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Steady-state free precession and other 3D methods for high-resolution FMRI
Steady-state free precession and other 3D methods for high-resolution FMRI
Karla L. Miller FMRIB Centre, Oxford University
Karla L. Miller FMRIB Centre, Oxford University
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Why is high-resolution FMRI so difficult?
• Signal-to-noise ratio:
– For example, 2x2x2 mm has 8x SNR of 1x1x1 mm (would require 64 times longer scan)
• For single-shot, distortion increases with matrix size
• Isotropic resolution (thin slices) is hard in 2D
€
SNR∝ΔxΔyΔz Tacq
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2D High-resolution FMRI
Segmented EPI[McKinnon MRM 1993]
7T, 2D segmented EPI0.5 x 0.5 x 3 mm3
[Yacoub et al MRM 2003]
Acquire EPI in multiple shots (“segmented” or “interleaved”)
Allows increased resolution without increased distortion
High-resolution in-plane, but limit on slice thickness!
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2D Multi-slice MRI
excited slice
Each slice excited & acquired separately
TR: time between repeated excitation of same slice (typically 1–3 seconds)
Slices no thinner than ~1 mm
t1
t2
t3
t4
t5
t6
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“True” 3D imaging
Excite entire slab, readout in 3D k-space
TR: time between repeated slab excitations (5-50 ms)
Can achieve thin slices (isotropic resolution, like structurals)!
excited volume
excited volume
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SNR Benefit of 3D Trajectories
SNR is higher for 3D since same magnetization is sampled more frequently
Calculated for 3D stack-of-spirals
[Yanle Hu and Gary Glover, Stanford]
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3D Functional MRI
• Advantages:– SNR benefits, provided short TR can be used– Can achieve thinner slices (e.g., for “isotropic” voxels)– 3D multi-shot low distortion
• Disadvantages:– Can require long volume scan times (may be fixable!)– Acquisition time (e.g., “slice timing”) is difficult to define– Slices must be contiguous (no inter-slice gap)
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3D stack-of-EPI
[Irarrazabal et al, MRM 1995]
Adapting echo planar imaging (EPI) to 3D
2D segmented EPI
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3D EPI GRE at 3T
0.8 x 0.8 x 0.8 mm3 = 0.5 mm3
TR=69 ms, 7 s/vol, 24 minutes scan time
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3D EPI GRE at 3T (0.8 x 0.8 x 0.8 mm3 )
Single image7 s scan time
Mean timecourse image4 min scan time
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Adapting spiral to 3D
3D stack-of-spiral
2D interleaved spiral
[Yang et al, MRM 1996]
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Comparison of 2D vs 3D spiral FMRI
[Hu and Glover, MRM 2006]
• 20% higher functional SNR in 3D compared to 2D
• Significantly more activated voxels (2x at chosen threshold)
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3D spiral GRE with partial k-space
full k-space
partial k-space
• Faster imaging: 64 slices in 6.4 s (full) vs. 4.0 s (partial)
[Hu and Glover, MRM 2006]
• Higher statistical power due to reduced physiological noise
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High-resolution retinotopy at 7T
QuickTime™ and aTIFF (Uncompressed) decompressor
are needed to see this picture.
2D single-shot EPI 3D segmented EPI
• 1x1x1 mm3 resolution• Identification of retinotopically-distinct regions• Reduced distortion in 3D segmented EPI
Itamar Kahn and Randy Buckner, MGH
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3D GRE BOLD at 7T
0.67 x 0.67 x 0.67 mm3 = 0.3 mm3
12 minutes scan time
Karla Miller and Chris Wiggins, MGH
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3D GRE BOLD at 7T
0.58 x 0.58 x 0.58 mm3 = 0.2 mm3
18 minutes scan time
Karla Miller and Chris Wiggins, MGH
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3D Imaging: GRE vs. SSFP
• 3D imaging generally requires short TR• SSFP tends to out-perform GRE in this regime
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Balanced Steady-state Free Precession (SSFP)
• SSFP signal dependence on off-resonance
Field mapSSFP image
• Transition band SSFP: image in signal transitions– Contrast: deoxyHb frequency shift
Scheffler 2001
Miller 2003
Bowen 2005
• Passband SSFP: image in flat part of signal profile– Contrast: T2 at short TR
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Transition-band SSFP
Functional contrast occurs in “bands”• Changing center frequency shifts region of
high signal (and functional contrast)
Multi-frequency experiments• Repeat stimulus at multiple center
frequencies to extend coverage• Combine data into single activation map
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3D Spiral transition-band SSFP at 1.5T
1 x 1 x 2 mm3, 3D spiral, standard head coil
QuickTime™ and a decompressor
are needed to see this picture.
Courtesy Jongho Lee, Stanford University
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3D EPI tbSSFP at 3T
0.8 x 0.8 x 0.8 mm3 = 0.5 mm3
TR=35 ms, 8.3 s/vol, 24 minutes scan time
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3D EPI tbSSFP FMRI at 7T
0.75 x 0.75 x 0.75 mm3 = 0.4 mm3
22 minutes scan time
Collaboration with Chris Wiggins, MGH
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Physiological noise: transition-band SSFP
Compared to GRE, higher physiological noise in tbSSFP
Poor fit with standard physiological noise model
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Real-timecomputerFID
Δ
ImageData
0+Δ
Respiration modulates frequency = shift in SSFP bands
Real-time feedback to compensate for frequency drift
[Jongho Lee et al, MRM 2006]
Reducing physiological noise in SSFP
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Dynamic frequency tracking
compensation off compensation on
[Jongho Lee et al, MRM 2006]
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Passband SSFP vs. GRE (3T)
TE=
3 m
sT
E=
25
ms
GRE pbSSFP
xo
GRESSFP
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Physiological noise: passband SSFP
Compared to GRE, lower physiological noise in pbSSFP
Short TR (6-12 ms)
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Conclusions
• Why 3D for high-resolution FMRI?
– High-res multi-shot short TR 3D
– Lower distortion with short, 3D readouts
– Can achieve isotropic resolution (thin slices)
• Challenges and advances
– Efficient 3D versions of both EPI and spiral trajectories
– Volume acquisition times: Speed up with partial k-space (or parallel imaging)
• SSFP FMRI
– New method for FMRI contrast
– Highly suitable to 3D due to short TR
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Acknowledgements
Martinos Centre, MGHChristopher WigginsGraham WigginsItamar Kahn
FMRIB, OxfordStephen SmithPeter Jezzard
StanfordJohn PaulyJongho LeeYanle HuGary Glover
Funding: NIH, GlaxoSmithKline, EPSRC, Royal Academy of Engineering
Related work: #357 SSFP analysis (Th-AM), #272 SSFP modeling (Th-PM)