Benjamin Fürsich^1,2, Tim Sprenger^1,2, Axel Haase¹, and Marion I. Menzel^2
1IMETUM, Technical University, Munich, Bavaria, Germany, ²GE Global Research, Munich, Germany

Different diffusion weighted sequences, including 2D DW-EPI, 2D simultaneous multi-slice EPI, 3D multi-slab EPI and an parameter optimized 3D DW-SSFP, were theoretically compared in terms of relative SNR and SNR efficiency concerning a complete brain scan. Therefore, an optimization of 3D DW-SSFP parameters was performed using an analytic model provided by Freed et al.. The analysis depicts 3D multi-slab EPI as the method of choice for highly efficient neuro-imaging at higher resolutions.

Zhigang Wu¹, Jing Zhang¹, Wenxin Fang¹, and Feng Huang^1
1Philips Healthcare (Suzhou), Suzhou, China

The goal of this work is to provide a new tilted algorithm for zoomed FOV DWI with improved image uniformity, and validate it on 1.5T system. It uses a different titled excitation k-space trajectory, which is also blipped at slice direction, but just tilts the PE direction gradients. It does not increase the k-space step at PE direction, so it has no influence on the sub-pulse bandwidth. It moderates the requirements for hardware components compared with rFOV. We called it iZoom (Improved Zoom FOV imaging).

Xiaodong Ma¹, Zhe Zhang¹, Hui Zhang¹, Bida Zhang², Sheng Fang³, and Hua Guo^1
1Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China, ²Healthcare Department, Philips Research China, Shanghai, China, ³Institute of nuclear and new energy technology, Tsinghua University, Beijing, China

While variable density spiral (VDS) has been used to generate high resolution diffusion tensor imaging, it has low sampling efficiency and severe off-resonance artifacts caused by prolonged readout duration. To solve this, a more efficient trajectory, dual-density spiral (DDS), was proposed to replace VDS in DTI. In vivo results show that DDS can improve the sampling efficiency and reduce off-resonance blurring compared to VDS. Besides, it can correct the motion-induced phase errors more effectively since a larger full-sampling region and thus higher resolution navigator can be provided.

Bertram J. Wilm^1,2, Christoph Barmet^1,2, Simon Gross¹, Lars Kasper¹, Johanna Vannesjo¹, Maximilian Haeberlin¹, Benjamin Dietrich¹, David Brunner¹, Thomas Schmid¹, and Klaas P. Pruessmann^1
1Institute for Biomedical Engineering, University & ETH, Zurich, Zurich, Switzerland, ²Skope Magnetic Resonance Technologies, Zurich, Zurich, Switzerland

Despite its great potential, single-shot spiral MRI is so far not used in clinical practice due to its sensitivity to any encoding deficiencies. We address this problem by applying magnetic field monitoring and demonstrate the benefit for high resolution diffusion imaging. The accurate and consistent encoding information retrieved from magnetic field monitoring data resulted in a strongly improved image quality and achieves image congruence among DW data without image co-registration. The high SNR efficiency and the motion robustness make this sequence ideal for its use for diffusion imaging in clinical practice and research.

Dan Wu¹ and Jiangyang Zhang^2
1Biomedical Engineering, Johns Hopkins University School of Medicine, BALTIMORE, Maryland, United States, ²Radiology, Johns Hopkins University School of Medicine, Maryland, United States

Oscillating gradient spin-echo (OGSE) diffusion MRI is useful to probe tissue microstructures at ultra-short diffusion times, and its applications on clinical MR systems are gradually emerging. However, OGSE diffusion measurements are commonly acquired at relatively low b-values due to gradient constraints, and such measurements contain contributions from perfusion related pseudo-diffusion. In this study, we showed the OGSE signals are sensitive to pseudo-diffusion at low b-values, and proposed to use pulsed and oscillating gradient on orthogonal directions to suppress the contributions from pseudo-diffusion. The hybrid sequence may be useful for future applications of OGSE diffusion MRI on clinical scanners.

Noam Shemesh¹, Andrada Ianuş², Daniel C Alexander², and Ivana Drobnjak^2
1Champalimaud Neuroscience Programme, Champalimaud Center for the Unknown, Lisbon, Portugal, ²Center for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom

Double-Diffusion-Encoding (DDE) MRI methodologies (e.g., double-Pulsed-Field-Gradient (dPFG) or Double-Wave-Vector (DWV)) rely on characteristic amplitude modulations that quantify microscopic anisotropy in highly heterogeneous systems. Here, we present Double-Oscillating-Diffusion-Encoding (DODE), and show that it can enhance DDE’s contrast, thereby providing increased sensitivity towards underlying microstructures. Simulations of DODE at long mixing times using the MISST framework reveal that low frequency oscillations enhance DDE’s contrast in randomly oriented anisotropic pores when compared to experiments in the long diffusion time / short diffusion gradient duration regime. These flexible DODE sequences show much potential for future applications.

Matthew J. Middione¹, Hua Wu², Robert F. Dougherty², Kangrong Zhu³, Adam B. Kerr³, and John M. Pauly^3
1Applied Sciences Laboratory West, GE Healthcare, Meno Park, CA, United States, ²CNI, Stanford University, Stanford, CA, United States, ³Electrical Engineering, Stanford University, Stanford, CA, United States

Echo planar imaging (EPI), especially single shot EPI, is the method of choice for diffusion MRI (dMRI) due to its short scan time and motion insensitivity. However, it is sensitive to chemical-shift artifacts due to the low bandwidth in the phase-encoding direction, which requires the use of efficient fat suppression. Herein we analyze the effects of removing chemical shift artifacts with different fat saturation and suppression techniques for single-spin-echo, dual-spin-echo, and multiband imaging. We propose a single-spin-echo dMRI sequence using multiband imaging and slice select gradient reversal to provide efficient fat suppression, comparable SNR, and reduced scan time.

Peter J Koopmans¹, Robert Frost¹, David A Porter², Wenchuan Wu¹, Peter Jezzard¹, Karla L Miller¹, and Markus Barth^3
1FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom, ²Institute for Medical Image Computing, Fraunhofer MEVIS, Bremen, Germany, ³Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia

Diffusion-weighted, readout-segmented echo-planar imaging is a technique that can produce higher resolution diffusion images than conventional single-shot approaches but is very slow. We accelerated it using simultaneous multislice methods and by using partial Fourier in the segmentation dimension. Results are shown with 133 whole-brain volumes of 1 mm isotropic, acquired in 45 minutes.

Mei-Lan Chu^1,2, Shayan Guhaniyogi¹, Hing-Chiu Chang¹, and Nan-kuei Chen^1
1Brain Imaging and Analysis Center, Duke University Medical Center, Durham, North Carolina, United States, ²Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan

A new POCSMUSE method is developed to produce high-quality and artifact-free multi-shot DTI data in the presence of large-scale intrascan subject motion, using coil sensitivity profiles, in-plane and through-plane position measures, and segment-specific signal variations as constraints. The developed method can effectively remove artifacts originating from both in-plane and through-plane motion in multi-shot DTI data, and is generally compatible with different types of sampling trajectories

Zhongbiao Xu¹, Zhigang Wu², Wufan Chen¹, Yanqiu Feng¹, Feng Huang², Wenxing Fang², and Jing Zhang^2
1Guangdong Provincial Key Laborary of Medical Image Processing, School of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong, China, ²Philips Healthcare (Suzhou) CO.LTD, Suzhou, Jiangsu, China

In this work, we extend multiplexed sensitivity-encoding (MUSE) to address the issues related to shot-to-shot large-scale motion. Our method groups shots into clusters, reconstructs each cluster with MUSE by taking advantage of the same magnitude property inside each cluster, and corrects the inter-shot motion by image registration techniques. The proposed can robustly deliver high quality image even when there is large scale inter-shot motion.