Synopsis

This work attempts to directly image ultrashort T₂ myelin signals using ultra short echo time (UTE) MRI. Long T₂ water signals were suppressed using either adiabatic inversion recovery (AIR) to null signal of a single T₁, or multiple adiabatic inversion recovery (MAIR) to null signal over a range of T₁s. AIR-UTE showed contrast in white matter, but no such signal was observed in MAIR-UTE. These findings indicate that the AIR-UTE white matter signals are unsuppressed water signals and that the solid proton signals of myelin decay too quickly to be observed by UTE MRI.

Introduction

The phospholipid protons in myelin are known produce a ¹H NMR signal with an ultrashort T₂ relaxation component [1,2]. Recent studies have attempted to image these signals using ultrashort echo time (UTE) or similar MRI techniques [3-7]. While these studies have found contrast in white matter, thought to be from myelin, the origins of these signals remain unclear.

One approach to distinguishing bound proton signals from those of water protons, is through T₂ selective magnetization preparation. Adiabatic inversion pulses of sufficient power will invert water proton magnetization while saturating magnetization with ultrashort T₂. Thus, an adiabatic inversion recovery (AIR) preparation with recovery time chosen to null magnetization with a T₁ of water protons, will provide enhanced contrast from ultrashort T₂ signals. However, longitudinal relaxation of water in white matter is not mono-exponential and will vary due to a number of physiological factors [8], including myelin concentration [9] and axon size [10]. Therefore, AIR prep is unlikely to fully suppress all water proton signals in the brain.

The multiple adiabatic inversion recovery (MAIR) pulse sequence has previously been used to suppress free water signals from bone across a wide range of T1s [11]. Here, we apply MAIR with the aim of imaging only the ultrashort T2 signals observable in the head.

Methods

Four UTE datasets were acquired using a 3T Philips scanner with local IRB approval and written, informed consent. One representative dataset is outlined below. Half-pulse excited 2D-UTE was used to image a single brain slice, with 1.5 mm in plane resolution, a FOV of 220 mm, and 5-mm thick slice. Half-pulse gradient waveforms were predistorted to minimize the influence of eddy currents on slice thickness [12,13]. Conventional UTE images were acquired with a TR = 4.85 ms, excitation flip angle = 7º, and TE = 0.07 ms with pseudo golden angle view ordering. AIR and MAIR prepared UTE images were acquired with TR = 400 ms. AIR images used an inversion time of 170, 175, or 180 ms to null long-lived T2 water signals from white matter. MAIR inversion times, TI₁ = 195.1 ms and TI₂ = 76.7 ms, were selected to suppress T₁s relaxation time constants in the range of 0.2–2 s.

Figure 1 shows predicted ultrashort T₂ signal from myelin solid protons as well as predicted long-T₂ signal magnitudes as a function of T₁ for UTE, AIR, and MAIR experiments. At the time of excitation, the AIR pulse sequence nulls signal from white matter, but signals are still present from a range of T₁ relaxation times. MAIR reduces total water signal within this range of T₁.

Results and Discussion

UTE, AIR (TI=175 ms), and MAIR images are shown in Figure 2. The AIR image shows signal in various locations, including white matter regions, the skull bone (known to contain an ultrashort T₂ component), and fat around the skull. Signal located outside the head near the top of the field of view originate from plastic within the RF receive coil. The MAIR image also shows relatively large signals from bone and the RF coils; the fat signal is present but suppressed relatively the AIR image; but no signal is present in white matter regions.

The absence of white matter signal in the MAIR image indicates that the AIR white matter signal was not an ultrashort T₂ component, but a water T₂ component that was not fully suppressed by the AIR preparation. Further, these observations indicate that the solid proton signal from myelin likely decays too quickly to be imaged using a clinical UTE sequence.

Acknowledgements

References

1. Wilhelm, M. J., Ong, H. H., Wehrli, S. L., Li, C., Tsai, P.-H., Hackney, D. B., & Wehrli, F. W. (2012). Direct magnetic resonance detection of myelin and prospects for quantitative imaging of myelin density. Proceedings of the National Academy of Sciences of the United States of America, 109(24), 9605–10. http://doi.org/10.1073/pnas.1115107109

2. Horch, R. A., Gore, J. C., & Does, M. D. (2011). Origins of the ultrashort-T2 1H NMR signals in myelinated nerve: a direct measure of myelin content? Magnetic Resonance in Medicine, 66(1), 24–31. http://doi.org/10.1002/mrm.22980

3. Sheth, V., Shoa, H., Chen, J., VandenBerg, S., Corey-Bloom, J., Bydder, G. M., & Du, J. (2016). Magnetic resonance imaging of myelin using ultrashort Echo time (UTE) pulse sequences: Phantom, specimen, volunteer and multiple sclerosis patient studies. NeuroImage, 136, 37–44. http://doi.org/10.1016/j.neuroimage.2016.05.012

4. Boucneau, T., Cao, P., Tang, S., Han, M., Xu, D., Henry, R. G., & Larson, P. E. Z. (2018). In vivo characterization of brain ultrashort-T2components. Magnetic Resonance in Medicine, 80(2), 726–735. http://doi.org/10.1002/mrm.27037

5. Jiang, X., van Gelderen, P., & Duyn, J. H. (2017). Spectral characteristics of semisolid protons in human brain white matter at 7 T. Magnetic Resonance in Medicine, 78(5), 1950–1958. http://doi.org/10.1002/mrm.26594

6. Fan, S. J., Ma, Y., Zhu, Y., Searleman, A., Szeverenyi, N. M., Bydder, G. M., & Du, J. (2018). Yet more evidence that myelin protons can be directly imaged with UTE sequences on a clinical 3T scanner: Bicomponent T2* analysis of native and deuterated ovine brain specimens. Magnetic Resonance in Medicine, 80(2), 538–547. http://doi.org/10.1002/mrm.27052

7. Seifert, A. C., Li, C., Wilhelm, M. J., Wehrli, S. L., & Wehrli, F. W. (2017). Towards quantification of myelin by solid-state MRI of the lipid matrix protons. NeuroImage, 163(June), 358–367. http://doi.org/10.1016/j.neuroimage.2017.09.054

8. Does, M. D. (2018). Inferring brain tissue composition and microstructure via MR relaxometry. Neuroimage, 182, 136–148. http://doi.org/10.1016/j.neuroimage.2017.12.087

9. Stüber, C., Morawski, M., Schäfer, A., Labadie, C., Wähnert, M., Leuze, C., … Turner, R. (2014). Myelin and iron concentration in the human brain: A quantitative study of MRI contrast. NeuroImage, 93, 95–106. http://doi.org/10.1016/j.neuroimage.2014.02.026

10.Harkins, K. D., Xu, J., Dula, A. N., Li, K., Valentine, W. M., Gochberg, D. F., … Does, M. D. (2016). The microstructural correlates of t 1 in white matter. Magnetic Resonance in Medicine, 75, 1341–1345. http://doi.org/10.1002/mrm.25709

11.Harkins KD, Uppuganti S, Nyman JS, Does MD. Robust Pore Water Suppression in Cortical Bone with Multiple Adiabatic Inversion Recovery. In: Proc ISMRM. 2017. p. 1588.

12.Harkins, K. D., Does, M. D., & Grissom, W. a. (2014). Iterative method for predistortion of MRI gradient waveforms. IEEE Transactions on Medical Imaging, 33(8), 1641–7. http://doi.org/10.1109/TMI.2014.2320987

13.Manhard, M. K., Harkins, K. D., Gochberg, D. F., Nyman, J. S., & Does, M. D. (2017). 30-Second Bound and Pore Water Concentration Mapping of Cortical Bone Using 2D UTE With. Magnetic Resonance in Medicine. http://doi.org/10.1002/mrm.26605