JP2018011659A - Magnetic resonance imaging apparatus and installation method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a magnetic resonance imaging apparatus that can be used in a stable state from the operation start, and an installation method.SOLUTION: A magnetic resonance imaging apparatus includes a selection part and an execution part. The selection part selects a sequence executed in a pre-operation for stabilizing a state of the apparatus from a plurality of sequences based on information on cooling of the apparatus in the installation place. The execution part executes the selected sequence in a pre-operation.SELECTED DRAWING: Figure 1

Description

  Embodiments described herein relate generally to a magnetic resonance imaging apparatus and an installation method.

  The nuclear spin of a subject placed in a static magnetic field is magnetically excited with a RF frequency (Larmor frequency) RF (Radio Frequency) pulse, and an image is re-created from the MR (Magnetic Resonance) signal generated by this excitation. There is a magnetic resonance imaging (MRI) apparatus that is configured.

  Such a magnetic resonance imaging apparatus is subjected to various processes during installation (installation) so that it can be used in a stable state from the start of operation.

JP-A-10-328160

  The problem to be solved by the present invention is to provide a magnetic resonance imaging apparatus and installation method that can be used in a stable state from the start of operation.

  The magnetic resonance imaging apparatus according to the embodiment includes a selection unit and an execution unit. A selection part selects the sequence performed at the time of prior operation in order to stabilize the state of the said own apparatus from several sequences based on the information regarding the cooling of the own apparatus in an installation place. The execution unit executes the selected sequence during the preliminary operation.

FIG. 1 is a functional block diagram showing the configuration of the MRI apparatus according to the first embodiment. FIG. 2 is a diagram illustrating an example of a data structure of a database for sequence acquisition during preliminary operation. FIG. 3 is a flowchart showing the flow of the pre-operation process according to the first embodiment. FIG. 4 is a functional block diagram showing the configuration of the MRI apparatus according to the second embodiment. FIG. 5 is a flowchart showing a flow of pre-operation processing according to the second embodiment. FIG. 6 is a diagram for explaining a second modification of the second embodiment. FIG. 7 is a flowchart showing a flow of pre-operation processing according to the third embodiment.

  Hereinafter, a magnetic resonance imaging apparatus (hereinafter referred to as “MRI apparatus” as appropriate) according to an embodiment will be described with reference to the drawings. Note that the embodiments are not limited to the following embodiments. Moreover, each embodiment and each modification can be combined suitably.

(First embodiment)
FIG. 1 is a functional block diagram showing the configuration of the MRI apparatus 100 according to the first embodiment. As shown in FIG. 1, the MRI apparatus 100 includes a static magnetic field magnet 1, a gradient magnetic field coil 2, a gradient magnetic field power source 3, a transmission coil 4, a transmission circuit 5, a reception coil 6, a reception circuit 7, The bed 8 includes an input circuit 9, a display 10, a storage circuit 11, processing circuits 12 to 15, a temperature sensor 20, and a flow rate sensor 21. The MRI apparatus 100 does not include the subject S (for example, a human body) shown in FIG. Moreover, the structure shown in FIG. 1 is only an example.

  A cooling system 200 is connected to the gradient coil 2 of the MRI apparatus 100 via a cooling pipe. The cooling system 200 is provided from a hospital where the MRI apparatus 100 is installed (installed).

  The static magnetic field magnet 1 is formed in a hollow, substantially cylindrical shape (including one having a cross section perpendicular to the central axis of the cylinder is elliptical), and generates a uniform static magnetic field in the imaging space formed on the inner peripheral side. Let For example, the static magnetic field magnet 1 is realized by a permanent magnet, a superconducting magnet, or the like.

  The gradient magnetic field coil 2 is formed in a hollow, substantially cylindrical shape (including one having a cross section perpendicular to the central axis of the cylinder is elliptical), and is disposed on the inner peripheral side of the static magnetic field magnet 1. The gradient coil 2 has three coils that generate gradient magnetic fields along the x-axis, y-axis, and z-axis that are orthogonal to each other. Here, the x axis, the y axis, and the z axis constitute an apparatus coordinate system unique to the MRI apparatus 100. For example, the x-axis direction is set to the vertical direction, and the y-axis direction is set to the horizontal direction. The direction of the z axis is set to be the same as the direction of the magnetic flux of the static magnetic field generated by the static magnetic field magnet 1. As will be described later, the position of the gradient coil 2 is fixed by a resin such as an epoxy resin.

  The gradient magnetic field power supply 3 individually supplies current to each of the three coils included in the gradient magnetic field coil 2 to generate gradient magnetic fields along the x axis, the y axis, and the z axis in the imaging space. By appropriately generating gradient magnetic fields along the x-axis, y-axis, and z-axis, it is possible to generate gradient magnetic fields along the readout direction, the phase encoding direction, and the slice direction that are orthogonal to each other. Here, the axes along the readout direction, the phase encoding direction, and the slice direction constitute a logical coordinate system for defining a slice region or a volume region to be imaged. Hereinafter, the gradient magnetic field along the readout direction is referred to as a readout gradient magnetic field, the gradient magnetic field along the phase encoding direction is referred to as a phase encoding gradient magnetic field, and the gradient magnetic field along the slice direction is referred to as a slice gradient magnetic field. .

  Each gradient magnetic field is superimposed on the static magnetic field generated by the static magnetic field magnet 1 and used to give spatial position information to a magnetic resonance (MR) signal. Specifically, the readout gradient magnetic field gives the MR signal position information along the readout direction by changing the frequency of the MR signal in accordance with the position in the readout direction. Further, the phase encoding gradient magnetic field changes the phase of the MR signal along the phase encoding direction, thereby giving position information in the phase encoding direction to the MR signal. The slice gradient magnetic field is used to determine the direction, thickness, and number of slice areas when the imaging area is a slice area, and according to the position in the slice direction when the imaging area is a volume area. By changing the phase of the MR signal, position information along the slice direction is given to the MR signal.

  The transmission coil 4 is formed in a hollow, substantially cylindrical shape (including one having a cross section perpendicular to the central axis of the cylinder is elliptical), and is disposed inside the gradient magnetic field coil 2. The transmission coil 4 applies an RF (Radio Frequency) pulse output from the transmission circuit 5 to the imaging space.

  The transmission circuit 5 outputs an RF pulse corresponding to the Larmor frequency to the transmission coil 4. For example, the transmission circuit 5 includes an oscillation circuit, a phase selection circuit, a frequency conversion circuit, an amplitude modulation circuit, and an RF amplification circuit. The oscillation circuit generates an RF pulse having a resonance frequency unique to a target nucleus placed in a static magnetic field. The phase selection circuit selects the phase of the RF pulse output from the oscillation circuit. The frequency conversion circuit converts the frequency of the RF pulse output from the phase selection circuit. The amplitude modulation circuit modulates the amplitude of the RF pulse output from the frequency conversion circuit according to, for example, a sinc function. The RF amplification circuit amplifies the RF pulse output from the amplitude modulation circuit and outputs the amplified RF pulse to the transmission coil 4.

  The receiving coil 6 is disposed inside the gradient coil 2 and receives an MR signal emitted from the subject S due to the influence of the RF pulse. When receiving the MR signal, the receiving coil 6 outputs the received MR signal to the receiving circuit 7.

  The receiving circuit 7 generates MR signal data based on the MR signal output from the receiving coil 6, and outputs the generated MR signal data to the processing circuit 13. For example, the reception circuit 7 includes a selection circuit, a preamplifier circuit, a phase detection circuit, and an analog / digital conversion circuit. The selection circuit selectively inputs the MR signal output from the receiving coil 6. The pre-amplifier circuit amplifies the MR signal output from the selection circuit. The phase detection circuit detects the phase of the MR signal output from the preceding amplifier. The analog-digital conversion circuit generates MR signal data by converting the analog signal output from the phase detector into a digital signal, and outputs the generated MR signal data to the processing circuit 13.

  Here, an example in which the transmission coil 4 applies an RF pulse and the reception coil 6 receives an MR signal will be described, but the forms of the transmission coil and the reception coil are not limited thereto. For example, the transmission coil 4 may further have a reception function for receiving MR signals. Moreover, the receiving coil 6 may further have a transmission function for applying an RF magnetic field. When the transmission coil 4 has a reception function, the reception circuit 7 also generates MR signal data from the MR signal received by the transmission coil 4. When the reception coil 6 has a transmission function, the transmission circuit 5 also outputs an RF pulse to the reception coil 6.

  The bed 8 includes a top plate 8a on which the subject S is placed, and when the subject S is imaged, the top plate 8a enters the imaging space formed inside the static magnetic field magnet 1 and the gradient magnetic field coil 2. Insert. For example, the bed 8 is installed so that the longitudinal direction is parallel to the central axis of the static magnetic field magnet 1.

  The input circuit 9 receives various instructions and various information input operations from the operator. For example, the input circuit 9 is realized by a trackball, a switch button, a mouse, a keyboard, a touch panel, or the like. The input circuit 9 is connected to the processing circuit 15, converts an input operation received from the operator into an electrical signal, and outputs the electrical signal to the processing circuit 15.

  The display 10 displays various information and various images. For example, the display 10 is realized by a liquid crystal monitor, a CRT (Cathode Ray Tube) monitor, a touch panel, or the like. The display 10 is connected to the processing circuit 15, converts various information and various image data sent from the processing circuit 15 into electric signals for display, and outputs them.

  The storage circuit 11 stores various data. For example, the storage circuit 11 stores MR signal data and image data for each subject S. For example, the storage circuit 11 is realized by a semiconductor memory device such as a RAM (Random Access Memory) or a flash memory, a hard disk, an optical disk, or the like.

  The storage circuit 11 stores a pre-operation sequence acquisition database (Data Base) 11a. Details of the pre-operation sequence acquisition database 11a will be described later.

  The processing circuit 12 has a bed control function 12a. For example, the processing circuit 12 is realized by a processor. The couch control function 12 a is connected to the couch 8, and controls the operation of the couch 8 by outputting a control electric signal to the couch 8. For example, the bed control function 12a receives an instruction from the operator to move the top plate 8a in the longitudinal direction, the up-down direction, or the left-right direction via the input circuit 9, and moves the top plate 8a according to the received instruction. The drive mechanism of the top board 8a which the bed 8 has is operated.

  The processing circuit 13 has an execution function 13a. For example, the processing circuit 13 is realized by a processor. The execution function 13a executes various protocols. Specifically, the execution function 13 a executes various protocols by driving the gradient magnetic field power supply 3, the transmission circuit 5, and the reception circuit 7 based on the sequence execution data output from the processing circuit 15.

  Here, the sequence execution data is information defining a protocol indicating a procedure for collecting MR signal data. Specifically, the sequence execution data includes the timing at which the gradient magnetic field power supply 3 supplies current to the gradient coil 2 and the magnitude (intensity) of the supplied current, and the RF pulse that the transmission circuit 5 supplies to the transmission coil 4. This is information defining current intensity, supply timing, detection timing at which the receiving circuit 7 detects the MR signal, and the like. This sequence execution data is also simply referred to as a sequence (pulse sequence).

  The execution function 13a receives MR signal data from the receiving circuit 7 as a result of executing various sequences, and stores the received MR signal data in the storage circuit 11. The execution function 13a is an example of an execution unit. The set of MR signal data received by the execution function 13a is arranged two-dimensionally or three-dimensionally according to the position information given by the readout gradient magnetic field, phase encoding gradient magnetic field, and slice gradient magnetic field. Thus, it is stored in the memory circuit 11 as data constituting the k space.

  The processing circuit 14 has an image generation function 14a. For example, the processing circuit 14 is realized by a processor. The image generation function 14 a generates an image based on the MR signal data stored in the storage circuit 11. Specifically, the image generation function 14a reads the MR signal data stored in the storage circuit 11 by the execution function 13a, and performs post-processing, that is, reconstruction processing such as Fourier transform, on the read MR signal data. Generate. Further, the image generation function 14 a stores the image data of the generated image in the storage circuit 11.

  The processing circuit 15 performs overall control of the MRI apparatus 100 by controlling each component included in the MRI apparatus 100. For example, the processing circuit 15 is realized by a processor. For example, the processing circuit 15 has a selection function 15a. The selection function 15a stabilizes the state of the MRI apparatus 100 from among a plurality of sequences based on information on cooling water supplied from the cooling system 200 at the installation site of the MRI apparatus 100 to cool the MRI apparatus 100. Therefore, the sequence to be executed during the pre-operation is selected. Details of the selection function 15a will be described later. The selection function 15a is an example of a selection unit.

  Here, for example, the selection function 15a that is a component of the processing circuit 15 is stored in the storage circuit 11 in the form of a program that can be executed by a computer. The processing circuit 15 reads the program corresponding to the selection function 15a from the storage circuit 11 and executes the read program, thereby realizing the selection function 15a corresponding to the program. In other words, the processing circuit 15 that has read the program has the selection function 15a shown in the processing circuit 15 of FIG.

  The term “processor” used in the above description is, for example, a central processing unit (CPU), a graphics processing unit (GPU), an application specific integrated circuit (ASIC), a programmable logic device (for example, It means circuits such as a simple programmable logic device (SPLD), a complex programmable logic device (CPLD), and a field programmable gate array (FPGA). Instead of storing the program in the storage circuit 11, the program may be directly incorporated in the processor circuit. In this case, the processor realizes the function by reading and executing the program incorporated in the circuit.

  Note that some or all of the processing circuit 12, the processing circuit 13, the processing circuit 14, and the processing circuit 15 may be realized by the same processor.

  The temperature sensor 20 is provided in the vicinity of the gradient magnetic field coil 2, detects the temperature of the cooling water flowing through the gradient magnetic field coil 2, and outputs a signal indicating the detected temperature to the processing circuit 15.

  The flow sensor 21 is provided in the vicinity of the gradient magnetic field coil 2, detects the flow rate of the cooling water flowing through the gradient magnetic field coil 2 per unit time (for example, 1 second or 1 minute), and processes a signal indicating the detected flow rate. Output to the circuit 15. The flow rate of the cooling water per unit time indicates the flow rate of the cooling water. That is, the signal output from the flow sensor 21 according to the present embodiment indicates the flow rate of the cooling water.

  The cooling system 200 allows water to flow into the gradient magnetic field coil 2 by flowing water adjusted to a predetermined temperature (for example, 20 degrees, 18 degrees, etc.) through the cooling pipe toward the gradient magnetic field coil 2. . Further, when the water that has flowed through the gradient magnetic field coil 2 returns via the cooling pipe, the cooling system 200 cools the returned water to a predetermined temperature, and then directs it toward the gradient magnetic field coil 2. Flow through the cooling pipe again. Thus, the cooling system 200 cools the gradient magnetic field coil 2 by circulating water between the gradient magnetic field coil 2.

  The overall configuration of the MRI apparatus 100 according to the embodiment has been described above.

  Here, each of the above-described three coils constituting the gradient magnetic field coil 2 of the MRI apparatus 100 is disposed in each of the X, Y, and Z layers. The cavity of each layer is filled with resin such as epoxy resin, and the position of the coil is fixed by this resin. When a current flows through the coil of each layer, the coil vibrates and a minute gap is formed between the coil and the resin. For example, the size of the gap increases as the width of the current flowing through the coil increases.

  Here, in imaging for obtaining one image, the image quality deteriorates when the size of the gap is not constant, but the image quality does not deteriorate when the size of the gap is constant.

  The size of this gap is related to the size of the MT (Maxwell term) value in the gradient magnetic field. For example, the larger the measured MT value, the larger the size of the gap.

  Here, when the MRI apparatus is continuously used for a certain period, the size of the gap between the coil and the resin may converge to a certain size. In this case, in the imaging for obtaining one image, the size of the gap is constant, so that the image quality does not deteriorate. When the size of the gap between the coil and the resin is converged to a constant size, the MT value is also converged to a constant value.

  However, immediately after the MRI apparatus is installed in a hospital or the like and started to be used, the size of the gap between the coil and the resin has not converged to a certain size, so the image quality of the obtained image is degraded. May end up.

  Therefore, the MRI apparatus 100 according to the present embodiment is configured to be used in a stable state from the start of operation, as will be described below. In addition, the stable state here refers to a state in which, for example, the size of the gap between the coil and the resin converges to a certain size, and deterioration of the image quality of the obtained image is suppressed. . In other words, the stable state is a state where the MT value converges to a constant value.

  Next, an example of the data structure of the pre-operation sequence acquisition database 11a shown in FIG. 1 will be described. In the following description, “pre-operation sequence acquisition database 11a” is abbreviated as “database 11a”. The database 11a is associated with the temperature and flow rate of the cooling water supplied from the hospital cooling system 200 in which the MRI apparatus 100 is installed, and an ID (Identification) that uniquely identifies the sequence executed during the preliminary operation. Registered. FIG. 2 is a diagram illustrating an example of the data structure of the database 11a. As shown in the example of FIG. 2, in the database 11a, a plurality of records in which values are registered in the items of “temperature”, “flow velocity”, “ID”, and “execution time” are registered.

  In the “temperature” item, the temperature range of the cooling water supplied from the cooling system 200 is registered. In the “flow velocity” item, the range of the flow velocity of the cooling water supplied from the cooling system 200 is registered. In the “ID” item, a temperature range registered in the “temperature” item and an ID for uniquely identifying a sequence corresponding to the flow velocity range registered in the “flow rate” item are registered. ing. In the “execution time” item, a time for executing the sequence indicated by the ID registered in the “ID” item is registered. The temperature range registered in the “temperature” item and the flow velocity range registered in the “flow rate” item are examples of information related to cooling of the MRI apparatus 100.

  For example, the first record shown in the example of FIG. 2 has an ID “AA” when the temperature of the cooling water is “T1” or more and less than “T2” and the flow velocity is “V1” or more and less than “V2”. This indicates that the sequence indicated by is executed for “t1” minutes during the preliminary operation of the MRI apparatus 100.

  Further, the second record shown in the example of FIG. 2 includes an ID “AB” when the temperature of the cooling water is “T1” or more and less than “T2” and the flow velocity is “V2” or more and less than “V3”. This indicates that the sequence indicated by is executed for “t2” minutes during the preliminary operation of the MRI apparatus 100.

  The third record shown in the example of FIG. 2 includes ID “AC” when the temperature of the cooling water is not less than “T1” and less than “T2” and the flow rate is not less than “V3” and less than “V4”. This indicates that the sequence indicated by is executed for “t3” minutes during the preliminary operation of the MRI apparatus 100.

  The same applies to other records (for example, a record when the temperature of the cooling water is not less than “T2” and less than “T3”). The temperature “T3” is higher than the temperature “T2”, and the temperature “T2” is higher than the temperature “T1”. Further, the flow velocity “V4” is larger than the flow velocity “V3”, the flow velocity “V3” is larger than the flow velocity “V2”, and the flow velocity “V2” is larger than the flow velocity “V1”.

  In the first embodiment, the sequence indicated by the ID registered in the “ID” item of the database 11a is the same type of sequence, although the parameter values are different. Examples of such a sequence include an EPI (Echo Planar Imaging) sequence (EPI sequence). For example, the sequences indicated by ID “AA”, ID “AB”, and ID “AC” are the same type of sequence, for example, an EPI sequence. However, the EPI sequence indicated by the ID “AA”, the EPI sequence indicated by the ID “AB”, and the EPI sequence indicated by the ID “AC” are respectively the repetition time (TR: Repetition Time) and the echo time (TE: Echo Time). ), Parameter values of various parameters such as the magnitude of current supplied to the gradient coil 2 are different. Therefore, the load of the gradient coil 2 due to the execution of the EPI sequence indicated by the ID “AA”, the load of the gradient coil 2 due to the execution of the EPI sequence indicated by the ID “AB”, and the ID “AC” The load on the gradient coil 2 due to the execution of the EPI sequence shown in FIG. A load here refers to the fluctuation | variation of the gradient magnetic field which the gradient magnetic field coil 2 generate | occur | produces, for example. The load increases as the value of the current flowing through the gradient coil 2 increases. Further, as the load increases, the vibration of the gradient coil 2 increases. Hereinafter, the sequence with a large load refers to a sequence that causes the gradient coil 2 to vibrate relatively large by being executed. A sequence with a small load refers to a sequence that, when executed, vibrates the gradient coil 2 relatively small.

  For example, when the temperature of the cooling water is low, the temperature of the heat generated from the gradient coil 2 is less likely to exceed the allowable temperature of the MRI apparatus 100 even if a sequence with a large load is executed. For this reason, for each record in the database 11a, if the flow velocity registered in the “flow velocity” item is the same, the load increases as the temperature of the coolant registered in the “temperature” item decreases. The ID indicating the EPI sequence in which the parameter value of the parameter is set is registered in the item “ID”. For example, the gradient magnetic field by executing the EPI sequence indicated by the ID registered in the “ID” item of the record in which the temperature of the cooling water registered in the “temperature” item is not less than “T1” and less than “T2”. The load of the coil 2 is executed by the EPI sequence indicated by the ID registered in the “ID” item of the record when the temperature of the cooling water registered in the “temperature” item is not less than “T2” and less than “T3”. It tends to be larger than the load of the gradient magnetic field coil 2 due to being performed.

  Further, when the flow rate of the cooling water is large (fast), the temperature of the heat generated from the gradient coil 2 is less likely to exceed the allowable temperature of the MRI apparatus 100 even if a sequence with a large load is executed. For this reason, for each record in the database 11a, an ID indicating an EPI sequence in which parameter values of various parameters are set so that the load increases as the flow rate of the coolant registered in the “flow rate” item increases. Is registered in the item. For example, when the temperature of the cooling water registered in the “temperature” item is the same (for example, when “T1” or more and less than “T2”), the following is true for a plurality of EPI sequences with different parameter values: I can say that. For example, the EPI sequence indicated by the ID “AB” registered in the “ID” item of the record in which the flow velocity of the coolant registered in the “flow rate” item is “V2” or more and less than “V3” is executed. The load of the gradient coil 2 by the ID is “ID” registered in the “ID” item of the record when the flow rate of the coolant registered in the “flow rate” item is “V1” or more and less than “V2”. It is larger than the load of the gradient coil 2 due to the execution of the EPI sequence shown in FIG. Further, the EPI sequence indicated by the ID “AC” registered in the “ID” item of the record is executed when the flow rate of the coolant registered in the “flow velocity” item is “V3” or more and less than “V4”. The load of the gradient magnetic field coil 2 is the ID “registered” in the “ID” item of the record when the coolant flow velocity registered in the “flow velocity” item is not less than “V2” and less than “V3”. It is larger than the load of the gradient coil 2 due to the execution of the EPI sequence indicated by “AB”.

  In the first embodiment, for each record in the database 11a, the sequence indicated by the ID registered in the item “ID” indicates that the temperature of the cooling water supplied from the cooling system 200 to the MRI apparatus 100 is “temperature”. A plurality of sequences that do not exceed the allowable temperature of the MRI apparatus 100 even if executed when the flow rate is within the range of the temperature registered in the item of "No." and the flow rate is within the range of the flow rate registered in the item of "flow rate" In this sequence, the size of the gap between the gradient coil 2 and the resin can be made to converge at a constant rate in the shortest time. As will be described later, the MRI apparatus 100 uses such a database 11a to select a sequence to be executed during preliminary operation, thereby setting the size of the gap between the gradient magnetic field coil 2 and the resin before starting operation. It can be made to converge to a certain level.

  Next, the flow of a process (pre-operation process) executed by the MRI apparatus 100 according to the first embodiment during the pre-operation will be described. FIG. 3 is a flowchart showing the flow of the pre-operation process according to the first embodiment. The pre-operation process is executed when the selection function 15a receives an instruction to execute the pre-operation process from the user via the input circuit 9 when the MRI apparatus 100 is installed (at the time of installation). In the first embodiment, for example, the subject S is not placed on the top board 8a when the pre-operation process is executed.

  As illustrated in the example of FIG. 3, the selection function 15 a performs a sequence corresponding to the coolant temperature indicated by the signal output from the temperature sensor 20 and the coolant flow rate indicated by the signal output from the flow sensor 21. Select (step S101). For example, in step S101, the selection function 15a registers the temperature range including the temperature of the cooling water indicated by the signal output from the temperature sensor 20 in the “temperature” item, and the “flow velocity” item. The record in which the range of the flow velocity including the flow velocity of the cooling water indicated by the signal output from the flow sensor 21 is registered is specified. In step S101, the selection function 15a selects the sequence indicated by the ID registered in the item “ID” of the identified record. In addition, the selection function 15a acquires the setting information including the temperature and the flow velocity of the cooling water set in the cooling system 200 without using the signals output from the temperature sensor 20 and the flow rate sensor 21, and uses the acquired setting information. The same processing may be performed to select the sequence.

  Then, the execution function 13a executes the selected sequence (step S102). For example, in step S102, the execution function 13a acquires the execution time registered in the item “execution time” of the record specified by the selection function 15a in step S101. In step S102, the execution function 13a executes the sequence selected by the selection function 15a in step S101 for the acquired execution time. Thereby, the magnitude | size of the clearance gap between the gradient magnetic field coil 2 and resin is converged uniformly before a driving | operation start. Therefore, the MRI apparatus 100 according to the first embodiment can be used in a stable state from the start of operation.

  The MRI apparatus 100 according to the first embodiment has been described above. The MRI apparatus 100 according to the first embodiment can be used in a stable state from the start of operation as described above.

  In the first embodiment, the cooling water temperature range, the cooling water flow velocity range, and the sequence are associated with each other and registered in the database 11a. In step S101, the selection function 15a is operated by the temperature sensor. The case where the sequence corresponding to the coolant temperature indicated by the signal output from 20 and the flow rate of the coolant indicated by the signal output from the flow sensor 21 has been described. However, in the first embodiment, the temperature range of the cooling water and the sequence may be associated with each other and registered in the database 11a. In this case, in step S101, the selection function 15a may select a sequence corresponding to the temperature of the cooling water indicated by the signal output from the temperature sensor 20. Moreover, in 1st Embodiment, the range of the flow rate of a cooling water and a sequence may be matched and registered into the database 11a. In this case, in step S101, the selection function 15a may select a sequence corresponding to the flow rate of the cooling water indicated by the signal output from the flow sensor 21. That is, in the first embodiment, at least one of the cooling water temperature range and the cooling water flow velocity range may be associated with the sequence and registered in the database 11a. In this case, in step S101, the selection function 15a corresponds to at least one of the coolant temperature indicated by the signal output from the temperature sensor 20 and the coolant flow rate indicated by the signal output from the flow sensor 21. A sequence to be searched may be searched from the database 11a, and a sequence obtained as a result of the search may be selected. That is, the selection function 15a may select a sequence based on at least one of the temperature and the flow rate of the cooling water supplied from the cooling system 200.

(Second Embodiment)
In the first embodiment described above, the case where the MRI apparatus 100 executes the sequence for the execution time acquired from the database 11a has been described. That is, in the first embodiment, a case has been described in which the timing at which execution of a sequence is completed is determined in advance at the time of execution. However, the MRI apparatus may determine the timing for completing the execution of the sequence. Such an embodiment will be described as a second embodiment.

  FIG. 4 is a functional block diagram showing the configuration of the MRI apparatus 300 according to the second embodiment. The MRI apparatus 300 according to the second embodiment shown in FIG. 4 is different from the MRI apparatus 100 according to the first embodiment shown in FIG. 1 in that it has a calculation function 15b. The database 11a according to the second embodiment is different from the database 11a according to the first embodiment shown in FIG. 2 in that there is no “execution time” item in each record. That is, in the second embodiment, since the timing for completing the execution of the sequence is determined, the execution time of the sequence is not registered in the database 11a.

  The calculation function 15b according to the second embodiment has a predetermined time interval (for example, every 1 minute or every 10 minutes) when the sequence is executed by the execution function 13a in the pre-operation process. MT value is calculated. For example, the calculation function 15b acquires MR signal data collected when the sequence is executed by the execution function 13a from the storage circuit 11, and calculates the MT value from the acquired MR signal data. The calculation function 15b is an example of a calculation unit. In the second embodiment, the subject S is not placed on the top board 8a when the pre-operation process is executed.

  Then, the execution function 13a according to the second embodiment determines whether or not the MT value has converged to a constant value based on the fluctuation of the MT value, and determines that the MT value has converged to a constant value. In this case, the execution of the sequence in the pre-operation process is terminated. Here, when the MT value is converged to a constant value, the MRI apparatus 300 is in a stable state. That is, the execution function 13a ends the execution of the sequence when the MRI apparatus 300 becomes stable. As described above, the execution function 13a according to the second embodiment ends the execution of the sequence when the MRI apparatus 300 is in a stable state. Occurrence of a situation that ends the processing can be suppressed. Therefore, the MRI apparatus 300 according to the second embodiment can be used in a stable state from the start of operation more reliably.

  A flow of pre-operation processing executed by the MRI apparatus 300 according to the second embodiment during pre-operation will be described. FIG. 5 is a flowchart showing a flow of pre-operation processing according to the second embodiment. The pre-operation process according to the second embodiment is executed when the selection function 15a receives an instruction to execute the pre-operation process from the user via the input circuit 9 when the MRI apparatus 300 is installed. In the second embodiment, as described above, the subject S is not placed on the top board 8a when the pre-operation process is executed.

  As illustrated in the example of FIG. 5, the selection function 15 a is output from the coolant temperature indicated by the signal output from the temperature sensor 20 and the flow sensor 21, as in step S <b> 101 according to the first embodiment. The sequence corresponding to the flow rate of the cooling water indicated by the signal is selected (step S201).

  Then, the execution function 13a starts executing the selected sequence (step S202).

  Then, the calculation function 15b calculates the MT value at predetermined time intervals after the execution of the sequence is started in step S202. For example, the calculation function 15b determines whether or not a predetermined time has elapsed since the execution of the sequence was started or the previous MT value was calculated (step S203). If it is determined that the predetermined time has not elapsed (step S203; No), the calculation function 15b determines again in step S203 whether the predetermined time has elapsed. On the other hand, when it is determined that the predetermined time has elapsed (step S203; Yes), the calculation function 15b calculates the MT value (step S204).

  Then, the execution function 13a determines whether or not to end the execution of the sequence based on the fluctuation of the MT value (Step S205). For example, the execution function 13a calculates the difference between the MT value calculated last time and the MT value calculated this time, and determines whether or not the calculated difference is within a predetermined threshold value α. If it is determined that the calculated difference is within the predetermined threshold value α, the MT value has converged to a constant value, and therefore the execution function 13a determines to end the execution of the sequence. On the other hand, when the execution function 13a determines that the calculated difference has exceeded the predetermined threshold value α, the MT value has not converged to a constant value, and therefore determines that the execution of the sequence is not terminated.

  When it is determined that the execution of the sequence is not finished (step S205; No), the calculation function 15b returns to step S203. On the other hand, when it is determined that the execution of the sequence is to be ended (step S205; Yes), the execution function 13a ends the execution of the selected sequence (step S206) and ends the pre-operation process.

  The MRI apparatus 300 according to the second embodiment has been described above. According to the MRI apparatus 300 according to the second embodiment, as described above, it can be used in a stable state from the start of operation as described above.

(First Modification of Second Embodiment)
Next, a first modification of the second embodiment will be described. In the second embodiment, a case where the execution function 13a of the MRI apparatus 300 determines in step S205 that the calculated difference is within the predetermined threshold value α and determines that the execution of the sequence is to be ended is determined. did. However, when the execution function 13a according to the first modification of the second embodiment determines that the calculated difference is within the predetermined threshold value α in step S205, a plurality of times (for example, four times) continuously, It may be determined that the execution of the sequence is finished. Thereby, it is possible to prevent the calculated difference from being within the predetermined threshold value α and terminating the execution of the sequence.

(Second modification of the second embodiment)
Further, in the second embodiment, the case has been described in which the MRI apparatus 300 executes one type of selected sequence during preliminary operation. However, the MRI apparatus 300 may execute a plurality of types of sequences during preliminary operation. Thus, such an embodiment will be described as a second modification of the second embodiment.

  FIG. 6 is a diagram for explaining a second modification of the second embodiment. FIG. 6 is a graph showing the number of times the difference between the MT value calculated last time and the MT value calculated this time is calculated on the horizontal axis, and the magnitude of the difference calculated each time on the vertical axis. As shown in the example of FIG. 6, the difference 60a is a difference calculated for the first time. Similarly, the difference 60b is a difference calculated for the second time, and the difference 60c is a difference calculated for the third time. As shown in the example of FIG. 6, the execution function 13a according to the second modification of the second embodiment, for example, determines that the calculated differences 60a, 60b, and 60c exceed a predetermined threshold value α in step S205. If the determination is made consecutively, a sequence having a larger load than the sequence being executed may be executed instead of the sequence being executed. That is, the execution function 13a according to the second modification of the second embodiment may change the sequence executed during the preliminary operation based on the fluctuation of the MT value. Thereby, since the magnitude | size of the clearance gap between the gradient magnetic field coil 2 and resin is converged more quickly, the whole execution time of the process at the time of preliminary operation can be shortened.

  Note that, in the second modification of the second embodiment, as in the first modification of the second embodiment, the execution function 13a has the difference calculated in step S205 within a predetermined threshold value α. A case will be described in which it is determined that the execution of the sequence is finished when it is continuously determined a plurality of times (for example, four times). In this case, if it is determined in step S205 that the calculated difference is within the predetermined threshold value α a plurality of times (for example, twice) continuously, the execution function 13a is executing in place of the sequence being executed. A sequence having a smaller load than the sequence may be executed.

(Third Modification of Second Embodiment)
An MRI apparatus 300 according to a third modification of the second embodiment will be described. In the second embodiment, the first modification of the second embodiment, and the second modification of the second embodiment, the execution function 13a uses the difference calculated in step S205 to perform the sequence. A case has been described in which it is determined whether or not to end the execution. However, in step S205, the execution function 13a of the MRI apparatus 300 according to the third modification example of the second embodiment replaces the above-described difference with the moving average of the differences (for example, the moving average of the three most recent differences). (The difference calculated this time, the difference calculated last time, and the average value of the difference calculated last time)), the same processing is performed to determine whether or not to end the execution of the sequence. Good.

(Third embodiment)
In the second embodiment, the first modification example of the second embodiment, and the second modification example of the second embodiment, the MRI apparatus 300 calculates the MT value and calculates the MT value. The case has been described in which it is determined whether or not to end the execution of the sequence or the type of the sequence is changed based on the fluctuation of the sequence. However, the MRI apparatus 300 calculates the phase correction information instead of the MT value, and determines whether or not to end the execution of the sequence based on the variation in the phase difference indicated by the phase correction information, You may change the type. Such an embodiment will be described as a third embodiment.

  The image generation function 14a according to the third embodiment reads MR signal data stored in the storage circuit 11 at predetermined time intervals, and performs post-processing, that is, reconstruction processing such as Fourier transform on the read MR signal data. To generate an image. Here, the image generation function 14a, when generating an image from MR signal data collected by executing the EPI sequence, corrects the phase difference between the even and odd lines in the image. Correction information is calculated, and the phase difference indicated by the calculated phase correction information is used to correct the phase difference between the even and odd lines to generate an image. In the third embodiment, assuming that the magnitude of the phase difference indicated by the phase correction information and the magnitude of the MT value are interlocked, the MRI apparatus 300 is based on the variation in the phase difference indicated by the phase correction information. Whether to end the execution of the sequence or to change the type of the sequence. As described above, in the third embodiment as well, as in the second embodiment, when the MRI apparatus 300 is in a stable state, the execution of the sequence is terminated, so the state of the MRI apparatus 300 is not stable. In addition, it is possible to suppress the occurrence of a situation where the pre-operation process is terminated. Therefore, the MRI apparatus 300 according to the third embodiment can be used in a stable state from the start of operation more reliably. The image generation function 14a is an example of an image generation unit.

  A flow of the pre-operation process executed by the MRI apparatus 300 according to the third embodiment during the pre-operation will be described. FIG. 7 is a flowchart showing a flow of pre-operation processing according to the third embodiment. The pre-operation process according to the third embodiment is executed when the selection function 15a receives an instruction to execute the pre-operation process from the user via the input circuit 9 when the MRI apparatus 300 is installed. In the third embodiment, when the pre-operation process is executed, a predetermined phantom (for example, a water phantom) is placed on the top plate 8a, or nothing is placed. Absent.

  As illustrated in the example of FIG. 7, the selection function 15a is configured to provide the cooling water indicated by the signal output from the temperature sensor 20 as in step S101 according to the first embodiment and step S201 according to the second embodiment. And a sequence corresponding to the cooling water flow rate indicated by the signal output from the flow rate sensor 21 (step S301).

  Then, the execution function 13a starts executing the selected sequence (step S302).

  Then, the image generation function 14a generates an image and calculates phase correction information at predetermined time intervals after the execution of the sequence is started in step S302. For example, the image generation function 14a determines whether or not a predetermined time has elapsed since the execution of the sequence was started or the previous phase correction information was calculated (step S303). If it is determined that the predetermined time has not elapsed (step S303; No), the image generation function 14a determines again in step S303 whether the predetermined time has elapsed. On the other hand, when it is determined that the predetermined time has elapsed (step S303; Yes), the image generation function 14a generates an image and calculates phase correction information (step S304).

  Then, the execution function 13a determines whether or not to end the execution of the sequence based on the variation in the phase difference indicated by the phase correction information (step S305). For example, the execution function 13a calculates a difference between the phase difference indicated by the previously calculated phase correction information and the phase difference indicated by the phase correction information calculated this time, and the calculated difference is within a predetermined threshold. It is determined whether or not. When it is determined that the calculated difference is within a predetermined threshold, the execution function 13a determines that the execution of the sequence is completed because the phase difference indicated by the phase correction information has converged to a certain value. On the other hand, when the execution function 13a determines that the calculated difference exceeds a predetermined threshold, the phase difference indicated by the phase correction information has not converged to a constant value, and thus the execution of the sequence is determined not to end. To do.

  If it is determined not to end the execution of the sequence (step S305; No), the image generation function 14a returns to step S303. On the other hand, when it is determined that the execution of the sequence is to be ended (step S305; Yes), the execution function 13a ends the execution of the selected sequence (step S306) and ends the pre-operation process.

  The MRI apparatus 300 according to the third embodiment has been described above. According to the MRI apparatus 300 according to the third embodiment, as described above, the MRI apparatus 300 can be used more reliably in a stable state from the start of operation.

  In the third embodiment, the execution function 13a of the MRI apparatus 300 executes the sequence only by determining in step S305 that the phase difference indicated by the calculated phase correction information is within a predetermined threshold value. The case where it is determined to end the process has been described. However, when the execution function 13a according to the third embodiment determines that the phase difference indicated by the calculated phase correction information is within a predetermined threshold in step S305, a plurality of times (for example, four times) continuously, It may be determined that the execution of the sequence is finished.

  In the third embodiment, the case has been described in which the MRI apparatus 300 executes one type of selected sequence during preliminary operation. However, the MRI apparatus 300 according to the third embodiment may execute a plurality of types of sequences during the preliminary operation.

  For example, the execution function 13a according to the third embodiment is being executed when, for example, in step S305, it is determined that the phase difference indicated by the calculated phase correction information has exceeded a predetermined threshold value three times in succession. Instead of this sequence, a sequence having a larger load than the sequence being executed may be executed. That is, the execution function 13a according to the third embodiment may change the sequence executed during the preliminary operation based on the variation in the phase difference indicated by the phase correction information. Thereby, since the magnitude | size of the clearance gap between the gradient magnetic field coil 2 and resin is converged more quickly, the whole execution time of the process at the time of preliminary operation can be shortened.

  Here, in the third embodiment, as described above, the execution function 13a performs a plurality of times (for example, four times) when the phase difference indicated by the calculated phase correction information is within a predetermined threshold in step S305. A case will be described in which it is determined that the execution of the sequence is completed when the determination is made continuously. In this case, if it is determined in step S305 that the phase difference indicated by the calculated phase correction information is within a predetermined threshold value a plurality of times (for example, twice), the execution function 13a Instead of this, a sequence having a smaller load than the sequence being executed may be executed.

  Further, in the third embodiment, a case has been described in which the execution function 13a determines in step S305 whether to end the execution of the sequence using the phase difference indicated by the calculated phase correction information. However, in step S305, the execution function 13a of the MRI apparatus 300 according to the third embodiment replaces the phase difference indicated by the phase correction information with a moving average of the phase difference indicated by the phase correction information (for example, calculated this time). Using the phase difference indicated by the phase correction information, the phase difference indicated by the previously calculated phase correction information, and the average value of the phase differences indicated by the phase correction information calculated two times before). It may be determined whether or not to end the execution of the sequence.

  According to the magnetic resonance imaging apparatus and installation method of at least one embodiment described above, it can be used in a stable state from the start of operation.

  Although several embodiments of the present invention have been described, these embodiments are presented by way of example 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 spirit of the invention. These embodiments and their modifications are included in the scope and gist of the invention, and are also included in the invention described in the claims and the equivalents thereof.

2 Gradient magnetic field coil 14a Image generation function 15a Selection function 15b Calculation function 100, 300 MRI apparatus

Claims (9)

Based on information related to cooling of the own device at the installation location, a selection unit that selects a sequence to be executed during preliminary operation to stabilize the state of the own device from a plurality of sequences;
An execution unit for executing the selected sequence during the preliminary operation;
A magnetic resonance imaging apparatus comprising: The selection unit selects a sequence having the shortest execution time from sequences that can be executed within the allowable temperature of the device based on the information,
The execution unit executes the selected sequence for the execution time.
The magnetic resonance imaging apparatus according to claim 1.   The magnetic resonance imaging apparatus according to claim 1, wherein the selection unit selects the sequence based on at least one of a temperature and a flow rate of cooling water supplied from a cooling system at the installation site as the information. . A magnetic field coil that is fixed in position by a resin and that applies a gradient magnetic field within a static magnetic field in which the subject is placed;
The said selection part selects the said sequence performed at the time of the said prior operation in order to make constant MT (Maxwell Term) value in the said gradient magnetic field based on the said information. The magnetic resonance imaging apparatus described in 1. A calculation unit for calculating the MT value at predetermined time intervals;
The execution unit ends the execution of the sequence at the time of the preliminary operation when the MT value is converged to a constant value based on the fluctuation of the MT value.
The magnetic resonance imaging apparatus according to claim 4. The selection unit changes a sequence executed during the preliminary operation based on a change in the MT value.
The magnetic resonance imaging apparatus according to claim 5. Based on the collected MR signal data, an image is generated at predetermined time intervals, and further includes an image generation unit that calculates phase correction information.
The execution unit, when the phase difference indicated by the phase correction information converges to a constant value based on the variation in the phase difference indicated by the phase correction information, End execution,
The magnetic resonance imaging apparatus according to claim 1. The selection unit changes a sequence executed during the preliminary operation based on a variation in a phase difference indicated by the phase correction information.
The magnetic resonance imaging apparatus according to claim 7. Magnetic resonance imaging device
Based on information related to cooling of the magnetic resonance imaging apparatus at the installation site, a sequence executed during preliminary operation is selected from a plurality of sequences to stabilize the state of the magnetic resonance imaging apparatus.
Executing the selected sequence during the pre-operation;
Installation method of magnetic resonance imaging apparatus.

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