Traditional Posters : Pulse Sequences, Reconstruction & Analysis
Click on to view the abstract pdf and click on to view the pdf of the poster viewable in the poster hall.
Trajectories & Novel Encoding Methods

 
Thursday May 12th
Exhibition Hall  13:30 - 15:30

2802.   A Looping Trajectory for Single-Shot 3D Imaging  
Robert Wayne Stobbe1, and Christian Beaulieu1
1Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada

 
A looping trajectory, as one may wind a ball of yarn, is introduced for single-shot 3D image acquisition. When acceleration is constrained for a constant rate of gradient change, a hardware limiting constraint, this rate of change is similar to that of a ‘back-and-forth’ approach sampling the same k-space volume in the same time. Sampling density and efficiency are addressed and preliminary phantom images created at 4.7 Tesla. Theoretical advantages of the yarn-ball trajectory include improved off-resonant performance, given early sampling of central k-space, and the potential for designed ‘random’ undersampling to increase the volume of k-space sampled.

 
2803.   Analysis of Variable Density FLORET trajectories 
James Grant Pipe1, and Nicholas Ryan Zwart1
1Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ, United States

 
FLORET is a 3D k-space trajectory previously described, which samples all of k-space twice, in orthogonal directions. This work shows the performance of variable density FLORET, which is very efficient and has very incoherent aliasing, which is desirable for many types of reconstruction algorithms.

 
2804.   Variable Gradient Delay Correction for Spiral MRI 
Payal Sharad Bhavsar1, and Jim Pipe1
1Neuroimaging, Barrow Neurological Institute, Phoenix, AZ, United States

 
A new method is proposed to estimate time varying gradient delays in spiral MRI. Gradient delays cause blurring and distortions in spiral images. Several methods have been proposed to estimate these delays. Continuous, independent delays are estimated for all three gradient channels as a function of the ADC time. This method includes gradient coupling effects and requires minimal modification of the pulse sequence design.A 3D spiral trajectory FLORET was used to estimate the gradient delays. To validate the results, a constant delay correction method was used for analysis. In-vivo and phantom experiments were reconstructed using constant and variable gradient delay correction. For in-vivo data, variable correction method showed significant reduction in the artifacts. Comparable results were obtained for constant and variable correction method for phantom simulations. The method can be applied to any stack of spirals based trajectory.

 
2805.   Localization by Nonlinear Phase Preparation and K-Space Trajectory Design (GradLoc) 
Walter RT Witschey1, Christian A. Cocosco1, Daniel Gallichan1, Gerrit Schultz1, Hans Weber1, Anna Masako Welz1, Jürgen Hennig1, and Maxim Zaitsev1
1Medical Physics, University Medical Center Freiburg, Freiburg i. Breisgau, Germany

 
A technique is described for localization of MR signals from a target volume using nonlinear pulsed magnetic fields and spatial encoding trajectories designed using local k-space theory. In vivo human brain images were obtained using a custom quadrupolar gradient coil integrated with a whole-body 3 T MRI scanner to demonstrate localization in 3D T2*-weighted imaging.

 
2806.   ExLoc: Excitation and Encoding of Curved Slices 
Hans Weber1, Daniel Gallichan1, Gerrit Schultz1, Walter R Witschey1, Anna Masako Welz1, Christian A Cocosco1, Jürgen Hennig1, and Maxim Zaitsev1
1Department of Radiology, Medical Physics, University Medical Center Freiburg, Freiburg, Germany

 
Adaptation of the slice shape to the volume of interest would be beneficial for many MRI applications, as it allows coverage with fewer excited slices. In this work, we theoretically design and demonstrate experimentally a method (ExLoc) for excitation of customized curved slices, based on a combination of linear and nonlinear gradients. As signal is encoded along the curved surface, a local rectangular voxel shape is maintained. In contrast to linear spatial encoding, partial volume effects and through-slice dephasing is avoided.

 
2807.   Strategies for Fast 3D Volumetric Coverage using Spatiotemporally-Encoded MRI 
Noam Ben-Eliezer1, and Lucio Frydman1
1Chemical-Physics, Weizmann Institute of Science, Rehovot, Israel

 
The generation of 2D NMR images in a single-scan is a common ingredient in a variety of applications. Real life applications, however, often require 3D volumetric coverage, while keeping the overall scanning on a sub-second timescale. Current ultrafast 3D methods are based on EPI, which notwithstanding its proven success is still challenged by B0 heterogeneities and/or multiple chemical sites. We explore here a new approach, based on combining spatiotemporal-encoding with super-resolution reconstruction algorithms, to achieve higher immunity to these artifacts. A number of 3D sequence schemes are presented and demonstrated on in-vivo mouse models.

 
2808.   Accelerated MR imaging with spread spectrum encoding 
Gilles Puy1,2, José Marques2,3, Rolf Gruetter2,3, Jean-Philippe Thiran1, Dimitri Van De Ville4,5, Pierre Vandergheynst1, and Yves Wiaux1,5
1Institute of Electrical Engineering, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland, 2Institute of the Physics of Biological Systems, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland, 3Department of Radiology, University of Lausanne (UNIL), Lausanne, Switzerland, 4Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland, 5Department of Radiology and Medical Informatics, University of Geneva (UniGE), Geneva, Switzerland

 
We advocate a spread spectrum technique for accelerated MRI. The method, justified by the compressed sensing theory, resides in pre modulating the signal by a linear chirp before uniform random k-space undersampling. Numerical simulations confirm the theoretical prediction according to which the pre-modulation is essential in enhancing the signal reconstruction quality. The chirp modulation was implemented on a 7T scanner with the use of a second order shim coil. Results from 3D single coil phantom and in vivo data acquisitions already exhibit slightly better reconstruction qualities than state of the art variable density sampling methods.

 
2809.   Moving Through k-Space by Point Reflections – the TRASE Method 
Jonathan C Sharp1, and Scott B King2
1Institute for Biodiagnostics (West), National Research Council of Canada, Calgary, AB, Canada, 2Institute for Biodiagnostics, National Research Council of Canada, Winnipeg, MB, Canada

 
Standard MRI methods achieve a scanning of k-space by 2 methods: B0-gradients (providing continuous motion) and refocusing (point reflection about the k-space origin). Here we analyze a third option: point reflection about other k-space locations. The method is achieved by refocusing with B1-phase-gradients and is the basis of the TRASE (Transmit Array Spatial Encoding) imaging method. These novel k-space operations offer the pulse sequence designer an expanded toolkit. Our aim here is to formalize the rules governing the construction of k-space trajectories for this type of sequence.

 
2810.   Spatial Encoding without Gradient Coils Using Field Perturbations from Susceptibility Markers 
Hirad Karimi1, and Charles H Cunningham1,2
1Medical Biophysics, University of Toronto, Toronto, ON, Canada, 2Imaging Research, Sunnybrook Health Sciences Centre, Toronto, ON, Canada

 
In conventional MRI systems, the gradient fields that encode the spatial information are stationary relative to any physiologic movements. In this abstract we propose a novel MR endoscope system based on spatial encoding using the field perturbations around susceptibility markers instead of conventional gradients.

Traditional Posters : Pulse Sequences, Reconstruction & Analysis
Click on to view the abstract pdf and click on to view the pdf of the poster viewable in the poster hall.
Radial Imaging & Projections

 
Monday May 9th
Exhibition Hall  14:00 - 16:00

2811.   Optimized Combination of Parallel MRI and Sliding Window Reconstruction for Accelerated Time Resolved Radial MRI 
Alexey A. Samsonov1, Julia V. Velikina2, and Walter F. Block2
1Radiology, University of Wisconsin, Madison, WI, United States, 2Medical Physics, University of Wisconsin, Madison, WI, United States

 
Sliding window (SW) gridding reconstruction has been an efficient way to reconstruct undersampled interleaved radial MRI data. Temporal SW filters reduce streaking artifacts, but also reduce temporal resolution at higher spatial frequencies. Parallel MRI (pMRI) may mitigate the artifacts and improve temporal footprint. However, the actual undersampling factors in existing radial MRI applications may result in significant noise/resolution loss. The combination of pMRI and SW may result in improved image quality than with each individual method alone. In this research, we propose an optimized method to combine k-space based parallel MRI with SW reconstruction for radial trajectories.

 
2812.   Efficient Direct Summation Reconstruction for Radial and PROPERLLER MRI Using the Chirp Transform Algorithm 
Yanqiu Feng1, Yanli Song1, Cong Wang1, Taigang He2, Xuegang Xin1, and Wufan Chen1
1School of Biomedical Engineering, Southern Medical University, Guangzhou, China, People's Republic of, 2Royal Brompton Hospital and Imperial College, London, United Kingdom

 
Direct Fourier transform (DFT) could reconstruct MR image from non-Cartesian data with high precision. However, the high computation complexity makes DFT impractical for clinical application. Up to now, the published "FFT" algorithms for non-equispaced data do not strictly compute the DFT of nonequispaced data, but rather some approximation. In this work, an efficient algorithm for DFT using the Chirp Transform Algorithm (CTA) was proposed to reconstruct MR image from non-Cartesian trajectories consisting of lines with equispaced points such as radial or PROPERLLER sampling. The proposed CTA-DFT algorithm is demonstrated to be significantly faster than DFT while keeping the same accuracy.

 
2813.   A Model-based Image Reconstruction Algorithm for Saturation Prepared Radially Acquired Data 
Johannes Tran-Gia1, Daniel Stäb1, Christian Oliver Ritter1, Dietbert Hahn1, and Herbert Köstler1
1Institute of Radiology, University of Würzburg, Würzburg, Bavaria, Germany

 
A model-based image reconstruction algorithm is presented using radially sampled data to reconstruct one fully sampled image for each acquired radial projection after magnetization preparation. For radial trajectories, every acquired projection contains information about the image contrast. By incorporating a signal model into the image reconstruction, it is possible to use this information to resolve the signal evolution with a high temporal resolution. The functionality of the algorithm is demonstrated in phantom studies as well as in in-vivo measurements on a healthy volunteer.

 
2814.   Filter implementation into a 2D radial trajectory for sodium MRI 
Simon Konstandin1, Armin Michael Nagel2, Patrick Michael Heiler1, and Lothar Rudi Schad1
1Computer Assisted Clinical Medicine, Heidelberg University, Mannheim, Germany, 2Medical Physics in Radiology, German Cancer Research Center, Heidelberg, Germany

 
Large voxel sizes (>30mm3) are required for sodium imaging due to its low sensitivity that can result in Gibbs ringing if no filter is used. In this work, a Hamming filter was implemented into a 2D radial trajectory and compared to imaging with a post-filter and without filtering. The absence of Gibbs ringing and an SNR increase of 60% for sodium heart imaging are clearly visible for the filtered images. In conclusion, the use of an implemented filter in the trajectory will improve the SNR and the shape of the PSF.

 
2815.   Ultra short Echo Time Imaging using Pointwise Encoding Time reduction with Radial Acquisition (PETRA) 
David Manuel Grodzki1,2, Peter M Jakob1, and Bjoern Heismann2
1Department of Physics EP5, University of Wuerzburg, Wuerzburg, Bavaria, Germany, 2Magnetic Resonance, Siemens AG, Erlangen, Bavaria, Germany

 
Sequences with ultra short echo time (TE) enable new applications of MRI, including bone, tendon, ligament and dent imaging. In this work a sequence is presented that achieves the shortest possible TE given by TX/RX switching time and gradient performance of the MR Scanner. In PETRA (Pointwise Encoding Time reduction with Radial Acquisition) outer k-space is filled with radial half-projections whereas the centre is measured single pointwise on a Cartesian trajectory. This hybrid sequence combines the features of single point imaging with radial projection imaging. No hardware changes are required.

 
2816.   Simple Method for Adaptive Gradient-Delay Compensation in Radial MRI 
Kai Tobias Block1, and Martin Uecker2
1MR Application and Workflow Development, Healthcare Sector, Siemens AG, Erlangen, Germany, 2Biomedizinische NMR Forschungs GmbH, Göttingen, Germany

 
This work describes a novel approach for the correction of system-dependent gradient delays, which pose a major problem for radial sampling in routine applications. The method performs a cross-correlation analysis of anti-parallel calibration spokes to assess the angle-dependent k-space shift introduced by the delay. The delay is compensated during the gridding procedure by realigning the data according to the estimated shift distance. The method has been implemented for a radial 2D and 3D sequence. It has been evaluated on a large number of commercial MR systems and proved to deliver consistent image quality at a wide range of acquisition bandwidths.

 
2817.   High resolution 3D imaging using multiple oblique view acquisitions 
MinOh Ghim1, Sang-Young Zho1, Eunhae Joe1, and Dong-Hyun Kim1
1Electrical and Electronic Engineering, Yonsei University, Seoul, Korea, Republic of

 
Conventional 3D MR imaging typically uses 3D Fourier encoding acquisitions and/or 3D Fourier transform based reconstruction. However, for high resolution 3D imaging using these methods, SNR can be a limiting factor along with side effects such as ringing with Fourier based reconstruction. Here, we propose an alternative 3D high resolution imaging method where multiple 2D acquisitions are performed using a variable oblique-view pulse scheme. An image-based reconstruction is performed using an iterative back projection process thereby enabling flexible tradeoffs between SNR and resolution.

Traditional Posters : Pulse Sequences, Reconstruction & Analysis
Click on to view the abstract pdf and click on to view the pdf of the poster viewable in the poster hall.
Optimization of 3D Fast Spin Echo

 
Tuesday May 10th
Exhibition Hall  13:30 - 15:30

2818.   Fat-signal Suppression in Single-slab 3D TSE (SPACE) using Water-Selective Refocusing 
John P. Mugler, III1, Dominik Paul2, Wilhelm Horger2, and Berthold Kiefer2
1Radiology, University of Virginia, Charlottesville, VA, United States, 2Siemens Healthcare, Erlangen, Germany

 
This work demonstrates the use of a water-selective refocusing RF pulse to achieve fat-signal suppression in slab-selective single-slab 3D-TSE imaging. This approach slightly extends the echo-train duration, but does not affect the echo spacing for the remainder of the echo train and thus does not compromise the efficiency of the single-slab 3D-TSE technique. Compared to conventional, spectrally-selective pre-pulses for fat suppression, the method illustrated here is insensitive to the degree that the fat magnetization is relaxed. The method is also insensitive to shifts of the fat frequency away from the water frequency due to field inhomogeneity.

 
2819.   Complementary Use of SPAIR and STIR for robust fat suppression in single-slab 3D TSE 
Guobin Li1, Wei Jun Zhang1, Dominik Paul2, and Lars Lauer2
1Siemens Mindit Magnetic Resonance Ltd., Shenzhen, Guang Dong, China, People's Republic of, 2Siemens Healthcare Sector, Erlangen

 
SPAIR fat suppression technique preserves the contrast, but is sensitive to B0 inhomogeneity. Compared to SPAIR, STIR is a robust fat suppression method, but the image contrast will be affected by the inversion recovry procedure. In this work, a new concept is presented, to Complementarily Use SPAIR in the homogeneous regions and short T1 selected inversion Recovery in the inhomogeneous regions for uniform fat suppression in a single acquisition in SPACE, to preserve good contrast in the main region of the FOV and achieve uniform fat suppression in whole FOV.

 
2820.   Variable-flip angle 3D-turbo spin echo imaging utilizing spiral acquisitions 
Samuel Fielden1, Craig Meyer1,2, and John P Mugler, III1,2
1Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States, 2Radiology, University of Virginia

 
Shaping the signal evolution by varying the refocusing RF-pulse amplitudes in turbo-spin-echo (TSE)-type sequences has proven useful for T2-weighted single-slab 3D-TSE imaging in a variety of applications. However, 3D T2-weighted imaging remains time consuming when the number of 3D phase encodes is large. Spiral acquisition gradients cover k-space more efficiently than the traditional, Cartesian approach, and thus provide an attractive method by which shortened scan times can be achieved, in addition to their low sensitivity to flow and motion. Here, we implement and perform a preliminary evaluation of variable-flip-angle 3D-TSE imaging using spiral k-space sampling.

 
2821.   Chemical shift induced slab boundary artifacts reduction in Multi-Slab SPACE 
Guobin Li1, and Dominik Paul2
1Siemens Mindit Magnetic Resonance Ltd., Shenzhen, Guang Dong, China, People's Republic of, 2Siemens Healthcare Sector, Erlangen

 
Slab Boundary Artifacts (SBA) in Multi-Slab SPACE seriously affect the imaging reliability. Chemical shift is a main source of the SBA on high field system. In this work, it is shown that the SBA can be dramatically reduced by shifting the frequency of RF pulses and manipulating the polarity of the slab-selection gradients.

 
2822.   Prosepective Phase Correction for 3D FSE 
Kristin L Granlund1,2, Weitian Chen3, Dawei Gui4, Donglai Huo4, Shawlee Zhao4, Kevin M Koch5, Richard Scott Hinks5, and Anja CS Brau3
1Radiology, Stanford University, Stanford, CA, United States, 2Electrical Engineering, Stanford University, Stanford, CA, United States, 3Global Applied Science Laboratory, GE Healthcare, Menlo Park, CA, United States, 4MR PSD and Applications, GE Healthcare, Waukesha, WI, United States, 5Global Applied Science Laboratory, GE Healthcare, Waukesha, WI, United States

 
Failure to achieve the CPMG conditions for a 3D FSE sequence results in significant image artifacts, particularly for off-isocenter imaging due to system non-idealities. We prospectively correct the sequence by measuring phase errors in the x and z directions during prescan and update the sequence parameters so that the modified sequence meets the CPMG conditions. This iterative correction allows us to collect images without banding artifacts.

Traditional Posters : Pulse Sequences, Reconstruction & Analysis
Click on to view the abstract pdf and click on to view the pdf of the poster viewable in the poster hall.
bSSFP: Improvements & Applications

 
Wednesday May 11th
Exhibition Hall  13:30 - 15:30

2823.   Use of Simulated Annealing for the Design of Fat-suppressed Multiple Repetition Time Balanced SSFP 
Kuan J. Lee1, Hsu-Lei Lee1, Jürgen Hennig1, and Jochen Leupold1
1Universitätsklinikum Freiburg, Freiburg, Baden-Württemberg, Germany

 
Balanced SSFP has high SNR efficiency but often a strong fat signal as well. The fat signal can be suppressed by modifying the spectral profile to place a stopband at the fat frequency. Using multiple TRs and pulses allows the spectral profile to be changed greatly, but the increased number of parameters makes it impossible to test every parameter combination. Until now, parameters for multiple TR SSFP have been chosen by trial-and-error or by using an approximate linear model. We report on the novel use of simulated annealing to search parameter combinations for optimal fat-suppressed multiple TR SSFP at 3T.

 
2824.   An Algebraic Solution for Banding Artifact Removal in bSSFP Imaging 
Michael Nicholas Hoff1, and Qing-San Xiang1,2
1Physics, University of British Columbia, Vancouver, British Columbia, Canada, 2Radiology, University of British Columbia, Vancouver, British Columbia, Canada

 
An algebraic solution (AS) to the bSSFP banding artifact problem is discovered and compared with a preceding geometric cross-solution (GS). Testing on simulated and actual MR images shows that both techniques eliminate bands. The solutions vary in form, in noise performance, and in response to real and imaginary data swapping. As noise is increased, GS outperforms AS in terms of SNR. Nonetheless, the incoherent nature of residual artifact in AS permits regional processing which can yield SNR levels comparable with GS. The existence of two independent solutions should encourage further investigation into optimized methods of bSSFP signal demodulation.

 
2825.   Eddy Current Minimization in Selective Flow Suppression bSSFP Sequences 
Karan Dara1, Mark A Griswold1, Jamal J Derakhshan1, Jeffrey L Sunshine2, and Jeffrey L Duerk1
1Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, United States, 2Department of Radiology, University Hospitals of Cleveland, Cleveland, Ohio, United States

 
Balanced SSFP (bSSFP) sequences with additional preparatory schemes like diffusion weighting, T2 weighting and selective flow suppression are extremely sensitive to changing eddy currents patterns. In this work, we demonstrate a mechanism to minimize eddy currents in bSSFP sequences with preparatory schemes without any change in the bSSFP image contrast. This is achieved by generating a continuous yet dynamically switching gradient pattern along the entire PE axis. This preferentially diminishes deviations in PE gradient amplitude near the centre of k-space and reduces the eddy current artifact intensity.

 
2826.   Time-Resolved 4D MRA using TrueFISP based Spin Tagging and Dynamic Golden Angle Radial Acquisition 
Lirong Yan1, Jiangsheng Yu2, Yiqun Xue2, Rajesh Kumar3, Hee Kwon Song2, and Danny JJ Wang1
1Neurology, UCLA, Los Angeles, CA, United States, 2Radiology, University of Pennsylvania, Philadelphia, PA, United States, 3Neurobiology, UCLA, Los Angeles, CA, United States

 
Unenhanced time-resolved 4D dynamic MRA (dMRA) has been recently introduced by combining arterial spin tagging with a segmented multiphase TrueFISP readout. The present study explored the feasibility for applying dynamic radial sampling with golden angle view increment in a TrueFISP based spin tagging sequence to reduce the total scan time by nearly 10 fold. The reconstructed dMRA images demonstrated the dynamic filling of the Circle of Willis and main branches, albeit with a small degree of temporal smoothing.

 
2827.   Simultaneous T1 and T2 Quantification Using Non-Continuous Balanced SSFP Look-Locker Imaging 
Glenn S. Slavin1
1Global Applied Science Laboratory, GE Healthcare, Bethesda, MD, United States

 
Look-Locker imaging using non-continuous (single-phase) balanced SSFP has been proposed for cardiac T1 mapping. Because data acquisition perturbs the magnetization during relaxation, correction methods are required to calculate the true T1 from the “apparent” T1 (T1*). Since a correction method specific for this approach has not been reported, current T1 estimation techniques can exhibit inconsistent results. This work presents an analytical correction method, derived specifically for non-continuous bSSFP, whereby the true T1 and T2 may be quantified accurately and simultaneously from Look-Locker acquisitions. T1/T2 calculated using this method demonstrated excellent agreement with actual T1/T2 of phantoms and skeletal muscle.

 
2828.   Ultra-short Echo Time Balanced SSFP for Highly Sensitive Detection and Quantification of Multi-resonant 19F Imaging Agents for Targeted Molecular MRI 
Jochen Keupp1, Samuel A Wickline2, Gregory M Lanza2, and Shelton D Caruthers2
1Philips Research Europe, Hamburg, Germany, 2C-TRAIN, Washington University School of Medicine, St. Louis, United States

 
19F-MRI bears a high potential for molecular imaging allowing the direct quantification of targeted perfluoro-carbon nanoparticles (NP). Towards human translation, clinically-relevant compounds (safety, stability) like perfluoro-octyl-bromide (PFOB) should be used. But rich spectra and large chemical shifts add significant complexity. A combination of ultra-short echo time with a balanced SSFP pulse sequence enables highly sensitive detection of multi-resonant imaging labels like PFOB. During the FID readout of 0.6 ms, the PFOB-CF2 line-group is recorded in constructive superposition. Sensitivity comparison to other 19F-MRI sequences like cartesian SSFP or fast-spin echo shows a superior performance of the novel sequence for PFOB imaging.

 
2829.   SPIO quantification using inversion recovery prepared bSSFP for targeted molecular imaging 
Chris V Bowen1,2, and Nicole A Pelot1,3
1Institute for Biodiagnostics (Atlantic), National Research Council, Halifax, NS, Canada, 2Physics and Atmospheric Science, Dalhousie University, Halifax, NS, Canada, 3Physics and Atmospheric Science & Electrical Engineering, Dalhousie University, Halifax, NS, Canada

 
An MRI-based iron quantification method could significantly advance molecular imaging of drugs and diseases in vivo. We propose obtaining R2 values in the presence of SPIO using phase-cycled inversion recovery bSSFP with a novel on-resonance frequency index selection algorithm. The on-resonance frequency was identified as the smallest R2 value after rejecting the largest residuals voxel-by-voxel. Phantoms were imaged at 3T to produce calibration curves using small flip angles to extend dynamic range. With a 20deg flip, quantification was achieved up to 100µgFe/mL. This technique has potential to significantly impact the use of MRI for pre-clinical studies using targeted molecular imaging.

Traditional Posters : Pulse Sequences, Reconstruction & Analysis
Click on to view the abstract pdf and click on to view the pdf of the poster viewable in the poster hall.
Undersampling & Compressed Sensing

 
Thursday May 12th
Exhibition Hall  13:30 - 15:30

2830.   Multiscale Dictionary Learning for MRI 
Saiprasad Ravishankar1, and Yoram Bresler1
1Department of Electrical and Computer Engineering and the Coordinated Science Laboratory, University of Illinois, Urbana, IL, United States

 
Compressed Sensing (CS) MRI with non-adaptive sparsifying transforms such as wavelets and finite differences can perform poorly at high undersampling factors. In this work, we introduce an adaptive framework for MR image reconstruction employing multiscale sparse representations. The multiscale patch-based sparsifying transform (dictionary) is learnt directly using the undersampled k-space data and is thus adapted to the current image. An alternating reconstruction algorithm learns the sparsifying dictionary at different scales, and uses it to remove aliasing and noise in one step, and subsequently restores and fills-in the sampled k-space data in the other step. Experimental results demonstrate the superior performance of such an image reconstruction formulation that exploits image patch sparsity at several scales. The multiscale framework provides highly accurate reconstructions at high undersampling factors. We also show the reconstructions with previous CSMRI methods employing nonadaptive dictionaries and demonstrate significant improvements with our approach over the former.

 
2831.   Adaptive compressed MRI sampling based on wavelet encoding 
Bo Kou1, Guoxi xie2, Bensheng Qiu2, and Xin Liu2
1Shenzhen Institutes of Advanced Technology, Chinese Academy of Science, Shenzhen, China, People's Republic of, 2Shenzhen Institutes of Advanced Technology, Chinese Academy of Science, China, People's Republic of

 
The main idea of Compressed Sensing is to exploit the fact that there is some structure and redundancy in most signals of interest. Clearly, the more we known about the signal and the more the information we encode into the signal processing algorithm, the better performance we can achieve. In this paper, we propose an adaptive compressed MRI sensing scheme that combined wavelet encoding with compressed sensing which originated from the optic image data acquisition . Our approach exploits not only the fact that most of the wavelet coefficients of MR images are small but also the fact that values and locations of the large coefficients have a particular structure. Exploiting the structure of the wavelet coefficients of MR images is achieved by replacing the pseudo-random measurements with a direct and fast method of adaptive wavelet coefficient acquisition.

 
2832.   Undersampled MRI reconstruction using edge-weighted lower case Greek iota1 norm minimization 
Changwei Hu1, Xiaobo Qu2, Di Guo2, Lijun Bao1, Shuhui Cai1, and Zhong Chen1
1Department of Physics, Xiamen University, Xiamen, Fujian, China, People's Republic of, 2Department of Communication Engineering, Xiamen University, Xiamen, Fujian, China, People's Republic of

 
Undersampling k-space is an effective way to reduce acquisition time for MRI. However, aliasing artifacts introduced by undersampling may blur the edges of MR images, which often contain important information for clinical diagnosis. In this work, we propose an edge-weighted model by pluging two weighting matrix into the objective function of constrained l1 norm minimization problem. Reconstructions with more precise edge recovery are then obtained by the proposed EWIT algorithm.

 
2833.   A swifter SWIFT using compressive sensing 
Sairam Geethanath1, Steen Moeller2, Curtis A Corum2, Matthew A Lewis1,3, and Vikram D Kodibagkar1,3
1Joint graduate program in biomedical engineering, UT Arlington and UT Southwestern Medical Center, Dallas, Texas, United States, 2Center for Magnetic Resonance Research, University of Minnesota, 3Radiology, UT Southwestern Medical Center

 
Sweep imaging with Fourier transformation (SWIFT) is a novel MRI technique which facilitates imaging of short T2 nuclei. Currently, exquisite 3D images can be acquired within minutes but imaging dynamic changes in short T2 species, such as T2 exchange contrast agents, would require an even faster imaging scheme. The application of compressed sensing to accelerate SWIFT MR imaging has been demonstrated on a phantom for an acceleration factor ~5. Compressed sensing based reconstruction of the MR volume shows high fidelity with reduced artifacts and lower noise. Future work involves the reconstruction of in vivo data and applications to dynamic imaging.

 
2834.   Investigation on Compressed Sensing Regularization Parameter using Case-PDM 
Jun Miao1, Feng Huang2, and David L Wilson3,4
1Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, United States, 2Invivo Corporation, Gainesville, Florida, United States, 3Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, 4Radiology, University Hospitals of Cleveland, Cleveland, Ohio, United States

 
Case-PDM is applied to investigate TV weight regularization parameter of Compressed Sensing (CS). Experimental results show that optimal TV weight varies across different imaged subject/ pulse sequence/ scanner, and may change slightly for the same data set with different sampling ratio. To achieve a high image quality CS reconstruction, a pre-calibration is necessary to find the optimal TV weight.

 
2835.   MR Compressed Sensing Using FREBAS Transform 
Satoshi Ito1, Koji Miyabayashi2, and Yoshifumi Yamada2
1Research Division of Intelligence and Information Sciencs, Utsunomiya University, Utsunomiya, Tochigi, Japan, 2Utsunomiya University, Utsunomiya, Tochigi, Japan

 
Compressed sensing (CS) aims to reconstruct signals and images from significantly fewer measurements than were traditionally thought necessary. MRI is a medical imaging tool burdened by an inherently slow data acquisition process. The application of CS to MRI has the potential for significant scan time reductions. In this paper we present a new CS method based on the FREBAS transform which we have proposed as a new kind of multi-resolution image analysis. The algorithm and the performances of proposed method were demonstrated and it was shown that proposed CS method can achieve a reduction factor higher than the standard CS method.

 
2836.   The Multiple Transforms Compressed Sensing for MR Angiography 
Joonsung Choi1, Yeji Han1, Jinyoung Hwang1, Jun-Young Chung2, Zang-Hee Cho2, and HyunWook Park1
1Department of Electrical Engineering, KAIST, Daejeon, Korea, Republic of, 2Neuroscience Research Institute, Gachon University of Medicine and Science

 
Compressed sensing (CS) is a newly emerging technique to reconstruct undersampled signal. If certain conditions, such as sparsity and incoherent sampling, are satisfied, the signal can be accurately reconstructed from undersampled data by the CS technique. Therefore, a sparsifying transform is required in the CS technique for the target signal. Conventionally, the CS uses a single sparsifying transform. However, the target signal can be more sparsely represented in some cases by adopting multiple sparsifying transforms. In this work, an adaptive CS algorithm using two transforms is proposed to reconstruct MR angiography images with high accuracy and quality.

 
2837.   Acceleration of High Angular Resolution Diffusion Weighted Images using Compressed Sensing 
Merry P Mani1, Tong Zhu2, Jianhui Zhong2, and Mathews Jacob3
1Rochester Center for Brain Imaging, Electrical and Computer Engineering, University of Rochester, Rochester, NY, United States, 2Imaging Sciences, University of Rochester, Rochester, NY, United States, 3Biomedical Engineering, University of Rochester, Rochester, NY, United States

 
The aim of the study is to test the feasibility of using compressed sensing to accelerate the high angular sampling schemes for DTI. A realistic but simulated k-space data was randomly under-sampled in the frequency-diffusion domain with 256 diffusion directions. By making use of the sparsity of the orientation information in each voxel and choosing an appropriate set of basis functions, the diffusion-weighted images were reconstructed using compressed sensing without aliasing. Up to 8 fold acceleration could be achieved within reasonable reconstruction errors. The technique allows to fit parametric models to high angular resolution DW data due to the chosen set of basis functions.

 
2838.   Gaussian scale mixture-based joint reconstruction of multicomponent MR images from undersampled k-space measurements 
Xiaobo Qu1, Changwei Hu2, Di Guo1, Lijun Bao2, and Zhong Chen2
1Department of Communication Engineering, Xiamen University, Xiamen, Fujian, China, People's Republic of, 2Department of Physics, Xiamen University, Xiamen, Fujian, China, People's Republic of

 
Undersampling the measurement can reduce the acquisition time in magnetic resonance imaging (MRI) at the cost of introducing the aliasing artifacts. The sparsity of magnetic resonance (MR) images in wavelet transforms shows promising results to suppress these artifacts [1]. Recent developments demonstrate the Gaussian Scale Mixture (GSM) for modeling dependency of wavelet coefficients for single image can incorporate more prior information and improve the traditional wavelet-based reconstruction. In this paper, we consider the cases that MR study is comprised by many different types of images of the same patient (e.g. T1, T2, Proton density-PD, etc). By modeling the dependency of wavelet coefficients of these multi-component images as multicomponent GSM (mGSM), we propose an iterative algorithm to jointly reconstruct these MR images from undersampled k-space measurements. Simulation demonstrates that this model can improve the reconstructed MR images than the wavelet-based hard iterative thresholding separately does for each image.

 
2839.   Group Sparse Reconstruction of Vector-Valued Images 
Joshua Trzasko1, and Armando Manduca1
1Mayo Clinic, Rochester, MN, United States

 
In this work we investigate a generalization of sparsity-driven undersampled image reconstruction strategies for image series which do not have a readily identifiable temporal or parametric sparse transformation but for which strong yet unknown spatiotemporal correlations are anticipated.

 
2840.   Compressed Sensing Diffusion Tensor Imaging (DTI) with Tensor and Phase Constraints 
Yue Li1, Manisha Aggarwal1, Jiangyang Zhang2, and Susumu Mori2
1Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, United States, 2Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, United States

 
Compressed sensing method and its variations have been developed for reconstruction of MRI using undersampled k space data. Here we propose a constraint dedicated for diffusion tensor imaging (DTI) as well as a phase constraint that has been used in partial Fourier reconstruction to improve compressed sensing reconstruction accuracy. The testing result on high field mouse embryo DTI shows improvement of reconstruction accuracy in both diffusion weighted (DW) and tensor images.

 
2841.   Separate Magnitude and Phase Regularization via Compressed Sensing 
Feng Zhao1, Jeffrey A. Fessler2, Jon-Fredrik Nielsen1, and Douglas C. Noll1
1Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, United States, 2Electrical Engineering, University of Michigan

 
It is an image reconstruction method which combines Compressed Sensing with separate magnitude and phase regularization. It is proposed to speed up the acquisition and improve performance in reconstructing images with rapid phase map variation.

 
2842.   Phase Constrained Compressed Sensing with Applications for PRF Temperature Mapping 
Zhipeng Cao1, Christopher T. Sica2, Philipp Ehses3, Sukhoon Oh2, Yeun C. Ryu2, Christopher M. Collins1,2, and Mark A. Griswold4
1Bioengineering, The Pennsylvania State University, Hershey, PA, United States, 2Radiology, The Pennsylvania State University, Hershey, PA, United States, 3Research Center for Magnetic Resonance Bavaria (MRB), Würzburg, Germany, 4Radiology, Case Western Reserve University, Cleveland, OH, United States

 
A phase-constrained compressed sensing reconstruction method is proposed. It is validated through simulation and experiments to be effective on smooth or focal, mild or dramatic temperature changes for rapid MRI temperature mapping both on phantom and in vivo based on proton resonance frequency shift. The method can also be combined with partially parallel acquisition techniques for additional acceleration.

 
2843.   Incorporating Support Constraints for Sparse Regularization Reconstruction 
Fan Lam1,2, Raman Subramanian3, Dan Xu3, and Kevin F. King3
1Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States, 2Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, United States, 3GE Healthcare, Waukesha, WI, United States

 
We present a novel reconstruction scheme incorporating not only the prior information that the MR image is sparse in certain transformation domain but also the support information for the target image to be reconstructed. Support can be detected either from low resolution estimate or from certain transformation domain of a high resolution reference image. A mix weighted L1-L2 regularization formulation is established for reconstruction. Data from a noncontrast MRA and a brain imaging experiment are used to demonstrate the advantageous performance of the proposed method compared to conventional compressed sensing based reconstruction from sparsely sampled data.

 
2844.   Novel partial Fourier reconstruction technique using FOCUSS 
Hisamoto Moriguchi1,2, Shin-ichi Urayama3, Yutaka Imai1, Manabu Honda4, and Takashi Hanakawa4,5
1Radiology, Tokai University, Isehara, Kanagawa, Japan, 2Radiology, Hiratsuka municipal hospital, Hiratsuka, Kanagawa, Japan, 3Human Brain Research Center, Kyoto University, Kyoto, Kyoto, Japan, 4Functional Brain Research, National Center of Neurology and Psychiatry, Kodaira, Tokyo, Japan, 5Precursory Research for Embryonic Science and Technology, Japan Science and Technology Agency, Japan

 
Partial Fourier (PF) imaging is one of the most widely used fast data acquisition methods in MRI. In existing PF reconstruction algorithms, image quality depends on estimated phase information. However, it is often difficult to estimate accurate phase. In this study, a novel PF reconstruction technique that does not require phase estimation has been demonstrated. Since the recently proposed focal underdetermined system solver (FOCUSS) has been taken advantage of, the new method is referred to as ePF-FOCUSSf. With PF-FOCUSS, over 50% reduction in scan time can be achieved. Furthermore, images reconstructed using PF-FOCUSS are generally of quite high quality.

 
2845.   Non-Sparse Phantom for Compressed Sensing MRI Reconstruction 
David S Smith1, and Edward Brian Welch1
1Radiology and Radiological Sciences and Institute of Imaging Science, Vanderbilt University, Nashville, TN, United States

 
We have designed a phantom that, unlike the Shepp-Logan phantom, is difficult to reconstruct with compressed sensing MRI techniques. This phantom is not sparse under a gradient transformation and contains many features susceptible to corruption under a partial Fourier measurement operator. And unlike real images, the phantom has no noise, so it may be used for exact measurements of noise-free reconstruction accuracy.

 
2846.   Compressed sensing on TDM-SENSE with rotating RF coil 
Hua Wang1, Adnan Trakic1, Bing Keong Li1, Yeyang Yu1, Feng Liu1, and Stuart Crozier1
1The University of Queensland, Brisbane, QLD, Australia

 
This abstract presents the application of compressed sensing to rotating RF coil concept to exploit the data acquisition redundancy and better imaging quality, based on the fact that compressible signals can be reconstructed from randomly under-sampled frequency information, thus, the imaging acceleration can be achieved without sacrificing much image quality. The proposed method applies the recently developed Time-Division-Multiplexed Sensitivity Encoding scheme with compressed sensing framework to improve and accelerate the image reconstruction using a physically rotating RF coil. RF excitation pulse is randomized to generate a measurement matrix which is incoherent to the sparsity basis. The reconstruction performance is evaluated and shows improved reconstruction performance as compared with conventional case.

 
2847.   Compressed Sensing Reconstruction Improves Variable Density Spiral Functional MRI 
Daniel Holland1, Careesa Liu2, Chris V. Bowen2, Andy Sederman1, Lynn Gladden1, and Steven D. Beyea2
1Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, United Kingdom, 2Institute for Biodiagnostics (Atlantic), National Research Council Canada, Halifax, Nova Scotia, Canada

 
We demonstrate that the use of Compressed Sensing reconstruction of variable density spiral fMRI data minimizes the aliasing artifact inherent to sparse k-space acquisitions that can result in additional signal fluctuations in the time course data. Our data demonstrate an improvement in the apparent fMRI sensitivity relative to the same images reconstructed without CS. CS reconstruction of a 50% undersampled VD spiral acquisition resulted in a 40% increase in whole brain activation volume relative to the same data reconstructed with conventional (non-CS) techniques, demonstrating that fMRI data obtained using VD trajectories should be reconstructed using Compressed Sensing.

 
2848.   Single-Shot Partial-Fourier Spiral Imaging 
Bertram Jakob Wilm1, Christoph Barmet1, Matthieu Guerquin-Kern1,2, Max Haeberlin3, and Klaas Paul Pruessmann1
1Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Zurich, Switzerland, 2Biomedical Imaging Group, EPFL Lausanne, Lausanne, Vaude, Switzerland, 3Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland

 
We show the application of Partial Fourier to spiral imaging. The method is demonstrated for phantom and in-vivo single-shot acquisition allowing for an increase in k-space undersampling. The images with an in-plane resolution of 1.4 mm do not show aliasing related artifacts and are virtually free from B0 off-resonance effects.

 
2849.   Compressed Sensing CPMG with Group-Sparse Reconstruction for Myelin Water Imaging 
Henry Szu-Meng Chen1, Angshul Majumdar2, Rabab Kreidieh Ward2, and Piotr Kozlowski1,3
1UBC MRI Research Centre, Vancouver, BC, Canada, 2Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada, 3ICORD, Vancouver, BC, Canada

 
Myelin water imaging based on multi-echo CPMG sequence is inherently slow, especially for high resolution in vivo animal studies. We hypothesize that using compressed sensing with group-sparse reconstruction will significantly increase the acquisition efficiency of myelin water images. CS accelerated myelin water fraction (MWF) maps were simulated using fully sampled k-space data acquired from excised rat spinal cords at 7T. MWF map quality was assessed and found to be minimally impacted up to an acceleration factor of 2, making the technique a promising approach at increasing acquisition efficiency in myelin water mapping.

 
2850.   Dynamic Contrast-Enhanced Three-Dimensional Lung Imaging Acceleration Using k-t PCA 
Yi-Yu Shih1, Jia-Shuo Hsu2, Yi-Ru Lin3, Shang-Yueh Tsai4, and Hsiao-Wen Chung1,2
1Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan, 2Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan,3Department of Electronic Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, 4Department of Electrical Engineering, Chang Gung University, Taoyuan, Taiwan

 
k-t PCA was used to reconstruct the dynamic 3D lung images under various accelerating conditions. The effects of the number of principal components (PC) were investigated, where the number of PC required was found to larger than in cardiac imaging due to the higher complexity of the branching pulmonary vasculature. The time-intensity curves showed very good consistency with the full-sampled data-set, and the overshoot resulting from temporal discontinuity at the beginning and the end of the curves was mildened, suggesting feasibility of accelerated 3D lung perfusion imaging with better slice coverage and improved temporal resolution.

 
2851.   A 3D-plus-time radial-Cartesian hybrid sampling of k-space with high temporal resolution and maintained image quality for MRI and fMRI 
Maria Magnusson1,2, Olof Dahlqvist Leinhard2,3, and Peter Lundberg2,3
1Dept. of Electrical Engineering, Linköping University, Linköping, Sweden, 2Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden, 3Radiation Physics, Linköping University, Linköping, Sweden

 
The novel method PRESTO-CAN for 3D-plus-time resolved MRI includes a radial-Cartesian hybrid sampling. Golden ratio angular sampling and hourglass filtering provides high temporal resolution. When the MRI-data is used for fMRI, the echo times are long, TE ≈ 37-40 ms, and result in field inhomogeneities and phase variations in the reconstructed images. Therefore, PRESTO-CAN also includes its own calibration and correction procedure. Reconstruction is performed using gridding. The image quality is almost identical to what can be obtained with conventional Cartesian sampling. However, it will be improved further by using a recently proposed optimal pre-weighting function during gridding.

 
2852.   Compressed Sensing in Phase-encoded Multi-dimensional Magnetic Resonance Imaging 
Peng Cao1,2, and Ed X. Wu1,2
1Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Hong Kong SAR, China, People's Republic of, 2Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong SAR, China, People's Republic of

 
This study aims to employ compressed sensing (CS) in phase-encoded 3D magnetic resonance imaging. In this study a CS recover algorithm is developed and implemented to 2 fold accelerate 3D imaging while maintaining image quality. This work reports the first demonstration of CS to phase-encoded, 3D, MR image.

Traditional Posters : Pulse Sequences, Reconstruction & Analysis
Click on to view the abstract pdf and click on to view the pdf of the poster viewable in the poster hall.
Spectroscopic Imaging & Compressed Sensing

 
Monday May 9th
Exhibition Hall  14:00 - 16:00

2853.   A novel parallel sparse MRSI reconstruction scheme 
Ramin Eslami1, and Mathews Jacob2
1Biomedical Engineering, University of Rochester, Rochester, NY, United States, 2University of Rochester

 
Recently, we proposed an efficient MRSI sparse reconstruction technique where we modeled the system using priors such as inhomogeneity, and brain and lipid masks estimated from a companion MR scan for the EPSI sequence using a single channel coil. Here, we propose a fast parallel MRSI acquisition scheme designed on a spiral trajectory. Using a 12-channel head coil, we acquire the in vivo MRSI data at spatial resolution of 44×44 with a single average. We extend our sparse reconstruction scheme to parallel MRSI data on the spiral trajectory. This way, we efficiently reduce measurement noise and other artifacts such as field inhomogeneity and spectral leakage in our proposed reconstruction while we have a fast MRSI acquisition (~1"min" for a slice). We show that the proposed scheme could recover the spectral data and outperforms Tikhonov-regularized SENSE reconstruction. We also demonstrate a two-fold acceleration of the acquisition that leads to a comparable reconstruction.

 
2854.   Undersampled MRSI k-space for spectra with limited support 
Dany Merhej1,2, Helene Ratiney1, Chaouki Diab3, Mohamad Khalil2, and Rémy Prost1
1CREATIS, CNRS UMR 5220, Inserm U1044, INSA-Lyon, Université Lyon 1, Université de Lyon, Lyon, France, 2EDST, Azm research center, Lebanese University, Tripoli, Lebanon, 3ISAE – Cnam Liban, Beirut, Lebanon

 
A major drawback in application of magnetic resonance spectroscopic imaging is the long acquisition time required to gather necessary data to achieve satisfactory resolution. When the chemical shift spectrum is inherently sparse, i.e. with a limited support, it is possible to reconstruct this spectrum from a subset of the k-space samples, thus reducing the number of phase encoding steps and subsequently reducing acquisition time. In this case, our approach outperforms compressive sensing using L1-minimization. The proposed reconstruction technique is validated on simulated, in vitro and in vivo data.

 
2855.   Temporal Acceleration in Hyperpolarization Imaging Using Image-domain Compressed Sensing 
Behzad Sharif1, Debiao Li1,2, and Shawn Wagner1
1Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States, 2Northwestern University, Chicago, IL, United States

 
In hyperpolarization imaging, the magnetization is limited from the start of an imaging sequence and should be utilized while relaxation to thermal equilibrium occurs. Compressed sensing has been used to overcome the rapid loss of magnetization from molecules with short T1. With the introduction of molecules with longer T1, there is potential for high resolution imaging with compressed sensing used in all aspects of data acquisition. We show that high-quality images can be reconstructed from 2-fold undersampled data by exploiting the image-domain sparsity in C-13 imaging. The resulting temporal acceleration will enable higher resolution full-body imaging of hyperpolarized biomarkers for cancer detection.

 
2856.   Accelerated Metabolic Imaging: Application of L1-SPIRiT to Hyperpolarized 13C Parallel Imaging and Compressed Sensing MRSI 
Peter J Shin1, Michael A Ohliger2, Simon Hu2, Peder E. Z. Larson2, Cornelius Von Morze2, Michael Lustig3, and Daniel B Vigneron2
1Joint Graduate Group in Bioengineering, University of California at San Francisco & Berkeley, San Francisco, California, United States, 2Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, California, United States, 3Department of Electrical Engineering and Computer Science, University of California at Berkeley, Berkeley, California, United States

 
Hyperpolarized 13C MRSI is a powerful tool for studying metabolic processes in vivo, enabling monitoring of 13C substrates and downstream metabolic products. However, spatial coverage and resolution of such metabolic images are fundamentally limited by the rapid metabolism and T1 relaxation, necessitating the development of fast data acquisition schemes. In this work, we investigated accelerating hyperpolarized 13C spectroscopic imaging with L1-SPIRiT compressed sensing autocalibration parallel imaging and showed that application of SPIRiT on simulated hyperpolarized 13C parallel imaging provided excellent noise performance and reduced artifacts in highly accelerated imaging schemes.