Publications

2018
Scott W Hoge, Kawin Setsompop, and Jonathan R Polimeni. 2018. “Dual-polarity slice-GRAPPA for concurrent ghost correction and slice separation in simultaneous multi-slice EPI.” Magn Reson Med, 80, 4, Pp. 1364-1375.Abstract
PURPOSE: A ghost correction strategy for Simultaneous Multi-Slice (SMS) EPI methods that provides improved ghosting artifact reduction compared to conventional methods is presented. Conventional Nyquist ghost correction methods for SMS-EPI rely on navigator data that contain phase errors from all slices in the simultaneously acquired slice-group. These navigator data may contain spatially nonlinear phase differences near regions of B inhomogeneity, which violates the linear model employed by most EPI ghost correction algorithms, resulting in poor reconstructions. METHODS: Dual-Polarity GRAPPA (DPG) was previously shown to accurately model and correct both spatially nonlinear and 2D phase errors in conventional single-slice EPI data. Here, an extension we call Dual-Polarity slice-GRAPPA (DPsG) is adapted to the slice-GRAPPA method and applied to SMS-EPI data for slice separation and ghost correction concurrently-eliminating the need for a separate ghost correction step while also providing improved slice-specific EPI phase error correction. RESULTS: Images from in vivo SMS-EPI data reconstructed using DPsG in place of conventional Nyquist ghost correction and slice-GRAPPA are presented. DPsG is shown to reduce ghosting artifacts and provide improved temporal SNR compared to the conventional reconstruction. CONCLUSION: The proposed use of DPsG for SMS-EPI reconstruction can provide images with lower artifact levels, higher image fidelity, and improved time-series stability compared to conventional reconstruction methods.
Uten Yarach, Yi-Hang Tung, Kawin Setsompop, Myung-Ho In, Itthi Chatnuntawech, Renat Yakupov, Frank Godenschweger, and Oliver Speck. 2018. “Dynamic 2D self-phase-map Nyquist ghost correction for simultaneous multi-slice echo planar imaging.” Magn Reson Med, 80, 4, Pp. 1577-1587.Abstract
PURPOSE: To develop a reconstruction pipeline that intrinsically accounts for both simultaneous multislice echo planar imaging (SMS-EPI) reconstruction and dynamic slice-specific Nyquist ghosting correction in time-series data. METHODS: After 1D slice-group average phase correction, the separate polarity (i.e., even and odd echoes) SMS-EPI data were unaliased by slice GeneRalized Autocalibrating Partial Parallel Acquisition. Both the slice-unaliased even and odd echoes were jointly reconstructed using a model-based framework, extended for SMS-EPI reconstruction that estimates a 2D self-phase map, corrects dynamic slice-specific phase errors, and combines data from all coils and echoes to obtain the final images. RESULTS: The percentage ghost-to-signal ratios (%GSRs) and its temporal variations for MB3R 2 with a field of view/4 shift in a human brain obtained by the proposed dynamic 2D and standard 1D phase corrections were 1.37 ± 0.11 and 2.66 ± 0.16, respectively. Even with a large regularization parameter λ applied in the proposed reconstruction, the smoothing effect in fMRI activation maps was comparable to a very small Gaussian kernel size 1 × 1 × 1 mm . CONCLUSION: The proposed reconstruction pipeline reduced slice-specific phase errors in SMS-EPI, resulting in reduction of GSR. It is applicable for functional MRI studies because the smoothing effect caused by the regularization parameter selection can be minimal in a blood-oxygen-level-dependent activation map.
An T Vu, Alex Beckett, Kawin Setsompop, and David A Feinberg. 2018. “Evaluation of SLIce Dithered Enhanced Resolution Simultaneous MultiSlice (SLIDER-SMS) for human fMRI.” Neuroimage, 164, Pp. 164-171.Abstract
High isotropic resolution fMRI is challenging primarily due to long repetition times (TR) and insufficient SNR, especially at lower field strengths. Recently, Simultaneous Multi-Slice (SMS) imaging with blipped-CAIPI has substantially reduced scan time and improved SNR efficiency of fMRI. Similarly, super-resolution techniques utilizing sub- voxel spatial shifts in the slice direction have increased both resolution and SNR efficiency. Here we demonstrate the synergistic combination of SLIce Dithered Enhanced Resolution (SLIDER) and SMS for high-resolution, high-SNR whole brain fMRI in comparison to standard resolution fMRI data as well as high-resolution data. With SLIDER-SMS, high spatial frequency information is recovered (unaliased) even in absence of super-resolution deblurring algorithms. Additionally we find that BOLD CNR (as measured by t-value in a visual checkerboard paradigm) is improved by as much as 100% relative to traditionally acquired high- resolution data. Using this gain in CNR, we are able to obtain unprecedented nominally isotropic resolutions at 3T (0.66 mm) and 7T (0.45 mm).
Kawin Setsompop, Qiuyun Fan, Jason Stockmann, Berkin Bilgic, Susie Huang, Stephen F Cauley, Aapo Nummenmaa, Fuyixue Wang, Yogesh Rathi, Thomas Witzel, and Lawrence L Wald. 2018. “High-resolution in vivo diffusion imaging of the human brain with generalized slice dithered enhanced resolution: Simultaneous multislice (gSlider-SMS).” Magn Reson Med, 79, 1, Pp. 141-151.Abstract
PURPOSE: To develop an efficient acquisition for high-resolution diffusion imaging and allow in vivo whole-brain acquisitions at 600- to 700-μm isotropic resolution. METHODS: We combine blipped-controlled aliasing in parallel imaging simultaneous multislice (SMS) with a novel slab radiofrequency (RF) encoding gSlider (generalized slice-dithered enhanced resolution) to form a signal-to-noise ratio-efficient volumetric simultaneous multislab acquisition. Here, multiple thin slabs are acquired simultaneously with controlled aliasing, and unaliased with parallel imaging. To achieve high resolution in the slice direction, the slab is volumetrically encoded using RF encoding with a scheme similar to Hadamard encoding. However, with gSlider, the RF-encoding bases are specifically designed to be highly independent and provide high image signal-to-noise ratio in each slab acquisition to enable self-navigation of the diffusion's phase corruption. Finally, the method is combined with zoomed imaging (while retaining whole-brain coverage) to facilitate low-distortion single-shot in-plane encoding with echo-planar imaging at high resolution. RESULTS: A 10-slices-per-shot gSlider-SMS acquisition was used to acquire whole-brain data at 660 and 760 μm isotropic resolution with b-values of 1500 and 1800 s/mm , respectively. Data were acquired on the Connectome 3 Tesla scanner with 64-channel head coil. High-quality data with excellent contrast were achieved at these resolutions, which enable the visualization of fine-scale structures. CONCLUSIONS: The gSlider-SMS approach provides a new, efficient way to acquire high-resolution diffusion data. Magn Reson Med 79:141-151, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
Bo Zhao, Kawin Setsompop, Elfar Adalsteinsson, Borjan Gagoski, Huihui Ye, Dan Ma, Yun Jiang, P Ellen Grant, Mark A Griswold, and Lawrence L Wald. 2018. “Improved magnetic resonance fingerprinting reconstruction with low-rank and subspace modeling.” Magn Reson Med, 79, 2, Pp. 933-942.Abstract
PURPOSE: This article introduces a constrained imaging method based on low-rank and subspace modeling to improve the accuracy and speed of MR fingerprinting (MRF). THEORY AND METHODS: A new model-based imaging method is developed for MRF to reconstruct high-quality time-series images and accurate tissue parameter maps (e.g., T , T , and spin density maps). Specifically, the proposed method exploits low-rank approximations of MRF time-series images, and further enforces temporal subspace constraints to capture magnetization dynamics. This allows the time-series image reconstruction problem to be formulated as a simple linear least-squares problem, which enables efficient computation. After image reconstruction, tissue parameter maps are estimated via dictionary-based pattern matching, as in the conventional approach. RESULTS: The effectiveness of the proposed method was evaluated with in vivo experiments. Compared with the conventional MRF reconstruction, the proposed method reconstructs time-series images with significantly reduced aliasing artifacts and noise contamination. Although the conventional approach exhibits some robustness to these corruptions, the improved time-series image reconstruction in turn provides more accurate tissue parameter maps. The improvement is pronounced especially when the acquisition time becomes short. CONCLUSIONS: The proposed method significantly improves the accuracy of MRF, and also reduces data acquisition time. Magn Reson Med 79:933-942, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
Berkin Bilgic, Tae Hyung Kim, Congyu Liao, Mary Kate Manhard, Lawrence L Wald, Justin P Haldar, and Kawin Setsompop. 2018. “Improving parallel imaging by jointly reconstructing multi-contrast data.” Magn Reson Med, 80, 2, Pp. 619-632.Abstract
PURPOSE: To develop parallel imaging techniques that simultaneously exploit coil sensitivity encoding, image phase prior information, similarities across multiple images, and complementary k-space sampling for highly accelerated data acquisition. METHODS: We introduce joint virtual coil (JVC)-generalized autocalibrating partially parallel acquisitions (GRAPPA) to jointly reconstruct data acquired with different contrast preparations, and show its application in 2D, 3D, and simultaneous multi-slice (SMS) acquisitions. We extend the joint parallel imaging concept to exploit limited support and smooth phase constraints through Joint (J-) LORAKS formulation. J-LORAKS allows joint parallel imaging from limited autocalibration signal region, as well as permitting partial Fourier sampling and calibrationless reconstruction. RESULTS: We demonstrate highly accelerated 2D balanced steady-state free precession with phase cycling, SMS multi-echo spin echo, 3D multi-echo magnetization-prepared rapid gradient echo, and multi-echo gradient recalled echo acquisitions in vivo. Compared to conventional GRAPPA, proposed joint acquisition/reconstruction techniques provide more than 2-fold reduction in reconstruction error. CONCLUSION: JVC-GRAPPA takes advantage of additional spatial encoding from phase information and image similarity, and employs different sampling patterns across acquisitions. J-LORAKS achieves a more parsimonious low-rank representation of local k-space by considering multiple images as additional coils. Both approaches provide dramatic improvement in artifact and noise mitigation over conventional single-contrast parallel imaging reconstruction. Magn Reson Med 80:619-632, 2018. © 2018 International Society for Magnetic Resonance in Medicine.
Fuyixue Wang, Berkin Bilgic, Zijing Dong, Mary Kate Manhard, Ned Ohringer, Bo Zhao, Melissa Haskell, Stephen F Cauley, Qiuyun Fan, Thomas Witzel, Elfar Adalsteinsson, Lawrence L Wald, and Kawin Setsompop. 2018. “Motion-robust sub-millimeter isotropic diffusion imaging through motion corrected generalized slice dithered enhanced resolution (MC-gSlider) acquisition.” Magn Reson Med, 80, 5, Pp. 1891-1906.Abstract
PURPOSE: To develop an efficient MR technique for ultra-high resolution diffusion MRI (dMRI) in the presence of motion. METHODS: gSlider is an SNR-efficient high-resolution dMRI acquisition technique. However, subject motion is inevitable during a prolonged scan for high spatial resolution, leading to potential image artifacts and blurring. In this study, an integrated technique termed Motion Corrected gSlider (MC-gSlider) is proposed to obtain high-quality, high-resolution dMRI in the presence of large in-plane and through-plane motion. A motion-aware reconstruction with spatially adaptive regularization is developed to optimize the conditioning of the image reconstruction under difficult through-plane motion cases. In addition, an approach for intra-volume motion estimation and correction is proposed to achieve motion correction at high temporal resolution. RESULTS: Theoretical SNR and resolution analysis validated the efficiency of MC-gSlider with regularization, and aided in selection of reconstruction parameters. Simulations and in vivo experiments further demonstrated the ability of MC-gSlider to mitigate motion artifacts and recover detailed brain structures for dMRI at 860 μm isotropic resolution in the presence of motion with various ranges. CONCLUSION: MC-gSlider provides motion-robust, high-resolution dMRI with a temporal motion correction sensitivity of 2 s, allowing for the recovery of fine detailed brain structures in the presence of large subject movements.
Benedikt A Poser and Kawin Setsompop. 2018. “Pulse sequences and parallel imaging for high spatiotemporal resolution MRI at ultra-high field.” Neuroimage, 168, Pp. 101-118.Abstract
The SNR and CNR benefits of ultra-high field (UHF) have helped push the envelope of achievable spatial resolution in MRI. For applications based on susceptibility contrast where there is a large CNR gain, high quality sub-millimeter resolution imaging is now being routinely performed, particularly in fMRI and phase imaging/QSM. This has enabled the study of structure and function of very fine-scale structures in the brain. UHF has also helped push the spatial resolution of many other MRI applications as will be outlined in this review. However, this push in resolution comes at a cost of a large encoding burden leading to very lengthy scans. Developments in parallel imaging with controlled aliasing and the move away from 2D slice-by-slice imaging to much more SNR-efficient simultaneous multi-slice (SMS) and 3D acquisitions have helped address this issue. In particular, these developments have revolutionized the efficiency of UHF MRI to enable high spatiotemporal resolution imaging at an order of magnitude faster acquisition. In addition to describing the main approaches to these techniques, this review will also outline important key practical considerations in using these methods in practice. Furthermore, new RF pulse design to tackle the B and SAR issues of UHF and the increased SAR and power requirement of SMS RF pulses will also be touched upon. Finally, an outlook into new developments of smart encoding in more dimensions, particularly through using better temporal/across-contrast encoding and reconstruction will be described. Just as controlled aliasing fully exploits spatial encoding in parallel imaging to provide large multiplicative gains in accelerations, the complimentary use of these new approaches in temporal and across-contrast encoding are expected to provide exciting opportunities for further large gains in efficiency to further push the spatiotemporal resolution of MRI.
Jaeyeon Yoon, Enhao Gong, Itthi Chatnuntawech, Berkin Bilgic, Jingu Lee, Woojin Jung, Jingyu Ko, Hosan Jung, Kawin Setsompop, Greg Zaharchuk, Eung Yeop Kim, John Pauly, and Jongho Lee. 2018. “Quantitative susceptibility mapping using deep neural network: QSMnet.” Neuroimage, 179, Pp. 199-206.Abstract
Deep neural networks have demonstrated promising potential for the field of medical image reconstruction, successfully generating high quality images for CT, PET and MRI. In this work, an MRI reconstruction algorithm, which is referred to as quantitative susceptibility mapping (QSM), has been developed using a deep neural network in order to perform dipole deconvolution, which restores magnetic susceptibility source from an MRI field map. Previous approaches of QSM require multiple orientation data (e.g. Calculation of Susceptibility through Multiple Orientation Sampling or COSMOS) or regularization terms (e.g. Truncated K-space Division or TKD; Morphology Enabled Dipole Inversion or MEDI) to solve an ill-conditioned dipole deconvolution problem. Unfortunately, they either entail challenges in data acquisition (i.e. long scan time and multiple head orientations) or suffer from image artifacts. To overcome these shortcomings, a deep neural network, which is referred to as QSMnet, is constructed to generate a high quality susceptibility source map from single orientation data. The network has a modified U-net structure and is trained using COSMOS QSM maps, which are considered as gold standard. Five head orientation datasets from five subjects were employed for patch-wise network training after doubling the training data using a model-based data augmentation. Seven additional datasets of five head orientation images (i.e. total 35 images) were used for validation (one dataset) and test (six datasets). The QSMnet maps of the test dataset were compared with the maps from TKD and MEDI for their image quality and consistency with respect to multiple head orientations. Quantitative and qualitative image quality comparisons demonstrate that the QSMnet results have superior image quality to those of TKD or MEDI results and have comparable image quality to those of COSMOS. Additionally, QSMnet maps reveal substantially better consistency across the multiple head orientation data than those from TKD or MEDI. As a preliminary application, the network was further tested for three patients, one with microbleed, another with multiple sclerosis lesions, and the third with hemorrhage. The QSMnet maps showed similar lesion contrasts with those from MEDI, demonstrating potential for future applications.
Ali M Golestani, Zahra Faraji-Dana, Mohammad Kayvanrad, Kawin Setsompop, Simon J Graham, and Jean J Chen. 2018. “Simultaneous Multislice Resting-State Functional Magnetic Resonance Imaging at 3 Tesla: Slice-Acceleration-Related Biases in Physiological Effects.” Brain Connect, 8, 2, Pp. 82-93.Abstract
Simultaneous multislice echo-planar imaging (SMS-EPI) can enhance the spatiotemporal resolution of resting-state functional MRI (rs-fMRI) by encoding and simultaneously imaging "groups" of slices. However, phenomena, including respiration, cardiac pulsatility, respiration volume per time (RVT), and cardiac rate variation (CRV), referred to as "physiological processes," impact SMS-EPI rs-fMRI in a manner that is yet to be well characterized. In particular, physiological noise may incur aliasing and introduce spurious signals from one slice into another within the "slice group" in rs-fMRI data, resulting in a deleterious effect on resting-state functional connectivity MRI (rs-fcMRI) maps. In the present work, we aimed to quantitatively compare the effects of physiological noise on regular EPI and SMS-EPI in terms of rs-fMRI data and resulting functional connectivity measurements. We compare SMS-EPI and regular EPI data acquired from 11 healthy young adults with matching parameters. The physiological noise characteristics were compared between the two data sets through different combinations of physiological regression steps. We observed that the physiological noise characteristics differed between SMS-EPI and regular EPI, with cardiac pulsatility contributing more to noise in regular EPI data but low-frequency heart rate variability contributing more to SMS-EPI. In addition, a significant slice-group bias was observed in the functional connectivity density maps derived from SMS-EPI data. We conclude that making appropriate corrections for physiological noise is likely more important for SMS-EPI than for regular EPI acquisitions.
Laura D Lewis, Kawin Setsompop, Bruce R Rosen, and Jonathan R Polimeni. 2018. “Stimulus-dependent hemodynamic response timing across the human subcortical-cortical visual pathway identified through high spatiotemporal resolution 7T fMRI.” Neuroimage, 181, Pp. 279-291.Abstract
Recent developments in fMRI acquisition techniques now enable fast sampling with whole-brain coverage, suggesting fMRI can be used to track changes in neural activity at increasingly rapid timescales. When images are acquired at fast rates, the limiting factor for fMRI temporal resolution is the speed of the hemodynamic response. Given that HRFs may vary substantially in subcortical structures, characterizing the speed of subcortical hemodynamic responses, and how the hemodynamic response shape changes with stimulus duration (i.e. the hemodynamic nonlinearity), is needed for designing and interpreting fast fMRI studies of these regions. We studied the temporal properties and nonlinearities of the hemodynamic response function (HRF) across the human subcortical visual system, imaging superior colliculus (SC), lateral geniculate nucleus of the thalamus (LGN) and primary visual cortex (V1) with high spatiotemporal resolution 7 Tesla fMRI. By presenting stimuli of varying durations, we mapped the timing and nonlinearity of hemodynamic responses in these structures at high spatiotemporal resolution. We found that the hemodynamic response is consistently faster and narrower in subcortical structures than in cortex. However, the nonlinearity in LGN is similar to that in cortex, with shorter duration stimuli eliciting larger and faster responses than would have been predicted by a linear model. Using oscillatory visual stimuli, we tested the frequency response in LGN and found that its BOLD response tracked high-frequency (0.5 Hz) oscillations. The LGN response magnitudes were comparable to V1, allowing oscillatory BOLD signals to be detected in LGN despite the small size of this structure. These results suggest that the increase in the speed and amplitude of the hemodynamic response when neural activity is brief may be the key physiological driver of fast fMRI signals, enabling detection of high-frequency oscillations with fMRI. We conclude that subcortical visual structures exhibit fast and nonlinear hemodynamic responses, and that these dynamics enable detection of fast BOLD signals even within small deep brain structures when imaging is performed at ultra-high field.
Daniel Polak, Kawin Setsompop, Stephen F Cauley, Borjan A Gagoski, Himanshu Bhat, Florian Maier, Peter Bachert, Lawrence L Wald, and Berkin Bilgic. 2018. “Wave-CAIPI for highly accelerated MP-RAGE imaging.” Magn Reson Med, 79, 1, Pp. 401-406.Abstract
PURPOSE: To introduce a highly accelerated T1-weighted magnetization-prepared rapid gradient echo (MP-RAGE) acquisition that uses wave-controlled aliasing in parallel imaging (wave-CAIPI) encoding to retain high image quality. METHODS: Significant acceleration of the MP-RAGE sequence is demonstrated using the wave-CAIPI technique. Here, sinusoidal waveforms are used to spread aliasing in all three directions to improve the g-factor. Combined with a rapid (2 s) coil sensitivity acquisition and data-driven trajectory calibration, we propose an online integrated acquisition-reconstruction pipeline for highly efficient MP-RAGE imaging. RESULTS: The 9-fold accelerated MP-RAGE acquisition can be performed in 71 s, with a maximum and average g-factor of g  = 1.27 and g  = 1.06 at 3T. Compared with the state-of-the-art method controlled aliasing in parallel imaging results in higher acceleration (2D-CAIPIRINHA), this is a factor of 4.6/1.4 improvement in g /g . In addition, we demonstrate a 57 s acquisition at 7T with 12-fold acceleration. This acquisition has a g-factor performance of g  = 1.15 and g  = 1.04. CONCLUSION: Wave encoding overcomes the g-factor noise amplification penalty and allows for an order of magnitude acceleration of MP-RAGE acquisitions. Magn Reson Med 79:401-406, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
Zhe Wu, Berkin Bilgic, Hongjian He, Qiqi Tong, Yi Sun, Yiping Du, Kawin Setsompop, and Jianhui Zhong. 2018. “Wave-CAIPI ViSTa: highly accelerated whole-brain direct myelin water imaging with zero-padding reconstruction.” Magn Reson Med, 80, 3, Pp. 1061-1073.Abstract
PURPOSE: This study introduces a highly accelerated whole-brain direct visualization of short transverse relaxation time component (ViSTa) imaging using a wave controlled aliasing in parallel imaging (CAIPI) technique, for acquisition within a clinically acceptable scan time, with the preservation of high image quality and sufficient spatial resolution, and reduced residual point spread function artifacts. METHODS: Double inversion RF pulses were applied to preserve the signal from short T components for directly extracting myelin water signal in ViSTa imaging. A 2D simultaneous multislice and a 3D acquisition of ViSTa images incorporating wave-encoding were used for data acquisition. Improvements brought by a zero-padding method in wave-CAIPI reconstruction were also investigated. RESULTS: The zero-padding method in wave-CAIPI reconstruction reduced the root-mean-square errors between the wave-encoded and Cartesian gradient echoes for all wave gradient configurations in simulation, and reduced the side-main lobe intensity ratio from 34.5 to 16% in the thin-slab in vivo ViSTa images. In a 4 × acceleration simultaneous-multislice scenario, wave-CAIPI ViSTa achieved negligible g-factors (g /g  = 1.03/1.10), while retaining minimal interslice artifacts. An 8 × accelerated acquisition of 3D wave-CAIPI ViSTa imaging covering the whole brain with 1.1 × 1.1 × 3 mm voxel size was achieved within 15 minutes, and only incurred a small g-factor penalty (g /g  = 1.05/1.16). CONCLUSION: Whole-brain ViSTa images were obtained within 15 minutes with negligible g-factor penalty by using wave-CAIPI acquisition and zero-padding reconstruction. The proposed zero-padding method was shown to be effective in reducing residual point spread function for wave-encoded images, particularly for ViSTa.
2017
Congyu Liao, Berkin Bilgic, Mary Kate Manhard, Bo Zhao, Xiaozhi Cao, Jianhui Zhong, Lawrence L Wald, and Kawin Setsompop. 2017. “3D MR fingerprinting with accelerated stack-of-spirals and hybrid sliding-window and GRAPPA reconstruction.” Neuroimage, 162, Pp. 13-22.Abstract
PURPOSE: Whole-brain high-resolution quantitative imaging is extremely encoding intensive, and its rapid and robust acquisition remains a challenge. Here we present a 3D MR fingerprinting (MRF) acquisition with a hybrid sliding-window (SW) and GRAPPA reconstruction strategy to obtain high-resolution T, T and proton density (PD) maps with whole brain coverage in a clinically feasible timeframe. METHODS: 3D MRF data were acquired using a highly under-sampled stack-of-spirals trajectory with a steady-state precession (FISP) sequence. For data reconstruction, k-k under-sampling was mitigated using SW combination along the temporal axis. Non-uniform fast Fourier transform (NUFFT) was then applied to create Cartesian k-space data that are fully-sampled in the in-plane direction, and Cartesian GRAPPA was performed to resolve k under-sampling to create an alias-free SW dataset. T, T and PD maps were then obtained using dictionary matching. RESULTS: Phantom study demonstrated that the proposed 3D-MRF acquisition/reconstruction method is able to produce quantitative maps that are consistent with conventional quantification techniques. Retrospectively under-sampled in vivo acquisition revealed that SW + GRAPPA substantially improves quantification accuracy over the current state-of-the-art accelerated 3D MRF. Prospectively under-sampled in vivo study showed that whole brain T, T and PD maps with 1 mm resolution could be obtained in 7.5 min. CONCLUSIONS: 3D MRF stack-of-spirals acquisition with hybrid SW + GRAPPA reconstruction may provide a feasible approach for rapid, high-resolution quantitative whole-brain imaging.
William A Grissom, Kawin Setsompop, Samuel A Hurley, Jeffrey Tsao, Julia V Velikina, and Alexey A Samsonov. 2017. “Advancing RF pulse design using an open-competition format: Report from the 2015 ISMRM challenge.” Magn Reson Med, 78, 4, Pp. 1352-1361.Abstract
PURPOSE: To advance the best solutions to two important RF pulse design problems with an open head-to-head competition. METHODS: Two sub-challenges were formulated in which contestants competed to design the shortest simultaneous multislice (SMS) refocusing pulses and slice-selective parallel transmission (pTx) excitation pulses, subject to realistic hardware and safety constraints. Short refocusing pulses are needed for spin echo SMS imaging at high multiband factors, and short slice-selective pTx pulses are needed for multislice imaging in ultra-high field MRI. Each sub-challenge comprised two phases, in which the first phase posed problems with a low barrier of entry, and the second phase encouraged solutions that performed well in general. The Challenge ran from October 2015 to May 2016. RESULTS: The pTx Challenge winners developed a spokes pulse design method that combined variable-rate selective excitation with an efficient method to enforce SAR constraints, which achieved 10.6 times shorter pulse durations than conventional approaches. The SMS Challenge winners developed a time-optimal control multiband pulse design algorithm that achieved 5.1 times shorter pulse durations than conventional approaches. CONCLUSION: The Challenge led to rapid step improvements in solutions to significant problems in RF excitation for SMS imaging and ultra-high field MRI. Magn Reson Med 78:1352-1361, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
Stephen F Cauley, Kawin Setsompop, Berkin Bilgic, Himanshu Bhat, Borjan Gagoski, and Lawrence L Wald. 2017. “Autocalibrated wave-CAIPI reconstruction; Joint optimization of k-space trajectory and parallel imaging reconstruction.” Magn Reson Med, 78, 3, Pp. 1093-1099.Abstract
PURPOSE: Fast MRI acquisitions often rely on efficient traversal of k-space and hardware limitations, or other physical effects can cause the k-space trajectory to deviate from a theoretical path in a manner dependent on the image prescription and protocol parameters. Additional measurements or generalized calibrations are typically needed to characterize the discrepancies. We propose an autocalibrated technique to determine these discrepancies. METHODS: A joint optimization is used to estimate the trajectory simultaneously with the parallel imaging reconstruction, without the need for additional measurements. Model reduction is introduced to make this optimization computationally efficient, and to ensure final image quality. RESULTS: We demonstrate our approach for the wave-CAIPI fast acquisition method that uses a corkscrew k-space path to efficiently encode k-space and spread the voxel aliasing. Model reduction allows for the 3D trajectory to be automatically calculated in fewer than 30 s on standard vendor hardware. The method achieves equivalent accuracy to full-gradient calibration scans. CONCLUSIONS: The proposed method allows for high-quality wave-CAIPI reconstruction across wide ranges of protocol parameters, such as field of view (FOV) location/orientation, bandwidth, echo time (TE), resolution, and sinusoidal amplitude/frequency. Our framework should allow for the autocalibration of gradient trajectories from many other fast MRI techniques in clinically relevant time. Magn Reson Med 78:1093-1099, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
Choukri Mekkaoui, Timothy G Reese, Marcel P Jackowski, Stephen F Cauley, Kawin Setsompop, Himanshu Bhat, and David E Sosnovik. 2017. “Diffusion Tractography of the Entire Left Ventricle by Using Free-breathing Accelerated Simultaneous Multisection Imaging.” Radiology, 282, 3, Pp. 850-856.Abstract
Purpose To develop a clinically feasible whole-heart free-breathing diffusion-tensor (DT) magnetic resonance (MR) imaging approach with an imaging time of approximately 15 minutes to enable three-dimensional (3D) tractography. Materials and Methods The study was compliant with HIPAA and the institutional review board and required written consent from the participants. DT imaging was performed in seven healthy volunteers and three patients with pulmonary hypertension by using a stimulated echo sequence. Twelve contiguous short-axis sections and six four-chamber sections that covered the entire left ventricle were acquired by using simultaneous multisection (SMS) excitation with a blipped-controlled aliasing in parallel imaging readout. Rate 2 and rate 3 SMS excitation was defined as two and three times accelerated in the section axis, respectively. Breath-hold and free-breathing images with and without SMS acceleration were acquired. Diffusion-encoding directions were acquired sequentially, spatiotemporally registered, and retrospectively selected by using an entropy-based approach. Myofiber helix angle, mean diffusivity, fractional anisotropy, and 3D tractograms were analyzed by using paired t tests and analysis of variance. Results No significant differences (P > .63) were seen between breath-hold rate 3 SMS and free-breathing rate 2 SMS excitation in transmural myofiber helix angle, mean diffusivity (mean ± standard deviation, [0.89 ± 0.09] × 10 mm/sec vs [0.9 ± 0.09] × 10 mm/sec), or fractional anisotropy (0.43 ± 0.05 vs 0.42 ± 0.06). Three-dimensional tractograms of the left ventricle with no SMS and rate 2 and rate 3 SMS excitation were qualitatively similar. Conclusion Free-breathing DT imaging of the entire human heart can be performed in approximately 15 minutes without section gaps by using SMS excitation with a blipped-controlled aliasing in parallel imaging readout, followed by spatiotemporal registration and entropy-based retrospective image selection. This method may lead to clinical translation of whole-heart DT imaging, enabling broad application in patients with cardiac disease. RSNA, 2016 Online supplemental material is available for this article.
Tae Hyung Kim, Kawin Setsompop, and Justin P Haldar. 2017. “LORAKS makes better SENSE: Phase-constrained partial fourier SENSE reconstruction without phase calibration.” Magn Reson Med, 77, 3, Pp. 1021-1035.Abstract
PURPOSE: Parallel imaging and partial Fourier acquisition are two classical approaches for accelerated MRI. Methods that combine these approaches often rely on prior knowledge of the image phase, but the need to obtain this prior information can place practical restrictions on the data acquisition strategy. In this work, we propose and evaluate SENSE-LORAKS, which enables combined parallel imaging and partial Fourier reconstruction without requiring prior phase information. THEORY AND METHODS: The proposed formulation is based on combining the classical SENSE model for parallel imaging data with the more recent LORAKS framework for MR image reconstruction using low-rank matrix modeling. Previous LORAKS-based methods have successfully enabled calibrationless partial Fourier parallel MRI reconstruction, but have been most successful with nonuniform sampling strategies that may be hard to implement for certain applications. By combining LORAKS with SENSE, we enable highly accelerated partial Fourier MRI reconstruction for a broader range of sampling trajectories, including widely used calibrationless uniformly undersampled trajectories. RESULTS: Our empirical results with retrospectively undersampled datasets indicate that when SENSE-LORAKS reconstruction is combined with an appropriate k-space sampling trajectory, it can provide substantially better image quality at high-acceleration rates relative to existing state-of-the-art reconstruction approaches. CONCLUSION: The SENSE-LORAKS framework provides promising new opportunities for highly accelerated MRI. Magn Reson Med 77:1021-1035, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
Lipeng Ning, Kawin Setsompop, Carl-Fredrik Westin, and Yogesh Rathi. 2017. “New insights about time-varying diffusivity and its estimation from diffusion MRI.” Magn Reson Med, 78, 2, Pp. 763-774.Abstract
PURPOSE: Characterizing the relation between the applied gradient sequences and the measured diffusion MRI signal is important for estimating the time-dependent diffusivity, which provides important information about the microscopic tissue structure. THEORY AND METHODS: In this article, we extend the classical theory of Stepišnik for measuring time-dependent diffusivity under the Gaussian phase approximation. In particular, we derive three novel expressions which represent the diffusion MRI signal in terms of the mean-squared displacement, the instantaneous diffusivity, and the velocity autocorrelation function. We present the explicit signal expressions for the case of single diffusion encoding and oscillating gradient spin-echo sequences. Additionally, we also propose three different models to represent time-varying diffusivity and test them using Monte-Carlo simulations and in vivo human brain data. RESULTS: The time-varying diffusivities are able to distinguish the synthetic structures in the Monte-Carlo simulations. There is also strong statistical evidence about time-varying diffusivity from the in vivo human data set. CONCLUSION: The proposed theory provides new insights into our understanding of the time-varying diffusivity using different gradient sequences. The proposed models for representing time-varying diffusivity can be utilized to study time-varying diffusivity using in vivo human brain diffusion MRI data. Magn Reson Med 78:763-774, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
Tommi Raij, Aapo Nummenmaa, Marie-France Marin, Daria Porter, Sharon Furtak, Kawin Setsompop, and Mohammed R Milad. 2017. “Prefrontal Cortex Stimulation Enhances Fear Extinction Memory in Humans.” Biol Psychiatry.Abstract
BACKGROUND: Animal fear conditioning studies have illuminated neuronal mechanisms of learned associations between sensory stimuli and fear responses. In rats, brief electrical stimulation of the infralimbic cortex has been shown to reduce conditioned freezing during recall of extinction memory. Here, we translated this finding to humans with magnetic resonance imaging-navigated transcranial magnetic stimulation (TMS). METHODS: Subjects (N = 28) were aversively conditioned to two different cues (day 1). During extinction learning (day 2), TMS was paired with one of the conditioned cues but not the other. TMS parameters were similar to those used in rat infralimbic cortex: brief pulse trains (300 ms at 20 Hz) starting 100 ms after cue onset, total of four trains (28 TMS pulses). TMS was applied to one of two targets in the left frontal cortex, one functionally connected (target 1) and the other unconnected (target 2, control) with a human homologue of infralimbic cortex in the ventromedial prefrontal cortex. Skin conductance responses were used as an index of conditioned fear. RESULTS: During extinction recall (day 3), the cue paired with TMS to target 1 showed significantly reduced skin conductance responses, whereas TMS to target 2 had no effect. Further, we built group-level maps that weighted TMS-induced electric fields and diffusion magnetic resonance imaging connectivity estimates with fear level. These maps revealed distinct cortical regions and large-scale networks associated with reduced versus increased fear. CONCLUSIONS: The results showed that spatiotemporally focused TMS may enhance extinction learning and/or consolidation of extinction memory and suggested novel cortical areas and large-scale networks for targeting in future studies.

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