Radiographic image analysis device and program

Abstract

To provide a radiographic image analysis device improving estimation accuracy when estimating a respiratory function from a dynamic image acquired by dynamic imaging.SOLUTION: A control part of an analysis device estimates a respiratory function of a subject on the basis of a feature amount of a region of interest extracted from a dynamic image of the chest of the subject and examination result information of a past respiratory function examination for the subject.SELECTED DRAWING: Figure 3

Description

[Technical Field] 【0001】 The present invention relates to a radiological image analyzing device and a program. [Background technology] 【0002】 Spirometry has traditionally been used to measure respiratory function. However, spirometry places a significant burden on patients. In particular, performing spirometry multiple times during follow-up observations of respiratory function places an even greater burden on patients. Furthermore, if a patient's condition worsens during follow-up observations, it becomes difficult to perform spirometry-based respiratory function tests. 【0003】 As an alternative to spirometry, a method of estimating respiratory function from dynamic images obtained by dynamic chest radiography is being studied (see, for example, Patent Document 1). Dynamic radiography is less invasive than spirometry and places less strain on patients. [Prior art documents] [Patent documents] 【0004】 [Patent Document 1] Japanese Patent Application Publication No. 2019-187862 Summary of the Invention [Problem to be solved by the invention] 【0005】 However, in follow-up observation, for example, to capture changes in respiratory function before and after surgery, it is necessary to estimate respiratory function more accurately. Furthermore, when replacing spirometry with dynamic imaging, it is necessary to improve estimation accuracy from the perspective of test reliability. 【0006】 An object of the present invention is to improve the estimation accuracy when estimating respiratory function from dynamic images acquired by dynamic imaging. [Means for solving the problem] 【0007】 In order to solve the above problems, the radiation image analysis device of the present invention comprises: an estimation means for estimating the respiratory function of the subject based on feature amounts of a region of interest extracted from a dynamic image of the chest of the subject and test result information of a past respiratory function test on the subject; Equipped with. 【0008】 The program of the present invention also includes: Computer, an estimation means for estimating the respiratory function of the subject based on feature amounts of a region of interest extracted from a dynamic image of the chest of the subject and test result information of a past respiratory function test on the subject; Function as. [Effects of the Invention] 【0009】 According to the present invention, it is possible to improve the estimation accuracy when estimating respiratory function from dynamic images acquired by dynamic imaging. [Brief explanation of the drawings] 【0010】 [Figure 1] 1 is a diagram showing the overall configuration of a radiological image analysis system according to an embodiment of the present invention. [Figure 2] 2 is a flowchart showing an imaging control process executed by a control unit of the imaging console of FIG. 1. [Figure 3] 2 is a flowchart showing a respiratory function estimation process executed by a control unit of the analysis device of FIG. [Figure 4] 1 is a graph showing the relationship between estimated FVC and measured FVC. DETAILED DESCRIPTION OF THE INVENTION 【0011】 Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings, but the scope of the invention is not limited to the illustrated examples. 【0012】 <Configuration of Radiation Image Analysis System 100> First, the configuration of the embodiment of the present invention will be described. FIG. 1 shows an example of the overall configuration of a radiological image analysis system 100 according to this embodiment. As shown in FIG. 1, the radiographic image analysis system 100 includes an imaging device 1, an imaging console 2, and an analysis device 3 (radiographic image analysis device). The imaging device 1 and the imaging console 2 are connected by a communication cable or the like. The imaging console 2 and the analysis device 3 are connected via a communication network NT such as a LAN (Local Area Network). The communication network NT may also be connected to a RIS (Radiology Information Systems), HIS (Hospital Information Systems), an electronic medical record system, a PACS (Picture Archiving and Communication System), etc. (not shown). Each device constituting the radiographic image analysis system 100 conforms to the DICOM (Digital Image and Communications in Medicine) standard, and communication between the devices is performed in accordance with DICOM. 【0013】 <Configuration of the imaging device 1> The imaging device 1 is an imaging means for capturing periodic (cyclic) dynamics of the chest, such as changes in the shape of lung expansion and contraction due to breathing, and heartbeat. Dynamic imaging refers to obtaining multiple images showing the dynamics of a subject by repeatedly irradiating the subject with pulsed radiation such as X-rays at predetermined time intervals (pulse irradiation) or by continuously irradiating the subject with low dose rate radiation without interruption (continuous irradiation). 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, dynamic imaging includes video recording, but does not include capturing still images while displaying the video. Dynamic images include video, but do not include images obtained by capturing still images while displaying the video. In the following embodiment, a case where dynamic imaging is performed using pulse irradiation will be described as an example. 【0014】 The radiation source 11 is disposed at a position facing the radiation detection unit 13 across the subject M (the region of the subject to be imaged), and irradiates the subject M with radiation (X-rays) under the control of the radiation irradiation controller 12. The radiation irradiation control device 12 is connected to the imaging console 2. The radiation irradiation control device 12 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, the pulse rate, pulse width, 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. 【0015】 The radiation detection unit 13 is composed of a semiconductor image sensor such as an FPD. The FPD has, for example, a glass substrate. A plurality of detection elements (pixels) are arranged in a matrix at predetermined positions on the glass substrate. Each pixel detects radiation that has been irradiated from the radiation source 11 and transmitted through at least the subject M according to its intensity, and converts the detected radiation into an electrical signal and stores it. Each pixel has a switching unit such as a TFT (Thin Film Transistor). FPDs can be of an indirect conversion type, in which X-rays are converted into an electrical signal by a photoelectric conversion element via a scintillator, or a direct conversion type, in which X-rays are directly converted into an electrical signal, and either type may be used. The radiation detection unit 13 is disposed opposite the radiation source 11 with the subject M interposed therebetween. 【0016】 The reading control device 14 is connected to the radiography console 2. The reading control device 14 controls the switching units of each pixel of the radiation detection unit 13 based on the image reading conditions input from the radiography console 2, switches the reading of the electrical signals accumulated in each pixel, and reads the electrical signals accumulated in the radiation detection unit 13. In this way, the reading control device 14 acquires image data. This image data is a frame image. The reading control device 14 then outputs the acquired frame image to the radiography console 2. The image reading conditions include, for example, the frame rate, frame interval, pixel size, image size (matrix size), etc. The frame rate is the number of frame images acquired per second and coincides with 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 coincides with the pulse interval. 【0017】 The radiation irradiation control device 12 and the reading control device 14 are connected to each other and exchange synchronization signals with each other to synchronize the radiation irradiation operation and the image reading operation. 【0018】 <Configuration of shooting console 2> The imaging console 2 outputs radiation irradiation conditions and image reading conditions to the imaging device 1 to control the operations of radiography and reading of radiographic images by the imaging device 1. The imaging console 2 also displays dynamic images acquired by the imaging device 1 so that the imaging technician or other person performing the imaging can check the positioning and whether the images are suitable for diagnosis. As shown in FIG. 1, the radiography console 2 comprises 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 . 【0019】 The control unit 21 is composed of a CPU (Central Processing Unit), RAM (Random Access Memory), etc. In response to operations performed by the operation unit 23, the CPU of the control unit 21 reads out a system program and various processing programs stored in the storage unit 22, loads them into the RAM, and executes various processes, including an imaging control process (to be described later), in accordance with the loaded programs. In this way, the control unit 21 centrally controls the operations of each unit of the imaging console 2 and the radiation irradiation and reading operations of the imaging device 1. 【0020】 The storage unit 22 is configured with 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 processing by the programs, data such as processing results, etc. For example, the storage unit 22 stores a program for executing the imaging control processing shown in FIG. 2. The storage unit 22 also stores radiation irradiation conditions and image reading conditions corresponding to the imaging region and imaging direction. The various programs are stored in the storage unit 22 in the form of readable program codes. The control unit 21 sequentially executes operations in accordance with the program codes. 【0021】 The operation unit 23 is configured to include a keyboard having cursor keys, numeric input keys, various function keys, etc., and a pointing device such as a mouse. The operation unit 23 outputs instruction signals input by operating the keys on the keyboard or the mouse to the control unit 21. The operation unit 23 may also include a touch panel provided on the display screen of the display unit 24. In this case, the operation unit 23 outputs instruction signals input via the touch panel to the control unit 21. 【0022】 The display unit 24 is configured with a monitor such as an LCD (Liquid Crystal Display) or a CRT (Cathode Ray Tube), etc. The display unit 24 displays input instructions, data, etc. from the operation unit 23 in accordance with instructions of a display signal input from the control unit 21. 【0023】 The communication unit 25 includes a LAN adapter, a modem, a TA (Terminal Adapter), etc. The communication unit 25 controls data transmission and reception between the radiography console 2 and each device connected to the communication network NT. 【0024】 <Configuration of analysis device 3> The analysis device 3 acquires dynamic images from the imaging console 2, analyzes the acquired dynamic images, and displays the analysis results. In this embodiment, the analysis device 3 estimates respiratory function (index values ​​representing respiratory function) based on the dynamic images of the chest. 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 . 【0025】 The control unit 31 is composed of a CPU, RAM, etc. In response to operations by the operation unit 33, the CPU of the control unit 31 reads out the system program and various processing programs stored in the storage unit 32, loads them into the RAM, and performs centralized control of the operations of each unit of the analysis device 3 according to the loaded programs. Furthermore, the CPU of the control unit 31 executes various processes including a respiratory function estimation process, which will be described later, in cooperation with the programs stored in the storage unit 32. The control unit 31 functions as an estimation means. 【0026】 The storage unit 32 is configured with a non-volatile semiconductor memory, a hard disk, or the like. The storage unit 32 stores various programs, parameters required for executing processing by the programs, data such as processing results, etc. The programs stored in the storage unit 32 include a program for the control unit 31 to execute respiratory function estimation processing. These various programs are stored in the storage unit 32 in the form of readable program codes. The control unit 31 sequentially executes operations in accordance with the program codes. The storage unit 32 also stores the dynamic image received from the imaging console 2 in association with the accompanying information and the estimation result of the respiratory function. The storage unit 32 also stores a regression equation (multiple regression model) used to estimate the respiratory function in the respiratory function estimation process. 【0027】 The operation unit 33 is configured to include a keyboard having cursor keys, numeric input keys, various function keys, etc., and a pointing device such as a mouse. The operation unit 33 outputs instruction signals input by operating the keys on the keyboard or the mouse to the control unit 31. The operation unit 33 may also include a touch panel provided on the display screen of the display unit 34. In this case, the operation unit 33 outputs instruction signals input via the touch panel to the control unit 31. 【0028】 The display unit 34 is configured by a monitor such as an LCD, a CRT, etc. The display unit 34 performs various displays in accordance with instructions of a display signal input from the control unit 31. 【0029】 The communication unit 35 includes a LAN adapter, a modem, a TA, etc. The communication unit 35 controls data transmission and reception between the analysis device 3 and each device connected to the communication network NT. 【0030】 <Operation of the Radiation Image Analysis System 100> Next, the operation of the radiation image analysis system 100 will be described. 【0031】 (Operation of imaging device 1 and imaging console 2) First, the imaging operation performed by the imaging device 1 and the imaging console 2 will be described. 2 shows an imaging control process executed in the control unit 21 of the imaging console 2. The imaging control process is executed by the control unit 21 in cooperation with a program stored in the storage unit 22. 【0032】 First, the control unit 21 accepts input of patient information and examination information by the imaging implementer operating the operation unit 23 (step S1). The patient information is information about the subject. The patient information includes information such as the patient ID, name, age, sex, height, and weight. The examination information includes the examination ID, examination date, imaging region, imaging direction, etc. In this embodiment, the imaging region is the chest, and the imaging direction is the front. The patient information and examination information may be acquired via the communication unit 25 from a RIS or HIS (not shown). 【0033】 Next, based on the input patient information and examination information, the control unit 21 reads out radiation irradiation conditions from the storage unit 22 and sets them in the radiation irradiation control device 12. The control unit 21 also reads out image reading conditions from the storage unit 22 and sets them in the reading control device 14 (step S2). 【0034】 Next, the control unit 21 waits for an instruction to irradiate radiation (step S3). Here, the person performing the imaging performs positioning by placing the subject M between the radiation source 11 and the radiation detection unit 13, and when the imaging preparations are complete, operates the operation unit 23 to input an instruction to irradiate radiation. 【0035】 When a radiation irradiation instruction is input via the operation unit 23 (step S3; YES), the control unit 21 outputs an imaging start instruction to the radiation irradiation control device 12 and the reading control device 14, and starts dynamic imaging (step S4). That is, the control unit 21 causes the radiation source 11 to irradiate radiation at pulse intervals set in the radiation irradiation control device 12, and causes the radiation detection unit 13 to acquire frame images. During dynamic imaging, the imaging operator is prompted to take a deep breath by providing breathing guidance such as "take a breath in" and "take a breath out." The imaging device 1 may also output a voice or display of breathing guidance such as "take a breath in" and "take a breath out." 【0036】 When an instruction to end radiation irradiation is input by the operation unit 23, the control unit 21 outputs an instruction to end imaging to the radiation irradiation control device 12 and the reading control device 14, and stops the imaging operation. 【0037】 Frame images of dynamic images acquired by photography are sequentially input to the photography console 2. The control unit 21 associates the input frame images with numbers (frame numbers) indicating the photography order and stores them in the storage unit 22 (step S5). The control unit 21 also displays the input frame images on the display unit 24 (step S6). The radiographer checks the positioning and the like using the displayed dynamic image and determines whether an image suitable for diagnosis has been acquired through radiography (radiography OK) or whether re-radiography is necessary (radiography NG).The radiographer then operates the operation unit 23 to input the result of the determination. 【0038】 When a determination result indicating that imaging is OK is input by a predetermined operation of the operation unit 23 (step S7; YES), the control unit 21 attaches an identification ID for identifying the dynamic image, patient information, examination information, radiation irradiation conditions, image reading conditions, a number indicating the imaging order (frame number), etc. to each of the series of frame images acquired by dynamic imaging as auxiliary information, and transmits the information to the analysis device 3 via the communication unit 25 (step S8). Then, the control unit 21 ends the imaging control process. On the other hand, when a determination result indicating that photography is NG is input by a predetermined operation of the operation unit 23 (step S7; NO), the control unit 21 deletes the series of frame images stored in the storage unit 22 (step S9). Then, the control unit 21 ends the photography control process. In this case, photography needs to be retaken. 【0039】 (Operation of analysis device 3) Next, the operation of the analysis device 3 will be described. In the analysis device 3, for example, when a dynamic image is received from the radiography console 2 via the communication unit 35, the control unit 31 associates the received dynamic image with additional information and stores the associated information in the storage unit 32. When an instruction to estimate respiratory function for the dynamic chest image stored in the storage unit 32 is given by operating the operation unit 33, the control unit 31 executes a respiratory function estimation process. The respiratory function estimation process is executed by cooperation between the control unit 31 and a program stored in the storage unit 32. The respiratory function estimation process will be described below with reference to FIG. 3. 【0040】 In the respiratory function estimation process, first, the control unit 31 extracts a feature amount of a region of interest from a dynamic image of a subject for respiratory function estimation (step S11). Here, the region of interest is a region of a specific structure. The specific structure is a structure that moves with respiratory movement, i.e., a structure whose size, position, density, etc. change with respiratory movement. In this embodiment, the region of interest is described as a lung field region. Furthermore, the feature amount of the region of interest is a value in the specific structure that changes with breathing. In this embodiment, the feature amount of the region of interest is described as the maximum lung field area (lung field area at maximum inspiration position) and the minimum lung field area (lung field area at maximum expiration position) during breathing. 【0041】 In step S11, the control unit 31 first recognizes lung field areas from each frame image of the dynamic image. Known image processing such as edge detection may be used to recognize the lung field areas, or machine learning may be used for recognition. Next, the control unit 31 counts the number of pixels in the recognized lung field areas and extracts (calculates) the area of ​​the lung field areas for each frame image based on the counted number of pixels. For example, the control unit 31 multiplies the number of pixels in each of the left and right lung field areas by the pixel size to calculate the area of ​​each of the left and right lung field areas, and calculates the total area of ​​the left and right lung field areas as the area of ​​the lung field area. The control unit 31 then acquires the maximum lung field area and the minimum lung field area from the calculated areas of the lung field areas as feature quantities of the region of interest. 【0042】 Next, the control unit 31 acquires test result information of a previous respiratory function test of the same patient (same subject) (step S12). For example, the control unit 31 may display an input screen for test result information of a past respiratory function test of the same patient on the display unit 34, and acquire the test result information of the past respiratory function test of the same patient in response to an input operation on the input screen by the operation unit 33. Alternatively, the control unit 31 may request a terminal device or system (e.g., a terminal device or electronic medical record system in a respiratory function testing room) that stores the test result information of the respiratory function test to transmit the test result information of the past respiratory function test of the same patient (for the same patient ID) via the communication unit 35. Then, the control unit 31 may acquire the test result information of the past respiratory function test of the same patient from such a terminal device or system. 【0043】 In this embodiment, the control unit 31 acquires test result information of FVC (forced vital capacity) and FEV1.0 (forced expiratory volume in one second) as test result information of the respiratory function test. In many cases, a respiratory function test such as spirometry and dynamic imaging are performed at the initial visit, so the control unit 31 can acquire test result information of the initial respiratory function test as test result information of a past respiratory function test. Furthermore, if respiratory function tests have been performed multiple times in the past, it is preferable that the control unit 31 acquires test result information of the most recent respiratory function test. This is because the respiratory condition in the most recent respiratory function test is considered to be closest to the patient's current respiratory condition. 【0044】 Next, the control unit 31 acquires the feature amount of the region of interest extracted from the previous dynamic chest image of the same patient (step S13). In step S13, the control unit 31 searches for and acquires from the storage unit 32 dynamic images captured at the same time as the previous respiratory function test for which the test result information was obtained in step S12. Generally, a respiratory function test and a dynamic imaging test are performed on the same day. Therefore, the control unit 31 acquires from the storage unit 32 dynamic images captured on the same day as the previous respiratory function test for which the test result information was obtained in step S12. Alternatively, the control unit 31 may acquire from a PACS (not shown) dynamic images captured on the same day as the previous respiratory function test for which the test result information was obtained in step S12. Then, the control unit 31 extracts feature amounts of the region of interest from the acquired dynamic images. The control unit 31 may store information on the feature amounts extracted from the dynamic image in association with the dynamic image in the storage unit 32. When information on the feature amounts of the region of interest is associated with a dynamic image captured at the same time as the past respiratory function test for which the test result information was obtained in step S12, the control unit 31 may read and acquire the information on the feature amounts from the storage unit 32. 【0045】 Next, the control unit 31 acquires patient attribute information (step S14). For example, the control unit 31 acquires patient attribute information by accessing an electronic medical record system (not shown) or the like via the communication unit 35. Examples of the patient attribute information include gender, age, and BMI (Body Mass Index). 【0046】 Next, the control unit 31 estimates the patient's respiratory function based on the information acquired in steps S11 to S14 (step S15). For example, the control unit 31 estimates the FVC as the respiratory function. If the patient is male, the control unit 31 estimates the FVC using the following formula (1). If the patient is female, the control unit 31 estimates the FVC using the following formula (2). The estimated FVC is defined as FVCest. 【number】 【number】 Here, Sins indicates the maximum lung field area. Sexp indicates the minimum lung field area. Age indicates age. Parameters with the ".clb" identifier (Sins.clb, Sexp.clb, FVC.clb, FEV1.0.clb) indicate that they are features extracted from past test result information or dynamic images acquired by past imaging. Parameters without the ".clb" identifier (Sins, Sexp) indicate that they are features extracted from dynamic images acquired by the current imaging. That is, if the patient is male, the control unit 31 calculates FVCest (estimated FVC) by substituting the maximum lung field area extracted from the current dynamic image for Sins in equation (1), the maximum lung field area extracted from the past dynamic image for Sins.clb, the minimum lung field area extracted from the current dynamic image for Sexp, the minimum lung field area extracted from the past dynamic image for Sexp.clb, the patient's BMI for BMI, the patient's age for Age, the FVC value from the past respiratory function test for FVC.clb, and the FEV1.0 from the past respiratory function test for FEV1.0.clb. If the patient is female, the control unit 31 calculates FVCest (estimated FVC) by substituting the maximum lung field area extracted from the current dynamic image for Sins in equation (2), the maximum lung field area extracted from the past dynamic image for Sins.clb, the minimum lung field area extracted from the current dynamic image for Sexp, the minimum lung field area extracted from the past dynamic image for Sexp.clb, the patient's BMI for BMI, the patient's age for Age, the FVC value from the past respiratory function test for FVC.clb, and the FEV1.0 from the past respiratory function test for FEV1.0.clb. 【0047】 The above equations (1) and (2) are regression equations (multiple regression models) generated by multiple regression analysis using FVC as the dependent variable and the parameters Sins, Sins.clb, Sexp, Sexp.clb, BMI, Age, FVC.clb, and FEV1.0.clb as explanatory variables. For example, FEV1.0 may be estimated using a regression equation (multiple regression model) generated by multiple regression analysis with FEV1.0 as the objective variable and the same parameters as above (Sins, Sins.clb, Sexp, Sexp.clb, BMI, Age, FVC.clb, FEV1.0.clb) as explanatory variables. 【0048】 Next, the control unit 31 displays the estimated FVC on the display unit 34, and stores the estimated FVC in the memory unit 32 in association with the dynamic image acquired by this imaging (step S16), thereby completing the respiratory function estimation process. 【0049】 FIG. 4 is a graph showing the relationship between the FVCest (estimated FVC) estimated using the above formula (1) or (2) and the FVC (measured FVC) measured by a respiratory function test for the same patient at the same time as the FVCest estimation. The vertical axis of the graph shown in FIG. 4 represents the estimated FVC (FVCest), and the horizontal axis represents the measured FVC. As shown in FIG. 4, it can be seen that the estimated FVC has a very high correlation with the measured FVC. In other words, it can be seen that respiratory function can be estimated with high accuracy based on the feature amounts of the region of interest extracted from dynamic images, test result information obtained by a previous respiratory function test for the same patient, feature amount information of the region of interest extracted from dynamic images obtained by previous dynamic imaging for the same patient, and patient attribute information. 【0050】 Here, it has been shown that respiratory function is correlated with features of regions of interest linked to respiration, such as lung field area, extracted from dynamic images (see, for example, Reference 1: N. Ohkura et al., “Chest Dynamic-Ventilatory Digital Radiography in Chronic Obstructive or Restrictive Lung Disease,” International Journal of Chronic Obstructive Pulmonary Disease 2021:16 1393-1399; Reference 2: M. Ueyama et al., “Prediction of forced vital capacity with dynamic chest radiography in interstitial lung disease,” European Journal of Radiology, July 21, 2021; Patent Document 1). Therefore, it has been proposed to estimate respiratory function based on features obtained from dynamic images. However, respiratory function varies significantly from person to person, and it is thought that estimating respiratory function solely from features of regions of interest in dynamic images may not reflect these individual differences, resulting in insufficient estimation accuracy. Therefore, by adding the patient's past respiratory function test results to the parameters used to estimate respiratory function, it is possible to reflect individual differences in respiratory function in the estimation of respiratory function, and it is thought that the accuracy of estimating respiratory function can be improved compared to conventional methods. In addition, it is believed that the accuracy of estimating respiratory function can be further improved by adding not only test result information from the patient's past respiratory function tests, but also information on the features of the areas of interest linked to breathing in past dynamic images taken at the same time as these past respiratory function tests. Furthermore, it is already widely known that factors such as age, gender, and physique affect respiratory function. Therefore, adding this patient attribute information to the parameters used to estimate respiratory function is expected to enable more accurate estimation of respiratory function. 【0051】 (Variation 1) In the above embodiment, an example of a regression equation used to estimate respiratory function when the feature quantities of the region of interest are the maximum lung field area and the minimum lung field area is shown. However, the feature quantities of the region of interest are not limited to the maximum lung field area and the minimum lung field area as long as they are feature quantities of a structure that moves with breathing. 【0052】 For example, the region of interest may be the diaphragm, the feature amount may be the displacement of the diaphragm due to breathing (Exc), and the FVCest may be estimated using the regression equation of the following equation (3). 【number】 Here, a to j represent partial regression coefficients (constants). Exc indicates displacement, _R indicates the right lung, and _L indicates the left lung. Parameters with the identifier "_clb" (Exc_R_clb, Exc_L_clb, FVC_clb, FEV1.0_clb) indicate that they are features obtained from test result information of past respiratory function tests or past dynamic images. Parameters without the identifier "_clb" (Exc_R, Exc_L) indicate that they are features obtained from dynamic images obtained by the current imaging. Age indicates age. Gender is a parameter indicating gender, for example, male: 1, female: 0. Note that a to h in equations (3), (4), and (5) are different. 【0053】 Furthermore, for example, the region of interest may be the trachea, the feature amount may be the amount of change in tracheal diameter due to breathing (Tra), and the FVCest may be estimated using the regression formula of the following formula (4). 【number】 Here, a to h indicate partial regression coefficients (constants). Tra indicates the amount of change in tracheal diameter. Parameters with the identifier "_clb" (Tra_clb, FVC_clb, FEV1.0_clb) indicate that they are features obtained from test result information of past respiratory function tests or past dynamic images. Parameters without the identifier "_clb" (Tra) indicate that they are features obtained from dynamic images obtained by the current scan. Age indicates age. Gender is a parameter indicating gender, for example, male: 1, female: 0. 【0054】 Furthermore, for example, the region of interest may be the lung field, the feature amount may be the density change rate (De) in the lung field region due to breathing, and the FVCest may be estimated using the regression formula of the following formula (5). Note that the density change rate of the lung field region is, for example, the average density change rate of each pixel value in the lung field region, including both the left and right. 【number】 Here, a to h indicate partial regression coefficients (constants). De indicates the concentration change rate (average concentration change rate) within the lung field region. Parameters with the identifier "_clb" (De_clb, FVC_clb, FEV1.0_clb) indicate that they are features obtained from test result information of past respiratory function tests or past dynamic images. Parameters without the identifier "_clb" (De) indicate that they are features obtained from dynamic images obtained by the current scan. Age indicates age. Gender is a parameter indicating gender, for example, male: 1, female: 0. 【0055】 In the above embodiment, the lung field area is the sum of the left and right lung field areas, but the lung field areas of the left and right lungs may be calculated separately and used as parameters for the multiple regression equation. Similarly, in the above modification, the concentration change rate is the average concentration change rate of each pixel value in the lung field area including the left and right lungs, but the concentration change rate may be calculated separately for the left and right lungs and used as parameters for the multiple regression equation. Furthermore, for example, FEV1.0 may be estimated using a regression equation generated by multiple regression analysis with FEV1.0 as the objective variable and the parameters used in Equations (3) to (5) as explanatory variables. 【0056】 (Variation 2) In the above embodiment, the feature values ​​of the region of interest extracted from the dynamic image of the front chest are used as the parameters for estimating respiratory function. Alternatively, the feature values ​​of the region of interest extracted from the dynamic image of the lateral chest may be used as the parameters for estimating respiratory function. Furthermore, the feature values ​​of the region of interest extracted from the dynamic images of both the front and lateral chest may be used as the parameters for estimating respiratory function. 【0057】 (Variation 3) In the above embodiment, the present invention has been described by taking as an example a case where it is applied to the estimation of FVC or FEV1.0. However, it may also be applied to predicting other respiratory functions such as VC (vital capacity), TLC (total lung capacity), RV (residual volume), and FRC (functional residual capacity). 【0058】 As described above, the control unit 31 of the analysis device 3 estimates the respiratory function of the subject based on the features of the area of ​​interest extracted from the dynamic image of the subject's chest and the test result information of the subject's past respiratory function test. Therefore, when estimating respiratory function from dynamic images acquired by dynamic imaging, estimation accuracy can be improved. 【0059】 Furthermore, the control unit 31 can further improve the accuracy of estimating the respiratory function of the subject by estimating the respiratory function of the subject based on the features of the area of ​​interest extracted from dynamic images of the subject's chest taken at the same time as the respiratory function test. 【0060】 Furthermore, the control unit 31 can further improve the accuracy of estimating the respiratory function by estimating the respiratory function of the subject based on attribute information such as the age, sex, and physique of the subject. 【0061】 The description in this embodiment is an example of a suitable radiographic image analysis device and program according to the present invention, and the present invention is not limited to this. For example, in the above embodiment, a case has been described in which a function for calculating feature amounts of a region of interest from a dynamic image and a function for estimating respiratory function using the calculated feature amounts are provided in one device. However, the function for calculating feature amounts of a region of interest from a dynamic image may be provided in a device separate from the device having the function for estimating respiratory function. 【0062】 In addition, for example, in the above description, examples have been disclosed in which a hard disk or a semiconductor nonvolatile memory is used as a computer-readable medium for the program according to the present invention, but the present invention is not limited to this example. Other computer-readable media include a CD-R It is possible to apply a portable recording medium such as an OM, etc. Furthermore, a carrier wave is also applied as a medium for providing the data of the program according to the present invention via a communication line. 【0063】 In addition, the detailed configuration and detailed operation of each device constituting the radiation image analysis system 100 may be modified as appropriate without departing from the spirit of the present invention. [Explanation of symbols] 【0064】 100 Radiation Image Analysis System 1. Imaging device 11 Radiation source 12 Radiation exposure control device 13 Radiation detection unit 14 Reading control device 2. Filming console 21 Control section 22 Memory section 23 Control section 24 Display section 25 Communications Department 26 Bus 3 Analysis device 31 Control Unit 32 Storage section 33 Operation section 34 Display section 35 Communications Department 36 Bus

Claims

[Claim 1] Estimation means for estimating the respiratory function of the subject at the same time as the acquisition of the first radiodynamic image, based on a first feature quantity extracted from a first radiodynamic image of the subject's chest and a second feature quantity extracted from a second radiodynamic image of the subject's chest taken prior to the time the first radiodynamic image was taken. A radiation image analysis device equipped with the following features. [Claim 2] The radiographic image analysis apparatus according to claim 1, wherein the estimation means estimates the respiratory function of the subject using a multiple regression model in which the first feature and the second feature are at least explanatory variables. [Claim 3] The radiographic image analysis apparatus according to claim 2, wherein the estimation means further estimates the respiratory function of the subject using the multiple regression model which includes the subject's attribute information as explanatory variables. [Claim 4] The radiation image analysis apparatus according to claim 3, wherein the attribute information includes at least one of the subject's sex, age, and BMI. [Claim 5] The radiographic image analysis apparatus according to claim 2, wherein the first feature quantity includes the maximum lung field area and the minimum lung field area extracted from the first radiographic image, and the second feature quantity includes the maximum lung field area and the minimum lung field area extracted from the second radiographic image. [Claim 6] The radiographic image analysis apparatus according to claim 2, wherein the first feature quantity includes diaphragmatic displacement, tracheal diameter change, or density change rate within the lung field region extracted from the first radiographic image, and the second feature quantity includes diaphragmatic displacement, tracheal diameter change, or density change rate within the lung field region extracted from the second radiographic image. [Claim 7] The radiographic image analysis apparatus according to any one of claims 2 to 6, wherein the estimation means further estimates the respiratory function of the subject based on the results of past respiratory function tests performed on the subject. [Claim 8] The radiographic image analysis apparatus according to claim 1, wherein the estimated respiratory function is FVC, FEV1.0, VC, TLC, RV, or FRC. [Claim 9] Computers Estimation means for estimating the respiratory function of the subject at the same time as the acquisition of the first radiodynamic image, based on a first feature quantity extracted from a first radiodynamic image of the subject's chest and a second feature quantity extracted from a second radiodynamic image of the subject's chest taken prior to the time the first radiodynamic image was taken. A program designed to function as such.

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