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The hippocampus is a highly scrutinized brain structure due to its entanglement in multiple neuropathologies and vulnerability to metabolic insults. This study aims to non-invasively assess the perfusion–mechanics relationship of the hippocampus in the healthy brain across magnetic resonance imaging sequences and magnetic field strengths. In total, 17 subjects (aged 22–35, 7 males/10 females) were scanned with magnetic resonance elastography and arterial spin labelling acquisitions at 3T and 7T in a baseline physiological state. No significant differences in perfusion or stiffness were observed across magnetic field strengths or acquisitions. The hippocampus had the highest vascularity within the deep grey matter, followed closely by the caudate nucleus and putamen. We discovered a positive perfusion–mechanics correlation in the hippocampus across both 3T and 7T groups, with a highly significant correlation overall (R= 0.71,p= 0.0019), which was not observed in the caudate nucleus, a similarly vascular region. Furthermore, we supported our hypothesis that increased perfusion in the hippocampus would lead to greater pulsatile displacement in a small cohort (n= 10). Given that the hippocampus is an exceptionally vulnerable structure, with perfusion deficits often seen in diseases related to learning and memory, our results suggest a unique mechanistic link between metabolic health and stiffness biomarkers in this key region for the first time. 

BackgroundThe prediction of rupture in intracranial aneurysms is challenging. Aneurysm growth has been identified as a strong risk factor for rupture and aneurysm wall motion is a potential biomarker for growth, but visualizing aneurysm wall motion using conventional imaging techniques is difficult. Computational fluid dynamic simulations have been used to identify hemodynamic risk factors of intracranial aneurysm instability, but often lack observable and quantifiable biomechanical correlates that can be directly measured in vivo. MethodsIn this retrospective case–control study of matched patients, cohorts with growing (n=6) and stable (n=6) unruptured intracranial aneurysms were selected from our institutional database of 4D Flow MRI scans. The amplified Flow algorithm was used to extract maps of wall motion for each aneurysm. Hemodynamics within the aneurysm dome were calculated using established computational fluid dynamic methods, and hemodynamic variables were evaluated against wall motion for stable and growing aneurysms. ResultsSeveral hemodynamic variables were found to be both significant predictors of aneurysm growth and highly correlated with aneurysm wall motion. The hemodynamic variable most correlated with both the maximum value of aneurysm wall motion and spatial variance of aneurysm wall motion, the time coefficient of variance of the directional wall shear stress gradient (representing changing directions of wall shear stress), was also the best hemodynamic predictor of aneurysm growth. ConclusionsSpatial variance of wall motion and hemodynamic variables are increased in growing aneurysms, and the fluctuations in the directional wall shear stress correlate directly with wall motion, indicating that heterogeneous wall motion and hemodynamics are interrelated and play a critical role in aneurysm instability. 

Understanding the pulsing dynamics of tissue and fluids in the intracranial environment is an evolving research theme aimed at gaining new insights into brain physiology and disease progression. This article provides an overview of related research in magnetic resonance imaging, ultrasound medical diagnostics and mathematical modelling of biological tissues and fluids. It highlights recent developments, illustrates current research goals and emphasizes the importance of collaboration between these fields. 

Abstract Magnetic resonance elastography (MRE) is a non-invasive method for determining the mechanical response of tissues using applied harmonic deformation and motion-sensitive MRI. MRE studies of the human brain are typically performed at conventional field strengths, with a few attempts at the ultra-high field strength, 7T, reporting increased spatial resolution with partial brain coverage. Achieving high-resolution human brain scans using 7T MRE presents unique challenges of decreased octahedral shear strain-based signal-to-noise ratio (OSS-SNR) and lower shear wave motion sensitivity. In this study, we establish high resolution MRE at 7T with a custom 2D multi-slice single-shot spin-echo echo-planar imaging sequence, using the Gadgetron advanced image reconstruction framework, applying Marchenko–Pastur Principal component analysis denoising, and using nonlinear viscoelastic inversion. These techniques allowed us to calculate the viscoelastic properties of the whole human brain at 1.1 mm isotropic imaging resolution with high OSS-SNR and repeatability. Using phantom models and 7T MRE data of eighteen healthy volunteers, we demonstrate the robustness and accuracy of our method at high-resolution while quantifying the feasible tradeoff between resolution, OSS-SNR, and scan time. Using these post-processing techniques, we significantly increased OSS-SNR at 1.1 mm resolution with whole-brain coverage by approximately 4-fold and generated elastograms with high anatomical detail. Performing high-resolution MRE at 7T on the human brain can provide information on different substructures within brain tissue based on their mechanical properties, which can then be used to diagnose pathologies (e.g. Alzheimer’s disease), indicate disease progression, or better investigate neurodegeneration effects or other relevant brain disorders,in vivo.