Diffusion: Pulse Sequences
Tuesday 4 May 2010
Victoria Hall 10:30-12:30 Moderators: Roland Bammer and Jenifer McNab

10:30   Debate: Journeys into Space: k or q

Delving Deeper into q (Space)
Derek K. Jones

Reaching into Outer (k) Space
Michael Moseley
     
10:42 187. 

Improving SNR Per Unit Time in Diffusion Imaging Using a Blipped-CAIPIRINHA Simultaneous Multi-Slice EPI Acquisition
Kawin Setsompop1,2, J Cohen-Adad1,2, J A. McNab1,2, B A. Gagoski3, V J. Wedeen1,2, L L. Wald1,2
1
Radiology, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States; 2Harvard Medical School, Boston, MA, United States; 3EECS, Massachusetts Institute of Technology, Cambridge, MA, United States

The acquisition of simultaneous slices using EPI has the potential to increase the number of diffusion directions obtained per unit time, thus allowing more diffusion encoding in HARDI and DSI acquisitions in a clinically relevant scan time. In this work, we apply simultaneous multi-slice method using a novel blipped-CAIPIRINHA technique to lower the g-factor penalty of parallel imaging. We validate the method using g-factor maps and bedpostx with HARDI acquisitions in the brain. We show that with this technique a 10 minutes, 64-direction HARDI acquisition can be acquired in ~3 minutes at no appreciable loss in SNR or diffusion information.

     
10:54 188

Diffusion Weighted Image Domain Propeller EPI (DW IProp EPI)
Stefan Skare1,2, Samantha J. Holdsworth1, Roland Bammer1
1
Radiology, Stanford University, Stanford, CA, United States; 2MR-Center, Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden

A new pulse sequence for diffusion imaging is presented, called image domain Propeller EPI (iProp-EPI). Here, propeller blades are acquired in the image domain ,distinct from other propeller-driven pulse sequences, such as PROPELLER and SAP-EPI, where blades are defined in k-space. iProp-EPI has significantly reduced distortions compared with EPI; is immune to spatially-varying non-linear phase changes; can correct for motion; and may be useful for multi-channel coils since the overlap between the blades results in a higher SNR in the image center where its most needed

     
11:06 189.  

Hadamard Slice-Encoding for Reduced-FOV Single-Shot Diffusion-Weighted EPI
Emine Ulku Saritas1, Daeho Lee1, Ajit Shankaranarayanan2, Dwight G. Nishimura1
1
Department of Electrical Engineering, Stanford University, Stanford, CA, United States; 2Applied Science Laboratory, GE Healthcare, Menlo Park, CA, United States

High in-plane resolution and the ability to acquire a large number of slices are essential for diffusion-weighted imaging (DWI) of small structures, such as the spinal cord. Recently, a reduced-FOV method that uses 2D echo-planar RF excitation pulses to achieve high in-plane resolution was proposed. In this work, we present a Hadamard slice-encoding scheme to double the number of slices without any SNR or time penalty, with significant improvements to increase the SNR efficiency and reduce the inter-slice crosstalk. We validate our results with in vivo high-resolution axial DWI of the spinal cord.

     
11:18 190.

Concurrent Higher-Order Field Monitoring Eliminates Thermal Drifts in Parallel DWI - not available
Bertram Jakob Wilm1, Christoph Barmet1, Carolin Reischauer1, Klaas Paul Pruessmann1
1
Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland

Concurrent higher-order field monitoring is introduced to diffusion weighted imaging, which was enabled by using 19F NMR for a 3rd order dynamic field camera. Concurrent field monitoring captures the full field dynamics during each diffusion weighted acquisition simultaneously with the imaging coils’ data. Integrating this field information into image reconstruction eliminates the effects of thermal drifts along with those induced by eddy currents and other gradient imperfections. To benefit from a shortened TE and reduced susceptibility artifacts, higher-order reconstruction was extended to encompass parallel imaging by incorporating coil sensitivities in the encoding matrix.

     
11:30 191

Novel Strategy for Accelerated Diffusion Imaging
Stephan E. Maier1, Bruno Madore2
1
Radiology Department, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States; 2Radiology Department, Brigham and Women's Hospital, Harvard Medical School , Boston, MA, United States

A method is presented here to exploit inherent redundancies in multi-b multi-direction datasets, for accelerated diffusion imaging. The approach is clearly not meant as an alternative to established acceleration methods such as parallel imaging and partial-Fourier imaging, but rather as a complement to these methods for additional imaging speed. We show how Fourier analysis along the b-factor and encoding direction parameter axes provides new insights into more efficient sampling of diffusion data with virtually no loss of information.

     
11:42 192

Comparison Between Readout-Segmented (RS)-EPI and an Improved Distortion Correction Method for Short-Axis Propeller (SAP)-EPI
Stefan Skare1, Samantha J. Holdsworth1, Kristen Yeom1, Patrick David Barnes1, Roland Bammer1

1Radiology, Stanford University, Palo Alto, CA, United States

Short-Axis readout Propeller EPI (SAP-EPI) and Readout-Segmented EPI (RS-EPI) have been proposed for use in high resolution diffusion-weighted (DW) imaging. SAP-EPI and RS-EPI share common characteristics, in that k-space is traversed by several EPI ‘segments’ in order to reduce the distortion and blurring that typically hampers EPI images. Previous work comparing RS-EPI and SAP-EPI concluded that SAP-EPI suffers from more blurring compared with RS-EPI despite attempts to correct for distortion. With an improved distortion correction method, we demonstrate that SAP-EPI results in similar image resolution to RS-EPI for a given SNR normalized for scan time/slice.

     
11:54 193

First Experimental Observation of Both Microscopic Anisotropy (UA) and Compartment Shape Anisotropy (CSA) in Randomly Oriented Biological Cells Using Double-PFG NMR
Noam Shemesh1, Evren Özarslan2, Peter J. Basser2, Yoram Cohen1
1
School of Chemistry, Tel Aviv University, Tel Aviv, Israel; 2Section on Tissue Biophysics and Biomimetics, NICHD, National Institutes of Health, Bethesda, MD, United States

Randomly oriented compartments pose an inherent limitation for single-pulsed-field-gradient (s-PFG) methodologies such as DTI and q-space, and microstructural information (such as compartment shape and size) is lost. In this study, we demonstrate that the double-PFG (d-PFG) methodology can overcome the inherent limitations of s-PFG and extract accurate compartmental dimensions in fixed yeast. The size extracted from the fit is in excellent agreement with the size obtained from light microscopy. Moreover, we show that using different mixing times, the d-PFG experiment differentiates between spherical yeast and eccentric cyanobacteria. Our findings may be important in characterizing grey matter and other CNS tissues.

     
12:06 194.

In Vivo Pore Size Estimation in White Matter with Double Wave Vector Diffusion Weighting
Martin A. Koch1, Jürgen Finsterbusch1
1
Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany

Diffusion weighting with two gradient pulse pairs of independent direction (double wave vector diffusion weighting) can provide tissue structure information which is not easily accessible otherwise, such as cell size or shape. For free diffusion, it is irrelevant whether the diffusion gradients in the two weightings are parallel or antiparallel with respect to each other. In restricted diffusion, differences between these situations occur at short mixing times. Here, a DWV sequence with short mixing time is used to estimate the pore size in the human corticospinal tracts in vivo, and analytical expressions for cylindrical pores are used for data analysis.

     
12:18 195

Optimal Diffusion-Gradient Waveforms for Measuring Axon Diameter
Ivana Drobnjak1, Bernard Siow2, Daniel C. Alexander1
1
Center for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom; 2Center for Advanced Biomedical Imaging, University College London, London, United Kingdom

Measuring microstructure parameters of brain tissue in vivo is a challenge in diffusion MRI. Non-standard diffusion-gradient pulses may provide more sensitivity to microstructure features. Here, we optimize the shape of the diffusion-gradient waveform, constrained only by hardware limits and fixed orientation, to give the best estimate of axon radius based on a simple model of the diffusion within white matter. Our results suggest that square-wave oscillating gradients maximize sensitivity to pore size over the set of PGSE sequences. They also show that the frequency of the waves increases as the radius size decreases.

     

 

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