Chemical exchange saturation transfer (CEST) is a technique to indirectly detect pools of exchangeable protons through the water signal. To increase its applicability to human studies, it is needed to develop sensitive pulse sequences for rapidly acquiring whole-organ images while adhering to stringent amplifier duty cycle limitations and SAR restrictions. In addition, the interfering effects of direct water saturation (DS) and conventional magnetization transfer contrast (MTC) complicate CEST quantification and need to be reduced as much as possible. It is shown that for protons exchanging with rates of less than 50–100 Hz, such as imaged in amide proton transfer (APT) experiments, these problems can be addressed by using a 3D steady state pulsed acquisition of limited B1 strength (~1 μT). Such an approach exploits the fact that the DS width, MTC magnitude, and SAR increase strongly with B1, while the size of the CEST effect for such protons depends minimally on B1. A short-TR (65 ms) steady state sequence consisting of a brief saturation pulse (25 ms) and a segmented EPI train allowed acquisition of a 3D whole-brain volume in approximately 11 s per saturation frequency, while remaining well within SAR and duty cycle limits. MTC was strongly reduced, but substantial saturation effects were found at frequencies upfield from water, which still confound the use of MT asymmetry analysis. Fortunately, the limited width of the DS signal could be exploited to fit it with a Lorentzian function allowing CEST quantification. APT effects ranged between 1.5 and 2.5% in selected white and gray matter regions. This power and time-efficient 3D pulsed CEST acquisition scheme should aid endogenous CEST quantification at both high and low field.

Recent animal studies at high field have shown that blood oxygen level-dependent (BOLD) contrast can be specific to the laminar vascular architecture of the cortex, by differences in its temporal dynamics in reference to cortical depth. In this study, we characterize the temporal dynamics of the hemodynamic response (HDR) across cortical depth in the human primary motor and visual cortex, at 7 T and using very short stimuli and with high spatial and temporal resolution. We find that the shape and temporal dynamics of the HDR changed in an orderly manner across cortical depth. Compared with the pial vasculature, HDRs in deeper gray matter are significantly faster in onset time (by B0.5 second) and peak time (B2 seconds), and are narrower (by B1 second) and with smaller amplitude, in line with the known vascular organization across cortical depth and the transit of deoxygenated blood through the vasculature. The width of the HDR in deeper gray matter was as short as 2.1 seconds, indicating that neurovascular coupling takes place at a shorter timescale than previously reported in the human brain. These findings open the possibility to probe layer-specific hemodynamics and neurovascular coupling mechanisms in human gray matter.

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The characterisation of the extravascular (EV) contribution to the blood oxygenation level-dependent (BOLD) effect is important for understanding the spatial specificity of BOLD contrast and for modelling approaches that aim to extract quantitative metabolic parameters from the BOLD signal. Using bipolar crusher gradients, total (b = 0 s/mm(2) ) and predominantly EV (b = 100 s/mm(2) ) gradient echo BOLD ΔR(2)* and signal changes (ΔS/S) in response to visual stimulation (flashing checkerboard; f = 8 Hz) were investigated sequentially (within < 3 h) at 1.5, 3.0 and 7.0 T in the same subgroup of healthy volunteers (n = 7) and at identical spatial resolutions (3.5 × 3.5 × 3.5 mm(3)). Total ΔR(2)* (z-score analysis) values were -0.61 ± 0.10 s(-1) (1.5 T), -0.74 ± 0.05 s(-1) (3.0 T) and -1.37 ± 0.12 s(-1) (7.0 T), whereas EV ΔR(2)* values were -0.28 ± 0.07 s(-1) (1.5 T), -0.52 ± 0.07 s(-1) (3.0 T) and -1.25 ± 0.11 s(-1) (7.0 T). Although EV ΔR(2)* increased linearly with field, as expected, it was found that EV ΔS/S increased less than linearly with field in a manner that varied with TE choice. Furthermore, unlike ΔR(2)*, total and EV ΔS/S did not converge at 7.0 T. These trends were similar whether a z-score analysis or occipital lobe-based region-of-interest approach was used for voxel selection. These findings suggest that calibrated BOLD approaches may benefit from an EV ΔR(2)* measurement as opposed to a ΔS/S measurement at a single TE.

Chemical exchange saturation transfer (CEST) exploits the chemical exchange of labile protons of an endogenous or exogenous compound with water to image the former indirectly through the water signal. Z-spectra of the brain have traditionally been analyzed for two most common saturation phenomena: downfield amide proton transfer (APT) and upfield nuclear Overhauser enhancement (NOE). However, a great body of brain metabolites, many of interest in neurology and oncology, contributes to the downfield saturation in Z-spectra. The extraction of these “hidden” metabolites from Z-spectra requires careful design of CEST sequences and data processing models, which is only possible by first obtaining CEST signatures of the brain metabolites possessing labile protons. In this work, we measured exchange rates of all major-for-CEST brain metabolites in the physiological pH range at 37 °C. Analysis of their contributions to Z-spectra revealed that regardless of the main magnetic field strength and pH, five main contributors, i.e. myo-inositol, creatine, phosphocreatine, glutamate, and mobile (poly)peptides, account for ca. 90% of downfield CEST effect. The fundamental CEST parameters presented in this study can be exploited in the design of novel CEST sequences and Z-spectra processing models, which will enable simultaneous and quantitative CEST imaging of multiple metabolites: multicolor CEST.

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Quantitative Magnetic Resonance Imaging (MRI) is based on a two-steps approach: estimation of the magnetic moments distribution inside the body, followed by a voxel-by-voxel quantification of the human tissue properties. This splitting simplifies the computations but poses several constraints on the measurement process, limiting its efficiency. Here, we perform quantitative MRI as a one step process; signal localization and parameter quantification are simultaneously obtained by the solution of a large scale nonlinear inversion problem based on first-principles. As a consequence, the constraints on the measurement process can be relaxed and acquisition schemes that are time efficient and widely available in clinical MRI scanners can be employed. We show that the nonlinear tomography approach is applicable to MRI and returns human tissue maps from very short experiments.

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