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
1Radiology, 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
1Radiology, 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
1Department 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
1Institute 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
1Radiology 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
1School 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
1Systems 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
1Center 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. |
|
|
|
|