JP6929695B2 - Medical diagnostic imaging equipment and management equipment - Google Patents

Description

Embodiments of the present invention relate to medical diagnostic imaging equipment and management equipment.

Conventionally, in an examination using an X-ray CT apparatus (CT; Computed Tomography), a contrast scan in which a contrast agent is administered to a subject may be executed. In such a case, the X-ray CT apparatus determines the injection conditions of the contrast medium to be administered to the subject using the height and weight of the subject, BMI (Body Mass Index), and the like.

Japanese Unexamined Patent Publication No. 2008-012171 Japanese Unexamined Patent Publication No. 2012-23209 Japanese Unexamined Patent Publication No. 2008-012229 Japanese Unexamined Patent Publication No. 2014-014715

An object to be solved by the present invention is to provide a medical diagnostic imaging apparatus and a management apparatus capable of accurately determining injection conditions of a contrast medium to be administered to a subject.

The medical image diagnostic apparatus of the embodiment includes an acquisition unit, a detection unit, a derivation unit, and a control unit. The acquisition unit acquires the image data of the subject. The detection unit detects each of a plurality of parts of the subject in the image data. The derivation unit derives information relating to the constituents in the subject from the detection result of the detection unit. The control unit determines the injection conditions of the contrast medium to be administered to the subject in the contrast scan based on the information related to the components.

FIG. 1 is a diagram showing an example of a configuration of a medical information processing system according to the first embodiment. FIG. 2 is a diagram showing an example of the configuration of the X-ray CT apparatus according to the first embodiment. FIG. 3 is a diagram for explaining three-dimensional scanno image capture by the scan control circuit according to the first embodiment. FIG. 4A is a diagram for explaining an example of a portion detection process by the detection function according to the first embodiment. FIG. 4B is a diagram for explaining an example of a portion detection process by the detection function according to the first embodiment. FIG. 5 is a diagram for explaining an example of a portion detection process by the detection function according to the first embodiment. FIG. 6 is a diagram for explaining an example of a portion detection process by the detection function according to the first embodiment. FIG. 7 is a diagram showing an example of a virtual patient image stored by the storage circuit according to the first embodiment. FIG. 8 is a diagram for explaining an example of collation processing by the position collation function according to the first embodiment. FIG. 9 is a diagram showing an example of conversion of the scan range by coordinate conversion according to the first embodiment. FIG. 10 is a diagram for explaining the first embodiment. FIG. 11 is a flowchart showing a processing procedure by the X-ray CT apparatus according to the first embodiment. FIG. 12 is a diagram for explaining a second embodiment. FIG. 13 is a diagram for explaining other embodiments.

Hereinafter, embodiments of the medical diagnostic imaging apparatus and the management apparatus will be described in detail with reference to the accompanying drawings. Hereinafter, a medical information processing system including an X-ray CT (Computed Tomography) apparatus will be described as an example. In the medical information processing system 100 shown in FIG. 1, only one server device and one terminal device are shown, but in reality, a plurality of server devices and terminal devices can be further included. Further, the medical information processing system 100 can also include, for example, a medical image diagnostic device such as an X-ray diagnostic device, an MRI (Magnetic Resonance Imaging) device, and an ultrasonic diagnostic device.

(First Embodiment)
FIG. 1 is a diagram showing an example of the configuration of the medical information processing system 100 according to the first embodiment. As shown in FIG. 1, the medical information processing system 100 according to the first embodiment includes an X-ray CT device 1, a server device 2, and a terminal device 3. The X-ray CT device 1, the server device 2, and the terminal device 3 can communicate with each other directly or indirectly by, for example, an in-hospital LAN (Local Area Network) installed in the hospital. ing. For example, when PACS (Picture Archiving and Communication System) is introduced in the medical information processing system 100, each device is DICOM (Digital Imaging and Communications in).
Medicine) Send and receive medical images, etc. to and from each other in accordance with the standard.

Further, in the medical information processing system 100, for example, HIS (Hospital Information System) and RIS (Radiology Information System) are introduced to manage various information. For example, the terminal device 3 transmits the inspection order created according to the above system to the X-ray CT device 1 and the server device 2. The X-ray CT device 1 acquires patient information from a patient list (modality work list) for each modality created by an examination order directly received from the terminal device 3 or a server device 2 that has received the examination order, and the patient. Collect X-ray CT image data for each. Then, the X-ray CT apparatus 1 transmits the collected X-ray CT image data and the image data generated by performing various image processing on the X-ray CT image data to the server apparatus 2. The server device 2 stores the X-ray CT image data and the image data received from the X-ray CT device 1, generates image data from the X-ray CT image data, and responds to the acquisition request from the terminal device 3. The data is transmitted to the terminal device 3. The terminal device 3 displays the image data received from the server device 2 on a monitor or the like. Hereinafter, each device will be described.

The terminal device 3 is a device that is arranged in each clinical department in the hospital and operated by a doctor working in each clinical department, and is a PC (Personal Computer), a tablet PC, a PDA (Personal Digital Assistant), a mobile phone, or the like. Is. For example, in the terminal device 3, medical record information such as a patient's symptom and a doctor's findings is input by a doctor. Further, the terminal device 3 is input with an inspection order for ordering the inspection by the X-ray CT device 1, and transmits the input inspection order to the X-ray CT device 1 and the server device 2. That is, the doctor in the clinical department operates the terminal device 3 to read the reception information of the patient who visited the hospital and the information of the electronic medical record, examine the corresponding patient, and input the medical record information into the read electronic medical record. Then, the doctor in the clinical department operates the terminal device 3 to transmit the test order according to the necessity of the test by the X-ray CT device 1.

The server device 2 stores medical images (for example, X-ray CT image data and image data collected by the X-ray CT device 1) collected by the medical image diagnostic device, and performs various image processing on the medical image. It is a device for performing, for example, a PACS server. For example, the server device 2 receives a plurality of examination orders from the terminal devices 3 arranged in each clinical department, creates a patient list for each medical image diagnosis device, and creates the created patient list for each medical image diagnosis device. Send to. As an example, the server device 2 receives an examination order for performing an examination by the X-ray CT device 1 from the terminal device 3 of each clinical department, creates a patient list, and X-rays the created patient list. It is transmitted to the CT device 1. Then, the server device 2 stores the X-ray CT image data and the image data collected by the X-ray CT device 1, and in response to the acquisition request from the terminal device 3, the X-ray CT image data and the image data are stored in the terminal device. Send to 3.

The X-ray CT apparatus 1 collects X-ray CT image data for each patient, and uses the collected X-ray CT image data and image data generated by performing various image processing on the X-ray CT image data as a server. It is transmitted to the device 2. FIG. 2 is a diagram showing an example of the configuration of the X-ray CT apparatus 1 according to the first embodiment. As shown in FIG. 2, the X-ray CT apparatus 1 according to the first embodiment includes a pedestal 10, a sleeper 20, and a console 30. Further, the X-ray CT apparatus 1 is connected to a contrast medium injector (not shown in FIG. 2).

The gantry 10 is a device that irradiates the subject P (patient) with X-rays, detects the X-rays transmitted through the subject P, and outputs the X-rays to the console 30. The X-ray irradiation control circuit 11 and the X-ray generator are generated. It has a device 12, a detector 13, a data acquisition circuit (DAS: Data Acquisition System) 14, a rotating frame 15, and a gantry drive circuit 16. The data acquisition circuit 14 is an example of an acquisition unit.

The rotating frame 15 supports the X-ray generator 12 and the detector 13 so as to face each other with the subject P in between, and rotates at high speed in a circular orbit centered on the subject P by a gantry drive circuit 16 described later. It is an annular frame.

The X-ray irradiation control circuit 11 is a device that supplies a high voltage to the X-ray tube 12a as a high voltage generating unit, and the X-ray tube 12a uses the high voltage supplied from the X-ray irradiation control circuit 11 to X. Generate a line. The X-ray irradiation control circuit 11 adjusts the X-ray dose to be irradiated to the subject P by adjusting the tube voltage and the tube current supplied to the X-ray tube 12a under the control of the scan control circuit 33 described later. ..

Further, the X-ray irradiation control circuit 11 switches the wedge 12b. Further, the X-ray irradiation control circuit 11 adjusts the X-ray irradiation range (fan angle and cone angle) by adjusting the opening degree of the collimator 12c. In this embodiment, the operator may manually switch between a plurality of types of wedges.

The X-ray generator 12 is a device that generates X-rays and irradiates the subject P with the generated X-rays, and has an X-ray tube 12a, a wedge 12b, and a collimator 12c.

The X-ray tube 12a is a vacuum tube that irradiates the subject P with an X-ray beam by a high voltage supplied by a high voltage generator (not shown), and the X-ray beam is sent to the subject P as the rotating frame 15 rotates. Irradiate against. The X-ray tube 12a generates an X-ray beam that spreads with a fan angle and a cone angle. For example, under the control of the X-ray irradiation control circuit 11, the X-ray tube 12a is continuously exposed to X-rays all around the subject P for full reconstruction, or half-reconstructable for half-reconstruction. It is possible to continuously expose X-rays within the range (180 degrees + fan angle). Further, under the control of the X-ray irradiation control circuit 11, the X-ray tube 12a can intermittently emit X-rays (pulse X-rays) at a preset position (tube position). The X-ray irradiation control circuit 11 can also modulate the intensity of X-rays exposed from the X-ray tube 12a. For example, the X-ray irradiation control circuit 11 increases the intensity of X-rays emitted from the X-ray tube 12a at a specific tube position, and exposes the X-ray tube 12a to a range other than the specific tube position. Decreases the intensity of the emitted X-rays.

The wedge 12b is an X-ray filter for adjusting the X-ray dose of X-rays exposed from the X-ray tube 12a. Specifically, the wedge 12b transmits the X-rays exposed from the X-ray tube 12a so that the X-rays radiated from the X-ray tube 12a to the subject P have a predetermined distribution. It is a filter that attenuates. For example, the wedge 12b is a filter made of aluminum so as to have a predetermined target angle and a predetermined thickness. The wedge is also called a wedge filter or a bow-tie filter.

The collimator 12c is a slit for narrowing down the X-ray irradiation range in which the X-ray dose is adjusted by the wedge 12b under the control of the X-ray irradiation control circuit 11 described later.

The gantry drive circuit 16 rotates the rotating frame 15 to rotate the X-ray generator 12 and the detector 13 on a circular orbit centered on the subject P.

The detector 13 is a two-dimensional array type detector (surface detector) that detects X-rays that have passed through the subject P, and the detection element sequence formed by arranging X-ray detection elements for a plurality of channels is the subject P. A plurality of rows are arranged along the body axis direction (Z-axis direction shown in FIG. 2). Specifically, the detector 13 in the first embodiment has X-ray detection elements arranged in multiple rows such as 320 rows along the body axis direction of the subject P, for example, the lungs of the subject P. It is possible to detect X-rays that have passed through the subject P over a wide range, such as in the range including the heart and the heart.

The data collection circuit 14 is a DAS and collects projection data from the X-ray detection data detected by the detector 13. For example, the data collection circuit 14 generates projection data by performing amplification processing, A / D conversion processing, sensitivity correction processing between channels, and the like on the X-ray intensity distribution data detected by the detector 13. The projected projection data is transmitted to the console 30 described later. For example, when X-rays are continuously exposed from the X-ray tube 12a during the rotation of the rotating frame 15, the data acquisition circuit 14 collects the projection data group for the entire circumference (360 degrees). Further, the data collection circuit 14 associates the tube position with each of the collected projection data and transmits the data to the console 30 described later. The tube position is information indicating the projection direction of the projection data. The sensitivity correction process between channels may be performed by the preprocessing circuit 34, which will be described later.

The sleeper 20 is a device on which the subject P is placed, and has a sleeper drive device 21 and a top plate 22 as shown in FIG. The sleeper drive device 21 moves the top plate 22 in the Z-axis direction to move the subject P into the rotating frame 15. The top plate 22 is a plate on which the subject P is placed.

The gantry 10 executes, for example, a helical scan in which the rotating frame 15 is rotated while the top plate 22 is moved to scan the subject P in a spiral shape. Alternatively, the gantry 10 executes a conventional scan in which the rotating frame 15 is rotated while the position of the subject P is fixed after the top plate 22 is moved to scan the subject P in a circular orbit. Alternatively, the gantry 10 executes a step-and-shoot method in which the position of the top plate 22 is moved at regular intervals to perform a conventional scan in a plurality of scan areas.

The console 30 is a device that accepts the operation of the X-ray CT device 1 by the operator and reconstructs the X-ray CT image data using the projection data collected by the gantry 10. As shown in FIG. 2, the console 30 includes an input circuit 31, a display 32, a scan control circuit 33, a preprocessing circuit 34, a storage circuit 35, an image reconstruction circuit 36, and a processing circuit 37. .. The preprocessing circuit 34 and the image reconstruction circuit 36 are examples of the acquisition unit.

The input circuit 31 has a mouse, keyboard, trackball, switch, button, joystick, etc. used by the operator of the X-ray CT apparatus 1 to input various instructions and various settings, and information on the instructions and settings received from the operator. Is transferred to the processing circuit 37. For example, the input circuit 31 receives from the operator the imaging conditions for the X-ray CT image data, the reconstruction conditions for reconstructing the X-ray CT image data, the image processing conditions for the X-ray CT image data, and the like. Further, the input circuit 31 accepts an operation for selecting a test for the subject P. Further, the input circuit 31 accepts a designation operation for designating a portion on the image.

The display 32 is a monitor referenced by the operator, and under the control of the processing circuit 37, displays the image data generated from the X-ray CT image data to the operator, or displays the image data to the operator via the input circuit 31. GUI (Graphical) for accepting various instructions and settings from
User Interface) is displayed. In addition, the display 32 displays a plan screen for a scan plan, a screen during scanning, and the like. In addition, the display 32 displays a virtual patient image including exposure information, image data, and the like. The virtual patient image displayed by the display 32 will be described in detail later.

The scan control circuit 33 controls the operations of the X-ray irradiation control circuit 11, the gantry drive circuit 16, the data acquisition circuit 14, and the sleeper drive device 21 under the control of the processing circuit 37, thereby displaying the projection data on the gantry 10. Control the collection process. Specifically, the scan control circuit 33 controls the collection process of projection data in the imaging for collecting the positioning image (scano image) and the main imaging (scan) for collecting the image used for diagnosis. Here, in the X-ray CT apparatus 1 according to the first embodiment, a two-dimensional scanno image and a three-dimensional scanno image can be taken.

For example, the scan control circuit 33 fixes the X-ray tube 12a at a position of 0 degrees (a position in the front direction with respect to the subject P), and continuously shoots while moving the top plate 22 at a constant speed. Take a two-dimensional scano image with. Alternatively, the scan control circuit 33 fixes the X-ray tube 12a at a position of 0 degrees, moves the top plate 22 intermittently, and intermittently repeats shooting in synchronization with the movement of the top plate, thereby causing two dimensions. Take a scanno image of. Here, the scan control circuit 33 can capture a positioning image not only from the front direction but also from an arbitrary direction (for example, a side surface direction) with respect to the subject P.

In addition, the scan control circuit 33 captures a three-dimensional scanno image by collecting projection data for the entire circumference of the subject P in capturing the scanno image. FIG. 3 is a diagram for explaining three-dimensional scanno image capture by the scan control circuit 33 according to the first embodiment. For example, as shown in FIG. 3, the scan control circuit 33 collects projection data for the entire circumference of the subject P by helical scan or non-helical scan. Here, the scan control circuit 33 executes a helical scan or a non-helical scan on a wide area such as the entire chest, abdomen, upper body, and whole body of the subject P at a lower dose than the main imaging. As the non-helical scan, for example, the above-mentioned step-and-shoot method scan is executed.

In this way, the scan control circuit 33 collects the projection data for the entire circumference of the subject P, and the image reconstruction circuit 36 described later reconstructs the three-dimensional X-ray CT image data (volume data). As shown in FIG. 3, it is possible to generate a positioning image from an arbitrary direction using the reconstructed volume data. Here, whether to capture the positioning image in two dimensions or in three dimensions may be arbitrarily set by the operator, or may be preset according to the inspection content.

Returning to FIG. 2, the preprocessing circuit 34 performs logarithmic conversion processing and correction processing such as offset correction, sensitivity correction, and beam hardening correction on the projection data generated by the data acquisition circuit 14. Generate corrected projection data. Specifically, the preprocessing circuit 34 generates corrected projection data for each of the projection data of the positioning image generated by the data acquisition circuit 14 and the projection data collected by the main shooting, and the storage circuit 35. Store in.

The storage circuit 35 stores the projection data generated by the preprocessing circuit 34. Specifically, the storage circuit 35 stores the projection data of the positioning image generated by the preprocessing circuit 34 and the projection data for diagnosis collected by the main imaging. Further, the storage circuit 35 stores the image data and the virtual patient image generated by the image reconstruction circuit 36 described later. Further, the storage circuit 35 appropriately stores the processing result by the processing circuit 37 described later. The virtual patient image and the processing result by the processing circuit 37 will be described later.

The image reconstruction circuit 36 reconstructs the X-ray CT image data using the projection data stored in the storage circuit 35. Specifically, the image reconstruction circuit 36 reconstructs the X-ray CT image data from the projection data of the positioning image and the projection data of the image used for diagnosis. Here, there are various reconstruction methods, and examples thereof include back projection processing. Further, as the back projection process, for example, a back projection process by the FBP (Filtered Back Projection) method can be mentioned. Alternatively, the image reconstruction circuit 36 can reconstruct the X-ray CT image data by using the successive approximation method.

Further, the image reconstruction circuit 36 generates image data by performing various image processing on the X-ray CT image data. Then, the image reconstruction circuit 36 stores the reconstructed X-ray CT image data and the image data generated by various image processes in the storage circuit 35.

The processing circuit 37 controls the entire operation of the X-ray CT apparatus 1 by controlling the operations of the gantry 10, the sleeper 20, and the console 30. Specifically, the processing circuit 37 controls the CT scan performed on the gantry 10 by controlling the scan control circuit 33. Further, the processing circuit 37 controls the image reconstruction process and the image generation process in the console 30 by controlling the image reconstruction circuit 36. Further, the processing circuit 37 controls the display 32 to display various image data stored in the storage circuit 35.

Further, as shown in FIG. 2, the processing circuit 37 executes the detection function 37a, the position matching function 37b, and the control function 37c. Here, for example, each processing function executed by the detection function 37a, the position matching function 37b, and the control function 37c, which are the components of the processing circuit 37 shown in FIG. 2, is stored in the form of a program that can be executed by a computer. It is recorded in. The processing circuit 37 is a processor that realizes a function corresponding to each program by reading each program from the storage circuit 35 and executing the program. In other words, the processing circuit 37 in the state where each program is read has each function shown in the processing circuit 37 of FIG. The detector function 37a is an example of a detection unit, and the control function 37c is an example of a derivation unit and a control unit.

The detection function 37a detects a plurality of parts of the subject P in the three-dimensional image data, respectively. Specifically, the detection function 37a detects a part such as an organ included in the three-dimensional X-ray CT image data (volume data) reconstructed by the image reconstruction circuit 36. For example, the detection function 37a detects a site such as an organ based on an anatomical landmark of at least one of the volume data of the positioning image and the volume data of the image used for diagnosis. Here, the anatomical feature point is a point showing the feature of a specific part such as a bone, an organ, a blood vessel, a nerve, or a lumen. That is, the detection function 37a detects bones, organs, blood vessels, nerves, lumens, etc. included in the volume data by detecting anatomical feature points such as specific organs and bones. Further, the detection function 37a has a detection function 37a.
By detecting the characteristic feature points of the human body, it is possible to detect the positions of the head, neck, chest, abdomen, legs, etc. included in the volume data. The site described in the present embodiment means a bone, an organ, a blood vessel, a nerve, a lumen, or the like including these positions. Hereinafter, an example of detecting a portion by the detection function 37a will be described. The "site detection process" executed by the detection function 37a is also referred to as "AL analysis".

For example, the detection function 37a extracts anatomical feature points from the voxel values included in the volume data in the volume data of the positioning image or the volume data of the image used for diagnosis. Then, the detection function 37a compares the three-dimensional position of the anatomical feature point in the information such as a textbook with the position of the feature point extracted from the volume data to obtain the feature point extracted from the volume data. Inaccurate feature points are removed from the inside to optimize the position of the feature points extracted from the volume data. As a result, the detection function 37a detects each part of the subject P included in the volume data. As an example, the detection function 37a first extracts anatomical feature points included in the volume data by using a supervised machine learning algorithm. Here, the above-mentioned supervised machine learning algorithm is constructed by using a plurality of supervised images in which correct anatomical feature points are manually arranged, and is used by, for example, a decision forest. Will be done.

Then, the detection function 37a optimizes the extracted feature points by comparing the model showing the three-dimensional positional relationship of the anatomical feature points in the body with the extracted feature points. Here, the above-mentioned model is constructed by using the above-mentioned teacher image, and for example, a point distribution model or the like is used. That is, the detection function 37a is a model in which the shape and positional relationship of the part, points unique to the part, etc. are defined based on a plurality of teacher images in which correct anatomical feature points are manually arranged, and the extracted features. By comparing with points, inaccurate feature points are removed and feature points are optimized.

Hereinafter, an example of the site detection process by the detection function 37a will be described with reference to FIGS. 4A, 4B, 5 and 6. 4A, 4B, 5 and 6 are diagrams for explaining an example of a portion detection process by the detection function 37a according to the first embodiment. In FIGS. 4A and 4B, the feature points are arranged two-dimensionally, but in reality, the feature points are arranged three-dimensionally. For example, the detection function 37a applies a supervised machine learning algorithm to the volume data to extract voxels regarded as anatomical feature points as shown in FIG. 4A (black dots in the figure). Then, the detection function 37a fits the position of the extracted voxels to a model in which the shape and positional relationship of the parts, points unique to the parts, etc. are defined, and as shown in FIG. 4B, among the extracted voxels. Inaccurate feature points are removed and only voxels corresponding to more accurate feature points are extracted.

Here, the detection function 37a assigns an identification code for identifying the feature points indicating the features of each part to the extracted feature points (voxels), and the identification code and the position (coordinate) information of each feature point. The information associated with and is attached to the image data and stored in the storage circuit 35. For example, as shown in FIG. 4B, the detection function 37a assigns identification codes such as C1, C2, and C3 to the extracted feature points (voxels). Here, the detection function 37a attaches an identification code to each of the data for which the detection process has been performed, and stores the data in the storage circuit 35. Specifically, the detection function 37a is performed from at least one of the projection data of the positioning image, the projection data collected under non-contrast, and the projection data collected in the state of being imaged by the contrast medium. The site of the subject contained in the reconstructed volume data is detected.

For example, as shown in FIG. 5, the detection function 37a attaches information associated with the coordinates of each voxel detected from the volume data (positioning in the figure) of the positioning image to the volume data to the storage circuit 35. Store in. As an example, the detection function 37a extracts the coordinates of the marking point from the volume data of the positioning image, and as shown in FIG. 5, "identification code: C1, coordinates (x ₁ , y ₁ , z ₁ )". , "Identification code: C2, coordinates (x ₂ , y _2,,
z ₂ ) ”etc. are stored in association with the volume data. Thereby, the detection function 37a can identify what kind of feature point is in which position in the volume data of the positioning image, and can detect each part such as an organ based on this information.

Further, as shown in FIG. 5, for example, the detection function 37a attaches information in which an identification code is associated with the coordinates of each voxel detected from the volume data (scan in the figure) of the diagnostic image to the volume data. Is stored in the storage circuit 35. Here, the detection function 37a is labeled from the volume data (contrast-enhanced Phase in the figure) imaged by the contrast medium and the volume data (non-contrast-enhanced Phase in the figure) not contrast-enhanced by the contrast medium in the scan. The coordinates of the points can be extracted and the identification code can be associated with the extracted coordinates.

As an example, the detection function 37a extracts the coordinates of the marking point from the volume data of the non-contrast phase from the volume data of the image for diagnosis, and as shown in FIG. 5, "identification code: C1, coordinates. _{(x '1, y' 1} , z '1) "," identification code: C2, coordinates (x' _2,
y _'2, z' ₂₎ "storing in association with such a volume data. In addition, detection function 3
7a, of the volume data of the image for diagnosis, and extracting coordinates of landmark from the volume data of the contrast Phase, as shown in FIG. 5, "identification code: C1, coordinates (x _'1, y' ₁ , z _'1) "," identification code: C2, coordinates _{(x' 2, y '2} , z' 2) "storing in association with such a volume data. Here, when the labeled points are extracted from the volume data of the contrast-enhanced Phase, the labeled points that can be extracted by being contrast-enhanced are included. For example, the detection function 37a can extract blood vessels and the like imaged by a contrast agent when extracting labeled points from the volume data of the contrast-enhanced Phase. Therefore, when the volume data of the contrast Phase, detection 37a, as shown in FIG. 5, the coordinates of the landmark, such as a blood vessel extracted by contrast _{(x '31, y' 31} , z '31) ~ such as the coordinate _{(x '34, y' 34} , z '34), the identification code C31 for identifying each vessel, C32, associates and C33 and C34.

As described above, the detection function 37a can identify what kind of marker point is in which position in the volume data of the positioning image or the diagnostic image, and based on this information, the organ or the like can be identified. Each site can be detected. For example, the detection function 37a detects the position of the target site by using the information of the anatomical positional relationship between the target site to be detected and the site around the target site. As an example, when the target site is the "lung", the detection function 37a acquires the coordinate information associated with the identification code indicating the characteristics of the lung, and also obtains the "ribs", "clavicle", and "heart". , The coordinate information associated with the identification code indicating the surrounding part of the "lung" such as the "diaphragm" is acquired. Then, the detection function 37a extracts the region of the "lung" in the volume data by using the information of the anatomical positional relationship between the "lung" and the surrounding portion and the acquired coordinate information.

For example, the detection function 37a is based on positional relationship information such as "lung apex: 2-3 cm above the clavicle" and "lung lower end: height of the 7th rib" and coordinate information of each part. As shown in, the region R1 corresponding to the “lung” in the volume data is extracted. That is, the detection function 37a extracts the coordinate information of the voxels in the region R1 in the volume data. The detection function 37a associates the extracted coordinate information with the part information, attaches it to the volume data, and stores it in the storage circuit 35. Similarly, as shown in FIG. 6, the detection function 37a can extract the region R2 and the like corresponding to the “heart” in the volume data.

Further, the detection function 37a detects a position included in the volume data based on a feature point that defines a position of the head, chest, or the like in the human body. Here, the positions of the head, chest, etc. in the human body can be arbitrarily defined. For example, if the area from the 7th cervical spine to the lower end of the lung is defined as the chest, the detection function 37a detects from the feature point corresponding to the 7th cervical spine to the feature point corresponding to the lower end of the lung as the chest. The detection function 37a can detect the site by various methods other than the method using the above-mentioned anatomical feature points. For example, the detection function 37a can detect a portion included in the volume data by a region expansion method based on a voxel value or the like.

The position matching function 37b collates the positions of the plurality of parts in the subject P included in the three-dimensional image data with the positions of the plurality of parts in the human body included in the virtual patient data. Here, the virtual patient data is information representing a standard position of each of a plurality of parts in the human body. That is, the position collation function 37b collates the site of the subject P with the position of the standard site, and stores the collation result in the storage circuit 35. For example, the position matching function 37b matches a virtual patient image in which a part of the human body is arranged at a standard position with the volume data of the subject P.

Here, first, a virtual patient image will be described. The virtual patient image is an image actually taken by X-ray of a human body having a standard physique according to multiple combinations of parameters related to physique such as age, adult / child, male / female, weight, and height. It is generated in advance and stored in the storage circuit 35. That is, the storage circuit 35 stores data of a plurality of virtual patient images according to the combination of the above-mentioned parameters. Here, anatomical feature points (feature points) are associated with and stored in the virtual patient image stored by the storage circuit 35. For example, the human body has a large number of anatomical features that can be relatively easily extracted from an image based on its morphological features and the like by image processing such as pattern recognition. The positions and arrangements of these many anatomical features in the body are roughly determined according to the physique such as age, adult / child, male / female, weight, and height.

In the virtual patient image stored by the storage circuit 35, a large number of these anatomical feature points are detected in advance, and the position data of the detected feature points is attached to the data of the virtual patient image together with the identification code of each feature point. Or it is associated and stored. FIG. 7 is a diagram showing an example of a virtual patient image stored by the storage circuit 35 according to the first embodiment. For example, as shown in FIG. 7, the memory circuit 35 has identification codes “V1”, “V2” and identification codes “V1”, “V2” for identifying anatomical feature points and feature points on a three-dimensional human body including a part such as an organ. A virtual patient image associated with "V3" or the like is stored.

That is, the storage circuit 35 stores the coordinates of the feature points in the coordinate space of the three-dimensional human body image in association with the corresponding identification code. As an example, the storage circuit 35 stores the coordinates of the corresponding feature points in association with the identification code “V1” shown in FIG. Similarly, the storage circuit 35 stores the identification code and the coordinates of the feature point in association with each other. In FIG. 7, only the lungs, heart, liver, stomach, kidneys, etc. are shown as organs, but in reality, the virtual patient image includes a larger number of organs, bones, vasculars, nerves, and the like. .. Further, in FIG. 7, only the feature points corresponding to the identification codes “V1”, “V2” and “V3” are shown, but in reality, a larger number of feature points are included.

The position matching function 37b matches the feature points in the volume data of the subject P detected by the detection function 37a with the feature points in the virtual patient image described above by using the identification code, and the coordinate space of the volume data. Is associated with the coordinate space of the virtual patient image. FIG. 8 is a diagram for explaining an example of collation processing by the position collation function 37b according to the first embodiment. Here, in FIG. 8, matching is performed using three sets of feature points to which identification codes indicating the same feature points are assigned between the feature points detected from the scanno image and the feature points detected from the virtual patient image. However, the embodiment is not limited to this, and matching can be performed using any set of feature points.

For example, as shown in FIG. 8, the position matching function 37b has the feature points indicated by the identification codes “V1”, “V2” and “V3” in the virtual patient image, and the identification codes “C1” and “C2” in the scanno image. When matching with the feature points indicated by "" and "C3", the coordinate space between the images is associated by performing coordinate transformation so that the positional deviation between the same feature points is minimized. For example, as shown in FIG. 8, the position matching function 37b has the same anatomically the same feature points “V1 (x1, y1, z1), C1 (X1, Y1, Z1)” and “V2 (x2, y2, z2). ), C2 (X2, Y2, Z2) ”,“ V3 (x3, y3, z3), C3 (X3, Y3, Z3) ”so as to minimize the total“ LS ”of the positional deviation below. Find the coordinate conversion matrix "H".

LS = ((X1, Y1, Z1) -H (x1, y1, z1))
+ ((X2, Y2, Z2) -H (x2, y2, z2))
+ ((X3, Y3, Z3) -H (x3, y3, z3))

The position matching function 37b can convert the scan range designated on the virtual patient image into the scan range on the positioning image by the obtained coordinate transformation matrix “H”. For example, the position matching function 37b uses the coordinate transformation matrix “H” to change the scan range “SRV” specified on the virtual patient image to the scan range “SRC” on the positioning image, as shown in FIG. Can be converted. FIG. 9 is a diagram showing an example of conversion of the scan range by coordinate conversion according to the first embodiment. For example, as shown on the virtual patient image of FIG. 9, when the operator sets the scan range “SRV” on the virtual patient image, the position matching function 37b uses the coordinate transformation matrix described above to set the scan. Convert the range "SRV" to the scan range "SRC" on the scanno image.

As a result, for example, the scan range "SRV" set to include the feature points corresponding to the identification code "Vn" on the virtual patient image is the identification code "Cn" corresponding to the same feature points on the scanno image. Is converted and set to the scan range "SRC" including. The coordinate transformation matrix "H" described above may be stored in the storage circuit 35 for each subject P and appropriately read out and used, or each time a scanno image is collected. It may be the case where it is calculated. As described above, according to the first embodiment, the virtual patient image is displayed for specifying the range at the time of presetting, and the position / range is planned on the virtual patient image, so that after the positioning image (scano image) is taken. , The position / range on the positioning image corresponding to the planned position / range can be automatically set numerically.

Return to FIG. The control function 37c determines the injection conditions of the contrast medium to be administered to the subject P. The control function 37c will be described in detail later.

The overall configuration of the medical information processing system 100 and the configuration of the X-ray CT apparatus 1 according to the first embodiment have been described above. Under such a configuration, the X-ray CT apparatus 1 according to the first embodiment includes anatomical feature points in a virtual patient image and components in a subject P in image data taken by a positioning scan or a contrast scan. By converting the designated scan position or scan range based on the collation result with the feature point based on the above, the accuracy of presetting the shooting position and the like is improved.

By the way, in the X-ray CT apparatus 1, a contrast agent may be administered to the subject P to perform a contrast scan. Here, in the X-ray CT apparatus according to the prior art, the amount of contrast medium is calculated using the height and weight of the patient, BMI, and the like. The internal circulation of contrast media also depends on the size of organs and blood volume. Therefore, it may not be possible to accurately determine the optimum amount of contrast medium only by factors such as height, weight, and BMI.

Therefore, the X-ray CT apparatus 1 according to the first embodiment detects the constituents of the subject P and administers the constituents to the subject P in a contrast scan based on the information related to the detected constituents. Determine the conditions for injecting the contrast medium. Such a function is realized by the control function 37c. Hereinafter, the control function 37c will be described.

The control function 37c determines the injection conditions of the contrast medium to be administered to the subject P in the contrast scan based on the information relating to the constituents. Here, the component is a scan target site of the contrast scan. For example, the control function 37c has information on the size of the organ of the subject P, information on the surface area of the organ of the subject P, information on the muscle mass of the subject P, and information on the subject P as information related to the constituents. At least one element of the information related to the fat amount of the subject P and the information related to the skeleton amount of the subject P is derived, and the amount of the contrast medium to be administered to the subject P is calculated as an injection condition. Here, the control function 37c derives information relating to the constituents in the subject from the detection result of the detection function 37a. That is, the control function 37c uses the detection result by the detection function 37a to obtain information on the size of the organ of the subject P, information on the surface area of the organ of the subject P, and information on the muscle mass of the subject P. At least one element of the information related to the fat amount of the subject P and the information related to the skeleton amount of the subject P is derived.

More specifically, the control function 37c obtains information on the size of the organ of the subject P by calculating the total number of pixels in the volume data corresponding to the organ of the subject P extracted by the detection function 37a. Derived. Further, the control function 37c relates to the surface area of the organ of the subject P by calculating the total number of pixels in the surface region (contour region) of the volume data corresponding to the organ of the subject P extracted by the detection function 37a. Derive information. Further, the control function 37c derives information relating to the skeleton amount of the subject P by calculating the total number of pixels in the volume data corresponding to the bone of the subject P extracted by the detection function 37a.

Further, when the control function 37c derives the information related to the muscle mass of the subject P and the information related to the fat mass of the subject P, the control function 37c executes the following processing. The control function 37c specifies a region excluding bones, organs, blood vessels, nerves, lumens, etc. detected by the detection function 37a from the volume data as a processing region. Then, the control function 37c specifies the volume data of the muscle region and the volume data of the fat region based on the pixel value (CT value) of the processing region. Here, the control function 37c identifies, for example, the pixels having a CT value in the range of 30 to 50 among the pixels in the processing region as the pixels of the volume data in the muscle region. Further, the control function 37c identifies, for example, the pixels having a CT value in the range of -100 to -50 among the pixels in the processing region as the pixels of the volume data in the fat region. Then, the control function 37c derives information related to the muscle mass of the subject P by calculating the number of pixels of the volume data of the muscle region. Further, the control function 37c derives information relating to the fat amount of the subject P by calculating the number of pixels of the volume data of the fat region. The control function 37c may derive information related to the muscle mass of the subject P and information related to the fat mass of the subject P without using the detection result of the detection function 37a. In such a case, the control function 37c specifies the volume data of the muscle region and the volume data of the fat region from the entire volume data without specifying the processing region, based on the pixel value (CT value).

In the following, a case where information related to the size of an organ is derived as information related to the constituents will be described. In addition, the case where the control function 37c derives the size of the liver will be described below. The control function 37c identifies the liver using, for example, the detection result by the detection function 37a, and derives the size of the liver.

Subsequently, the control function 37c calculates the amount of contrast medium to be administered to the subject P in the contrast scan based on the derived liver size. Here, the control function 37c calculates the amount of contrast medium with reference to the reference information. Reference information will be described with reference to FIG. FIG. 10 is a diagram for explaining the first embodiment. As shown in FIG. 10, the reference information stores information in which "organ type", "organ size", and "contrast agent amount" are associated with each other.

FIG. 10 shows a case where the “organ type” is the liver. The "organ size" shown in FIG. 10 indicates the range of the size of the organ. For example, in the "organ size", values such as "X1 to X2" and "X2 to X3" are stored. Here, X1 <X2 <X3 <X4 <X5 <X6. The "contrast medium amount" shown in FIG. 10 indicates the amount of contrast medium to be administered according to the size of the organ. For example, a value such as "0.90Y (ml)" or "Y (ml)" is stored in the "contrast agent amount". As an example, the reference information shown in FIG. 10 sets the amount of contrast medium to "0" when the size of the organ derived using the detection result by the detection function 37a is in the range of "X1 to X2". It is derived as ".90Y (ml)". Although FIG. 10 shows an example of reference information for each organ type, the embodiment is not limited to this. For example, the X-ray CT apparatus 1 may store basic information of the organ type according to the body weight or BMI of the subject P. Further, the X-ray CT apparatus 1 also stores information relating to the constituents and the amount of contrast medium in association with respect to the skeleton mass, muscle mass, fat mass, and body surface area of the subject P. .. Further, the X-ray CT apparatus 1 may store the reference information as a function.

FIG. 11 is a flowchart showing a processing procedure by the X-ray CT apparatus 1 according to the first embodiment. FIG. 11 shows a flowchart explaining the operation of the entire X-ray CT apparatus 1, and describes which step of the flowchart each component corresponds to.

Step S101 is a step realized by the input circuit 31. In step S101, the input circuit 31 accepts a selection of protocol presets. Step S102 is a step realized by the scan control circuit 33. In step S102, the scan control circuit 33 executes a positioning scan.

Step S103 is a step corresponding to the detection function 37a. This is a step in which the detection function 37a is realized by the processing circuit 37 calling and executing a predetermined program corresponding to the detection function 37a from the storage circuit 35. In step S103, the detection function 37a executes AL analysis on the positioning image.

Step S104 is a step corresponding to the position matching function 37b. This is a step in which the position matching function 37b is realized by the processing circuit 37 calling and executing a predetermined program corresponding to the position matching function 37b from the storage circuit 35. In step S104, the position collation function 37b collates the AL analysis result with the preset position.

Steps S105 to S110 are steps corresponding to the control function 37c. This is a step in which the control function 37c is realized by the processing circuit 37 calling and executing a predetermined program corresponding to the control function 37c from the storage circuit 35. In step S105, the control function 37c estimates the optimum value of the amount of contrast medium in the imaging site with reference to the reference value in the imaging site. For example, the control function 37c detects the constituents of the subject P and determines the injection conditions of the contrast agent to be administered to the subject P in the contrast scan based on the information related to the detected constituents.

Then, in step S106, the control function 37c compares the set amount of contrast medium with the estimated optimum amount of contrast medium. Subsequently, in step S107, the control function 37c determines whether or not the difference between the set optimum amount of the contrast medium and the estimated amount of the contrast medium is within the threshold range. Here, the control function 37c shifts to step S111 when it is determined that the difference between the set amount of contrast medium and the estimated optimum amount of contrast medium is within the threshold range (steps S107, Yes). On the other hand, when the control function 37c does not determine that the difference between the set amount of contrast medium and the estimated optimum amount of contrast medium is within the threshold range (steps S107 and No), in step S108, the contrast medium Notify the amount change. That is, when the control function 37c does not determine that the difference between the set amount of contrast medium and the estimated optimum amount of contrast medium is within the threshold range, the determined injection condition and the preset injection condition Is determined to be different. Then, the control function 37c notifies the operator that the determined injection condition and the preset injection condition are different.

Then, in step S109, the control function 37c determines whether or not the change in the amount of contrast medium has been accepted. Here, when the control function 37c does not determine that the change in the amount of contrast medium has been accepted (steps S109, No), the process proceeds to step S111. On the other hand, when the control function 37c determines that the change in the contrast medium amount has been accepted (steps S109, Yes), the control function 37c updates the setting of the contrast medium amount in step S110. For example, when the control function 37c receives a change from the injection condition preset by the operator to the determined injection condition, the control function 37c sets the determined injection condition in the contrast agent injector.

Step S111 is a step realized by the scan control circuit 33. In step S111, the scan control circuit 33 determines whether or not the execution of the contrast scan is accepted. Here, when the scan control circuit 33 does not determine that the execution of the contrast scan is accepted (steps S111 and No), the process proceeds to step S107. On the other hand, when the scan control circuit 33 determines that the execution of the contrast scan is accepted (steps S111, Yes), the scan control circuit 33 executes the contrast scan in step S112.

As described above, in the first embodiment, the injection conditions of the contrast medium to be administered to the subject P in the contrast scan are determined based on the information relating to the constituents. For example, in the X-ray CT apparatus 1 according to the first embodiment, even if the body weight of the subject P is heavy, when the contrast target is the liver and the size of the liver of the subject P is smaller than the reference value, Reduce the amount of contrast medium below the reference value. On the contrary, in the X-ray CT apparatus 1 according to the first embodiment, even if the body weight of the subject P is light, when the object to be imaged is the liver and the liver of the subject P is large, the amount of the contrast medium is used as a reference value. Will increase. Further, in the X-ray CT apparatus 1 according to the first embodiment, when the body shape of the subject P is large but the muscle mass is small and the fat mass is large, the amount of contrast medium is reduced or the skeleton is large and the muscle mass is large. If there is a large amount, the amount of contrast medium may be increased. This allows the operator to accurately determine the amount of contrast medium to be administered to the subject P. As a result, according to the first embodiment, it is possible to support highly accurate interpretation of a high-contrast image.

Further, as a result, according to the first embodiment, it is possible to support highly accurate image interpretation, and it is possible to suppress the dose of the contrast medium to the patient to the minimum necessary. As a result, the burden on the patient can be reduced.

In the first embodiment described above, the control function 37c notifies the operator that the determined injection condition and the preset injection condition are different, and the operator sets the injection condition in advance. Although it has been described that the determined injection condition is set in the contrast agent injector when the change to the determined injection condition is accepted, the embodiment is not limited to this. For example, the control function 37c sets the determined injection condition as a contrast medium without notifying the operator that the determined injection condition is different from the preset injection condition or accepting a change from the operator. It may be set in the injector.

(Second Embodiment)
In the first embodiment, a case where one element is derived as the information relating to the constituent and the amount of the contrast medium to be administered to the subject is calculated as the injection condition has been described. By the way, there may be a plurality of elements to be derived as information relating to the component. Therefore, in the second embodiment, a case where a plurality of elements are used as information relating to the constituents will be described.

The configuration of the X-ray CT apparatus according to the second embodiment is the same as the configuration of the X-ray CT apparatus 1 according to the first embodiment, except that some functions of the control function 37c are different. Therefore, the description other than the control function 37c will be omitted. When a plurality of elements are used, the control function 37c calculates the statistic of the amount of contrast medium to be administered to the subject calculated for each of the plurality of elements as the amount of contrast medium to be administered to the subject. FIG. 12 is a diagram for explaining the second embodiment.

FIG. 12 shows a case where "skeleton mass", "muscle mass", and "organ size" are derived as information related to the constituents, and the amount of contrast medium is calculated for each of the derived elements. For example, the control function 37c calculates the amount of contrast medium as "1.10Y (ml)" based on the derived "skeleton amount", and sets the amount of contrast medium to "0.90Y (ml)" based on the derived "muscle mass". The amount of contrast medium is calculated as "0.90Y (ml)" based on the derived "organ size". Subsequently, the control function 37c calculates a statistic of the amount of contrast medium to be administered to the calculated subject P. For example, the control function 37c calculates the average value of each contrast medium amount and calculates it as the contrast medium amount to be administered to the subject P. In the example shown in FIG. 12, the control function 37c calculates the amount of contrast medium to be administered as "0.97Y (ml)". The control function 37c may calculate the average value after weighting each element.

As described above, in the second embodiment, the X-ray CT apparatus 1 calculates the amount of contrast medium to be administered to the subject P by using a plurality of elements as information relating to the constituents. This makes it possible to more accurately determine the injection conditions of the contrast medium to be administered to the subject P according to the second embodiment.

Also in the second embodiment, the control function 37c notifies the operator that the determined injection condition and the preset injection condition are different, and determines from the injection condition preset by the operator. Although it has been described that the determined injection condition is set in the contrast medium injector when the change to the injection condition is accepted, the embodiment is not limited to this. For example, the control function 37c sets the determined injection condition as a contrast medium without notifying the operator that the determined injection condition is different from the preset injection condition or accepting a change from the operator. It may be set in the injector.

(Third Embodiment)
In the first and second embodiments described above, the control function 37c determines the amount of contrast medium based on the information relating to the constituents. However, when the blood flow velocity is high, it may not be possible to image the contrast medium even if the contrast medium is injected. Therefore, in the third embodiment, a case where at least one of the concentration of the contrast medium to be administered to the subject and the injection rate is calculated as the injection condition will be described.

The configuration of the X-ray CT apparatus according to the third embodiment is the same as the configuration of the X-ray CT apparatus 1 according to the first embodiment, except that some functions of the control function 37c are different. .. Therefore, the description other than the control function 37c will be omitted.

For example, the control function 37c according to the third embodiment is a contrast medium to be administered to the subject P as an injection condition based on the scan condition and the information related to the heart size derived as the information related to the component. Calculate at least one of the agent concentration and injection rate. Here, for example, the control function 37c derives the ejection amount and calculates the blood flow velocity by performing a helical scan so as to include states of different cardiac phases. Then, the control function 37c increases the contrast medium concentration so as to inject the contrast medium at the same speed as the blood flow velocity, for example, when the amount of contrast medium required for the organ to be contrast-enhanced is insufficient. Pop up comments to increase injection speed. Then, the control function 37c increases the concentration of the contrast medium or increases the injection rate when the operator accepts a change in the injection conditions. The control function 37c may calculate the ejection amount from the systolic blood pressure and the diastolic blood pressure. Thereby, according to the third embodiment, it is possible to generate a reconstructed image having a clear contrast even when the blood flow velocity is high.

(Other embodiments)
By the way, although the first embodiment to the third embodiment have been described so far, they may be implemented in various different forms other than the above-mentioned first embodiment to the third embodiment. ..

The control function 37c acquires information indicating the sensitivity of the subject P to the contrast medium, and determines the injection conditions of the contrast medium to be administered to the subject P with reference to the acquired information. For example, the control function 37c acquires renal function information such as the presence or absence of contrast medium allergy and blood creatine level from HIS. Then, the control function 37c calls attention to the operator when the subject P is allergic to the contrast medium or when the creatine value is equal to or higher than a predetermined threshold value. FIG. 13 is a diagram for explaining other embodiments.

FIG. 13 shows a case where the subject P is allergic to the contrast medium. For example, the control function 37c pops up, for example, "[Caution] I have a contrast agent allergy." In order to call the operator's attention. Further, the control function 37c may stop the injection of the contrast medium into the contrast medium injector when the operator is alerted. Alternatively, the control function 37c limits the amount of contrast medium to an injection of a preset amount or less, which is set in advance, when receiving an instruction for contrast imaging from the operator when calling attention to the operator. It may be.

In addition, the control function 37c may require the attending physician to approve the change of the injection condition of the contrast medium. For example, the control function 37c generates an email prompting to approve the change in the contrast medium injection condition and sends it to the attending physician. Alternatively, the control function 37c contacts the doctor's in-hospital extension or the like to urge the doctor to approve the change in the contrast medium injection condition. In such a case, the control function 37c changes the contrast medium injection conditions when approval is obtained from the attending physician. In other words, the control function 37c does not change the amount of contrast medium set in the contrast medium injector until approval is obtained from the attending physician.

In addition, as a result of AL analysis, when the kidney or lung is present on only one side or when the information on the size of the organ is less than a predetermined reference value, a difference from the standard human body model occurs. In such a case, the control function 37c suppresses the injection condition of the contrast medium to be administered to the subject P to less than a predetermined threshold value. That is, the control function 37c derives information on the size of the organ as information on the constituents, and when the information on the size of the organ is equal to or less than a predetermined reference value, or at least one of the organs. When the portion is deleted, the injection condition of the contrast medium to be administered to the subject P is suppressed to less than a predetermined threshold value. In addition, the X-ray CT apparatus 1 displays in a recognizable state that the organ is deleted on the virtual patient. For example, fill or annotate the missing organ.

Further, the control function 37c may store the determined injection conditions in a predetermined storage unit when the determined injection conditions are used for the contrast scan. For example, the X-ray CT apparatus 1 stores the contrast medium injection conditions in HIS or RIS. Then, the X-ray CT apparatus 1 utilizes the contrast agent injection condition at the time of the next imaging. Further, the X-ray CT apparatus 1 may output the determined injection conditions to an external apparatus.

In the above-described embodiment, the detection function 37a has been described as performing AL analysis using the volume data of the positioning image or the volume data of the image used for diagnosis, but the embodiment is limited to this. It's not something. For example, the detection function 37a may perform AL analysis using a two-dimensional positioning image. Further, the detection function 37a may execute the AL analysis by using the image used for the diagnosis of the same subject imaged in the past by the own device. Further, the detection function 37a may execute the AL analysis using the medical image data of the same subject imaged by another device.

Further, in the above-described embodiment, the X-ray CT apparatus has been described as an example of the medical image imaging apparatus, but the embodiment is not limited to this. For example, the medical image imaging device may be an X-ray diagnostic device, an ultrasonic diagnostic device, an MRI (Magnetic Resonance Imaging) device, or the like.

Further, in the above-described embodiment, the medical image imaging apparatus has been described as performing a process of determining the injection conditions of the contrast medium to be administered to the subject P, but the embodiment is not limited to this. For example, a medical image processing device or the like may be provided as a management device, and the management device may execute a process of determining the injection conditions of the contrast medium to be administered to the subject P. That is, the management device acquires the image data of the subject. Then, the management device detects each of the plurality of parts of the subject in the image data. Subsequently, the management device derives information relating to the constituents in the subject from the detection result. Then, the management device determines the injection conditions of the contrast medium to be administered to the subject in the contrast scan based on the information related to the components.

The word "processor" used in the above description means, for example, a CPU (Central Preprocess Unit), a GPU (Graphics Processing Unit), an integrated circuit for a specific application (ASIC), or a programmable logic device (for example, a programmable logic device). Simple Programmable Logic Device (SPLD), Complex Programmable Logic Device (CPLD), and Field Programmable Gate Array (Field Programmable)
It means a circuit such as Gate Array: FPGA)). The processor realizes the function by reading and executing the program stored in the storage circuit. Instead of storing the program in the storage circuit, the program may be directly embedded in the circuit of the processor. In this case, the processor realizes the function by reading and executing the program embedded in the circuit. It should be noted that each processor of the present embodiment is not limited to the case where each processor is configured as a single circuit, and a plurality of independent circuits may be combined to form one processor to realize its function. good. Further, the plurality of components in FIG. 2 may be integrated into one processor to realize the function.

Further, each component of each device shown in the above-described embodiment is a functional concept, and does not necessarily have to be physically configured as shown in the figure. That is, the specific form of distribution / integration of each device is not limited to the one shown in the figure, and all or part of the device is functionally or physically dispersed / physically distributed in any unit according to various loads and usage conditions. Can be integrated and configured. Further, each processing function performed by each device may be realized by a CPU and a program analyzed and executed by the CPU, or may be realized as hardware by wired logic.

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

As described above, according to each embodiment, it is possible to accurately determine the injection conditions of the contrast medium to be administered to the subject.

Although some embodiments of the present invention have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the gist of the invention. These embodiments and modifications thereof are included in the scope and gist of the invention, as well as in the scope of the invention described in the claims and the equivalent scope thereof.

1 X-ray CT device 37 Processing circuit 37a Detection function 37c Control function

Claims (11)

The acquisition unit that acquires the image data of the subject,
A detection unit that detects a plurality of parts of the subject in the image data, and a detection unit.
A derivation unit that derives information related to the constituents in the subject from the detection results of the detection unit, and a derivation unit.
It is provided with a control unit that determines the injection conditions of the contrast medium to be administered to the subject in the contrast scan based on the information related to the components .
When the control unit uses a plurality of elements derived as information relating to the component, the control unit administers to the subject a statistic of the amount of contrast medium to be administered to the subject calculated for each of the plurality of elements. calculated as a contrast agent amount, the medical image diagnostic apparatus. The derivation unit includes information on the size of the organ of the subject, information on the surface area of the organ of the subject, information on the muscle mass of the subject, and information on the muscle mass of the subject as information relating to the constituent. information relating to fat mass, that issues guiding the plurality of elements from among the information relating to skeletal mass of the subject, a medical image diagnostic apparatus according to claim 1. The medical image diagnostic apparatus according to claim 1 or 2 , wherein the component is a scan target site of the contrast scan. The control unit further, based on the scan condition and the information related to the size of the heart derived as the information related to the component, as the injection condition, the concentration and injection of the contrast medium to be administered to the subject. The medical diagnostic imaging apparatus according to any one of claims 1 to 3 , which calculates at least one of the speeds. Any of claims 1 to 4 , wherein the control unit acquires information indicating sensitivity to the contrast medium for the subject, and determines the injection conditions of the contrast medium to be administered to the subject with reference to the information. The medical diagnostic imaging apparatus described in one. The control unit derives information related to the size of the organ as information related to the constituent, and when the information related to the size of the organ is equal to or less than a predetermined reference value, or at least a part of the organ. The medical image diagnostic apparatus according to any one of claims 1 to 5 , wherein the injection condition of the contrast medium to be administered to the subject is suppressed to less than a predetermined threshold value when is deleted. The medical diagnostic imaging apparatus according to any one of claims 1 to 6 , wherein the control unit sets the determined injection conditions in the contrast medium injector. The medical image diagnostic apparatus according to any one of claims 1 to 6 , wherein the control unit further notifies the operator when the determined injection condition and the preset injection condition are different. Wherein the control unit from the preset injection conditions from the operator, if accepted the change to the injection conditions with the determined set injection conditions the determined contrast agent injector, in claim 8 The medical diagnostic imaging apparatus described. The medical image diagnostic apparatus according to any one of claims 1 to 9 , wherein the control unit stores the determined injection conditions in a predetermined storage unit when the determined injection conditions are used for the contrast scan. .. The acquisition unit that acquires the image data of the subject,
A detection unit that detects a plurality of parts of the subject in the image data, and a detection unit.
A derivation unit that derives information related to the constituents in the subject from the detection results of the detection unit, and a derivation unit.
It is provided with a control unit that determines the injection conditions of the contrast medium to be administered to the subject in the contrast scan based on the information related to the components .
When the control unit uses a plurality of elements derived as information relating to the component, the control unit administers to the subject a statistic of the amount of contrast medium to be administered to the subject calculated for each of the plurality of elements. calculated as a contrast agent amount, the management apparatus.

Images