Multi-use of multi-echo GRE
Poster No:
1973
Submission Type:
Abstract Submission
Authors:
Roman Fleysher1, Sachin Jambawalikar1, Pascal Spincemaille2, Michael Lipton1
Institutions:
1Columbia University Medical Center, New York, NY, 2Weill Cornell Medicine, New York, NY
First Author:
Co-Author(s):
Introduction:
Most brain MRI imaging protocols include a structural T1-weighted image, one or several functional, diffusion or arterial-spin labeling scans acquired using fast echo-planar imaging (EPI) technique and an auxiliary field map acquisition (or its near equivalent using reversed traversal in phase-encoding direction (Andersson, 2003, Hwang, 2023)) to correct susceptibility induced distortion in EPI scans (Jezzard, 1995). Field map is also used to correct small susceptibility induced distortions in the structural image (Fleysher, 2018).
Quantitative susceptibility mapping (QSM) sequence provides unique contrast information that is particularly useful in studies of disease states and aging. In this study we show that the QSM acquisition, with its multi-echo-based readout, is much more versatile than its typical application for mapping tissue iron content. We demonstrate that besides the susceptibility map, a high resolution multi-echo gradient echo (mGRE) scan can produce a T1-weighted image of spin density suitable for tissue segmentation, a field map suitable for distortion corrections, a map of R2* and susceptibility-weighted images.
Quantitative susceptibility mapping (QSM) sequence provides unique contrast information that is particularly useful in studies of disease states and aging. In this study we show that the QSM acquisition, with its multi-echo-based readout, is much more versatile than its typical application for mapping tissue iron content. We demonstrate that besides the susceptibility map, a high resolution multi-echo gradient echo (mGRE) scan can produce a T1-weighted image of spin density suitable for tissue segmentation, a field map suitable for distortion corrections, a map of R2* and susceptibility-weighted images.
Methods:
For the purposes of this demonstration, MRI data were collected from a healthy 22-year-old woman using a 3T Signa Premier GE MRI scanner with its 48-channel head coil. A single high resolution (1mm isotropic) 3-echo mGRE sequence with TR/TE/ΔTE=32.0/6.5/9ms, 122Hz bandwidth per pixel and flip angle=25° covered a 256x256x190mm field of view (whole brain) with parallel imaging acceleration of 3 along the right-left phase encoding direction and total imaging time of 9min. Logarithm of magnitude and complex phase were fit using weighted least squares to obtain a map of R2*, T1-weighted image of spin density and the field map. Maps of susceptibility were produced using MEDI method (Liu, 2013). Anatomical regions over the T1W spin density were delineated using FastSurfer (Henschel, 2020).
Results:
Image processing pipeline for data from mGRE sequence is shown in Figure 1. Top row represents raw magnitude and complex phase images collected at multiple echo times. Initial processing produces T1-weighted spin density, decay and field map which are in turn used to derive susceptibility map, susceptibility-weighted image and tissue segmentation. Figure 2 shows images created by this pipeline.
·Figure 1. Schematic of multi-echo GRE image processing pipeline.
·Figure 2. Zoomed view on output of pipeline in Figure 1. Top: T1W spin density, field map, map of R2*. Bottom: tissue segmentation, map of tissue susceptibility (QSM), susceptibility-weighted image.
Conclusions:
Magnetic field in the scanner is never exactly uniform and readout bandwidth is always finite. Consequently, all images are somewhat distorted. Field map scan, often viewed as auxiliary and sometimes omitted, is the only type of image that contains data to correct its own distortions and those of other images obtained during the same session. Enhanced by multiple echoes and finer spatial resolution it generates multiple image contrasts that can replace other scans and diminish total scan duration. Indeed, the MP-RAGE sequence, typically used to collect structural T1W images at 1mm isotropic resolution, runs for 3min with parallel imaging acceleration of 3 in right-left and 2 in superior-inferior directions. Applying similar acceleration to the mGRE scan would add 1.5min to scan duration and provide five contrasts/metrics: T1W, field map, R2*, QSM. SWI. Assuming identical readouts, noise in MP-RAGE and mGRE is identical, but signal in mGRE is about a factor of 2 higher thanks to the absence of the signal suppression by the inversion pulse. The gray/white matter tissue contrast is similar and sufficiently good for tissue segmentation and image registration.
In conclusion, multi-echo gradient-echo sequence is very versatile and in addition to generating quantitative susceptibility maps and susceptibility-weighted images, provides high resolution structural information, R2* and auxiliary field maps to correct susceptibility induced distortions large and small. It therefore can be used to replace individual dedicated MRI acquisitions to reduce overall scan protocol duration.
In conclusion, multi-echo gradient-echo sequence is very versatile and in addition to generating quantitative susceptibility maps and susceptibility-weighted images, provides high resolution structural information, R2* and auxiliary field maps to correct susceptibility induced distortions large and small. It therefore can be used to replace individual dedicated MRI acquisitions to reduce overall scan protocol duration.
Novel Imaging Acquisition Methods:
Multi-Modal Imaging 1
Imaging Methods Other 2
Keywords:
Acquisition
Design and Analysis
MRI
STRUCTURAL MRI
Other - quantitative susceptibility mapping, distortion correction
1|2Indicates the priority used for review
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2. Fleysher, R., et al. (2018). White matter structural integrity and transcranial Doppler blood flow pulsatility in normal aging, Magnetic Resonance Imaging, 47, 97-102.
3. Henschel, L., et al. (2020). FastSurfer - A fast and accurate deep learning based neuroimaging pipeline. NeuroImage 219, 117012.
4. Hwang, SH., et al. (2023). Distortion correction using topup algorithm by single k-space (TASK) for echo planar imaging. Sci Rep 13, 18751.
5. Jezzard, P. et al. (1995). Correction for geometric distortion in echo planar images from B0 field variations. Magn. Reson. Med. 34, 65–73.
6. Liu, T., et al. (2013). “Nonlinear formulation of the magnetic field to source relationship for robust quantitative susceptibility mapping,” Magn. Reson. Med., 69, 467–476.