JP6747898B2 - Magnetic resonance imaging apparatus and installation method - Google Patents

Description

Embodiments of the present invention relate to a magnetic resonance imaging apparatus and an installation method.

Nuclear spins of a subject placed in a static magnetic field are magnetically excited by RF (Radio Frequency) pulse of Larmor frequency, and the image is reconstructed from MR (Magnetic Resonance) signal generated by this excitation. There is a magnetic resonance imaging (MRI: Magnetic Resonance Imaging) apparatus which comprises.

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, 10-328160, A

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

The magnetic resonance imaging apparatus of the embodiment includes a selection unit and an execution unit. The selection unit selects, from a plurality of sequences, a sequence to be executed during the pre-operation in order to stabilize the state of the own device, based on the information regarding the cooling of the own device at the installation location. The executing unit executes the selected sequence during the pre-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 showing an example of the data structure of the pre-operation sequence acquisition database. FIG. 3 is a flowchart showing the flow of the pre-driving 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 time 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 the flow of pre-driving process according to the third embodiment.

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

(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, and a reception circuit 7. The bed 8, 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 are provided. Note that the MRI apparatus 100 does not include the subject S (for example, human body) shown in FIG. The configuration shown in FIG. 1 is merely an example.

A cooling system 200 is connected to the gradient magnetic field coil 2 of the MRI apparatus 100 via a cooling pipe. The cooling system 200 is provided by the hospital in which the MRI apparatus 100 is installed (installed).

The static magnetic field magnet 1 is formed in a hollow, substantially cylindrical shape (including one in which the cross section orthogonal 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 in which a cross section orthogonal to the central axis of the cylinder is elliptical), and is arranged on the inner peripheral side of the static magnetic field magnet 1. The gradient magnetic field coil 2 has three coils that generate gradient magnetic fields along the x-axis, the y-axis, and the z-axis, which are orthogonal to each other. Here, the x-axis, the y-axis, and the z-axis form a device 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. Further, 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 magnetic field coil 2 is fixed by a resin such as epoxy resin.

The gradient magnetic field power supply 3 individually supplies currents to the three coils of 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 the gradient magnetic fields along the x-axis, the y-axis, and the z-axis, the gradient magnetic fields can be generated along the read-out direction, the phase encode direction, and the slice direction, which are orthogonal to each other. Here, the axes along the read-out direction, the phase encode direction, and the slice direction respectively constitute a logical coordinate system for defining a slice area or a volume area to be imaged. In the following, a gradient magnetic field along the readout direction is called a readout gradient magnetic field, a gradient magnetic field along the phase encoding direction is called a phase encoding gradient magnetic field, and a gradient magnetic field along the slice direction is called a slice gradient magnetic field. ..

Each gradient magnetic field is superposed on the static magnetic field generated by the static magnetic field magnet 1, and is used to add spatial position information to the magnetic resonance (Magnetic Resonance: MR) signal. Specifically, the readout gradient magnetic field changes the frequency of the MR signal in accordance with the position in the readout direction, thereby giving the MR signal position information along the readout direction. Further, the phase encode gradient magnetic field changes the phase of the MR signal along the phase encode direction to give the MR signal position information in the phase encode direction. 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 is dependent on the position in the slice direction when the imaging area is a volume area. By changing the phase of the MR signal in accordance with the above, position information along the slice direction is added to the MR signal.

The transmission coil 4 is formed in a hollow, substantially cylindrical shape (including one in which a cross section orthogonal to the central axis of the cylinder is elliptical), and is arranged 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 has an oscillation circuit, a phase selection circuit, a frequency conversion circuit, an amplitude modulation circuit, and an RF amplification circuit. The oscillating circuit generates an RF pulse having a resonance frequency specific to the target nucleus placed in the 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 it to the transmission coil 4.

The reception coil 6 is arranged inside the gradient magnetic field coil 2 and receives the MR signal emitted from the subject S under 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 pre-stage amplification 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-stage 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 pre-stage 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 to this. For example, the transmission coil 4 may further have a reception function of receiving MR signals. Further, the receiving coil 6 may further have a transmitting function of 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 receiving coil 6 has a transmitting function, the transmitting circuit 5 also outputs an RF pulse to the receiving 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 is moved to an 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 its longitudinal direction is parallel to the central axis of the static magnetic field magnet 1.

The input circuit 9 receives an input operation of various instructions and various information from an 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 and converts the input operation received from the operator into an electric signal and outputs the electric 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 and converts various information and various image data sent from the processing circuit 15 into electrical signals for display and outputs the electrical signals.

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), 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 bed control function 12a is connected to the bed 8, and outputs an electric signal for control to the bed 8 to control the operation of the bed 8. For example, the bed control function 12a receives an instruction from the operator via the input circuit 9 to move the top 8a in the longitudinal direction, the vertical direction, or the left-right direction, and moves the top 8a according to the received instruction. The drive mechanism for the top plate 8a of the bed 8 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 13a 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 a current to the gradient magnetic field coil 2, the magnitude (strength) of the supplied current, and the RF pulse supplied by the transmission circuit 5 to the transmission coil 4. The information defines the strength of the current, the supply timing, the detection timing at which the receiving circuit 7 detects the MR signal, and the like. This sequence execution data is also simply called a sequence (pulse sequence).

Further, the execution function 13a receives the 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 above-mentioned readout gradient magnetic field, phase encoding gradient magnetic field, and slice gradient magnetic field. As a result, the data is stored in the memory circuit 11 as the data forming 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 14a 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 to form an image. To generate. The image generation function 14a also stores the image data of the generated image in the storage circuit 11.

The processing circuit 15 controls the respective constituent elements of the MRI apparatus 100 to perform overall control of 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 the information of the cooling water that cools the MRI apparatus 100, which is supplied from the cooling system 200 at the installation location of the MRI apparatus 100. In order to select the sequence to be executed during pre-operation. 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, which is a component of the processing circuit 15, is stored in the storage circuit 11 in the form of a program executable by a computer. The processing circuit 15 realizes the selection function 15a corresponding to the program by reading the program corresponding to the selection function 15a from the storage circuit 11 and executing the read program. In other words, the processing circuit 15 in the state where the program is read out has the selection function 15a shown in the processing circuit 15 of FIG.

The word "processor" used in the above description means, for example, a CPU (central processing unit), a GPU (Graphics Processing Unit), an application specific integrated circuit (ASIC), a programmable logic device (for example, It means a circuit 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 memory circuit 11, the program may be directly incorporated in the circuit of the processor. 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 near 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 rate 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 cooling water per unit time indicates the flow rate of cooling water. That is, the signal output from the flow rate sensor 21 according to this embodiment indicates the flow velocity of the cooling water.

The cooling system 200 flows water in the gradient magnetic field coil 2, for example, by flowing water adjusted to a predetermined temperature (for example, 20 degrees or 18 degrees) toward the gradient magnetic field coil 2 through a cooling pipe. .. In addition, when the water flowing in 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 again to the condenser. In this way, the cooling system 200 cools the gradient magnetic field coil 2 by circulating water with 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-mentioned three coils forming the gradient magnetic field coil 2 of the MRI apparatus 100 is arranged in each layer of XYZ. 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. The size of this gap increases, for example, as the width of the current passed through the coil increases.

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

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

However, immediately after the MRI apparatus is installed in a hospital or the like and its use is started, the size of the gap between the coil and the resin does not converge to a certain size, so the image quality of the obtained image deteriorates. It may happen.

Therefore, as described below, the MRI apparatus 100 according to the present embodiment is configured so that it can be used in a stable state from the start of operation. Note that the stable state here refers to, for example, a state in which 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 also a state in which 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, the “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 cooling system 200 of the hospital in which the MRI apparatus 100 is installed, and the ID (Identification) that uniquely identifies the sequence executed during the pre-operation. Have been registered. FIG. 2 is a diagram showing 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. The range of the flow velocity of the cooling water supplied from the cooling system 200 is registered in the item "flow velocity". An ID for uniquely identifying a sequence corresponding to the temperature range registered in the “temperature” item and the flow velocity range registered in the “flow velocity” item is registered in the “ID” item. ing. In the "execution time" item, the 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 velocity” item are examples of information regarding cooling of the MRI apparatus 100.

For example, in the first record shown in the example of FIG. 2, 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”, the ID is “AA”. Shows that the sequence shown by is executed for “t1” minutes during the pre-operation of the MRI apparatus 100.

In the second record shown in the example of FIG. 2, 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”, the ID “AB” is displayed. Indicates that the sequence shown by is executed for "t2" minutes during the pre-operation of the MRI apparatus 100.

Further, the third record shown in the example of FIG. 2 has the ID “AC” when the temperature of the cooling water is “T1” or more and less than “T2” and the flow velocity is “V3” or more and less than “V4”. Indicates that the sequence shown by is executed for “t3” minutes during the pre-operation of the MRI apparatus 100.

The same applies to other records (for example, records when the temperature of the cooling water is equal to or higher than "T2" and lower than "T3"). The temperature "T3" is higher than the temperature "T2", and the temperature "T2" is higher than the temperature "T1". 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 sequences indicated by the IDs registered in the “ID” item of the database 11a are of the same type, although the parameter values are different. An example of such a sequence is 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, 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). ), the parameter values of various parameters such as the magnitude of the current supplied to the gradient coil 2 are different. Therefore, the load on the gradient magnetic field coil 2 due to the execution of the EPI sequence indicated by ID “AA”, the load on the gradient magnetic field coil 2 due to the execution of the EPI sequence indicated by ID “AB”, and the ID “AC”. The load on the gradient magnetic field coil 2 due to the execution of the EPI sequence indicated by is different. The load here refers to, for example, fluctuations in the gradient magnetic field generated by the gradient magnetic field coil 2. The larger the current value of the current flowing through the gradient coil 2, the larger the load. Further, the larger the load, the larger the vibration of the gradient magnetic field coil 2. Hereinafter, the sequence with a large load refers to a sequence in which the gradient magnetic field coil 2 is vibrated relatively large by being executed. Further, the sequence with a small load refers to a sequence in which the gradient magnetic field coil 2 is vibrated relatively small by being executed.

For example, when the temperature of the cooling water is low, the temperature of the heat generated from the gradient magnetic field coil 2 is less likely to exceed the allowable temperature of the MRI apparatus 100 even if the sequence in which the load is large is executed. Therefore, for each record in the database 11a, if the flow velocity registered in the item of "flow velocity" is the same, the load increases as the temperature of the cooling water registered in the item of "temperature" 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 due to the execution of the EPI sequence indicated by the ID registered in the item “ID” of the record in which the temperature of the cooling water registered in the item “temperature” is equal to or more than “T1” and less than “T2” For the load of the coil 2, 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 “T2” or more and less than “T3” is executed. The load of the gradient magnetic field coil 2 due to this tends to be larger.

When the flow velocity of the cooling water is high (fast), the temperature of the heat generated from the gradient magnetic field coil 2 is less likely to exceed the allowable temperature of the MRI apparatus 100 even if the sequence in which the load is large is executed. Therefore, for each record in the database 11a, the ID indicating the EPI sequence in which the parameter values of various parameters are set such that the load increases as the flow velocity of the cooling water registered in the item of "velocity" increases. It is registered in the item of ". For example, when the temperatures of the cooling water registered in the “temperature” item are the same (for example, “T1” or more and less than “T2”), the following may be said regarding a plurality of EPI sequences having different parameter values. I can say. For example, the EPI sequence indicated by the ID "AB" registered in the item "ID" of the record in which the flow velocity of the cooling water registered in the item "Flow velocity" is greater than or equal to "V2" and less than "V3" is executed. The load of the gradient magnetic field coil 2 is due to the ID “AA” registered in the “ID” item of the record when the flow velocity of the cooling water registered in the “velocity” item is “V1” or more and less than “V2”. Is larger than the load on the gradient coil 2 due to the execution of the EPI sequence indicated by. Further, when the flow velocity of the cooling water registered in the item of “flow velocity” is equal to or more than “V3” and less than “V4”, the EPI sequence indicated by the ID “AC” registered in the item of “ID” of the record is executed. The load of the gradient magnetic field coil 2 due to this is the ID registered in the item “ID” of the record when the flow velocity of the cooling water registered in the item “flow velocity” is greater than or equal to “V2” and less than “V3”. It is larger than the load on the gradient coil 2 due to the execution of the EPI sequence indicated by “AB”.

Further, in the first embodiment, the sequence indicated by the ID registered in the “ID” item for each record of the database 11a 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 when executed within the range of the temperature registered in the item of “No.” and when the flow rate is within the range of the flow rate registered in the item of “Flow rate” Among these, the sequence is such that the size of the gap between the gradient magnetic field coil 2 and the resin can be converged to a constant value in the shortest time. As will be described later, the MRI apparatus 100 uses such a database 11a to select the sequence to be executed during the pre-operation to determine the size of the gap between the gradient magnetic field coil 2 and the resin before the operation is started. It can be converged to a constant value.

Next, a flow of processing (pre-operation processing) executed by the MRI apparatus 100 according to the first embodiment during pre-operation will be described. FIG. 3 is a flowchart showing the flow of the pre-driving 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 during the installation (installation) of the MRI apparatus 100. In the first embodiment, when the pre-operation process is executed, for example, the subject S is not placed on the top plate 8a.

As shown in the example of FIG. 3, the selection function 15a selects a sequence corresponding to the temperature of the cooling water indicated by the signal output from the temperature sensor 20 and the flow velocity of the cooling water indicated by the signal output from the flow rate sensor 21. A selection is made (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. Then, in step S101, the selection function 15a selects the sequence indicated by the ID registered in the "ID" item of the specified record. 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 the acquired setting information is displayed. The same process may be performed to select a 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 "execution time" item of the record specified by the selection function 15a in step S101. Then, in step S102, the execution function 13a executes the sequence selected by the selection function 15a in step S101 for the acquired execution time. As a result, the size of the gap between the gradient magnetic field coil 2 and the resin is uniformly converged before the operation is started. 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 temperature range of the cooling water, the flow velocity range of the cooling water, and the sequence are associated with each other and registered in the database 11a. In step S101, the selection function 15a causes the temperature sensor to detect the temperature sensor. The case of selecting the sequence corresponding to the temperature of the cooling water indicated by the signal output from 20 and the flow velocity of the cooling water indicated by the signal output from the flow rate sensor 21 has been described. However, in the first embodiment, the temperature range of the cooling water and the sequence may be registered in the database 11a in association with each other. In this case, in step S101, the selection function 15a may select the sequence corresponding to the temperature of the cooling water indicated by the signal output from the temperature sensor 20. In addition, in the first embodiment, the flow velocity range of the cooling water and the sequence may be registered in the database 11a in association with each other. In this case, in step S101, the selection function 15a may select the sequence corresponding to the flow velocity of the cooling water indicated by the signal output from the flow rate 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 registered in the database 11a in association with the sequence. In this case, in step S101, the selection function 15a corresponds to at least one of the temperature of the cooling water indicated by the signal output from the temperature sensor 20 and the flow velocity of the cooling water indicated by the signal output from the flow rate sensor 21. The database 11a may be searched for the sequence to be performed, and the sequence obtained as a result of the search may be selected. That is, the selection function 15a may select the sequence based on at least one of the temperature and the flow velocity of the cooling water supplied from the cooling system 200.

(Second embodiment)
In the above-described first embodiment, 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 the sequence is completed is predetermined at the time of execution. However, the MRI apparatus may determine when to complete the execution of the sequence. Therefore, 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 differs from the MRI apparatus 100 according to the first embodiment shown in FIG. 1 above in that it has a calculation function 15b. Further, the database 11a according to the second embodiment differs from the database 11a according to the first embodiment shown in FIG. 2 above in that there is no item “execution time” 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, in the pre-operation process, when the sequence is executed by the execution function 13a, at a predetermined time interval (for example, every one minute, or every ten minutes), Calculate the MT value. For example, the calculation function 15b acquires the MR signal data collected by the execution function 13a executing the sequence 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. Further, in the second embodiment, the subject S is not placed on the top 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 change in the MT value, and determines that the MT value has converged to a constant value. In that case, the execution of the sequence in the pre-operation process is ended. Here, when the MT value converges 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 is in a stable state. In this way, the execution function 13a according to the second embodiment ends the sequence execution when the MRI apparatus 300 is in a stable state, so the state of the MRI apparatus 300 is not stable, and the pre-operation is performed. It is possible to suppress the occurrence of a situation in which the processing ends. Therefore, according to the MRI apparatus 300 of the second embodiment, the MRI apparatus 300 can be used more reliably and stably from the start of operation.

The flow of the pre-operation process performed by the MRI apparatus 300 according to the second embodiment during the pre-operation will be described. FIG. 5 is a flowchart showing a flow of pre-operation time 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 plate 8a when the pre-operation process is executed.

As shown in the example of FIG. 5, the selection function 15a is output from the flow sensor 21 and the temperature of the cooling water indicated by the signal output from the temperature sensor 20, as in step S101 according to the first embodiment. The sequence corresponding to the flow velocity 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 a predetermined time interval 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). When 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 to end the sequence execution based on the change in 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 the calculated difference is within a predetermined threshold value α. Then, when it is determined that the calculated difference is within the predetermined threshold value α, the MT value has converged to a constant value, and thus the execution function 13a determines to end the execution of the sequence. On the other hand, when it is determined that the calculated difference exceeds the predetermined threshold value α, the execution function 13a determines that the execution of the sequence is not ended because the MT value has not converged to a constant value.

When it is determined that the sequence execution is not finished (step S205; No), the calculation function 15b returns to step S203. On the other hand, when the execution function 13a determines to end the execution of the sequence (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, the MRI apparatus 300 can be used more reliably and stably from the start of operation.

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

(Second Modification of Second Embodiment)
Further, in the second embodiment, the case where the MRI apparatus 300 executes the selected one type of sequence during the pre-operation has been described. However, the MRI apparatus 300 may execute a plurality of types of sequences during the pre-operation. Therefore, 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 the difference calculated the first time. Similarly, the difference 60b is the difference calculated the second time, and the difference 60c is the difference calculated the third time. As illustrated in the example of FIG. 6, the execution function 13a according to the second modification of the second embodiment determines that the calculated differences 60a, 60b, and 60c exceed a predetermined threshold value α in step S205. When 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 modified example of the second embodiment may change the sequence executed during the pre-operation based on the change in the MT value. As a result, the size of the gap between the gradient magnetic field coil 2 and the resin is converged more quickly, so that the overall execution time of the pre-operation process can be shortened.

In addition, in the second modification of the second embodiment, the execution function 13a causes the difference calculated in step S205 to be within a predetermined threshold value α, as in the first modification of the second embodiment. A case will be described where it is determined that the execution of the sequence ends when a plurality of times (for example, four times) are continuously determined. In this case, when it is determined in step S205 that the calculated difference is within the predetermined threshold value α continuously a plurality of times (for example, twice), the execution function 13a replaces the sequence being executed and executes it. A sequence having a smaller load than the sequence may be executed.

(Third Modification of Second Embodiment)
An MRI apparatus 300 according to the third modified example 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 execute the sequence. The case has been described where it is determined whether or not to end the execution of. However, the execution function 13a of the MRI apparatus 300 according to the third modified example of the second embodiment changes the moving average of the differences (for example, the moving average of the latest three differences) in step S205. (The difference calculated this time, the difference calculated last time, and the average value of the difference calculated two times before) are used to determine whether or not the sequence execution is ended by performing the same process. Good.

(Third Embodiment)
In the second embodiment, the first modification of the second embodiment, and the second modification of the second embodiment described above, the MRI apparatus 300 calculates the MT value and the MT value. The case has been described in which it is determined whether the sequence execution is terminated or the type of the sequence is changed based on the variation of 1. However, the MRI apparatus 300 calculates the phase correction information instead of the MT value, determines whether or not to end the execution of the sequence based on the fluctuation of the phase difference indicated by the phase correction information, and You may change the type. Therefore, 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 memory circuit 11 at predetermined time intervals, and performs post-processing, that is, reconstruction processing such as Fourier transform, on the read MR signal data. Generate an image with. Here, when the image generation function 14a generates an image from the MR signal data collected by executing the EPI sequence, the image generation function 14a corrects the phase for correcting the phase difference between the even line and the odd line in the image. The correction information is calculated, and the phase difference between the even line and the odd line is corrected using the phase difference indicated by the calculated phase correction information 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 with each other, the MRI apparatus 300 calculates the difference in the phase indicated by the phase correction information. , Determines whether to end execution of a sequence, or changes the type of sequence. As described above, also in the third embodiment, the sequence is terminated when the MRI apparatus 300 is in a stable state, as in the second embodiment, so that the state of the MRI apparatus 300 is not stable. Moreover, it is possible to suppress the occurrence of a situation in which the pre-operation process is ended. Therefore, according to the MRI apparatus 300 of the third embodiment, it is possible to more reliably use the MRI apparatus in a stable state from the start of operation. The image generation function 14a is an example of an image generation unit.

The flow of the pre-driving process executed by the MRI apparatus 300 according to the third embodiment during the pre-driving will be described. FIG. 7 is a flowchart showing the flow of pre-driving process according to the third embodiment. The pre-driving process according to the third embodiment is executed when the selection function 15a receives an instruction to execute the pre-driving process from the user via the input circuit 9 when the MRI apparatus 300 is installed. In addition, 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 shown in the example of FIG. 7, the selection function 15a is similar to step S101 according to the first embodiment and step S201 according to the second embodiment in that the cooling water indicated by the signal output from the temperature sensor 20 is used. And the sequence corresponding to the flow rate of the cooling water indicated by the signal output from the flow rate sensor 21 are selected (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 the phase correction information at a predetermined time interval 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). When 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 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 the difference between the phase difference indicated by the phase correction information calculated last time and the phase difference indicated by the phase correction information calculated this time, and the calculated difference is within a predetermined threshold value. Or not. When it is determined that the calculated difference is within the predetermined threshold, the phase difference indicated by the phase correction information has converged to a constant value, and thus 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 exceeds the predetermined threshold value, the phase difference indicated by the phase correction information has not converged to a constant value, and thus the execution of the sequence is not ended. To do.

When it is determined that the sequence execution is not ended (step S305; No), the image generation function 14a returns to step S303. On the other hand, when the execution function 13a determines to end the execution of the sequence (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 of the third embodiment, as described above, the MRI apparatus 300 can be used more reliably and stably from the start of operation.

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

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

For example, when the execution function 13a according to the third embodiment determines that the phase difference indicated by the calculated phase correction information exceeds the predetermined threshold value three times in a row in step S305, the execution function 13a is in execution. Instead of the sequence No., 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 pre-operation based on the fluctuation of the phase difference indicated by the phase correction information. As a result, the size of the gap between the gradient magnetic field coil 2 and the resin is converged more quickly, so that the overall execution time of the pre-operation process 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 in step S305 is within a predetermined threshold value. A case will be described where it is determined that the execution of the sequence is ended when the determination is continuously performed. In this case, in step S305, when it is determined that the phase difference indicated by the calculated phase correction information is within the predetermined threshold value a plurality of times (for example, twice) in succession, the execution function 13a determines that the sequence being executed is in progress. 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 or not 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 the moving average of the phase difference indicated by the phase correction information (for example, this time calculation). The same process is performed using the phase difference indicated by the calculated phase correction information, the phase difference indicated by the previously calculated phase correction information, and the phase difference indicated by the phase correction information calculated two times before). Alternatively, it may be determined whether or not to end the execution of the sequence.

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

While 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 spirit of the invention. The embodiments and their modifications are included in the scope of the invention and the scope thereof, as well as in the invention described in the claims and the scope of 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 the information about the cooling of the own device at the installation location, from a plurality of sequences, a selection unit that selects a sequence executed during pre-operation to stabilize the state of the own device,
An execution unit that executes the selected sequence during the pre-operation,
A magnetic resonance imaging apparatus comprising: Based on the information, the selection unit selects a sequence having the shortest execution time from sequences that can be executed within the allowable temperature of the own device,
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 as the information based on at least one of a temperature and a flow velocity of cooling water supplied from a cooling system at the installation location. .. The position is fixed by the resin, further comprising a gradient magnetic field coil for applying a gradient magnetic field in the static magnetic field in which the subject is placed,
The selection unit selects the sequence executed during the pre-operation in order to make the MT (Maxwell Term) value in the gradient magnetic field constant based on the information. Magnetic resonance imaging apparatus according to item 1. Further comprising a calculator for calculating the MT value at predetermined time intervals,
When the MT value is converged to a constant value based on the change in the MT value, the execution unit ends the execution of the sequence during the pre-operation,
The magnetic resonance imaging apparatus according to claim 4. The selector changes the sequence executed during the pre-operation based on the change in the MT value,
The magnetic resonance imaging apparatus according to claim 5. Based on the collected MR signal data, an image generating unit that generates an image at predetermined time intervals and calculates phase correction information is further provided.
The execution unit, based on the fluctuation of the phase difference indicated by the phase correction information, when the phase difference indicated by the phase correction information is converged to a constant value, Terminate execution,
The magnetic resonance imaging apparatus according to claim 1. The selection unit changes the sequence executed during the preliminary operation based on a change in the phase difference indicated by the phase correction information.
The magnetic resonance imaging apparatus according to claim 7. Magnetic resonance imaging device
Based on information about cooling the magnetic resonance imaging apparatus at the installation location, from among a plurality of sequences, to select a sequence to be executed during pre-operation to stabilize the state of the magnetic resonance imaging apparatus,
Executing the selected sequence during the pre-operation,
Magnetic resonance imaging apparatus installation method.

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