Information processing device, program, and information processing method

Abstract

To support diagnostic relating to pulmonary valve regurgitation with a method that has low impact on a subject and is relatively simple, such as image analysis of a dynamic image.SOLUTION: An information processing device (dynamic image analysis device; analyzer 3) includes a control unit 31 for outputting a 'determination result relating to pulmonary valve regurgitation', as an output part, which is determined on the basis of dynamic image information on a 'dynamic image' acquired by kymography of imaging a 'dynamic image' of the chest of a subject without using a contrast agent by emitting a radiant ray.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present invention relates to an information processing device, a program, and an information processing method. [Background technology]

[0002] If blood flow to the lungs, heart, etc. is restricted for a long period of time due to pulmonary valve regurgitation (pulmonary valve regurgitation disease), it can cause serious life-threatening complications such as right heart failure. For this reason, if pulmonary regurgitation is present or suspected, it is advisable to periodically monitor the patient's progress and determine the timing of reoperation. Pulmonary regurgitation is one of the symptoms that occurs in patients with, for example, tetralogy of Fallot. Tetralogy of Fallot is a congenital heart disease designated as an intractable disease, and patients with the condition generally undergo cardiac surgery, but there is a high possibility that symptoms of pulmonary regurgitation will occur after surgery. Pulmonary regurgitation is also known to occur in secondary and idiopathic pulmonary hypertension.

[0003] The main methods used to observe and diagnose the presence and severity of pulmonary valve regurgitation include echocardiography, which uses ultrasound to produce images of the heart, blood vessels, etc., and MRI (Magnetic Resonance Imaging).

[0004] However, in ultrasound examinations, a simple diagnosis can be made by viewing color Doppler in addition to ultrasound images, but the technique of probe operation is required, and there are cases where clinical data suggests pulmonary regurgitation but the quality of the transthoracic echogram is poor, resulting in a discrepancy between clinical data and echo indices. In such cases, an MRI examination is ultimately required. MRI examinations can perform simple diagnoses (diagnosis of the presence or absence of reflux) as well as quantitative evaluations of the extent of reflux (detailed examinations such as calculating the reflux rate), but they have the limitation that they cannot be used if there is metal in the patient's body that is not compatible with MRI. Furthermore, MRI examinations take a relatively long time to scan, and patients must remain still in a small, noisy device during the scan, which can make it difficult to use for patients who suffer from claustrophobia or have mental retardation.

[0005] In this regard, for example, Patent Document 1 discloses a method for analyzing blood flows such as pulmonary blood flow and cardiac blood flow using dynamic chest X-ray images taken continuously. If it were possible to determine the presence or absence of pulmonary valve regurgitation by performing blood flow analysis using dynamic X-ray images, it would be possible to widely meet the diagnostic needs for pulmonary valve regurgitation using a simple method with less burden on patients. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] JP 2020-14562 A Summary of the Invention [Problem to be solved by the invention]

[0007] However, as described in Patent Document 1, although the blood flow analysis method using X-ray dynamic images has been used to diagnose pulmonary embolism, its use in diagnosing pulmonary valve regurgitation has not yet been considered.

[0008] The present invention has been made in consideration of the above points, and aims to provide an information processing device, a program, and an information processing method that can provide diagnostic support for pulmonary valve regurgitation by performing image analysis of dynamic images, which is a relatively simple technique that places little burden on the subject. [Means for solving the problem]

[0009] In order to solve the above problems, the information processing device of the present invention comprises: Radiation From one direction Dynamic image of subject's chest after irradiation Take a photo The dynamic image obtained by dynamic photography A first acquisition unit that acquires a second acquisition unit that analyzes the dynamic image acquired by the first acquisition unit and acquires information regarding pulmonary valve regurgitation; Information regarding pulmonary valve regurgitation acquired by the second acquisition unit. an output unit for outputting a determination result regarding pulmonary regurgitation determined based on the and, The present invention is characterized by comprising: Effect of the Invention

[0010] According to the present invention, diagnostic support for pulmonary valve regurgitation can be performed by performing image analysis of dynamic images, which is a relatively simple technique that places little burden on the subject. [Brief description of the drawings]

[0011] [Figure 1] FIG. 1 is a diagram illustrating an image capturing system including an analysis device according to an embodiment of the present invention. [Diagram 2] FIG. 13 is a diagram showing an example of a dynamic chest X-ray image, and is an image showing a case where target regions are set in the heart (ventricle) and lung fields, respectively. [Diagram 3] 13 is a flowchart showing an example of the flow of dynamic image analysis processing when information regarding pulmonary valve regurgitation is a blood flow waveform. [Figure 4] FIG. 2 is a diagram showing an example of a blood flow waveform at a site related to the pulmonary artery. [Diagram 5] FIG. 1 is a diagram showing an example of a blood flow waveform at a site related to the pulmonary artery in a healthy subject. [Figure 6] FIG. 1 is a diagram showing an example of a blood flow waveform at a site related to the pulmonary artery in a patient with pulmonary valve regurgitation. [Figure 7] 13 is a flowchart showing an example of the flow of dynamic image analysis processing when information regarding pulmonary valve regurgitation is skewness and kurtosis obtained based on a blood flow waveform. [Figure 8] FIG. 11 is an explanatory diagram for explaining skewness. [Figure 9] FIG. 11 is an explanatory diagram for explaining kurtosis. [Figure 10] 13 is a flowchart showing an example of the flow of dynamic image analysis processing when information regarding pulmonary valve regurgitation is a predicted regurgitation rate and a determination result based thereon. [Figure 11] FIG. 13 is a diagram showing an example of a graph showing a calculation result when a predicted reflux rate is calculated by multiple regression analysis. [Figure 12] FIG. 13 is an explanatory diagram for explaining the signal value ratio of the heart to the lung field, where (a) shows the case of a healthy subject, and (b) shows the case of a patient with pulmonary valve regurgitation. [Figure 13] 11 is a graph showing signal values ​​of a blood flow waveform in a target region set on the heart. [Figure 14] 13 is a graph showing signal values ​​of a blood flow waveform in a target region set in a lung field. [Figure 15] 13 is a flowchart showing an example of the flow of dynamic image analysis processing when information regarding pulmonary valve regurgitation is a heart-lung field signal value ratio. [Figure 16] 1 is a graph showing the relationship between the heart-lung field signal value ratio and the regurgitation rate of pulmonary valve regurgitation. [Figure 17] FIG. 17 is a box plot showing the distribution of the data in FIG. 16. [Figure 18] FIG. 2 is a diagram showing an example of a dynamic chest X-ray image, showing an image in which the entire heart and the entire lung field are the target regions. [Figure 19] 13 is a graph showing signal values ​​of a blood flow waveform when the entire heart is used as a target region. [Figure 20] 13 is a graph showing signal values ​​of a blood flow waveform when the entire lung field is the target region. [Figure 21] 13 is a graph showing the relationship between the heart-lung field signal value ratio and the regurgitation rate of pulmonary valve regurgitation when the entire heart and the entire lung field are used as target regions. [Figure 22] FIG. 22 is a box plot showing the distribution of the data in FIG. 21. [Diagram 23] 13 is a graph showing integrated signal values ​​of a blood flow waveform when the entire heart is treated as a target region. [Figure 24] 13 is a graph showing integrated signal values ​​of a blood flow waveform when the entire lung field is the target region. [Diagram 25] 13 is a graph showing the relationship between the heart-lung field signal value ratio and the regurgitation rate of pulmonary valve regurgitation when integrated signal values ​​are used for the entire heart and the entire lung field as target regions. [Figure 26] FIG. 26 is a box plot showing the distribution of data in FIG. 25. [Figure 27] 13 is a flowchart showing an example of the flow of dynamic image analysis processing when information regarding pulmonary valve regurgitation is the result of determining the presence or absence of pulmonary valve regurgitation using skewness and kurtosis. [Figure 28] FIG. 13 is an explanatory diagram showing an example in which thresholds are set using skewness and kurtosis as parameters to classify patients with respect to pulmonary valve regurgitation. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] Hereinafter, an embodiment of an information processing device (analysis device), a program, and an information processing method according to the present invention will be described with reference to the drawings. However, although the embodiments described below are subject to various limitations that are technically preferable for implementing the present invention, the technical scope of the present invention is not limited to the following embodiments and illustrated examples.

[0013] [Positioning of dynamic image analyzers] The information processing device of this embodiment (dynamic image analysis device, hereinafter referred to as the "analysis device") acquires X-ray dynamic images (hereinafter simply referred to as the "dynamic images") from an image capturing system (an imaging device installed within the image capturing system), analyzes the acquired dynamic images, and displays the analysis results to assist doctors and others in making diagnoses. First, as a premise, the relationship between an image capturing system and an analysis device assumed in this embodiment will be described with reference to FIG.

[0014] FIG. 1 shows the overall configuration of an image capturing system 100 according to this embodiment. 1, the image capturing system 100 includes an image capturing device 1 and an image capturing console 2 that is connected to the image capturing device 1 by a communication cable or the like and controls the image capturing device 1. The image capturing device 1 is capable of capturing dynamic images as described below. The imaging device 1 is connected via an imaging console 2 to a communication network NT such as a LAN (Local Area Network). Moreover, the analysis device 3 in this embodiment is connected to the image capturing system 100 via the communication network NT, and dynamic images acquired by the image capturing device 1 are sent to the analysis device 3 via the image capturing console 2.

[0015] In this embodiment, the analysis device (information processing device) 3 is, for example, a diagnostic console as shown in Fig. 1. The analysis device (information processing device) 3 in this embodiment generates and outputs "information on pulmonary valve regurgitation" as an analysis result based on dynamic images, and may be a diagnostic console or may be provided as a device separate from the diagnostic console. Each device constituting the image capturing system 100 complies with the Digital Image and Communications in Education (DICOM) standard, and communication between the devices is performed in accordance with the DICOM standard.

[0016] [Configuration of imaging equipment] The imaging device 1 is an imaging means capable of imaging dynamics such as changes in the shape of lung expansion and contraction accompanying respiratory movement, and heartbeat. In "dynamic imaging", a subject M is repeatedly irradiated with pulsed radiation such as X-rays at a predetermined time interval (pulse irradiation), or is continuously irradiated with a low dose without interruption (continuous irradiation) to obtain multiple images showing the dynamics of the subject M. A series of images obtained by "dynamic imaging" is called a "dynamic image". Each of the multiple images constituting a "dynamic image" is called a frame image. Here, the chest of a subject (patient, etc.) is used as the subject M. The imaging may be performed in an upright position (subject (patient, etc.) standing) or in a supine position (subject (patient, etc.) lying down).

[0017] In this embodiment, "dynamic photography" includes video photography. The photography device 1 can also take still images, but taking still images while displaying a video is not included in "dynamic photography." Furthermore, "dynamic images" include videos, but do not include images obtained by taking still images while displaying a video. "Dynamic radiography" involves low-exposure imaging, which places less strain on the subject (patient, etc.), and has the advantage that it can be suitably used for simple examinations.

[0018] The radiation source 11 is disposed at a position facing the radiation detection unit 13 with the subject M in between, and irradiates the subject M with radiation (X-rays) under the control of the radiation irradiation control device 12. The radiation irradiation control device 12 is connected to the imaging console 2, and controls the radiation source 11 based on the radiation irradiation conditions input from the imaging console 2 to perform radiation imaging. The radiation irradiation conditions input from the imaging console 2 include, for example, a pulse rate, a pulse width, a pulse interval, the number of imaging frames per imaging, the value of the X-ray tube current, the value of the X-ray tube voltage, and the type of additional filter. The pulse rate is the number of radiation irradiations per second, and coincides with the frame rate, which will be described later. The pulse width is the radiation irradiation time per radiation irradiation. The pulse interval is the time from the start of one radiation irradiation to the start of the next radiation irradiation, and coincides with the frame interval, which will be described later.

[0019] The radiation detection unit 13 is composed of a semiconductor image sensor such as a flat panel detector (FPD). The FPD has a glass substrate or the like, and a plurality of detection elements (pixels) are arranged in a matrix at predetermined positions on the substrate. The detection elements detect radiation irradiated from the radiation source 11 and transmitted through at least the subject M according to its intensity, and convert the detected radiation into an electrical signal and accumulate the signal. Each pixel is equipped with a switching unit such as a thin film transistor (TFT). There are two types of FPD: an indirect conversion type in which X-rays are converted into an electrical signal by a photoelectric conversion element via a scintillator, and a direct conversion type in which X-rays are directly converted into an electrical signal, and either type may be used.

[0020] The reading control device 14 is connected to the imaging console 2. The reading control device 14 controls the switching unit of each pixel of the radiation detection unit 13 based on the image reading conditions input from the imaging console 2, switches the reading of the electric signal accumulated in each pixel, and acquires image data by reading the electric signal accumulated in the radiation detection unit 13. This image data is each frame image of a dynamic image or a still image. If a structure exists between the radiation source 11 and the radiation detection unit 13, the amount of radiation reaching the radiation detection unit 13 is reduced by the structure, so that the signal value (pixel value, concentration value) of each pixel of the image data changes according to the structure of the subject M. The reading control device 14 outputs the acquired dynamic image or still image to the imaging console 2. The image reading conditions are, for example, a frame rate, a frame interval, a pixel size, an image size (matrix size), etc. The frame rate is the number of frames acquired per second, and is equal to the pulse rate. The frame interval is the time from the start of acquisition of one frame image to the start of acquisition of the next frame image, and is equal to the pulse interval. The radiation irradiation control device 12 and the reading control device 14 are connected to each other and exchange synchronous signals with each other to synchronize the radiation irradiation operation and the image reading operation.

[0021] [Configuration of the shooting console] The imaging console 2 outputs radiation irradiation conditions and image reading conditions to the imaging device 1 to control the operations of the imaging device 1 for radiography and reading of radiographic images. As shown in FIG. 1, the radiography console 2 is configured to include a control unit 21, a storage unit 22, an operation unit 23, a display unit 24, and a communication unit 25, and each unit is connected by a bus .

[0022] The control unit 21 is composed of a CPU (Central Processing Unit), a RAM (Random Access Memory), etc. The CPU of the control unit 21 reads out the system program and various processing programs stored in the storage unit 22 in response to an operation of the operation unit 23, expands them in the RAM, executes various processes according to the expanded programs, and centrally controls the operation of each part of the radiography console 2 and the radiation irradiation operation and reading operation of the radiography device 1.

[0023] The storage unit 22 is composed of a non-volatile semiconductor memory, a hard disk, etc. The storage unit 22 stores various programs executed by the control unit 21, parameters required for executing processes by the programs, data such as processing results, etc. For example, the storage unit 22 stores radiation irradiation conditions and image reading conditions in association with subject regions. The various programs are stored in the form of readable program codes, and the control unit 21 sequentially executes operations in accordance with the program codes.

[0024] The operation unit 23 is configured with a keyboard having cursor keys, letter / number input keys, various function keys, etc., and a pointing device such as a mouse, and outputs instruction signals input by key operations on the keyboard or mouse operations to the control unit 21. The operation unit 23 may also have a touch panel on the display screen of the display unit 24, and in this case, outputs instruction signals input via the touch panel to the control unit 21.

[0025] The display unit 24 is configured with a monitor such as an LCD (Liquid Crystal Display), and displays input instructions and data from the operation unit 23 according to instructions of a display signal input from the control unit 21.

[0026] The communication unit 25 includes a LAN adapter, a modem, a TA (Terminal Adapter), etc., and controls data transmission and reception between each device connected to the communication network NT.

[0027] [Analysis equipment configuration] The analysis device 3 is an information processing device that acquires dynamic images (X-ray dynamic images) taken by the imaging device 1, generates "information regarding pulmonary valve regurgitation" based on dynamic image information of "areas related to the pulmonary artery" in the dynamic images, and outputs the generated results to a display unit 34 (described below) of the analysis device 3 or an external display device (not shown), and is used as a diagnostic support device that assists doctors in making diagnoses. The analysis device 3 is, for example, a computer device such as a PC (Personal Computer) or a workstation.

[0028] As shown in FIG. 1, the analysis device 3 comprises a control unit 31, a storage unit 32, an operation unit 33, a display unit , and a communication unit , and each unit is connected by a bus . 1 illustrates an example in which the analysis device 3, which is a diagnostic console, and the imaging console 2 are separate devices, but the system configuration is not limited to this. For example, the analysis device 3, which is a diagnostic console, may be configured as a dual-purpose device that also functions as the imaging console 2, and this analysis device 3 and the imaging device 1 may be connected by a communication network NT. Also, a diagnostic console may be provided separately from the analysis device 3.

[0029] The control unit 31 is composed of a CPU, a RAM, etc. The CPU of the control unit 31 reads out the system program and various processing programs stored in the storage unit 32 in response to the operation of the operation unit 33, expands them in the RAM, executes various processes according to the expanded programs, and centrally controls the operations of each unit of the analysis device 3.

[0030] The storage unit 32 is composed of a non-volatile semiconductor memory, a hard disk, etc. The storage unit 32 stores various programs executed by the control unit 31, parameters required for executing processes by the programs, data such as processing results, etc. The various programs are stored in the form of readable program codes, and the control unit 31 sequentially executes operations in accordance with the program codes.

[0031] The operation unit 33 is configured with a keyboard having cursor keys, letter / number input keys, various function keys, etc., and a pointing device such as a mouse, and outputs instruction signals input by key operations on the keyboard or mouse operations to the control unit 31. The operation unit 33 may also have a touch panel on the display screen of the display unit 34, and in this case, outputs instruction signals input via the touch panel to the control unit 31.

[0032] The display unit 34 is configured with a monitor such as an LCD, and performs various displays according to instructions of a display signal input from the control unit 31.

[0033] The communication unit 35 includes a LAN adapter, a modem, a TA, etc., and controls data transmission and reception between each device connected to the communication network NT.

[0034] In this embodiment, the control unit 31 acquires, for example, dynamic images of the chest obtained by the imaging device 1 performing dynamic radiography on the chest of the subject via the communication unit 35. That is, the control unit 31 functions as an acquisition unit.

[0035] Furthermore, the control unit 31 generates "information on pulmonary valve regurgitation" based on dynamic image information of a "site related to the pulmonary artery" (also simply referred to as a "site") in the dynamic image. That is, the control unit 31 functions as a generating unit.

[0036] Here, the function of the control unit 31 as a generating unit will be described in detail. First, the "area related to the pulmonary artery," which is the area that the control unit 31 focuses on to generate "information regarding pulmonary valve regurgitation," is a "area" where the blood flow condition of the pulmonary artery (presence or absence of regurgitation, etc.) can be observed. Figure 2 is an image of a dynamic chest X-ray (dynamic radiography). The area enclosed by a dashed line in the figure indicates the heart, and the dark areas on the left and right indicate the left and right lung fields. The pulmonary artery is the artery that sends blood from the heart to the lungs; it begins at the pulmonary valve in the right ventricle, passes through the relatively thick and short pulmonary artery trunk as shown by the dashed line in the figure, and then branches into two pulmonary arteries (left pulmonary artery and right pulmonary artery) corresponding to the left and right lungs. The area around the pulmonary artery trunk before it branches into the right pulmonary artery and left pulmonary artery is generally called the pulmonary artery origin.

[0037] Conventionally, magnetic resonance imaging (MRI) has been used to diagnose the state of blood flow in the pulmonary artery (presence or absence of reflux, etc.), but in MRI, the origin of the pulmonary artery is primarily used as the region of interest (ROI). It is desirable that the "part related to the pulmonary artery" in the dynamic image is also a part close to the origin of the pulmonary artery, but many structures are gathered around the pulmonary artery trunk, and it is difficult to obtain a signal only from the origin of the pulmonary artery even if a radiation (X-ray) image is taken. Therefore, in this embodiment, for example, a part inside at least the left or right lung field region and including the proximal part of the left and right pulmonary arteries is set as the "part related to the pulmonary artery" as the region of interest (ROI). More preferably, the target regions set inside the left and right lung field regions and proximal parts of the left and right pulmonary arteries, shown as "β" and "γ" in FIG. 2, are set as the "part related to the pulmonary artery".

[0038] By setting "areas related to the pulmonary artery" (target areas "β" and "γ" in the figure) in the left and right lung field regions respectively and diagnosing the blood flow status of the pulmonary artery (presence or absence of regurgitation, etc.), pulmonary valve regurgitation will not be overlooked, even in cases where there is only a small amount of regurgitation from one of the left and right lungs but a large amount of regurgitation from the other lung. When setting "areas related to the pulmonary artery" in the left and right lung field regions respectively, it is preferable that the "information regarding pulmonary valve regurgitation" is the average value of the values ​​in both the left and right target areas (target areas "β" and "γ" in Figure 2). By considering the values ​​in both the left and right target areas, it is possible to obtain highly accurate results similar to those obtained with MRI, which performs examinations using the area around the pulmonary artery trunk (the so-called origin of the pulmonary artery) as the target area.

[0039] In this embodiment, as described later, a region of interest (ROI) for extracting information is also set in the heart (denoted as "α" in FIG. 2). Waveforms differ between the atria and ventricles of the heart, and in this embodiment, the region of interest (ROI, "α" in FIG. 2) for the heart is placed in the ventricle (the area where the left ventricle and right ventricle are thought to overlap). The target regions (target regions "α", "β", and "γ" shown in Figure 2) are all regions with a diameter of, for example, about 10 mm, and may be set automatically as described below, or may be set manually by a user such as a doctor while looking at a screen, etc. The target region (the region set in the "pulmonary artery-related region" or the heart) is not limited to a region with a diameter of about 10 mm. As described later, the entire lung field or the entire heart may be the target region.

[0040] Moreover, the dynamic image information of the "part related to the pulmonary artery" in the dynamic image is, for example, the signal value (pixel value, etc.) of each pixel extracted from the dynamic image. That is, the dynamic image information includes information on the color shade (density) and brightness (luminance) of each pixel in the "part related to the pulmonary artery" in the dynamic image. In this case, the "pixel" from which the signal value is extracted may be a pixel on hardware, or may be a pixel after various image processing (for example, binning processing, etc.) is performed by software. In this embodiment, the control unit 31 as a generating unit generates "information related to pulmonary valve regurgitation" based on information obtained from signal values ​​of pixels in the "site related to the pulmonary artery." Note that the control unit 31 as a generating unit may generate the "information related to pulmonary valve regurgitation" based on an average value of signal values ​​of pixels in the "site related to the pulmonary artery."

[0041] The "information regarding pulmonary valve regurgitation" generated by the control unit 31 as a generating unit is, for example, information regarding whether or not the subject (patient, etc.) from whom the dynamic image was taken has pulmonary valve regurgitation (presence or absence of pulmonary valve regurgitation, or possibility of regurgitation). For example, when the value of the dynamic image information is equal to or greater than a predetermined reference value, the control unit 31 generates "information regarding pulmonary valve regurgitation" indicating "present" regurgitation, and when the value is less than the reference value, indicating "absent" regurgitation. The predetermined reference value is set as appropriate. Note that "information regarding pulmonary valve regurgitation" is not limited to information regarding the presence or absence of pulmonary valve regurgitation, and may be, for example, information regarding the severity of pulmonary valve regurgitation when pulmonary valve regurgitation is present. Information regarding the severity (degree or level of regurgitation) of pulmonary valve regurgitation may be numerically or quantified information, such as a regurgitation rate or a predicted regurgitation rate value indicating the amount of blood that flows back into the heart out of the blood pumped from the heart to the lungs.

[0042] Furthermore, the "information on pulmonary valve regurgitation" generated by the control unit 31 as a generating unit may be information on the shape of the blood flow waveform in the "part related to the pulmonary artery." The blood flow waveform is a signal waveform synchronized with the heart rate. Furthermore, the "information on pulmonary valve regurgitation" may be information that visualizes the blood flow in the "part related to the pulmonary artery." That is, it may be, for example, a color map or the like that visually indicates the blood flow (regurgitation amount) in a region of interest (ROI) of the lung field. By displaying information that visualizes the blood flow, users such as doctors can easily understand the patient's condition (presence or absence of regurgitation, severity, etc.).

[0043] Furthermore, the control unit 31 as a generating unit may perform a more detailed analysis based on the blood flow waveform in the "part related to the pulmonary artery" and generate the analysis result as "information related to pulmonary valve regurgitation." Furthermore, the control unit 31 as a generating unit may generate "information on pulmonary valve regurgitation" based on various indices (other than blood flow waveforms) obtained in the "site related to the pulmonary artery." Examples of various indices other than blood flow waveforms include, but are not limited to, blood flow velocity, blood flow rate (≒ amplitude), and the ratio of signal values ​​of the heart and lung field (amplitude ratio). The "information regarding pulmonary valve regurgitation" generated by the control unit 31 as a generating unit will be described in detail later.

[0044] Furthermore, the control unit 31 outputs the "information regarding pulmonary valve regurgitation" (diagnosis assistance information) generated by the generation unit to various output destinations. That is, the control unit 31 in this embodiment functions as an output unit that outputs the "information regarding pulmonary valve regurgitation." There is no particular limitation on the destination to which the control unit 31 as an output unit outputs various pieces of information. For example, it may be the display unit 34 of the analysis device 3, or various external display devices or printers (not shown). "Output" also includes output to an external device as print data or image data. "Output" may be performed via various networks, or by wired or wireless communication. It may also be performed via various connectors or ports of various media.

[0045] [Image capture system operation] Next, the operation of the image capturing system 100 will be described.

[0046] (Operation of imaging device and imaging console) First, the imaging operation performed by the imaging device 1 and the imaging console 2 will be described. The control unit 21 of the radiographing console 2 sets radiation irradiation conditions in the radiation irradiation control device 12 and sets image reading conditions in the reading control device 14 .

[0047] Next, the control unit 21 outputs an instruction to start capturing dynamic images to the radiation irradiation control device 12 and the reading control device 14, and controls the capturing of dynamic images. Specifically, the radiation source 11 irradiates radiation at a pulse interval set in the radiation irradiation control device 12, and the reading control device 14 outputs image data (frame images) acquired from the radiation detection unit 13 to the imaging console 2. When the capturing of a predetermined number of frames is completed, the control unit 21 outputs an instruction to end the capturing to the radiation irradiation control device 12 and the reading control device 14, and stops the capturing operation. The control unit 21 stores each frame image acquired by capturing in the memory unit 22 in association with a number (frame number) indicating the capturing order.

[0048] Next, the control unit 21 causes the dynamic images to be displayed on the display unit 24. When the person performing the imaging checks that the images are suitable for diagnosis and inputs a confirmation instruction from the operation unit 23, the control unit 21 attaches patient information (patient ID of the subject, patient name, etc.) and examination information, etc. to each of the series of frame images acquired by the dynamic imaging, and transmits them via the communication unit 25 to the analysis device 3, which is a diagnostic console, etc.

[0049] (Operation of the analysis device) Next, the operation of the analysis device 3 will be described. 3 is a flowchart showing an example of dynamic image analysis processing (information processing) executed in the analysis device 3. The dynamic image analysis processing (information processing) is processing for assisting a doctor in diagnosing pulmonary valve regurgitation by using dynamic images, and is executed by the control unit 31 in cooperation with a program stored in the storage unit 32. The example shown in FIG. 3 illustrates processing when the "information regarding pulmonary valve regurgitation" is information regarding the blood flow waveform of the pulmonary artery (information regarding the shape of the blood flow waveform).

[0050] First, when dynamic radiography is performed on the chest of a subject in the radiography device 1, the control unit 31 acquires the dynamic image generated by the radiography device 1 from the radiography console 2 via the communication unit 35 (step S1). The dynamic image is composed of a plurality of frame images. The control unit 31 stores the acquired dynamic image in the storage unit 32. For example, Fig. 2 shows an example of a dynamic image of the chest taken while holding one's breath.

[0051] Next, the control unit 31 sets target regions ("β" and "γ" surrounded by circles in Figure 2) within the left and right lung field regions and proximal to the left and right pulmonary arteries as "areas related to the pulmonary arteries" (step S2). This target region is an area with a lot of blood flow and appears whitish in the image. For this reason, the control unit 31 automatically sets the target region ("β" and "γ") to, for example, an area in the lung field in the dynamic image where many pixels with high brightness values ​​are concentrated. As described above, the target regions ("β", "γ") are not limited to being set automatically, but may be set manually by a user, such as a doctor. In this case, it is preferable to provide setting assistance by, for example, displaying an image on the display unit 34 or the like that clearly shows the contrast between the areas that appear white due to blood flow and the other areas to guide the setting position of the target region. Furthermore, if the position of the target region set by the user is significantly deviated from the position that should be set, the user may be asked to correct the setting position by issuing an error message or alert, for example. In this case, a marker or the like may be displayed at the desired setting position to show the user the position to be set as the target region.

[0052] When extracting pixel signal values ​​from a "part related to the pulmonary artery," various types of noise are included in the signal values, making it difficult to obtain only the necessary information. Therefore, in this embodiment, a target region ("α" surrounded by a circle in Fig. 2) is also set on the heart, and the frequency of brightness changes caused by cardiac pulsation is measured from the signal values ​​of pixels within the target region ("α") to obtain the frequency of the heart rate. The control unit 31 then generates a band-pass filter corresponding to the frequency of the heart rate, and applies this to values ​​detected from the target regions ("β" and "γ" in Fig. 2) set as "areas related to the pulmonary artery", thereby obtaining values ​​in which noise other than that of the required signal has been reduced.

[0053] FIG. 4 shows an example of a blood flow waveform detected from target regions ("β" and "γ" in FIG. 2) set inside the left and right lung field regions and proximal to the left and right pulmonary arteries as "parts related to the pulmonary arteries." Note that FIG. 4 shows a waveform after applying a bandpass filter based on information obtained from a target region ("α" in FIG. 2) set in the heart. Also, the minimum value of the amplitude of the blood flow waveform (approximately "-10") is set as the start of the wavelength. Generally, the heart beats about once per second, and dynamic imaging takes about 5 to 15 seconds. Therefore, a series of dynamic imaging captures the blood flow waveform in the pulmonary artery for about 5 to 10 cycles of the heart's beat (heartbeat) (Figure 4 shows an example of blood flow waveform for 5 cycles).

[0054] The shape of the blood flow waveform is viewed as the blood flow waveform of the pulmonary artery for one heartbeat. For this reason, the control unit 31 extracts the blood flow waveform of the pulmonary artery for one heartbeat from the blood flow waveforms detected from the target regions ("β", "γ") (or the average value of the data obtained from the target regions "β", "γ") (step S3, see FIG. 5). Note that the blood flow waveform of the pulmonary artery for one heartbeat referred to here may be the average value of multiple waveforms as shown in FIG. 4 (blood flow waveforms for five heartbeats in FIG. 4). When extracting the pulmonary artery blood flow waveform for one heartbeat, the control unit 31 may normalize the signal values ​​constituting the blood flow waveform so that they fall within a certain range (for example, the maximum value minus the minimum value is a value of 0 to 100). Figures 5 and 6 show graphs in which the signal values ​​are normalized.

[0055] In a normal state without pulmonary regurgitation, for example, when it is necessary to send "100" of blood from the heart to the lungs, "100" of blood is sent out from the heart, flows into the lungs all at once, and then gradually flows out. For this reason, the peak occurs at an early stage in time, and the peak is closer to the left of the center when viewed on a graph. When there is no regurgitation, the gradient of the blood flow decrease is also gentle, and when viewed on a graph, the blood flow waveform falls gently (for example, Figure 5 shows an example of a blood flow waveform for a person (patient) with a regurgitation rate of 0). In contrast, for example, in the case of a person with 20% pulmonary regurgitation, when it is necessary to send "100" of blood from the heart to the lungs, "120" of blood, which includes the amount that flows back to the heart, is sent out from the heart and flows into the lungs. In this case, the amount of blood flowing in is large, so it takes longer to reach the peak, and when viewed on a graph, the peak is closer to the center than in Figure 5. After that, due to the influence of the refluxed blood outflow, the gradient of the blood flow waveform after the peak is steep, and when viewed on a graph, the blood flow waveform drops off sharply (for example, Figure 6 shows an example of a blood flow waveform for a person (patient) with a reflux rate of 54.5).

[0056] When the control unit 31 as a generating unit extracts the shape of the blood flow waveform of the pulmonary artery, the control unit 31 as an output unit outputs the blood flow waveform to the display unit 34 or the like (step S4). As a result, a blood flow waveform such as that shown in Fig. 5 or Fig. 6 is displayed on the display unit 34, and a doctor or the like as a user can confirm the shape of the waveform on the display screen. The user can determine (diagnose) that the person (patient) does not have symptoms of pulmonary valve regurgitation (or is highly likely to not have pulmonary valve regurgitation) if the blood flow waveform displayed on display unit 34 is close to the shape shown in Figure 5. Also, the user can determine (diagnose) that the person (patient) has symptoms of pulmonary valve regurgitation (or is highly likely to have pulmonary valve regurgitation) if the blood flow waveform displayed on display unit 34 is close to the shape shown in Figure 6. If the shape of the blood flow waveform indicates that there is a symptom of pulmonary valve regurgitation or that there is a high possibility of such a symptom, the user (doctor) may instruct the patient to undergo further detailed examination, such as an MRI scan.

[0057] Next, the example shown in FIG. 7 illustrates processing when the "information about pulmonary valve regurgitation" is a parameter related to the shape of the blood flow waveform in the pulmonary artery. Here, the "parameters relating to the shape of the pulmonary artery blood flow waveform" include, for example, "skewness" and "kurtosis". In this case, after extracting the pulmonary artery blood flow waveform for one heartbeat based on the information obtained from the target region ("β" and "γ" in Fig. 2), the control unit 31 normalizes the signal values ​​constituting the blood flow waveform so that they are within a certain range of values ​​(for example, maximum value-minimum value 0-100) (step S24). Note that steps 21 to S23 in Fig. 7 are the same as steps S1 to S3 in Fig. 3, and therefore their explanation will be omitted. Furthermore, the control unit 31 as a generating unit calculates "skewness" and "kurtosis" as parameters related to the shape of the blood flow waveform (steps S25 and S26). The calculations of "skewness" and "kurtosis" may be performed in parallel as shown in Fig. 7, or may be performed sequentially, such as first calculating one and then calculating the other.

[0058] "Skewness" can be calculated by the following formula 1. In Equation 1, "n" indicates the sample amount, "xi" indicates the sample data, the X bar indicates the average value, and "s" indicates the standard deviation.

number

[0059] Figure 8 shows the calculated "skewness." "Skewness" is the degree of deviation of the peak when the blood flow waveform (change in the signal value of blood flow) is viewed over time. As shown in FIG. 8, when there is no "skewness" ("skewness = 0" in FIG. 8), the blood flow peak is located almost in the center of the blood flow waveform, which is close to the graph shape in FIG. 6. Also, on the right side of FIG. 8 ("skewness = 1.24"), the blood flow peak is shifted to the left of the center of the blood flow waveform and drops gradually after reaching the peak, which is close to the graph trend in FIG. 5. Furthermore, on the left side of FIG. 8 ("skewness = -1.24"), in contrast to the right side of FIG. 8, the blood flow peak is shifted to the right of the center of the blood flow waveform and drops sharply after reaching the peak. As shown in Figures 6 and 8, the closer the "skewness" is to 0, the higher the degree of pulmonary artery regurgitation rate tends to be. In addition, the lower the pulmonary artery regurgitation rate, the higher the "skewness" tends to be in the positive (+) direction. For this reason, by calculating the "skewness," the degree (level, severity) of the regurgitation rate can be quantified and shown to users such as doctors as a quantitative value, making it possible to provide quantitative information that is useful for diagnosing pulmonary valve regurgitation.

[0060] Moreover, “kurtosis” can be calculated using the following formula 2. In Equation 2, "n" indicates the sample amount, "xi" indicates the sample data, the X bar indicates the average value, and "s" indicates the standard deviation.

number

[0061] FIG. 9 shows the calculated "kurtosis." As shown in FIG. 9, the higher the "kurtosis" (the further to the right in FIG. 9, the higher the "kurtosis"), the steeper the change in signal value of the blood flow waveform. As shown in Figures 5 and 9, the higher the "kurtosis," the higher the degree of pulmonary regurgitation rate tends to be. Therefore, by calculating the "kurtosis," the degree (level, severity) of the regurgitation rate can be quantified and shown to users such as doctors as a quantitative value, providing quantitative information that is useful for diagnosing pulmonary valve regurgitation.

[0062] Furthermore, the control unit 31 as a generating unit may obtain the "amplitude" of the blood flow waveform (see FIG. 4) as the "parameter related to the shape of the pulmonary artery blood flow waveform." The "amplitude" of the blood flow waveform tends to be larger, that is, the height of the amplitude tends to be higher, in people with a higher regurgitation rate. For this reason, it is possible to determine the presence or absence, possibility, degree, etc. of pulmonary valve regurgitation by looking at the "amplitude" of the blood flow waveform. As mentioned above, if the signal value of the blood flow waveform is normalized to have a certain range of values ​​(for example, 0-100), it becomes impossible to differentiate the "amplitude" values. Therefore, when determining the "amplitude" of the signal value of the blood flow waveform, the "amplitude" is extracted without normalization.

[0063] In this manner, in this embodiment, the control unit 31 as a generating unit is exemplified as being able to acquire the "skewness," "kurtosis," and "amplitude" of the blood flow waveform as the "parameters relating to the shape of the blood flow waveform of the pulmonary artery." The control unit 31 may acquire all of these, or may acquire only a part of these. Also, various indices other than these three parameters may be acquired.

[0064] Furthermore, when the control unit 31 as a generating unit obtains "parameters related to the shape of the blood flow waveform of the pulmonary artery" (i.e., for example, the "skewness," "kurtosis," and "amplitude" of the blood flow waveform) as information obtained from the signal values ​​of pixels in the "area related to the pulmonary artery," it may further use these parameters to perform a detailed analysis and generate "information related to pulmonary valve regurgitation." For example, multiple regression analysis may be performed using three parameters, "skewness," "kurtosis," and "amplitude." In this case, for example, a threshold value may be set in advance, and a determination as to whether or not pulmonary valve regurgitation is present may be made based on whether or not the threshold value is exceeded, and the determination result may be used as "information regarding pulmonary valve regurgitation." If pulmonary valve regurgitation is minor, such as a few percent, it does not immediately pose a health problem, and may occur in healthy individuals. For this reason, only when there is a pathological level of regurgitation rate, it should be determined that there is pulmonary valve regurgitation. The threshold value for determining whether or not there is pulmonary valve regurgitation is, for example, a regurgitation rate of 25%. Whether or not there is pulmonary valve regurgitation when the regurgitation rate is exactly 25% may be set appropriately.

[0065] For example, by performing multiple regression analysis using three parameters (variables), "skewness", "kurtosis", and "amplitude", the regurgitation rate can be predicted from these parameters. In this case, for example, as shown in FIG. 10, the control unit 31, which is a generating unit, acquires a blood flow waveform in a target region (for example, "β" and "γ" in FIG. 2) that is a "site related to the pulmonary artery" (step S31), and extracts three parameters, "skewness", "kurtosis", and "amplitude", from the blood flow waveform (step S32). Then, using these parameters (variables), multiple regression analysis is performed (step S33) to predict the pulmonary artery regurgitation rate (step S34). Then, the control unit 31 determines whether the derived predicted regurgitation rate exceeds a predetermined regurgitation rate threshold (step S35), and if it exceeds the regurgitation rate threshold (step S35; YES), it determines that there is pulmonary valve regurgitation (step S36). On the other hand, if the regurgitation rate is equal to or less than the threshold (step S35; NO), it determines that there is no pulmonary valve regurgitation (step S37). That is, for example, if the regurgitation rate threshold is 25% as described above, then if the predicted regurgitation rate is less than 25%, such as 0% or 10%, then the person (patient) is determined not to have pulmonary regurgitation (at a pathological level). On the other hand, if the predicted regurgitation rate is greater than 25%, such as 30%, then the person (patient) is determined to have pulmonary regurgitation.

[0066] When the judgment result regarding the predicted regurgitation rate and the corresponding pulmonary valve regurgitation is obtained, the control unit 31 outputs the judgment result and the derived regurgitation rate (predicted regurgitation rate) to the display unit 34 or the like as an output unit (step S38) and displays them. Doctors and other users can look at the output results and, if it is determined that the patient has pulmonary valve regurgitation or the predicted regurgitation rate is high, take action such as ordering an MRI scan to confirm the situation in more detail. Even if the predicted regurgitation rate does not exceed the regurgitation rate threshold, if a value close to the threshold is obtained, an MRI examination or the like may be instructed to be performed as a precaution. Pulmonary valve regurgitation is likely to appear after surgery in patients with tetralogy of Fallot, and it is possible that predicted regurgitation rates and the like are derived periodically during follow-up observations after surgery. In such cases, if there is a change in the derived value, even if it does not exceed the threshold, a further detailed examination such as an MRI examination may be instructed.

[0067] FIG. 11 is an example of a graph showing the results of a multiple regression analysis using three variables. When the analysis results are plotted, a straight line (regression line) is drawn that best fits each piece of data, and this is expressed as a linear function to become the regression equation. "r" is an index that shows the extent to which the regression equation obtained as a result of regression analysis can explain the fluctuations in the value of the predicted reflux rate, which is the objective variable, and the closer "r" is to "1," the more accurate the prediction can be. Figure 11 shows the example of "r = 0.754," which shows that the reflux rate can be predicted with considerable accuracy. The parameters used to predict the reflux rate using multiple regression analysis are not limited to the three parameters "skewness," "kurtosis," and "amplitude." Any part of these parameters may be used, or other parameters may be included.

[0068] Also, as mentioned above, in the case of a person with pulmonary regurgitation, instead of sending "100" of blood from the heart to the lungs, there is a tendency for the amount of blood that flows back to be added and sent to be "120" or "150". For this reason, when viewed in dynamic images, for example, it is expected that there will be a difference between a healthy person without regurgitation and a patient with pulmonary regurgitation in the ratio of the "amplitude" of the signal value of the pixel that changes in the heart during beating to the "amplitude" of the signal value of the pixel that changes in the lung field.

[0069] FIG. 12(a) is an image showing blood flow in the lung field of a healthy subject, and FIG. 12(b) is an image showing blood flow in the lung field of a patient with pulmonary regurgitation. FIG. 13 shows the change in signal value of a target region (ROI, “α” in FIG. 2) set in the heart, and the “amplitude” of the signal value is “amplitude A”. FIG. 14 shows the change in signal value of a target region (ROI, “β” and “γ” in FIG. 2) set in the lung field, and the “amplitude” of the signal value is “amplitude B”. Note that “amplitude A” shown in FIG. 13 and “amplitude B” shown in FIG. 14 are both obtained by removing noise by applying a bandpass filter according to the frequency of the heart rate. The change in the "amplitude A" of the signal value in the heart is the left ventricular stroke volume LVSV+right ventricular stroke volume RVSV, and the change in the "amplitude B" of the signal value in the lung field is the right ventricular stroke volume RVSV.

[0070] As shown in Figure 12(a), in the case of a healthy person, LVSV = RVSV, and B / A = 1 / 2. However, as shown in Figure 12(b), in the case of a patient with reflux, a lot of blood is sent to the lungs as described above, so LVSV<RVSVとなり、B / A> The ratio becomes 1 / 2. Since such a relationship is observed between the "amplitude A" of the signal value in the heart and the "amplitude B" of the signal value in the lung field, the control unit 31 as a generating unit can obtain information indicating the degree of regurgitation rate (the severity of pulmonary valve regurgitation) ("information regarding pulmonary valve regurgitation") by calculating and comparing the ratio between the "amplitude A" of the signal value for one heartbeat of the heart and the "amplitude B" of the signal value corresponding to one heartbeat in the lung field.

[0071] When the control unit 31 as a generating unit generates "information regarding pulmonary valve regurgitation" from the ratio between "amplitude A" of the signal value in the heart and "amplitude B" of the signal value in the lung field, the control unit 31 performs processing such as that illustrated in FIG. 15. 15, the control unit 31 acquires pixel signal values ​​from a target region (ROI, "α" in FIG. 2) set in the heart (step S41), and also acquires pixel signal values ​​from target regions (ROI, "β" and "γ" in FIG. 2) set in the left and right lung fields (step S42).

[0072] Furthermore, the control unit 31 extracts five consecutive wavelengths whose waveform shape is not distorted from the signal values ​​of the blood flow waveform acquired from the target region "α" of the heart (step S43), and averages the amplitudes of each wavelength to obtain "amplitude A" (step S44). Similarly, for the lung field, the control unit 31 extracts five consecutive wavelengths whose waveform shape is not distorted from the signal values ​​of the blood flow waveform acquired from the target regions "β" and "γ" of the lung field (step S45), and averages the amplitudes of each wavelength to obtain "amplitude B" (step S44). Note that the order of step S41 (and steps S43 and S44) for the signal values ​​of the heart and step S42 (and steps S45 and S46) for the signal values ​​of the lung field does not matter.

[0073] Then, the signal value ratio of the heart to the lung field (amplitude B / amplitude A) is calculated (step S47). After the signal value ratio of the heart to the lung field (amplitude B / amplitude A) is calculated, the control unit outputs it to the display unit 34 or the like (step S48) to display it. This allows the system to provide users (such as doctors) with "information regarding pulmonary valve regurgitation," such as whether or not pulmonary valve regurgitation is present, and if so, how severe the symptoms are (severity of regurgitation), thereby assisting in diagnosis.

[0074] Furthermore, the relationship between the heart-lung field signal value ratio (amplitude B / amplitude A) and the pulmonary valve regurgitation rate has been shown to have a significant correspondence when compared with the regurgitation rate actually confirmed by MRI scans, etc. For example, Figure 16 is a graph showing the average signal value ratio between the heart and lung fields (amplitude B / amplitude A) on the horizontal axis and the pulmonary valve regurgitation rate (%) actually confirmed by MRI or other examinations on the vertical axis. As shown in Figure 16, it can be seen that people with a higher pulmonary valve regurgitation rate (%) (people with more severe regurgitation symptoms) tend to have a larger heart-lung field average signal value ratio (amplitude B / amplitude A).

[0075] FIG. 17 is a box plot showing the degree of variability in the data shown in FIG. The left side of Fig. 17 shows the group with reflux rates of 0% to 25%, which is the data group indicated by the black dots in Fig. 16 (the number of samples is n=24). The right side of Fig. 17 shows the group with reflux rates of 25% and over, which is the data group indicated by the white dots in Fig. 16 (the number of samples is n=11). In addition, the points (singular points) shown in the upper left of FIG. 17 and the two points in the upper right of FIG. 17 indicate data that deviates from the average spread range of each data group. There are various factors that cause data corresponding to singular points in the sample. For example, when the body movement is large during imaging, or when the shape of the lung field is unique and correct data cannot be obtained, it may be judged as noise, but there may be circumstances that should be considered. In this embodiment, such singular points are included in the average value, etc., and are shown as one of the sample data in FIG. 16 and FIG. 17. Note that how to handle the singular points is not limited to the example shown here. For example, if it is known that it is simply due to an error during imaging, it may be removed from the sample data shown in FIG. 16 and FIG. 17, or the average value, etc., may be obtained by excluding the singular points.

[0076] Up to this point, we have illustrated the case where the heart-lung field average signal value ratio (amplitude B / amplitude A) is calculated based on the signal values ​​of the blood flow waveform obtained from target region "α", which is an area of ​​approximately 10 mm in the heart, and target regions "β" and "γ", which are areas of approximately 10 mm in the lung field. However, the heart-lung field average signal value ratio (amplitude B / amplitude A) is not limited to being based on the signal values ​​of the blood flow waveform obtained from these target regions "α", "β", and "γ". For example, signal values ​​may be extracted from the entire heart and the entire lung field as target regions. Fig. 18 is an image diagram of a dynamic image in which the entire heart and the entire lung fields are the target regions. In Fig. 18, the heart region is shown surrounded by a thin dashed dotted line, and the left and right lung fields are shown surrounded by two-dot dashed lines.

[0077] In this case, the control unit 31 extracts five continuous wavelengths whose shapes are not distorted from the signal values ​​of multiple blood flow waveforms in the entire heart ("α2" in FIG. 18) which is the target region, and averages the amplitudes of each wavelength. Also, for the lung field, the control unit 31 extracts five continuous wavelengths whose shapes are not distorted from the signal values ​​of multiple blood flow waveforms in the entire lung field ("β2" and "γ2" in FIG. 18) which is the target region, and averages the amplitudes of each wavelength. Fig. 19 shows the change in signal value when the entire heart is the target region (ROI, "α2" in Fig. 18), and the "amplitude" of the average signal value is taken as "amplitude A". Fig. 20 shows the change in signal value when the entire lung field is the target region (ROI, "β2" and "γ2" in Fig. 18), and the "amplitude" of the average signal value is taken as "amplitude B". Note that "amplitude A" shown in Fig. 19 and "amplitude B" shown in Fig. 20 are both obtained by removing noise by applying a bandpass filter according to the frequency of the heart's heart rate.

[0078] FIG. 21 shows a graph of the average signal value ratio (amplitude B / amplitude A) of the heart to lung fields calculated using the "amplitude A" and "amplitude B" obtained in this manner, and FIG. 22 is a box plot showing the degree of variation in the data shown in FIG. 21. The contents expressed by the box plot and the treatment of the singular points are the same as those in FIG. 17 described above, and therefore the explanation will be omitted. Even when obtaining the signal values ​​"amplitude A" and "amplitude B" for the entire heart ("α2" in Figure 18) and the entire lung field ("β2" and "γ2" in Figure 18), and calculating the average signal value ratio between the heart and the lung field (amplitude B / amplitude A), it can be seen that people with a higher pulmonary valve regurgitation rate (%) (people with more severe regurgitation symptoms) tend to have a larger average signal value ratio between the heart and the lung field (amplitude B / amplitude A).

[0079] Furthermore, the control unit 31 may extract five consecutive wavelengths whose shapes are not distorted from the integrated signal values ​​within the entire target region of the heart ("α2" in Figure 18) and the integrated signal values ​​within the entire target region of the lung field ("β2" and "γ2" in Figure 18), and obtain "amplitude A" and "amplitude B" by averaging the amplitude for each wavelength. Fig. 23 shows the change in integrated signal value when the entire heart is the target region (ROI, "α2" in Fig. 18), and the "amplitude" of the average signal value is taken as "amplitude A". Fig. 24 shows the change in integrated signal value when the entire lung field is the target region (ROI, "β2" and "γ2" in Fig. 18), and the "amplitude" of the average signal value is taken as "amplitude B". Note that "amplitude A" shown in Fig. 23 and "amplitude B" shown in Fig. 24 are both obtained by removing noise by applying a bandpass filter according to the frequency of the heart's heart rate.

[0080] Figure 25 shows a graph of the average signal value ratio (amplitude B / amplitude A) between the heart and lung fields calculated using the "amplitude A" and "amplitude B" obtained in this manner, and Figure 26 is a box plot showing the degree of variation in the data shown in Figure 25. The contents expressed by the box plot and the treatment of the singular points are the same as those in FIG. 17 described above, and therefore the explanation will be omitted. Even when obtaining the "amplitude A" and "amplitude B" of the integrated signal values ​​for the entire heart ("α2" in Figure 18) and the entire lung field ("β2" and "γ2" in Figure 18), and determining the average signal value ratio between the heart and the lung field (amplitude B / amplitude A), it can be seen that people with a higher pulmonary valve regurgitation rate (%) (people with more severe regurgitation symptoms) tend to have a larger average signal value ratio between the heart and the lung field (amplitude B / amplitude A).

[0081] Thus, a correspondence is recognized between the heart-lung field average signal value ratio (amplitude B / amplitude A) and the pulmonary valve regurgitation rate (%). Therefore, the control unit 31 as a generating unit generates information on the heart-lung field average signal value ratio (amplitude B / amplitude A) from the dynamic image as "information on pulmonary valve regurgitation" and outputs and displays this to the display unit 34 or the like, thereby making it possible to show a user such as a doctor the presence or absence of pulmonary valve regurgitation and the degree of regurgitation rate (level, severity of pulmonary valve regurgitation) with the same degree of accuracy as an echo test or the like, without performing an ultrasonic echo test or an MRI test, thereby making it possible to support the diagnosis of pulmonary valve regurgitation.

[0082] Furthermore, when further parameters (such as "skewness" or "kurtosis") are obtained from the blood flow waveform obtained based on the pixel signal values, and a threshold is set using these parameters, the "information regarding pulmonary valve regurgitation" generated by the control unit 31 from the dynamic image may be the result of determining whether or not the patient being diagnosed has a blood flow above the threshold. In this case, as shown in FIG. 27, for example, a reliable examination such as an MRI examination is first performed on a sample patient to obtain the pulmonary artery reflux rate (step S51). Then, dynamic imaging is performed on the patient from whom these reflux rates have been acquired, blood flow waveforms are obtained from the dynamic images, and values ​​of items that will become parameters such as "skewness" and "kurtosis" are acquired (step S52). The data of the patient from whom the reflux rates and parameter values ​​have been acquired are used as sample data.

[0083] Once the sample data thus obtained has been accumulated, each sample data is plotted two-dimensionally with the parameter values ​​on the vertical and horizontal axes (step S53).For each parameter, a threshold is set at a point where the plotted sample data is correctly classified into a group of "pulmonary regurgitation present" and a group of "pulmonary regurgitation absent" that have been confirmed by testing (step S54).

[0084] For example, Figure 28 shows the results of obtaining "skewness" and "kurtosis" as parameters, plotting sample data with "kurtosis" on the vertical axis and "skewness" on the horizontal axis. In Figure 28, open circles represent samples that were determined to have "pulmonary valve regurgitation" in an MRI test or the like, and filled circles represent samples that were determined to have "no pulmonary valve regurgitation." As shown in Figure 28, patients with a high regurgitation rate tend to have a low "skewness" close to zero, and a high "kurtosis." Additionally, patients with high "skewness" or a not-so-high "kurtosis" tend to have a low regurgitation rate. In the example shown in Figure 28, sample data was classified by setting a threshold value of 0.55 for the parameter "skewness" and a threshold value of -0.3 for the parameter "kurtosis." As a result, it was found that patients with a regurgitation rate of 25% or more could be classified as having "pulmonary valve regurgitation" with a classification accuracy of 94.3%.

[0085] In this way, when thresholds are set for parameters (e.g., "skewness" and "kurtosis") based on the accumulation of sample data, when a new patient who has not undergone an MRI or other examination arrives, dynamic images are acquired (step S55), and the values ​​of "skewness" and "kurtosis" are obtained by image analysis (step S56). The patient is then classified according to thresholds such as "skewness" and "kurtosis," and a determination is made as to whether "pulmonary regurgitation is present" or "pulmonary regurgitation is absent" (step S57). For example, if a patient is classified into the position indicated by the open star in FIG. 28, the patient is determined to have "pulmonary regurgitation," whereas if the patient is classified into the position indicated by the black star, the patient is determined to have "no pulmonary regurgitation."

[0086] The classification determination result is output from the control unit 31 as an output unit to the display unit 34 or the like (step S56) and is displayed. The content output to the display unit 34 etc. may be only the judgment result, or the result itself may be displayed, plotting a new patient in a table such as that shown in FIG. 28 based on the values ​​of "skewness" and "kurtosis." Doctors and other users can look at the output results and, if it is determined that the patient has pulmonary valve regurgitation or if the determined regurgitation rate is high, take action such as ordering an MRI scan to confirm the situation in more detail.

[0087] Once enough sample data has been accumulated to enable correlation with the regurgitation rate, it will be possible to derive not only "pulmonary valve regurgitation present" or "pulmonary valve regurgitation absent," but also a more specific regurgitation rate (a quantitative value indicating the degree and severity of pulmonary valve regurgitation) from values ​​such as "skewness" and "kurtosis." In addition, by using multiple regression analysis or the like, the relationship (correlation, etc.) between parameters such as "skewness" and "kurtosis" and the pulmonary valve regurgitation rate can be considered, thereby ensuring the accuracy of the regurgitation rate determination.

[0088] According to this embodiment, blood flow analysis can be performed based on dynamic images (X-ray dynamic images) that can be obtained relatively easily and non-invasively for the subject M, ie, a patient.

[0089] In this embodiment, the processes shown in Figures 3, 7, 15, and 27 are exemplified as analysis processes for dynamic images, but the analysis device 3 may perform a portion of one or more of these processes, or may perform all of the processes. When multiple types of "information on pulmonary regurgitation" are obtained by performing each process, all of the information may be output to the display unit 34 or the like for display, or the user may be able to select the information he or she wishes to display. Also, the various types of acquired information may be combined to generate more reliable information, and the final information may be output and provided to a user such as a doctor.

[0090] [effect] As described above, the analysis device 3, which is an information processing device in this embodiment, is equipped with a control unit 31 that functions as an acquisition unit that acquires dynamic images of the chest obtained by dynamic radiography using radiation, functions as a generation unit that generates "information related to pulmonary valve regurgitation" based on dynamic image information of "areas related to at least one of the pulmonary artery and the heart" in the dynamic images, and functions as an output unit that outputs the "information related to pulmonary valve regurgitation" generated by the generation unit. In this manner, in this embodiment, "information on pulmonary valve regurgitation" is obtained using dynamic images obtained by X-ray dynamic imaging. Therefore, compared to, for example, conventional echography using ultrasound or MRI examination, this can be performed relatively easily using a general device. In addition, since it is sufficient to perform normal dynamic images, there is little risk of variation in results depending on the skill of the technician, as occurs with, for example, echography. It is non-invasive, and X-ray exposure is relatively low, so the burden on the patient is small. Furthermore, unlike MRI examinations, it can be used on patients who have MRI-uncompatible metals in their bodies, and there are no operational restrictions, making it possible to widely meet various needs. Furthermore, this method, which places little burden and restrictions, can obtain "information on pulmonary valve regurgitation" that is as reliable as other tests, such as ultrasound echography and MRI, thereby assisting doctors and other users in making diagnoses.

[0091] Furthermore, in this embodiment, the site (site related to the pulmonary artery) includes at least a region inside either the left or right lung field region and proximal to the left and right pulmonary arteries. Since data is collected from a region of the dynamic image that includes the proximal portions of the left and right pulmonary arteries, where the blood flow conditions in the pulmonary arteries, which are necessary for determining whether or not there is pulmonary regurgitation, are visible, it is possible to obtain signal values ​​appropriate for determining whether or not there is pulmonary regurgitation.

[0092] In addition, in this embodiment, the area (the area related to the pulmonary artery) is a target area set inside the left and right lung field areas and proximal to the left and right pulmonary arteries, and the "information regarding pulmonary valve regurgitation" is the average value of the values ​​in both the left and right target areas. Therefore, appropriate values ​​can be obtained even for patients with different abnormalities such as pulmonary valve regurgitation in the left and right lungs, and diagnosis can be supported to ensure that a correct diagnosis is made.

[0093] Furthermore, in this embodiment, the dynamic image information is the signal values ​​of pixels, and the control unit 31, which is the generating unit, generates "information regarding pulmonary valve regurgitation" based on information obtained from the signal values ​​of pixels in a region (a region related to the pulmonary artery). Since data is collected from a region of the dynamic image that includes the proximal portions of the left and right pulmonary arteries, where the blood flow conditions in the pulmonary arteries, which are necessary for determining whether or not there is pulmonary regurgitation, are visible, it is possible to obtain signal values ​​appropriate for determining whether or not there is pulmonary regurgitation.

[0094] Furthermore, if the "information regarding pulmonary valve regurgitation" is generated based on the average signal values ​​of the pixels in the dynamic image, appropriate information can be obtained even if some signal values ​​show peculiar values, without being influenced by those values.

[0095] In this embodiment, "information regarding pulmonary valve regurgitation" is information regarding the presence or absence of pulmonary valve regurgitation. This makes it possible to determine whether or not pulmonary valve regurgitation is present from dynamic images obtained by dynamic X-ray photography without having to perform an MRI or other examination, providing diagnostic support for easily diagnosing patients with pulmonary valve regurgitation or suspected of having it.

[0096] Furthermore, if it is possible to obtain information on the severity of pulmonary valve regurgitation, such as the regurgitation rate, from dynamic images obtained by X-ray dynamic imaging, it will be possible to obtain similar information to that obtained by an MRI examination through a simple examination such as X-ray dynamic imaging, thereby providing significant diagnostic support.

[0097] It is also possible to determine the presence or absence of pulmonary regurgitation (or suspicion of pulmonary regurgitation) from the shape of the blood flow waveform itself. By generating information on the shape of this blood flow waveform and displaying it on the display unit 34, etc., it is possible to provide users such as doctors with diagnostic support regarding pulmonary regurgitation.

[0098] In addition, when the control unit 31, which is the generating unit, generates information that visualizes blood flow in a region (a region related to the pulmonary artery) as "information regarding pulmonary valve regurgitation," the "information regarding pulmonary valve regurgitation" can be displayed on the display unit 34, etc. in an easy-to-understand manner, thereby appropriately assisting in diagnosis.

[0099] Furthermore, when the control unit 31, which is the generating unit, generates information obtained based on the blood flow waveform (e.g., "kurtosis," "skewness," "amplitude," etc.) as "information regarding pulmonary valve regurgitation" rather than the blood flow waveform itself, it becomes possible to perform a multifaceted, quantitative analysis of pulmonary valve regurgitation, thereby obtaining useful information for diagnostic support.

[0100] Furthermore, the control unit 31, which is a generating unit, may generate "information about pulmonary valve regurgitation" based on indices obtained in areas related to the pulmonary artery. When "information about pulmonary valve regurgitation" is generated from "indices," such as blood flow velocity, blood flow rate (≒ amplitude), and the ratio of signal values ​​of the heart and lung field (amplitude ratio), it becomes possible to perform multifaceted analysis of pulmonary valve regurgitation, and obtain information that is significant for diagnostic support. In this way, various information can be extracted from the dynamic images obtained by X-ray dynamic imaging. As shown in this embodiment, by using this information, it is possible to widely meet the need for diagnostic support for pulmonary valve regurgitation, which has previously been difficult to diagnose with only limited techniques such as ultrasound echography and MRI.

[0101] [Variations] It goes without saying that the present invention is not limited to the above-described embodiment, and various modifications can be made without departing from the spirit of the present invention.

[0102] For example, in this embodiment, an example is given of the analysis device 3, which is an information processing device, having a display unit 34 that displays dynamic images, images showing the results of image analysis, the presence or absence and the degree of reflux, etc., but it is not essential that the analysis device 3 is equipped with a display unit 34. For example, a display device or the like equipped with a high-resolution monitor or the like may be provided separately from the analysis device 3 so that the analysis results or the like in the analysis device 3 can be confirmed on the monitor of the display device or the like. Furthermore, when multiple analysis results, such as indicators showing the presence or absence and the degree of reflux, and judgment results, are obtained, these may be displayed in parallel so that they can be compared and considered.

[0103] Furthermore, when dynamic images and various examinations are continuously and periodically performed on the same patient, the information obtained from these can be stored and accumulated in the memory unit 32, etc., and when a new examination, etc. is performed, the past data can also be displayed in parallel in chronological order for comparison. This allows doctors and other medical professionals to easily grasp the progression and improvement of symptoms, and provides useful information to support diagnosis when performing ongoing treatment. [Explanation of symbols]

[0104] 1. Imaging device 2. Shooting console 3 Analysis equipment (dynamic image analysis equipment, information processing equipment) 31 Control Unit 34 Display section 100 Image capture system

Claims

1. a first acquisition unit that acquires a dynamic image obtained by dynamic radiography in which radiation is irradiated from one direction to capture a dynamic image of the chest of a subject; a second acquisition unit that analyzes the dynamic image acquired by the first acquisition unit and acquires information regarding pulmonary valve regurgitation; an output unit that outputs a determination result regarding pulmonary valve regurgitation determined based on the information regarding pulmonary valve regurgitation acquired by the second acquisition unit.

2. The information processing device according to claim 1 , further comprising a determination unit for performing a determination regarding the pulmonary valve regurgitation.

3. The information processing device according to claim 2 , wherein the determination unit makes a determination regarding the pulmonary valve regurgitation based on dynamic image information of a portion related to at least one of the heart and the pulmonary artery in the dynamic image.

4. The information processing device according to claim 1 , wherein the determination result is the presence or absence of pulmonary valve regurgitation.

5. The information processing device according to claim 1 , wherein the output unit outputs the determination result and a regurgitation rate of pulmonary valve regurgitation.

6. The information processing apparatus according to claim 2 , further comprising an acquisition unit for acquiring the dynamic image.

7. The information processing device according to claim 3 , wherein the region includes at least an area inside either the left or right lung field region and proximal to the left and right pulmonary arteries.

8. The information processing apparatus according to claim 3 , wherein the region is a target region set inside the left and right lung field regions and proximal to the left and right pulmonary arteries.

9. The information processing apparatus according to claim 8 , wherein the determination unit makes the determination based on an average value of values ​​in both the left and right target regions.

10. The dynamic image information is the signal value of the pixel. The information processing apparatus according to claim 3 , wherein the determination section makes the determination based on information obtained from a signal value of the pixel.

11. The dynamic image information is the signal value of the pixel. The information processing apparatus according to claim 3 , wherein the determination section makes the determination based on an average value of signal values ​​of pixels in the region.

12. The information processing device according to claim 1 , wherein the determination result is a severity of the pulmonary valve regurgitation.

13. The information processing apparatus according to claim 3 , wherein the determining unit performs the determination based on information on a shape of a blood flow waveform in the region.

14. The information processing apparatus according to claim 1 , wherein the output unit outputs information in which blood flow is visualized.

15. The information processing apparatus according to claim 3 , wherein the determination unit makes a determination based on an index obtained for the part.

16. 4. The information processing device according to claim 3, wherein the determination unit makes a determination based on at least one of information regarding a blood flow waveform at the site, a skewness of the blood flow waveform, a kurtosis of the blood flow waveform, an amplitude of the blood flow waveform, and a backflow rate.

17. On the computer, a first acquisition process for acquiring a dynamic image obtained by dynamic imaging in which radiation is irradiated from one direction to capture a dynamic image of the chest of a subject; a second acquisition process for analyzing the dynamic image acquired by the first acquisition process and acquiring information regarding pulmonary valve regurgitation; a process of outputting a determination result regarding pulmonary regurgitation determined based on information regarding pulmonary regurgitation acquired by the second acquisition process; and A program that executes the following.

18. a first acquisition step of acquiring a dynamic image obtained by dynamic radiography in which radiation is irradiated from one direction to acquire a dynamic image of the chest of a subject; a second acquisition step of analyzing the dynamic image acquired in the first acquisition step to acquire information regarding pulmonary valve regurgitation; and outputting a determination result regarding pulmonary valve regurgitation determined based on the information regarding pulmonary valve regurgitation acquired in the second acquisition step.

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