The MRE inverse problem for the elastic shear modulus

Magnetic resonance elastography (MRE) is a powerful technique for noninvasive determination of the biomechanical properties of tissue, with important applications in disease diagnosis. A typical experimental scenario is to induce waves in the tissue by time-harmonic external mechanical oscillation and then measure the tissue's displacement at fixed spatial positions 8 times during a complete time-period, extracting the dominant frequency signal from the discrete Fourier transform in time. Accurate reconstruction of the tissue's elastic moduli from MRE data is a challenging inverse problem, and we derive and analyze two new methods which address different aspects. The first of these concerns the time signal: using only the dominant frequency component loses information for noisy data and typically gives a complex value for the (real) shear modulus, which is then hard to interpret. Our new reconstruction method is based on the Fourier time-interpolant of the displacement: it uses all the measured information and automatically gives a real value of shear modulus up to rounding error. This derivation is for homogeneous materials, and our second new method (stacked frequency wave inversion, SFWI) concerns the inhomogeneous shear modulus in the time-harmonic case. The underlying problem is ill-conditioned because the coefficient of the shear modulus in the governing equations can be zero or small, and the SFWI approach overcomes this by combining approximations at different frequencies into a single overdetermined matrix--vector equation. Careful numerical tests confirm that both these new algorithms perform well

Magnetic resonance elastography (MRE) of the human brain: technique, findings and clinical applications

Neurological disorders are one of the most important public health concerns in developed countries. Established brain imaging techniques such as magnetic resonance imaging (MRI) and x-ray computerised tomography (CT) have been essential in the identification and diagnosis of a wide range of disorders, although usually are insufficient in sensitivity for detecting subtle pathological alterations to the brain prior to the onset of clinical symptoms—at a time when prognosis for treatment is more favourable. The mechanical properties of biological tissue provide information related to the strength and integrity of the cellular microstructure. In recent years, mechanical properties of the brain have been visualised and measured non-invasively with magnetic resonance elastography (MRE), a particularly sensitive medical imaging technique that may increase the potential for early diagnosis. This review begins with an introduction to the various methods used for the acquisition and analysis of MRE data. A systematic literature search is then conducted to identify studies that have specifically utilised MRE to investigate the human brain. Through the conversion of MRE-derived measurements to shear stiffness (kPa) and, where possible, the loss tangent (rad), a summary of results for global brain tissue and grey and white matter across studies is provided for healthy participants, as potential baseline values to be used in future clinical investigations. In addition, the extent to which MRE has revealed significant alterations to the brain in patients with neurological disorders is assessed and discussed in terms of known pathophysiology. The review concludes by predicting the trends for future MRE research and applications in neuroscience

Heterogeneous multifrequency direct inversion (HMDI) for magnetic resonance elastography with application to a clinical brain exam

A new viscoelastic wave inversion method for MRE, called Heterogeneous Multifrequency Direct Inversion (HMDI), was developed which accommodates heterogeneous elasticity within a direct inversion (DI) by incorporating first-order gradients and combining results from a narrow band of multiple frequencies. The method is compared with a Helmholtz-type DI, Multifrequency Dual Elasto-Visco inversion (MDEV), both on ground-truth Finite Element Method simulations at varied noise levels and a prospective in vivo brain cohort of 48 subjects ages 18–65. In simulated data, MDEV recovered background material within 5% and HMDI within 1% of prescribed up to SNR of 20 dB. In vivo HMDI and MDEV were then combined with segmentation from SPM to create a fully automated “brain palpation” exam for both whole brain (WB), and brain white matter (WM), measuring two parameters, the complex modulus magnitude |G*| , which measures tissue “stiffness”, and the slope of |G*| values across frequencies, a measure of viscous dispersion. |G*| values for MDEV and HMDI were comparable to the literature (for a 3-frequency set centered at 50 Hz, WB means were 2.17 and 2.15 kPa respectively, and WM means were 2.47 and 2.49 kPa respectively). Both methods showed moderate correlation to age in both WB and WM, for both |G*| and |G*| slope, with Pearson’s r ≥ 0.4 in the most sensitive frequency sets. In comparison to MDEV, HMDI showed better preservation of recovered target shapes, more noise-robustness, and stabler recovery values in regions with rapid property change, however summary statistics for both methods were quite similar. By eliminating homogeneity assumptions within a fast, fully automatic, regularization-free direct inversion, HMDI appears to be a worthwhile addition to the MRE image reconstruction repertoire. In addition to supporting the literature showing decrease in brain viscoelasticity with age, our work supports a wide range of inter-individual variation in brain MRE results

Bionovelty and ecological restoration

Anthropogenic activity has irreparably altered the ecological fabric of Earth. The emergence of ecological novelty from diverse drivers of change is an increasingly challenging dimension of ecosystem restoration. At the same time, the restorationist's tool kit continues to grow, including a variety of powerful and increasingly prevalent technologies. Thus, ecosystem restoration finds itself at the center of intersecting challenges. How should we respond to increasingly common emergence of environmental system states with little or no historical precedent, whilst considering the appropriate deployment of potentially consequential and largely untested interventions that may give rise to organisms, system states, and/or processes that are likewise without historical precedent? We use the term bionovelty to encapsulate these intersecting themes and examine the implications of bionovelty for ecological restoration