A Systematic Investigation on the BOLD Contrast in S1- and S2-SSFP fMRI
Mahdi Khajehim1 and Abbas Nasiraei Moghaddam1,2

1Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran, 2School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran

Synopsis

Non-balanced SSFP can provide banding artifact free images, with reduced sensitivity to B1 inhomogeneity and SAR level. Recently, non-balanced SSFP which is known by the S1 and S2 signals, has been utilized for fMRI. In this study to model the BOLD contrast in S1- and S2-SSFP fMRI a Monte Carlo simulation has been performed. It will enable us to accurately investigate the dependence of the BOLD contrast on vessel size and acquisition parameters. Results are in accordance with the reported experimental values and show the increased sensitivity to capillary-sized vessels for only S2 signal.

Introduction:

Due to the limitations of the traditional GRE BOLD fMRI, there has been a growing interest to investigate other fMRI methods, such as spin echo and Balanced SSFP fMRI. Recently, Non-Balanced SSFP which is known by the S1 and S2 signals, has been utilized for fMRI 1,2. This method provides images free of banding artifacts and are particularly useful in high field, due to its reduced sensitivity to SAR level and B1 inhomogeneity. While the S1 signal is assumed to be more gradient echo like, S2-SSFP is supposed to show a more spin echo like behavior 2. Thus far, there has not been a systematic investigation on the BOLD contrast in non-Balanced SSFP fMRI. In this study, we use a Monte Carlo simulation to investigate the dependence of the BOLD contrast on vessel size and acquisition parameters for both S1- and S2-SSFP fMRI to reveal their potential advantages.

Methods:

Monte Carlo simulations were performed in B0=7 T by considering vessels as infinite cylinders occupying 2 % of the total voxel volume. To study the dependence of BOLD contrast on acquisition parameters (TR and FA) , a voxel with vessel diameters and distributions based on the model by Piechnik et al. 3 was simulated and then to assess the vessel size dependency, a fixed diameter ranging from 5 up to 100 µm were considered. Blood oxygenation was changed from 67% to 75% 4 for resting and active states, respectively. Blood susceptibility and field inhomogeneity for this change were calculated from previous studies 5,6. Intravascular relaxation changes based on the oxygenation level were calculated from approximations provided by Uludag et al. 7. For the extravascular contrast, 2500 spins capable of 3D Brownian random walk with apparent diffusion coefficient of 0.001 mm2/s were placed only in the extravascular space. Tissue relaxation parameters of T1=2000 and T2=47 ms were selected 8 ,for gray matter in 7 T. Double Echo (DESS or FADE) sequence was used to detect the S1 and S2 signals as shown in Figure 1. All signals were recorded after reaching steady state. Intra and extravascular signals were combined based on their volume fractions to yield the total signal. Simulations were performed for a range of TRs (8-40 ms) and flip angels (10-60⁰). Signal change between the active and resting states divided by the rest signal was considered as relative functional contrast.

Results:

Two examples of the 3D vessel networks and 2D field maps for small and large vessels are shown in Figure 2. Figure 3 shows the percent functional contrast for a range of TRs and FAs for both S1 and S2. Finally the vessel size sensitivity of these two signals for different TRs (FA=45⁰) is illustrated in Figure 4. These patterns are generally repeated for other FA values.

Discussion:

Figure 2 shows that S1 contrast, unlike S2, is mainly dependent on TR. The simulated values reported in this figure are in good agreement with the few experimental results , reported in 1 and 2. As an example 1 for S2, reported 2.7% and 5.4% in TR=15 ms and TR=27 ms (FA=25⁰), respectively, while the simulated values are 3.3% and 5.5% . Results in Figure 3 obviously show that S2-SSFP fMRI is more sensitive to capillary-sized vessels (with diameters around 5-10 µm) and therefore to some extent, shows the spin echo like spatial specificity, while S1 does not show such a sensitivity and contrast is mainly driven by TR. This figure is in accordance with the experimental observations by Barth et al. 1 which showed the spin echo like spatial localization for S2-SSFP fMRI . It also shows that some increased sensitivity for larger veins would be observed for higher TRs which is in agreement by the results reported by 9 and 2. It is worth noting, due to the dramatic reduction of blood T2 in high field, intravascular contrast plays only a minor role in forming the total contrast and therefore the uncertainty in approximating intravascular relaxation changes have a negligible impact on results.

Conclusion:

We have presented a systematic investigation on the BOLD contrast in S1- and S2-SSFP fMRI which are especially of interest in high field imaging for their low artifact and low SAR nature. Obtained results which agree well with the reported experimental values show the increased sensitivity to capillary-sized vessels for only S2 signal. These results also help in selecting acquisition parameters to obtain optimum functional contrast and/or spatial specificity.

Acknowledgements

This work was funded in part by Iranian Cognitive Science and Technologies Council (CSTC).

References

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9. P. Ehses, J. Budde , G. Shajan KS. T2-weighted BOLD fMRI at 9.4 T using a S2-SSFP-EPI sequence. In:Proceedings of 21th Annual Meeting of ISMRM, Salt Lake City,Utah,USA, 2013. p. 414.

Figures

Figure 1 . Double Echo (DESS or FADE) sequence was used to detect S1 and S2 signals

Figure 2. Two examples of the 3D vessel networks and 2D field maps for small (top row, diameter 8 μm) and large ( bottom row, diameter 80 μm) vessels

Figure 3. Relative functional contrast (%) for S1 (top) and S2 (bottom) SSFP fMRI

Figure 4. Vessel size sensitivity for S1 (top) and S2 (bottom) SSFP fMRI for a range of TRs



Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)
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