Characterization of Structural Dynamics of the Human Head Using Magnetic Resonance Elastography

In traumatic brain injury (TBI), the skull-brain interface, composed of three meningeal layers: the dura mater, arachnoid mater, and pia mater, along with cerebrospinal fluid (CSF) between the layers, plays a vital role in transmitting motion from the skull to brain tissue. Magnetic resonance elastography (MRE) is a noninvasive imaging modality capable of providing in vivo estimates of tissue motion and material properties. The objective of this work is to augment human and phantom MRE studies to better characterize the mechanical contributions of the skull-brain interface to improve the parameterization and validation of computational models of TBI. Three specific aims were to: 1) relate 3D skull kinematics estimated from tri-axial accelerometers to brain tissue motion (rigid-body motion and deformation) estimated from MRE, 2) modify existing MRE data collection methods to capture simultaneous scalp and brain displacements, and 3) create cylindrical and cranial phantoms capable of simulating a CSF interface and dural membranes. Achievement of these aims has provided new quantitative understanding of the transmission of skull motion to the brain

Image-guided subject-specific modeling of glymphatic transport and amyloid deposition

The glymphatic system is a brain-wide system of perivascular networks that facilitate exchange of cerebrospinal fluid (CSF) and interstitial fluid (ISF) to remove waste products from the brain. A greater understanding of the mechanisms for glymphatic transport may provide insight into how amyloid beta (Aβ) and tau agglomerates, key biomarkers for Alzheimer's disease and other neurodegenerative diseases, accumulate and drive disease progression. In this study, we develop an image-guided computational model to describe glymphatic transport and Aβ deposition throughout the brain. Aβ transport and deposition are modeled using an advection–diffusion equation coupled with an irreversible amyloid accumulation (damage) model. We use immersed isogeometric analysis, stabilized using the streamline upwind Petrov–Galerkin (SUPG) method, where the transport model is constructed using parameters inferred from brain imaging data resulting in a subject-specific model that accounts for anatomical geometry and heterogeneous material properties. Both short-term (30-min) and long-term (12-month) 3D simulations of soluble amyloid transport within a mouse brain model were constructed from diffusion weighted magnetic resonance imaging (DW-MRI) data. In addition to matching short-term patterns of tracer deposition, we found that transport parameters such as CSF flow velocity play a large role in amyloid plaque deposition. The computational tools developed in this work will facilitate investigation of various hypotheses related to glymphatic transport and fundamentally advance our understanding of its role in neurodegeneration, which is crucial for the development of preventive and therapeutic interventions.</p

A Hyperfluorinated Hydrophilic Molecule for Aqueous 19F MRI Contrast Media

Fluorine-19 (19F) magnetic resonance imaging (MRI) has the potential for a wide range of in vivo applications but is limited by lack of flexibility in exogenous probe formulation. Most 19F MRI probes are composed of perfluorocarbons (PFCs) or perfluoropolyethers (PFPEs) with intrinsic properties which limit formulation options. Hydrophilic organofluorine molecules can provide more flexibility in formulation options. We report herein a hyperfluorinated hydrophilic organoflourine, ET1084, with ∼24 wt. % 19F content. It dissolves in water and aqueous buffers to give solutions with ≥8 M 19F. 19F MRI phantom studies at 9.4T employing a 10-minute multislice multiecho (MSME) scan sequence show a linear increase in signal-to-noise ratio (SNR) with increasing concentrations of the molecule and a detection limit of 5 mM. Preliminary cytotoxicity and genotoxicity assessments suggest it is safe at concentrations of up to 20 mM

Polymorphism and Second Harmonic Generation in a Novel Diamond-like Semiconductor: Li2MnSnS4

High-temperature, solid-state synthesis in the Li2MnSnS4 system led to the discovery of two new polymorphic compounds that were analyzed using single crystal X-ray diffraction. The α-polymorph crystallizes in Pna21 with the lithium cobalt (II) silicate, Li2CoSiO4, structure type, where Z=4, R1=0.0349 and wR2=0.0514 for all data. The β-polymorph possesses the wurtz-kesterite structure type, crystallizing in Pn with Z=2, R1=0.0423, and wR2=0.0901 for all data. Rietveld refinement of synchrotron X-ray powder diffraction was utilized to quantify the phase fractions of the polymorphs in the reaction products. The α/β-Li2MnSnS4 mixture exhibits an absorption edge of ∼2.6–3.0 eV, a wide region of optical transparency in the mid- to far-IR, and moderate SHG activity over the fundamental range of 1.1–2.1 μm. Calculations using density functional theory indicate that the ground state energies and electronic structures for α- and β-Li2MnSnS4, as well as the hypothetical polymorph, γ-Li2MnSnS4 with the wurtz-stannite structure type, are highly similar