Merlin J Fair^1,2, Congyu Liao^1,2, Daeun Kim³, Divya Varadarajan^1,2, Justin P Haldar^3,4, and Kawin Setsompop^1,2,5
1A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States, ²Department of Radiology, Harvard Medical School, Boston, MA, United States, ³Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, United States, ⁴Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, United States, ⁵Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, United States

Diffusion-PEPTIDE incorporates the recently developed rapid multi-shot relaxometry technique Propeller EPTI with Dynamic Encoding (PEPTIDE) into a diffusion acquisition scheme. PEPTIDE enables fast acquisition of distortion- and blurring-free images, time-resolved for different timepoints with varying T2 & T2* weighting, with self-navigation for correction of shot-to-shot phase-variation and motion. Diffusion-PEPTIDE is demonstrated here to enable distortion-free in vivo diffusion-relaxometry with large parameter space in an sensible acquisition time.

Michiel Cottaar¹, Benjamin C. Tendler¹, Wenchuan Wu¹, Karla L. Miller¹, and Saad Jbabdi^1
1WIN@FMRIB, University of Oxford, Oxford, United Kingdom

We propose a novel sequence that adds a second asymmetric spin echo after a standard Stejskal-Tanner sequence. This allows the estimation of the off-resonance frequency of the diffusion-weighted signal due to the myelin magnetic susceptibility. Varying the orientation of the diffusion-weighting gradient dephases different fibre populations. In simulations we show that for a sufficiently high b-value (>~3 ms/μm²), the intra-axonal water will dominate leading to a simple relation between the myelin-induced frequency shift and the log g-ratio. This allows the difference in log g-ratio between crossing fibres to be measured and hence estimate the myelination of individual crossing tracts.

Jochen Keupp¹, Bernhard Gleich¹, and Ulrich Katscher^1
1Philips Research, Hamburg, Germany

A combined acquisition of distortion-free diffusion-weighted images and tissue conductivity maps is explored using a fully balanced double echo steady state (DESS) sequence. Banding artifacts are avoided using sufficiently high gradient moments of the diffusion gradient, such that the banding is contained within single voxels. The stability of the B1 transceive phase measurement by the balanced DESS sequence allows the derivation of quantitative tissue conductivity based second derivative using standard EPT (electrical properties tomography) methods. Feasibility of simultaneous DWI and EPT is shown on a 3T MRI system in phantom and volunteer experiments (head).

Pamela Wochner¹, Torben Schneider², Jason Stockmann³, Jack Lee¹, and Ralph Sinkus^1,4
1School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom, ²Philips Healthare, Guildford, United Kingdom, ³Department of Radiology, Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States, ⁴Inserm U1148, LVTS, University Paris Diderot, Paris, France

Diffusion MRI classically uses linear gradients to encode information about micro-structure in the loss of signal magnitude. When replaced by gradients varying quadratically in space, anisotropic diffusion results in a net phase shift, while the signal magnitude is largely preserved.  This allows the extraction of information from signal phase inaccessible to other diffusion MRI methods. The phase evolution of anisotropic fiber phantoms were studied in simulations and diffusion experiments. Simulations confirm increasing phase change with increasing anisotropy and mixing time between diffusion gradients. First MR experiments with different mixing times show a phase shift in good agreement with theoretical estimate.

Filip Szczepankiewicz^1,2,3, Irvin Teh⁴, Erica Dall'Armellina⁴, Sven Plein⁴, Jurgen E. Schneider⁴, and Carl-Fredrik Westin^2,3
1Clinical Sciences Lund, Lund University, Lund, Sweden, ²Radiology, Brigham and Women's Hospital, Boston, MA, United States, ³Harvard Medical School, Boston, MA, United States, ⁴Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom

Motion compensation is vital for cardiac diffusion MRI. In this paper we propose an optimized gradient waveform design that allows tensor-valued diffusion encoding with motion compensation. We demonstrate that it works for in vivo cardiac imaging and we show that it is more efficient than previous designs.

Kun Zhou¹, Wei Liu¹, and Yulin V Chang^2
1Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China, ²Siemens Medical Solutions USA, Boston, MA, United States

Diffusion weighted imaging with EPI can suffer from image distortions due to sensitivity to B0 inhomogeneity and chemical shift related artifacts induced by incomplete fat suppression. In this study, we propose a TSE BLADE sequence with Dixon water-fat separation for DWI. With this technique, distortion-free DWI with robust fat suppression was shown to be feasible, even in body regions with strong B0 inhomogeneity.

Henrik Lundell¹, Samo Lasič^1,2, Filip Szczepankiewicz^3,4,5, Markus Nilsson³, Daniel Topgaard⁶, Jürgen E. Schneider⁷, and Irvin Teh^7
1Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark, ²Random Walk Imaging AB, Lund, Denmark, ³Clinical Sciences, Lund University, Lund, Sweden, ⁴Harvard Medical School, Boston, MA, United States, ⁵Brigham and Women's Hospital, Boston, MA, United States, ⁶Physical Chemistry, Lund University, Lund, Sweden, ⁷Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom

Diffusion encoding with general gradient waveforms provides flexibility and experimental efficiency for multidimensional diffusion encoding (MDE). Here we investigate b-tensor shape and spectral content as two independent measurement dimensions for imaging myocardial microstructure. By tuning spectral content, we demonstrate that time-dependent diffusion can be controlled for across b-tensor shapes and that tuning in itself provide a strong image contrast in a clinically feasible setting. For encoding high frequencies alone, our isotropic encoding provides higher experimental efficiency. 

Marco Pizzolato¹, Marco Palombo², Elisenda Bonet-Carne^2,3, Francesco Grussu^2,4, Andrada Ianus⁵, Fabian Bogusz⁶, Tomasz Pieciak^6,7, Lipeng Ning⁸, Stefano B. Blumberg², Thomy Mertzanidou², Daniel C. Alexander², Maryam Afzali⁹, Santiago Aja-Fernández^7,9, Derek K. Jones^9,10, Carl-Fredrik Westin⁸, Yogesh Rathi⁸, Steven H. Baete^11,12, Lucilio Cordero-Grande¹³, Thilo Ladner¹⁴, Paddy J. Slator², Daan Christiaens^13,15, Jean-Philippe Thiran^1,16, Anthony N. Price¹³, Farshid Sepehrband¹⁷, Fan Zhang⁸, and Jana Hutter^13
1Signal Processing Lab (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland, ²Department of Computer Science, Centre for Medical Image Computing, University College London, London, United Kingdom, ³BCNatal Fetal Medicine Research Center, Barcelona, Spain, ⁴Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom, ⁵Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal, ⁶AGH University of Science and Technology, Kraków, Poland, ⁷Laboratorio de Procesado de Imagen (LPI), Universidad de Valladolid, Valladolid, Spain, ⁸Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States, ⁹Cardiff University Brain Research Imaging Center (CUBRIC), School of Psychology, University of Cardiff, Cardiff, United Kingdom, ¹⁰Mary MacKillop Institute for Health Research, Faculty of Health Sciences, Australian Catholic University, Melbourne, Australia, ¹¹Center for Biomedical Imaging, Dept. of Radiology, New York University School of Medicine, New York, NY, United States, ¹²Center for Advanced Imaging Imaging, Innovation and Research, New York University School of Medicine, New York, NY, United States, ¹³Centre for Medical Engineering, Centre for the Developing Brain, King's College London, London, United Kingdom, ¹⁴Department of Chemistry and Applied Biosciences, ETH Zurich, Zurich, Switzerland, ¹⁵Department of Electrical Engineering (ESAT-PSI), KU Leuven, Leuven, Belgium, ¹⁶Radiology Department, Centre Hospitalier Universitaire Vaudois and University of Lausanne, Lausanne, Switzerland, ¹⁷Laboratory of Neuro Imaging (LONI), USC Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, United States

The variety of possible combinations of acquisition parameters is key to the versatility of MRI as a diagnostic modality. However, the full exploration of the parameter space defined by b-values, gradient directions, inversion and echo times comes at the expense of the acquisition time. We present the results of an open challenge where different methods were proposed to predict the content of a densely sampled acquisition, which explores such parameter space, from only a subset of parameter combinations. These indicate the possibility of leveraging the redundancy in the data to shorten the acquisition time while minimizing information loss.

Martins Otikovs¹, Lingceng Ma¹, and Lucio Frydman^1
1Weizmann Institute of Science, Rehovot, Israel

Spatiotemporal encoding (SPEN) is an alternative ultrafast imaging technique which allows one to manipulate the bandwidth along the phase-encoding (PE) direction as well as to achieve T₂* refocusing throughout the FID acquisition, thereby overcoming distortions observed along EPI’s PE dimension. The study compares multislice 2D SPEN and a 3D SPEN sequence variants against EPI derivatives, evaluating their ability to deliver prostate diffusion-weighted imaging (DWI) data and apparent diffusion coefficient (ADC) maps on healthy human volunteers.  Essentially distortion-free diffusion weighted images and ADC maps of prostate with good SNR were achieved by the 2D SPEN variant.

Grant Kaijuin Yang^1,2, Ek Tsoon Tan³, Eric Fiveland⁴, Thomas Foo⁴, and Jennifer McNab^2
1Electrical Engineering, Stanford University, Stanford, CA, United States, ²Radiology, Stanford University, Stanford, CA, United States, ³Hospital for Special Surgery in Manhattan, New York, NY, United States, ⁴GE Global Research, Niskayuna, NY, United States

In this work, we measure time-dependent effects on diffusion kurtosis estimates in the in vivo human brain over an extended range of b-values(458-2000s/mm²) and frequencies(0-96Hz) using a high-performance head gradient coil on a whole-body 3T MRI.