Functional MRI at Low Magnetic Field Strength
Jacco A de Zwart1
1Advanced MRI section, LFMI, NINDS, National Institutes of Health

Synopsis

There is renewed interest in MRI at low field because of cost, portability, and safety benefits. Functional MRI benefits from high field strength since intrinsic SNR and susceptibility contrast increase with B0. However, physiological noise limits detection sensitivity at moderate resolution. Furthermore, low-field MR benefits from increased T2* and decreased T1. Finally, high field uniformity at low field is essential for transition-band balanced SSFP, an alternative to EPI for BOLD imaging at low field. Preliminary investigation shows that, when accounting for imaging-gradient concomitant field effects, both SSFP and EPI can be readily performed at 0.55 T, EPI showing highest performance.

Syllabus

Recently there has been renewed interest in low-field (<1 Tesla) MRI. This is motivated by the cost-effectiveness, safety considerations, and greater ease of siting (even portability) of a low-field system. A compact, low-cost low-field MR system may increase the use of MRI in rural areas, underdeveloped countries, and in point-of-care and intra-operative scenarios [1,2].

Whereas low-field MR inherently provides reduced SNR, this can under some conditions be partially offset by the increased T2 and T2*, and reduced T1 relaxation times characteristic of lower magnetic field strength MR.

One part of this renewed low-field effort focuses on the optimization of the system design for portable or low-cost scanners [3]. But there is also a need to re-evaluate what applications are particularly suitable for low-field MR, and how intrinsic image contrasts are affected by low-field. Obviously, an abundance of low-field data from the early days of MRI is available, however substantial performance increases in gradient hardware [4], RF coils, and computer technology have been made, giving rise to the need for this re-evaluation.

Functional MRI is commonly based on local Blood Oxygen Level Dependent (BOLD) signal changes that coincide with neuronal activation. Generally, fMRI is considered to benefit from high magnetic field strength, firstly because the intrinsic SNR scales with B0, and secondly because of increases in the magnetic susceptibility contrast that underlies BOLD fMRI [5-8]. The elevated SNR and sensitivity may be traded for high spatial resolution, enabling applications such as laminar fMRI and imaging of neural circuits [9-11]. However, at the modest spatial resolutions frequently used (tens of mm3 voxel volume), the dominant source of temporal signal variance is physiological noise. This physiology-limited temporal SNR (tSNR) limits the beneficial effect of high field on the contrast-to-noise ratio (CNR) of BOLD fMRI [12,13]. Performance differences between low and high field scanners in terms of CNR, and thus the sensitivity in detecting brain activation, are therefore expected to be small at modest resolution.

At the same time, fMRI techniques at low field may benefit from a few technical advantages that one may leverage to compensate for the lower SNR and CNR. First, fMRI signal is less affected by signal dropout and image distortions caused by macroscopic susceptibility effects that may be severe at high field, and which are particularly troublesome in the frontal lobe, temporal lobe, and the lower (inferior) brain [14-16]. Second, the shortened T1 relaxation time may enable more efficient sequence design by reducing TR, and the prolonged T2* allows lengthening the data readout window without the penalty of substantial T2* blurring and geometrical distortions. Therefore, sufficiently high SNR with a reasonable temporal resolution and spatial coverage may be achieved. Since the advent of fMRI, a modest number of low-field studies have confirmed the possibility of performing task-based BOLD fMRI (mostly based on FLASH) in the motor cortex [17-22] and the visual cortex [5,17,23], but generally research into this application has been limited.

The improved field uniformity is particularly advantageous for fMRI techniques based on the transition band of balanced SSFP (also called "true FISP/FIESTA"), which has exquisite sensitivity in a narrow frequency band of a few Hz around resonance (known as the transition band) [24,25]. This characteristic of SSFP has been employed for flow imaging [26], enhancement of brain tissue contrast [27], and the detection of subtle field changes associated with the BOLD effect [28-32]. This high sensitivity to frequency changes results in stringent requirements on spatial and temporal field uniformity that are prohibitive at high field [33] but much more easily met at low field. One issue to be considered at low field are magnetic field effects concomitant to the use of imaging gradients. These concomitant field effects scale with 1/B0 (see Equation 1), and therefore may significantly impact frequency/phase-sensitive applications such as transition-band SSFP at low field [34,35].

$$B_c=\frac{G_z^2}{8B_0}(x^2+y^2)+\frac{G_x^2+G_y^2}{2B_0}z^2-\frac{G_yG_z}{2B_0}yz-\frac{G_xG_z}{2B_0}xz\qquad(1)$$
Recent work by our group has compared the feasibility of EPI-based BOLD fMRI and transition-band SSFP-based fMRI on a modern 0.55 T MRI scanner equipped with modern hardware, including shielded high-performance gradients [36]. The work optimized SSFP acquisition parameters by simulations, and calculated the adjustments needed to compensate for concomitant field effects. EPI data was acquired at the optimal TE=T2*, with other parameters set to facilitate a reasonable comparison to SSFP. Visual stimulation experiments in human volunteers demonstrated that sufficient sensitivity was available for robust detection of brain activation in ~40 μl voxels in under 5 min scans, and that standard EPI outperformed the SSFP-based approach in terms of signal stability. This suggests that at modest spatial resolution, fMRI can be readily performed on low field MRI systems.

Acknowledgements

This syllabus was derived from [36], so that work's other authors, Yicun Wang, Peter van Gelderen, Adrienne Campbell-Washburn and Jeff Duyn are acknowledged. The work is supported by the intramural research programs of the National Institutes of Neurological Disorders and Stroke and the National Hearth, Lung, and Blood Institute at the National Institutes of Health.

References

[1] Marques JP, Simonis FFJ, Webb AG. Low-field MRI: An MR physics perspective. J Magn Reson Imaging 2019;49(6):1528-42.

[2] Geethanath S, Vaughan JT, Jr. Accessible magnetic resonance imaging: A review. J Magn Reson Imaging 2019;49(7):e65-e77.

[3] Wald LL, McDaniel PC, Witzel T, Stockmann JP, Cooley CZ. Low-cost and portable MRI. J Magn Reson Imaging 2020;52(3):686-96.

[4] Campbell-Washburn AE, Ramasawmy R, Restivo MC, Bhattacharya I, Basar B, Herzka DA, et al. Opportunities in Interventional and Diagnostic Imaging by Using High-Performance Low-Field-Strength MRI. Radiology 2019;293(2):384-93.

[5] Gati JS, Menon RS, Ugurbil K, Rutt BK. Experimental determination of the BOLD field strength dependence in vessels and tissue. Magn Reson Med 1997;38(2):296-302.

[6] Uludag K, Muller-Bierl B, Ugurbil K. An integrative model for neuronal activity-induced signal changes for gradient and spin echo functional imaging. Neuroimage 2009;48(1):150-65.

[7] Duyn JH. The future of ultra-high field MRI and fMRI for study of the human brain. Neuroimage 2012;62(2):1241-8.

[8] Guerin B, Villena JF, Polimeridis AG, Adalsteinsson E, Daniel L, White JK, et al. The ultimate signal-to-noise ratio in realistic body models. Magn Reson Med 2017;78(5):1969-80.

[9] Duyn J, Koretsky AP. Magnetic resonance imaging of neural circuits. Nat Clin Pract Cardiovasc Med 2008;5 Suppl 2:S71-8.

[10] Polimeni JR, Fischl B, Greve DN, Wald LL. Laminar analysis of 7T BOLD using an imposed spatial activation pattern in human V1. Neuroimage 2010;52(4):1334-46.

[11] Dumoulin SO, Fracasso A, van der Zwaag W, Siero JCW, Petridou N. Ultra-high field MRI: Advancing systems neuroscience towards mesoscopic human brain function. Neuroimage 2018;168:345-57.

[12] Kruger G, Glover GH. Physiological noise in oxygenation-sensitive magnetic resonance imaging. Magn Reson Med 2001;46(4):631-7.

[13] Triantafyllou C, Hoge RD, Krueger G, Wiggins CJ, Potthast A, Wiggins GC, et al. Comparison of physiological noise at 1.5 T, 3 T and 7 T and optimization of fMRI acquisition parameters. Neuroimage 2005;26(1):243-50.

[14] Jezzard P, Balaban RS. Correction for geometric distortion in echo planar images from B0 field variations. Magn Reson Med 1995;34(1):65-73.

[15] Robson MD, Gore JC, Constable RT. Measurement of the point spread function in MRI using constant time imaging. Magn Reson Med 1997;38(5):733-40.

[16] Jezzard P. Correction of geometric distortion in fMRI data. Neuroimage 2012;62(2):648-51.

[17] Santosh CG, Rimmington JE, Best JJ. Functional magnetic resonance imaging at 1 T: motor cortex, supplementary motor area and visual cortex activation. Br J Radiol 1995;68(808):369-74.

[18] Gering DT, Weber DM. Intraoperative, real-time, functional MRI. J Magn Reson Imaging 1998;8(1):254-7.

[19] Jones AP, Hughes DG, Brettle DS, Robinson L, Sykes JR, Aziz Q, et al. Experiences with functional magnetic resonance imaging at 1 tesla. Br J Radiol 1998;71(842):160-6.

[20] van der Kallen BF, van Erning LJ, van Zuijlen MW, Merx H, Thijssen HO. Activation of the sensorimotor cortex at 1.0 T: comparison of echo-planar and gradient-echo imaging. AJNR Am J Neuroradiol 1998;19(6):1099-104.

[21] Schulder M, Azmi H, Biswal B. Functional magnetic resonance imaging in a low-field intraoperative scanner. Stereotact Funct Neurosurg 2003;80(1-4):125-31.

[22] Boghi A, Rampado O, Bergui M, Avidano F, Manzone C, Coriasco M, et al. Functional MR study of a motor task and the tower of London task at 1.0 T. Neuroradiology 2006;48(10):763-71.

[23] Lundervold A, Ersland L, Gjesdal KI, Smievoll AI, Tillung T, Sundberg H, et al. Functional magnetic resonance imaging of primary visual processing using a 1.0 Tesla scanner. Int J Neurosci 1995;81(3-4):151-68.

[24] Carr HY. Steady-state free precession in nuclear magnetic resonance. Phys Rev 1958;112(5):1693-701.

[25] Scheffler K, Hennig J. Is TrueFISP a gradient-echo or a spin-echo sequence? Magn Reson Med 2003;49(2):395-7.

[26] Markl M, Alley MT, Elkins CJ, Pelc NJ. Flow effects in balanced steady state free precession imaging. Magn Reson Med 2003;50(5):892-903.

[27] Lee J, Fukunaga M, Duyn JH. Improving contrast to noise ratio of resonance frequency contrast images (phase images) using balanced steady-state free precession. Neuroimage 2011;54(4):2779-88.

[28] Scheffler K, Seifritz E, Bilecen D, Venkatesan R, Hennig J, Deimling M, et al. Detection of BOLD changes by means of a frequency-sensitive trueFISP technique: preliminary results. NMR Biomed 2001;14(7-8):490-6.

[29] Miller KL, Hargreaves BA, Lee J, Ress D, deCharms RC, Pauly JM. Functional brain imaging using a blood oxygenation sensitive steady state. Magn Reson Med 2003;50(4):675-83.

[30] Miller KL, Smith SM, Jezzard P, Pauly JM. High-resolution FMRI at 1.5T using balanced SSFP. Magn Reson Med 2006;55(1):161-70.

[31] Lee J, Shahram M, Schwartzman A, Pauly JM. Complex data analysis in high-resolution SSFP fMRI. Magn Reson Med 2007;57(5):905-17.

[32] Sun K, Xue R, Zhang P, Zuo Z, Chen Z, Wang B, et al. Integrated SSFP for functional brain mapping at 7T with reduced susceptibility artifact. J Magn Reson 2017;276:22-30.

[33] Miller KL. FMRI using balanced steady-state free precession (SSFP). Neuroimage 2012;62(2):713-9.

[34] Norris DG, Hutchison JM. Concomitant magnetic field gradients and their effects on imaging at low magnetic field strengths. Magn Reson Imaging 1990;8(1):33-7.

[35] Bernstein MA, Zhou XJ, Polzin JA, King KF, Ganin A, Pelc NJ, et al. Concomitant gradient terms in phase contrast MR: analysis and correction. Magn Reson Med 1998;39(2):300-8.

[36] Wang Y, van Gelderen P, de Zwart JA, Campbell-Washburn AE, Duyn JH. FMRI based on transition-band balanced SSFP in comparison with EPI on a high-performance 0.55 T scanner. Magn Reson Med 2021;85(6):3196-210.

Proc. Intl. Soc. Mag. Reson. Med. 30 (2022)