. are accumulated for each patient. Thereby, the blood flow analysis system 200 can obtain statistical data corresponding to the temporal change of the blood flow situation.
  • the three-dimensional model such as a blood vessel here is a three-dimensional model of a portion to be subjected to blood flow analysis, such as a blood vessel and a heart.
  • the blood flow analysis system 200 acquires statistical data on the temporal change in blood flow as described above. Thereby, the blood flow analysis system 200 can provide the prediction data of the future risk with respect to the current state of the blood flow.
  • the doctor in charge can determine the necessity of treatment such as medication or surgery based on the prediction data provided by the blood flow analysis system 200, and explain the future risk to the examinee. Medical examinees can reduce their anxiety by receiving explanations of future risks.
  • prediction diagnosis prediction of the future state of blood flow is referred to as prediction diagnosis.
  • the blood flow analysis system 200 calculates blood flow after surgery by simulation. Thereby, the attending physician can confirm in advance whether or not the planned operation is appropriate. For example, when a plurality of bypass methods for a patient having a stenosis in a coronary artery can be considered, the blood flow analysis system 200 calculates postoperative blood flow by simulation for each bypass method. Accordingly, the attending physician can examine which bypass method is better before the operation, and can select any bypass method.
  • the blood flow analysis system 200 also simulates blood flow for each of a plurality of lengths with respect to the length of the bypassed blood vessel. This allows the attending physician to consider which length is better before surgery.
  • the simulation of the blood flow situation after surgery is referred to as virtual surgery.
  • the analysis request receiving system 210 receives a blood flow analysis request from the user terminal device 100, generates CFD data (data used for CFD), and performs a CFD calculation on the analysis server device 240.
  • the operator of the analysis request receiving system 210 and the operator of the analysis server device 240 may be the same or different.
  • a high-performance computer is required as the analysis server device 240 in order to quickly perform blood flow analysis.
  • the analysis server device 240 need not be a computer dedicated to blood flow analysis, and may be a general-purpose computer as long as it can perform CFD calculations.
  • the reception server device 211 illustrated in FIG. 1 receives a blood flow analysis request from the user terminal device 100 and transmits (replies) the analysis result.
  • the reception server device 211 is configured using a computer, for example.
  • the communication network 900 is the Internet, and the reception server device 211 receives a blood flow analysis request via the Internet and answers the analysis result.
  • the blood flow analysis system 200 provides a blood flow analysis cloud service to the user terminal device 100.
  • the blood flow analysis system 200 provides a blood flow analysis cloud service, so that the user terminal device 100 can communicate with the reception server device 211 to transmit an analysis request and receive an analysis result. .
  • time burden and money burden especially burden of a mailing cost
  • the reception server device 211 deletes information that can identify an individual such as a patient's name from the analysis request received from the user terminal device 100.
  • information that can identify an individual is referred to as personal identification information.
  • the process which deletes personal identification information is called anonymization. Since the reception server device 211 anonymizes the analysis request, even if information included in the analysis request such as information on a medical condition leaks, the leaked information is not linked to an individual.
  • the reception server device 211 gives a management number to the anonymized analysis request.
  • the management number here is an identification number for identifying a patient. This management number is used to anonymize the analysis request and analysis result information.
  • the reception server device 211 simply anonymizes the information, even if the blood flow analysis system 200 (medical data file database device 222) stores the information of the analysis request and the analysis result, It is difficult to classify by patient. In this case, it is difficult to track how the condition of the same patient has changed over time.
  • the reception server device 211 issues a management number for each patient, and the blood flow analysis system 200 classifies and accumulates patient information for each patient according to the management number. Thereby, in the blood flow analysis system 200, it becomes possible to track how the medical condition of the same patient has changed over time. As described above, the blood flow analysis system 200 can obtain statistical data indicating changes in the medical condition over time.
  • the blood flow analysis system 200 can associate multiple types of information using management information, such as associating an analysis request and an analysis result with the same management number.
  • the item management server device 212 shown in FIG. 1 generates CFD data based on the analysis request anonymously accepted by the reception server device 211 and requests the analysis server device 240 to perform CFD calculation.
  • the item management server device 212 is configured using, for example, a computer.
  • the item management server device 212 generates a three-dimensional model such as a blood vessel from a two-dimensional tomographic image included in the analysis request.
  • the item management server device 212 generates setting condition information for the finite volume method, such as a boundary condition for performing CFD calculation by the finite volume method.
  • the item management server device 212 transmits a CFD calculation request (finite volume method calculation request) including the generated three-dimensional model and setting condition information to the analysis server device 240.
  • the accepting server device 211 is anonymizable to be connectable (anonymization and assignment of a management number)
  • the item management server device 212 Based on the information that the accepting server device 211 is anonymizable to be connectable (anonymization and assignment
  • the operator of the analysis server device 240 may be an organization other than a medical institution such as an IT (Information Technology) company. Even in such a case, the item management server device 212 generates anonymized CFD data, so that the barrier regarding personal privacy can be kept relatively low. For this reason, the reception server device 211 can request the calculation of CFD by transmitting CFD data to the analysis server device 240.
  • the user authentication database device 221 shown in FIG. 1 stores user authentication information for the reception server device 211 to perform user authentication.
  • a user who requests blood flow analysis from the blood flow analysis system 200 logs in to the blood flow analysis system 200 in order to request blood flow analysis. Therefore, the reception server device 211 performs user authentication by password authentication.
  • the user authentication database device 221 stores user authentication information in which a user name and a password are associated with each other.
  • the user terminal device 100 may transmit an analysis request including authentication information such as a user name and a password by e-mail. In this case, the user terminal device 100 reads out the authentication information from the e-mail, performs user authentication, and performs the requested analysis when the user authentication is successful.
  • the medical data file database device 222 shown in FIG. 1 stores (accumulates) information related to the patient state included in the analysis request, such as a two-dimensional tomographic image included in the analysis request, under the control of the item management server device 212.
  • the medical data file database device 222 stores information related to the patient's state in an anonymized state.
  • the medical data file database device 222 may store the analysis request itself, or may store only a part of the analysis request.
  • the analysis file database apparatus 223 shown in FIG. 1 stores (accumulates) the CFD data generated by the item management server apparatus 212 according to the control of the item management server apparatus 212.
  • the analysis file database device 223 stores the CFD data generated by the item management server device 212 in a connectable and anonymized state.
  • the analysis file database apparatus 223 may store the CFD calculation request itself to the analysis server apparatus 240 or may store only a part of the calculation request.
  • the analysis result file database device 224 shown in FIG. 1 stores (accumulates) the analysis result by the analysis server device 240 in accordance with the control of the item management server device 212.
  • the analysis result file database device 224 stores the analysis result in an anonymized state that can be connected.
  • the analysis result file database device 224 may store the analysis result itself, or may store only a part of the analysis result.
  • An operation terminal device 231 illustrated in FIG. 1 is an operator terminal device that assists the item management server device 212 in generating a CFD calculation request to the analysis server device 240. For example, by operating the operation terminal device 231, the operator cuts (deletes) branch and vein blood vessels that are not necessary for analysis from a three-dimensional model such as blood vessels generated by the item management server device 212. Thereby, the calculation amount of the analysis server apparatus 240 can be reduced.
  • the shape of the model may be inaccurate, such as a convex portion that should not originally exist due to the influence of the resolution of the original tomographic image, etc. . Therefore, the operator operates the operation terminal device 231 to shape (smooth) the three-dimensional model. Thereby, the accuracy of the three-dimensional model is improved and the accuracy of blood flow analysis is improved.
  • the operator may use the operation terminal device 231 to extract blood vessels, hearts, and the like from the two-dimensional tomographic image.
  • the item management server device 212 may automatically extract blood vessels, hearts, and the like from the two-dimensional tomographic image.
  • the diagnostic report creation terminal device 232 shown in FIG. 1 is a terminal device for a dedicated doctor of the analysis request reception system 210 to create a diagnostic report based on the simulation result (calculation result of CFD) by the analysis server device 240. .
  • the dedicated doctor of the analysis request reception system 210 adds additional information to the simulation result, such as findings when viewing the simulation result, and summarizes it as a diagnostic report.
  • the diagnostic report creation terminal device 232 is not essential for the analysis request receiving system 210. That is, the analysis request reception system 210 may be configured not to include the diagnostic report creation terminal device 232.
  • the analysis server device 240 shown in FIG. 1 is configured using a computer, performs CFD calculation in response to a request from the item management server device 212, and transmits (replies) the calculation result to the item management server device 212.
  • the item management server device 212 and the analysis server device 240 are communicatively connected via the Internet, and the analysis server device 240 provides the item management server device 212 with computation by a high-performance computer through a cloud service.
  • the analysis server device 240 corresponds to an example of an analysis execution unit.
  • a blood vessel space is finely divided into, for example, a region of about 1 million to 2 million, for example, with a tetrahedral mesh.
  • a blood pressure is set at the entrance of the three-dimensional model, and a resistance value for blood flow is set at the exit.
  • the inlet and outlet referred to here are the inlet and outlet of blood flow in the three-dimensional model, respectively. Both the entrance and the exit correspond to the boundary of the 3D model.
  • equations based on physical laws such as a flow rate conservation law and a momentum conservation law are set.
  • the item management server device 212 performs mesh division of the blood space and sets these equations and conditions.
  • the analysis server device 240 calculates a blood flow that satisfies the set equation and the set condition. For example, the analysis server device 240 repeats the calculation of the blood flow velocity and blood pressure for each mesh until an error with respect to a given condition becomes equal to or less than a predetermined error.
  • the pattern of the blood flow in each mesh is obtained.
  • the analysis server device 240 may execute a simulation of blood flow analysis in real time, and the user terminal device 100 may display a moving image of the simulation result in real time.
  • FIG. 2 is a schematic block diagram showing a functional configuration of the reception server device 211 shown in FIG.
  • the reception server device 211 includes a first communication unit 310, a first storage unit 380, and a first control unit 390.
  • the first control unit 390 includes a user authentication unit 391 and an anonymization processing unit 392.
  • the first communication unit 310 communicates with other devices.
  • the first communication unit 310 communicates with the user terminal device 100 via the communication network 900 and receives an analysis request (a blood flow analysis request) from the user terminal device 100.
  • the first communication unit 310 corresponds to an example of an analysis request receiving unit.
  • the first communication unit 310 transmits a diagnostic report of an answer to the analysis request to the user terminal device 100 that is the request source.
  • the first communication unit 310 communicates with the user authentication database device 221 to register and read information for user authentication.
  • the first communication unit 310 communicates with the item management server device 212 and transmits the connection request anonymized analysis request to the item management server device 212. Further, the first communication unit 310 receives a diagnostic report of an answer to the analysis request from the item management server device 212.
  • the first storage unit 380 is configured using a storage device provided in the reception server device 211 and stores various types of information.
  • the first storage unit 380 stores patient identification information and a management number in association with each other. Accordingly, when the first communication unit 310 receives an analysis request of a patient that has been analyzed by the blood flow analysis system 200 in the past, the reception server device 211 (anonymization processing unit 392) The same management number as in the above can be assigned to the analysis request. Thereby, the reception server device 211 can realize connectable anonymization.
  • the 1st control part 390 controls each part of the reception server apparatus 211, and performs various functions.
  • the first control unit 390 is realized by, for example, a CPU (Central Processing Unit) provided in the reception server device 211 reading and executing a program from the first storage unit 380.
  • the user authentication unit 391 performs user authentication when receiving a blood flow analysis request from the user terminal device 100.
  • the user authentication unit 391 performs password authentication based on the user name and password included in the analysis request (blood flow analysis request) and the user authentication information stored in the user authentication database device 221. Perform user authentication.
  • the anonymization processing unit 392 anonymizes the analysis request received by the first communication unit 310. Specifically, the anonymization processing unit 392 deletes the personal identification information from the analysis request. Moreover, the anonymization processing unit 392 gives the above-described management number to the anonymized analysis request. Thereby, the reception server device 211 can anonymize the analysis request to be connectable.
  • FIG. 3 is a schematic block diagram showing a functional configuration of the item management server device 212 shown in FIG.
  • the item management server device 212 includes a second communication unit 410, a second storage unit 480, and a second control unit 490.
  • the second control unit 490 includes a model generation unit 491, a preprocessing unit 492, a simulation request processing unit 493, and a diagnosis report processing unit 494.
  • the second communication unit 410 communicates with other devices.
  • the second communication unit 410 communicates with the reception server device 211 and receives the connection request anonymized analysis request from the reception server device 211.
  • the second communication unit 410 transmits a diagnostic report of a response to the analysis request to the reception server device 211.
  • the second communication unit 410 communicates with the medical data file database device 222 and stores (accumulates) the analysis request from the user terminal device 100 in the medical data file database device 222.
  • the second communication unit 410 communicates with the analysis file database device 223 to store (accumulate) the CFD data in the analysis file database device 223.
  • the second communication unit 410 communicates with the analysis result file database device 224 and stores (accumulates) the analysis result by the analysis server device 240 in the analysis result file database device 224.
  • the second communication unit 410 communicates with the operation terminal device 231, and displays information indicating user operations (operations by an operator) for generating CFD calculation requests such as assistance for generating a three-dimensional model such as a blood vessel. Receive.
  • storage part 480 is comprised using the storage device with which the item management server apparatus 212 is provided, and memorize
  • the second storage unit 480 functions as a working memory of the second control unit 490, and temporarily stores a two-dimensional tomographic image included in the analysis request and a three-dimensional model such as a blood vessel.
  • the second control unit 490 realizes various functions by controlling each unit of the item management server device 212.
  • the second control unit 490 is realized by, for example, a CPU included in the item management server device 212 reading and executing a program from the second storage unit 480.
  • the model generation unit 491 generates a three-dimensional model such as a blood vessel. As described above, the model generation unit 491 may automatically generate a three-dimensional model, or based on the extraction result of blood vessels or the like from a two-dimensional tomographic image by an operator who operates the operation terminal device 231. May be generated. In addition, the model generation unit 491 corrects the three-dimensional model in accordance with the operator's operation on the operation terminal device 231. For example, the model generation unit 491 cuts branches and veins that are not necessary for the above-described analysis. The model generation unit 491 performs the above-described shaping (smoothing) of the three-dimensional model.
  • the model generation unit 491 performs the above-described shaping (smoothing) of the three-dimensional model.
  • the preprocessing unit 492 performs various settings for CFD by the finite volume method.
  • the preprocessing unit 492 corresponds to an example of a condition setting unit.
  • the preprocessing unit 492 extends the inlet and outlet (blood vessels) of the three-dimensional model. This is to reduce the influence of blood flow at the inlet and outlet of the model and stabilize the flow rate ratio.
  • the flow rate ratio changes depending on the amount of extension of the inlet and outlet of the three-dimensional model. Further, as the inlet and outlet are lengthened, the number of meshes in the finite volume method increases and the amount of calculation increases.
  • the preprocessing unit 492 extends the inlet and outlet blood vessels of the three-dimensional model by 50 times the diameter of the blood vessels.
  • the blood vessel extension performed by the preprocessing unit 492 is not necessarily strictly 50 times the diameter of the blood vessel.
  • the preprocessing unit 492 may extend the blood vessel in the range of 40 to 60 times the diameter of the blood vessel.
  • extending the inlet and outlet of the three-dimensional model is referred to as mesh extension.
  • the preprocessing unit 492 sets boundary conditions in the finite volume method.
  • the boundary conditions set by the preprocessing unit 492 will be described later.
  • the simulation request processing unit 493 requests the analysis server device 240 for blood flow simulation (blood flow analysis by CFD using a finite volume method). Specifically, the simulation request processing unit 493 generates an analysis request (simulation request) including a three-dimensional model such as a blood vessel generated by the model generation unit 491 and information indicating the conditions set by the preprocessing unit 492. And transmitted to the analysis server device 240 via the second communication unit 410.
  • an analysis request simulation request
  • simulation request including a three-dimensional model such as a blood vessel generated by the model generation unit 491 and information indicating the conditions set by the preprocessing unit 492.
  • the diagnostic report processing unit 494 creates a diagnostic report. Specifically, the diagnostic report processing unit 494 creates a diagnostic report based on a specialist's operation on the diagnostic report creation terminal device 232.
  • the diagnosis report created by the diagnosis report processing unit 494 includes various information according to the analysis request from the user terminal device 100. For example, the diagnostic report processing unit 494 may create a diagnostic report including a hemodynamic evaluation index value such as WSS or blood flow energy loss. Or the diagnostic report process part 494 may produce the diagnostic report containing the statistical data regarding the time change of the condition of a blood flow. Alternatively, the diagnostic report processing unit 494 may create a diagnostic report including the result of virtual surgery. For example, the user terminal device 100 transmits an analysis request including information indicating necessary items as an analysis result.
  • the diagnosis report processing unit 494 generates a diagnosis report including information on items required for the analysis request.
  • the diagnosis report processing unit 494 corresponds to an example of an analysis result generation unit.
  • the diagnosis report corresponds to an example of the analysis result.
  • the 1st communication part 310 of the reception server apparatus 211 which transmits a diagnostic report to the user terminal device 100 corresponds to the example of an analysis result transmission part.
  • FIG. 4 is a flowchart illustrating an example of a procedure of processing performed by the reception server device 211 described in FIG.
  • the reception server device 211 starts the process of FIG.
  • the user authentication unit 391 performs user authentication based on the user information received from the user terminal device 100 by the first communication unit 310 (step S101).
  • the first communication unit 310 receives user information including a user name and a password from the user terminal device 100.
  • the user authentication unit 391 performs password authentication using the user name and password received by the first communication unit 310.
  • the user authentication unit 391 determines whether or not the user authentication is successful in step S101 (step S102).
  • the anonymization process part 392 When it determines with having succeeded in authentication (step S102: YES), the anonymization process part 392 performs the anonymization process which deletes personal identification information (information which can identify individuals, such as a name) from patient information (step S111). ).
  • the anonymization processing unit 392 gives a management number to the anonymized patient information (step S112).
  • the management number here is an identification number for identifying a patient. This management number is used to anonymize patient information.
  • the patient information is simply anonymized, it is difficult to classify the stored patient information for each patient even if the medical data file database device 222 stores the patient information. For this reason, it is difficult to track how the same patient's medical condition has changed over time.
  • the medical data file database device 222 stores (accumulates) patient information and management numbers in association with each other, the accumulated patient information can be classified for each patient. Therefore, it becomes possible to track how the medical condition of the same patient has changed over time.
  • the anonymization processing unit 392 assigns the management number to the patient information and anonymizes the information so that statistical data indicating changes in the medical condition with time can be obtained.
  • patient information stored in the medical data file database device 222, information on the three-dimensional model of blood vessels stored in the analysis file database device 223, and analysis result information stored in the analysis result file database device 224 are stored for each patient. Can be associated. In this way, a plurality of types of information can be associated using management information.
  • the medical data file database device 222, the analysis file database device 223, and the analysis result file database device 224 are all at least of the information included in the analysis request, the simulation result, and the information included in the analysis result based on the simulation result. One of them is stored for each person to be analyzed based on the management number.
  • the medical data file database device 222, the analysis file database device 223, and the analysis result file database device 224 all correspond to examples of the time information storage unit.
  • the diagnosis report processing unit 494 indicates the prediction of the blood flow situation such as the future risk of aneurysm rupture based on the analysis result stored (accumulated) in time series by the analysis result file database device 224, for example. Generate diagnostic reports with information.
  • the anonymization processing unit 392 assigns a management number to each patient. Specifically, when the first communication unit 310 receives patient information, the anonymization processing unit 392 determines whether the first communication unit 310 has received patient information of the same patient in the past. judge. When it is determined that the patient information of the same patient has been received in the past, the anonymization processing unit 392 assigns the same management number as the management number issued to the patient to the current patient information (first communication unit 310). To the patient information received this time). On the other hand, when it is determined that the patient information of the same patient has not been received in the past, the anonymization processing unit 392 issues a new management number, and uses the issued new management number as the current patient information. Give.
  • the analysis request reception system 210 (for example, the first storage unit 380) A management number may be stored in association with each other.
  • the anonymization processing unit 392 issues a new management number in step S112
  • the issued management number and the personal identification information deleted in step S111 are associated with each other and stored in the first storage unit 380.
  • the anonymization processing unit 392 extracts the personal identification information from the patient information in step S111, and deletes the extracted personal identification information from the patient information.
  • the anonymization processing unit 392 determines whether or not the personal identification information extracted in step S111 is already stored in association with the management number, so that the first communication unit 310 has the same patient in the past. It is determined whether or not patient information has been received.
  • step S112 the first control unit 390 transmits the information of the anonymized patient connectable in step S112 to the item management server device 212 via the first communication unit 310 (step S113).
  • step S102: NO the user authentication unit 391 notifies the user of the request source via the first communication unit 310 that the user authentication has failed. It transmits to the terminal device 100 (step S121). After step S121, the process of FIG. 4 ends.
  • FIG. 5 is a flowchart illustrating an example of a procedure of processing performed by the item management server apparatus 212 described with reference to FIG.
  • the item management server device 212 starts the process of FIG. 5 when the second communication unit 410 receives the patient information transmitted by the reception server device 211 in step S113 of FIG.
  • the second control unit 490 stores the patient information received by the second communication unit 410 in the medical data file database device 222 (step S201). Specifically, the second control unit 490 transmits an instruction to store patient information and patient information to be stored (patient information received by the second communication unit 410) via the second communication unit 410. Transmit to the file database device 222.
  • the model generation unit 491 generates a three-dimensional model of the blood vessel based on the tomographic image (CT image or MRI image) included in the patient information (step S202).
  • the preprocessing unit 492 performs preprocessing such as setting of analysis conditions (step S203).
  • the model generation unit 491 stores the three-dimensional blood vessel model generated in step S202 in the analysis file database device 223 (step S204). Specifically, the model generation unit 491 sends an instruction to store the three-dimensional model and a file of the three-dimensional model to be stored (data file indicating the three-dimensional model of the blood vessel generated in step S202) to the second communication unit.
  • the data is transmitted to the analysis file database apparatus 223 via 410.
  • the simulation request processing unit 493 transmits a blood flow analysis request to the analysis server device 240 (step S205). Specifically, the simulation request processing unit 493 analyzes the blood flow based on the three-dimensional model of the blood vessel generated by the model generation unit 491 in step S202, the file indicating the analysis conditions set in step S203, and the information to be transmitted. Is transmitted to the analysis server device 240 via the second communication unit 410.
  • the analysis server device 240 performs blood flow analysis (blood flow simulation) using the finite volume method based on the obtained information. Specifically, the space is divided into regular tetrahedral meshes. Then, an equation indicating the relationship between meshes is established using a law such as a flow rate conservation law, and the calculation is repeated until the boundary condition is met (until the magnitude of the error falls below a predetermined allowable value). As described above, the item management server device 212 performs space mesh division and simultaneous equations and boundary condition setting. And the analysis server apparatus 240 performs a calculation.
  • the simulation request processing unit 493 stores the analysis result in the analysis result file database device 224 (step S207). Specifically, the simulation request processing unit 493 sends an instruction to store the analysis result and the analysis result to be stored (the analysis result received by the second communication unit 410 in step S206) via the second communication unit 410. To the analysis result file database device 224.
  • the simulation request processing unit 493 creates a diagnostic report based on a user operation on the diagnostic report creation terminal device 232 (step S208). Then, the simulation request processing unit 493 transmits the created diagnostic report to the requesting user terminal device 100 (step S209). Specifically, the simulation request processing unit 493 transmits the diagnostic report created in step S208 to the reception server device 211 via the second communication unit 410. Then, the reception server device 211 transmits (transfers) the received diagnostic report to the requesting user terminal device 100. After step S209, the process of FIG.
  • the preprocessing unit 492 sets a boundary condition based on the reflected wave.
  • blood pressure is classified into incident waves and reflected waves as shown in Equation (1).
  • the value P indicates a blood pressure measurement value (measurement pressure).
  • the value P for indicates the incident wave.
  • the value P ref indicates the reflected wave.
  • the incident wave P for simulates the pressure due to the energy of pulsation.
  • the reflected wave Pref simulates pressure return (reflection) from peripheral blood vessels and the like.
  • the incident wave P for is defined as shown in Equation (2).
  • the value Q indicates the blood flow rate.
  • the value Z 0 indicates impedance.
  • the impedance here is a value obtained by dividing blood pressure by blood flow. Impedance quantitatively indicates the difficulty of blood flow (the magnitude of resistance to blood flow). Also, the reflected wave Pref is defined as shown in Equation (3).
  • Impedance Z 0 is determined according to PQ loop.
  • FIG. 6 is an explanatory diagram showing an example of a PQ loop.
  • the horizontal axis of the graph shown in the figure indicates the blood flow volume passing through the aorta.
  • the vertical axis indicates the pressure at that portion.
  • the line L11 the pressure increases and the flow rate increases early in the systole of the heart. In the early part of this systole, the reflected wave does not return again.
  • the inclination “dP / dQ” in the early stage of the systole of the heart is used as the impedance Z 0 . This inclination is indicated by the inclination of the line L12.
  • the impedance obtained here may be used as a resistance value in a ramped parameter method for simulating blood flow with an electric circuit.
  • the preprocessing unit 492 sets a variable impedance based on the actual measurement.
  • the fluctuation impedance here is an impedance whose value fluctuates with time (specifically, an impedance whose value fluctuates in accordance with the heartbeat phase).
  • the preprocessing unit 492 sets the impedance Z (t) according to Expression (4).
  • the value P (t) indicates the measured pressure waveform (blood pressure at each time).
  • the value Q (t) indicates a flow waveform (blood flow volume at each time).
  • the steady venous pressure is a blood pressure in the venous portion.
  • equation (4) a pressure difference obtained by subtracting the steady venous pressure from the pressure waveform is used in order to accurately obtain the pressure difference of the capillaries.
  • the value “P (t) ⁇ steady venous pressure” indicates the pressure applied to the capillary portion.
  • a pressure of this value “P (t) ⁇ steady venous pressure” is required.
  • the resistance in the capillary is obtained by dividing the value “P (t) ⁇ steady venous pressure” by the flow rate.
  • the preprocessing unit 492 sets a variable impedance in consideration of myocardial viability and myocardial perfusion.
  • the viability of the myocardium is the rate at which myocardial cells are alive.
  • the preprocessing unit 492 obtains a variable impedance based on the perfusion region of the myocardium for each coronary artery and the viability of the myocardium in the perfusion region.
  • the preprocessing unit 492 estimates a perfusion area from the CT image.
  • the preprocessing unit 492 divides the myocardial region into the nearest perfusion region for each coronary artery. Then, the preprocessing unit 492 calculates the volume of the myocardium in the perfusion region, and obtains the impedance to the blood flow based on the obtained volume and the viability of the myocardium. For example, the preprocessing unit 492 modifies the fluctuation width and average value of the fluctuation impedance based on the myocardial volume and viability, and obtains the impedance for each branch of the coronary artery. Thereby, it becomes possible to obtain
  • the preprocessing unit 492 sets the exit boundary condition according to the presence or absence of stenosis of the blood vessel in the three-dimensional model and the influence of the stenosis on the blood flow. Specifically, the preprocessing unit 492 or the operator (user of the operation terminal device 231) determines whether or not there is stenosis and whether or not the influence of stenosis on the blood flow can be ignored.
  • the preprocessing unit 492 automatically performs the above determination, for example, the determination is performed based on image analysis on a two-dimensional tomographic image to be analyzed for blood flow.
  • the preprocessing unit 492 has a region in the blood vessel having a predetermined length or less (for example, 1 centimeter or less), and the diameter of the narrowest part is equal to the diameter of any end of the region.
  • a predetermined first ratio or less for example, 90% or less
  • the preprocessing unit 492 locally performs a blood flow analysis on, for example, a region determined to have stenosis.
  • the preprocessing unit 492 calculates that the pressure behind the stenosis is a predetermined second ratio or less (for example, 80% or less) with respect to the pressure before the stenosis, the influence of the stenosis on the blood flow cannot be ignored. Is determined.
  • the preprocessing unit 492 calculates the outlet pressure including the reflected wave by the above method and sets it as the outlet boundary condition. The same applies when the preprocessing unit 492 or the operator determines that the influence of stenosis can be ignored. On the other hand, when the preprocessing unit 492 or the operator determines that the influence of the stenosis cannot be ignored, the preprocessing unit 492 calculates the fluctuation impedance on the external side of the model viewed from the exit boundary by the above method, and the exit boundary condition Set as.
  • FIG. 7 is an explanatory diagram showing an example of the internal pressure of the aorta.
  • the horizontal axis of the graph shown in the figure represents time, and the vertical axis represents pressure.
  • the pressure overshoots.
  • the pressure undershoots In the area A11, the pressure overshoots.
  • the pressure undershoots In the area A12, the pressure undershoots.
  • This large change in blood pressure is considered to be a simulation error caused by simulating a blood vessel wall, which is an elastic body, with a rigid body wall.
  • a waveform similar to this sudden change in pressure was obtained.
  • the pressure waveform can be estimated from the inlet flow rate waveform, the relationship between the inlet flow rate and the pressure is unknown. Therefore, assuming that the equation is as shown in Equation (5), a proportionality constant is obtained according to an experiment.
  • the value k indicates a proportionality constant.
  • the value P a indicates the pressure.
  • a boundary condition is set such that the flow rate increases linearly and the flow rate decreases linearly.
  • FIG. 8 is a graph showing an example of boundary conditions set for obtaining the value of the proportionality constant k.
  • the horizontal axis of the graph shown in the figure represents time, and the vertical axis represents flow rate. According to line L21 in FIG. 8, the flow rate increases at a constant rate and then decreases at a constant rate.
  • FIG. 9 is a graph showing an example of the calculation result of the internal pressure of the aorta when the inlet flow rate of FIG. 8 is set.
  • the horizontal axis of the graph shown in FIG. 9 indicates time, and the vertical axis indicates pressure.
  • the pressure P11 is offset when the inlet flow rate is increased. This pressure P11 is considered to be a pressure due to the value dQ / dt.
  • the pressure P12 is considered to be a pressure due to the flow rate Q. Therefore, the pressure P12 is assigned to P a of formula (5), the slope of the flow rate Q is substituted into the value dQ / dt of the formula (5). As a result, the value of the proportionality constant k can be obtained.
  • the preprocessing unit 492 sets the outlet pressure as shown in Expression (6) using the obtained proportionality constant k.
  • the value Pout indicates the outlet pressure.
  • the value P ref is a term of the reflected wave shown in Expression (3).
  • the term “ ⁇ k ⁇ (dQ / dt)” is a term for canceling the rapid increase and decrease in blood pressure described above.
  • the value “k ⁇ (dQ / dt)” corresponds to an example of a value proportional to the derivative of the blood inlet flow rate.
  • the preprocessing unit 492 sets boundary conditions corresponding to blood flow adjustment by the autonomic nerve.
  • the blood flow amount flowing through the upper body and the lower body is adjusted by the autonomic nerve.
  • the autonomic nerve causes blood flow to flow toward the head by closing the muscles of the blood vessels and controlling the flow rate so that blood does not flow too much in the lower body.
  • the preprocessing unit 492 sets the outlet pressure represented by Expression (7) in order to simulate the adjustment of blood flow by the autonomic nerve.
  • the value Pout indicates the outlet pressure.
  • the value P INER, outlet pressure P out of the equation (6) is substituted.
  • H represents a snake site function.
  • the value of the term “Q out ⁇ Q in ” is positive, the value of the heavy site function H (Q out ⁇ Q in ) is “1”.
  • the value of the term “Q out ⁇ Q in ” is zero, the value of the heavy site function H (Q out ⁇ Q in ) is “1 ⁇ 2”.
  • the value of the term “Q out ⁇ Q in ” is negative, the value of the heavy site function H (Q out ⁇ Q in ) is “0”.
  • the values Q out and Q in indicate the outlet flow rate and the inlet flow rate, respectively.
  • the value K is a constant.
  • the value of the constant K is set empirically, for example.
  • the pressure is increased by the amount of backflow according to the equation (7).
  • the snake site function H may be offset.
  • the reception server device 211 provides an input screen to the user terminal device 100.
  • the reception server device 211 (first control unit 390) provides an input screen in which default values are input to these input items. By using this default value without changing it, the user can request blood flow analysis without having to set complicated numerical values.
  • the reception server device 211 (first control unit 390) provides an input screen for each pattern of blood flow analysis such as coronary artery or aortic stenosis. Thereby, the reception server device 211 can provide an appropriate default value for each pattern of blood flow analysis.
  • the user can grasp necessary input items according to the pattern of blood flow analysis.
  • the preprocessing unit 492 sets either the inlet flow rate or the inlet pressure as the inlet boundary condition based on whether the inlet flow rate is known.
  • the preprocessing unit 492 may automatically determine whether the inlet flow rate is known or may be determined by an operator (user of the operation terminal device 231).
  • the preprocessing unit 492 determines, for example, whether the analysis request from the user terminal device 100 includes blood flow information corresponding to the inlet flow rate. By determining, it is determined whether or not the inlet flow rate is known. When it is determined that the inlet flow rate is known (that is, when it is determined that blood flow information corresponding to the inlet flow rate is included in the analysis request), the preprocessing unit 492 sets the blood flow rate as the inlet flow rate. To do. On the other hand, when it is determined that the inlet flow rate is unknown (that is, when it is determined that blood flow information corresponding to the inlet flow rate is not included in the analysis request), the preprocessing unit 492 displays the blood pressure corresponding to the inlet pressure. Is read from the analysis request and set as the inlet pressure.
  • the preprocessing unit 492 sets the inlet flow rate as the inlet boundary condition when the inlet flow rate is known.
  • the preprocessing unit 492 sets the inlet pressure as the inlet boundary condition.
  • the first communication unit 310 of the reception server device 211 receives an analysis request including a two-dimensional tomographic image to be analyzed for blood flow from the user terminal device 100 via the communication network 900. Then, the anonymization processing unit 392 deletes information specifying the analysis target person from the analysis request, and assigns a management number for identifying the analysis target person.
  • the analysis server device 240 generates a three-dimensional model of the blood vessel shape based on the two-dimensional tomographic image. Then, the preprocessing unit 492 performs finite volume method condition setting for blood flow simulation based on the three-dimensional model.
  • the simulation request processing unit 493 generates a simulation request (a blood flow analysis request) including the conditions set by the 3D model and the preprocessing unit 492 and the management number.
  • the analysis server device 240 performs blood flow simulation by a fluid analysis method using a finite volume method based on the simulation request.
  • the diagnosis report processing unit 494 generates an analysis result based on the simulation result by the simulation request processing unit 493. Then, the first communication unit 310 transmits the analysis result to the request source based on the management number.
  • the anonymization processing unit 392 deletes information for identifying the analysis target person from the analysis request, and assigns a management number for each analysis countermeasure, so that information included in the analysis request such as information on a medical condition is leaked. Even if you do, the leaked information is not tied to the individual.
  • blood flow analysis can be requested in consideration of patient privacy.
  • the database group of the medical data file database device 222, the analysis file database device 223, and the analysis result file database device 224 includes information included in the analysis request, simulation results, and information included in the analysis results based on the simulation results. At least one of them is stored for each person to be analyzed based on the management number. Then, the diagnosis report processing unit 494 generates an analysis result including information indicating the prediction of the blood flow state based on the information stored in the database group. As described above, the database group stores information for each person to be analyzed based on the management number, so that statistical data can be obtained regarding the temporal change in the blood flow state.
  • the 1st communication part 310 receives the analysis request containing the information which shows the content of the operation regarding blood flow. Then, the diagnosis report processing unit 494 generates an analysis result including information indicating a blood flow state when an operation is performed with the content of the operation. Thereby, a user (for example, a doctor in charge performing an operation) can confirm in advance whether or not the planned operation is appropriate.
  • the preprocessing unit 492 extends at least one of the inlet and outlet blood vessels in the three-dimensional model. Thereby, the preprocessing unit 492 can reduce the influence of blood flow at the entrance and exit of the three-dimensional model, and can improve the accuracy of blood flow analysis.
  • the preprocessing unit 492 sets an outlet pressure including a reflected wave of blood pressure. Accordingly, even when at least one of the inlet and outlet blood vessels in the three-dimensional model is extended, the preprocessing unit 492 can set an appropriate boundary condition. Thereby, the preprocessing unit 492 can improve the accuracy of blood flow analysis.
  • the preprocessing unit 492 determines that there is no stenosis in the blood vessel in the three-dimensional model in the analysis of the coronary artery and determines that the influence of the stenosis on the blood flow can be ignored.
  • the preprocessing unit 492 sets a variable impedance (impedance whose value varies with time) at the exit boundary of the three-dimensional model. Thereby, the preprocessing unit 492 can perform blood flow analysis more accurately regardless of the presence or absence of stenosis of blood vessels.
  • the preprocessing unit 492 performs correction to subtract a value proportional to the derivative of the inlet flow rate of the blood flow from the outlet pressure. Thereby, the preprocessing unit 492 can simulate the elasticity of the blood vessel wall, and in this respect, the accuracy of blood flow analysis can be improved.
  • the preprocessing unit 492 sets an outlet pressure simulating blood flow adjustment by the autonomic nerve using a snake sight function.
  • the preprocessing unit 492 can improve the accuracy of blood flow analysis by simulating blood flow adjustment by the autonomic nerve.
  • the preprocessing unit 492 determines that the flow rate at the inlet boundary of the three-dimensional model is known, the preprocessing unit 492 sets the inlet flow rate of the blood flow as the inlet boundary condition. On the other hand, when determining that the flow rate at the inlet boundary is unknown, the preprocessing unit 492 sets the inlet pressure of the blood flow as the inlet boundary condition. Thereby, the preprocessing unit 492 can perform blood flow analysis more accurately regardless of whether or not the flow rate at the inlet boundary is known.
  • FIG. 10 is a schematic block diagram showing the minimum configuration of the blood flow analysis system according to the embodiment.
  • the blood flow analysis system 10 includes an analysis request receiving unit 11, an anonymization processing unit 12, a model generation unit 13, a condition setting unit 14, a simulation request processing unit 15, and an analysis execution unit. 16, an analysis result generation unit 17, and an analysis result transmission unit 18.
  • the analysis request receiving unit 11 receives an analysis request including a two-dimensional tomographic image to be analyzed for blood flow via a communication network.
  • the anonymization processing unit 12 deletes information for specifying the analysis target person from the analysis request and assigns a management number for identifying the analysis target person.
  • the model generation unit 13 generates a three-dimensional model of the blood vessel shape based on the two-dimensional tomographic image.
  • the condition setting unit 14 sets conditions for a finite volume method for blood flow simulation based on a three-dimensional model.
  • the simulation request processing unit 15 generates a simulation request including the conditions set by the three-dimensional model and condition setting unit 14 and a management number.
  • the analysis execution unit 16 performs a blood flow simulation by a fluid analysis method using a finite volume method based on the simulation request.
  • the analysis result generation unit 17 generates an analysis result based on the simulation result by the analysis execution unit 16.
  • the analysis result transmission unit 18 transmits the analysis result to the request source based on the management number.
  • the anonymization processing unit 12 deletes information for identifying the person to be analyzed from the analysis request, and assigns a management number for each analysis countermeasure. Thereby, even if information included in the analysis request such as medical condition information is leaked, the leaked information is not linked to an individual.
  • the blood flow analysis system 10 can request blood flow analysis in consideration of patient privacy.
  • FIG. 11 is a schematic block diagram showing the minimum configuration of the analysis request receiving system according to the embodiment.
  • the analysis request receiving system 20 includes an analysis request receiving unit 21, an anonymization processing unit 22, a model generation unit 23, a condition setting unit 24, a simulation request processing unit 25, and an analysis result generation.
  • Unit 26 and an analysis result transmitting unit 27.
  • the analysis request receiving unit 21 receives an analysis request including a two-dimensional tomographic image to be analyzed for blood flow via a communication network.
  • the anonymization processing unit 22 deletes information for identifying the analysis target person from the analysis request and assigns a management number for identifying the analysis target person.
  • the model generation unit 23 generates a three-dimensional model of the blood vessel shape based on the two-dimensional tomographic image.
  • the condition setting unit 24 sets conditions for the finite volume method for blood flow simulation based on the three-dimensional model.
  • the simulation request processing unit 25 generates a simulation request including the conditions set by the three-dimensional model and condition setting unit 24 and the management number.
  • the analysis result generation unit 26 generates an analysis result based on the result of the blood flow simulation performed by the fluid analysis method using the finite volume method based on the simulation request.
  • the analysis result transmission unit 27 transmits the analysis result to the request source based on the management number.
  • the anonymization processing unit 22 deletes information for identifying the person to be analyzed from the analysis request, and assigns a management number for each analysis countermeasure.
  • the analysis request reception system 20 it is possible to request blood flow analysis in consideration of patient privacy.
  • the blood flow analysis systems 10 and 200 and the analysis request reception system 20 can be realized by the CPU reading and executing the program.
  • a program for realizing this function may be recorded on a computer-readable recording medium, and the program recorded on this recording medium may be read into a computer system and executed.
  • the “computer system” includes an OS and hardware such as peripheral devices.
  • the “computer-readable recording medium” refers to a storage device such as a flexible medium, a magneto-optical disk, a portable medium such as a ROM or a CD-ROM, and a hard disk incorporated in a computer system.
  • the program may be a program for realizing a part of the above-described functions, and may be a program capable of realizing the functions described above in combination with a program already recorded in a computer system.
  • blood flow analysis can be requested in consideration of patient privacy.
  • DESCRIPTION OF SYMBOLS 100 User terminal device 10, 200 Blood flow analysis system 11, 21 Analysis request receiving part 12, 22, 392 Anonymization processing part 13, 23, 491 Model generation part 14, 24 Condition setting part 15, 25, 493 Simulation request process Unit 16 analysis execution unit 17, 26 analysis result generation unit 18, 27 analysis result transmission unit 20, 210 analysis request reception system 211 reception server device 310 first communication unit 380 first storage unit 390 first control unit 391 user authentication unit 212 Item management server device 410 Second communication unit 480 Second storage unit 490 Second control unit 492 Preprocessing unit 494 Diagnostic report processing unit 221 User authentication database device 222 Medical data file database device 223 Analysis file database device 224 Analysis result Phi Database system 231 operation terminal 232 diagnostic report creation terminal unit 240 analyzes the server device 900 a communication network

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Abstract

This blood flow analysis system is provided with: an analysis request receiving unit which receives an analysis request including a two-dimensional tomographic image of a blood flow analysis target via a communication network; an anonymization processing unit which deletes information specifying the subject of the analysis from the analysis request, and assigns a management number to identify the subject of the analysis; a model generating unit which generates a three-dimensional model of the shape of blood vessels on the basis of the two-dimensional tomographic image; a condition setting unit which sets finite volume method conditions to be used in a simulation of the blood flow based on the three-dimensional model; a simulation request processing unit which generates a simulation request including the three-dimensional model, the conditions set by the condition setting unit, and the management number; an analysis execution unit which performs the blood flow simulation using a fluid analysis technique employing said finite volume method, on the basis of the simulation request; an analysis result generating unit which generates an analysis result based on a simulation result obtained by the analysis execution unit; and an analysis result transmitting unit which transmits the analysis result to a requesting party on the basis of the management number.

Description

血流解析システム、解析依頼受付システム、血流解析方法及びプログラムBlood flow analysis system, analysis request reception system, blood flow analysis method and program
 本発明は、血流解析システム、解析依頼受付システム、血流解析方法及びプログラムに関する。 The present invention relates to a blood flow analysis system, an analysis request reception system, a blood flow analysis method, and a program.
 患者の血流を解析する方法の1つに、解析対象の三次元モデルを用いて解析を行う方法がある。
 例えば、特許文献1には、患者の心臓の少なくとも一部を表す三次元モデルを作成し、作成した三次元モデルに基づいて患者の心臓内の冠血流予備量比を特定する手法が記載されている。
One method for analyzing a patient's blood flow is to perform analysis using a three-dimensional model to be analyzed.
For example, Patent Literature 1 describes a method of creating a three-dimensional model representing at least a part of a patient's heart and identifying a coronary flow reserve ratio in the patient's heart based on the created three-dimensional model. ing.
特表2013-534154号公報Special table 2013-534154 gazette
 解析対象の三次元モデルを用いての血流の解析を高精度に行おうとすると、高度な解析技術及び高性能なコンピュータが必要になる。そこで、解析結果を必要とする医師等が他者に解析を依頼することが考えられる。ところが、他者に解析を依頼する場合、患者のプライバシーに対する配慮が問題となり得る。 In order to analyze the blood flow using the 3D model to be analyzed with high accuracy, advanced analysis technology and a high-performance computer are required. Therefore, it is conceivable that a doctor or the like who needs the analysis result requests an analysis from another person. However, consideration of patient privacy can be a problem when requesting analysis from others.
 本発明は、上述の課題を解決することのできる血流解析システム、解析依頼受付システム、血流解析方法及びプログラムを提供することを目的としている。 An object of the present invention is to provide a blood flow analysis system, an analysis request reception system, a blood flow analysis method, and a program that can solve the above-described problems.
 本発明の第1の態様によれば、血流解析システムは、血流解析対象の二次元断層画像を含む解析依頼を通信ネットワークを介して受信する解析依頼受信部と、前記解析依頼から解析対象者を特定する情報を削除し、前記解析対象者を識別する管理番号を付与する匿名化処理部と、前記二次元断層画像に基づいて血管形状の三次元モデルを生成するモデル生成部と、前記三次元モデルに基づく血流のシミュレーションに用いられる有限体積法の条件を設定する条件設定部と、前記三次元モデル、前記条件設定部が設定した前記条件、及び、前記管理番号を含むシミュレーション依頼を生成するシミュレーション依頼処理部と、前記シミュレーション依頼に基づいて、前記有限体積法を用いた流体解析手法によって前記血流のシミュレーションを行う解析実行部と、前記解析実行部によるシミュレーション結果に基づく解析結果を生成する解析結果生成部と、前記解析結果を前記管理番号に基づいて依頼元へ送信する解析結果送信部と、を備える。 According to the first aspect of the present invention, the blood flow analysis system includes an analysis request receiving unit that receives an analysis request including a two-dimensional tomographic image to be analyzed for blood flow via a communication network, and an analysis target from the analysis request. An anonymization processing unit that deletes information for identifying a person and assigns a management number for identifying the analysis subject, a model generation unit that generates a three-dimensional model of a blood vessel shape based on the two-dimensional tomographic image, A condition setting unit for setting a finite volume method condition used for blood flow simulation based on a three-dimensional model, a simulation request including the three-dimensional model, the condition set by the condition setting unit, and the management number Based on the simulation request processing unit to be generated and the simulation request, the blood flow simulation is performed by the fluid analysis method using the finite volume method. It comprises a analyzing unit for performing an analysis result generation unit that generates an analysis result based on the simulation result by the analyzing unit, and a analysis result transmitting unit that transmits to the requester on the basis of the management number of the analysis results.
 本発明の第2の態様によれば、解析依頼受付システムは、血流解析対象の二次元断層画像を含む解析依頼を通信ネットワークを介して受信する解析依頼受信部と、前記解析依頼から解析対象者を特定する情報を削除し、前記解析対象者を識別する管理番号を付与する匿名化処理部と、前記二次元断層画像に基づいて血管形状の三次元モデルを生成するモデル生成部と、前記三次元モデルに基づく血流のシミュレーションに用いられる有限体積法の条件を設定する条件設定部と、前記三次元モデル、前記条件設定部が設定した前記条件、及び、前記管理番号を含むシミュレーション依頼を生成するシミュレーション依頼処理部と、前記シミュレーション依頼に基づいて、前記有限体積法を用いた流体解析手法によって行われた前記血流のシミュレーションの結果に基づく解析結果を生成する解析結果生成部と、前記解析結果を前記管理番号に基づいて依頼元へ送信する解析結果送信部と、を備える。 According to the second aspect of the present invention, an analysis request receiving system includes an analysis request receiving unit that receives an analysis request including a two-dimensional tomographic image to be analyzed for blood flow via a communication network, and an analysis target from the analysis request. An anonymization processing unit that deletes information for identifying a person and assigns a management number for identifying the analysis subject, a model generation unit that generates a three-dimensional model of a blood vessel shape based on the two-dimensional tomographic image, A condition setting unit for setting a finite volume method condition used for blood flow simulation based on a three-dimensional model, a simulation request including the three-dimensional model, the condition set by the condition setting unit, and the management number A simulation request processing unit to be generated; and a blood flow stain performed by a fluid analysis method using the finite volume method based on the simulation request. Comprising an analysis result generation unit that generates an analysis result based on the result of the translation, and the analysis result transmitting unit that transmits to the request source based on the analysis result to the management number.
 本発明の第3の態様によれば、血流解析方法は、血流解析対象の二次元断層画像を含む解析依頼を通信ネットワークを介して受信する解析依頼受信ステップと、前記解析依頼から解析対象者を特定する情報を削除し、前記解析対象者を識別する管理番号を付与する連結可能匿名化ステップと、前記二次元断層画像に基づいて血管形状の三次元モデルを生成するモデル生成ステップと、前記三次元モデルに基づく血流のシミュレーションに用いられる有限体積法の条件を設定する条件設定ステップと、前記三次元モデル、前記条件設定ステップが設定した前記条件、及び、前記管理番号を含むシミュレーション依頼を生成するシミュレーション依頼処理ステップと、前記シミュレーション依頼に基づいて、前記有限体積法を用いた流体解析手法によって前記血流のシミュレーションを行う解析実行ステップと、前記解析実行ステップによるシミュレーション結果に基づく解析結果を生成する解析結果生成ステップと、前記解析結果を前記管理番号に基づいて依頼元へ送信する解析結果送信ステップと、を含む。 According to the third aspect of the present invention, the blood flow analysis method includes an analysis request receiving step for receiving an analysis request including a two-dimensional tomographic image to be analyzed for blood flow via a communication network, and an analysis target from the analysis request. Delete the information that identifies the person, a connectable anonymization step that assigns a management number that identifies the analysis subject, a model generation step that generates a three-dimensional model of the blood vessel shape based on the two-dimensional tomographic image, A condition setting step for setting a finite volume method condition used for blood flow simulation based on the three-dimensional model, a simulation request including the three-dimensional model, the condition set by the condition setting step, and the management number And a simulation request processing step for generating a fluid analysis method using the finite volume method based on the simulation request. An analysis execution step for performing simulation of the blood flow, an analysis result generation step for generating an analysis result based on the simulation result by the analysis execution step, and an analysis result for transmitting the analysis result to the request source based on the management number A transmission step.
 本発明の第4の態様によれば、プログラムは、コンピュータに、血流解析対象の二次元断層画像を含む解析依頼を通信ネットワークを介して受信する解析依頼受信ステップと、前記解析依頼から解析対象者を特定する情報を削除し、前記解析対象者を識別する管理番号を付与する連結可能匿名化ステップと、前記二次元断層画像に基づいて血管形状の三次元モデルを生成するモデル生成ステップと、前記三次元モデルに基づく血流のシミュレーションに用いられる有限体積法の条件を設定する条件設定ステップと、前記三次元モデル、前記条件設定ステップが設定した前記条件、及び、前記管理番号を含むシミュレーション依頼を生成するシミュレーション依頼処理ステップと、前記シミュレーション依頼に基づいて、前記有限体積法を用いた流体解析手法によって行われた前記血流のシミュレーションの結果に基づく解析結果を生成する解析結果生成ステップと、前記解析結果を前記管理番号に基づいて依頼元へ送信する解析結果送信ステップと、を実行させるためのプログラムである。 According to the fourth aspect of the present invention, the program causes the computer to receive an analysis request including a two-dimensional tomographic image to be analyzed for blood flow via a communication network, and to analyze the analysis request from the analysis request. Delete the information that identifies the person, a connectable anonymization step that assigns a management number that identifies the analysis subject, a model generation step that generates a three-dimensional model of the blood vessel shape based on the two-dimensional tomographic image, A condition setting step for setting a finite volume method condition used for blood flow simulation based on the three-dimensional model, a simulation request including the three-dimensional model, the condition set by the condition setting step, and the management number And a simulation request processing step for generating the finite volume method based on the simulation request. An analysis result generation step for generating an analysis result based on the result of the blood flow simulation performed by the fluid analysis method, and an analysis result transmission step for transmitting the analysis result to the request source based on the management number. This is a program to be executed.
 この発明によれば、患者のプライバシーに配慮して血流の解析を依頼することができる。 According to the present invention, blood flow analysis can be requested in consideration of patient privacy.
本発明の一実施形態に係る利用者端末装置の機能構成を示す概略ブロック図である。It is a schematic block diagram which shows the function structure of the user terminal device which concerns on one Embodiment of this invention. 図1に示す受付サーバ装置の機能構成を示す概略ブロック図である。It is a schematic block diagram which shows the function structure of the reception server apparatus shown in FIG. 図1に示すアイテム管理サーバ装置の機能構成を示す概略ブロック図である。It is a schematic block diagram which shows the function structure of the item management server apparatus shown in FIG. 図2で説明した受付サーバ装置が行う処理の手順の例を示すフローチャートである。It is a flowchart which shows the example of the procedure of the process which the reception server apparatus demonstrated in FIG. 2 performs. 図3で説明したアイテム管理サーバ装置が行う処理の手順の例を示すフローチャートである。It is a flowchart which shows the example of the procedure of the process which the item management server apparatus demonstrated in FIG. 3 performs. 同実施形態におけるPQループの例を示す説明図である。It is explanatory drawing which shows the example of the PQ loop in the same embodiment. 同実施形態における大動脈の内圧の例を示す説明図である。It is explanatory drawing which shows the example of the internal pressure of the aorta in the same embodiment. 同実施形態で比例定数の値を求めるために設定する境界条件の例を示すグラフである。It is a graph which shows the example of the boundary condition set in order to obtain | require the value of a proportionality constant in the same embodiment. 図8の入口流量を設定した場合の大動脈の内圧の計算結果の例を示すグラフである。It is a graph which shows the example of the calculation result of the internal pressure of the aorta when the inlet flow rate of FIG. 8 is set. 実施の形態に係る血流解析システムの最小構成を示す概略ブロック図である。It is a schematic block diagram which shows the minimum structure of the blood-flow analysis system which concerns on embodiment. 実施の形態に係る解析依頼受付システムの最小構成を示す概略ブロック図である。It is a schematic block diagram which shows the minimum structure of the analysis request reception system which concerns on embodiment.
 以下、本発明の実施形態を説明するが、以下の実施形態は請求の範囲にかかる発明を限定するものではない。また、実施形態の中で説明されている特徴の組み合わせの全てが発明の解決手段に必須であるとは限らない。
 図1は、本発明の一実施形態に係る利用者端末装置の機能構成を示す概略ブロック図である。同図に示すように、血流解析システム200は、解析依頼受付システム210と、解析サーバ装置240とを備える。解析依頼受付システム210は、受付サーバ装置211と、アイテム管理サーバ装置212と、利用者認証用データベース装置221と、医療データファイルデータベース装置222と、解析用ファイルデータベース装置223と、解析結果ファイルデータベース装置224と、オペレーション端末装置231と、診断レポート作成用端末装置232とを備える。
 また、受付サーバ装置211は、通信ネットワーク900を介して1つ以上の利用者端末装置100と通信を行う。
Hereinafter, although embodiment of this invention is described, the following embodiment does not limit the invention concerning a claim. In addition, not all the combinations of features described in the embodiments are essential for the solving means of the invention.
FIG. 1 is a schematic block diagram showing a functional configuration of a user terminal device according to an embodiment of the present invention. As shown in the figure, the blood flow analysis system 200 includes an analysis request reception system 210 and an analysis server device 240. The analysis request reception system 210 includes a reception server device 211, an item management server device 212, a user authentication database device 221, a medical data file database device 222, an analysis file database device 223, and an analysis result file database device. 224, an operation terminal device 231, and a diagnostic report creation terminal device 232.
In addition, the reception server device 211 communicates with one or more user terminal devices 100 via the communication network 900.
 利用者端末装置100は、血流解析システム200に対して血流の解析依頼を送信する。具体的には、利用者端末装置100は、血流の解析を依頼する担当医によるユーザ操作を受けて解析依頼ファイルを生成し、CT(Computed Tomography)又はMRI(Magnetic Resonance Imaging)の画像など、解析対象部分の二次元断層画像を解析依頼に含めて受付サーバ装置211へ送信する。利用者端末装置100が解析依頼に含める二次元断層画像のデータ形式として、DICOM(Digital Imaging and Communication in Medicine)データなど一般的なデータ形式を用いることができる。利用者端末装置100は、例えばコンピュータを用いて実現される。 The user terminal device 100 transmits a blood flow analysis request to the blood flow analysis system 200. Specifically, the user terminal device 100 generates an analysis request file in response to a user operation by a doctor in charge of requesting blood flow analysis, and an image of CT (Computed Tomography) or MRI (Magnetic Resonance Imaging), etc. A two-dimensional tomographic image of the analysis target portion is included in the analysis request and transmitted to the reception server device 211. As the data format of the two-dimensional tomographic image included in the analysis request by the user terminal device 100, a general data format such as DICOM (Digital Imaging and Communication in Medicine) data can be used. The user terminal device 100 is realized using a computer, for example.
 通信ネットワーク900は、利用者端末装置100と受付サーバ装置211との通信を仲介する通信ネットワークである。通信ネットワーク900は、例えばインターネットなど汎用の通信ネットワークであってもよいし、血流解析システム200専用の通信ネットワークであってもよい。以下では、通信ネットワーク900がインターネットである場合を例に説明する。 The communication network 900 is a communication network that mediates communication between the user terminal device 100 and the reception server device 211. The communication network 900 may be a general-purpose communication network such as the Internet, or may be a dedicated communication network for the blood flow analysis system 200. Hereinafter, a case where the communication network 900 is the Internet will be described as an example.
 血流解析システム200は、医師からの解析依頼を受けて患者の血流を解析するシミュレーションを行い、シミュレーション結果に基づく診断レポートを回答する。なお、ここでいう患者は、解析を受ける対象の人であり、必ずしも病状が現れている必要は無い。
 ここで、血管等の状態に対するリスクや手術の要否等を把握するためには、血管に付着したプラークの状態や心臓の大きさのみならず、血流の状態も把握することが必要になる場合がある。
The blood flow analysis system 200 performs a simulation for analyzing the blood flow of a patient in response to an analysis request from a doctor, and returns a diagnosis report based on the simulation result. In addition, the patient here is a person to be analyzed, and it is not always necessary to have a medical condition.
Here, in order to grasp the risk to the state of the blood vessel and the necessity of the operation, it is necessary to grasp not only the state of the plaque attached to the blood vessel and the size of the heart but also the state of the blood flow. There is a case.
 但し、血流の解析(以下、血流解析と称する)に用いられるCFD(Computational Fluid Dynamics、数値流体力学)は高度な技術を要する。このため、血流の状態を把握したい医師が各々CFDを用いて血流を解析することは現実的でない。また、高性能なCFD用ソフトウェアは一般的にライセンス費用が高額である。ここでいうCFDは、流体の運動を方程式で表現して演算するシミュレーションである。 However, CFD (Computational Fluid Dynamics) used for blood flow analysis (hereinafter referred to as blood flow analysis) requires advanced technology. For this reason, it is not realistic for doctors who want to know the state of blood flow to analyze blood flow using CFD. Further, high-performance CFD software generally has a high license cost. The CFD referred to here is a simulation in which the motion of the fluid is expressed by an equation.
 さらには、CFDでは複雑な演算を行う必要があり、血流解析を迅速に行うためには高性能なコンピュータを要する。例えば、患者が手術の1週間前に入院し、検査を行った場合を例示する。この場合、検査から2日程度で解析結果を得られれば、得られた結果を参照しながら手術の方法を決定し、患者に説明することができる。一方、検査から2週間後に解析結果を得られた場合、手術に間に合わない。 Furthermore, it is necessary to perform complex calculations in CFD, and a high-performance computer is required to perform blood flow analysis quickly. For example, a case where the patient is hospitalized one week before the operation and examined is illustrated. In this case, if an analysis result is obtained in about two days from the examination, the method of surgery can be determined with reference to the obtained result and explained to the patient. On the other hand, when an analysis result is obtained two weeks after the examination, it is not in time for the operation.
 そこで、図1に示す血流解析システム200は、医師からの診断依頼を受けてCFDによるシミュレーションを行い、解析結果を返信する。特に、血流解析システム200は、高性能なコンピュータを用いて1、2日程度の短期間で血流解析を行いその解析結果を返信する。これにより、診断依頼元の医師は、CFDの技術習得、CFD用ソフトウェアライセンス取得、及び、高性能なコンピュータの確保等の負担無しに解析結果を得ることができる。 Therefore, the blood flow analysis system 200 shown in FIG. 1 receives a diagnosis request from a doctor, performs a simulation by CFD, and returns an analysis result. In particular, the blood flow analysis system 200 performs a blood flow analysis in a short period of about 1 or 2 days using a high-performance computer and returns the analysis result. As a result, the doctor who requested the diagnosis can obtain the analysis results without burdens such as acquiring CFD technology, obtaining a CFD software license, and securing a high-performance computer.
 血流解析システム200は、例えば冠動脈(冠状動脈)、大動脈、脳動脈及び心臓など、血流に関する様々な部分を対象として血流解析を行う。例えば、血流解析システム200は、狭心症に対して冠動脈の血流解析を行う。また、血流解析システム200は、大動脈瘤及び大動脈解離に対して大動脈の血流解析を行う。また、血流解析システム200は、脳動脈瘤及びくも膜下出血に対して脳動脈の血流解析を行う。また、血流解析システム200は、先天性心疾患などの心奇形に対して心臓を含む血液循環の血流解析を行う。 The blood flow analysis system 200 performs blood flow analysis on various parts related to blood flow, such as coronary arteries (coronary arteries), aorta, cerebral arteries, and heart. For example, the blood flow analysis system 200 performs coronary blood flow analysis for angina pectoris. In addition, the blood flow analysis system 200 performs blood flow analysis of the aorta for aortic aneurysm and aortic dissection. In addition, the blood flow analysis system 200 performs blood flow analysis of the cerebral artery for cerebral aneurysm and subarachnoid hemorrhage. In addition, the blood flow analysis system 200 performs blood flow analysis of the blood circulation including the heart for heart deformities such as congenital heart diseases.
 また、血流解析システム200は、血流の現状評価のための情報、血流の将来の状況を予測するための情報、及び、手術を行う場合の術後の血流の状況を予測するための情報を提供する。
 ここで、血流の現状評価のための情報について説明する。
 血流の現状評価のための情報として、血流解析システム200は、例えば、血管の狭窄の重症度の評価指標値、及び、瘤の破裂リスクを示す評価指標値など、血流の現状を評価するための様々な評価指標値を算出する。
The blood flow analysis system 200 also predicts information for evaluating the current state of the blood flow, information for predicting the future state of the blood flow, and the state of the blood flow after surgery when performing surgery. Providing information.
Here, information for evaluating the current state of blood flow will be described.
As information for evaluating the current state of the blood flow, the blood flow analysis system 200 evaluates the current state of the blood flow, for example, an evaluation index value of the severity of blood vessel stenosis and an evaluation index value indicating the risk of aneurysm rupture. To calculate various evaluation index values.
 さらに例えば、血流解析システム200は、血流が血管壁に及ぼす力の強さを示すWSS(Wall Shear Stress、壁面せん断応力)、及び、血流を循環させるエネルギー効率を示す血流エネルギー損失など、血行力学的な評価指標値を算出する。
 WSSは、血管の狭窄及び破裂等のリスクを評価するための指標値となる。WSSが大きい部分では、血管に大きな負荷がかかっていることになる。一方、WSSが小さい部分では、プラークが溜まり易い可能性がある。
Further, for example, the blood flow analysis system 200 includes a WSS (Wall Shear Stress) indicating the strength of the force exerted on the blood vessel wall, a blood flow energy loss indicating energy efficiency for circulating the blood flow, and the like. The hemodynamic evaluation index value is calculated.
WSS is an index value for evaluating the risk of stenosis and rupture of blood vessels. In a portion where WSS is large, a large load is applied to the blood vessel. On the other hand, there is a possibility that plaque is likely to accumulate in a portion where WSS is small.
 また、血流エネルギー損失は、心臓の負担を評価するための指標値となる。血流エネルギー損失が大きいほど心臓の負担が大きいと考えられる。
 また、血流解析システム200がシミュレーションによって血流を算出することで、実測していない部分についてもその血圧や血流の情報を得ることができる。これにより、血圧や血流の実測の回数を減らすことができ、患者の負担を軽減させることができる。
 以下では、血流の現状評価を術前評価と称する。
The blood flow energy loss is an index value for evaluating the burden on the heart. The greater the blood flow energy loss, the greater the burden on the heart.
In addition, blood flow analysis system 200 calculates blood flow by simulation, so that blood pressure and blood flow information can be obtained even for portions that are not actually measured. Thereby, the frequency | count of measurement of a blood pressure and a blood flow can be reduced, and a patient's burden can be eased.
Hereinafter, the current evaluation of blood flow is referred to as preoperative evaluation.
 次に、血流の将来の状況を予測するための情報について説明する。
 また、血流の将来の状況を予測するための情報を提供するために、血流解析システム200は、症例のデータ(血流解析の元になる断層画像、血管等の三次元モデル、及び、解析結果のデータ等)を患者毎に、蓄積しておく。これにより、血流解析システム200は、血流の状況の時間変化に応じた統計データを得ることができる。なお、ここでいう血管等の三次元モデルとは、血管及び心臓など、血流解析の対象となる部分の三次元モデルである。
Next, information for predicting the future situation of blood flow will be described.
In addition, in order to provide information for predicting the future state of the blood flow, the blood flow analysis system 200 includes case data (a three-dimensional model such as a tomographic image, a blood vessel, etc. Analysis result data etc. are accumulated for each patient. Thereby, the blood flow analysis system 200 can obtain statistical data corresponding to the temporal change of the blood flow situation. Note that the three-dimensional model such as a blood vessel here is a three-dimensional model of a portion to be subjected to blood flow analysis, such as a blood vessel and a heart.
 ここで、例えば血管の狭窄があっても、その程度によっては必ずしも直ちに手術を行う必要は無く、経過観察等の措置が取られる場合がある。また、例えば、健康診断で冠動脈にプラークが見つかって経過観察となった場合、被健診者がどの程度のリスクがあるのかを知ることができず不安になることが考えられる。但し、血管や心臓の形状のみに基づいて、心筋梗塞等のリスクがどの程度あるのかを把握することが困難な場合がある。例えば、同様の狭窄率であっても、血管の湾曲の内側と外側とでは、シェアストレスの変動のパタンが局在するかばらつくかに違いが生じる場合がある。この違いにより、将来のリスクが大きく変わってくることが考えられる。ところが、現状では、血流の状況と将来のリスクとの関係が、詳細には明らかになっていない。 Here, for example, even if there is a stenosis of a blood vessel, depending on the degree, it is not always necessary to perform an operation immediately, and measures such as follow-up may be taken. In addition, for example, when a plaque is found in a coronary artery in a medical examination and it is followed up, it may be anxious because the person being examined cannot know how much risk there is. However, it may be difficult to determine the risk of myocardial infarction or the like based only on the shape of the blood vessel or heart. For example, even if the stenosis rate is the same, there may be a difference in whether the variation pattern of the shear stress varies locally between the inside and outside of the curve of the blood vessel. This difference can greatly change future risks. However, at present, the relationship between the blood flow situation and future risks has not been clarified in detail.
 そこで、血流解析システム200は、上記のように、血流の時間変化について統計データを取得する。これにより、血流解析システム200は、血流の現状に対する、将来のリスクの予測データを提供することができる。担当医は、血流解析システム200が提供する予測データに基づいて投薬又は手術等の処置の要否を判断し、被健診者に対して将来的なリスクを説明することができる。被健診者は、将来的なリスクの説明を受けることで、不安を低減させることができる。
 以下では、血流の将来の状況の予測を予測診断と称する。
Therefore, the blood flow analysis system 200 acquires statistical data on the temporal change in blood flow as described above. Thereby, the blood flow analysis system 200 can provide the prediction data of the future risk with respect to the current state of the blood flow. The doctor in charge can determine the necessity of treatment such as medication or surgery based on the prediction data provided by the blood flow analysis system 200, and explain the future risk to the examinee. Medical examinees can reduce their anxiety by receiving explanations of future risks.
Hereinafter, prediction of the future state of blood flow is referred to as prediction diagnosis.
 次に、手術を行う場合の、術後の血流の状況を予測するための情報について説明する。
 術後の血流の状況を予測するための情報として、例えば、血流解析システム200は、手術後の血流をシミュレーションにて算出する。これにより、担当医は、予定している手術の適否を事前に確認することができる。また、例えば、冠動脈に狭窄のある患者に対するバイパス方法が複数考えられる場合、血流解析システム200は、各々のバイパス方法について、術後の血流をシミュレーションによって算出する。これにより、担当医は、どのバイパス方法がより良いかを術前に検討することができ、いずれかのバイパス方法を選択することができる。また、血流解析システム200は、バイパスする血管の長さについても、複数の長さの各々について血流をシミュレーションする。これにより、担当医は、どの長さがより良いかを術前に検討することができる。
 以下では、術後の血流の状況のシミュレーションを仮想手術と称する。
Next, information for predicting the postoperative blood flow situation when performing surgery will be described.
As information for predicting the state of blood flow after surgery, for example, the blood flow analysis system 200 calculates blood flow after surgery by simulation. Thereby, the attending physician can confirm in advance whether or not the planned operation is appropriate. For example, when a plurality of bypass methods for a patient having a stenosis in a coronary artery can be considered, the blood flow analysis system 200 calculates postoperative blood flow by simulation for each bypass method. Accordingly, the attending physician can examine which bypass method is better before the operation, and can select any bypass method. The blood flow analysis system 200 also simulates blood flow for each of a plurality of lengths with respect to the length of the bypassed blood vessel. This allows the attending physician to consider which length is better before surgery.
Hereinafter, the simulation of the blood flow situation after surgery is referred to as virtual surgery.
 図1に戻り、解析依頼受付システム210は、利用者端末装置100からの血流解析の依頼を受け付けてCFD用データ(CFDに用いられるデータ)を生成し、解析サーバ装置240にCFDの演算を依頼する。解析依頼受付システム210の運用者と解析サーバ装置240の運用者は同一であってもよいし異なっていてもよい。
 ここで、上述したように血流解析を迅速に行うために、解析サーバ装置240として高性能なコンピュータが必要となる。一方、解析サーバ装置240は、血流解析専用のコンピュータである必要は無く、CFDの演算を行えるものであれば汎用のコンピュータでよい。そこで、解析依頼受付システム210の運用者が、解析サーバ装置240の運用者にCFDの演算を委託する形態が考えられる。これにより、解析依頼受付システム210の運用者自らは高性能なコンピュータを有している必要がなく、また、解析サーバ装置240の運用者は血流解析の専門知識を有している必要がない。これにより、血流解析システム200の実現が比較的容易になる。以下では、解析依頼受付システム210の運用者と解析サーバ装置240の運用者が異なる場合を例に説明する。
Returning to FIG. 1, the analysis request receiving system 210 receives a blood flow analysis request from the user terminal device 100, generates CFD data (data used for CFD), and performs a CFD calculation on the analysis server device 240. Ask. The operator of the analysis request receiving system 210 and the operator of the analysis server device 240 may be the same or different.
Here, as described above, a high-performance computer is required as the analysis server device 240 in order to quickly perform blood flow analysis. On the other hand, the analysis server device 240 need not be a computer dedicated to blood flow analysis, and may be a general-purpose computer as long as it can perform CFD calculations. Therefore, a mode in which the operator of the analysis request receiving system 210 entrusts the CFD calculation to the operator of the analysis server device 240 is conceivable. Thereby, the operator of the analysis request receiving system 210 does not need to have a high-performance computer, and the operator of the analysis server device 240 does not need to have expertise in blood flow analysis. . Thereby, realization of blood flow analysis system 200 becomes comparatively easy. Hereinafter, a case where the operator of the analysis request receiving system 210 and the operator of the analysis server device 240 are different will be described as an example.
 図1に示す受付サーバ装置211は、利用者端末装置100から血流解析の依頼を受信し、解析結果を送信(返信)する。受付サーバ装置211は、例えばコンピュータを用いて構成される。
 上記のように通信ネットワーク900はインターネットであり、受付サーバ装置211は、インターネットを介して血流解析の依頼を受け、解析結果を回答する。このように、血流解析システム200は、利用者端末装置100に対して血流解析のクラウドサービスを提供する。
The reception server device 211 illustrated in FIG. 1 receives a blood flow analysis request from the user terminal device 100 and transmits (replies) the analysis result. The reception server device 211 is configured using a computer, for example.
As described above, the communication network 900 is the Internet, and the reception server device 211 receives a blood flow analysis request via the Internet and answers the analysis result. As described above, the blood flow analysis system 200 provides a blood flow analysis cloud service to the user terminal device 100.
 ここで、仮に血流解析の依頼を郵送にて受け付ける場合、郵送に時間がかかり短期間での解析結果の回答に支障をきたす可能性がある。また、解析の依頼を送信する郵送料が必要となる。さらに、解析結果も郵送する場合、解析の依頼の送信から解析結果の受信までに要する時間が更に長くなり、郵送料の負担も増大する。
 これに対し、血流解析システム200が血流解析のクラウドサービスを提供することで、利用者端末装置100は、受付サーバ装置211と通信して解析依頼を送信し解析結果を受信することができる。これにより、解析依頼及び解析結果の少なくともいずれか一方を郵送にてやり取りする場合と比較して、時間的負担及び金銭的負担(特に、郵送料の負担)を軽減させることができる。
Here, if a blood flow analysis request is received by mail, it takes time for mailing, and there is a possibility that the answer of the analysis result in a short period may be hindered. In addition, a postage for sending a request for analysis is required. Further, when the analysis result is also mailed, the time required from the transmission of the analysis request to the reception of the analysis result is further increased, and the postage burden is also increased.
In contrast, the blood flow analysis system 200 provides a blood flow analysis cloud service, so that the user terminal device 100 can communicate with the reception server device 211 to transmit an analysis request and receive an analysis result. . Thereby, compared with the case where at least any one of an analysis request and an analysis result is exchanged by mail, time burden and money burden (especially burden of a mailing cost) can be reduced.
 受付サーバ装置211は、利用者端末装置100から受信した解析依頼から、患者の氏名など個人を特定可能な情報を削除する。以下では、個人を特定可能な情報を個人特定情報と称する。また、個人特定情報を削除する処理を匿名化と称する。受付サーバ装置211が、解析依頼を匿名化することで、仮に、病状の情報など解析依頼に含まれる情報が流出した場合でも、流出した情報は個人に結び付けられない。 The reception server device 211 deletes information that can identify an individual such as a patient's name from the analysis request received from the user terminal device 100. Hereinafter, information that can identify an individual is referred to as personal identification information. Moreover, the process which deletes personal identification information is called anonymization. Since the reception server device 211 anonymizes the analysis request, even if information included in the analysis request such as information on a medical condition leaks, the leaked information is not linked to an individual.
 この点で、プライバシー侵害を回避することができる。また、このように情報流出時のプライバシー侵害を回避できることで、解析依頼に含まれる情報、及び、血流解析システム200による解析結果の情報を上記のように統計的使用のために蓄積する場合において、これら情報の管理が比較的容易になる。なお、以下では、解析依頼や解析結果の情報など、患者個人毎の情報を患者情報と称する。 In this respect, privacy infringement can be avoided. In addition, since privacy infringement at the time of information leakage can be avoided in this way, the information included in the analysis request and the analysis result information by the blood flow analysis system 200 are accumulated for statistical use as described above. The management of these information becomes relatively easy. In the following, information for each individual patient such as an analysis request and analysis result information is referred to as patient information.
 また、受付サーバ装置211は、匿名化された解析依頼に管理番号を付与する。ここでいう管理番号は、患者を識別するための識別番号である。この管理番号は、解析依頼、及び、解析結果の情報を連結可能匿名化するために用いられる。
 ここで、受付サーバ装置211が情報を単に匿名化しただけの場合、血流解析システム200(医療データファイルデータベース装置222)が解析依頼や解析結果の情報を蓄積したとしても、蓄積された情報を患者毎に分類することは難しい。この場合、同一の患者の病状が、時間経過につれてどのように変化したかを追跡することは難しい。
In addition, the reception server device 211 gives a management number to the anonymized analysis request. The management number here is an identification number for identifying a patient. This management number is used to anonymize the analysis request and analysis result information.
Here, when the reception server device 211 simply anonymizes the information, even if the blood flow analysis system 200 (medical data file database device 222) stores the information of the analysis request and the analysis result, It is difficult to classify by patient. In this case, it is difficult to track how the condition of the same patient has changed over time.
 そこで、受付サーバ装置211が患者毎に管理番号を発行し、血流解析システム200は、患者情報を管理番号にしたがって患者毎に分類して蓄積する。これにより、血流解析システム200では、同一の患者の病状が時間経過につれてどのように変化したか追跡可能になる。このように、血流解析システム200は、時間経過による病状の変化を示す統計データを得ることができる。
 また、血流解析システム200は、解析依頼と解析結果をと同一の管理番号で対応付けるなど、管理情報を用いて複数種類の情報の関連付けを行うことができる。
Therefore, the reception server device 211 issues a management number for each patient, and the blood flow analysis system 200 classifies and accumulates patient information for each patient according to the management number. Thereby, in the blood flow analysis system 200, it becomes possible to track how the medical condition of the same patient has changed over time. As described above, the blood flow analysis system 200 can obtain statistical data indicating changes in the medical condition over time.
The blood flow analysis system 200 can associate multiple types of information using management information, such as associating an analysis request and an analysis result with the same management number.
 図1に示すアイテム管理サーバ装置212は、受付サーバ装置211が連結可能匿名化した解析依頼に基づいて、CFD用データを生成し、解析サーバ装置240にCFDの演算を依頼する。アイテム管理サーバ装置212は、例えばコンピュータを用いて構成される。
 特に、アイテム管理サーバ装置212は、解析依頼に含まれる二次元断層画像から血管等の三次元モデルを生成する。また、アイテム管理サーバ装置212は、有限体積法にてCFDの演算を行うための境界条件など、有限体積法のための設定条件情報を生成する。
そして、アイテム管理サーバ装置212は、生成した三次元モデル及び設定条件情報を含むCFD演算依頼(有限体積法の演算依頼)を解析サーバ装置240に送信する。受付サーバ装置211が連結可能匿名化(匿名化および管理番号の付与)した情報に基づいて、アイテム管理サーバ装置212は、連結可能匿名化されたCFD用データを生成する。
The item management server device 212 shown in FIG. 1 generates CFD data based on the analysis request anonymously accepted by the reception server device 211 and requests the analysis server device 240 to perform CFD calculation. The item management server device 212 is configured using, for example, a computer.
In particular, the item management server device 212 generates a three-dimensional model such as a blood vessel from a two-dimensional tomographic image included in the analysis request. In addition, the item management server device 212 generates setting condition information for the finite volume method, such as a boundary condition for performing CFD calculation by the finite volume method.
Then, the item management server device 212 transmits a CFD calculation request (finite volume method calculation request) including the generated three-dimensional model and setting condition information to the analysis server device 240. Based on the information that the accepting server device 211 is anonymizable to be connectable (anonymization and assignment of a management number), the item management server device 212 generates CFD data that is anonymized to be connectable.
 ここで、医療機関同士の間では、医療情報の共有、セカンドオピニオン、あるいは患者の照会など、個人特定情報を含む情報のやり取りが行われる場合がある。従って、個人特定情報を含む情報を医療機関に送信することは比較的容易である。
 これに対し、解析サーバ装置240の運用者はIT(Information Technology)系の企業など、医療機関以外の機関であることが考えられる。このような場合であっても、アイテム管理サーバ装置212が匿名化されたCFD用データを生成することで、個人のプライバシーに関する障壁が比較的低く抑えられる。このため、受付サーバ装置211は、解析サーバ装置240にCFD用データを送信してCFDの演算を依頼することができる。
Here, there are cases where information including personal identification information is exchanged between medical institutions, such as sharing of medical information, second opinion, or patient inquiry. Therefore, it is relatively easy to transmit information including personal identification information to a medical institution.
On the other hand, the operator of the analysis server device 240 may be an organization other than a medical institution such as an IT (Information Technology) company. Even in such a case, the item management server device 212 generates anonymized CFD data, so that the barrier regarding personal privacy can be kept relatively low. For this reason, the reception server device 211 can request the calculation of CFD by transmitting CFD data to the analysis server device 240.
 図1に示す利用者認証用データベース装置221は、受付サーバ装置211がユーザ認証を行うための利用者認証用情報を記憶する。例えば、血流解析システム200に血流解析を依頼するユーザ(例えば、解析対象の患者の担当医)は、血流解析を依頼するために、血流解析システム200にログインする。そのため、受付サーバ装置211は、パスワード認証によるユーザ認証を行う。この場合、利用者認証用データベース装置221は、ユーザ名とパスワードとが対応付けられた利用者認証情報を記憶する。あるいは、利用者端末装置100がユーザ名とパスワードなど認証用の情報を含む解析依頼を電子メールにて送信してもよい。この場合、利用者端末装置100は、電子メールから認証用の情報を読み出してユーザ認証を行い、ユーザ認証に成功した場合に、依頼された解析を行う。 The user authentication database device 221 shown in FIG. 1 stores user authentication information for the reception server device 211 to perform user authentication. For example, a user who requests blood flow analysis from the blood flow analysis system 200 (for example, a doctor in charge of a patient to be analyzed) logs in to the blood flow analysis system 200 in order to request blood flow analysis. Therefore, the reception server device 211 performs user authentication by password authentication. In this case, the user authentication database device 221 stores user authentication information in which a user name and a password are associated with each other. Alternatively, the user terminal device 100 may transmit an analysis request including authentication information such as a user name and a password by e-mail. In this case, the user terminal device 100 reads out the authentication information from the e-mail, performs user authentication, and performs the requested analysis when the user authentication is successful.
 図1に示す医療データファイルデータベース装置222は、解析依頼に含まれる二次元断層画像など、解析依頼に含まれる患者の状態に関する情報を、アイテム管理サーバ装置212の制御に従って記憶(蓄積)する。特に、医療データファイルデータベース装置222は、患者の状態に関する情報を、連結可能匿名化された状態で記憶する。医療データファイルデータベース装置222は、解析依頼そのものを記憶してもよいし、解析依頼の一部のみを記憶してもよい。 The medical data file database device 222 shown in FIG. 1 stores (accumulates) information related to the patient state included in the analysis request, such as a two-dimensional tomographic image included in the analysis request, under the control of the item management server device 212. In particular, the medical data file database device 222 stores information related to the patient's state in an anonymized state. The medical data file database device 222 may store the analysis request itself, or may store only a part of the analysis request.
 図1に示す解析用ファイルデータベース装置223は、アイテム管理サーバ装置212が生成するCFD用データを、アイテム管理サーバ装置212の制御に従って記憶(蓄積)する。特に解析用ファイルデータベース装置223は、アイテム管理サーバ装置212が生成するCFD用データを連結可能匿名化された状態で記憶する。解析用ファイルデータベース装置223は、解析サーバ装置240へのCFDの演算依頼そのものを記憶してもよいし、演算依頼の一部のみを記憶してもよい。 The analysis file database apparatus 223 shown in FIG. 1 stores (accumulates) the CFD data generated by the item management server apparatus 212 according to the control of the item management server apparatus 212. In particular, the analysis file database device 223 stores the CFD data generated by the item management server device 212 in a connectable and anonymized state. The analysis file database apparatus 223 may store the CFD calculation request itself to the analysis server apparatus 240 or may store only a part of the calculation request.
 図1に示す解析結果ファイルデータベース装置224は、解析サーバ装置240による解析結果を、アイテム管理サーバ装置212の制御に従って記憶(蓄積)する。特に解析結果ファイルデータベース装置224は、解析結果を連結可能匿名化された状態で記憶する。解析結果ファイルデータベース装置224は、解析結果そのものを記憶してもよいし、解析結果の一部のみを記憶してもよい。 The analysis result file database device 224 shown in FIG. 1 stores (accumulates) the analysis result by the analysis server device 240 in accordance with the control of the item management server device 212. In particular, the analysis result file database device 224 stores the analysis result in an anonymized state that can be connected. The analysis result file database device 224 may store the analysis result itself, or may store only a part of the analysis result.
 図1に示すオペレーション端末装置231は、アイテム管理サーバ装置212による解析サーバ装置240へのCFDの演算依頼の生成を補助するオペレータの端末装置である。
 例えば、オペレータはオペレーション端末装置231を操作することにより、アイテム管理サーバ装置212が生成する血管等の三次元モデルから、解析に必要のない枝葉の血管をカット(削除)する。これにより、解析サーバ装置240の演算量を低減させることができる。
An operation terminal device 231 illustrated in FIG. 1 is an operator terminal device that assists the item management server device 212 in generating a CFD calculation request to the analysis server device 240.
For example, by operating the operation terminal device 231, the operator cuts (deletes) branch and vein blood vessels that are not necessary for analysis from a three-dimensional model such as blood vessels generated by the item management server device 212. Thereby, the calculation amount of the analysis server apparatus 240 can be reduced.
 また、アイテム管理サーバ装置212が生成する血管等の三次元モデルについて、元の断層画像の解像度等の影響により本来存在しないはずの凸部が生じるなど、モデルの形状が不正確になる場合がある。そこで、オペレータは、オペレーション端末装置231を操作して、三次元モデルを整形(スムージング)する。これにより、三次元モデルの精度が向上し、血流解析の精度が向上する。
 また、二次元断層画像からの血管や心臓などの抽出を、オペレータがオペレーション端末装置231を用いて行ってもよい。あるいは、アイテム管理サーバ装置212が、二次元断層画像からの血管や心臓などの抽出を自動で行ってもよい。
In addition, for a three-dimensional model such as a blood vessel generated by the item management server device 212, the shape of the model may be inaccurate, such as a convex portion that should not originally exist due to the influence of the resolution of the original tomographic image, etc. . Therefore, the operator operates the operation terminal device 231 to shape (smooth) the three-dimensional model. Thereby, the accuracy of the three-dimensional model is improved and the accuracy of blood flow analysis is improved.
In addition, the operator may use the operation terminal device 231 to extract blood vessels, hearts, and the like from the two-dimensional tomographic image. Alternatively, the item management server device 212 may automatically extract blood vessels, hearts, and the like from the two-dimensional tomographic image.
 図1に示す診断レポート作成用端末装置232は、解析サーバ装置240によるシミュレーション結果(CFDの演算結果)に基づいて、解析依頼受付システム210の専属医が診断レポートを作成するための端末装置である。解析依頼受付システム210の専属医は、シミュレーション結果を見た際の所見など、シミュレーション結果に付加的な情報を加えて診断レポートとして纏める。
 但し、診断レポート作成用端末装置232は、解析依頼受付システム210にとって必須ではない。すなわち、解析依頼受付システム210は、診断レポート作成用端末装置232を備えない構成であってもよい。
The diagnostic report creation terminal device 232 shown in FIG. 1 is a terminal device for a dedicated doctor of the analysis request reception system 210 to create a diagnostic report based on the simulation result (calculation result of CFD) by the analysis server device 240. . The dedicated doctor of the analysis request reception system 210 adds additional information to the simulation result, such as findings when viewing the simulation result, and summarizes it as a diagnostic report.
However, the diagnostic report creation terminal device 232 is not essential for the analysis request receiving system 210. That is, the analysis request reception system 210 may be configured not to include the diagnostic report creation terminal device 232.
 図1に示す解析サーバ装置240は、コンピュータを用いて構成され、アイテム管理サーバ装置212からの依頼に応じてCFDの演算を行い、演算結果をアイテム管理サーバ装置212に送信(返信)する。
 例えば、アイテム管理サーバ装置212と解析サーバ装置240とがインターネットを介して通信接続され、解析サーバ装置240はアイテム管理サーバ装置212に対して高性能コンピュータによる演算をクラウドサービスにて提供する。
 解析サーバ装置240は、解析実行部の例に該当する。
The analysis server device 240 shown in FIG. 1 is configured using a computer, performs CFD calculation in response to a request from the item management server device 212, and transmits (replies) the calculation result to the item management server device 212.
For example, the item management server device 212 and the analysis server device 240 are communicatively connected via the Internet, and the analysis server device 240 provides the item management server device 212 with computation by a high-performance computer through a cloud service.
The analysis server device 240 corresponds to an example of an analysis execution unit.
 有限体積法によるCFDでは、血管の空間が、例えば四面体のメッシュで、例えば100万個~200万個程度の領域に細かく分割されている。また、三次元モデル入口には血圧が設定され、出口には血流に対する抵抗値が設定されている。ここでいう入口、出口は、それぞれ三次元モデルにおける血流の入口、出口である。入口、出口のいずれも、三次元モデルの境界に該当する。また、有限体積法によるCFDでは、流量保存則や運動量保存則等の物理法則に基づく方程式が設定される。血流解析システム200では、アイテム管理サーバ装置212が、血液の空間のメッシュ分割を行い、これら方程式及び条件を設定する。
 解析サーバ装置240は、設定された方程式及び設定された条件を満たす血流を算出する。例えば、解析サーバ装置240は、メッシュ毎の血流の流速及び血圧の演算を、与えられた条件に対する誤差が所定の誤差以下になるまで繰り返す。
In CFD based on the finite volume method, a blood vessel space is finely divided into, for example, a region of about 1 million to 2 million, for example, with a tetrahedral mesh. In addition, a blood pressure is set at the entrance of the three-dimensional model, and a resistance value for blood flow is set at the exit. The inlet and outlet referred to here are the inlet and outlet of blood flow in the three-dimensional model, respectively. Both the entrance and the exit correspond to the boundary of the 3D model. In CFD based on the finite volume method, equations based on physical laws such as a flow rate conservation law and a momentum conservation law are set. In the blood flow analysis system 200, the item management server device 212 performs mesh division of the blood space and sets these equations and conditions.
The analysis server device 240 calculates a blood flow that satisfies the set equation and the set condition. For example, the analysis server device 240 repeats the calculation of the blood flow velocity and blood pressure for each mesh until an error with respect to a given condition becomes equal to or less than a predetermined error.
 これにより、各メッシュでの血流のパタンが求まる。その結果、例えば、血流がどこで加速していて、血管の各枝にどれぐらいの流量が流れているか、あるいは、狭窄の前後で血圧の差がどれぐらいあるかなど、血流の状況を精密に把握することが可能になる。
 なお、解析サーバ装置240が血流解析のシミュレーションをリアルタイムで実行し、利用者端末装置100がシミュレーション結果の動画像をリアルタイムで表示するようにしてもよい。
Thereby, the pattern of the blood flow in each mesh is obtained. As a result, for example, where the blood flow is accelerating, how much flow is flowing in each branch of the blood vessel, or how much the difference in blood pressure is before and after stenosis, it is precise It becomes possible to grasp.
Note that the analysis server device 240 may execute a simulation of blood flow analysis in real time, and the user terminal device 100 may display a moving image of the simulation result in real time.
 図2は、図1に示す受付サーバ装置211の機能構成を示す概略ブロック図である。図2に示すように、受付サーバ装置211は、第1通信部310と、第1記憶部380と、第1制御部390とを備える。第1制御部390は、ユーザ認証部391と、匿名化処理部392とを備える。 FIG. 2 is a schematic block diagram showing a functional configuration of the reception server device 211 shown in FIG. As illustrated in FIG. 2, the reception server device 211 includes a first communication unit 310, a first storage unit 380, and a first control unit 390. The first control unit 390 includes a user authentication unit 391 and an anonymization processing unit 392.
 第1通信部310は、他機器と通信を行う。特に、第1通信部310は通信ネットワーク900を介して利用者端末装置100と通信し、利用者端末装置100から解析依頼(血流解析の依頼)を受信する。第1通信部310は、解析依頼受信部の例に該当する。
 また、第1通信部310は、解析依頼に対する回答の診断レポートを依頼元の利用者端末装置100へ送信する。また、第1通信部310は、利用者認証用データベース装置221と通信して、ユーザ認証のための情報の登録及び読出を行う。また、第1通信部310は、アイテム管理サーバ装置212と通信し、連結可能匿名化した解析依頼をアイテム管理サーバ装置212に送信する。また、第1通信部310は、解析依頼に対する回答の診断レポートをアイテム管理サーバ装置212から受信する。
The first communication unit 310 communicates with other devices. In particular, the first communication unit 310 communicates with the user terminal device 100 via the communication network 900 and receives an analysis request (a blood flow analysis request) from the user terminal device 100. The first communication unit 310 corresponds to an example of an analysis request receiving unit.
In addition, the first communication unit 310 transmits a diagnostic report of an answer to the analysis request to the user terminal device 100 that is the request source. The first communication unit 310 communicates with the user authentication database device 221 to register and read information for user authentication. In addition, the first communication unit 310 communicates with the item management server device 212 and transmits the connection request anonymized analysis request to the item management server device 212. Further, the first communication unit 310 receives a diagnostic report of an answer to the analysis request from the item management server device 212.
 第1記憶部380は、受付サーバ装置211が備える記憶デバイスを用いて構成され、各種情報を記憶する。例えば、第1記憶部380は、患者特定情報と管理番号とを対応付けて記憶する。これにより、血流解析システム200が過去に解析を行ったことがある患者の解析依頼を第1通信部310が受信した場合に、受付サーバ装置211(匿名化処理部392)は、過去の解析の際と同一の管理番号を、解析依頼に付与することができる。これにより、受付サーバ装置211は連結可能匿名化を実現することができる。 The first storage unit 380 is configured using a storage device provided in the reception server device 211 and stores various types of information. For example, the first storage unit 380 stores patient identification information and a management number in association with each other. Accordingly, when the first communication unit 310 receives an analysis request of a patient that has been analyzed by the blood flow analysis system 200 in the past, the reception server device 211 (anonymization processing unit 392) The same management number as in the above can be assigned to the analysis request. Thereby, the reception server device 211 can realize connectable anonymization.
 第1制御部390は、受付サーバ装置211の各部を制御して各種機能を実行する。第1制御部390は、例えば受付サーバ装置211が備えるCPU(Central Processing Unit、中央処理装置)が、第1記憶部380からプログラムを読み出して実行することで実現される。
 ユーザ認証部391は、利用者端末装置100から血流解析の依頼を受ける際のユーザ認証を行う。例えば、ユーザ認証部391は解析依頼(血流解析の依頼)に含まれるユーザ名及びパスワードと、利用者認証用データベース装置221が記憶している利用者認証用情報とに基づいて、パスワード認証によるユーザ認証を行う。
The 1st control part 390 controls each part of the reception server apparatus 211, and performs various functions. The first control unit 390 is realized by, for example, a CPU (Central Processing Unit) provided in the reception server device 211 reading and executing a program from the first storage unit 380.
The user authentication unit 391 performs user authentication when receiving a blood flow analysis request from the user terminal device 100. For example, the user authentication unit 391 performs password authentication based on the user name and password included in the analysis request (blood flow analysis request) and the user authentication information stored in the user authentication database device 221. Perform user authentication.
 匿名化処理部392は、第1通信部310が受信した解析依頼を匿名化する。具体的には、匿名化処理部392は、解析依頼から個人特定情報を削除する。
 また、匿名化処理部392は、匿名化した解析依頼に対し、上述した管理番号を付与する。これにより、受付サーバ装置211は、解析依頼を連結可能匿名化することができる。
The anonymization processing unit 392 anonymizes the analysis request received by the first communication unit 310. Specifically, the anonymization processing unit 392 deletes the personal identification information from the analysis request.
Moreover, the anonymization processing unit 392 gives the above-described management number to the anonymized analysis request. Thereby, the reception server device 211 can anonymize the analysis request to be connectable.
 図3は、図1に示すアイテム管理サーバ装置212の機能構成を示す概略ブロック図である。図3に示すように、アイテム管理サーバ装置212は、第2通信部410と、第2記憶部480と、第2制御部490とを備える。第2制御部490は、モデル生成部491と、プリプロセッシング部492と、シミュレーション依頼処理部493と、診断レポート処理部494とを備える。 FIG. 3 is a schematic block diagram showing a functional configuration of the item management server device 212 shown in FIG. As illustrated in FIG. 3, the item management server device 212 includes a second communication unit 410, a second storage unit 480, and a second control unit 490. The second control unit 490 includes a model generation unit 491, a preprocessing unit 492, a simulation request processing unit 493, and a diagnosis report processing unit 494.
 第2通信部410は、他機器と通信を行う。特に、第2通信部410は、受付サーバ装置211と通信し、連結可能匿名化された解析依頼を受付サーバ装置211から受信する。また、第2通信部410は、解析依頼に対する回答の診断レポートを受付サーバ装置211へ送信する。
 また、第2通信部410は医療データファイルデータベース装置222と通信を行い、利用者端末装置100からの解析依頼を医療データファイルデータベース装置222に記憶(蓄積)させる。また、第2通信部410は解析用ファイルデータベース装置223と通信を行い、CFD用データを解析用ファイルデータベース装置223に記憶(蓄積)させる。また、第2通信部410は解析結果ファイルデータベース装置224と通信を行い、解析サーバ装置240による解析結果を解析結果ファイルデータベース装置224に記憶(蓄積)させる。
 また、第2通信部410は、オペレーション端末装置231と通信を行い、血管等の三次元モデルの生成の補助など、CFDの演算依頼の生成の補助のユーザ操作(オペレータによる操作)を示す情報を受信する。
The second communication unit 410 communicates with other devices. In particular, the second communication unit 410 communicates with the reception server device 211 and receives the connection request anonymized analysis request from the reception server device 211. In addition, the second communication unit 410 transmits a diagnostic report of a response to the analysis request to the reception server device 211.
Further, the second communication unit 410 communicates with the medical data file database device 222 and stores (accumulates) the analysis request from the user terminal device 100 in the medical data file database device 222. The second communication unit 410 communicates with the analysis file database device 223 to store (accumulate) the CFD data in the analysis file database device 223. Further, the second communication unit 410 communicates with the analysis result file database device 224 and stores (accumulates) the analysis result by the analysis server device 240 in the analysis result file database device 224.
In addition, the second communication unit 410 communicates with the operation terminal device 231, and displays information indicating user operations (operations by an operator) for generating CFD calculation requests such as assistance for generating a three-dimensional model such as a blood vessel. Receive.
 第2記憶部480は、アイテム管理サーバ装置212が備える記憶デバイスを用いて構成され、各種情報を記憶する。例えば、第2記憶部480は、第2制御部490のワーキングメモリとして機能し、解析依頼に含まれる二次元断層画像や、血管等の三次元モデルを一時的に記憶する。
 第2制御部490は、アイテム管理サーバ装置212の各部を制御して各種機能を実現する。第2制御部490は、例えばアイテム管理サーバ装置212が備えるCPUが、第2記憶部480からプログラムを読み出して実行することで実現される。
The 2nd memory | storage part 480 is comprised using the storage device with which the item management server apparatus 212 is provided, and memorize | stores various information. For example, the second storage unit 480 functions as a working memory of the second control unit 490, and temporarily stores a two-dimensional tomographic image included in the analysis request and a three-dimensional model such as a blood vessel.
The second control unit 490 realizes various functions by controlling each unit of the item management server device 212. The second control unit 490 is realized by, for example, a CPU included in the item management server device 212 reading and executing a program from the second storage unit 480.
 モデル生成部491は、血管等の三次元モデルを生成する。上述したように、モデル生成部491が自動で三次元モデルを生成してもよいし、オペレーション端末装置231を操作するオペレータによる二次元断層画像からの血管等の抽出結果に基づいて、三次元モデルを生成してもよい。
 また、モデル生成部491は、オペレーション端末装置231でのオペレータの操作に従って、三次元モデルを修正する。例えば、モデル生成部491は、上述した解析に必要のない枝葉の血管のカットを行う。また、モデル生成部491は、上述した三次元モデルの整形(スムージング)を行う。
The model generation unit 491 generates a three-dimensional model such as a blood vessel. As described above, the model generation unit 491 may automatically generate a three-dimensional model, or based on the extraction result of blood vessels or the like from a two-dimensional tomographic image by an operator who operates the operation terminal device 231. May be generated.
In addition, the model generation unit 491 corrects the three-dimensional model in accordance with the operator's operation on the operation terminal device 231. For example, the model generation unit 491 cuts branches and veins that are not necessary for the above-described analysis. The model generation unit 491 performs the above-described shaping (smoothing) of the three-dimensional model.
 プリプロセッシング部492は、有限体積法によるCFDのための各種設定を行う。プリプロセッシング部492は、条件設定部の例に該当する。
 特に、プリプロセッシング部492は、三次元モデルの入口及び出口(の血管)を伸ばす。これは、モデルの入口及び出口における血流の影響を低減させ、流量比を安定させるためである。
 ここで、三次元モデルの入口及び出口を伸ばす量によって流量比が変化する。また、入口及び出口を長くするほど有限体積法におけるメッシュの数が増えて演算量が増加する。
The preprocessing unit 492 performs various settings for CFD by the finite volume method. The preprocessing unit 492 corresponds to an example of a condition setting unit.
In particular, the preprocessing unit 492 extends the inlet and outlet (blood vessels) of the three-dimensional model. This is to reduce the influence of blood flow at the inlet and outlet of the model and stabilize the flow rate ratio.
Here, the flow rate ratio changes depending on the amount of extension of the inlet and outlet of the three-dimensional model. Further, as the inlet and outlet are lengthened, the number of meshes in the finite volume method increases and the amount of calculation increases.
 これに対し、実験の結果、血管の直径の50倍程度延長すると実測データに近いシミュレーション結果を得られるとの知見が得られた。そこで、プリプロセッシング部492は、三次元モデルの入口及び出口の血管を、その血管の直径の50倍分延長する。但し、プリプロセッシング部492が行う血管の延長は厳密に血管の直径の50倍である必要は無い。例えば、プリプロセッシング部492が、血管の直径の40倍~60倍の範囲で血管の延長を行うようにしてもよい。
 なお、以下では、三次元モデルの入口及び出口を伸ばすことをメッシュの延長と称する。
On the other hand, as a result of experiments, it was found that a simulation result close to actual measurement data can be obtained by extending the diameter of the blood vessel by about 50 times. Therefore, the preprocessing unit 492 extends the inlet and outlet blood vessels of the three-dimensional model by 50 times the diameter of the blood vessels. However, the blood vessel extension performed by the preprocessing unit 492 is not necessarily strictly 50 times the diameter of the blood vessel. For example, the preprocessing unit 492 may extend the blood vessel in the range of 40 to 60 times the diameter of the blood vessel.
In the following, extending the inlet and outlet of the three-dimensional model is referred to as mesh extension.
 また、プリプロセッシング部492は、有限体積法における境界条件を設定する。プリプロセッシング部492が設定する境界条件については後述する。 Also, the preprocessing unit 492 sets boundary conditions in the finite volume method. The boundary conditions set by the preprocessing unit 492 will be described later.
 シミュレーション依頼処理部493は、解析サーバ装置240への血流のシミュレーション(有限体積法を用いたCFDによる血流解析)の依頼を行う。具体的には、シミュレーション依頼処理部493は、モデル生成部491が生成した血管等の三次元モデルと、プリプロセッシング部492が設定した条件を示す情報とを含む解析依頼(シミュレーション依頼)を生成し、第2通信部410を介して解析サーバ装置240へ送信する。 The simulation request processing unit 493 requests the analysis server device 240 for blood flow simulation (blood flow analysis by CFD using a finite volume method). Specifically, the simulation request processing unit 493 generates an analysis request (simulation request) including a three-dimensional model such as a blood vessel generated by the model generation unit 491 and information indicating the conditions set by the preprocessing unit 492. And transmitted to the analysis server device 240 via the second communication unit 410.
 診断レポート処理部494は、診断レポートを作成する。具体的には、診断レポート処理部494は、診断レポート作成用端末装置232での専門医の操作に基づいて診断レポートを作成する。
 診断レポート処理部494が作成する診断レポートには、利用者端末装置100からの解析依頼に応じて様々な情報が含まれる。例えば、診断レポート処理部494は、WSSまたは血流エネルギー損失など、血行力学的な評価指標値を含む診断レポートを作成してもよい。あるいは、診断レポート処理部494は、血流の状況の時間変化に関する統計データを含む診断レポートを作成してもよい。あるいは、診断レポート処理部494は、仮想手術の結果を含む診断レポートを作成してもよい。
 例えば、利用者端末装置100は、解析結果として必要な項目を示す情報を含む解析依頼を送信する。そして、診断レポート処理部494は、解析依頼で必要とされた項目の情報を含む診断レポートを生成する。
 診断レポート処理部494は、解析結果生成部の例に該当する。診断レポートは、解析結果の例に該当する。また、診断レポートを利用者端末装置100へ送信する受付サーバ装置211の第1通信部310は、解析結果送信部の例に該当する。
The diagnostic report processing unit 494 creates a diagnostic report. Specifically, the diagnostic report processing unit 494 creates a diagnostic report based on a specialist's operation on the diagnostic report creation terminal device 232.
The diagnosis report created by the diagnosis report processing unit 494 includes various information according to the analysis request from the user terminal device 100. For example, the diagnostic report processing unit 494 may create a diagnostic report including a hemodynamic evaluation index value such as WSS or blood flow energy loss. Or the diagnostic report process part 494 may produce the diagnostic report containing the statistical data regarding the time change of the condition of a blood flow. Alternatively, the diagnostic report processing unit 494 may create a diagnostic report including the result of virtual surgery.
For example, the user terminal device 100 transmits an analysis request including information indicating necessary items as an analysis result. Then, the diagnosis report processing unit 494 generates a diagnosis report including information on items required for the analysis request.
The diagnosis report processing unit 494 corresponds to an example of an analysis result generation unit. The diagnosis report corresponds to an example of the analysis result. Moreover, the 1st communication part 310 of the reception server apparatus 211 which transmits a diagnostic report to the user terminal device 100 corresponds to the example of an analysis result transmission part.
 次に、図4~図5を参照して血流解析システム200の動作について説明する。
 図4は、図2で説明した受付サーバ装置211が行う処理の手順の例を示すフローチャートである。受付サーバ装置211は、利用者端末装置100からの解析依頼を受信すると図4の処理を開始する。
 図4の処理で、ユーザ認証部391は、第1通信部310が利用者端末装置100から受信した利用者情報に基づいてユーザ認証を行う(ステップS101)。例えば、第1通信部310は、ユーザ名とパスワードとを含む利用者情報を利用者端末装置100から受信する。そして、ユーザ認証部391は、第1通信部310が受信したユーザ名とパスワードとを用いてパスワード認証を行う。
 そして、ユーザ認証部391は、ステップS101でユーザ認証に成功したか否かを判定する(ステップS102)。
Next, the operation of the blood flow analysis system 200 will be described with reference to FIGS.
FIG. 4 is a flowchart illustrating an example of a procedure of processing performed by the reception server device 211 described in FIG. When receiving the analysis request from the user terminal device 100, the reception server device 211 starts the process of FIG.
In the process of FIG. 4, the user authentication unit 391 performs user authentication based on the user information received from the user terminal device 100 by the first communication unit 310 (step S101). For example, the first communication unit 310 receives user information including a user name and a password from the user terminal device 100. Then, the user authentication unit 391 performs password authentication using the user name and password received by the first communication unit 310.
Then, the user authentication unit 391 determines whether or not the user authentication is successful in step S101 (step S102).
 認証に成功したと判定した場合(ステップS102:YES)、匿名化処理部392は、患者の情報から個人特定情報(氏名など個人を特定可能な情報)を削除する匿名化処理を行う(ステップS111)。
 次に、匿名化処理部392は、匿名化された患者の情報に管理番号を付与する(ステップS112)。ここでいう管理番号は、患者を識別するための識別番号である。この管理番号は、患者の情報を連結可能匿名化するために用いられる。
 ここで、患者の情報を単に匿名化した場合、医療データファイルデータベース装置222が患者の情報を蓄積しても、蓄積された患者の情報を、患者毎に分類することは困難である。このため、同一の患者の病状が時間経過につれてどのように変化したか追跡することは難しい。
When it determines with having succeeded in authentication (step S102: YES), the anonymization process part 392 performs the anonymization process which deletes personal identification information (information which can identify individuals, such as a name) from patient information (step S111). ).
Next, the anonymization processing unit 392 gives a management number to the anonymized patient information (step S112). The management number here is an identification number for identifying a patient. This management number is used to anonymize patient information.
Here, when the patient information is simply anonymized, it is difficult to classify the stored patient information for each patient even if the medical data file database device 222 stores the patient information. For this reason, it is difficult to track how the same patient's medical condition has changed over time.
 一方、医療データファイルデータベース装置222が患者の情報と管理番号とを対応付けて記憶(蓄積)することで、蓄積された患者の情報を患者毎に分類可能になる。従って、同一の患者の病状が時間経過につれてどのように変化したか追跡可能になる。このように、匿名化処理部392が患者の情報に管理番号を付与して連結可能匿名化することで、時間経過による病状の変化を示す統計データを得ることが可能になる。
 また、医療データファイルデータベース装置222が記憶する患者情報と、解析用ファイルデータベース装置223が記憶する血管の三次元モデルの情報と、解析結果ファイルデータベース装置224が記憶する解析結果の情報とを患者毎に対応付けることができる。このように、管理情報を用いて複数種類の情報の関連付けを行うことができる。
On the other hand, when the medical data file database device 222 stores (accumulates) patient information and management numbers in association with each other, the accumulated patient information can be classified for each patient. Therefore, it becomes possible to track how the medical condition of the same patient has changed over time. As described above, the anonymization processing unit 392 assigns the management number to the patient information and anonymizes the information so that statistical data indicating changes in the medical condition with time can be obtained.
Further, patient information stored in the medical data file database device 222, information on the three-dimensional model of blood vessels stored in the analysis file database device 223, and analysis result information stored in the analysis result file database device 224 are stored for each patient. Can be associated. In this way, a plurality of types of information can be associated using management information.
 医療データファイルデータベース装置222、解析用ファイルデータベース装置223及び解析結果ファイルデータベース装置224は、いずれも、解析依頼に含まれる情報、シミュレーション結果、及び、シミュレーション結果に基づく解析結果に含まれる情報のうち少なくともいずれか一つを、管理番号に基づいて解析対象者毎に記憶する。医療データファイルデータベース装置222、解析用ファイルデータベース装置223及び解析結果ファイルデータベース装置224は、いずれも、経時情報記憶部の例に該当する。
 診断レポート処理部494は、例えば解析結果ファイルデータベース装置224が時系列的に記憶(蓄積)している解析結果に基づいて、瘤の破裂の将来的危険性など、血流の状況の予測を示す情報を含む診断レポートを生成する。
The medical data file database device 222, the analysis file database device 223, and the analysis result file database device 224 are all at least of the information included in the analysis request, the simulation result, and the information included in the analysis result based on the simulation result. One of them is stored for each person to be analyzed based on the management number. The medical data file database device 222, the analysis file database device 223, and the analysis result file database device 224 all correspond to examples of the time information storage unit.
The diagnosis report processing unit 494 indicates the prediction of the blood flow situation such as the future risk of aneurysm rupture based on the analysis result stored (accumulated) in time series by the analysis result file database device 224, for example. Generate diagnostic reports with information.
 患者の情報を連結可能匿名化するために、匿名化処理部392は、患者毎に管理番号を付与する。具体的には、第1通信部310が患者の情報を受信すると、匿名化処理部392は、第1通信部310が過去に同一患者の、患者の情報を受信したことがあるか否かを判定する。過去に同一患者の、患者の情報を受信したことがあると判定した場合、匿名化処理部392は、この患者に発行した管理番号と同じ管理番号を今回の患者の情報(第1通信部310が今回受信した患者の情報)に付与する。
 一方、過去に同一患者の、患者の情報を受信したことがないと判定した場合、匿名化処理部392は、新たな管理番号を発行し、発行した新たな管理番号を今回の患者の情報に付与する。
In order to anonymize patient information, the anonymization processing unit 392 assigns a management number to each patient. Specifically, when the first communication unit 310 receives patient information, the anonymization processing unit 392 determines whether the first communication unit 310 has received patient information of the same patient in the past. judge. When it is determined that the patient information of the same patient has been received in the past, the anonymization processing unit 392 assigns the same management number as the management number issued to the patient to the current patient information (first communication unit 310). To the patient information received this time).
On the other hand, when it is determined that the patient information of the same patient has not been received in the past, the anonymization processing unit 392 issues a new management number, and uses the issued new management number as the current patient information. Give.
 第1通信部310が過去に同一患者の、患者の情報を受信したことがあるか否かを判定するために、解析依頼受付システム210(例えば、第1記憶部380)は、患者特定情報と管理番号とを対応付けて記憶してもよい。例えば、匿名化処理部392がステップS112で新たな管理番号を発行する際、発行した管理番号とステップS111で削除した個人特定情報とを対応付けて第1記憶部380に記憶させる。そして、第1通信部310が患者の情報を受信すると、匿名化処理部392は、ステップS111で患者の情報から個人特定情報を抽出し、抽出した個人特定情報を患者の情報から削除する。そして、匿名化処理部392は、ステップS111で抽出した個人特定情報が管理番号と対応付けられて既に記憶されているか否かを判定することで、第1通信部310が過去に同一患者の、患者の情報を受信したことがあるか否かを判定する。 In order to determine whether the first communication unit 310 has received patient information of the same patient in the past, the analysis request reception system 210 (for example, the first storage unit 380) A management number may be stored in association with each other. For example, when the anonymization processing unit 392 issues a new management number in step S112, the issued management number and the personal identification information deleted in step S111 are associated with each other and stored in the first storage unit 380. Then, when the first communication unit 310 receives the patient information, the anonymization processing unit 392 extracts the personal identification information from the patient information in step S111, and deletes the extracted personal identification information from the patient information. Then, the anonymization processing unit 392 determines whether or not the personal identification information extracted in step S111 is already stored in association with the management number, so that the first communication unit 310 has the same patient in the past. It is determined whether or not patient information has been received.
 ステップS112の後、第1制御部390は、ステップS112で連結可能匿名化された患者の情報を、第1通信部310を介してアイテム管理サーバ装置212へ送信する(ステップS113)。
 一方、ステップS102でユーザ認証に失敗したと判定した場合(ステップS102:NO)、ユーザ認証部391は、ユーザ認証に失敗した旨の通知を、第1通信部310を介して依頼元の利用者端末装置100へ送信する(ステップS121)。
 ステップS121の後、図4の処理を終了する。
After step S112, the first control unit 390 transmits the information of the anonymized patient connectable in step S112 to the item management server device 212 via the first communication unit 310 (step S113).
On the other hand, if it is determined in step S102 that the user authentication has failed (step S102: NO), the user authentication unit 391 notifies the user of the request source via the first communication unit 310 that the user authentication has failed. It transmits to the terminal device 100 (step S121).
After step S121, the process of FIG. 4 ends.
 図5は、図3で説明したアイテム管理サーバ装置212が行う処理の手順の例を示すフローチャートである。アイテム管理サーバ装置212は、第2通信部410が、図4のステップS113で受付サーバ装置211が送信した患者の情報を受信すると図5の処理を開始する。
 図5の処理で、第2制御部490は、第2通信部410が受信した患者の情報を医療データファイルデータベース装置222に格納する(ステップS201)。具体的には、第2制御部490は、患者の情報を記憶させる指示と記憶させる患者の情報(第2通信部410が受信した患者の情報)とを第2通信部410を介して医療データファイルデータベース装置222へ送信する。
FIG. 5 is a flowchart illustrating an example of a procedure of processing performed by the item management server apparatus 212 described with reference to FIG. The item management server device 212 starts the process of FIG. 5 when the second communication unit 410 receives the patient information transmitted by the reception server device 211 in step S113 of FIG.
In the process of FIG. 5, the second control unit 490 stores the patient information received by the second communication unit 410 in the medical data file database device 222 (step S201). Specifically, the second control unit 490 transmits an instruction to store patient information and patient information to be stored (patient information received by the second communication unit 410) via the second communication unit 410. Transmit to the file database device 222.
 次に、モデル生成部491は、患者の情報に含まれる断層画像(CT画像でもよいし、MRI画像でもよい)に基づいて血管の三次元モデルを生成する(ステップS202)。
 次に、プリプロセッシング部492は、解析条件の設定などの事前処理を行う(ステップS203)。
 また、モデル生成部491は、ステップS202で生成した血管の三次元モデルを解析用ファイルデータベース装置223に格納する(ステップS204)。具体的には、モデル生成部491は、三次元モデルを記憶させる指示と、記憶させる三次元モデルのファイル(ステップS202で生成した血管の三次元モデルを示すデータファイル)とを、第2通信部410を介して解析用ファイルデータベース装置223へ送信する。
Next, the model generation unit 491 generates a three-dimensional model of the blood vessel based on the tomographic image (CT image or MRI image) included in the patient information (step S202).
Next, the preprocessing unit 492 performs preprocessing such as setting of analysis conditions (step S203).
The model generation unit 491 stores the three-dimensional blood vessel model generated in step S202 in the analysis file database device 223 (step S204). Specifically, the model generation unit 491 sends an instruction to store the three-dimensional model and a file of the three-dimensional model to be stored (data file indicating the three-dimensional model of the blood vessel generated in step S202) to the second communication unit. The data is transmitted to the analysis file database apparatus 223 via 410.
 次に、シミュレーション依頼処理部493は、血流解析の依頼を解析サーバ装置240へ送信する(ステップS205)。具体的には、シミュレーション依頼処理部493は、ステップS202でモデル生成部491が生成した血管の三次元モデルと、ステップS203で設定された解析条件を示すファイルと、送信する情報に基づく血流解析の依頼とを、第2通信部410を介して解析サーバ装置240へ送信する。 Next, the simulation request processing unit 493 transmits a blood flow analysis request to the analysis server device 240 (step S205). Specifically, the simulation request processing unit 493 analyzes the blood flow based on the three-dimensional model of the blood vessel generated by the model generation unit 491 in step S202, the file indicating the analysis conditions set in step S203, and the information to be transmitted. Is transmitted to the analysis server device 240 via the second communication unit 410.
 解析サーバ装置240では、得られた情報に基づいて有限体積法を用いて血流解析(血流のシミュレーション)を行う。
 具体的には、空間を正四面体のメッシュに分割する。そして、流量保存則等の法則を用いてメッシュ間の関係を示す方程式を立て、与えられた境界条件に整合するまで(誤差の大きさが所定の許容値以下となるまで)演算を繰り返す。上記のように、アイテム管理サーバ装置212は、空間のメッシュ分割と連立方程式及び境界条件の設定とを行う。そして、解析サーバ装置240が演算を実行する。
The analysis server device 240 performs blood flow analysis (blood flow simulation) using the finite volume method based on the obtained information.
Specifically, the space is divided into regular tetrahedral meshes. Then, an equation indicating the relationship between meshes is established using a law such as a flow rate conservation law, and the calculation is repeated until the boundary condition is met (until the magnitude of the error falls below a predetermined allowable value). As described above, the item management server device 212 performs space mesh division and simultaneous equations and boundary condition setting. And the analysis server apparatus 240 performs a calculation.
 解析サーバ装置240からの解析結果を第2通信部410が受信すると(ステップS206)、シミュレーション依頼処理部493は、解析結果を解析結果ファイルデータベース装置224に格納する(ステップS207)。具体的には、シミュレーション依頼処理部493は、解析結果を記憶させる指示と、記憶対象の解析結果(ステップS206で第2通信部410が受信した解析結果)とを、第2通信部410を介して解析結果ファイルデータベース装置224に送信する。 When the second communication unit 410 receives the analysis result from the analysis server device 240 (step S206), the simulation request processing unit 493 stores the analysis result in the analysis result file database device 224 (step S207). Specifically, the simulation request processing unit 493 sends an instruction to store the analysis result and the analysis result to be stored (the analysis result received by the second communication unit 410 in step S206) via the second communication unit 410. To the analysis result file database device 224.
 また、シミュレーション依頼処理部493は、診断レポート作成用端末装置232でのユーザ操作に基づいて診断レポートを作成する(ステップS208)。
 そして、シミュレーション依頼処理部493は、作成した診断レポートを依頼元の利用者端末装置100へ送信する(ステップS209)。具体的には、シミュレーション依頼処理部493は、ステップS208で作成した診断レポートを、第2通信部410を介して受付サーバ装置211へ送信する。そして、受付サーバ装置211は、受信した診断レポートを依頼元の利用者端末装置100へ送信(転送)する。
 ステップS209の後、図5の処理を終了する。
In addition, the simulation request processing unit 493 creates a diagnostic report based on a user operation on the diagnostic report creation terminal device 232 (step S208).
Then, the simulation request processing unit 493 transmits the created diagnostic report to the requesting user terminal device 100 (step S209). Specifically, the simulation request processing unit 493 transmits the diagnostic report created in step S208 to the reception server device 211 via the second communication unit 410. Then, the reception server device 211 transmits (transfers) the received diagnostic report to the requesting user terminal device 100.
After step S209, the process of FIG.
 次に、プリプロセッシング部492による境界条件の設定について説明する。
 上述したように三次元モデルの出入口における血管を延長した場合、元の出入口における測定値を延長後の出入口に変更することなく適用することはできない。
 そこで、例えば冠動脈など解析対象の血管に狭窄が無い場合、プリプロセッシング部492は、反射波に基づく境界条件を設定する。
 ここで、式(1)のように血圧を入射波と反射波とに分類する。
Next, setting of boundary conditions by the preprocessing unit 492 will be described.
As described above, when the blood vessel at the entrance / exit of the three-dimensional model is extended, the measurement value at the original entrance / exit cannot be applied to the extended entrance / exit.
Therefore, for example, when there is no stenosis in the blood vessel to be analyzed such as a coronary artery, the preprocessing unit 492 sets a boundary condition based on the reflected wave.
Here, blood pressure is classified into incident waves and reflected waves as shown in Equation (1).
Figure JPOXMLDOC01-appb-M000001
                  
Figure JPOXMLDOC01-appb-M000001
                  
 ここで、値Pは血圧の計測値(計測圧)を示す。値Pforは入射波を示す。値Prefは反射波を示す。入射波Pforは、拍出のエネルギーによる圧力を模擬する。一方、反射波Prefは末梢の血管等からの圧力の戻り(反射)を模擬する。
 ここで、入射波Pforを式(2)のように定義する。
Here, the value P indicates a blood pressure measurement value (measurement pressure). The value P for indicates the incident wave. The value P ref indicates the reflected wave. The incident wave P for simulates the pressure due to the energy of pulsation. On the other hand, the reflected wave Pref simulates pressure return (reflection) from peripheral blood vessels and the like.
Here, the incident wave P for is defined as shown in Equation (2).
Figure JPOXMLDOC01-appb-M000002
                  
Figure JPOXMLDOC01-appb-M000002
                  
 ここで、値Qは血流量を示す。また、値Zは、インピーダンスを示す。ここでいうインピーダンスとは、血圧を血流量で除算した値である。インピーダンスは、血流の流れにくさ(血流に対する抵抗の大きさ)を定量的に示す。
 また反射波Prefを式(3)のように定義する。
Here, the value Q indicates the blood flow rate. Further, the value Z 0 indicates impedance. The impedance here is a value obtained by dividing blood pressure by blood flow. Impedance quantitatively indicates the difficulty of blood flow (the magnitude of resistance to blood flow).
Also, the reflected wave Pref is defined as shown in Equation (3).
Figure JPOXMLDOC01-appb-M000003
                  
Figure JPOXMLDOC01-appb-M000003
                  
 インピーダンスZは、PQループにしたがって求められる。
 図6は、PQループの例を示す説明図である。同図に示すグラフの横軸は、大動脈を通過する血流量を示す。また、縦軸は、その部分での圧力を示す。
 線L11に示されるように、心臓の収縮期の早期は圧力が上がるとともに流量も増えていく。この収縮期の早期の部分では、また反射波が戻って来てない。この心臓の収縮期の早期における傾き「dP/dQ」がインピーダンスZとして用いられる。この傾きは、線L12の傾きによって示されている。
Impedance Z 0 is determined according to PQ loop.
FIG. 6 is an explanatory diagram showing an example of a PQ loop. The horizontal axis of the graph shown in the figure indicates the blood flow volume passing through the aorta. The vertical axis indicates the pressure at that portion.
As indicated by the line L11, the pressure increases and the flow rate increases early in the systole of the heart. In the early part of this systole, the reflected wave does not return again. The inclination “dP / dQ” in the early stage of the systole of the heart is used as the impedance Z 0 . This inclination is indicated by the inclination of the line L12.
 この反射波を用いることで、心拍に伴う血圧の変動を模擬することが可能になり、血管を延長した三次元モデルの出口における血圧を、より高精度に設定することができる。特に、患者固有の血管の弾性及び末梢抵抗を再現した境界条件を設定することができる。
 なお、ここで得られたインピーダンスを、血流を電気回路で模擬するランプドパラメータの手法における抵抗値として用いるようにしてもよい。
By using this reflected wave, it is possible to simulate blood pressure fluctuations associated with heartbeats, and the blood pressure at the outlet of the three-dimensional model with the blood vessels extended can be set with higher accuracy. In particular, it is possible to set boundary conditions that reproduce the elasticity and peripheral resistance of the blood vessels inherent to the patient.
The impedance obtained here may be used as a resistance value in a ramped parameter method for simulating blood flow with an electric circuit.
 解析対象の血管に狭窄が無い場合の、反射波に基づく境界条件を説明した。
 一方、血管の狭窄がある場合、上述したような反射波は返らなくなる。そこで、冠動脈の解析で血管の狭窄がある場合、プリプロセッシング部492は、実測に基づく変動インピーダンスを設定する。ここでいう変動インピーダンスとは、値が時間変動するインピーダンス(具体的には、心拍の位相に応じて値が変動するインピーダンス)である。
 具体的には、プリプロセッシング部492は、式(4)によるインピーダンスZ(t)を設定する。
The boundary conditions based on the reflected wave when there is no stenosis in the blood vessel to be analyzed have been described.
On the other hand, when there is a stenosis of the blood vessel, the reflected wave as described above does not return. Therefore, when there is a stenosis of the blood vessel in the analysis of the coronary artery, the preprocessing unit 492 sets a variable impedance based on the actual measurement. The fluctuation impedance here is an impedance whose value fluctuates with time (specifically, an impedance whose value fluctuates in accordance with the heartbeat phase).
Specifically, the preprocessing unit 492 sets the impedance Z (t) according to Expression (4).
Figure JPOXMLDOC01-appb-M000004
                  
Figure JPOXMLDOC01-appb-M000004
                  
 ここで、値P(t)は、測定された圧力波形(時刻毎の血圧)を示す。値Q(t)は、流量波形(時刻毎の血流量)を示す。また、定常静脈圧は、静脈部分での血圧である。式(4)では、毛細血管の圧較差を正確に求めるために、圧力波形から定常静脈圧を減算した圧較差が用いられている。 Here, the value P (t) indicates the measured pressure waveform (blood pressure at each time). The value Q (t) indicates a flow waveform (blood flow volume at each time). The steady venous pressure is a blood pressure in the venous portion. In equation (4), a pressure difference obtained by subtracting the steady venous pressure from the pressure waveform is used in order to accurately obtain the pressure difference of the capillaries.
 ここで、値「P(t)-定常静脈圧」は、毛細血管の部分にかかっている圧を示す。毛細血管に血流を流すためには、この値「P(t)-定常静脈圧」の圧力が必要となる。式(4)では、値「P(t)-定常静脈圧」を流量で除算して毛細血管での抵抗が求められている。
 この変動インピーダンス(インピーダンスZ(t))を用いることで、患者固有の変動インピーダンスを設定することができる。
Here, the value “P (t) −steady venous pressure” indicates the pressure applied to the capillary portion. In order to allow blood flow to flow through the capillaries, a pressure of this value “P (t) −steady venous pressure” is required. In the equation (4), the resistance in the capillary is obtained by dividing the value “P (t) −steady venous pressure” by the flow rate.
By using this variable impedance (impedance Z (t)), a patient-specific variable impedance can be set.
 また、プリプロセッシング部492は、心筋のバイアビリティ及び心筋灌流量を考慮した変動インピーダンスを設定する。ここでいう心筋のバイアビリティとは、心筋の細胞が生存している割合である。心筋細胞が死ぬと、その分、毛細血管の通路が少なくなり血流の抵抗値が変化する。そこで、プリプロセッシング部492は、冠動脈ごとの心筋の灌流域、及び、灌流域における心筋のバイアビリティに基づいて、変動インピーダンスを求める。 Also, the preprocessing unit 492 sets a variable impedance in consideration of myocardial viability and myocardial perfusion. Here, the viability of the myocardium is the rate at which myocardial cells are alive. When cardiomyocytes die, the amount of capillary passage is reduced and the resistance of blood flow changes. Therefore, the preprocessing unit 492 obtains a variable impedance based on the perfusion region of the myocardium for each coronary artery and the viability of the myocardium in the perfusion region.
 具体的には、プリプロセッシング部492は、CT画像から灌流域を推定する。プリプロセッシング部492は、心筋の領域を、最も近い冠動脈毎の灌流域に分割する。そして、プリプロセッシング部492は、灌流域における心筋の体積を算出し、得られた体積と心筋のバイアビリティとに基づいて血流に対するインピーダンスを求める。例えば、プリプロセッシング部492は、変動インピーダンスの変動幅及び平均値を心筋の体積及びバイアビリティに基づいて修正し、冠動脈の枝ごとにインピーダンスを求める。
 これにより、心筋ごとの血流の配分を求めることが可能になり、血流の配分に応じたインピーダンスを設定することができる。
Specifically, the preprocessing unit 492 estimates a perfusion area from the CT image. The preprocessing unit 492 divides the myocardial region into the nearest perfusion region for each coronary artery. Then, the preprocessing unit 492 calculates the volume of the myocardium in the perfusion region, and obtains the impedance to the blood flow based on the obtained volume and the viability of the myocardium. For example, the preprocessing unit 492 modifies the fluctuation width and average value of the fluctuation impedance based on the myocardial volume and viability, and obtains the impedance for each branch of the coronary artery.
Thereby, it becomes possible to obtain | require the distribution of the blood flow for every myocardium, and can set the impedance according to the distribution of the blood flow.
 プリプロセッシング部492は、三次元モデル内の血管の狭窄の有無及び血流に対する狭窄の影響に応じて、出口境界条件の設定を行う。
 具体的には、プリプロセッシング部492又はオペレータ(オペレーション端末装置231のユーザ)が、狭窄の有無、及び、狭窄がある場合は血流に対する狭窄の影響を無視し得るか否かを判定する。
The preprocessing unit 492 sets the exit boundary condition according to the presence or absence of stenosis of the blood vessel in the three-dimensional model and the influence of the stenosis on the blood flow.
Specifically, the preprocessing unit 492 or the operator (user of the operation terminal device 231) determines whether or not there is stenosis and whether or not the influence of stenosis on the blood flow can be ignored.
 プリプロセッシング部492が上記の判定を自動的に行う場合、例えば、血流解析対象の二次元断層画像に対する画像解析に基づいて判定を行う。
 具体的には、プリプロセッシング部492は、血管中に所定の長さ以下(例えば、1センチメートル以下)の領域、かつ、最狭部分の径が領域のいずれの端部の径に対しても所定の第一割合以下(例えば9割以下)の領域を検出した場合、検出した領域に狭窄ありと判定する。
 また、プリプロセッシング部492は、例えば、狭窄ありと判定した領域について局所的に血流のフロー解析を行う。そして、プリプロセッシング部492は、狭窄の後ろの圧力が狭窄の前の圧力に対して所定の第二割合以下(例えば8割以下)であると算出した場合、血流に対する狭窄の影響を無視できないと判定する。
When the preprocessing unit 492 automatically performs the above determination, for example, the determination is performed based on image analysis on a two-dimensional tomographic image to be analyzed for blood flow.
Specifically, the preprocessing unit 492 has a region in the blood vessel having a predetermined length or less (for example, 1 centimeter or less), and the diameter of the narrowest part is equal to the diameter of any end of the region. When an area of a predetermined first ratio or less (for example, 90% or less) is detected, it is determined that the detected area has stenosis.
In addition, the preprocessing unit 492 locally performs a blood flow analysis on, for example, a region determined to have stenosis. When the preprocessing unit 492 calculates that the pressure behind the stenosis is a predetermined second ratio or less (for example, 80% or less) with respect to the pressure before the stenosis, the influence of the stenosis on the blood flow cannot be ignored. Is determined.
 プリプロセッシング部492又はオペレータが狭窄無しと判定した場合、プリプロセッシング部492は、反射波を含む出口圧力を上記の方法で算出し、出口境界条件として設定する。プリプロセッシング部492又はオペレータが、狭窄の影響を無視し得ると判定した場合も同様である。
 一方、プリプロセッシング部492又はオペレータが、狭窄の影響を無視できないと判定した場合、プリプロセッシング部492は、出口境界から見たモデルの外部側の変動インピーダンスを上記の方法で算出し、出口境界条件として設定する。
When the preprocessing unit 492 or the operator determines that there is no stenosis, the preprocessing unit 492 calculates the outlet pressure including the reflected wave by the above method and sets it as the outlet boundary condition. The same applies when the preprocessing unit 492 or the operator determines that the influence of stenosis can be ignored.
On the other hand, when the preprocessing unit 492 or the operator determines that the influence of the stenosis cannot be ignored, the preprocessing unit 492 calculates the fluctuation impedance on the external side of the model viewed from the exit boundary by the above method, and the exit boundary condition Set as.
 また、大動脈の解析の場合、プリプロセッシング部492は、血圧の急激な変動に対する補正を行う。
 ここで、出口圧を値「0」としてCFDの演算を行った場合、大動脈の内圧に生体では起こりえない血圧の急激な上昇及び降下(オーバーシュート及びアンダーシュート)が見られた。
 図7は、大動脈の内圧の例を示す説明図である。同図に示すグラフの横軸は時刻を示し、縦軸は圧力を示す。また、領域A11では圧力がオーバーシュートしている。一方、領域A12では圧力がアンダーシュートしている。
In the case of analysis of the aorta, the preprocessing unit 492 performs correction for a rapid change in blood pressure.
Here, when the CFD calculation was performed with the outlet pressure as the value “0”, rapid increase and decrease in blood pressure (overshoot and undershoot) that could not occur in the living body were observed in the internal pressure of the aorta.
FIG. 7 is an explanatory diagram showing an example of the internal pressure of the aorta. The horizontal axis of the graph shown in the figure represents time, and the vertical axis represents pressure. In the area A11, the pressure overshoots. On the other hand, in the area A12, the pressure undershoots.
 この血圧の大きな変動は、弾性体である血管壁を剛体壁で模擬することによるシミュレーション誤差と考えられる。
 ここで、入口流量を微分すると、この圧力の急変と同様の波形を得られた。この入口流量の微分に基づいて、入口流量から圧力の急変を予測して逆位相の波形を重ねることができれば異常な圧力の変化を打ち消すことができる。
 但し、入口流量の波形から圧力の波形を推定することはできるが、入口流量の大きさと圧力の大きさとの関係は不明である。そこで、式(5)のように仮定し、実験にしたがって比例定数が求められる。
This large change in blood pressure is considered to be a simulation error caused by simulating a blood vessel wall, which is an elastic body, with a rigid body wall.
Here, when the inlet flow rate was differentiated, a waveform similar to this sudden change in pressure was obtained. Based on the differential of the inlet flow rate, if an abrupt change in pressure is predicted from the inlet flow rate and the waveforms of opposite phases can be superimposed, the abnormal pressure change can be canceled out.
Although the pressure waveform can be estimated from the inlet flow rate waveform, the relationship between the inlet flow rate and the pressure is unknown. Therefore, assuming that the equation is as shown in Equation (5), a proportionality constant is obtained according to an experiment.
Figure JPOXMLDOC01-appb-M000005
                  
Figure JPOXMLDOC01-appb-M000005
                  
 ここで、値kは比例定数を示す。また、値Pは圧を示す。
 比例定数kの値を求めるために、線形的に流量が上昇して線形的に流量が下がるという境界条件が設定される。
 図8は、比例定数kの値を求めるために設定する境界条件の例を示すグラフである。同図に示すグラフの横軸は時刻を示し、縦軸は流量を示す。図8の線L21によると、流量が一定の割合で増加した後、一定の割合で減少している。
Here, the value k indicates a proportionality constant. The value P a indicates the pressure.
In order to obtain the value of the proportionality constant k, a boundary condition is set such that the flow rate increases linearly and the flow rate decreases linearly.
FIG. 8 is a graph showing an example of boundary conditions set for obtaining the value of the proportionality constant k. The horizontal axis of the graph shown in the figure represents time, and the vertical axis represents flow rate. According to line L21 in FIG. 8, the flow rate increases at a constant rate and then decreases at a constant rate.
 図9は、図8の入口流量を設定した場合の大動脈の内圧の計算結果の例を示すグラフである。図9に示すグラフの横軸は時刻を示し、縦軸は圧力を示す。
 図9に示すグラフでは、入口流量の増加時に圧力P11のオフセットが生じている。この圧力P11が値dQ/dtによる圧力と考えられる。一方、圧力P12は、流量Qによる圧力と考えられる。そこで、圧力P12が式(5)のPに代入され、流量Qの傾きが式(5)の値dQ/dtに代入される。これにより、比例定数kの値を求めることができる。
FIG. 9 is a graph showing an example of the calculation result of the internal pressure of the aorta when the inlet flow rate of FIG. 8 is set. The horizontal axis of the graph shown in FIG. 9 indicates time, and the vertical axis indicates pressure.
In the graph shown in FIG. 9, the pressure P11 is offset when the inlet flow rate is increased. This pressure P11 is considered to be a pressure due to the value dQ / dt. On the other hand, the pressure P12 is considered to be a pressure due to the flow rate Q. Therefore, the pressure P12 is assigned to P a of formula (5), the slope of the flow rate Q is substituted into the value dQ / dt of the formula (5). As a result, the value of the proportionality constant k can be obtained.
 プリプロセッシング部492は、得られた比例定数kを用いて出口圧力を式(6)のように設定する。 The preprocessing unit 492 sets the outlet pressure as shown in Expression (6) using the obtained proportionality constant k.
Figure JPOXMLDOC01-appb-M000006
                  
Figure JPOXMLDOC01-appb-M000006
                  
 ここで、値Poutは出口圧力を示す。値Prefは、式(3)に示される反射波の項である。また、項「-k×(dQ/dt)」は、上述した血圧の急激な上昇及び降下を打ち消すための項である。値「k×(dQ/dt)」は、血液の入口流量の微分に比例する値の例に該当する。
 この出口圧力を用いることで、出口圧力に実際の血圧に近い血圧を設定することができる。
Here, the value Pout indicates the outlet pressure. The value P ref is a term of the reflected wave shown in Expression (3). The term “−k × (dQ / dt)” is a term for canceling the rapid increase and decrease in blood pressure described above. The value “k × (dQ / dt)” corresponds to an example of a value proportional to the derivative of the blood inlet flow rate.
By using this outlet pressure, a blood pressure close to the actual blood pressure can be set as the outlet pressure.
 また、プリプロセッシング部492は、自律神経による血流の調整に対応する境界条件を設定する。
 ここで上半身及び下半身に流れる血流量は自律神経で調整されている。例えば、自律神経は、下半身に血流が流れ過ぎないよう血管の筋肉を閉めて流量を制御することで頭の方に血流が流れるようにする。
 これに対しプリプロセッシング部492は、自律神経による血流の調整を模擬するため、式(7)に示される出口圧力を設定する。
The preprocessing unit 492 sets boundary conditions corresponding to blood flow adjustment by the autonomic nerve.
Here, the blood flow amount flowing through the upper body and the lower body is adjusted by the autonomic nerve. For example, the autonomic nerve causes blood flow to flow toward the head by closing the muscles of the blood vessels and controlling the flow rate so that blood does not flow too much in the lower body.
On the other hand, the preprocessing unit 492 sets the outlet pressure represented by Expression (7) in order to simulate the adjustment of blood flow by the autonomic nerve.
Figure JPOXMLDOC01-appb-M000007
                  
Figure JPOXMLDOC01-appb-M000007
                  
 ここで、値Poutは出口圧力を示す。また、値Pinerには、式(6)の出口圧力Poutが代入される。またHはヘビサイト関数を示す。項「Qout-Qin」の値がプラスの場合、ヘビサイト関数H(Qout-Qin)の値は「1」になる。項「Qout-Qin」の値がゼロの場合、ヘビサイト関数H(Qout-Qin)の値は「1/2」になる。また、項「Qout-Qin」の値がマイナスの場合、ヘビサイト関数H(Qout-Qin)の値は「0」になる。 Here, the value Pout indicates the outlet pressure. Further, the value P INER, outlet pressure P out of the equation (6) is substituted. H represents a snake site function. When the value of the term “Q out −Q in ” is positive, the value of the heavy site function H (Q out −Q in ) is “1”. When the value of the term “Q out −Q in ” is zero, the value of the heavy site function H (Q out −Q in ) is “½”. Further, when the value of the term “Q out −Q in ” is negative, the value of the heavy site function H (Q out −Q in ) is “0”.
 また、値Qout、Qinはそれぞれ、出口流量、入口流量を示す。また、値Kは定数である。この定数Kの値は例えば経験的に設定される。
 式(7)で、項「Qout-Qin」の値がプラスの場合、値Qoutの方が値Qinよりも大きいことを示し、血流が逆流していることを意味する。そこで、式(7)によって、逆流している分だけ圧力が上昇される。これにより、自律神経による血流の調整が模擬される。なお、ヘビサイト関数Hにオフセットを持たせるようにしてもよい。
The values Q out and Q in indicate the outlet flow rate and the inlet flow rate, respectively. The value K is a constant. The value of the constant K is set empirically, for example.
In the equation (7), when the value of the term “Q out −Q in ” is positive, it indicates that the value Q out is larger than the value Q in , which means that the blood flow is flowing backward. Therefore, the pressure is increased by the amount of backflow according to the equation (7). Thereby, adjustment of blood flow by the autonomic nerve is simulated. The snake site function H may be offset.
 CFDにおける条件設定を容易にするために、受付サーバ装置211は、利用者端末装置100に入力画面を提供する。例えば、メッシュのサイズや境界領域の長さを、ユーザ(解析を依頼する担当医)が適切に設定することは現実的ではない。そこで、受付サーバ装置211(第1制御部390)は、これらの入力項目にデフォルト値が入力された入力画面を提供する。ユーザは、このデフォルト値を変更することなく使うことで、複雑な数値の設定を行う必要無しに、血流解析を依頼することができる。
 また、受付サーバ装置211(第1制御部390)は、例えば冠動脈、あるいは、大動脈の狭窄など、血流解析のパタン毎に入力画面を提供する。これにより、受付サーバ装置211は、血流解析のパタン毎に適切なデフォルト値を提供することができる。また、ユーザは、血流解析のパタンに応じて必要な入力項目を把握することができる。
In order to facilitate condition setting in CFD, the reception server device 211 provides an input screen to the user terminal device 100. For example, it is not realistic for the user (the doctor in charge who requests the analysis) to appropriately set the size of the mesh and the length of the boundary region. Therefore, the reception server device 211 (first control unit 390) provides an input screen in which default values are input to these input items. By using this default value without changing it, the user can request blood flow analysis without having to set complicated numerical values.
In addition, the reception server device 211 (first control unit 390) provides an input screen for each pattern of blood flow analysis such as coronary artery or aortic stenosis. Thereby, the reception server device 211 can provide an appropriate default value for each pattern of blood flow analysis. In addition, the user can grasp necessary input items according to the pattern of blood flow analysis.
 また、プリプロセッシング部492は、入口流量が既知か否かに基づいて、入口流量又は入口圧力のいずれかを入口境界条件として設定する。入口流量が既知か否かの判定を、プリプロセッシング部492が自動で行ってもよいし、オペレータ(オペレーション端末装置231のユーザ)が行ってもよい。 Further, the preprocessing unit 492 sets either the inlet flow rate or the inlet pressure as the inlet boundary condition based on whether the inlet flow rate is known. The preprocessing unit 492 may automatically determine whether the inlet flow rate is known or may be determined by an operator (user of the operation terminal device 231).
 入口流量が既知か否かの判定を自動で行う場合、プリプロセッシング部492は、例えば、利用者端末装置100からの解析依頼に入口流量に相当する血流量の情報が含まれているか否かを判定することで、入口流量を既知か否かを判定する。入口流量を既知であると判定した場合(すなわち、入口流量に相当する血流量の情報が解析依頼に含まれていると判定した場合)、プリプロセッシング部492は、この血流量を入口流量として設定する。
 一方、入口流量を未知であると判定した場合(すなわち、入口流量に相当する血流量の情報が解析依頼に含まれていないと判定した場合)、プリプロセッシング部492は、入口圧力に相当する血圧の情報を解析依頼から読み出し、入口圧力として設定する。
When automatically determining whether the inlet flow rate is known, the preprocessing unit 492 determines, for example, whether the analysis request from the user terminal device 100 includes blood flow information corresponding to the inlet flow rate. By determining, it is determined whether or not the inlet flow rate is known. When it is determined that the inlet flow rate is known (that is, when it is determined that blood flow information corresponding to the inlet flow rate is included in the analysis request), the preprocessing unit 492 sets the blood flow rate as the inlet flow rate. To do.
On the other hand, when it is determined that the inlet flow rate is unknown (that is, when it is determined that blood flow information corresponding to the inlet flow rate is not included in the analysis request), the preprocessing unit 492 displays the blood pressure corresponding to the inlet pressure. Is read from the analysis request and set as the inlet pressure.
 このように、プリプロセッシング部492は、入口流量が既知の場合は入口流量を入口境界条件として設定する。一方、入口流量が未知の場合、プリプロセッシング部492は、入口圧力を入口境界条件として設定する。
 これにより、血流解析システム200は、入口流量が未知の場合でも血流解析を行うことができる。従って、血流解析システム200によれば、入口流量を求めるための追加的な検査が行われていない場合でも、血流解析を行うことができる。
Thus, the preprocessing unit 492 sets the inlet flow rate as the inlet boundary condition when the inlet flow rate is known. On the other hand, when the inlet flow rate is unknown, the preprocessing unit 492 sets the inlet pressure as the inlet boundary condition.
Thereby, the blood flow analysis system 200 can perform blood flow analysis even when the inlet flow rate is unknown. Therefore, according to the blood flow analysis system 200, blood flow analysis can be performed even when an additional test for obtaining the inlet flow rate is not performed.
 以上のように、受付サーバ装置211の第1通信部310は、血流解析対象の二次元断層画像を含む解析依頼を、通信ネットワーク900を介して利用者端末装置100から受信する。そして、匿名化処理部392は、解析依頼から解析対象者を特定する情報を削除し、解析対象者を識別する管理番号を付与する。解析サーバ装置240は、二次元断層画像に基づいて血管形状の三次元モデルを生成する。そして、プリプロセッシング部492は、三次元モデルに基づく血流のシミュレーションのための有限体積法の条件設定を行う。シミュレーション依頼処理部493は、三次元モデル及びプリプロセッシング部492が設定した条件と管理番号とを含むシミュレーション依頼(血流解析の依頼)を生成する。解析サーバ装置240は、シミュレーション依頼に基づいて有限体積法を用いた流体解析手法によって血流のシミュレーションを行う。診断レポート処理部494は、シミュレーション依頼処理部493によるシミュレーション結果に基づく解析結果を生成する。そして、第1通信部310は、解析結果を管理番号に基づいて依頼元へ送信する。 As described above, the first communication unit 310 of the reception server device 211 receives an analysis request including a two-dimensional tomographic image to be analyzed for blood flow from the user terminal device 100 via the communication network 900. Then, the anonymization processing unit 392 deletes information specifying the analysis target person from the analysis request, and assigns a management number for identifying the analysis target person. The analysis server device 240 generates a three-dimensional model of the blood vessel shape based on the two-dimensional tomographic image. Then, the preprocessing unit 492 performs finite volume method condition setting for blood flow simulation based on the three-dimensional model. The simulation request processing unit 493 generates a simulation request (a blood flow analysis request) including the conditions set by the 3D model and the preprocessing unit 492 and the management number. The analysis server device 240 performs blood flow simulation by a fluid analysis method using a finite volume method based on the simulation request. The diagnosis report processing unit 494 generates an analysis result based on the simulation result by the simulation request processing unit 493. Then, the first communication unit 310 transmits the analysis result to the request source based on the management number.
 このように、匿名化処理部392が解析依頼から解析対象者を特定する情報を削除し、解析対処毎の管理番号を付与することで、仮に、病状の情報など解析依頼に含まれる情報が流出した場合であっても、流出した情報は個人に結び付けられない。
 この点で、血流解析システム200によれば、患者のプライバシーに配慮して血流の解析を依頼することができる。
As described above, the anonymization processing unit 392 deletes information for identifying the analysis target person from the analysis request, and assigns a management number for each analysis countermeasure, so that information included in the analysis request such as information on a medical condition is leaked. Even if you do, the leaked information is not tied to the individual.
In this regard, according to the blood flow analysis system 200, blood flow analysis can be requested in consideration of patient privacy.
 また、医療データファイルデータベース装置222、解析用ファイルデータベース装置223及び解析結果ファイルデータベース装置224のデータベース群は、解析依頼に含まれる情報、シミュレーション結果、及び、シミュレーション結果に基づく解析結果に含まれる情報のうち少なくともいずれか一つを、管理番号に基づいて解析対象者毎に記憶する。そして、診断レポート処理部494は、データベース群が記憶する情報に基づいて、血流の状況の予測を示す情報を含む解析結果を生成する。
 このように、データベース群が管理番号に基づいて解析対象者毎に情報を記憶することで、血流の状況の時間変化について統計データを得ることができる。
The database group of the medical data file database device 222, the analysis file database device 223, and the analysis result file database device 224 includes information included in the analysis request, simulation results, and information included in the analysis results based on the simulation results. At least one of them is stored for each person to be analyzed based on the management number. Then, the diagnosis report processing unit 494 generates an analysis result including information indicating the prediction of the blood flow state based on the information stored in the database group.
As described above, the database group stores information for each person to be analyzed based on the management number, so that statistical data can be obtained regarding the temporal change in the blood flow state.
 また、第1通信部310は、血流に関する手術の内容を示す情報を含む解析依頼を受信する。そして、診断レポート処理部494は、その手術の内容で手術を行った場合における血流の状況を示す情報を含む解析結果を生成する。
 これにより、ユーザ(例えば、手術を行う担当医)は、予定している手術の適否を事前に確認することができる。
Moreover, the 1st communication part 310 receives the analysis request containing the information which shows the content of the operation regarding blood flow. Then, the diagnosis report processing unit 494 generates an analysis result including information indicating a blood flow state when an operation is performed with the content of the operation.
Thereby, a user (for example, a doctor in charge performing an operation) can confirm in advance whether or not the planned operation is appropriate.
 また、プリプロセッシング部492は、三次元モデルにおける入口及び出口の血管のうち少なくともいずれか一方を延長する。
 これにより、プリプロセッシング部492は、三次元モデルの入口及び出口における血流の影響を低減させることができ、血流解析の精度を向上させることができる。
The preprocessing unit 492 extends at least one of the inlet and outlet blood vessels in the three-dimensional model.
Thereby, the preprocessing unit 492 can reduce the influence of blood flow at the entrance and exit of the three-dimensional model, and can improve the accuracy of blood flow analysis.
 また、プリプロセッシング部492は、血圧の反射波を含む出口圧力を設定する。
 これにより、三次元モデルにおける入口及び出口の血管のうち少なくともいずれか一方を延長した場合でも、プリプロセッシング部492は、適切な境界条件を設定することができる。これにより、プリプロセッシング部492は、血流解析の精度を向上させることができる。
Further, the preprocessing unit 492 sets an outlet pressure including a reflected wave of blood pressure.
Accordingly, even when at least one of the inlet and outlet blood vessels in the three-dimensional model is extended, the preprocessing unit 492 can set an appropriate boundary condition. Thereby, the preprocessing unit 492 can improve the accuracy of blood flow analysis.
 また、プリプロセッシング部492は、冠動脈の解析で三次元モデル内の血管に狭窄が無いと判定した場合、及び、血流に対する狭窄の影響を無視できると判定した場合、血圧の反射波を含む出口圧力を設定する。一方、血流に対する狭窄の影響を無視できないと判定した場合、プリプロセッシング部492は、三次元モデルの出口境界に変動インピーダンス(値が時間変動するインピーダンス)を設定する。
 これにより、プリプロセッシング部492は、血管の狭窄の有無にかかわらず、血流解析をより精度に行うことができる。
In addition, when the preprocessing unit 492 determines that there is no stenosis in the blood vessel in the three-dimensional model in the analysis of the coronary artery and determines that the influence of the stenosis on the blood flow can be ignored, Set the pressure. On the other hand, when it is determined that the influence of stenosis on the blood flow cannot be ignored, the preprocessing unit 492 sets a variable impedance (impedance whose value varies with time) at the exit boundary of the three-dimensional model.
Thereby, the preprocessing unit 492 can perform blood flow analysis more accurately regardless of the presence or absence of stenosis of blood vessels.
 また、プリプロセッシング部492は、血流の入口流量の微分に比例する値を出口圧力から減算する修正を行う。
 これにより、プリプロセッシング部492は、血管壁の弾性を模擬することができ、この点で、血流解析の精度を向上させることができる。
The preprocessing unit 492 performs correction to subtract a value proportional to the derivative of the inlet flow rate of the blood flow from the outlet pressure.
Thereby, the preprocessing unit 492 can simulate the elasticity of the blood vessel wall, and in this respect, the accuracy of blood flow analysis can be improved.
 また、プリプロセッシング部492は、ヘビサイト関数を用いて自律神経による血流の調整を模擬した出口圧力を設定する。プリプロセッシング部492は、自律神経による血流の調整を模擬することで、血流解析の精度を向上させることができる。 Also, the preprocessing unit 492 sets an outlet pressure simulating blood flow adjustment by the autonomic nerve using a snake sight function. The preprocessing unit 492 can improve the accuracy of blood flow analysis by simulating blood flow adjustment by the autonomic nerve.
 また、プリプロセッシング部492は、三次元モデルの入口境界における流量が既知であると判定した場合、入口境界条件として血流の入口流量を設定する。一方、入口境界における流量が未知であると判定した場合、プリプロセッシング部492は、入口境界条件として血流の入口圧力を設定する。
 これにより、プリプロセッシング部492は、入口境界における流量が既知か否かにかかわらず、血流解析をより精度に行うことができる。
Further, when the preprocessing unit 492 determines that the flow rate at the inlet boundary of the three-dimensional model is known, the preprocessing unit 492 sets the inlet flow rate of the blood flow as the inlet boundary condition. On the other hand, when determining that the flow rate at the inlet boundary is unknown, the preprocessing unit 492 sets the inlet pressure of the blood flow as the inlet boundary condition.
Thereby, the preprocessing unit 492 can perform blood flow analysis more accurately regardless of whether or not the flow rate at the inlet boundary is known.
 次に、図10及び図11を参照して実施の形態の最小構成について説明する。
 図10は、実施の形態に係る血流解析システムの最小構成を示す概略ブロック図である。同図に示すように、血流解析システム10は、解析依頼受信部11と、匿名化処理部12と、モデル生成部13と、条件設定部14と、シミュレーション依頼処理部15と、解析実行部16と、解析結果生成部17と、解析結果送信部18とを備える。
Next, the minimum configuration of the embodiment will be described with reference to FIGS.
FIG. 10 is a schematic block diagram showing the minimum configuration of the blood flow analysis system according to the embodiment. As shown in the figure, the blood flow analysis system 10 includes an analysis request receiving unit 11, an anonymization processing unit 12, a model generation unit 13, a condition setting unit 14, a simulation request processing unit 15, and an analysis execution unit. 16, an analysis result generation unit 17, and an analysis result transmission unit 18.
 図10の血流解析システム10において、解析依頼受信部11は、血流解析対象の二次元断層画像を含む解析依頼を、通信ネットワークを介して受信する。匿名化処理部12は、解析依頼から解析対象者を特定する情報を削除し、解析対象者を識別する管理番号を付与する。モデル生成部13は、二次元断層画像に基づいて血管形状の三次元モデルを生成する。条件設定部14は、三次元モデルに基づく血流のシミュレーションのための有限体積法の条件設定を行う。シミュレーション依頼処理部15は、三次元モデル及び条件設定部14が設定した条件と管理番号とを含むシミュレーション依頼を生成する。解析実行部16は、シミュレーション依頼に基づいて有限体積法を用いた流体解析手法によって血流のシミュレーションを行う。解析結果生成部17は、解析実行部16によるシミュレーション結果に基づく解析結果を生成する。解析結果送信部18は、解析結果を管理番号に基づいた依頼元へ送信する。 10, the analysis request receiving unit 11 receives an analysis request including a two-dimensional tomographic image to be analyzed for blood flow via a communication network. The anonymization processing unit 12 deletes information for specifying the analysis target person from the analysis request and assigns a management number for identifying the analysis target person. The model generation unit 13 generates a three-dimensional model of the blood vessel shape based on the two-dimensional tomographic image. The condition setting unit 14 sets conditions for a finite volume method for blood flow simulation based on a three-dimensional model. The simulation request processing unit 15 generates a simulation request including the conditions set by the three-dimensional model and condition setting unit 14 and a management number. The analysis execution unit 16 performs a blood flow simulation by a fluid analysis method using a finite volume method based on the simulation request. The analysis result generation unit 17 generates an analysis result based on the simulation result by the analysis execution unit 16. The analysis result transmission unit 18 transmits the analysis result to the request source based on the management number.
 このように、匿名化処理部12は、解析依頼から解析対象者を特定する情報を削除し、解析対処毎の管理番号を付与する。これにより、仮に、病状の情報など解析依頼に含まれる情報が流出した場合でも、流出した情報は個人に結び付けられない。
 この点で、血流解析システム10によれば、患者のプライバシーに配慮して血流の解析を依頼することができる。
In this way, the anonymization processing unit 12 deletes information for identifying the person to be analyzed from the analysis request, and assigns a management number for each analysis countermeasure. Thereby, even if information included in the analysis request such as medical condition information is leaked, the leaked information is not linked to an individual.
In this regard, the blood flow analysis system 10 can request blood flow analysis in consideration of patient privacy.
 図11は、実施の形態に係る解析依頼受付システムの最小構成を示す概略ブロック図である。同図に示すように、解析依頼受付システム20は、解析依頼受信部21と、匿名化処理部22と、モデル生成部23と、条件設定部24と、シミュレーション依頼処理部25と、解析結果生成部26と、解析結果送信部27とを備える。 FIG. 11 is a schematic block diagram showing the minimum configuration of the analysis request receiving system according to the embodiment. As shown in the figure, the analysis request receiving system 20 includes an analysis request receiving unit 21, an anonymization processing unit 22, a model generation unit 23, a condition setting unit 24, a simulation request processing unit 25, and an analysis result generation. Unit 26 and an analysis result transmitting unit 27.
 図11の解析依頼受付システム20において、解析依頼受信部21は、血流解析対象の二次元断層画像を含む解析依頼を、通信ネットワークを介して受信する。匿名化処理部22は、解析依頼から解析対象者を特定する情報を削除し、解析対象者を識別する管理番号を付与する。モデル生成部23は、二次元断層画像に基づいて血管形状の三次元モデルを生成する。条件設定部24は、三次元モデルに基づく血流のシミュレーションのための有限体積法の条件設定を行う。シミュレーション依頼処理部25は、三次元モデル及び条件設定部24が設定した条件と管理番号とを含むシミュレーション依頼を生成する。解析結果生成部26は、シミュレーション依頼に基づいて有限体積法を用いた流体解析手法によって行われた血流のシミュレーションの結果に基づく解析結果を生成する。解析結果送信部27は、解析結果を管理番号に基づいて依頼元へ送信する。 In the analysis request receiving system 20 in FIG. 11, the analysis request receiving unit 21 receives an analysis request including a two-dimensional tomographic image to be analyzed for blood flow via a communication network. The anonymization processing unit 22 deletes information for identifying the analysis target person from the analysis request and assigns a management number for identifying the analysis target person. The model generation unit 23 generates a three-dimensional model of the blood vessel shape based on the two-dimensional tomographic image. The condition setting unit 24 sets conditions for the finite volume method for blood flow simulation based on the three-dimensional model. The simulation request processing unit 25 generates a simulation request including the conditions set by the three-dimensional model and condition setting unit 24 and the management number. The analysis result generation unit 26 generates an analysis result based on the result of the blood flow simulation performed by the fluid analysis method using the finite volume method based on the simulation request. The analysis result transmission unit 27 transmits the analysis result to the request source based on the management number.
 このように、匿名化処理部22は解析依頼から解析対象者を特定する情報を削除し、解析対処毎の管理番号を付与する。これにより、仮に、病状の情報など解析依頼に含まれる情報が流出した場合であっても、流出した情報は個人に結び付けられない。
 これにより、解析依頼受付システム20によれば、患者のプライバシーに配慮して血流の解析を依頼することができる。
As described above, the anonymization processing unit 22 deletes information for identifying the person to be analyzed from the analysis request, and assigns a management number for each analysis countermeasure. Thus, even if information included in the analysis request such as medical condition information is leaked, the leaked information is not tied to an individual.
Thereby, according to the analysis request reception system 20, it is possible to request blood flow analysis in consideration of patient privacy.
 なお、血流解析システム10、200及び解析依頼受付システム20の全部又は一部の機能を、CPUがプログラムを読み出して実行することで実現することができる。その場合、この機能を実現するためのプログラムをコンピュータ読み取り可能な記録媒体に記録して、この記録媒体に記録されたプログラムをコンピュータシステムに読み込ませ、実行することによって実現してもよい。なお、ここでいう「コンピュータシステム」とは、OSや周辺機器等のハードウェアを含むものとする。また、「コンピュータ読み取り可能な記録媒体」とは、フレキシブルディスク、光磁気ディスク、ROM、CD-ROM等の可搬媒体、コンピュータシステムに内蔵されるハードディスク等の記憶装置のことをいう。
また上記プログラムは、前述した機能の一部を実現するためのものであってもよく、さらに前述した機能をコンピュータシステムにすでに記録されているプログラムとの組み合わせで実現できるものであってもよく、FPGA(Field Programmable Gate Array)等のプログラマブルロジックデバイスを用いて実現されるものであってもよい。
Note that all or some of the functions of the blood flow analysis systems 10 and 200 and the analysis request reception system 20 can be realized by the CPU reading and executing the program. In that case, a program for realizing this function may be recorded on a computer-readable recording medium, and the program recorded on this recording medium may be read into a computer system and executed. Here, the “computer system” includes an OS and hardware such as peripheral devices. The “computer-readable recording medium” refers to a storage device such as a flexible medium, a magneto-optical disk, a portable medium such as a ROM or a CD-ROM, and a hard disk incorporated in a computer system.
Further, the program may be a program for realizing a part of the above-described functions, and may be a program capable of realizing the functions described above in combination with a program already recorded in a computer system. You may implement | achieve using programmable logic devices, such as FPGA (Field Programmable Gate Array).
 以上、この発明の実施形態について図面を参照して詳述してきたが、具体的な構成はこの実施形態に限られるものではなく、この発明の要旨を逸脱しない範囲の設計等も含まれる。 As described above, the embodiment of the present invention has been described in detail with reference to the drawings. However, the specific configuration is not limited to this embodiment, and includes design and the like within the scope not departing from the gist of the present invention.
 この出願は、2016年4月12日に日本に出願された特願2016-079905号を基礎とする優先権を主張し、その開示の全てをここに取り込む。 This application claims priority based on Japanese Patent Application No. 2016-079905 filed in Japan on April 12, 2016, the entire disclosure of which is incorporated herein.
 本発明によれば、患者のプライバシーに配慮して血流の解析を依頼することができる。 According to the present invention, blood flow analysis can be requested in consideration of patient privacy.
 100 利用者端末装置
 10、200 血流解析システム
 11、21 解析依頼受信部
 12、22、392 匿名化処理部
 13、23、491 モデル生成部
 14、24 条件設定部
 15、25、493 シミュレーション依頼処理部
 16 解析実行部
 17、26 解析結果生成部
 18、27 解析結果送信部
 20、210 解析依頼受付システム
 211 受付サーバ装置
 310 第1通信部
 380 第1記憶部
 390 第1制御部
 391 ユーザ認証部
 212 アイテム管理サーバ装置
 410 第2通信部
 480 第2記憶部
 490 第2制御部
 492 プリプロセッシング部
 494 診断レポート処理部
 221 利用者認証用データベース装置
 222 医療データファイルデータベース装置
 223 解析用ファイルデータベース装置
 224 解析結果ファイルデータベース装置
 231 オペレーション端末装置
 232 診断レポート作成用端末装置
 240 解析サーバ装置
 900 通信ネットワーク
DESCRIPTION OF SYMBOLS 100 User terminal device 10, 200 Blood flow analysis system 11, 21 Analysis request receiving part 12, 22, 392 Anonymization processing part 13, 23, 491 Model generation part 14, 24 Condition setting part 15, 25, 493 Simulation request process Unit 16 analysis execution unit 17, 26 analysis result generation unit 18, 27 analysis result transmission unit 20, 210 analysis request reception system 211 reception server device 310 first communication unit 380 first storage unit 390 first control unit 391 user authentication unit 212 Item management server device 410 Second communication unit 480 Second storage unit 490 Second control unit 492 Preprocessing unit 494 Diagnostic report processing unit 221 User authentication database device 222 Medical data file database device 223 Analysis file database device 224 Analysis result Phi Database system 231 operation terminal 232 diagnostic report creation terminal unit 240 analyzes the server device 900 a communication network

Claims (12)

  1.  血流解析対象の二次元断層画像を含む解析依頼を通信ネットワークを介して受信する解析依頼受信部と、
     前記解析依頼から解析対象者を特定する情報を削除し、前記解析対象者を識別する管理番号を付与する匿名化処理部と、
     前記二次元断層画像に基づいて血管形状の三次元モデルを生成するモデル生成部と、
     前記三次元モデルに基づく血流のシミュレーションに用いられる有限体積法の条件を設定する条件設定部と、
     前記三次元モデル、前記条件設定部が設定した前記条件、及び、前記管理番号を含むシミュレーション依頼を生成するシミュレーション依頼処理部と、
     前記シミュレーション依頼に基づいて、前記有限体積法を用いた流体解析手法によって前記血流のシミュレーションを行う解析実行部と、
     前記解析実行部によるシミュレーション結果に基づく解析結果を生成する解析結果生成部と、
     前記解析結果を前記管理番号に基づいて依頼元へ送信する解析結果送信部と、
     を備える血流解析システム。
    An analysis request receiving unit that receives an analysis request including a two-dimensional tomographic image to be analyzed for blood flow via a communication network;
    Anonymization processing unit that deletes information for identifying an analysis target person from the analysis request and gives a management number for identifying the analysis target person;
    A model generation unit that generates a three-dimensional model of a blood vessel shape based on the two-dimensional tomographic image;
    A condition setting unit for setting conditions of a finite volume method used for simulation of blood flow based on the three-dimensional model;
    A simulation request processing unit that generates a simulation request including the three-dimensional model, the condition set by the condition setting unit, and the management number;
    Based on the simulation request, an analysis execution unit that simulates the blood flow by a fluid analysis method using the finite volume method;
    An analysis result generation unit that generates an analysis result based on a simulation result by the analysis execution unit;
    An analysis result transmitter for transmitting the analysis result to the requester based on the management number;
    A blood flow analysis system comprising:
  2.  前記解析依頼に含まれる情報、前記シミュレーション結果、及び、前記解析結果に含まれる情報のうち少なくともいずれか一つを、前記管理番号に基づいて解析対象者毎に記憶する経時情報記憶部を備え、
     前記解析結果生成部は、前記経時情報記憶部が記憶する情報に基づいて、前記血流の状況の予測を示す情報を含む前記解析結果を生成する、
     請求項1に記載の血流解析システム。
    A temporal information storage unit that stores at least one of the information included in the analysis request, the simulation result, and the information included in the analysis result for each person to be analyzed based on the management number;
    The analysis result generation unit generates the analysis result including information indicating prediction of the blood flow state based on information stored in the time-lapse information storage unit.
    The blood flow analysis system according to claim 1.
  3.  前記解析依頼受信部は、前記血流に関する手術の内容を示す情報をさらに含む前記解析依頼を受信し、
     前記解析結果生成部は、前記手術の内容で手術が行われた場合の前記血流の状況を示す情報を含む前記解析結果を生成する、
     請求項1または請求項2に記載の血流解析システム。
    The analysis request receiving unit receives the analysis request further including information indicating the content of the surgery related to the blood flow,
    The analysis result generation unit generates the analysis result including information indicating the state of the blood flow when an operation is performed with the content of the operation.
    The blood flow analysis system according to claim 1 or 2.
  4.  前記条件設定部は、前記三次元モデルにおける入口及び出口の血管のうち少なくともいずれか一方の延長を設定する、
     請求項1から3のいずれか1項に記載の血流解析システム。
    The condition setting unit sets an extension of at least one of the inlet and outlet blood vessels in the three-dimensional model.
    The blood flow analysis system according to any one of claims 1 to 3.
  5.  前記条件設定部は、血圧の反射波を含む出口圧力を設定する、
     請求項1から4のいずれか1項に記載の血流解析システム。
    The condition setting unit sets an outlet pressure including a reflected wave of blood pressure.
    The blood flow analysis system according to any one of claims 1 to 4.
  6.  前記条件設定部は、冠動脈の解析で前記三次元モデル内の血管に狭窄が無いと判定された場合、及び、前記血流に対する狭窄の影響を無視できると判定された場合に、血圧の反射波を含む出口圧力を設定し、前記影響を無視できないと判定された場合に、前記三次元モデルの出口境界に値が時間変動するインピーダンスを設定する、
     請求項1から4のいずれか一項に記載の血流解析システム。
    When the condition setting unit determines that there is no stenosis in the blood vessel in the three-dimensional model in the analysis of the coronary artery, and when it is determined that the influence of the stenosis on the blood flow can be ignored, the reflected wave of blood pressure When the outlet pressure including is determined and it is determined that the influence cannot be ignored, an impedance whose value varies with time at the outlet boundary of the three-dimensional model is set.
    The blood flow analysis system according to any one of claims 1 to 4.
  7.  前記条件設定部は、前記血流の入口流量の微分に比例する値を出口圧力から減算する修正を行う、請求項1から6のいずれか1項に記載の血流解析システム。 The blood flow analysis system according to any one of claims 1 to 6, wherein the condition setting unit performs correction by subtracting a value proportional to the derivative of the inlet flow rate of the blood flow from the outlet pressure.
  8.  前記条件設定部は、ヘビサイト関数を用いて自律神経による前記血流の調整を模擬した出口圧力を設定する、請求項1から7のいずれか1項に記載の血流解析システム。 The blood flow analysis system according to any one of claims 1 to 7, wherein the condition setting unit sets an outlet pressure simulating the adjustment of the blood flow by an autonomic nerve using a snake sight function.
  9.  前記条件設定部は、前記三次元モデルの入口境界における流量が既知であると判定した場合、入口境界条件として前記血流の入口流量を設定し、前記入口境界における流量が未知であると判定した場合、前記入口境界条件として前記血流の入口圧力を設定する、
     請求項1から8のいずれか一項に記載の血流解析システム。
    When determining that the flow rate at the inlet boundary of the three-dimensional model is known, the condition setting unit sets the inlet flow rate of the blood flow as the inlet boundary condition, and determines that the flow rate at the inlet boundary is unknown. The inlet pressure of the blood flow is set as the inlet boundary condition,
    The blood flow analysis system according to any one of claims 1 to 8.
  10.  血流解析対象の二次元断層画像を含む解析依頼を通信ネットワークを介して受信する解析依頼受信部と、
     前記解析依頼から解析対象者を特定する情報を削除し、前記解析対象者を識別する管理番号を付与する匿名化処理部と、
     前記二次元断層画像に基づいて血管形状の三次元モデルを生成するモデル生成部と、
     前記三次元モデルに基づく血流のシミュレーションに用いられる有限体積法の条件を設定する条件設定部と、
     前記三次元モデル、前記条件設定部が設定した前記条件、及び、前記管理番号を含むシミュレーション依頼を生成するシミュレーション依頼処理部と、
     前記シミュレーション依頼に基づいて、前記有限体積法を用いた流体解析手法によって行われた前記血流のシミュレーションの結果に基づく解析結果を生成する解析結果生成部と、
     前記解析結果を前記管理番号に基づいて依頼元へ送信する解析結果送信部と、
     を備える解析依頼受付システム。
    An analysis request receiving unit that receives an analysis request including a two-dimensional tomographic image to be analyzed for blood flow via a communication network;
    Anonymization processing unit that deletes information for identifying an analysis target person from the analysis request and gives a management number for identifying the analysis target person;
    A model generation unit that generates a three-dimensional model of a blood vessel shape based on the two-dimensional tomographic image;
    A condition setting unit for setting conditions of a finite volume method used for simulation of blood flow based on the three-dimensional model;
    A simulation request processing unit that generates a simulation request including the three-dimensional model, the condition set by the condition setting unit, and the management number;
    Based on the simulation request, an analysis result generation unit that generates an analysis result based on a result of the blood flow simulation performed by a fluid analysis method using the finite volume method;
    An analysis result transmitter for transmitting the analysis result to the requester based on the management number;
    An analysis request reception system comprising:
  11.  血流解析対象の二次元断層画像を含む解析依頼を通信ネットワークを介して受信する解析依頼受信ステップと、
     前記解析依頼から解析対象者を特定する情報を削除し、前記解析対象者を識別する管理番号を付与する連結可能匿名化ステップと、
     前記二次元断層画像に基づいて血管形状の三次元モデルを生成するモデル生成ステップと、
     前記三次元モデルに基づく血流のシミュレーションに用いられる有限体積法の条件を設定する条件設定ステップと、
     前記三次元モデル、前記条件設定ステップで設定した前記条件、及び、前記管理番号を含むシミュレーション依頼を生成するシミュレーション依頼処理ステップと、
     前記シミュレーション依頼に基づいて、前記有限体積法を用いた流体解析手法によって前記血流のシミュレーションを行う解析実行ステップと、
     前記解析実行ステップでのシミュレーション結果に基づく解析結果を生成する解析結果生成ステップと、
     前記解析結果を前記管理番号に基づいて依頼元へ送信する解析結果送信ステップと、
     を含む血流解析方法。
    An analysis request receiving step for receiving an analysis request including a two-dimensional tomographic image to be analyzed for blood flow via a communication network;
    A connectable anonymization step that deletes information for identifying the analysis target person from the analysis request and gives a management number for identifying the analysis target person;
    A model generation step of generating a three-dimensional model of a blood vessel shape based on the two-dimensional tomographic image;
    A condition setting step for setting conditions of a finite volume method used for simulation of blood flow based on the three-dimensional model;
    A simulation request processing step for generating a simulation request including the three-dimensional model, the condition set in the condition setting step, and the management number;
    Based on the simulation request, an analysis execution step of simulating the blood flow by a fluid analysis method using the finite volume method;
    An analysis result generation step for generating an analysis result based on a simulation result in the analysis execution step;
    An analysis result transmission step of transmitting the analysis result to a requester based on the management number;
    A blood flow analysis method including:
  12.  コンピュータに、
     血流解析対象の二次元断層画像を含む解析依頼を通信ネットワークを介して受信する解析依頼受信ステップと、
     前記解析依頼から解析対象者を特定する情報を削除し、前記解析対象者を識別する管理番号を付与する連結可能匿名化ステップと、
     前記二次元断層画像に基づいて血管形状の三次元モデルを生成するモデル生成ステップと、
     前記三次元モデルに基づく血流のシミュレーションに用いられる有限体積法の条件を設定する条件設定ステップと、
     前記三次元モデル、前記条件設定ステップで設定した前記条件、及び、前記管理番号を含むシミュレーション依頼を生成するシミュレーション依頼処理ステップと、
     前記シミュレーション依頼に基づいて、前記有限体積法を用いた流体解析手法によって行われた前記血流のシミュレーションの結果に基づく解析結果を生成する解析結果生成ステップと、
     前記解析結果を前記管理番号に基づいて依頼元へ送信する解析結果送信ステップと、
     を実行させるためのプログラム。
    On the computer,
    An analysis request receiving step for receiving an analysis request including a two-dimensional tomographic image to be analyzed for blood flow via a communication network;
    A connectable anonymization step that deletes information for identifying the analysis target person from the analysis request and gives a management number for identifying the analysis target person;
    A model generation step of generating a three-dimensional model of a blood vessel shape based on the two-dimensional tomographic image;
    A condition setting step for setting conditions of a finite volume method used for simulation of blood flow based on the three-dimensional model;
    A simulation request processing step for generating a simulation request including the three-dimensional model, the condition set in the condition setting step, and the management number;
    Based on the simulation request, an analysis result generating step for generating an analysis result based on a result of the blood flow simulation performed by a fluid analysis method using the finite volume method;
    An analysis result transmission step of transmitting the analysis result to a requester based on the management number;
    A program for running
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