Hyperpolarized Xenon for NMR and MRI Applications

Nuclear magnetic resonance (NMR) spectroscopy and imaging (MRI) suffer from intrinsic low sensitivity because even strong external magnetic fields of ~10 T generate only a small detectable net-magnetization of the sample at room temperature ¹. Hence, most NMR and MRI applications rely on the detection of molecules at relative high concentration (e.g., water for imaging of biological tissue) or require excessive acquisition times. This limits our ability to exploit the very useful molecular specificity of NMR signals for many biochemical and medical applications. However, novel approaches have emerged in the past few years: Manipulation of the detected spin species prior to detection inside the NMR/MRI magnet can dramatically increase the magnetization and therefore allows detection of molecules at much lower concentration ².Here, we present a method for polarization of a xenon gas mixture (2-5% Xe, 10% N₂, He balance) in a compact setup with a ca. 16000-fold signal enhancement. Modern line-narrowed diode lasers allow efficient polarization ⁷ and immediate use of gas mixture even if the noble gas is not separated from the other components. The SEOP apparatus is explained and determination of the achieved spin polarization is demonstrated for performance control of the method.The hyperpolarized gas can be used for void space imaging, including gas flow imaging or diffusion studies at the interfaces with other materials ^8,9. Moreover, the Xe NMR signal is extremely sensitive to its molecular environment ⁶. This enables the option to use it as an NMR/MRI contrast agent when dissolved in aqueous solution with functionalized molecular hosts that temporarily trap the gas ^10,11. Direct detection and high-sensitivity indirect detection of such constructs is demonstrated in both spectroscopic and imaging mode.     

Depolarization Laplace Transform Analysis of Exchangeable Hyperpolarized 129Xe for Detecting Ordering Phases and Cholesterol Content of Biomembrane Models

We present a highly sensitive nuclear-magnetic resonance technique to study membrane dynamics that combines the temporary encapsulation of spin-hyperpolarized xenon (¹²⁹Xe) atoms in cryptophane-A-monoacid (CrA_ma) and their indirect detection through chemical exchange saturation transfer. Radiofrequency-labeled Xe@CrA_ma complexes exhibit characteristic differences in chemical exchange saturation transfer-driven depolarization when interacting with binary membrane models composed of different molecular ratios of DPPC (1,2-dipalmitoyl-sn-glycero-3-phosphocholine) and POPC (1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine). The method is also applied to mixtures of cholesterol and POPC. The existence of domains that fluctuate in cluster size in DPPC/POPC models at a high (75–98%) DPPC content induces up to a fivefold increase in spin depolarization time τ at 297 K. In POPC/cholesterol model membranes, the parameter τ depends linearly on the cholesterol content at 310 K and allows us to determine the cholesterol content with an accuracy of at least 5%.     

Evidence for Functional Groupings of Vibrissae across the Rodent Mystacial Pad

During natural exploration, rats exhibit two particularly conspicuous vibrissal-mediated behaviors: they follow along walls, and “dab” their snouts on the ground at frequencies related to the whisking cycle. In general, the walls and ground may be located at any distance from, and at any orientation relative to, the rat’s head, which raises the question of how the rat might determine the position and orientation of these surfaces. Previous studies have compellingly demonstrated that rats can accurately determine the horizontal angle at which a vibrissa first touches an object, and we therefore asked whether this parameter could provide the rat with information about the pitch, distance, and yaw of a surface relative to its head. We used a three-dimensional model of the whisker array to construct mappings between the horizontal angle of contact of each vibrissa and every possible (pitch, distance, and yaw) configuration of the head relative to a flat surface. The mappings revealed striking differences in the patterns of contact for vibrissae in different regions of the array. The exterior (A, D, E) rows provide information about the relative pitch of the surface regardless of distance. The interior (B, C) rows provide distance cues regardless of head pitch. Yaw is linearly correlated with the difference between the number of right and left whiskers touching the surface. Compared to the long reaches that whiskers can make to the side and below the rat, the reachable distance in front of the rat’s nose is relatively small. We confirmed key predictions of these functional groupings in a behavioral experiment that monitored the contact patterns that the vibrissae made with a flat vertical surface. These results suggest that vibrissae in different regions of the array are not interchangeable sensors, but rather functionally grouped to acquire particular types of information about the environment.     

A New Functional MRI Approach for Investigating Modulations of Brain Oxygen Metabolism

Functional MRI (fMRI) using the blood oxygenation level dependent (BOLD) signal is a common technique in the study of brain function. The BOLD signal is sensitive to the complex interaction of physiological changes including cerebral blood flow (CBF), cerebral blood volume (CBV), and cerebral oxygen metabolism (CMRO₂). A primary goal of quantitative fMRI methods is to combine BOLD imaging with other measurements (such as CBF measured with arterial spin labeling) to derive information about CMRO₂. This requires an accurate mathematical model to relate the BOLD signal to the physiological and hemodynamic changes; the most commonly used of these is the Davis model. Here, we propose a new nonlinear model that is straightforward and shows heuristic value in clearly relating the BOLD signal to blood flow, blood volume and the blood flow-oxygen metabolism coupling ratio. The model was tested for accuracy against a more detailed model adapted for magnetic fields of 1.5, 3 and 7T. The mathematical form of the heuristic model suggests a new ratio method for comparing combined BOLD and CBF data from two different stimulus responses to determine whether CBF and CMRO₂ coupling differs. The method does not require a calibration experiment or knowledge of parameter values as long as the exponential parameter describing the CBF-CBV relationship remains constant between stimuli. The method was found to work well for 1.5 and 3T but is prone to systematic error at 7T. If more specific information regarding changes in CMRO₂ is required, then with accuracy similar to that of the Davis model, the heuristic model can be applied to calibrated BOLD data at 1.5T, 3T and 7T. Both models work well over a reasonable range of blood flow and oxygen metabolism changes but are less accurate when applied to a simulated caffeine experiment in which CBF decreases and CMRO₂ increases.     

An Approach for Identifying Brainstem Dopaminergic Pathways Using Resting State Functional MRI

Here, we present an approach for identifying brainstem dopaminergic pathways using resting state functional MRI. In a group of healthy individuals, we searched for significant functional connectivity between dopamine-rich midbrain areas (substantia nigra; ventral tegmental area) and a striatal region (caudate) that was modulated by both a pharmacological challenge (the administration of the dopaminergic agonist bromocriptine) and a dopamine-sensitive cognitive trait (an individual’s working memory capacity). A significant inverted-U shaped connectivity pattern was found in a subset of midbrain-striatal connections, demonstrating that resting state fMRI data is sufficiently powerful to identify brainstem neuromodulatory brain networks.     

An Automated,Adaptive Framework for Optimizing Preprocessing Pipelines in Task-Based Functional MRI

BOLD fMRI is sensitive to blood-oxygenation changes correlated with brain function; however, it is limited by relatively weak signal and significant noise confounds. Many preprocessing algorithms have been developed to control noise and improve signal detection in fMRI. Although the chosen set of preprocessing and analysis steps (the “pipeline”) significantly affects signal detection, pipelines are rarely quantitatively validated in the neuroimaging literature, due to complex preprocessing interactions. This paper outlines and validates an adaptive resampling framework for evaluating and optimizing preprocessing choices by optimizing data-driven metrics of task prediction and spatial reproducibility. Compared to standard “fixed” preprocessing pipelines, this optimization approach significantly improves independent validation measures of within-subject test-retest, and between-subject activation overlap, and behavioural prediction accuracy. We demonstrate that preprocessing choices function as implicit model regularizers, and that improvements due to pipeline optimization generalize across a range of simple to complex experimental tasks and analysis models. Results are shown for brief scanning sessions (<3 minutes each), demonstrating that with pipeline optimization, it is possible to obtain reliable results and brain-behaviour correlations in relatively small datasets.     

Validating Serum S100B and Neuron-Specific Enolase as Biomarkers for the Human Brain - A Combined Serum, Gene Expression and MRI Study

Introduction

Former studies have investigated the potential of serum biomarkers for diseases affecting the human brain. In particular the glial protein S100B, a neuro- and gliotrophin inducing plasticity, seems to be involved in the pathogenesis and treatment of psychiatric diseases such as major depression and schizophrenia. Neuron-specific enolase (NSE) is a specific serum marker for neuronal damage. However, the specificity of these biomarkers for cell type and brain region has not been investigated in vivo until now.

Methods

We acquired two magnetic resonance imaging parameters sensitive to changes in gray and white matter (T₁-weighted/diffusion tensor imaging) and obtained serum S100B and NSE levels of 41 healthy subjects. Additionally, we analyzed whole brain gene expressions of S100B in another male cohort of three subjects using the Allen Brain Atlas. Furthermore, a female post mortal brain was investigated using double immunofluorescence labelling with oligodendrocyte markers.

Results

We show that S100B is specifically related to white matter structures, namely the corpus callosum, anterior forceps and superior longitudinal fasciculus in female subjects. This effect was observed in fractional anisotropy and radial diffusivity – the latest an indicator of myelin changes. Histological data confirmed a co-localization of S100B with oligodendrocyte markers in the human corpus callosum. S100B was most abundantly expressed in the corpus callosum according to the whole genome Allen Human Brain Atlas. In addition, NSE was related to gray matter structures, namely the amygdala. This effect was detected across sexes.

Conclusion

Our data demonstrates a very high S100B expression in white matter tracts, in particular in human corpus callosum. Our study is the first in vivo study validating the specificity of the glial marker S100B for the human brain, and supporting the assumption that radial diffusivity represents a myelin marker. Our results open a new perspective for future studies investigating major neuropsychiatric disorders.