Hyungseok Jang1, Zhao Wei1, Mei Wu1, Yajun Ma1, Eric Chang1,2, Jody Corey-Bloom1, and Jiang Du1
1University of California, San Diego, San Diego, CA, United States, 2VA San Diego Healthcare System, San Diego, CA, United States
Synopsis
Myelin accelerates neural signaling in the
central and peripheral nervous systems. Ultrashort echo time (UTE)-based imaging
techniques have been proposed for direct capture of magnetic resonance (MR)
signal from myelin lipid protons with extremely short T2* (~0.3 ms). To
suppress signal from long T2 water components and thereby improve myelin
imaging, inversion recovery (IR)-based UTE techniques have been proposed. In
this study, we explored the efficacy and feasibility of qualitative myelin
imaging in vivo combining dual-echo IR-UTE with complex echo subtraction.
Introduction
Myelin accelerates
transfer of neural signal in the central and peripheral nervous systems. Recently,
ultrashort echo time (UTE)-based imaging techniques have been proposed for
direct capture of the magnetic resonance (MR) signal from myelin lipid protons
with extremely short T2* (~0.3 ms)1,2. To suppress signal from long T2 water
components and thereby improve the dynamic range of myelin imaging, inversion
recovery (IR)-based UTE imaging techniques have been proposed3–7. In this study,
we explored the efficacy and feasibility of qualitative myelin imaging in vivo combining
dual-echo IR-UTE with the complex echo subtraction technique.Methods
Figure 1-a illustrates
the IR-UTE-Cones sequence, where an adiabatic IR pulse inverts the longitudinal
magnetization (Mz) of long T2 water components8. Figure 1-b shows typical IR of long T2 white
matter (WML), gray matter (GM), and myelin. The myelin magnetization
is not inverted, but partially saturated, by the long adiabatic inversion pulse,
showing positive Mz following the pulse9. The TI is adjusted to the nulling
point of WML. At that point, two images at UTE and TE2 are acquired
by dual echo UTE imaging (Figure 1-c), where the subsequent echo subtraction
reveals myelin signal with short T2*. Unfortunately, it is difficult to
completely suppress all WML signals at the TI due to inhomogeneous
T1 (Figure 1-d). Consequently, residual WML signal with negative Mz can
lead to error in myelin detection with magnitude subtraction (Figure 1-e) due
to the opposite initial phases of transverse magnetizations in the residual WML.
Conversely, complex subtraction can resolve the myelin signal regardless of the
initial phase of residual WML by correcting for the phase error due
to RF pulse, readout10, and B0 inhomogeneity11. After phase correction, the complex
signal at UTE is subtracted by the signal at TE2, and the remaining real
component is myelin signal.
To evaluate the
proposed method, 3D IR-UTE-Cones imaging was performed on 3T GE-MR750. Five
healthy volunteers (41.4±10.3 years) and five multiple sclerosis (MS) patients (59.4±7.7 years) were
recruited per IRB guidelines. Subjects underwent MP-RAGE,
FLAIR, and IR-UTE-Cones imaging. A dual echo UTE-Cones acquisition was also performed
to acquire a B0 map. For one healthy volunteer, actual flip angle imaging based
variable flip angle (AFI-VFA) UTE-Cones sequences were added to map T112. A 12-channel receive-only head coil was used
for imaging with the following parameters: 1) MP-RAGE: flip angle (FA)=12°,
FOV=256x256x178mm3, matrix=256x256x148, readout bandwidth (rBW)=±41.7kHz,
TE=3.2ms, TR/TI=8.2/450ms, acceleration factor=4, scantime=5 min. 2) FLAIR:
FA=90°, FOV=256x256x256mm3, matrix=256x256x256, rBW=±41.7kHz,
TE=116.5ms, TR/TI=7600ms/2162ms, acceleration factor=4, scantime=6min 54sec. 3)
IR-UTE-Cones: adiabatic inversion pulse (Silver-Hoult, duration=6.048ms and
bandwidth=1.643kHz), TR=1000ms, TI=330ms, TE=0.032/2.2ms, number-of-spoke-per-IR=21,
tau=7.1ms, FA=20°, bandwidth=±125kHz, FOV=220×220×151mm3,
matrix=192×192×42, scantime=8min 18sec. 4) Field map acquisition: matched IR-UTE-Cones
excepting TR=7.2ms, TE=0.032/2.2ms, FA=10°, scantime=1min 13sec. 5) AFI-VFA-T1
mapping: matched IR-UTE-Cones excepting FA=5/10/15/20/30°, TE=2.2ms,
scantime=16min 47sec. The UTE-Cones images were reconstructed using NuFFT13. The phase offset was estimated by
using the phase at UTE. B0 field map was estimated using FMRIB Software Library
(v5.0)14. For AFI-VFA UTE-Cones T1 measurement
in a brain, the Levenberg‐Marquardt
algorithm was used to solve the non‐linear
fitting for T1 measurement15.Results
For all subjects, complex subtraction showed
obvious improvement in detection of fine myelin structures. Figures 2 and 3
show results from a representative healthy volunteer. The artifact due to field
inhomogeneity was suppressed by phase correction (Figure 2). Figure 3 shows that
more morphological structures of myelin were detected with complex subtraction
in the WM region (red arrows); the fine myelin structures detected by complex
subtraction correspond to the pixels with higher T1 (blue arrows). Figure 3-e displays
the normalized error map between complex and magnitude subtraction, showing
increased error in the region with higher T1 (yellow arrows), implying that T1
variation is associated with underestimated/undetected myelin signal in magnitude
subtraction. Figure 4 shows results from MS patients. The myelin image obtained
with complex subtraction exhibits more fine myelin structures. Complex
subtraction detects the foci of demyelinated lesion more clearly than magnitude
subtraction (red arrows). Moreover, myelin signal is underestimated with the
magnitude subtraction (white arrow), presumably due to increased T1 associated
with pathological changes in WM. Figure 5 shows the detected myelin signal from
an MS patient. In all regions of interest, complex subtraction showed enhanced
myelin signal, also demonstrated by the shifted histogram in Figure 5-d. In
total, the myelin signal intensity measured with complex subtraction in the
left frontal lobe or left parietal lobe was enhanced by 53.8% or 79.6% for healthy
volunteers, and 126.8% or 135.9% for MS patients.Discussion and Conclusion
We showed that complex subtraction improved morphological
imaging of myelin by reducing residual WML signal contamination
caused by regional T1 variations. In both healthy volunteers and MS patients,
the signal intensity in the region of myelin was dramatically improved with complex
subtraction. The improvement was more dramatic in the myelin with fine
structures. In MS patients, the demyelinated lesions were more clearly detected
by the complex subtraction. Moreover, the signal intensity of the detected
myelin tended to be higher with the complex subtraction in the normal
appearing white matter. These results imply that complex subtraction may also
improve quantitative myelin imaging, such as in the estimation of myelin proton
density, T1, and T2*, which will be investigated in future studies.Acknowledgements
The authors acknowledge grant
support from the NIH (1R01 NS092650 and T32 EB005970), and GE Healthcare.References
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