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Compressed sensing for body MRI

Feng, Li; Benkert, Thomas; Block, Kai Tobias; Sodickson, Daniel K; Otazo, Ricardo; Chandarana, Hersh
The introduction of compressed sensing for increasing imaging speed in magnetic resonance imaging (MRI) has raised significant interest among researchers and clinicians, and has initiated a large body of research across multiple clinical applications over the last decade. Compressed sensing aims to reconstruct unaliased images from fewer measurements than are traditionally required in MRI by exploiting image compressibility or sparsity. Moreover, appropriate combinations of compressed sensing with previously introduced fast imaging approaches, such as parallel imaging, have demonstrated further improved performance. The advent of compressed sensing marks the prelude to a new era of rapid MRI, where the focus of data acquisition has changed from sampling based on the nominal number of voxels and/or frames to sampling based on the desired information content. This article presents a brief overview of the application of compressed sensing techniques in body MRI, where imaging speed is crucial due to the presence of respiratory motion along with stringent constraints on spatial and temporal resolution. The first section provides an overview of the basic compressed sensing methodology, including the notion of sparsity, incoherence, and nonlinear reconstruction. The second section reviews state-of-the-art compressed sensing techniques that have been demonstrated for various clinical body MRI applications. In the final section, the article discusses current challenges and future opportunities. LEVEL OF EVIDENCE: 5 J. Magn. Reson. Imaging 2016.
PMCID:5352490
PMID: 27981664
ISSN: 1522-2586
CID: 2363682

Mitigation of B1+ inhomogeneity using spatially selective excitation with jointly designed quadratic spatial encoding magnetic fields and RF shimming

Hsu, Yi-Cheng; Lattanzi, Riccardo; Chu, Ying-Hua; Cloos, Martijn A; Sodickson, Daniel K; Lin, Fa-Hsuan
PURPOSE: The inhomogeneity of flip angle distribution is a major challenge impeding the application of high-field MRI. We report a method combining spatially selective excitation using generalized spatial encoding magnetic fields (SAGS) with radiofrequency (RF) shimming to achieve homogeneous excitation. This method can be an alternative approach to address the challenge of B1+ inhomogeneity using nonlinear gradients. METHODS: We proposed a two-step algorithm that jointly optimizes the combination of nonlinear spatial encoding magnetic fields and the combination of multiple RF transmitter coils and then optimizes the locations, RF amplitudes, and phases of the spokes. RESULTS: Our results show that jointly designed SAGS and RF shimming can provide a more homogeneous flip angle distribution than using SAGS or RF shimming alone. Compared with RF shimming alone, our approach can reduce the relative standard deviation of flip angle by 56% and 52% using phantom and human head data, respectively. CONCLUSION: The jointly designed SAGS and RF shimming method can be used to achieve homogeneous flip angle distributions when fully parallel RF transmission is not available. Magn Reson Med, 2016. (c) 2016 International Society for Magnetic Resonance in Medicine.
PMCID:5538365
PMID: 27696518
ISSN: 1522-2594
CID: 2273952

Free-Breathing Volumetric Fat/Water Separation by Combining Radial Sampling, Compressed Sensing, and Parallel Imaging

Benkert, Thomas; Feng, Li; Sodickson, Daniel K; Chandarana, Hersh; Block, Kai Tobias
PURPOSE: Conventional fat/water separation techniques require that patients hold breath during abdominal acquisitions, which often fails and limits the achievable spatial resolution and anatomic coverage. This work presents a novel approach for free-breathing volumetric fat/water separation. METHODS: Multiecho data are acquired using a motion-robust radial stack-of-stars three-dimensional GRE sequence with bipolar readout. To obtain fat/water maps, a model-based reconstruction is used that accounts for the off-resonant blurring of fat and integrates both compressed sensing and parallel imaging. The approach additionally enables generation of respiration-resolved fat/water maps by detecting motion from k-space data and reconstructing different respiration states. Furthermore, an extension is described for dynamic contrast-enhanced fat-water-separated measurements. RESULTS: Uniform and robust fat/water separation is demonstrated in several clinical applications, including free-breathing noncontrast abdominal examination of adults and a pediatric subject with both motion-averaged and motion-resolved reconstructions, as well as in a noncontrast breast exam. Furthermore, dynamic contrast-enhanced fat/water imaging with high temporal resolution is demonstrated in the abdomen and breast. CONCLUSION: The described framework provides a viable approach for motion-robust fat/water separation and promises particular value for clinical applications that are currently limited by the breath-holding capacity or cooperation of patients. Magn Reson Med, 2016. (c) 2016 International Society for Magnetic Resonance in Medicine.
PMCID:5344788
PMID: 27612300
ISSN: 1522-2594
CID: 2238792

Four-dimensional respiratory motion-resolved whole heart coronary MR angiography

Piccini, Davide; Feng, Li; Bonanno, Gabriele; Coppo, Simone; Yerly, Jerome; Lim, Ruth P; Schwitter, Juerg; Sodickson, Daniel K; Otazo, Ricardo; Stuber, Matthias
PURPOSE: Free-breathing whole-heart coronary MR angiography (MRA) commonly uses navigators to gate respiratory motion, resulting in lengthy and unpredictable acquisition times. Conversely, self-navigation has 100% scan efficiency, but requires motion correction over a broad range of respiratory displacements, which may introduce image artifacts. We propose replacing navigators and self-navigation with a respiratory motion-resolved reconstruction approach. METHODS: Using a respiratory signal extracted directly from the imaging data, individual signal-readouts are binned according to their respiratory states. The resultant series of undersampled images are reconstructed using an extradimensional golden-angle radial sparse parallel imaging (XD-GRASP) algorithm, which exploits sparsity along the respiratory dimension. Whole-heart coronary MRA was performed in 11 volunteers and four patients with the proposed methodology. Image quality was compared with that obtained with one-dimensional respiratory self-navigation. RESULTS: Respiratory-resolved reconstruction effectively suppressed respiratory motion artifacts. The quality score for XD-GRASP reconstructions was greater than or equal to self-navigation in 80/88 coronary segments, reaching diagnostic quality in 61/88 segments versus 41/88. Coronary sharpness and length were always superior for the respiratory-resolved datasets, reaching statistical significance (P < 0.05) in most cases. CONCLUSION: XD-GRASP represents an attractive alternative for handling respiratory motion in free-breathing whole heart MRI and provides an effective alternative to self-navigation. Magn Reson Med, 2016. (c) 2016 Wiley Periodicals, Inc.
PMCID:5040623
PMID: 27052418
ISSN: 1522-2594
CID: 2066172

Online Radial Multiband Magnetic Resonance Fingerprinting [Meeting Abstract]

Cloos, Martijn A; Zhao, Tiejun; Knoll, Florian; Sodickson, Daniel K
ORIGINAL:0014723
ISSN: 1524-6965
CID: 4535152

Learning a Variational Model for Compressed Sensing MRI Reconstruction [Meeting Abstract]

Hammernik, Kerstin; Knoll, Florian; Sodickson, Daniel K; Pock, Thomas
ORIGINAL:0014692
ISSN: 1524-6965
CID: 4534382

AN ANALYSIS OF THE EFFECT OF 3D PRINTED RENAL CANCER MODELS ON SURGICAL PLANNING [Meeting Abstract]

Rude, Temitope; Wake, Nicole; Sodickson, Daniel K; Borin, James; Stifelman, Michael; Chandarana, Hersh; Huang, William C
ISI:000375278600474
ISSN: 1527-3792
CID: 2509792

Low Rank plus Sparse Spatiotemporal MRI: Acceleration, Background Suppression, and Motion Learning

Chapter by: Otazo, Ricardo; Candes, Emmanuel; Sodickson, Daniel K
in: Handbook of robust low-rank and sparse matrix decomposition : applications in image and video processing by Bouwmans, Thierry; Aybat, Necdet Serhat; Zahzah, El-hadi [Eds]
Boca Raton, FL : CRC Press, 2016
pp. 17-1-17-18
ISBN: 1498724620
CID: 2492982

Dependence of B1+ and B1- Field Patterns of Surface Coils on the Electrical Properties of the Sample and the MR Operating Frequency

Vaidya, Manushka V; Collins, Christopher M; Sodickson, Daniel K; Brown, Ryan; Wiggins, Graham C; Lattanzi, Riccardo
In high field MRI, the spatial distribution of the radiofrequency magnetic ( B1) field is usually affected by the presence of the sample. For hardware design and to aid interpretation of experimental results, it is important both to anticipate and to accurately simulate the behavior of these fields. Fields generated by a radiofrequency surface coil were simulated using dyadic Green's functions, or experimentally measured over a range of frequencies inside an object whose electrical properties were varied to illustrate a variety of transmit [Formula: see text] and receive [Formula: see text] field patterns. In this work, we examine how changes in polarization of the field and interference of propagating waves in an object can affect the B1 spatial distribution. Results are explained conceptually using Maxwell's equations and intuitive illustrations. We demonstrate that the electrical conductivity alters the spatial distribution of distinct polarized components of the field, causing "twisted" transmit and receive field patterns, and asymmetries between [Formula: see text] and [Formula: see text]. Additionally, interference patterns due to wavelength effects are observed at high field in samples with high relative permittivity and near-zero conductivity, but are not present in lossy samples due to the attenuation of propagating EM fields. This work provides a conceptual framework for understanding B1 spatial distributions for surface coils and can provide guidance for RF engineers.
PMCID:5082994
PMID: 27795697
ISSN: 1552-5031
CID: 2296462

Introductory magnetic resonance imaging physics

Chapter by: Sodickson, Aaron D; Sodickson, Daniel K
in: Handbook of neuro-oncology neuroimaging by Newton, Herbert B [Eds]
San Diego, CA, US: Elsevier Academic Press, 2016
pp. 157-166
ISBN: 978-0-12-800945-1
CID: 2259702