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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. 

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. 

Objective: To establish the sensitivity of magnetic resonance elastography (MRE) to active muscle contraction in multiple muscles of the forearm. Methods: We combined MRE of forearm muscles with an MRI-compatible device, the MREbot, to simultaneously measure the mechanical properties of tissues in the forearm and the torque applied by the wrist joint during isometric tasks. We measured shear wave speed of thirteen forearm muscles via MRE in a series of contractile states and wrist postures and fit these outputs to a force estimation algorithm based on a musculoskeletal model. Results: Shear wave speed changed significantly upon several factors, including whether the muscle was recruited as an agonist or antagonist (p = 0.0019), torque amplitude (p ≤ 0.0001), and wrist posture (p = 0.0002). Shear wave speed increased significantly during both agonist (p ≤ 0.0001) and antagonist (p = 0.0448) contraction. Additionally, there was a greater increase in shear wave speed at greater levels of loading. The variations due to these factors indicate the sensitivity to functional loading of muscle. Under the assumption of a quadratic relationship between shear wave speed and muscle force, MRE measurements accounted for an average of 70% of the variance in the measured joint torque. Conclusion: This study shows the ability of MM-MRE to capture variations in individual muscle shear wave speed due to muscle activation and presents a method to estimate individual muscle force through MM-MRE derived measurements of shear wave speed. Significance: MM-MRE could be used to establish normal and abnormal muscle co-contraction patterns in muscles of the forearm controlling hand and wrist function.