Merlin J Fair1,2, Congyu Liao1,2, Daeun Kim3, Divya Varadarajan1,2, Justin P Haldar3,4, and Kawin Setsompop1,2,5
1A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States, 2Department of Radiology, Harvard Medical School, Boston, MA, United States, 3Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, United States, 4Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, United States, 5Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, United States
Synopsis
Diffusion-PEPTIDE incorporates the recently developed rapid multi-shot relaxometry technique Propeller EPTI with Dynamic Encoding (PEPTIDE) into a diffusion acquisition scheme. PEPTIDE enables fast acquisition of distortion- and blurring-free images, time-resolved for different timepoints with varying T2 & T2* weighting, with self-navigation for correction of shot-to-shot phase-variation and motion. Diffusion-PEPTIDE is demonstrated here to enable distortion-free in vivo diffusion-relaxometry with large parameter space in an sensible acquisition time.
Introduction
Combining diffusion with relaxometry techniques is a topic of
increasing interest1,2, with the hope that it will enable
investigation of sub-voxel microstructure3. However, repetition of the
diffusion experiment for every change in relaxation-encoding variable (TE,TI,
etc) creates impractically long acquisition durations and is a major current
limitation in the field. Recent works have attempted to address this with
efficient modifications to the sequence acquisition4,5,
however it is still difficult to achieve a large range in both b-values and relaxation-encodings in a reasonable timeframe, particularly if combined with higher directional
diffusion-encoding.
A recent multi-shot EPI approach termed EPTI6 is a rapid
relaxometry technique that acquires data free from the typical distortion and
blurring of standard-EPI acquisitions. This has been used to acquire accurate whole-brain
T2,T2*,PD and susceptibility maps from a single scan <1min. The
multi-shot ky-t sampling pattern of EPTI (Figure 1) allows a B0-phase-informed GRAPPA kernel7 to reconstruct data across complete ky-t
space, therefore providing a time-series of data with each image free from
T2*-decay and B0-inhomogeniety-induced phase evolution effects. PEPTIDE8 is a PROPELLER9 extension to this methodology, which enables
self-navigation and correction of shot-to-shot phase variation10, and has been shown to rapidly acquire quantitative information
with robustness to motion of up to 30° rotation8.
This work proposes to extend the use of PEPTIDE into a
diffusion acquisition scheme, utilizing its highly rapid acquisition of
relaxometry data to enable joint diffusion-relaxometry in a previously
infeasible acquisition duration, at high spatial-resolution and free from image
distortion and blurring.Methods
PEPTIDE sampling was incorporated into a Stejskal-Tanner
diffusion sequence to achieve time-resolved distortion-free imaging, that
contains multi-echo data with varying degrees of T2 and T2* weighting around
the spin-echo timepoint (Figure 1). For each diffusion-direction, 12 shots of
PEPTIDE blade-acquisitions are acquired to provide this distortion-free
time-resolved data. The PEPTIDE specific parameters were set as previously published8 - Rseg=36, Rpe=4,
ETL or Ntimepoints=72 (time-resolved images). Two diffusion-PEPTIDE
protocols were tested. Protocol A: 30
directions at b=1000s/mm2 and 1 b=0 image, resolution=1.1x1.1x3.0mm3,
with a TESE=108ms, TR=2.5s, ESP=1.11ms for a total scan duration of
16mins. Protocol B: 12 directions at
b=500,1000,1500,2000,3000,4000,5000mm/s2 and 1 b=0 image,
resolution=1.0x1.0x3.0mm3, with TESE=125ms, TR=3s, ESP=1.2ms
for a total scan duration of 51mins.
Three subjects were scanned. Subjects 1&2 were scanned with Protocol A and Subject 3 with
Protocol B. In addition, MPRAGE and standard EPI-diffusion (R=3 in-plane
acceleration, parameters otherwise matched to diffusion-PEPTIDE acquisition)
data were acquired in one of the subjects, for comparing
image-distortion.
Reconstruction was performed offline using MATLAB, with
diffusion analysis performed in FSL11. PEPTIDE reconstruction
followed the previously described pipeline8, applying phase-correction to
each shot prior to combination. FSL processing was performed only to provide
the diffusion modeling (“dtifit”), without any application of
distortion-correction, further motion-correction, or any other typical
diffusion pre-processing steps.Results
The diffusion-PEPTIDE acquisitions successfully enabled
reconstruction of distortion-free time-resolved b=0 and diffusion-weighted
images.
Figure 2 compares the b=0 and DWI images from PEPTIDE and
traditional-EPI, using the MPRAGE acquisition as a structural reference. From axial slices from different levels of the brain, typical distortion
artifacts are visible for EPI whereas the PEPTIDE acquired distortion- and
blurring-free images match with the structure of the reference. A zoomed-in
region demonstrates that, even in regions of high EPI-distortion, PEPTIDE
maintains good structural shape without the application of retrospective
correction.
Figure 3 demonstrates the time-resolved capabilities of
diffusion-PEPTIDE, showing example b=0 and DWI images for a small selection of
the different reconstructed timepoints with different T2 & T2*
weightings (7 out of 72).
Figure 4 shows the calculated FA, MD and ε1 maps
acquired using Protocol A, with a zoomed region showing the dynamic capability of
these maps, cycling through the varying timepoints.
Figure 5 highlights some results for the dataset acquired
with Protocol B, which enabled reconstruction of (timepoints*b-values)=(72*7)=504
diffusion datasets (each from 12 diffusion-directions). Example MD maps
are shown for 5 of the b-values at 5 timepoints. On the right, plots of FA
values across this dataset are demonstrated for averaged ROIs in regions associated with
white-matter, gray-matter and CSF, highlighting the quantity of the
potential information contained within such a dataset. Discussion/Conclusion
PEPTIDE has been successfully incorporated into diffusion
acquisitions with a reasonable acquisition time, providing distortion-free diffusion imaging capable of being resolved into a large timeseries dataset.
Here we display results from a very preliminary exploration
this rich diffusion-relaxometry data. FA reduces with increasing b-value as expected12, with the addition of apparent variations in FA along timepoints, differing between regions. Work is underway to utilize recent
advances in diffusion-relaxation correlation modeling1,13,14 to extract
interesting microstructure composition and information.
One goal of this research is to utilize the high acquisition
efficiency of PEPTIDE to acquire extensive diffusion-relaxometry data to mine and better understand its limitations, for example allowing investigation
into the impact of subsampling on in vivo diffusion-relaxometry spectra
estimation (e.g. T2-D space1). This could potentially guide future
acquisition protocols for improved focus on key parameters.
Inversion-prepared EPTI has previously been
demonstrated15, which could be combined with the current approach, utilizing efficient sampling schemes such as in ZEBRA4, to
provide comprehensive in vivo signal sampling (T1-T2-Diso-Ddir
space), e.g. as previously performed for structural analysis of
materials16,17.Acknowledgements
This work was supported in
part by NIH research grants: R01MH116173, R01EB020613, R01EB019437, U01EB025162,
P41EB015896, and the shared instrumentation grants: S10RR023401, S10RR019307,
S10RR019254, S10RR023043.References
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