Congyu Liao^1,2, Uten Yarach³, Xiaozhi Cao^1,2, Siddharth Srinivasan Iyer⁴, Nan Wang^1,2, Tae Hyung Kim^5,6, Berkin Bilgic^5,6, Adam Kerr^1,7, and Kawin Setsompop^1,2
1Department of Radiology, Stanford University, Stanford, CA, United States, ²Department of Electrical Engineering, Stanford University, Stanford, CA, United States, ³Radiologic Technology Department, Associated Medical Sciences, Chiang Mai University, Chiang Mai, Thailand, ⁴Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, United States, ⁵Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States, ⁶Department of Radiology, Harvard Medical School, Boston, MA, United States, ⁷Stanford Center for Cognitive and Neurobiological Imaging, Stanford University, Stanford, CA, United States

BUDA-cEPI combines a circular-EPI (cEPI) trajectory with Blip-Up and Down Acquisition (BUDA), to achieve high-fidelity diffusion imaging. It employs full-ramp-sampling to efficiently cover a circular k-space to shorten the readout-train and mitigate T₂*-blurring. For further readout-shortening, a combined phase-encoding(PE) & readout(RO) partial-Fourier (pF) is employed, where PE-pF is resolved via opposing the blip-up and down EPI-shots, and S-LORAKS reconstruction is used to effectively fill-out the remaining k-space. This resulted in an acquisition with markedly-reduced TE and ~40% reduced echo-train-length and T₂*-blurring compared to standard-EPI at the same R_inplane and PE-pF. To achieve high-SNR, BUDA-cEPI is also combined with a gSlider-multi-slab acquisition. 

Rafael O'Halloran¹, Hadrien Dyvorne¹, Laura Sacolick¹, Jo Schlemper¹, Michal Sofka¹, Sadegh Salehi¹, Samantha By¹, Riana Schleicher², Edmond Knopp¹, Kevin Sheth³, and W. Taylor Kimberly^2
1Hyperfine, Inc, Guilford, CT, United States, ²Neurology, Massachusetts General Hospital, Boston, MA, United States, ³Yale New Haven Hospital, New Haven, CT, United States

A sequence is described for DWI on a portable, 0.064T scanner. Images in a healthy subject and a patient with pathology are shown.

Ekin Karasan¹, Zhiyong Zhang², and Michael Lustig^1
1University of California, Berkeley, Berkeley, CA, United States, ²Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China

Displacement Spectrum Imaging (DiSpect) is a Fourier encoding variant of Displacement Encoding with Stimulated Echoes (DENSE). DiSpect can resolve a multi-dimensional spectrum of displacements that spins exhibit between tagging and imaging. We previously demonstrated ASL-like retrospective vessel-selective perfusion imaging with DiSpect. Here, we demonstrate the versatility of DiSpect by doing the reverse; tracing how blood drains from the capillary bed through the cerebral venous system. We image two locations in the superior sagittal sinus and trace how the superior superficial veins drain into the superior sagittal sinus, in a sense measuring reverse perfusion.

Jana Hutter^1,2, Raphael Tomi-Tricot³, Thomas A Wilkinson^1,2, Philippa A Bridgen^1,2, Enrico DeVita², Shaihan A Malik^1,2, and Joseph V Hajnal^1,2
1London Collaborative Ultra high field System (LoCUS), London, United Kingdom, ²Centre for Medical Engineering, King's College London, London, United Kingdom, ³Siemens Healthcare Limited, Frimley, United Kingdom

Spin tagging perfusion MR imaging allows the movement of blood in human tissue to be visualized and quantified non-invasively and contrast agent-free. Velicity-selection Arterial Spin Labeling (VSASL) relies on the velocity instead of the location for tagging. It is less dependent on the anatomy and coil coverage but includes directional dependence and can suffer from reduced SNR. POSSUM expands VSASL to spherical, directional-independant encoding and slice shuffling to enable more robust perfusion imaging at 7T.

Dimo Ivanov¹, Sriranga Kashyap^1,2, Laurentius Huber¹, Josef Pfeuffer³, Kâmil Uludağ⁴, and Benedikt A Poser^1
1Department of Cognitive Neuroscience, Maastricht University, Maastricht, Netherlands, ²Techna Institute, University Health Network, Toronto, ON, Canada, ³Siemens Healthineers, Erlangen, Germany, ⁴Techna Institute & Koerner Scientist in MR Imaging, Toronto, ON, Canada

Arterial spin labeling (ASL) at 7T is beneficial due to the higher signal-to-noise ratio (SNR) and the longer T₁ of blood and tissues. A whole-brain 7T pulsed ASL approach with simultaneous multi-slice (SMS) echo planar imaging readouts at multiple inversion times is presented. The interplay between the number of inversion times acquired, the total acceleration factor employed, and the temporal SNR was investigated. In summary, a protocol with in-plane acceleration factor 2 and SMS factor 2 offers the best compromise between perfusion tSNR and number of inversion times and can be used in clinical applications investigating perfusion parameters beyond CBF.

Eve Shalom¹, Harrison Kim², Rianne A. van der Heijden³, Zaki Ahmed⁴, Reyna Patel⁵, David A. Hormuth⁶, Julie C. DiCarlo⁷, Nicholas J. Sisco⁸, Richard D. Dortch⁸, Ashley M. Stokes⁸, Marianna Inglese^9,10, Matthew Grech-Sollars^11,12, Nicola Toschi^13,14, Prativa Sahoo¹⁵, Anup Singh¹⁶, Sanjay K. Verma¹⁷, Divya K. Rathore¹⁸, Ali Nabavizadeh¹⁹, Hamidreza Saligheh Rad^20,21, Leland S. Hu²², Laura C. Bell²³, Steven Sourbron²⁴, and Anahita Fathi Kazerooni^25
1School of Physics and Astronomy, University of Leeds, Leeds, United Kingdom, ²The University of Alabama at Birmingham, Birmingham, AL, United States, ³Department of Radiology & Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, Netherlands, ⁴Mayo Clinic, Rochester, MN, United States, ⁵Department of Radiology, Neuroradiology Division, Mayo Clinic, Scottsdale, AZ, United States, ⁶Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX, United States, ⁷University of Texas at Austin, Austin, TX, United States, ⁸Neurological Imaging, Barrow Neurological Innovation Center, Phoenix, AZ, United States, ⁹Department of Surgery and Cancer, Imperial College London, London, United Kingdom, ¹⁰Department of Biomedicine and Prevention, University of Rome “Tor Vergata”, Roma, Italy, ¹¹Department of Surgery & Cancer, Imperial College London, London, United Kingdom, ¹²Department of Medical Physics, Royal Surrey NHS Foundation Trust, Guildford, United Kingdom, ¹³Department of Biomedicine and Prevention, University of Rome "Tor Vergata", Rome, Italy, ¹⁴Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School, Boston, MA, United States, ¹⁵University Medicine Göttingen, Göttingen, Germany, ¹⁶Indian Institute of Technology Delhi, New Delhi, India, ¹⁷Singapore Bioimaging Consortium (SBIC), Singapore, Singapore, ¹⁸GPU.IO, Pune, India, ¹⁹Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States, ²⁰Quantitative MR Imaging and Spectroscopy Group, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran (Islamic Republic of), ²¹Centre for Computational Imaging & Simulation Technologies in Biomedicine, School of Computing / School of Medicine, University of Leeds, Leeds, United Kingdom, ²²Neuroradiology Division, Department of Radiology, Mayo Clinic, Phoenix, AZ, United States, ²³Genentech, Inc., South San Francisco, CA, United States, ²⁴Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom, ²⁵Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States

While there is growing evidence that DCE-MRI may provide insights about the response of patients to therapies, there is a lack of standardized software quantification tools, resulting in variability in reported K^trans values across different studies and limiting its utility in clinical applications. We have designed and launched the Open Science Initiative for Perfusion Imaging (OSIPI)-DCE challenge to provide recommended and benchmarked analysis tools for K^trans estimation in the brain, by evaluating and comparing DCE software tools in terms of accuracy, repeatability, and reproducibility. Here, we report on the preliminary results of this challenge.