Magnetic resonance imaging apparatus and image generating method

Abstract

To reduce an imaging time in imaging using different MT pulses.SOLUTION: An MRI apparatus includes: a sequence control unit which performs a first pulse sequence that repeats application of a first MT pulse and collection of a first MR signal related to a high frequency region being a part of a k space during a transition period until magnetization shifts to a steady state and repeats application of the first MT pulse and collection of a second MR signal related to a low frequency region in the k space in the steady state, and a second pulse sequence that repeats application of a second MT pulse different from the first MT pulse and collection of a third MR signal related to the high frequency region during the transition period and repeats application of the second MT pulse and collection of a fourth MR signal related to the low frequency region in the steady state; an allocation part which allocates the third MR signal to a high frequency region of other parts in the k space related to the first pulse sequence; and an image generating part which generates an MR image related to the first pulse sequence on the basis of the first to third MR signals.SELECTED DRAWING: Figure 7

Description

[Technical field]

[0001] The embodiments disclosed in this specification and the drawings relate to a magnetic resonance imaging apparatus and an image generating method. [Background technology]

[0002] In recent years, there has been an increase in the number of techniques for creating computational maps from multiple images of image types using different magnetization exchange (MT) pulses. Examples include MTRasym maps, MTR maps, and ihMTR maps of CEST (Chemical exchange saturation transfer). In order to obtain a steady state of image contrast for each image type using different MT pulses, it is necessary to apply MT pulses multiple times before data acquisition for each image type. For this reason, the imaging time for each image type using different MT pulses is longer than that for imaging without different MT pulses. Furthermore, when multiple MT image types are acquired, the imaging time is further extended. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2004-24783 A Summary of the Invention [Problem to be solved by the invention]

[0004] One of the problems to be solved by the embodiments disclosed in this specification and the drawings is to shorten the imaging time in imaging using different magnetization exchange pulses. However, the problems to be solved by the embodiments disclosed in this specification and the drawings are not limited to the above problem. Problems corresponding to the effects of each configuration shown in the embodiments described later can also be positioned as other problems. [Means for solving the problem]

[0005] The magnetic resonance imaging apparatus according to the present embodiment includes a sequence controller, an allocation unit, and an image generator. The sequence controller executes a first pulse sequence and a second pulse sequence. The first pulse sequence repeats application of a first MT (Magnetization Transfer) pulse and collection of a first MR (Magnetic Resonance) signal corresponding to a high-frequency region of a part of k-space during a transition period until magnetization transitions to a steady state. The second pulse sequence repeats application of a second MT pulse different from the first MT pulse and collection of a third MR signal corresponding to the high-frequency region during the transition period, and repeats application of the second MT pulse and collection of a fourth MR signal corresponding to the low-frequency region in the steady state. The allocation unit allocates the third MR signal to a high-frequency region of another part of the k-space related to the first pulse sequence. The image generator generates an MR image corresponding to the first pulse sequence based on the first MR signal, the second MR signal, and the third MR signal. [Brief description of the drawings]

[0006] [Figure 1] FIG. 1 is a block diagram showing a magnetic resonance imaging apparatus according to an embodiment. [Diagram 2] FIG. 2 is a diagram showing an example of an MT imaging method as a comparative example of the embodiment. [Diagram 3] FIG. 3 is a diagram showing an example of an MT imaging method according to the embodiment. [Figure 4] FIG. 4 is a diagram showing an example of a preparation pulse train in the MT imaging method according to the embodiment. [Diagram 5] FIG. 5 is a diagram showing an example of a change in MT contrast with respect to imaging time in the MT imaging method according to the embodiment. [Figure 6] FIG. 6 is a diagram showing an example of a change in longitudinal magnetization with respect to imaging time in the MT imaging method according to the embodiment. [Figure 7] FIG. 7 is a diagram showing an example of an outline of processing by the allocation function in a case where there are five types of images produced by application of MT pulses according to the embodiment. [Figure 8] FIG. 8 is a flowchart showing an example of a procedure of an MT map generation process according to the embodiment. [Figure 9] FIG. 9 is a diagram illustrating an example of a plurality of functions included in a processing circuit according to a first application example of the embodiment. [Figure 10] FIG. 10 is a diagram showing an outline of processing by the allocation function in a case where there are five types of images produced by application of MT pulses according to a first application example of the embodiment. [Figure 11] FIG. 11 is a diagram illustrating an example of a plurality of functions included in a processing circuit according to a second application example of the embodiment. [Figure 12] FIG. 12 is a diagram showing an outline of processing by the allocation function in a case where there are five types of images produced by application of MT pulses according to a second application example of the embodiment. [Figure 13] FIG. 13 is a flowchart showing an example of a procedure of an MT map generation process according to a second application example of the embodiment. [Figure 14] FIG. 14 is a diagram showing an example of an input user interface UI displayed on the display when the view share rate is 0% according to a fourth application example of the embodiment. [Figure 15] FIG. 15 is a diagram showing an example of an input user interface UI displayed on the display in a case where the view share rate is 20% according to a fourth application example of the embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0007] Hereinafter, with reference to the drawings, an embodiment of a magnetic resonance imaging apparatus (hereinafter referred to as an MRI (Magnetic Resonance Imaging) apparatus) and an image reconstruction method will be described. Note that the embodiments are not limited to the following embodiments. In principle, the contents described in each embodiment can be similarly applied to other embodiments. In the following embodiments, parts with the same reference numerals perform similar operations, and duplicated descriptions will be omitted as appropriate.

[0008] (Embodiment) FIG. 1 is a block diagram showing an MRI apparatus 100 according to an embodiment. As shown in FIG. 1, the MRI apparatus 100 includes a static magnetic field magnet 101, a static magnetic field power supply 102, a gradient magnetic field coil 103, a gradient magnetic field power supply 104, a bed 105, a bed control circuit 106, a transmission coil 107, a transmission circuit 108, a reception coil 109, a reception circuit 110, a sequence control circuit 120, and a computer 130 (also called an image processing device). Note that the MRI apparatus 100 does not include a subject P (e.g., a human body). The configuration shown in FIG. 1 is merely an example. For example, each part in the sequence control circuit 120 and the computer 130 may be appropriately integrated or separated.

[0009] The static magnetic field magnet 101 is a magnet formed in a hollow, approximately cylindrical shape, and generates a static magnetic field in the internal space. The static magnetic field magnet 101 is, for example, a superconducting magnet, and is excited by receiving a current from a static magnetic field power supply 102. The static magnetic field power supply 102 supplies a current to the static magnetic field magnet 101. Note that the static magnetic field magnet 101 may be a permanent magnet, and in this case, the MRI apparatus 100 does not need to include the static magnetic field power supply 102. Also, the static magnetic field power supply 102 may be provided separately from the MRI apparatus 100.

[0010] The gradient magnetic field coil 103 is a hollow coil formed in a substantially cylindrical shape, and is disposed inside the static magnetic field magnet 101. The gradient magnetic field coil 103 is formed by combining three coils corresponding to the mutually orthogonal X, Y, and Z axes, and these three coils are individually supplied with current from a gradient magnetic field power supply 104 to generate gradient magnetic fields whose magnetic field strength changes along the X, Y, and Z axes. The gradient magnetic fields of the X, Y, and Z axes generated by the gradient magnetic field coil 103 are, for example, a slice gradient magnetic field Gs, a phase encoding gradient magnetic field Ge, and a readout gradient magnetic field Gr. The gradient magnetic field power supply 104 supplies current to the gradient magnetic field coil 103.

[0011] The bed 105 includes a top plate 105a on which the subject P is placed, and under the control of a bed control circuit 106, the top plate 105a is inserted into the cavity (imaging port) of the gradient magnetic field coil 103 with the subject P placed thereon. The bed 105 is usually installed so that its longitudinal direction is parallel to the central axis of the static magnetic field magnet 101. Under the control of a computer 130, the bed control circuit 106 drives the bed 105 to move the top plate 105a in the longitudinal direction and up and down directions.

[0012] The transmission coil 107 is disposed inside the gradient magnetic field coil 103, and generates a high-frequency magnetic field upon receiving an RF pulse from a transmission circuit 108. The transmission circuit 108 supplies the transmission coil 107 with an RF pulse corresponding to a Larmor frequency determined by the type of target atom and the magnetic field strength.

[0013] The receiving coil 109 is disposed inside the gradient magnetic field coil 103, and receives magnetic resonance signals (hereinafter, referred to as MR signals) emitted from the subject P due to the influence of a high frequency magnetic field. Upon receiving the MR signals, the receiving coil 109 outputs the received MR signals to the receiving circuitry 110.

[0014] The above-mentioned transmitting coil 107 and receiving coil 109 are merely examples. The transmitting coil 107 and receiving coil 109 may be configured by combining one or more of a coil having only a transmitting function, a coil having only a receiving function, or a coil having a transmitting and receiving function.

[0015] The receiving circuit 110 detects the MR signal output from the receiving coil 109, and generates MR data based on the detected MR signal. Specifically, the receiving circuit 110 generates MR data by digitally converting the MR signal output from the receiving coil 109. The receiving circuit 110 also transmits the generated MR data to the sequence control circuit 120. The receiving circuit 110 may be provided on the side of a gantry device including the static magnetic field magnet 101, the gradient magnetic field coil 103, and the like.

[0016] The sequence control circuit 120 performs imaging of the subject P by driving the gradient magnetic field power supply 104, the transmission circuit 108, and the reception circuit 110 based on sequence information transmitted from the computer 130. Here, the sequence information is information that defines a procedure for performing imaging, and is also referred to as a sequence condition. The sequence information defines the strength of the current that the gradient magnetic field power supply 104 supplies to the gradient magnetic field coil 103 and the timing of supplying the current, the strength of the RF pulse that the transmission circuit 108 supplies to the transmission coil 107 and the timing of applying the RF pulse, the timing of the reception circuit 110 detecting an MR signal, and the like. For example, the sequence control circuit 120 is an integrated circuit such as an application specific integrated circuit (ASIC) or a field programmable gate array (FPGA), a central processing unit (CPU), a micro processing unit (MPU), or other electronic circuit. The sequence control circuit 120 corresponds to a sequence control unit.

[0017] When the sequence control circuit 120 receives MR data from the receiving circuit 110 as a result of driving the gradient magnetic field power supply 104, the transmitting circuit 108, and the receiving circuit 110 to image the subject P, the sequence control circuit 120 transfers the received MR data to the computer 130.

[0018] The computer 130 performs overall control of the MRI apparatus 100, generates images, etc. The computer 130 includes a memory circuitry 132, an input device 141, a display 143, and a processing circuitry 150. The processing circuitry 150 includes an interface function 131, a control function 133, an allocation function 134, and an image generation function 136.

[0019] Each processing function performed by the interface function 131, the control function 133, the allocation function 134, and the image generation function 136 is stored in the memory circuitry 132 in the form of a program executable by a computer. The processing circuitry 150 is a processor that realizes the function corresponding to each program by reading the program from the memory circuitry 132 and executing it. In other words, the processing circuitry 150 in a state in which each program has been read has each function shown in the processing circuitry 150 in FIG.

[0020] In FIG. 1, the processing functions performed by the interface function 131, the control function 133, the allocation function 134, and the image generation function 136 are described as being realized by a single processing circuit 150. However, the processing circuit 150 may be configured by combining a plurality of independent processors, and each processor may execute a program to realize the functions.

[0021] In other words, each of the above-mentioned functions may be configured as a program and one processing circuit 150 may execute each program, or a specific function may be implemented in a dedicated, independent program execution circuit.

[0022] The term "processor" used in the above description means a circuit such as a CPU, a GPU (Graphical Processing Unit), an application specific integrated circuit, a programmable logic device (e.g., a Simple Programmable Logic Device (SPLD), a Complex Programmable Logic Device (CPLD), and a Field Programmable Gate Array (FPGA)). The processor realizes functions by reading and executing a program stored in the memory circuit 132.

[0023] Instead of storing the program in the memory circuitry 132, the program may be directly built into the circuitry of the processor. In this case, the processor realizes the function by reading and executing the program built into the circuitry. The bed control circuitry 106, the transmission circuitry 108, the reception circuitry 110, etc. are also similarly composed of electronic circuits such as the above-mentioned processor.

[0024] The processing circuitry 150 transmits sequence information to the sequence control circuit 120 through the interface function 131, and receives MR data from the sequence control circuit 120. Furthermore, when the processing circuitry 150 having the interface function 131 receives MR data, it stores the received MR data in the memory circuitry 132. The processing circuitry 150 that realizes the interface function 131 corresponds to an interface unit. The MR data stored in the memory circuitry 132 is arranged in k-space by the control function 133. The memory circuitry 132 stores the k-space data.

[0025] The memory circuitry 132 stores the MR data received by the processing circuitry 150 having the interface function 131, the k-space data arranged in the k-space by the processing circuitry 150 having the allocation function 134, the image data generated by the processing circuitry 150 having the image generation function 136, etc. For example, the memory circuitry 132 is realized by a semiconductor memory element such as a RAM (Random Access Memory) or a flash memory, a hard disk, an optical disk, etc.

[0026] The input device 141 accepts various instructions and information input from a user. The input device 141 is, for example, a pointing device such as a mouse or a trackball, a selection device such as a mode changeover switch, or an input device such as a keyboard. The display 143 displays, under the control of the processing circuit 150 having the control function 133, a GUI (Graphical User Interface) for accepting input of imaging conditions, an image generated by the processing circuit 150 having the image generation function 136, and the like. The display 143 is, for example, a display device such as a liquid crystal display.

[0027] The processing circuit 150 performs overall control of the MRI apparatus 100 by the control function 133, and controls imaging, image generation, image display, and the like. For example, the processing circuit 150 having the control function 133 accepts input of imaging conditions (imaging parameters, etc.) on a GUI, and generates sequence information according to the accepted imaging conditions. The processing circuit 150 having the control function 133 also transmits the generated sequence information to the sequence control circuit 120. The processing circuit 150 realizing the control function 133 corresponds to a control unit. The processing circuit 150 reads out k-space data from the storage circuit 132 by the image generation function 136, and generates an image by performing reconstruction processing such as Fourier transform on the read out k-space data. The processing circuit 150 realizing the image generation function 136 corresponds to an image generation unit.

[0028] A brief description will be given of the Chemical Exchange Saturation Transfer (CEST) effect in this embodiment. Protons in free water (bulk water) and protons in polymers are exchanged with each other. For example, protons in polymers such as amide groups (-NH), hydroxyl groups (-OH), and amino groups (-NH2) are exchangeable protons. The CEST effect is described using quantities called "Z spectrum" and "MTRasym spectrum." Imaging related to the CEST effect is an MR imaging technique that utilizes the exchange of protons such as amide groups (-NH), hydroxyl groups (-OH), and amino groups (-NH2) with protons in free water.

[0029] The MT effect related to this embodiment will be described. The MT effect (also called Magnetization Transfer Contrast (MTC)) is used to generate images that utilize image contrast between blood (blood flow) and tissue in applications such as, but not limited to, MR Angiography (MRA). The MT effect is based on chemical exchange and cross relaxation between protons (e.g., hydrogen protons) of multiple types of proton pools, such as chemical exchange, cross relaxation, and dipole relaxation between free water (bulk water) and various macromolecules. Each of the multiple types of proton pools may contain protons bound in different ways and may have a different Larmor frequency from the protons in the other proton pools.

[0030] The MT effect is shown by an MT (magnetization transfer ratio) R map by the MT method or an ih (inhomogeneous) MTR map by the ihMT method. The MTR map is, for example, a map image in which the MTR (magnetization transfer ratio) value calculated for each pixel based on the collected MR signal is arranged in the pixel. The MTR map is an image showing the distribution of MTR values. The MTR map is, for example, a map image in which the MTR value calculated for each pixel based on the collected MR signal is arranged in the pixel. The MTR map corresponds to an image showing the distribution of MTR values ​​(MTR image).

[0031] The ihMTR map is, for example, a map image in which the ihMTR (inhomogeneous magnetization transfer ratio (ihMT ratio)) value calculated for each pixel based on the collected MR signal is arranged at the pixel. The ihMTR map corresponds to an image (ihMTR image) showing the distribution of the ihMTR values.

[0032] In the magnetic resonance imaging technique related to the CEST effect and the MT effect, the sequence control circuit 120 applies a frequency-selective RF (Radio Frequency) pulse (hereinafter referred to as an MT (Magnetic Transfer) pulse) to the subject P before collecting MR signals, the frequency being an off-resonance frequency that is separate from the resonance frequency of free water and is the resonance frequency of exchangeable protons (e.g., protons of a polymer). The MT pulse corresponds to a preparation pulse.

[0033] In the following, in order to make the explanation more specific, an imaging method related to the MT effect (hereinafter referred to as the MT imaging method) will be taken as an example. In this case, the image generated by the image generating function 136 is assumed to be, for example, an image such as an MTR image or an ihMTR image (hereinafter referred to as an MT map image). The MT map image is derived by calculation as described above, and is therefore also called a calculated image.

[0034] FIG. 2 is a diagram showing an example of an MT imaging method as a comparative example. As shown in FIG. 2, a preparation pulse train (MT pulse number of about several tens to several hundreds) of about several seconds is applied before data collection of MR signals. Data collection is performed, for example, by two-dimensional collection using a single shot. In the comparative example shown in FIG. 2, data collection is performed in a steady state in which the effect of the application of the MT pulse on the contrast (hereinafter referred to as MT contrast) of an image (such as an MTR image and an ihMTR image) becomes steady. The steady state corresponds to, for example, a period in which the temporal change of the MT contrast accompanying the application of the MT pulse is constant or is equal to or greater than a predetermined threshold. In other words, the steady state corresponds to a state in which the magnitude of longitudinal magnetization of protons in an imaging target becomes steady due to the application of the MT pulse. The steady state can be set, for example, by a simulation of the Bloch equation using the image type and sequence information described later.

[0035] 2, the preparation pulse train is applied to the subject P for about several seconds during a transition period from the start of application of the MT pulse to the subject P to a steady state (hereinafter referred to as the steady state transition period). The steady state transition period corresponds to a non-steady state in which the MT contrast changes over time with application of the MT pulse. In other words, the steady state transition period corresponds to a period in which the magnitude of longitudinal magnetization related to protons in the imaging target changes (becomes non-steady) due to application of the MT pulse (non-steady state). That is, in the comparative example, first, a preparation pulse train consisting of a plurality of MT pulses is applied to the subject P, and data collection is performed in the steady state.

[0036] FIG. 3 is a diagram showing an example of the MT imaging method in this embodiment. The scale of the time axis in FIG. 3 is shown shorter than that shown in FIG. 2. As shown in FIG. 3, a preparation pulse train (MT pulse number of about 1 to about 10) of about several tens to several hundreds of msec is applied to the subject P before data collection of MR signals by the control of the sequence control circuit 120 based on sequence information corresponding to the MT imaging method. Thereafter, data collection is performed, for example, by three-dimensional collection using Multi-Shot. Note that data collection may be two-dimensional collection. In the following, for the sake of concrete explanation, data collection in the MT imaging method is described as being performed three-dimensionally.

[0037] As shown in Fig. 3, in the MT imaging method, a preparation pulse train having a smaller number of MT pulses than that in the comparative example is applied to the subject P during a short TR in a steady state transition period, and MR signals (hereinafter referred to as first MR signals) are collected for a high frequency region in k-space. Specifically, as shown in Fig. 3, application of the preparation pulse train and collection of the first MR signals for the high frequency region are repeatedly performed during the steady state transition period. The high frequency region is a frequency region that has a smaller effect on the MT contrast than the low frequency region.

[0038] Next, in the MT imaging method, in a steady state, a preparation pulse train having a smaller number of MT pulses than in the comparative example is applied to the subject P, and MR signals (hereinafter referred to as second MR signals) are collected for the low-frequency region in k-space. Specifically, in the steady state, application of the preparation pulse train and collection of the second MR signals for the low-frequency region are repeatedly performed. The low-frequency region is a frequency region in which the influence on the MT contrast is greater than that of the high-frequency region. Therefore, according to the MT imaging method, the MT contrast is ensured in the images (MTR images and ihMTR images, etc.) obtained by applying MT pulses, similar to the comparative example. In addition, according to the MT imaging method, the imaging time can be shortened compared to the comparative example.

[0039] 4 is a diagram showing an example of a preparation pulse train in the MT imaging method. As shown in FIG. 4, after each of the MT pulses in the preparation pulse train is applied, for example, a spoiler gradient magnetic field is applied to the subject P.

[0040] FIG. 5 is a diagram showing an example of a change in MT contrast (e.g., ihMTR (ihMT ratio)) with respect to imaging time in the MT imaging method. As shown in FIG. 5, the MT contrast increases with application of a preparation pulse train in the MT imaging method. On the other hand, the MT contrast decreases during data collection. As shown in FIG. 5, during the steady-state transition period (unsteady state), the MT contrast decreases during collection of the first MR signal, and increases by a larger amount than the amount of decrease in MT contrast associated with collection of the first MR signal when the preparation pulse train is applied. As a result, during the steady-state transition period, the MT contrast increases to the value of the MT contrast in the steady state. Also, as shown in FIG. 5, in the steady state, the MT contrast decreases during collection of the second MR signal, and increases by an amount equal to the amount of decrease in MT contrast associated with collection of the second MR signal when the preparation pulse train is applied. As a result, during collection of the second MR signal in the steady state, the MT contrast becomes approximately constant as shown in FIG. 5.

[0041] FIG. 6 is a diagram showing an example of change in longitudinal magnetization with respect to imaging time in the MT imaging method. As shown in FIG. 6, longitudinal magnetization decreases with application of a preparation pulse train in the MT imaging method. On the other hand, longitudinal magnetization increases during data collection. As shown in FIG. 6, during the steady-state transition period (unsteady state), longitudinal magnetization increases during collection of the first MR signal, and decreases by a larger amount than the increase in longitudinal magnetization associated with collection of the first MR signal when the preparation pulse train is applied. As a result, during the steady-state transition period, longitudinal magnetization decreases to the value of longitudinal magnetization in the steady state. Also, as shown in FIG. 6, in the steady state, longitudinal magnetization increases during collection of the second MR signal, and decreases by an amount equivalent to the increase in longitudinal magnetization associated with collection of the second MR signal when the preparation pulse train is applied. As a result, during collection of the second MR signal in the steady state, longitudinal magnetization becomes approximately constant as shown in FIG. 6. As shown in FIG. 6, the steady-state transition period corresponds to a transition period until magnetization transitions to the steady state.

[0042] As explained in Fig. 3 to Fig. 6, the MT imaging method according to this embodiment has a first pulse sequence that repeats application of at least one MT pulse and acquisition of a first MR signal corresponding to one high frequency region of k-space during a transition period, and repeats application of at least one MT pulse and acquisition of a second MR signal corresponding to a low frequency region of k-space during a steady state. In other words, the first pulse sequence repeats application of a first MT pulse and acquisition of a first MR signal corresponding to a part of a high frequency region of k-space during a transition period until magnetization transitions to a steady state, and repeats application of the first MT pulse and acquisition of a second MR signal corresponding to a low frequency region of k-space during the steady state.

[0043] In addition, the MT imaging method according to this embodiment further includes a second pulse sequence. The second pulse sequence uses an MT pulse different from the MT pulse in the first pulse sequence to collect MR signals in a similar procedure to the first pulse sequence. Specifically, the second pulse sequence repeats application of a second MT pulse different from the first MT pulse and collection of a third MR signal corresponding to a high frequency region during the transition period, and repeats application of the second MT pulse and collection of a fourth MR signal corresponding to a low frequency region during the steady state.

[0044] The difference in MT pulses is, for example, when the sequence is imaging related to the CEST effect, the difference in the offset value of the MT pulse frequency (deviation from the resonance frequency (0 ppm) of free water caused by a static magnetic field). Also, the difference in MT pulses is, for example, when the sequence is imaging related to the ihMT method, the difference in the change in polarity (±) of the frequency (offset value) based on the resonance frequency (0 ppm) of free water caused by a static magnetic field within the preparation pulse train (MT pulse train). The difference in MT pulses is due to the different target substances for MT images.

[0045] In addition, the MT imaging method according to the present embodiment is not limited to the first pulse sequence and the second pulse sequence, and may have a plurality of pulse sequences according to the image type by applying different MT pulses. The high frequency region has a high frequency band in at least one direction of the phase encoding direction and the slice encoding direction in the k-space. In the following, for the sake of concrete explanation, the high frequency region is described as having a high frequency band in the slice encoding direction in the k-space.

[0046] The processing circuitry 150 assigns the third MR signal corresponding to one high frequency region in the k space and collected by executing the second pulse sequence to the other high frequency region of the k space related to the first pulse sequence by the assignment function 134. That is, the assignment function 134 assigns the third MR signal to the high frequency region of another part of the k space related to the first pulse sequence. This completes the focusing of the MR signals (more specifically, also referred to as MR data or k space data) in the k space corresponding to the first pulse sequence (hereinafter referred to as the first k space). Specifically, the assignment function 134 assigns the first MR signal to one high frequency region, the second MR signal to the low frequency region, and the third MR signal to the other high frequency region in the first k space. The processing circuitry 150 that realizes the assignment function 134 corresponds to an assignment unit.

[0047] When the MT imaging method according to the present embodiment has a plurality of pulse sequences, the allocation function 134, for example, allocates MR signals in one high frequency region acquired by a chronologically subsequent pulse sequence in chronologically adjacent pulse sequences to the other high frequency region of the k-space corresponding to the chronologically previous sequence (hereinafter referred to as the previous k-space). Also, the allocation function 134 allocates MR signals in one high frequency region acquired by a chronologically previous pulse sequence in chronologically adjacent pulse sequences to one high frequency region of the previous k-space, and allocates MR signals in a low frequency region acquired by a chronologically previous pulse sequence to one high frequency region of the previous k-space.

[0048] Fig. 7 is a diagram showing an example of an outline of processing by the allocation function 134 in the case where there are five types of image types by application of MT pulses, that is, in the case where the MT imaging method according to this embodiment has five types of pulse sequences. Each of the arrows Vol1 to Vol5 on the time axis shown in Fig. 7 corresponds to the imaging time of each of the imaging volumes corresponding to image types 1 to 5. The arrows showing the allocation of MR signals in Fig. 7 indicate that MR signals (k-space data) of one high-frequency region at the start point of the arrow are allocated to the other high-frequency region at the end point of the arrow to share at least a part of the k-space data. Sharing of k-space data is also called view sharing.

[0049] As shown in FIG. 7, the sequence control circuit 120 executes a first pulse sequence for a volume Vol1 corresponding to an image type 1. As a result, a first MR signal corresponding to one high frequency region V1H1 of the first k-space kVol1 related to the volume Vol1 and a second MR signal corresponding to a low frequency region V1L of the first k-space kVol1 are acquired. Next, the sequence control circuit 120 executes a second pulse sequence for a volume Vol2 corresponding to an image type 2. As a result, a third MR signal corresponding to one high frequency region V2H1 of the k-space (hereinafter referred to as the second k-space) kVol2 related to the volume Vol2 and a fourth MR signal corresponding to the low frequency region V2L of the second k-space kVol2 are acquired. At this time, the allocation function 134 allocates the first MR signal to one high frequency region V1H1, allocates the second MR signal to the low frequency region V1L, and allocates the third MR signal to the other high frequency region V1H2 in the first k-space kVol1. This completes filling of the MR data into the first k-space kVol1.

[0050] After executing the second pulse sequence, the sequence control circuit 120 executes the third pulse sequence for the volume Vol3 corresponding to the image type 3. As a result, a fifth MR signal corresponding to one high frequency region V3H1 of the k-space (hereinafter referred to as the third k-space) kVol3 related to the volume Vol3 and a sixth MR signal corresponding to the low frequency region V3L of the third k-space kVol3 are acquired. At this time, the allocation function 134 allocates the third MR signal to one high frequency region V2H1 in the second k-space kVol2, allocates the fourth MR signal to the low frequency region V2L, and allocates the fifth MR signal to the other high frequency region V2H2. As a result, filling of the MR data into the second k-space kVol2 is completed.

[0051] After executing the third pulse sequence, the sequence control circuit 120 executes the fourth pulse sequence on the volume Vol4 corresponding to the image type 4. As a result, the seventh MR signal corresponding to one high frequency region V4H1 of the k-space (hereinafter referred to as the fourth k-space) kVol4 related to the volume Vol4 and the eighth MR signal corresponding to the low frequency region V4L of the fourth k-space kVol4 are acquired. At this time, the allocation function 134 allocates the fifth MR signal to one high frequency region V3H1 in the third k-space kVol3, allocates the sixth MR signal to the low frequency region V3L, and allocates the seventh MR signal to the other high frequency region V3H2. As a result, filling of the MR data into the third k-space kVol3 is completed.

[0052] After executing the fourth pulse sequence, the sequence control circuit 120 executes the fifth pulse sequence on the volume Vol5 corresponding to the image type 5. As a result, a ninth MR signal corresponding to one high frequency region V5H1 of the k-space (hereinafter referred to as the fifth k-space) kVol5 related to the volume Vol5 and a tenth MR signal in the low frequency region V4L of the fifth k-space kVol5 are acquired. At this time, the allocation function 134 allocates the seventh MR signal to one high frequency region V4H1, the eighth MR signal to the low frequency region V4L, and the ninth MR signal to the other high frequency region V4H2 in the fourth k-space. As a result, filling of the MR data into the fourth k-space is completed.

[0053] In addition, the allocation function 134 allocates the ninth MR signal to one high frequency region V5H1 in the 5th k-space, allocates the tenth MR signal to the low frequency region V5L, and allocates the first MR signal to the other high frequency region V5H2 in the 5th k-space. This completes filling of the MR data into the 5th k-space kVol5. That is, the other high frequency region of the k-space related to the pulse sequence executed last in the MT imaging method according to this embodiment is filled with MR signals corresponding to one high frequency region of the k-space related to the pulse sequence executed first in the MT imaging method. Note that, when MR signals related to the other high frequency region V5H2 are collected in the 5th sequence, the allocation function 134 fills the 5th k-space kVol5 with MR data based on the MR signals collected by the 5th sequence. That is, the pulse sequence executed last in the MT imaging method according to this embodiment may collect MR signals corresponding to the entire k-space.

[0054] As shown in Fig. 7, the imaging period in the high frequency region V1H1 for image type 1, the imaging period in the high frequency region V2H1 for image type 2, the imaging period in the high frequency region V3H1 for image type 3, the imaging period in the high frequency region V4H1 for image type 4, and the imaging period in the high frequency region V1H1 for image type 5 correspond to steady state transition periods. Also, as shown in Fig. 7, the imaging period in the low frequency region V1L for image type 1, the imaging period in the low frequency region V2L for image type 2, the imaging period in the low frequency region V3L for image type 3, the imaging period in the low frequency region V4L for image type 4, and the imaging period in the low frequency region V5L for image type 5 correspond to steady states.

[0055] As shown in Fig. 7, imaging in the high frequency region V2H1 is performed after imaging in the low frequency region V1L, imaging in the high frequency region V3H1 is performed after imaging in the low frequency region V2L, imaging in the high frequency region V4H1 is performed after imaging in the low frequency region V3L, and imaging in the high frequency region V5H1 is performed after imaging in the low frequency region V4L. This imaging order is due to the fact that the target material of the MT pulse is different for the MT image of each image type. That is, even if the longitudinal magnetization is not fully recovered after imaging in the low frequency region, such an imaging order can be realized because the target material is different for each image type, and the MT pulse is different for each image type.

[0056] The processing circuitry 150 generates an MR image corresponding to the first pulse sequence based on the first MR signal, the second MR signal, and the third MR signal by the image generation function 136. For example, the image generation function 136 generates a map image showing the MT effect (hereinafter, referred to as an MT map image) for the volume Vol1 corresponding to the image type 1 based on the MR data filled into the first k-space kVol1. A known method can be used to generate the MT map image, and therefore a description thereof will be omitted.

[0057] The processing circuit 150 generates an MT map image for volume Vol2 corresponding to image type 2 based on the MR data filled into the second k-space kVol2 by the image generation function 136. The image generation function 136 generates an MT map image for volume Vol3 corresponding to image type 3 based on the MR data filled into the third k-space kVol3. The image generation function 136 generates an MT map image for volume Vol4 corresponding to image type 4 based on the MR data filled into the fourth k-space kVol4. The image generation function 136 generates an MT map image for volume Vol2 corresponding to image type 5 based on the MR data filled into the fifth k-space kVol5.

[0058] The overall configuration of the MRI apparatus 100 according to the embodiment has been described above. With this configuration, the MRI apparatus 100 according to the embodiment executes a process (hereinafter, referred to as an MT map generation process) for generating an MT map image with a shorter imaging time than the comparative example, as shown in Fig. 7. The MT map generation process is a process in which an MT imaging method having a plurality of sequences is executed by the sequence control circuit 120, MR signals in a steady state transition period are assigned by the assignment function 134, and an MT map image is generated.

[0059] Hereinafter, the procedure of the MT map generation process will be described with reference to Fig. 8. Fig. 8 is a flowchart showing an example of the procedure of the MT map generation process. For the sake of simplicity, the MT imaging method according to this embodiment will be described as including the first to fifth pulse sequences as shown in Fig. 7.

[0060] (MT map generation process) (Step S801) The processing circuit 150 determines the steady state transition period based on the image type and sequence information in the MT imaging method by the control function 133. For example, when the image type of the MT map image and sequence information corresponding to the image type are input by the user via the input device 141, the control function 133 determines the steady state transition period by, for example, simulating the Bloch equation using the image type and the sequence information.

[0061] (Step S802) The processing circuitry 150 generates a plurality of pulse sequences (first to fifth pulse sequences) in the MT imaging method by the control function 133 based on the view share ratio set by the user via the input device 141 and the determined steady state transition period. The view share ratio corresponds to the ratio of the other high frequency region to the k space, in other words, the ratio (sharing ratio) of k space data shared with one high frequency region of another image type to the total k space data. The view share ratio may be expressed, for example, as the ratio of imaging time in one high frequency region of another image type to the total data acquisition time in the k space. The control function 133 sequentially outputs the generated plurality of pulse sequences to the sequence control circuitry 120. The processing in steps S801 and S802 may be realized, for example, by a sequence setting function different from the control function 133. The processing circuitry 150 that realizes the sequence setting function corresponds to a sequence setting unit.

[0062] (Step S803) The sequence control circuit 120 collects MR signals according to an MT imaging method having a plurality of pulse sequences. That is, the sequence control circuit 120 sequentially executes a plurality of pulse sequences, for example, as shown in Fig. 7. As a result, the sequence control circuit 120 acquires the first to tenth MR signals, for example, as shown in Fig. 7.

[0063] (Step S804) The processing circuitry 150 allocates MR signals to k-spaces according to the view share ratio by the allocation function 134. For example, when there are n types of sequences in the MT imaging method (n is a natural number equal to or greater than 2), the allocation function 134 allocates, in the (n-1)th k-space, MR signals acquired in one high-frequency region of the (n-1)th k-space by the (n-1)th pulse sequence to one high-frequency region, MR signals acquired in the low-frequency region of the (n-1)th k-space by the (n-1)th pulse sequence to a low-frequency region, and MR signals acquired in one high-frequency region of the (n)th k-space by the (n)th pulse sequence to the other high-frequency region.

[0064] (Step S805) The processing circuit 150 generates MT map images corresponding to a plurality of pulse sequences based on the assigned MR signals by the image generating function 136. The image generating function 136 may generate an MT map image based on the data of the k-space filled with MR data, triggered by the completion of filling the k-space with MR data. For example, in the case shown in FIG. 7, the image generating function 136 generates an MT map image corresponding to the first sequence based on the MR data filled in the first k-space kVol1 during the execution of the third sequence. The image generating function 136 generates an MT map image corresponding to the second sequence based on the MR data filled in the second k-space kVol2 during the execution of the fourth sequence. The image generating function 136 generates an MT map image corresponding to the third sequence based on the MR data filled in the third k-space kVol3 during the execution of the fifth sequence.

[0065] The MRI apparatus 100 according to the embodiment described above executes a first pulse sequence in which the application of a first MT pulse and the acquisition of a first MR signal corresponding to a part of a high frequency region of the k-space are repeated during a transition period until the magnetization transitions to a steady state, and the application of the first MT pulse and the acquisition of a second MR signal corresponding to a low frequency region of the k-space are repeated during the steady state, and a second pulse sequence in which the application of a second MT pulse different from the first MT pulse and the acquisition of a third MR signal corresponding to the high frequency region are repeated during the transition period, and the application of the second MT pulse and the acquisition of a fourth MR signal corresponding to the low frequency region are repeated during the steady state. In addition, the MRI apparatus 100 according to the embodiment assigns the third MR signal acquired by the execution of the second pulse sequence to the other high frequency region of the first k-space kVol1, and generates an MT map image corresponding to the first pulse sequence based on the first to third MR signals.

[0066] As a result, according to the present MRI apparatus 100, MR signals related to one high frequency region are acquired during the steady state transition period as shown in Fig. 5 and Fig. 6, and acquisition of MR signals in the other high frequency region, which has an extremely small effect on image contrast as shown in Fig. 7, can be omitted, so that the imaging time for multiple image types related to the MT effect and the CEST effect can be made more efficient and shortened while maintaining the contrast of the MT map image. For these reasons, according to the MRI apparatus 100 of this embodiment, the throughput of an examination in which multiple image types related to the MT effect and the CEST effect are desired can be improved, and the burden on the subject P related to the imaging time in the examination can be reduced.

[0067] (First application example) The first application example is to improve the SNR of the MT map generated by the MT map generation process by adding MR signals. Fig. 9 is a diagram showing an example of a plurality of functions of the processing circuitry 151 in this application example. The processing circuitry 151 shown in Fig. 9 is mounted on the MRI device 100 in place of the processing circuitry 150. Among the various components in the processing circuitry 151 and the MRI device 100, components different from those in the embodiment will be described.

[0068] The sequence control circuit 120 acquires MR signals multiple times in accordance with a preset number of additions for the low-frequency region in the MT imaging method. For example, the sequence control circuit 120 executes acquisition of the second MR signal multiple times in the first pulse sequence according to the number of additions. The sequence control circuit 120 also executes multiple pulse sequences including the second pulse sequence, each having a different MT pulse, according to the number of additions.

[0069] The processing circuit 151 averages multiple MR signals related to the low frequency region in the same pulse sequence by the addition function 135, and generates an added signal related to the low frequency region (hereinafter referred to as a low frequency added signal). For example, the addition function 135 averages the second MR signal over the number of additions to generate a low frequency added signal. Also, the addition function 135 averages multiple MR signals related to one high frequency region in a different pulse sequence over the number of additions to generate an added signal related to the high frequency region (hereinafter referred to as a high frequency added signal). For example, the addition function 135 averages multiple third MR signals in multiple pulse sequences over the number of additions to generate a high frequency added signal. The processing circuit 151 that realizes the addition function 135 corresponds to an adder.

[0070] The processing circuitry 151 assigns MR signals in one high frequency region acquired by the pulse sequence in the k space corresponding to the pulse sequence to one high frequency region of the k space corresponding to the pulse sequence, assigns a low frequency addition signal to the low frequency region, and assigns a high frequency addition signal to the other high frequency region by the assignment function 134. This completes the filling of the MR signals in the k space corresponding to the pulse sequence.

[0071] The processing circuitry 151 generates an MT map image corresponding to the pulse sequence based on the MR data in the filled k-space by the image generation function 136. For example, the image generation function 136 generates an MR image based on the first MR signal, the low-frequency sum signal, and the high-frequency sum signal.

[0072] Hereinafter, the MT map generation process involving addition allocation will be described with reference to FIG. 10. FIG. 10 is a diagram showing an outline of the process by the allocation function 134 in the case where there are five types of image types by application of MT pulses, that is, in the case where the MT imaging method of this modified example has five types of pulse sequences. The arrows of Vol1 to Vol5 on the time axis shown in FIG. 10 correspond to the imaging time of each imaging volume corresponding to image type 1 to image type 5. The arrows showing the allocation of MR signals in FIG. 10 correspond to the sharing (view sharing) of k-space data. Hereinafter, with reference to FIG. 10, the process different from the description in FIG. 7 will be described. Also, for the sake of concreteness, the number of additions is assumed to be two. Note that the number of additions is not limited to two, and can be set arbitrarily as long as it is a natural number of two or more.

[0073] As shown in Fig. 10, the sequence control circuit 120 executes acquisition of the second MR signal multiple times in the first pulse sequence according to the number of additions. That is, the sequence control circuit 120 executes acquisition of the second MR signal twice in the first pulse sequence. As shown in Fig. 10, the second acquisition of the second MR signal is executed immediately after the first acquisition of the second MR signal in the steady state.

[0074] The sequence control circuit 120 executes a plurality of pulse sequences, including the second pulse sequence, in which the MT pulses in the first pulse sequence are different, according to the number of additions. When the number of additions is 2, the sequence control circuit 120 needs to execute at least the second pulse sequence. In the example shown in FIG. 10, since there are five image types, the number of additions can be set up to 4.

[0075] 10, the sequence control circuit 120 executes acquisition of a fourth MR signal twice for the low-frequency region V2L. The sequence control circuit 120 executes acquisition of a sixth MR signal twice for the low-frequency region V3L. The sequence control circuit 120 executes acquisition of an eighth MR signal twice for the low-frequency region V4L. The sequence control circuit 120 executes acquisition of a tenth MR signal twice for the low-frequency region V5L.

[0076] The addition function 135 averages the second MR signal over the number of additions to generate a first low-frequency sum signal. That is, the addition function 135 averages two second MR signals to generate a first low-frequency sum signal. The addition function 135 averages two fourth MR signals to generate a second low-frequency sum signal. The addition function 135 averages two sixth MR signals to generate a third low-frequency sum signal. The addition function 135 averages two eighth MR signals to generate a fourth low-frequency sum signal. The addition function 135 averages two tenth MR signals to generate a fifth low-frequency sum signal.

[0077] The addition function 135 averages a plurality of third magnetic resonance signals in a plurality of pulse sequences over the number of additions to generate a high frequency sum signal. Specifically, the addition function 135 averages the third MR signal and the fifth MR signal to generate a first high frequency sum signal. The addition function 135 averages the fifth MR signal and the seventh MR signal to generate a second high frequency sum signal. The addition function 135 averages the seventh MR signal and the ninth MR signal to generate a third high frequency sum signal. The addition function 135 averages the ninth MR signal and the first MR signal to generate a fourth high frequency sum signal. The addition function 135 averages the first MR signal and the third MR signal to generate a fifth high frequency sum signal.

[0078] The allocation function 134 allocates the low-frequency sum signal to the low-frequency region of the k-space, allocates the high-frequency sum signal to the other high-frequency region of the k-space, and allocates the MR signal related to one high-frequency region to one high-frequency region. This completes filling of the MR data in the k-space. Specifically, in the first k-space kVol1, the allocation function 134 allocates the first MR signal to one high-frequency region V1H1, allocates the first low-frequency sum signal to the low-frequency region V1L, and allocates the first high-frequency sum signal to the other high-frequency region V1H2. This completes filling of the MR data in the first k-space kVol1.

[0079] In addition, the allocation function 134 allocates the third MR signal to one high frequency region V2H1, allocates the second low frequency addition signal to the low frequency region V2L, and allocates the second high frequency addition signal to the other high frequency region V2H2 in the second k space kVol2. This completes filling of the MR data in the second k space kVol2. In the third k space kVol3, the allocation function 134 allocates the fifth MR signal to one high frequency region V3H1, allocates the third low frequency addition signal to the low frequency region V3L, and allocates the third high frequency addition signal to the other high frequency region V3H2. This completes filling of the MR data in the third k space kVol3.

[0080] In addition, the allocation function 134 allocates the seventh MR signal to one high frequency region V4H1, allocates the fourth low frequency addition signal to the low frequency region V4L, and allocates the fourth high frequency addition signal to the other high frequency region V4H2 in the 4k space kVol4. This completes filling of the 4k space kVol4 with MR data. In the 5k space kVol5, the allocation function 134 allocates the ninth MR signal to one high frequency region V5H1, allocates the fifth low frequency addition signal to the low frequency region V5L, and allocates the fifth high frequency addition signal to the other high frequency region V5H2. This completes filling of the 5k space kVol5 with MR data.

[0081] The image generating function 136 generates an MT map image based on the first magnetic resonance signal, the low frequency addition signal, and the high frequency addition signal. Specifically, the image generating function 136 generates an MT map image corresponding to the first pulse sequence based on the first MR signal, the first low frequency addition signal, and the first high frequency addition signal. Also, the image generating function 136 generates an MT map image corresponding to the second pulse sequence based on the third MR signal, the second low frequency addition signal, and the second high frequency addition signal. The image generating function 136 generates an MT map image corresponding to the third pulse sequence based on the fifth MR signal, the third low frequency addition signal, and the third high frequency addition signal. The image generating function 136 generates an MT map image corresponding to the fourth pulse sequence based on the seventh MR signal, the fourth low frequency addition signal, and the fourth high frequency addition signal. The image generating function 136 generates an MT map image corresponding to the fifth pulse sequence based on the ninth MR signal, the fifth low frequency addition signal, and the fifth high frequency addition signal.

[0082] The MRI apparatus 100 according to the first application example of the embodiment described above executes collection of second MR signals in the first pulse sequence multiple times according to the number of additions, executes multiple pulse sequences including the second pulse sequence according to the number of additions, averages the second MR signals over the number of additions to generate a low-frequency summation signal, averages multiple third magnetic resonance signals in the multiple pulse sequences over the number of additions to generate a high-frequency summation signal, assigns the low-frequency summation signal to a low-frequency region of k-space and assigns the high-frequency summation signal to the other high-frequency region of k-space, and generates an MT map image based on the first MR signal, the low-frequency summation signal, and the high-frequency summation signal.

[0083] As a result, according to the present MRI apparatus 100, by using the MT imaging method having the number of additions, MR signals related to one high frequency region can be collected multiple times during the steady state transition period as shown in Fig. 5 and Fig. 6, and collection of MR signals in the other high frequency region can be omitted as shown in Fig. 10, so that the imaging time for multiple image types related to the MT effect and the CEST effect can be made more efficient and shortened, and furthermore, the SNR of the generated MT map image can be improved by the signal addition effect. Other effects are similar to those of the embodiment, so description thereof will be omitted.

[0084] (Second application example) The second application example is to select an MR signal to be assigned to the other high frequency region according to an image corresponding to a low frequency region, with respect to the assignment function 134 in the embodiment. Fig. 11 is a diagram showing an example of a plurality of functions of the processing circuitry 153 in this application example. The processing circuitry 153 shown in Fig. 11 is mounted on the MRI apparatus 100 in place of the processing circuitry 151. Among the various components in the processing circuitry 153 and the MRI apparatus 100, components different from those in the embodiment will be described.

[0085] The sequence control circuit 120 executes a plurality of pulse sequences including the second pulse sequence, each of which corresponds to a plurality of image types having different MT pulses.

[0086] The processing circuitry 153 generates a first low-frequency image based on the second MR signal by the image generating function 136. Also, the image generating function 136 generates a plurality of low-frequency images corresponding to the plurality of pulse sequences based on the MR signals in the low-frequency region in the plurality of pulse sequences.

[0087] The processing circuit 153 selects an image type similar to the first low-frequency image from the multiple low-frequency images based on the similarity between the multiple low-frequency images and the first low-frequency image by the selection function 137. Specifically, the selection function 137 calculates the similarity regarding the contrast of the images between the multiple low-frequency images and the first low-frequency image, with one image of the two images being a reference (hereinafter referred to as a reference image) and the other image (hereinafter referred to as a comparison image). For example, the similarity is calculated by performing a statistical calculation on multiple pixels in the two images. Since a known method can be applied to the calculation of the similarity, a description thereof will be omitted. The selection function 137 selects the image type of the low-frequency image with the maximum similarity between each of the multiple low-frequency images and the first low-frequency image. The processing circuit 153 that realizes the selection function 137 corresponds to a selection unit.

[0088] The processing circuitry 153 allocates the third MR signal related to the selected image type to a high frequency region in another part of the k-space by the allocation function 134. That is, the allocation function 134 allocates the magnetic resonance signal corresponding to one high frequency region related to the selected image type to the other high frequency region related to the reference image serving as a basis for the selection.

[0089] 12 is a diagram showing an outline of processing by the allocation function 134 when there are five types of image types by application of MT pulses, that is, when the MT imaging method of this application example has five types of pulse sequences. Each of the arrows Vol1 to Vol5 on the time axis shown in FIG. 12 corresponds to the imaging time of each of the imaging volumes corresponding to image types 1 to 5. The arrows showing the allocation of MR signals in FIG. 12 correspond to sharing of k-space data (view sharing). Below, processing different from that explained in FIG. 7 will be explained with respect to FIG. 12.

[0090] The processing circuit 150 reconstructs an MR image (hereinafter referred to as a first low-frequency image) of the low-frequency region V1L of the first k-space kVol1 based on the second MR signal by the image generating function 136. The image generating function 136 reconstructs an MR image (hereinafter referred to as a second low-frequency image) of the low-frequency region V2L of the second k-space kVol2 based on the fourth MR signal. The image generating function 136 reconstructs an MR image (hereinafter referred to as a third low-frequency image) of the low-frequency region V3L of the third k-space kVol3 based on the sixth MR signal. The image generating function 136 reconstructs an MR image (hereinafter referred to as a fourth low-frequency image) of the low-frequency region V4L of the fourth k-space kVol4 based on the eighth MR signal. The image generating function 136 reconstructs an MR image (hereinafter, referred to as a fifth low-frequency image) of the low-frequency region V5L of the fifth k-space kVol5 based on the tenth MR signal. The reconstruction of the first to fifth low-frequency images is realized by, for example, Fourier transform.

[0091] The processing circuit 150 uses the selection function 137 to calculate a plurality of similarities (hereinafter referred to as first similarities) for the first low-frequency image, with the first low-frequency image as a reference image and the second to fifth low-frequency images as comparison images. The selection function 137 also calculates a plurality of similarities (hereinafter referred to as second similarities) for the second low-frequency image, with the second low-frequency image as a reference image and the first low-frequency image and the third to fifth low-frequency images as comparison images. The selection function 137 calculates a plurality of similarities (hereinafter referred to as third similarities) for the third low-frequency image, with the third low-frequency image as a reference image and the first, second, fourth, and fifth low-frequency images as comparison images. The selection function 137 calculates a plurality of similarities (hereinafter referred to as fourth similarities) for the fourth low-frequency image, with the fourth low-frequency image as a reference image and the first to third low-frequency images and the fifth low-frequency image as comparison images. The selection function 137 calculates a plurality of similarities (hereinafter referred to as fifth similarities) related to the fifth low-frequency image, with the fifth low-frequency image as a reference image and the first to fourth low-frequency images as comparison images.

[0092] The selection function 137 selects an image type related to a low-frequency image related to the maximum similarity in each of the first to third similarities from a plurality of image types related to the MT imaging method of this application example. In Fig. 11, the image type selected for image type 1 is image type 4. In Fig. 11, the image type selected for image type 2 is image type 3. In Fig. 11, the image type selected for image type 3 is image type 2. In Fig. 11, the image type selected for image type 4 is image type 5. Although not shown in Fig. 11, it is assumed that the image type selected for image type 5 is image type 1.

[0093] 11, the processing circuitry 153 assigns the first MR signal to one high-frequency region V1H1, assigns the first MR signal to the low-frequency region V1L, and assigns the seventh MR signal related to the fourth low-frequency image to the other high-frequency region V1H2 in the first k-space kVol1 by the assignment function 134. In the second k-space kVol2, the assignment function 134 assigns the third MR signal to one high-frequency region V2H1, assigns the fourth MR signal to the low-frequency region V2L, and assigns the fifth MR signal related to the third low-frequency image to the other high-frequency region V2H2. In the third k-space kVol3, the assignment function 134 assigns the fifth MR signal to one high-frequency region V3H1, assigns the sixth MR signal to the low-frequency region V3L, and assigns the third MR signal related to the second low-frequency image to the other high-frequency region V3H2.

[0094] In the 4k-space kVol4, the allocation function 134 allocates the 7th MR signal to one high-frequency region V4H1, the 8th MR signal to the low-frequency region V4L, and the 9th MR signal related to the 5th low-frequency image to the other high-frequency region V4H2. In the 5k-space kVol5, the allocation function 134 allocates the 9th MR signal to one high-frequency region V5H1, the 10th MR signal to the low-frequency region V5L, and the 1st MR signal related to the 1st low-frequency image to the other high-frequency region V5H2.

[0095] Hereinafter, the procedure of the MT map generation process in this application example will be described with reference to Fig. 13. Fig. 13 is a flowchart showing an example of the procedure of the MT map generation process. For ease of explanation, the MT imaging method in this application example will be described as including the first to fifth pulse sequences as shown in Fig. 12. Steps S131, S132, and S133 in Fig. 13 correspond to steps S801, S802, and S803 in Fig. 8, respectively, and therefore will not be described.

[0096] (MT map generation process) (Step S134) The processing circuitry 153 reconstructs a low-frequency image for each image type based on the MR signal in the low-frequency region of the image type by the image generation function 136. That is, the image generation function 136 reconstructs the first to fifth low-frequency images based on the MR signals in the first to fifth low-frequency regions.

[0097] (Step S135) The processing circuit 153 calculates the similarity by using the low-frequency image for each of the multiple image types as a reference image through the selection function 137. Specifically, the selection function 137 calculates the similarity of each of the multiple image types to the other image types by using the low-frequency image for each of the multiple image types as a reference image and the low-frequency image of the other image types as a comparison image.

[0098] (Step S136) The selection function 137 selects the image type of the low frequency image corresponding to the maximum similarity for each image type. Specifically, the selection function 137 selects the image type related to the maximum similarity for each of the multiple image types.

[0099] (Step S137) The processing circuitry 153 assigns the MR signals in the high frequency region of the selected image type to the other high frequency region of the reference image serving as a basis for the selection by the assignment function 134. Specifically, the assignment function 134 assigns the MR signals in one high frequency region of the selected image type to the other high frequency region of the k-space related to the image type serving as a basis for the selected image type. Since the MR signals are assigned to each of the one high frequency region and the low frequency region of the k-space related to the image type serving as a basis for the selected image type as described in step S804, filling of the MR data into the k-space is completed.

[0100] (Step S138) The processing circuitry 153 generates MT map images corresponding to a plurality of image types using the assigned MR signals by the image generating function 136. The procedure for generating the MT map images is similar to that of step S805, and therefore will not be described.

[0101] The MRI apparatus 100 according to the second application example of the embodiment described above includes a second pulse sequence, executes multiple pulse sequences each corresponding to multiple image types with different MT pulses, generates a first low-frequency image based on the second MR signal, generates multiple low-frequency images corresponding to the multiple pulse sequences based on magnetic resonance signals in the low-frequency region in the multiple pulse sequences, selects an image type similar to the first low-frequency image from the multiple low-frequency images based on the similarity between the multiple low-frequency images and the first low-frequency image, and assigns a third MR signal related to the selected image type to the other high-frequency region of k-space.

[0102] As a result, according to the present MRI apparatus 100, when the contrast and signal intensity of each MT image type are extremely different, the image type to be the subject of k-space data sharing (view sharing) is automatically selected using the similarity related to the image reconstructed only in the low frequency region, so that k-space data can be shared between image types with similar image contrast. The selection of the image type by the selection function 137 corresponds to, for example, selecting an image type with a closer MT contrast in the steady state shown in FIG. 5 and FIG. 6. From these points, according to this application example, the influence of the view share on the image contrast can be reduced, and the image quality of the generated MT map image can be guaranteed. Other effects are the same as those of the embodiment, so a description thereof will be omitted.

[0103] (Third application example) This application example is to combine the processes in the first application example and the second application example. For example, the addition function 135 adds up a plurality of MR signals in the low-frequency region in each of a plurality of pulse sequences corresponding to a plurality of image types over the number of additions, and generates a plurality of addition signals corresponding to the plurality of pulse sequences. The image generation function 136 reconstructs a first low-frequency image based on the low-frequency addition signal, and reconstructs a plurality of low-frequency images corresponding to the plurality of pulse sequences based on the plurality of addition signals. The selection function 137 selects a plurality of image types similar to the first low-frequency image from the plurality of low-frequency images according to the number of additions based on the similarity between the plurality of low-frequency images and the first low-frequency image. In addition, the addition function 135 adds up a plurality of third magnetic resonance signals related to the selected plurality of image types over the number of additions to generate a high-frequency addition signal. The effect of this application example corresponds to that of the first application example and the second application example, and therefore a description thereof will be omitted.

[0104] (Example 4) 8, a display mode (hereinafter referred to as an input user interface) related to a user's input is displayed on the display 143. The display 143 displays, for example, an imaging target region related to the first pulse sequence, an imaging time related to the first pulse sequence, a ratio of a steady state transition period to the imaging time (hereinafter referred to as a steady state transition period time rate), allocation setting information related to the setting of allocation of other parts of the k-space to high frequency regions, a total imaging time of a plurality of pulse sequences executed on the subject P using MT pulses, and a ratio of the high frequency region of other parts to the k-space (hereinafter referred to as a view share rate).

[0105] The imaging target part is a part of the subject P that is the subject of the examination by the MT map image, such as the brain or muscle. The imaging time of the plurality of pulse sequences including the first pulse sequence is set by the image type of the MT map image and the imaging target part. The steady state transition time rate is determined, for example, by a simulation for the target pulse sequence. The steady state transition time rate corresponds to the ratio of the time until the MT effect reaches a steady state according to the imaging target part (brain, muscle, etc.) with respect to the imaging time. The allocation setting information is information for setting, for example, whether to set the pulse sequence adjacent in time series as the allocation to one high frequency region as shown in the embodiment, or to automatically select the image type to be the optimal view sharing target based on the similarity as shown in the second application example. That is, the allocation setting information corresponds to a pattern related to view sharing, such as adjacent or automatic (hereinafter referred to as a view sharing pattern).

[0106] The total imaging time is calculated by adding up the imaging times of the multiple pulse sequences in the MT imaging method of this application example. When the view share rate is 0%, the MT map generation process in this embodiment is turned off. The steady state transition time rate is displayed on the display 143, for example, as reference information regarding the view share rate setting by the user.

[0107] Fig. 14 is a diagram showing an example of an input user interface UI displayed on the display 143 in the case where the viewshare rate is 0%. As shown in Fig. 14, the input user interface UI displays an imaging target region for the first pulse sequence, an imaging time for the first pulse sequence, a steady state transition time rate, a viewshare rate, a total imaging time of a plurality of pulse sequences executed on the subject P using MT pulses, and a viewshare pattern. Fig. 14 also shows that the UI displays that the total imaging time for the first and second volumes is 40 seconds, and that the total imaging time for the first to third volumes is 60 seconds.

[0108] The upper limit of the ratio of the high frequency region of the other part to the k-space is set based on the ratio of the steady state transition period to the imaging time and the first pulse sequence. More specifically, the upper limit is set based on the ratio of the steady state transition period to the imaging time and each of the multiple pulse sequences in each of the multiple pulse sequences. At this time, if the user tries to set the view share rate beyond the upper limit, the display 143 may display, for example, a predetermined warning indicating that the image quality cannot be guaranteed. Items that can be set by the user among the information displayed on the display 143 are, for example, the imaging target part, the view share rate, and the view share pattern. That is, the input device 141 inputs the imaging target part, the allocation setting information, and the ratio of the high frequency region of the other part to the k-space according to the user's instruction.

[0109] Fig. 15 is a diagram showing an example of an input user interface UI displayed on the display 143 in the case where the view share rate is 20%. Differences from Fig. 14 are the imaging target region for the first pulse sequence, the imaging time for the first pulse sequence, the steady state transition time rate, the view share pattern, the total imaging time for the first volume and the second volume, and the total imaging time for the first to third volumes. In Fig. 15, the view share rate is 20%. When the imaging times for the first to third volumes in Fig. 14 are the same as those in Fig. 14, the view share rate is 20%, so the time shown in Fig. 15 is shown as 16 seconds, which is 80% of 20 seconds. The imaging time and the like in the UI shown in Fig. 15 are dynamically changed and displayed in response to an input by the user.

[0110] The MRI apparatus 100 according to the fourth application example of the above-described embodiment displays the imaging target region for the first pulse sequence, the imaging time for the first pulse sequence, the ratio of the transition period to the imaging time, allocation setting information regarding the setting of allocation to the other high frequency region of the k space, the total imaging time of a plurality of pulse sequences executed on the subject P using the MT pulse, and the ratio of the other high frequency region to the k space, and inputs the imaging target region, the allocation setting information, and the ratio of the other high frequency region to the k space. According to this MRI apparatus 100, the upper limit of the ratio of the other high frequency region to the k space is set based on the ratio of the transition period to the imaging time and the first pulse sequence.

[0111] As a result, according to the present MRI apparatus 100, the view-share rate can be easily input by inputting the imaging target area and the view-share pattern in the UI for various settings related to the present MT imaging method and using the steady-state transition period time rate as reference information. Therefore, according to the MRI apparatus 100 in this application example, it is possible to improve the operability of various settings related to the present MT imaging method, and to improve the throughput of the examination.

[0112] When the technical idea of ​​the embodiment is realized by an image generating method, the image generating method executes a first pulse sequence in which application of a first MT pulse and collection of a first MR signal corresponding to a part of a high frequency region of k-space are repeated during a transition period until magnetization transitions to a steady state, application of the first MT pulse and collection of a second MR signal corresponding to a low frequency region of k-space are repeated during the steady state, application of a second MT pulse different from the first MT pulse and collection of a third MR signal corresponding to the high frequency region are repeated during the transition period, application of the second MT pulse and collection of a fourth MR signal corresponding to the low frequency region are repeated during the steady state, and the third MR signal is assigned to the high frequency region of the other part of k-space related to the first pulse sequence, and an MR image corresponding to the first pulse sequence is generated based on the first MR signal, the second MR signal, and the third MR signal. The procedure and effect of the MT map generation process executed by the image generating method are similar to those of the embodiment, and therefore will not be described.

[0113] According to at least the embodiments, applications, and the like described above, imaging time can be reduced in imaging using different magnetization exchange pulses.

[0114] Although some embodiments 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, substitutions, modifications, and combinations of embodiments can be made without departing from the spirit of the invention. These embodiments and their modifications are included in the scope of the invention and its equivalents as described in the claims, as well as in the scope and spirit of the invention. [Explanation of symbols]

[0115] 100 Magnetic resonance imaging device 101 Static magnetic field magnet 102 Static magnetic field power supply 103 Gradient magnetic field coil 104 Gradient magnetic field power supply 105 Bed 105a Tabletop 106 Bed control circuit 107 Transmitting Coil 108 Transmitting circuit 109 Receiving coil 120 Sequence control circuit 130 Computers 131 Interface Functions 132 Memory circuit 133 Control Functions 134 Assignment Function 135 Addition function 136 Image Generation Function 137 Selection Function 141 Input Devices 143 Display 150 Processing circuit 151 Processing circuit 153 Processing Circuit

Claims

1. a sequence controller that executes a first pulse sequence that repeats application of a first MT (Magnetization Transfer) pulse and acquisition of a first MR (Magnetic Resonance) signal corresponding to a high frequency region of a part of k-space during a transition period until magnetization transitions to a steady state, and repeats application of the first MT pulse and acquisition of a second MR signal corresponding to a low frequency region of the k-space in the steady state; and a second pulse sequence that repeats application of a second MT pulse different from the first MT pulse and acquisition of a third MR signal corresponding to the high frequency region during the transition period, and repeats application of the second MT pulse and acquisition of a fourth MR signal corresponding to the low frequency region in the steady state; an allocator for allocating the third MR signal to a high frequency region in another portion of the k-space related to the first pulse sequence; an image generating unit that generates an MR image corresponding to the first pulse sequence based on the first MR signal, the second MR signal, and the third MR signal; A magnetic resonance imaging apparatus comprising:

2. The sequence control unit includes: In the first pulse sequence, the acquisition of the second MR signal is performed a plurality of times according to the number of additions; A plurality of pulse sequences including the second pulse sequence, each having a different MT pulse, are executed according to the number of additions; an adder that averages the second MR signal over the number of additions to generate a low-frequency sum signal, and that averages the third MR signals in the plurality of pulse sequences over the number of additions to generate a high-frequency sum signal; The allocation unit: assigning the low frequency sum signal to a low frequency region of the k-space; assigning the high frequency sum signal to a high frequency region in another portion of the k-space; the image generating unit generates the MR image based on the first MR signal, the low-frequency sum signal, and the high-frequency sum signal.

2. A magnetic resonance imaging apparatus according to claim 1.

3. the sequence controller executes a plurality of pulse sequences including the second pulse sequence, the plurality of pulse sequences corresponding to a plurality of image types each having a different MT pulse; The image generating unit includes: generating a first low frequency image based on the second MR signal; generating a plurality of low-frequency images corresponding to the plurality of pulse sequences based on the magnetic resonance signals in the low-frequency region in the plurality of pulse sequences; a selection unit that selects an image type similar to the first low-frequency image from the plurality of low-frequency images based on a similarity between the plurality of low-frequency images and the first low-frequency image, the allocating unit allocates the third MR signal related to the selected image type to a high frequency region in another portion of the k-space.

2. A magnetic resonance imaging apparatus according to claim 1.

4. the adder adds up a plurality of MR signals in a low frequency region in each of the plurality of pulse sequences corresponding to a plurality of image types over the number of additions to generate a plurality of added signals corresponding to the plurality of pulse sequences; The image generating unit includes: reconstructing a first low-frequency image based on the low-frequency sum signal; reconstructing a plurality of low-frequency images corresponding to the plurality of pulse sequences based on the plurality of summed signals; a selection unit that selects a plurality of image types similar to the first low-frequency image from the plurality of low-frequency images in accordance with the number of additions based on a similarity between the plurality of low-frequency images and the first low-frequency image, the adder adds up the third MR signals related to the selected image types over the number of additions to generate the high-frequency sum signal.

3. A magnetic resonance imaging apparatus according to claim 2.

5. a display that displays an imaging target region for the first pulse sequence, an imaging time for the first pulse sequence, a ratio of the transition period to the imaging time, allocation setting information for setting an allocation of another portion of the k-space to a high frequency region, a total imaging time of a plurality of pulse sequences executed on a subject using an MT pulse, and a ratio of the high frequency region of the other portion to the k-space; an input device for inputting the imaging target region, allocation setting information, and a ratio of a high frequency region of the other portion to the k-space; The magnetic resonance imaging apparatus according to claim 1 , further comprising:

6. an upper limit of a ratio of a high frequency region of the other portion to the k space is set based on a ratio of the transition period to the imaging time and the first pulse sequence; 6. A magnetic resonance imaging apparatus according to claim 5.

7. a first pulse sequence is executed in which application of a first MT (Magnetization Transfer) pulse and acquisition of a first MR (Magnetic Resonance) signal corresponding to a high frequency region of a part of k-space are repeated during a transition period until magnetization transitions to a steady state, and application of the first MT pulse and acquisition of a second MR signal corresponding to a low frequency region of the k-space are repeated in the steady state; a second pulse sequence is executed in which application of a second MT pulse different from the first MT pulse and acquisition of a third MR signal corresponding to the high frequency region are repeated during a transition period, and application of the second MT pulse and acquisition of a fourth MR signal corresponding to the low frequency region are repeated in a steady state; assigning the third MR signal to a high frequency region in another portion of the k-space relative to the first pulse sequence; generating an MR image corresponding to the first pulse sequence based on the first MR signal, the second MR signal, and the third MR signal; An image generating method comprising:

Images