Transcript 1518_Corum_0457

#457
Sweep Imaging with Fourier Transform
(SWIFT) in Breast Cancer
Curtis A. Corum, Andrew Babcock, Djaudat Idiyatullin,
Angela L. Styczynski-Snyder, Diane Hutter,
Lenore Everson, Michael Nelson, and Michael Garwood
University of Minnesota, Minneapolis, MN, United States
Declaration of Relevant
Financial Interests or Relationships
Speaker Name: Curtis A. Corum
I have the following relevant financial interest or relationship to disclose with regard to the subject
matter of this presentation:
Dr. Corum is entitled to sales royalties under an agreement between the University of Minnesota
and GE Healthcare, which is developing products related to the research described in this paper.
The University of Minnesota also has a royalty interest in GE Healthcare. These relationships
have been reviewed and managed by the University of Minnesota in accordance with its Conflict
of Interest policies.
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Breast MRI
While many MRI sequence types are sometimes indicated in Breast MRI
the two main image sets usually desired are:
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High spatial resolution pre and post-contrast T1 weighted images (and
subtractions) for morphological assessment (circumscribed vs
spiculated, homogeneous vs heterogeneus enhancing, etc.)
High temporal resolution dynamic contrast enhanced (DCE) T1
weighted image series with at least 1 min temporal resolution for
contrast kinetics (uptake vs washout)
Emerging standard of care utilizes semi and fully-quantitative
pharmacokinetic modelling, with active research in improving models
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SWIFT
SWeep Imgaing with Fourier Transform
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Simultaneous interleaved excitation
and acquisition
3D Radial Sampling (Halton
sequence)
PD or T1 weighted
Smooth Gradient Update (Quiet)
robust against motion, eddy currents,
and system timing
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SWIFT
SWeep Imgaing with Fourier Transform




Simultaneous interleaved excitation
and acquisition
3D Radial Sampling (Halton
sequence)
PD or T1 weighted
Smooth Gradient Update (Quiet)
robust against motion, eddy currents,
and system timing
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May 9
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SWIFT Timing
SWIFT has extremely short dead time
On the order of 2-6 μs
Sensitive to fast relaxing spins
Preserves signal from off resonant spins
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4 T SWIFT Breast Coils
Modified Single Breast Coils
2 ch Transmit/Receive, 4 T
SWIFT compatible Dual Breast Coil
4 ch Transmit/Receive, 4 T
CMRR Carl Snyder
Helmut Merkle (now at NIH)
UMN Physics Machine Shop, Peter Ness
CMRR Gregor Adriany, Carl Snyder
Currently in use
Now in imaging testing
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Halton View Order
Pseudo Random 3d radial view-ordering
Sorted for smooth gradient transition
Full sphere coverage every 512 views
Designed for View Sharing and CS reconstruction
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Goals
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Implement SWIFT based protocol for Breast MRI
SWIFT compatible (no short T2 background from polymers, fast
switching and/or ring-down times) transcieve coil(s)
Demonstrate high temporal resolution SWIFT DCE imaging
Demonstrate high spatial resolution morphological pre and post
contrast imaging from same scan data
Scan an initial cohort of patient volunteers
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SWIFT Protocol
2 min
shimming, pre-scan, scout
20 sec
SWIFT pre-scans, phase reference and gain
1-2 min
SWIFT FOV check, FS
(2-4 min)
(optional) Double Angle Method GRE B1 map
(2-4 min)
(optional) SWIFT Variable Flip Angle T1 map
2-6 min
SWIFT DCE FS, pre-contrast (MagnavistTM 0.1 mM/kg at 2 cc/s)
6 min
SWIFT DCE FS post-contrast,
(optional)
further SWIFT test scans
11.33 min
Minimum total time
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4 T SWIFT Parameters
TR 4.4 ms, 62 kHz, 4.1 ms HS1, Flip 8-16 deg, 256 points
Fat Suppression (FS)1/8 views, 4 ms Gauss, Flip 120 deg, offset -625 Hz
3d Radial Isotropic Vieworder
Sorted Halton** sequence, 512 views per k-space sphere
128 full spheres per 4.5 min acquisition (6 min with FS)
65,536 views total before restarting
Gridding based reconstruction
Sliding window reconstruction for DCE, 6 sec frames
* 10 ms HS4 R20 pulse for dual fat and silicone suppression
** Wong TT, Sampling with Hammersley and Halton Points,
J Graph Tools archive, Volume 2 , Issue 2, 1997., Chan RW et al., MRM 2010.
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Case FA
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Case mass like DCIS
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Case IDC
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Ongoing Study...
We have now recruited 12 patients and have 8 successful sessions
3 of the incompletes were due to last minute exclusions
one due to scanner failure
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Conclusions
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SWIFT can produce high temporal resolution DCE and high resolution
morphological data from the same scan data
Work in
progress....
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Model based evaluation of DCE data
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Compressed Sensing reconstruction
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Case reviews and search for novel contrast (short T2)
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Continue recruiting patients....
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Acknowlegdements
We gratefully acknowledge NIH R21 CA139688,
P41 RR008079, S10 RR023730, S10 RR027290,
and the Minnesota Medical Foundation 3932-9227-09
for grant support.
Thanks to physicians and residents at the Fairview University Breast
Center and Jinjin Zhang for assistance with patient studies
Thanks to S. Suddarth and A. Rath of Agilent, B. Hannah,
J. Strupp, and P. Anderson of CMRR for software and hardware
support.
Thanks especially to Djaudat Idiyatullin, Mike Garwood, Mike Tesch,
and Ryan Chamberlain (The rest of the SWIFT team) and colleagues
at the UMN CMRR!
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NMR and Convolution
h(t)
spin
impulse
response
*
x(t)
RF pulse
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r(t)
=
system
response
NMR and Convolution
The fundamental basis of SWIFT signal processing
is that a frequency modulated pulse alters the system
response away from the familiar hard pulse impulse
response.
In the small flip angle limit the relationship is convolution.
Practically it works well up to 90°.
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SWIFT and Correlation
r(t)
system
response
x(t)
RF pulse
h(t)
=
spin
impulse
response
Recovering a standard FID by correlation
SWIFT produces an FID if the raw data (system reposnse)
is correlatied with the complex RF pulse shape as a post
processing step.
In practice this is performed in the frequency domain by
multiplication with the complex conjugate of the complex
pulse profile.
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