Prospects for "bloodless fMRI"
Mukund Balasubramanian1,2

1Department of Radiology, Boston Children's Hospital, Boston, MA, United States, 2Harvard Medical School, Boston, MA, United States

Synopsis

It may surprise many to learn that attempts to record fMRI signals in the human brain that are nonvascular in origin are almost as old as those utilizing the hemodynamic response to neuronal activity. But whereas hemodynamic fMRI (especially BOLD-fMRI) has gone on to achieve fame and fortune, “bloodless fMRI” has floundered in the shadows of its more illustrious (“bloody”) counterpart. Here we will review several contrast mechanisms that have been proposed for bloodless fMRI and discuss the possibility that substantive progress in this area might have been impeded, in part, by our collective failure to ask the right questions.

Contrast mechanisms for bloodless fMRI

Neuronal-current MRI (ncMRI)

The oldest contrast mechanism that has been proposed for bloodless fMRI is also perhaps the simplest one to understand conceptually: associated with any electric current, such as a neuronal one, is an accompanying magnetic field (from Ampère’s law or the Biot-Savart law). The z-component of this neuronal magnetic field (i.e., the component along the main magnetic field B0), will alter the Larmor precession frequency of spins experiencing this field, resulting in a change in the phase of the net transverse magnetization vector within a voxel or a reduction in the magnitude of this vector (due to intra-voxel dephasing), or possibly both, depending on the spatial pattern of the neuronal magnetic field. This mechanism, most commonly referred to as neuronal-current MRI or ncMRI (Bandettini et al., 2005, Hagberg et al., 2006), but also as magnetic-source MRI or msMRI (Xiong et al., 2003), Direct-MR Neuronal Detection or DND (Chow et al., 2008), etc., has been clearly demonstrated in electric-current phantoms (Bodurka et al., 1999, Bodurka and Bandettini, 2002, Pell et al., 2006).

The first attempt to use this contrast mechanism to detect neuronal currents in the human brain was over two decades ago, and was a negative result (Singh, 1994). Since then, several groups have reported positive results on the detection of neuronal currents in humans (Kamei et al., 1999, Xiong et al., 2003, Bianciardi et al., 2004, Konn et al., 2004, Liston et al., 2004, Chow et al., 2006, Chow et al., 2007, Chow et al., 2008, Sundaram et al., 2010). These results, however, conflict with published reports of negative findings (Chu et al., 2004, Parkes et al., 2007, Mandelkow et al., 2007, Tang et al., 2008, Rodionov et al., 2010, Luo et al., 2011b, Huang, 2014) as well as theoretical arguments (i.e., based on modeling and simulations) against the feasibility of detecting these signals using present-day MRI technology (Cassara et al., 2008, Luo et al., 2011a, Jay et al., 2012).

Lorentz effect imaging (LEI) and magnetohydrodynamic (MHD) flow

A wire or nerve fiber carrying an electric current in the presence of an external magnetic field, such as the main magnetic field B0 of an MRI scanner, will experience a Lorentz force with a magnitude proportional to both the amplitude of the current and the strength of the external magnetic field. Allen Song and colleagues proposed that MR signals sensitive to the resulting displacement of nerve fibers could therefore serve as the basis for non-invasively detecting currents in these fibers, a method they called Lorentz effect imaging or LEI (Song and Takahashi, 2001, Truong et al., 2006), and ostensibly demonstrated this effect in vivo in the human median nerve (Truong and Song, 2006). This work has, however, been challenged by Bradley Roth and colleagues, who argue that Lorentz effect displacements would likely be far too small to explain the median nerve results of Truong and Song, on the basis of calculations incorporating realistic values of the current density, the size of the human arm and median nerve, and the elastic properties of soft tissue (Roth and Basser, 2009).

The Lorentz effect mechanism was subsequently reincarnated for the purpose of imaging ionic currents in solution (rather than currents carried by a wire or nerve), motivated by the argument that these ionic currents are more appropriate models for neural conduction in biological systems (Truong et al., 2008), thus perhaps providing a better basis for bloodless fMRI. To demonstrate this effect, Truong et al. investigated ionic volume currents in a spherical phantom scanned at 4T, and observed a large apparent displacement of the currents in a direction orthogonal to the main magnetic field B0, an effect they explained with a simple mechanism incorporating the Lorentz force law and a drag term. However, this work was again challenged by Roth and colleagues, who pointed out that when realistic values of ion mobility are used in the model proposed by Truong et al., the predicted displacement of the volume currents by the magnetic field is negligible (Wijesinghe and Roth, 2010). They suggested that the signals observed by Truong et al. might instead be explained by magnetohydrodynamic (MHD) flow—i.e., fluid flow that can occur when a conducting fluid experiences both an electric and a magnetic field, a consequence of combining Maxwell’s equations from electromagnetism with the Navier-Stokes equations from fluid mechanics (Jackson, 1975). Subsequent experiments (Balasubramanian et al., 2015) and computer simulations (Pourtaheri et al., 2013) have lent support to this explanation. To the best of my knowledge, this mechanism has only been demonstrated in phantoms thus far.

Using oscillatory neuronal activity to excite spins (ULF and SIRS)

In an MR experiment, an oscillating magnetic field (the B1 field) is used to “tip” spins into the transverse plane, with the subsequent transverse magnetization forming the basis for MR signal reception. If this B1 field, typically generated by the transmit coil in an MR scanner, were to instead be generated by neuronal currents, MR signals would in principle only be observed in the vicinity of this neuronal activity. This would, however, require neuronal currents to oscillate at the Larmor frequency, which is typically on the order of ~100 MHz (i.e., in the radiofrequency or RF regime) for proton resonance at typical MR scanner field strengths, far above the ~100 Hz frequency regime of neuronal currents. Ultra-low-field (ULF) MRI scanners, on the other hand, operate in the 1-100 µT range (Espy et al., 2013), raising the intriguing possibility that transient neuronal fields could provide the resonant excitation of proton magnetization in these scanners (Kraus et al., 2008, Cassara and Maraviglia, 2008, Cassara et al., 2009, Hofner et al., 2011, Hilschenz et al., 2013). The extremely low signal-to-noise ratio (SNR) at these low field strengths does, however, pose a major challenge.

In order to use the contrast mechanism above at the typical field strengths of MR scanners (1.5T and above), thereby potentially overcoming SNR limitations, Larry Wald and colleagues (Witzel et al., 2008) proposed a method they termed Stimulus-induced Rotary Saturation or SIRS, which exploits the spin-locking mechanism. The idea behind this is as follows: consider a magnetization vector that has already been tipped into the transverse plane. The transmit coil then generates a spin-lock magnetic field B1Lock in the same direction as the magnetization vector (i.e., a field that, in the laboratory frame, rotates at the same frequency and phase as the magnetization). From the perspective of the rotating frame, the magnetization only experiences the B1Lock field and not the B0 field, in the on-resonance condition (Fukushima and Roeder, 1981). The effective Larmor frequency in the rotating frame is then (very close to) γB1Lock, and if the amplitude of the spin-lock field B1Lock is chosen judiciously such that the effective Larmor frequency is matched to the neuronal-current frequency, this would allow these currents to tip the magnetization in the rotating frame. The spin-lock field B1Lock is then switched off, and the magnetization vector (unaffected in the absence of neuronal currents, but altered in their presence) is manipulated in the usual ways to generate an MR image (Witzel et al., 2008). Further refinements and extensions of this idea have aimed at improving the sensitivity of the technique (Halpern-Manners et al., 2010, De Luca, 2011, Jiang et al., 2016). At the time of writing, this mechanism has only been demonstrated in phantoms, to the best of my knowledge.

Nonvascular diffusion fMRI at high b-values (DfMRI)

The mechanisms described above are all, in one way or another, based on electromagnetic changes accompanying neuronal activity. Mechanical changes, however, also accompany neuronal activity, with dendritic spines twitching (Crick, 1982) and "dancing" (Halpain, 2000), and with neurons and glial cells rapidly and transiently swelling with activation (Tasaki et al., 1985, Andrew and Macvicar, 1994, Holthoff and Witte, 1996, Tasaki, 1999, Takagi et al., 2002).

Denis Le Bihan and colleagues have proposed that such mechanical changes might be the basis for a bloodless fMRI contrast mechanism based on diffusion imaging with high b-values, a mechanism they refer to as “DfMRI”. The basic idea here is that the use of high b-values (i.e., strong diffusion weighting) enables the separation and identification of fast and slow diffusing water pools, with the slow diffusing water pool believed to reflect the interaction of water with cell membranes, and thus being sensitive to changes in the size and configuration of these membranes during neuronal activity (Le Bihan, 2012). Although several studies in humans and other animals have reported high b-value diffusion changes with functional activation (Darquie et al., 2001, Le Bihan et al., 2006, Yacoub et al., 2008, Aso et al., 2009), the hypothesis that these signal changes are truly nonvascular in origin has been challenged by several groups, either on experimental (Miller et al., 2007, Jin and Kim, 2008) or theoretical (Kershaw et al., 2009, Autio et al., 2011) grounds.

Other potential contrast mechanisms for bloodless fMRI

The contrast mechanisms for bloodless fMRI described above hardly constitute an exhaustive list, due to the following two points: (1) the phenomenon we would like to measure, i.e., neuronal activity in the human brain, is characterized by a plethora of (nearly) simultaneous events: electric-current discharges and their accompanying electromagnetic fields, movement of several different types of ion (Na+, K+, Cl-, Ca2+), mechanical effects such as cell swelling, consumption of various metabolites and resulting production of waste products, and so on, and (2) the device we would like to use to measure neuronal activity, i.e., the MR scanner, is an incredibly versatile instrument, capable of providing information on tissue structure and function, anatomy and physiology, diffusion and perfusion, and so on. Therefore it should come as no surprise that when it comes to conjuring up novel contrast mechanisms for bloodless fMRI, we may only be limited by our imagination. However, determining the sensitivity and specificity with which such mechanisms can detect neuronal activity, as well as the accuracy and precision with which we can localize such activity, and on top of all that, figuring out the right questions to ask, may well be where the true challenge lies and where the really hard work begins.

Acknowledgements

The term “bloodless fMRI” was liberally borrowed from Alan Jasanoff’s excellent review article (Jasanoff, 2007).

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