Gabriel Ramos-Llorden¹, Daniel Park¹, Christian Mirkes², Cameron M. Cushing³, Paul Weavers³, Hong-Hsi Lee¹, Qiyuan Tian¹, Alina Scholz⁴, Boris Keil⁴, Berkin Bilgic^1,5, Anastasia Yendiki¹, Thomas Witzel⁶, and Susie Y. Huang^1,5
1Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States, ²Skope Magnetic Resonance Technologies AG, Zurich, Switzerland, ³Skope Magnetic Resonance Inc, Lake Mills, WI, United States, ⁴Institute of Medical Physics and Radiation Protection, Giessen, Germany, ⁵Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, United States, ⁶Q Bio Inc,, San Carlos, MA, United States

Whole brain ex vivo diffusion MRI needs high b-value encoding to compensate for the reduced diffusivity, requiring human brain scanners with ultra-strong diffusion gradients. At that regime, eddy currents become too severe, to the point image distortions and ghosting artifacts cannot be enough mitigated with conventional image reconstruction and post-processing approaches.  On a 3T Connectom scanner , we demonstrate the importance of spatiotemporal field monitoring  to measure and model eddy currents. When Fourier reconstruction is informed with  the unwanted spatiotemporal evolution of the phase, distortion- and ghosting-free high-resolution DW images  can be achieved.

Anjali Datta¹, Dwight Nishimura¹, and Corey Baron^2
1Stanford University, Stanford, CA, United States, ²Western University, London, ON, Canada

Phase-cycled bSSFP enables off-resonance-robust bSSFP imaging. Conventional phase-cycle combination methods weight brighter phase-cycles more, assuming that passband signal is brighter than off-resonant signal. However, near-band signal can be hyperintense, most notably for flowing spins, so traditional methods fail to mitigate these artifacts. Incorporating knowledge of B_o enables inclusion of only passband signal, and exclusion of dark bands and near-band hyperintense artifacts. Using a golden-angle radial trajectory for a free-breathing, phase-cycled acquisition enables reconstruction of a B_o-map time series without any additional scans. This facilitates field-map-based combination throughout the respiratory and cardiac cycles, resulting in substantially reduced hyperintense artifacts than root-sum-of-squares.

Seon-Ha Hwang¹, Hyun-Soo Lee², Seung Hong Choi³, and Sung-Hong Park^1
1Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea, Republic of, ²Siemens Healthineers, Seoul, Korea, Republic of, ³Department of Radiology, Seoul National University College of Medicine, Seoul, Korea, Republic of

Top-up algorithm requires two EPI images with opposite gradient polarities to make one corrected image. Here, top-up algorithm with a single k-space is proposed for single-shot pseudo-centric EPI, where a k-space can be separated into two halves with opposite distortions. A field map could be estimated by applying top-up algorithm to the two halves. The estimated map compensated the distortions well while preserving inner brain structures. The proposed approach provided 1.8 times higher perfusion SNR than conventional linear EPI. The approach is promising for magnetization-prepared imaging that requires high SNR, high temporal resolution, and minimal distortion with no additional scan.

Melissa W. Haskell¹, Anish Lahiri¹, Jon-Fredrik Nielsen², Jeffrey A. Fessler¹, and Douglas C. Noll^2
1Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, United States, ²Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States

Artifacts due to B₀ field off-resonance result in image distortions and blurring in non-Cartesian acquisitions. FieldMapNet is a learning-based method to map from each image in a spiral-in BOLD fMRI acquisition to a corresponding B₀ fieldmap at that timepoint. We train FieldMapNet in a supervised fashion using custom data acquired at three echo times to generate ground truth dynamic fieldmaps. We then perform a tailored B₀ correction at each fMRI timepoint using a model-based image reconstruction (MBIR). We show improved image space RMSE using FieldMapNet vs. a separately acquired GRE fieldmap, and a reduction in distortion artifacts and blurring.

Tess E Wallace^1,2, Tobias Kober^3,4,5, Jason P Stockmann^1,6, Jonathan R Polimeni^1,6, Simon K Warfield^1,2, and Onur Afacan^1,2
1Radiology, Harvard Medical School, Boston, MA, United States, ²Computational Radiology Laboratory, Boston Children's Hospital, Boston, MA, United States, ³Advanced Clinical Imaging Technology Group, Siemens Healthcare, Lausanne, Switzerland, ⁴Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland, ⁵LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland, ⁶Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States

Real-time B₀ shimming enables improved compensation for the effects of dynamic field perturbations in MRI compared to retrospective approaches, which are computationally intensive and cannot compensate for inherent losses of information. FID navigators can rapidly characterize spatiotemporal field changes using a forward model that predicts the effect of B₀ shim changes on the measured FID signal, making them ideally suited for real-time applications. In this work, we implement real-time field control using FID navigators to compensate for spatially linear field changes and demonstrate substantially improved T₂*-weighted image quality in the presence of field perturbations in three volunteers scanned at 3T.  

Negin Yaghmaie^1,2, Warda T. Syeda^3,4, Yasmin Blunck^1,2, Rebecca Glarin^1,5, Daniel Staeb⁶, Kieran O'Brien⁶, Scott Kolbe^7,8,9, and Leigh A. Johnston^1,2
1Melbourne Brain Centre Imaging Unit, The University of Melbourne, Melbourne, Australia, ²Department of Biomedical Engineering, The University of Melbourne, Melbourne, Australia, ³Melbourne Neuropsychiatry Centre, The University of Melbourne, Melbourne, Australia, ⁴Department of Medicine, The University of Melbourne, Melbourne, Australia, ⁵Department of Radiology, Royal Melbourne Hospital, Melbourne, Australia, ⁶MR Research Collaborations, Siemens Healthcare Pty Ltd, Australia, ⁷Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia, ⁸Department of Radiology, Alfred Hospital, Melbourne, Australia, ⁹Department of Medicine and Radiology, The University of Melbourne, Melbourne, Australia

An eddy current correction algorithm is proposed that exploits the spatially distributed nature of the receive coil array with signal acquisition immediately preceding image readout in PGSE-EPI diffusion-weighted imaging. The array coil phase for each diffusion gradient direction is expanded using spherical harmonics to yield an estimate of the eddy current-induced field shift in the FOV, and the resultant eddy current-induced pixel shift maps. Distortion corrected diffusion-weighted images are subsequently produced using the estimated pixel shift maps for each diffusion direction, with the method demonstrated in phantom and in-vivo 7T experimental data.

Alessandro M Scotti¹, Zheng Zhong², and Xiaohong Joe Zhou^1,3,4,5
1Center for MR Research, University of Illinois at Chicago, Chicago, IL, United States, ²Department of Radiology, Stanford University, Stanford, CA, United States, ³Department of Radiology, University of Illinois at Chicago, Chicago, IL, United States, ⁴Department of Neurosurgery, University of Illinois at Chicago, Chicago, IL, United States, ⁵Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, IL, United States

Crusher gradients, typically having very high amplitude, can induce a substantial amount of eddy currents, causing various artifacts. In order to fully characterize the spatiotemporal characteristics of the currents, we have developed a spin echo version of the previously reported SPEEDI technique. The method consists of a series of spin echo acquisitions where each echo point is assigned to a different k-space, reaching a temporal resolution equal to the dwell time. The measured phase difference between sequences with positive and negative crushers revealed B₀  and linear eddy currents with time constants equal to the ones measured by the manufacturer’s tool.

Hyungseok Jang¹, Jiyo S Athertya¹, Yajun Ma¹, Alecio F Lombardi¹, Saeed Jerban¹, Christine B Chung^1,2, Eric Y Chang^1,2, and Jiang Du^1
1Radiology, University of California, San Diego, San Diego, CA, United States, ²Radiology Service, Veterans Affairs San Diego Healthcare System, San Diego, CA, United States

The double echo steady state (DESS) sequence has been investigated extensively due to its short scan time and flexible image contrast achieved from a combination of a free induction decay (FID)-like S+ signal and simulated echo-based S- signal. Ultrashort echo time-based DESS (UTE-DESS) has recently been proposed for imaging of short T₂ tissues in the human knee joint, but the effect of eddy currents in this technique has not yet been investigated. In this study, we demonstrate the effects of B₀ and linear eddy current and elucidate the importance of eddy current compensation (ECC) for reliable UTE-DESS imaging.