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Accelerated DESPOT1 with Parallel Imaging. April 9, 2012 Jason Su. Questions. Can we reproduce our earlier DISCO results? How does ARC affect the T1 maps? Do DISCO and ARC work well together for this DESPOT1 application?. Acquisition.
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Accelerated DESPOT1 with Parallel Imaging April 9, 2012 Jason Su
Questions • Can we reproduce our earlier DISCO results? • How does ARC affect the T1 maps? • Do DISCO and ARC work well together for this DESPOT1 application?
Acquisition • 3T, in vivo volunteer, 2mm isotropic resolution (110x110x80) • 8ch head coil, shim ON • B-S B1 mapping was acquired by not used in the analysis • SPGR, fully sampled • TR was set to min, unfortunately not controlled • 9 exponentially spaced angles up to fa10, TR = 3.649ms • 7 linearly spaced angles up to fa11, TR = 3.708ms (1.6% higher) • SSFP was also collected in a similar scheme for future mcDESPOT pursuits
Acquisition – Angles • Two data sets were collected for each scan type due to the pfile numbering issue • I was wrong earlier about it overwriting the last file with new data • No new pfiles are written after the 512 limit is reached • This gives us 7 images per set (1+floor(512/80)) • Manual pre-scan is performed between sets to ensure images are comparable • Combining the two sets gives a good sampling of the curve
Processing • kacq files were also read off the scanner to simulate the exact ARC pattern used in product • These are generated when the series is saved, so they are easy to make • Matlab to impose ARC and DISCO sampling schemes on the data • ARC images must not be F-transformed in slice direction for offline.recon? Was getting really bad results otherwise. • catania:~alley/offline.recon.64bit.arconly for reconstruction (-arc switch when applicable)
Product ARC Sampling Patterns • ARC2x1, ARC2x1.5 • ARC2x1, ARC2x1.5 with “slice resolution = 70”
Processing – Matlab • We use a different way to get a slice resolution of 70% in the Matlab code for DISCO sampling, so I instead impose that on the fully sampled ARC patterns • The center used for computing the scale factor correction between flip angle frames is taken as the A-region • Accelerations performed: • SR70 (the reference) • DISCO (AB1, B2, B3) • ARC2x1 • ARC2x1.5 • DISCO+ARC2x1 • DISCO+ARC2x1.5
Implemented Sampling Patterns • SR70 • This is the reference sampling pattern that I use to compare all accelerations to • Avoided using fully sampled version so that slice resolution wouldn’t be an issue, this is in contrast to earlier results in the ISMRM abstract • ARC2x1, ARC2x1.5 with DISCO slice resolution • There’s a few more sample sample points than in product GE • Broken line at the bottom, not sure if ARC recon would struggle with that
Post-Processing • Linear registration of the volumes is performed on each acceleration type separately • This means that the quality of registration is (very slightly) dependent on the acceleration • I preferred this over applying the same transforms across all acceleration types because it’s a more realistic scenario • DESPOT1 is performed via linearization of the SPGR signal equation • TR is taken as the mean between the two sets: TR = 3.6785ms • Hopefully the resulting error due to this discrepancy is within the noise of the images • Deviation would be a factor exp(-0.0295/T1), for T1 = 1100ms in WM at 3T -> 0.999973182177786
Conclusions • DISCO is working very well • Artifacts are incoherent and noise-like • Clearly something is going wrong with ARC • Very weird that it’s like enhancing the contrast of the T1 map, pushing WM and GM/CSF in different directions • ARC artifacts are visible in the maps • Useless to look at DISCO+ARC vs. SR70 when ARC is so bad • We can compare DISCO+ARC vs. ARC • Already saw a slight deviation near the Ernst angle (fa6-7) in the curves
Conclusions • We can sort of see the effect of adding on more parallel imaging and DISCO • DISCO adds error with an IQR of 2.55 • Addition 1.27x parallel imaging adds 2.82 • Probably less accurate to use IQR here since there are coherent artifacts • Together the error has an IQR of 4.00, a bit better than additive • Could try to actually add the difference images of DISCO+ARC2x1 and ARC2x15 to see if it looks like DISCO+ARC2x15 difference • I have confidence that DISCO+ARC is completely viable with errors within 5-10% once ARC is done right
Remaining Questions • What did I do wrong with ARC? • FFT the slice dimension, apply the sampling pattern to each coil, then write to new pfile, do not iFFT before writing since normally ARC pfiles are in pure k-space • offline.recon with –arc option • What should I keep in the eposter? • DISCO vs. SR70 • DISCO+ARC vs. ARC
ISMRM 2012 E-Poster #5787 Accelerated Variable Flip Angle T1 Mapping via View Sharing of Pseudo-Random Sampled Higher Order K-Space J.Su1, M.Saranathan1, and B.K.Rutt1 1Department of Radiology, Stanford University, Stanford, CA, United States Declaration of Conflict of Interest or Relationship I have no conflicts of interest to disclose with regard to the subject matter of this presentation.
Accelerated Variable Flip Angle T1 Mapping via View Sharing of Pseudo-Random Sampled Higher Order K-Space ISMRM 2012 #5787 Background • Variable flip angle T1 mapping (VFA) is a quantitative image method in which a series of scans at different flip angles are collected to extract whole brain relaxation times • The collection of many angles for accuracy across the wide range of T1 values in tissue is time consuming1 1Deoni et al. Magn Reson Med. 2003 Mar;49(3):515-26.
Accelerated Variable Flip Angle T1 Mapping via View Sharing of Pseudo-Random Sampled Higher Order K-Space ISMRM 2012 #5787 Purpose • Accelerate VFA by using a view sharing scheme, variations of which have seen applications in MR angiography2 and DCE-MRI3 • Assess the accuracy and precision of the accelerated T1 maps compared to the fully sampled source 2Korosec et al. Magn Reson Med. 1996;36(3):345-351. 3Saranathan et al. Proc ISMRM p2941 (2011).
