Hyungseok Jang1, Yajun Ma1, Adam C Searleman1, Michael Carl2, Jody Corey-Bloom3, Eric Y Chang1,4, and Jiang Du1
1Department of Radiology, University of California San Diego, San Diego, CA, United States, 2GE Healthcare, San Diego, CA, United States, 3Department of Neurosciences, University of California San Diego, San Diego, CA, United States, 4Radiology Service, VA San Diego Healthcare System, San Diego, CA, United States
Synopsis
Multiple sclerosis (MS) is the most common
immune-mediated demyelinating inflammatory disease, afflicting over 2.3 million
people globally. Magnetic resonance imaging (MRI) is the gold standard
non-invasive imaging modality to identify MS lesions. Clinically, both
CSF-suppressed T2-weighted and T1-weighted images are used for the
characterization of MS lesions (FLAIR and MP-RAGE sequences). However, these
sequences are not specific for demyelinating lesions and can be challenging to
interpret. In this study, we propose a direct myelin imaging technique utilizing
IR-prepared hybrid encoded UTE imaging, which provides highly specific
volumetric myelin images with scan time less than 7min.
Introduction
Multiple sclerosis (MS) is the most common
immune-mediated demyelinating inflammatory disease. Although MRI is the gold
standard imaging modality to identify MS-lesions, the clinical sequences are
not specific for demyelinating lesions and can be challenging to interpret.
Direct imaging of myelin could provide highly specific information to
characterize demyelinating lesions in MS. Unfortunately, it is challenging to
directly image myelin protons in white matter using MRI due to myelin’s
extremely low proton density and rapid signal decay (T2*<0.5ms at 3T)1,2. A breakthrough development
demonstrated that direct myelin imaging is feasible using inversion recovery
(IR) prepared ultrashort echo time (UTE) MRI3–6. In this study, we explore
the efficacy of IR prepared hybrid encoded UTE (IR-HE-UTE) with a novel
sampling strategy for direct 3D myelin imaging.Methods
Figure
1-a illustrates the typical T1-recovery curves of tissues in a brain. By
selecting TI matched to the nulling point of white matter, the white matter signal
can be suppressed. Residual gray matter signal can be suppressed utilizing dual-echo
UTE imaging by subtracting the second echo from UTE. After adiabatic inversion
preparation, imaging is performed, where multiple spokes are acquired after
each IR preparation in order to reduce the scan time for 3D imaging (Figure
1-b). Unfortunately, in the multi-spoke acquisition, image contrast is
inevitably degraded due to the spokes acquired at suboptimal TIs, resulting in
suboptimal white matter suppression. To address this issue, we propose a
strategy benefiting from hybrid encoding (HE)7. Figure 1-c
illustrates an example of the HE-sampling pattern. Figure 1-d shows a typical
sampling strategy for multi-spoke HE, sequentially performing the radial
frequency encoding and the SPI encoding. Figure 1-e shows the proposed sampling
strategy where SPI encodings are interleaved to the best time slot near the
optimal TI, which allows more efficient white matter suppression with a high
degree of multi-spoking since the central k-space encoded by SPI
significantly contributes to the image contrast. The proposed
IR-HE-UTE was evaluated with computer simulation, myelin phantom, ex-vivo MS brain, in-vivo healthy volunteers, and in-vivo
MS patients. For the computer simulation, a digital phantom was generated with T1s
selected to cover the typical T1 of myelin, white matter, gray matter, and CSF
at 3T (Figure 2-a). Then, multi-spoke IR imaging was simulated to null Tube-C
(white matter), using three different encoding schemes (radial frequency
encoding, conventional HE with sequential sampling, and the proposed HE with
interleaved SPI) with different levels of multi-spoking (1 to 91-spokes/IR).
For the phantom experiment, D2O-myelin and H2O-myelin
phantoms were prepared by compounding bovine myelin lipid powder with D2O
or H2O and imaged in 3T GE-MR750 using a custom-made birdcage-coil. An
ex-vivo experiment was performed with
a cadaveric MS brain in 3T GE-MR750 using 8-ch-receive-only head-coil. An in-vivo experiment was performed with 8
healthy volunteers and 13 MS patients in 3T GE-MR750 using 12-ch-receive-only
HNU coil. The MR imaging parameters can be found in the Figure captions.Results
Figures 2-b and 2-c show the result of the computer
simulation, where the proposed strategy shows overall better error performance when
compared to the conventional methods at a high degree of multi-spoking. Figure 3-a shows the H2O-myelin phantom imaged
with the proposed method at different TIs, demonstrating robust suppression of water
with TI=335ms at which the estimated T2* was 222.3±4.1µs (Figure 3-b). The
estimated T2* of the D2O-myelin phantom was 362.5±18.8µs (Figure
3-c), showing the elevated value presumably due to residual water in the
phantom. Figure 3-d shows results with a MS brain, where the demyelinated
lesions are clearly seen (yellow arrows). The estimated T2* was 271.8±2.6µs
(Figure 3-e), which was consistent with our previous studies (200-350µs)2. Figure 4-a shows the results
with a healthy volunteer. As seen, the strategy of interleaving SPI
dramatically improves the myelin contrast. Figure 4-b shows four different
myelin images by the proposed IR-HE-UTE method, reconstructed with different
sizes of the SPI-encoding region. As seen, the background signal tends to be
spatially biased with the smaller SPI size, which is well-suppressed with
larger SPI size (green arrows)8. Figure 5
shows the IR-HE-UTE and clinical MR images obtained with MS patients. The
demyelinated areas can be detected by the proposed IR-HE-UTE imaging as regions
where there is loss of the normal myelin signal (red arrows). Discussion and Conclusion
In this study, we have demonstrated the efficacy
and feasibility of inversion recovery prepared hybrid encoding for direct
myelin imaging in the human brain, which provides highly specific volumetric
myelin images, achieving both good image contrast with white matter suppressed
near-completely and a clinically feasible scan time of less than 7min.Acknowledgements
The authors acknowledge research support from GE Healthcare, NIH (R01NS092650), and VA Clinical Science and Rehabilitation R&D Awards (I01CX001388 and I01RX002604).References
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