Patent Publication Number: US-10324149-B2

Title: Systems and methods for generalized slice dithered enhanced resolution magnetic resonance imaging

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application claims the benefit of U.S. Provisional Patent Application Ser. No. 62/238,782, filed on Oct. 8, 2015, and entitled “Systems and Methods for Generalized Slice Dithered Enhanced Resolution Magnetic Resonance Imaging.” 
    
    
     STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH 
     This invention was made with government support under MH106096 and EB019437 awarded by the National Institutes of Health. The government has certain rights in the invention. 
    
    
     BACKGROUND OF THE INVENTION 
     The field of the invention is systems and methods for magnetic resonance imaging (“MRI”). More particularly, the invention relates to systems and methods for high-resolution MRI. 
     Slice dithered enhanced resolution simultaneous multislice (“SLIDER-SMS”) MRI has recently been used in diffusion MRI scans to resolve sub-millimeter slices, as described in co-pending PCT Application Serial No. PCT/US15/53719. Acquiring sub-millimeter slices is impractical with conventional slice selection due to the low SNR and constraints on practical RF pulse duration. SLIDER-SMS overcomes these limitations by selecting a thick slab and introducing sub-voxel shifts along the slice direction between acquisitions. Thin slices are then obtained using a super-resolution technique during image reconstruction, providing slice images that are thinner than the originally excited slabs. 
     As compared with serial acquisition from individual thin slices, SLIDER provides higher SNR because the spins from a thick-slice are always contributing to the signal at any moment in time. The high signal level of each thick-slice acquisition is advantageous in diffusion imaging, where it permits accurate removal of background phase, thereby providing real-valued diffusion images (assuming minimal through-slice dephasing). 
     A drawback of the SLIDER approach, however, is that the shifted thick-slices do not form an orthonormal encoding basis. This causes noise amplification during the image reconstruction process that must be suppressed using regularization, which in turn blurs the slice profiles of the final high resolution slices. Therefore, a tradeoff exists between noise level and spatial resolution due to the linear dependence in the slice encoding functions. 
     SUMMARY OF THE INVENTION 
     The present invention overcomes the aforementioned drawbacks by providing a method for producing a plurality of images of a subject with a magnetic resonance imaging (MRI) system. A radio frequency (RF) excitation field that excites spins in a slab composed of a plurality of sub-slices that are each thinner than the slab, is applied to a subject. The RF excitation field is defined by a basis set in which a particular RF magnitude and RF phase are associated with each of the plurality of sub-slices. Data are acquired from the slab, and this process is repeated to acquire additional data while the basis set of the RF excitation field is adjusted during each repetition of the RF excitation. Slab images are reconstructed from the data and the additional data. High-resolution images are then produced from the slab images. The high-resolution images are associated with the sub-slices and have a higher through-plane resolution than the slab images. 
     The foregoing and other aspects and advantages of the invention will appear from the following description. In the description, reference is made to the accompanying drawings that form a part hereof, and in which there is shown by way of illustration a preferred embodiment of the invention. Such embodiment does not necessarily represent the full scope of the invention, however, and reference is made therefore to the claims and herein for interpreting the scope of the invention. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is an example of a basis set for a radio frequency (“RF”) excitation field that excites spins in a thick slab composed of multiple thinner sub-slices, and where a different phase is associated with one of the sub-slices (e.g., one sub-slice has a 180 degree phase and the others have zero degree phase) and the sub-slice with which the different phase is associated changes in each repetition time (“TR”); 
         FIG. 2A  is an example of Hadamard encoding with an even number of sub-slices; 
         FIG. 2B  is an example of Hadamard encoding with an odd number of sub-slices; 
         FIG. 3  is an example of a basis set for an RF excitation field that excites spins in a thick slab composed of multiple thinner sub-slices in which one sub-slice is separated from the others by a gap, and where the locations of the sub-slices are shifted in each TR; 
         FIG. 4  is an example of a basis set for an RF excitation field that excites spins in a thick slab composed of multiple thinner sub-slices, and where a different phase is associated with one of the sub-slices and the locations of the sub-slices are shifted in each TR; and 
         FIG. 5  is a block diagram of an example of a magnetic resonance imaging (“MRI”) system. 
     
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
     Described here are systems and methods for using excited slice profiles to improve the point spread function (“PSF”) of super-resolution slices in SLIDER acquisitions while preserving all of the advantages of the SLIDER technique. The techniques described here may generally be referred to as “Generalized SLIDER” (“g-SLIDER”). 
     The g-SLIDER technique overcomes the drawbacks of SLIDER techniques described above by exploring the available degrees of freedom to additionally allow for variation of the amplitude profile, phase profile, or both, of the excited thick-slice in between acquisitions instead of just relying on a simple amplitude shifting of the entire thick-slice. Using appropriately designed RF pulses, the magnitude profile, phase profile, or both, can be set so as to make subsequent acquisitions less linearly dependent, thereby improving the condition number of the super-resolution image reconstruction problem. 
     One important constraint in the design of these basis sets is to design them such that a high SNR can be maintained in each individual thick-slice acquisition. This allows for the needed removal of background phase contamination in each thick-slice prior to super-resolution reconstruction. In cases where the SNR of each thick-slice is very high, the magnitude operation can be used as an simple way to remove phase, whereas in cases where the SNR is relatively lower (but not too low due to the way the thick-slice basis has been designed), the phase variation can be estimated using prior information about its smoothness, such as in the “real-diffusion” method described by C. Eichner, et al., in Real diffusion-weighted MRI enabling true signal averaging and increased diffusion contrast,”  NeuroImage,  2015; 122:373-384. One important consideration for the techniques described here, therefore, is to keep the SNR of the thick-slice acquisition high by designing the basis sets such that most of the spins in the sub-slices of the thick slice are contributing constructively to the overall signal of the thick slice. The end result of this is to create a basis set that is close to orthogonal while maintaining high SNR in each acquisition. This enable high quality super-resolution reconstruction with minimal noise and a sharper slice point spread function. 
     In one embodiment, illustrated in  FIG. 1 , a thick slice containing five sub-slice segments is excited with a pulse that imparts zero degree phase to four of the sub-slices and a 180 degree phase to the remaining, fifth sub-slice. In subsequent acquisitions (e.g., subsequent repetition time (“TR”) periods), the location of the sub-slice with the 180 degree phase profile is shifted until all five configurations have been excited. In this example, all of the sub-slices are excited with pulses having the same magnitude; however, in some instances the magnitude of the pulses applied to the sub-slices could also be varied. 
     This approach is similar to Hadamard encoding, such as described by E. U. Saritas, in “Hadamard slice encoding for reduced-FOV diffusion-weighted imaging,”  Magnetic Resonance in Medicine,  2014; 72(5):1277-1290, with the crucial distinction that, unlike Hadamard encoding, g-SLIDER uses only one 180-degree phase shift per acquisition, thereby canceling signal from only one adjacent segment. With this distinction, full signal is retained from the remaining three segments, providing an approximately three-fold gain in SNR for purposes of background phase estimation as compared with individually acquiring a thin sub-slice. 
     This gain in SNR provides sufficient SNR to accurately remove background phase contamination from each diffusion image. By contrast, in Hadamard encoding the signal cancelation between sub-slices with zero degree and 180 degree phase profiles results in essentially no SNR gain relative to the intrinsic signal of a single sub-slice for some of the basis sets, as described below, which is inadequate for removing phase contamination for cases of high resolution imaging. 
     For the final reconstructed SLIDER image, the SNR is theoretically √{square root over (N)} times higher than the standard thin slice acquisition, where N is the number of thin slices excited in the larger thick slice volume. Using the improved slice profile orthogonality described above, this SNR gain can be approached without the need for regularization, which otherwise blurs the slice point spread function. Although the bases described above are not perfectly orthogonal, the small amount of linear dependence in the basis sets is a good tradeoff for improved SNR in each thick-slice acquisition to allow accurate phase removal. 
     This particular implementation of g-SLIDER has an added benefit over the original SLIDER slice shift approach, with less contamination from varying spin-history effects from one TR to the next. Here, the sub-slice with 180 degree phase is shifted between acquisitions rather than shifting the whole slab. With this approach, there is less opportunity for the spin history to vary due to spatially shifting the slice position from one TR to the next, which can contaminate the acquired signal, particularly for short TRs. 
     There are some instances where standard Hadamand encoding can achieve the desired criteria for basis set design in generalized-SLIDER. Specifically, the criteria can be achieved for odd numbers of sub-slice encoding, where the level of signal from each individual sub-slice would provide sufficient SNR for phase contamination estimation and removal. In these instances, there could be sufficient SNR to perform phase estimation and reliably use the estimated phase to correct for phase issues prior to super-resolution reconstruction. As a result, it can be possible to implement diffusion-weighted imaging without the need to acquire navigator data. For even numbers of sub-slice encoding, however, the Hadamand basis set will always result in at least one of the thick-slice acquisitions having SNR close to zero due to the deconstructive combination of signals from the sub-slices. This is illustrated in  FIGS. 2A and 2B . 
     In another embodiment of generalized-SLIDER, illustrated in  FIG. 3 , the magnitude basis of the excitation is chosen such that there is a gap in the excitation of the sub-slices. As one example, for five sub-slice SLIDER, one basis would be to have four adjacent slices excited with a gap one sub-slice thick and then another slice excited next to this gap, as shown in  FIG. 3 . The other basis sets in this embodiment would be the slice-shifted version of this first basis set (e.g., where the second basis set would retain the shape of the first basis set, but be shifted in the z-direction by one sub-slice distance). In this example, the same phase is associated with each sub-slice; however, in some other instances the phase associated with one or more of the sub-slices could also be varied. For instance, the phase associated with sub-slice  5  could be 180 degrees while the phase associated with sub-slices  1 - 4  could be zero degrees. 
     It is contemplated that this would be a good basis set to use in cases where the signal level is low because all of the sub-slices&#39; signal add constructively in each thick-slice acquisition to provide an approximately five-fold gain in SNR relative to that of a single sub-slice (assuming minimal phase variation across slices). This particular basis contains a sharp profile transition that decrease the basis dependence of the original SLIDER slice-shifting method, while maintaining high SNR of thick slice acquisition. As such, it should also improve the super-resolution reconstruction trade-offs between SNR benefit and blurring. 
     In another embodiment of generalized-SLIDER, illustrated in  FIG. 4 , slice shifting is combined with phase modulation within the thick-slice direction. As one example, a thick-slice containing five sub-slices is excited with a phase of {π, 0, 0, 0, 0} for the sub-slices, respectively. To create the different basis sets, the thick-slice excitation is then incrementally shifted in the slice-encoding direction (e.g., incrementally shifted by the thickness of one sub-slice). 
     In general, generalized-SLIDER provides the ability to perform thick-slice encoding (i.e., slab-encoding) without the need for additional time-consuming and potentially high specific absorption rate (“SAR”) navigator scans to correct for phase contamination, particularly in diffusion images. This is achieved by designing the basis of the thick-slice encoding so that each acquisition contains sufficient SNR to allow for phase contamination estimation and removal (with an assumption that there is only a small or minimal through slice dephasing). This reduces the scan time and avoids the extra RF power deposition associated with the refocusing pulses in the navigator scans. It is also straightforward to incorporate the parallel receive array simultaneous multi-slice (“SMS”) feature in order to acquire multiple thick-slices at the same time, using methods such as blipped-CAIPIRINHA to allow simultaneously acquired slabs to be untangled in an efficient manner with low SNR loss. The SLIDER technique is also compatible with compressed sensing approaches for Q-space imaging. 
     The generalized-SLIDER technique provides a sharp slice point spread function while retaining around ninety percent of maximum achievable SNR gain with no or minimal regularization. 
     Referring particularly now to  FIG. 5 , an example of a magnetic resonance imaging (“MRI”) system  500  is illustrated. The MRI system  500  includes an operator workstation  502 , which will typically include a display  504 ; one or more input devices  506 , such as a keyboard and mouse; and a processor  508 . The processor  508  may include a commercially available programmable machine running a commercially available operating system. The operator workstation  502  provides the operator interface that enables scan prescriptions to be entered into the MRI system  500 . In general, the operator workstation  502  may be coupled to four servers: a pulse sequence server  510 ; a data acquisition server  512 ; a data processing server  514 ; and a data store server  516 . The operator workstation  502  and each server  510 ,  512 ,  514 , and  516  are connected to communicate with each other. For example, the servers  510 ,  512 ,  514 , and  516  may be connected via a communication system  540 , which may include any suitable network connection, whether wired, wireless, or a combination of both. As an example, the communication system  540  may include both proprietary or dedicated networks, as well as open networks, such as the internet. 
     The pulse sequence server  510  functions in response to instructions downloaded from the operator workstation  502  to operate a gradient system  518  and a radiofrequency (“RF”) system  520 . Gradient waveforms necessary to perform the prescribed scan are produced and applied to the gradient system  518 , which excites gradient coils in an assembly  522  to produce the magnetic field gradients G x , G y , and G z  used for position encoding magnetic resonance signals. The gradient coil assembly  522  forms part of a magnet assembly  524  that includes a polarizing magnet  526  and a whole-body RF coil  528 . 
     RF waveforms are applied by the RF system  520  to the RF coil  528 , or a separate local coil (not shown in  FIG. 5 ), in order to perform the prescribed magnetic resonance pulse sequence. Responsive magnetic resonance signals detected by the RF coil  528 , or a separate local coil (not shown in  FIG. 5 ), are received by the RF system  520 , where they are amplified, demodulated, filtered, and digitized under direction of commands produced by the pulse sequence server  510 . The RF system  520  includes an RF transmitter for producing a wide variety of RF pulses used in MRI pulse sequences. The RF transmitter is responsive to the scan prescription and direction from the pulse sequence server  510  to produce RF pulses of the desired frequency, phase, and pulse amplitude waveform. The generated RF pulses may be applied to the whole-body RF coil  528  or to one or more local coils or coil arrays (not shown in  FIG. 5 ). 
     The RF system  520  also includes one or more RF receiver channels. Each RF receiver channel includes an RF preamplifier that amplifies the magnetic resonance signal received by the coil  528  to which it is connected, and a detector that detects and digitizes the I and Q quadrature components of the received magnetic resonance signal. The magnitude of the received magnetic resonance signal may, therefore, be determined at any sampled point by the square root of the sum of the squares of the I and Q components:
 
 M =√{square root over ( I   2   +Q   2 )}  (1);
         and the phase of the received magnetic resonance signal may also be determined according to the following relationship:       

     
       
         
           
             
               
                 
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     The pulse sequence server  510  also optionally receives patient data from a physiological acquisition controller  530 . By way of example, the physiological acquisition controller  530  may receive signals from a number of different sensors connected to the patient, such as electrocardiograph (“ECG”) signals from electrodes, or respiratory signals from a respiratory bellows or other respiratory monitoring device. Such signals are typically used by the pulse sequence server  510  to synchronize, or “gate,” the performance of the scan with the subject&#39;s heart beat or respiration. 
     The pulse sequence server  510  also connects to a scan room interface circuit  532  that receives signals from various sensors associated with the condition of the patient and the magnet system. It is also through the scan room interface circuit  532  that a patient positioning system  534  receives commands to move the patient to desired positions during the scan. 
     The digitized magnetic resonance signal samples produced by the RF system  520  are received by the data acquisition server  512 . The data acquisition server  512  operates in response to instructions downloaded from the operator workstation  502  to receive the real-time magnetic resonance data and provide buffer storage, such that no data is lost by data overrun. In some scans, the data acquisition server  512  does little more than pass the acquired magnetic resonance data to the data processor server  514 . However, in scans that require information derived from acquired magnetic resonance data to control the further performance of the scan, the data acquisition server  512  is programmed to produce such information and convey it to the pulse sequence server  510 . For example, during prescans, magnetic resonance data is acquired and used to calibrate the pulse sequence performed by the pulse sequence server  510 . As another example, navigator signals may be acquired and used to adjust the operating parameters of the RF system  520  or the gradient system  518 , or to control the view order in which k-space is sampled. In still another example, the data acquisition server  512  may also be employed to process magnetic resonance signals used to detect the arrival of a contrast agent in a magnetic resonance angiography (“MRA”) scan. By way of example, the data acquisition server  512  acquires magnetic resonance data and processes it in real-time to produce information that is used to control the scan. 
     The data processing server  514  receives magnetic resonance data from the data acquisition server  512  and processes it in accordance with instructions downloaded from the operator workstation  502 . Such processing may, for example, include one or more of the following: reconstructing two-dimensional or three-dimensional images by performing a Fourier transformation of raw k-space data; performing other image reconstruction algorithms, such as iterative or backprojection reconstruction algorithms; applying filters to raw k-space data or to reconstructed images; generating functional magnetic resonance images; calculating motion or flow images; and so on. 
     Images reconstructed by the data processing server  514  are conveyed back to the operator workstation  502  where they are stored. Real-time images are stored in a data base memory cache (not shown in  FIG. 5 ), from which they may be output to operator display  502  or a display  536  that is located near the magnet assembly  524  for use by attending physicians. Batch mode images or selected real time images are stored in a host database on disc storage  538 . When such images have been reconstructed and transferred to storage, the data processing server  514  notifies the data store server  516  on the operator workstation  502 . The operator workstation  502  may be used by an operator to archive the images, produce films, or send the images via a network to other facilities. 
     The MRI system  500  may also include one or more networked workstations  542 . By way of example, a networked workstation  542  may include a display  544 ; one or more input devices  546 , such as a keyboard and mouse; and a processor  548 . The networked workstation  542  may be located within the same facility as the operator workstation  502 , or in a different facility, such as a different healthcare institution or clinic. 
     The networked workstation  542 , whether within the same facility or in a different facility as the operator workstation  502 , may gain remote access to the data processing server  514  or data store server  516  via the communication system  540 . Accordingly, multiple networked workstations  542  may have access to the data processing server  514  and the data store server  516 . In this manner, magnetic resonance data, reconstructed images, or other data may be exchanged between the data processing server  514  or the data store server  516  and the networked workstations  542 , such that the data or images may be remotely processed by a networked workstation  542 . This data may be exchanged in any suitable format, such as in accordance with the transmission control protocol (“TCP”), the internet protocol (“IP”), or other known or suitable protocols. 
     The present invention has been described in terms of one or more preferred embodiments, and it should be appreciated that many equivalents, alternatives, variations, and modifications, aside from those expressly stated, are possible and within the scope of the invention.