The molecular basis for gray and white matter contrast in phase imaging
Introduction
The phase is an essential property of the signal-generating transverse magnetization in magnetic resonance imaging (MRI). However, in most conventional MRI studies, only the magnitude data representing tissue spin densities, relaxation properties, etc. are preserved, and the phase information is usually discarded. Exceptions do exist, e.g., in cardiac imaging where phase difference maps contain information about blood flow patterns or tissue motion. Such methods utilize the additionally accumulated phase of macroscopically mobile spins traveling inside a linear magnetic field gradient. However, little attention is paid to the intrinsic local frequency or phase differences in tissue, and most often, such frequency shifts are attributed to magnetic field inhomogeneity effects and removed.
Recently, increased interest in the image phase arose in order to enhance the image contrast, e.g., for susceptibility weighted imaging (SWI) (Abduljalil et al., 2003, Haacke et al., 2004). In addition, direct phase imaging at 1.5 T also demonstrated high contrast containing information different from magnitude images (Rauscher et al., 2005). Such phase contrast was greatly enhanced with the availability of ultra-high field. Phase images acquired at 7 T (Duyn et al., 2007) and in this study (Fig. 1) showed superior gray matter (GM) and white matter (WM) contrast with a contrast-to-noise ratio (CNR) gain of up to 10 compared to conventional magnitude images. It was tentatively suggested that the bulk tissue susceptibility accounts for the GM/WM phase contrast. Possible sources of susceptibility differences between GM and WM, such as blood deoxyhemoglobin (Duyn et al., 2007, Haacke et al., 2005), tissue myelin content (Annese et al., 2004, Duyn et al., 2007, O'Brien and Sampson, 1965), and tissue iron content (Bizzi et al., 1990, Drayer et al., 1986, Duyn et al., 2007, Haacke et al., 2005, Morris et al., 1992, Ogg et al., 1999, Schenck, 2003, Schenck and Zimmerman, 2004, Zhou et al., 2001) have been discussed. However, none of those factors can fully explain the observed in vivo phase difference between GM and WM. For example, the maximum estimated frequency shift from blood deoxyhemoglobin is around 2 Hz (Duyn et al., 2007) and is much smaller than the observed 6-Hz in vivo GM/WM phase separation. Therefore, either a detailed model integrating all potential sources of susceptibility contrast is needed to verify that susceptibility alone can explain the observed data or an alternate contrast generating mechanism is needed. In this work, we propose a novel source of frequency differences, which can plausibly explain the observed GM/WM phase contrast, namely the microscopic chemical exchange processes between free water and macromolecules. It is well known from magnetization transfer studies (Balaban and Ceckler, 1992, Bryant, 1996, Gochberg and Gore, 2007, Gochberg et al., 1998, Henkelman et al., 2001, Kennan et al., 1996, Koenig and Brown, 1993, Liepinsh and Otting, 1996, Sled et al., 2004, van Zijl et al., 2003) as well as from water–bovine serum albumin (BSA) measurements (Gallier et al., 1987, Hills et al., 1989, Olechnowicz et al., 1999) that the spin relaxation times T1 and T2 are closely related to the macromolecule concentration via exchange between bulk tissue water and the hydrophilic groups on the surface of macromolecules. Such exchange processes are typically fast (on the order of 10− 10 s) but can result in a small frequency shift of the water resonance due to the different chemical environment between free water and the hydrophilic groups on the macromolecule surface. Since the exchange is not rate limited (Koenig and Brown, 1993, Liepinsh and Otting, 1996), the frequency shift will mainly depend on the macromolecule concentration and the macromolecule type. Therefore, a phase difference between GM and WM is to be expected due to their different macromolecule content (Mader et al., 2002b, McLean and Barker, 2006, O'Brien and Sampson, 1965). Surprisingly, such a direct frequency effect has not yet been assessed in water–macromolecule exchange studies despite the overwhelming number of publications in this field. The lack of such a direct frequency measurement might be due to the fact that most exchange studies focus on the water relaxation properties. In addition, most MR scanners are not equipped with an internal frequency lock to differentiate any minute frequency shift that might arise from water–macromolecule exchange, and often the water resonance frequency was used as a reference (4.73 ppm).
In this study, we first determined the in vivo GM/WM phase contrast dependency on field strength and echo time (TE) to verify that the observed phase contrast is a pure frequency effect that could originate either from susceptibility contrast or from a microscopic water–macromolecule exchange model as proposed in this work. Subsequently, we performed direct water frequency shift measurements with different macromolecule concentrations in order to assess the interaction strength of water–macromolecule exchange and compared this to the in vivo situation. The water–macromolecule exchange as a major source of contribution to in vivo GM/WM phase contrast is discussed.
Section snippets
MRI data acquisition
Experiments were carried out on three scanners: Siemens Sonata (1.5 T), Trio (3 T) and MAGNETOM 7 T. Two volunteers were scanned at all field strengths. Informed written consent was provided prior to each scan following the guidelines of the institutional review board. Eight-channel head coils were used to acquire all images at different field strengths. A modified echo-shifted 3D FLASH sequence (Chung and Duerk, 1999) was used to acquire the phase maps. Image matrix size was 208 × 256 × 80 with
Results and discussion
The in vivo data presented are from a single subject although both subjects gave similar results. Data averaging was not performed in this study since the local field effects depend on tissue geometry and coregistration induced errors are difficult to avoid.
Acknowledgments
We thank Dr. Michael Mueller, Dr. Constantin von zur Muehlen, Dr. Dominik Paul, Dr. Ute Ludwig, Anja Kurutsch, Volker Brecht, and Irene Neuendorfer for their assistance with the experiments, and Dr. Valerij Kiselev for the helpful discussion. This study is supported by grant #13N9208 in the project INUMAC supported by the BMBF (Federal Ministry for Education and Research, Germany).
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