beth israel school medical compressed sensing in cardiac mr · • advantages 1: • higher snr •...
TRANSCRIPT
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Mehmet Akçakaya, Ph.D.
Department of Medicine (Cardiovascular Division)
Beth Israel Deaconess Medical Center
Harvard Medical School
Boston, MA
Beth Israel Deaconess
Medical Center
Harvard Medical School
Compressed Sensing
in Cardiac MR
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long acquisition time impact :
• spatial and temporal resolution
• spatial coverage
• SNR, CNR
• artifact level (motion, contrast media change)
long CMR exams:
• cardiac MR exams are generally long
• comprehensive exams are becoming more common
• emphasis on patient throughput to reduce cost
Motivation
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- Brief overview of acceleration methods
- A new CS reconstruction algorithm for high-resolution CMR
- CS-accelerated image acquisition for
• coronary
• late gadolinium enhancement
• cine
• perfusion
• other CMR applications
Outline
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• Partial Fourier
• Parallel Imaging
• Non-Cartesian Trajectories
• Compressed Sensing
• Spatio-temporal methods
(for dynamic imaging)
Methods for Acceleration
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Multiple Receiver Coils
• In clinical MRI, receiver coil arrays are used.
• They modulate the intensity of the signal based on their spatial locations.
Ck : Coil sensitivity profiles
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• Utilizes redundancy in acquisition due to phased-array coils.
• SENSE
• Image-domain least squares solution
• Uses estimates of coil sensitivity maps
• GRAPPA
• k-space interpolation
• Interpolation kernels estimated from center of k-space
Parallel Imaging
• SENSE and GRAPPA are linearreconstruction methods.
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Compressed Sensing (CS)
Recently proposed MRI acceleration technique1
Images are compressible in transform domains
Image Domain Transform Domain
1 Block et al, MRM, 2007; Lustig et al, MRM, 2007.
Wavelet
Finite Differences
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FΩ : incoherent k-space undersampling operator
S : measured k-space data (undersampled)
• CS reconstruction solves
Φ : sparsity regularizer (e. g. lp norm, p ≤ 1)
Ψ : transform domain (e. g. wavelet, finite differences)
τ : weight of sparsity term
CS Reconstruction
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• Potential for higher acceleration rates
• Limited use in high spatial-resolution cardiac MR applications
• Blurring and residual artifacts
CS in Cardiac MR
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• To use patient-specific and anatomic-specific information for improved reconstruction
• We propose: Low-dimensional-structure self-learning and thresholding (LOST)
Aim
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LOST
• Coronary images contain
2D patches of similar signal content at various spatial locations
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LOST
• Coronary images contain
2D patches of similar signal content at various spatial locations
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LOST
Apply 2D FFT to each block:
Promotes sparsity withineach block
FFT along 3rd dimension
enhances sparsity greatly since all blocks are similar
3D FFT
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Block Matching
• Construct similarity clusters by block matching1
reference
block
check similarity
with
other blocks
matched similar
blocks
(similarity cluster for the reference
block / voxel)
• Clusters are produced for every voxel of the image.1 Dabov et al, IEEE TIP, 2007.
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• Remove aliasing by using the FFT-sparsity of similarity clusters
1) Hard thresholding in FFT domain
• Captures l0 norm of similarity clusters
• If FFT coefficient < τht, set to zero. Otherwise unchanged
• Efficiently removes aliasing
• Blurring artifacts
Thresholding
τht
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2) Wiener Filtering in FFT domain
• Captures weighted l2 norm of similarity clusters
• Weight each FFT coefficient, fk by
|fk|2 / (|fk|
2 + τ2wie)
• Reduces blurring artifacts
• Useful in later iterations when the weights are reliable
Thresholding
τwie
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• Each block may be in multiple clusters
• Combine these by weighted averaging
• Intuition: Smaller weight to more aliased blocks
Combining Blocks
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LOST
Similarity Clusters
3D FFT
Hard Thresholding
/
Wiener Filtering
3D IFFT De-alised Blocks
Weighted
Average
Weights
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Stage 1: Generate low-resolution
estimate from center of k-space
1) Adaptively identify similarity
clusters (Nb = 8)
2) Threshold via hard-thresholding
Implementation
Stage 2: From estimate of stage 1
1) Adaptively identify similarity
clusters (Nb = 4)
2) Alternate between hard-
thresholding and Wiener filtering
low-resolutionzero-filled(IFFT of
measurements)
LOST stage 1
LOST stage 2
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• Performance evaluation of LOST
• Targeted coronary MRI
• Retrospective undersampling
• Prospective undersampling
• Clinical application of LOST
• Contrast-enhanced coronary MRI
• Late Gadolinium enhancement
Methods
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• 1.5T Philips Achieva magnet with 5-channel cardiac coil.
• Right and left coronaries (NH = 10)
Retrospective Undersampling
Fully Sampled k-space
Under-sample(rates 2, 3, 4)
LOSTReconstruction
l1 Minimization1
(Wavelet)Total Variation (TV)
Regularization2
• Retrospective undersampling:
• 50x5 lines in the center• randomly discarding the edges1 van den Berg et al, SIAM JSC, 2008; 2 Yang et al, IEEE JSTSP, 2010.
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• NAV-gated
• ECG-triggered
• T2-Prep SSFP
• 1×1×3 mm3 resolution
• Retrospective random
under-sampling
• 5-channel cardiac coil
LAD/LCX ResultsReference Rate 2 Rate 3 Rate 4
RCA: Right Coronary Artery, LAD: Left Anterior Descending Artery, LCX: Left Circumflex Artery
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• Our evaluation shows improved
• subjective image scores
• sharpness of the RCA
• mean square error
with respect to l1 minimization and TV regularization
• Next step: implement and evaluate LOST in prospective acquisition
Performance Evaluation
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• Random k-space undersampling in SSFP sequences à artifacts
• Radial profile-order to mitigate artifacts1
Prospective Undersampling
1Basha et al, ISMRM, 2011
kz
ky
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Prospective Undersampling
Fully Sampled k-space
Randomly undersampledData (rates 2, 3, 4)
LOSTReconstruction
l1 Minimization (Wavelet)
Uniformly undersampledData (rates 2, 3, 4)
SENSE
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• NAV-gated
• ECG-triggered
• T2-Prep SSFP
• 1×1×3 mm3 resolution
• Prospective random
under-sampling with
radial profile order
• 5-channel cardiac coil
LOST allows images to be acquired with 4×acceleration even with 5-channel coil
RCA ResultsReference Rate 2 Rate 3 Rate 4
RCA: Right Coronary Artery, AO: Aortic Root, LV: Left Ventricle, RV: Right Ventricle
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LAD/LCX Results
Reference Rate 2 Rate 3 Rate 4
RCA: Right Coronary Artery, LAD: Left Anterior Descending Artery, LCX: Left Circumflex Artery
• NAV-gated
• ECG-triggered
• T2-Prep SSFP
• 1×1×3 mm3 resolution
• Prospective random
under-sampling with
radial profile order
• 5-channel cardiac coil
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Contrast Enhanced (CE) Coronary MRI
1 Bi et al, MRM, 2007; Hu et al, MRM, 2010.
• 10 healthy subjects
• 4-fold acceleration
• Advantages1:
• higher SNR
• higher CNR
• Disadvantages:
• long acquisition time (~10-12 minutes)
• artifacts due to varying inversion time /
contrast washout
Rapid acquisition is needed
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• IR-SSFP
• NAV-gated, ECG-Triggered
• bolus 0.2 mmol/kg Gd-BOPTA
• imaging after 2 min of contrast
• resolution =1.3×1.3×1.3 mm3
• 4-fold ky-kz acceleration
• 5-channel phased-array coil
• 2:50 minutes at 70 bpm, 100% gating efficiency
zero
-fill
ed
CE WH Coronary MRI Results
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• IR-SSFP
• bolus 0.2 mmol/kg Gd-BOPTA
• resolution =1.3×1.3×1.3 mm3
• 4-fold ky-kz acceleration
• 5-channel phased-array coil
CE WH Coronary MRI Results
zero
-fill
ed
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LAD
LCX
RCA: Right Coronary Artery, LAD: Left Anterior Descending Artery, LCX: Left Circumflex Artery
LOSTzero-filled
RCA
CE WH Coronary MRI Results
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• Subjective quality assessment by two blinded readers
in consensus
• 1 = poor, 4 = excellent 1
• Overall score: 3.6 ± 0.5
CE WH Coronary MRI Results
1 Kim et al, NEJM, 2001
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• Late Gadolinium Enhancement (LGE) is used for
viability studies
• Quantification of scar volume and border zone
morphology1
Late Gadolinium Enhancement
2D with BH2×2 mm2,10 mm gap• Higher resolution allows2
• Identification of small areas of scar
• Improved gray zone
characterization
Higher resolution and shorter
acquisition are desirable1 Kim et al, Circulation, 1999; Kim et al, NEJM, 20002 Yan et al, Circulation, 2006; Peters et al, JMRI, 2007
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• 46 year old male
• hypertrophic cardiomyopathy
• LGE in myocardium
• IR-GRE
• axial acquisition with WH coverage
• resolution =1.0×1.0×1.5 mm3
• 3-fold ky-kz acceleration
• 5-channel phased-array coil
• 7 minutes total acquisition time
3D WH LGE ResultsLow Resolution
1.5×1.5×4.0 mm3
LOST
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3D WH LGE ResultsLow Resolution
1.5×1.5×4.0 mm3
LOST, Rate = 31.0×1.0×1.5 mm3
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• 51 year old female
• pericarditis
• LGE in pericardium
• IR-GRE
• resolution =1.3×1.7×1.7 mm3
• 5-channel phased-array coil
Motion Correction in LGE1
Low-Resolution1.7×1.7×5.0 mm3
with LOST
1 Moghari et al, MRM, in press Images courtesy of S. Hong and M. H. Moghari
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• Image the cardiac morphology throughout different
phases of the cardiac cycle.
• Used for functional assessment.
• Quantification of ejection fraction, end-diastolic volume, end-systolic volume, stroke volume, etc
Cine CMR
• Accelerated imaging allows
• Higher spatial or temporal
resolution
• Less breath-holds
2D with BH2×2 mm2, 30 ms temp. res.
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Retrospective Cine
Fully-SampledZerofilled (retrospective undersampling, R = 6)
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Transform Domain LOST
l1 minimization in x-f space , R = 6reconstruction in x-f space, with transform-domain LOST , R = 6
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reconstruction in x-f space, with transform-domain LOST , R = 6Fully-Sampled
Transform Domain LOST
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kt-SPIRiT for Retrospective Cine
fully-sampled kt-GRAPPA (R=7) kt-SPIRiT (R=7)
Courtesy of Drs. P. Lai (GE), M. Lustig (UC Berkeley)
Lai, ISMRM 2010
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kt-SPIRiT for Prospective Gating
fully-sampled kt-GRAPPA (R=6) kt-SPIRiT(R=6)
Courtesy of Drs. P. Lai (GE), M. Lustig (UC Berkeley)
Lai, ISMRM 2010
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kt group sparse
R =
3
R =
5
R =
7
Training data: 12.5%
kt-Group Sparse for Cine
x-f space signal support
Courtesy of U. Muhammad, T. Schaeffter, KCL
fully
-sam
ple
d
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• Images wash-in of contrast media with the blood
during the initial pass through myocardium
• Used for assessment of perfusion defects
• Diagnosis of coronary artery disease
Perfusion CMR
• Accelerated imaging allows
• Higher spatial or temporal
resolution
• Better coverage
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Multislice-2D CMR Perfusion
• Multislice TurboFLASH sequence with 8-fold ky-t acceleration
• Spatial resolution = 1.6×1.6×8 mm3
• Temporal resolution = 60 ms
• 3T Siemens Tim Trio, 12-element coil
z
ky
t
z
Courtesy of R. Otazo, D. Sodickson, NYU
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3D First-Pass CMR Perfusion
•TurboFLASH sequence
•FOV = 340×340×100 mm3
•40 dynamics
•temporal resolution = 220.8 ms
•spatial resolution = 2.7×2.7×8 mm3
•16-fold ky-kz-t acceleration
•3 Tesla Siemens Verio
•32-channel body array
Courtesy of Drs. R. Otazo, D. Sodickson, NYU
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Other CMR Applications
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Non-Contrast PV-MRAFully Sampled R = 2
R = 4 R = 6
Akcakaya, JMRI, 2011
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Top: 12.5 fold accelerated blood-pool contrast-enhanced extremity MR angiogram in a 4 year old with a parallel
imaging alone (ARC) using a dedicated 32 channel pediatric coil. 750 x 750 x 800 µm resolution. Bottom: L1-
SPIRiT reconstruction recovers substantial detail, with quality rivaling a catheter angiogram. The fast scan
avoids venous contamination.
Courtesy of Drs. M. Lustig and S. Vasanawalla, Stanford
MR Angiography with L1-SPIRiT
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• True-FISP
• 8-fold acceleration
• Temporal resolution = 42.5 ms
• Spatial resolution = 2.3 mm
Real-Time Cine MRI
Feng et al. ISMRM 2010; 3602
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51
Results: Retrospective undersampling
Accelerating MRI using Compressed Sensing
Fully sampled
CSauto-calibrated
SparseSENSE
CS in Black Blood CMR
Courtesy of Drs. C. Prieto, T. Schaeffter, R. Botnar KCL
Prieto, ISMRM 2010
R = 5 R = 5
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• Introduced the LOST algorithm, which uses patient-specific and anatomy-specific information for improved reconstruction
• Provided an overview of applications of CS in CMR
Conclusions
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• More clinical validation needed
• Not available by vendors
• Faster and robust reconstruction needed
The Future
§ Potential to significantly accelerate and/or improve CMR image acquisition
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BIDMC Cardiac MR Center
•Reza Nezafat, Ph. D.
•Warren J. Manning, M.D.
•Michael L. Chuang, M.D.
•Neil M. Rofsky, M.D.
•Vahid Tarokh, Ph.D.
•Tamer A. Basha, Ph.D.
•Peng Hu, Ph.D.
•Mehdi H. Moghari, Ph.D.
•Seunghoon Nam, M. S.
Acknowledgements
Slide Contribution:
•Michael Lustig, Ph.D.
•Rene Botnar, Ph.D.
•Daniel Sodickson, Ph.D.
•Ricardo Otazo, Ph.D.
•Tobias Schaeffter, Ph.D.
•Muhammad Usman