Background. Magnetic resonance elastography (MRE) is used to non-invasively estimate biomechanical tissue properties via the imaging of propagating mechanical shear waves. Several factors including mechanical transducer design, MRI sequence design and viscoelastic reconstruction influence data quality and hence the reliability of the derived biomechanical properties.Purpose. To design and characterize a novel mechanical MRE transducer concept based on a rotational eccentric mass, coined the gravitational transducer.Materials and methods. Table top measurements were performed using accelerometers to characterize the frequency response of the new transducer concept at different driving frequencies (f VIB ) and different rotating masses. These were compared to a commercially available pneumatically driven MRE transducer. MR data were acquired on a 3T scanner using a fractionally encoded gradient echo MRE sequence in three healthy volunteers. Acceleration and displacement spectra were plotted in units of g and mm, respectively, and visually compared, emphasizing the ratio between the peaks at f VIB and its 2nd harmonic, a known cause of error in the reconstruction of biomechanical properties as is explored in more detail in numerical simulations here. No formal statistical testing was performed in this proof-of-principle paper.Results. The new transducer concept shows-as expected from theory-a quadratic or linear increase of acceleration amplitude with increase in f VIB or mass, respectively. Furthermore, different versions of the transducer show markedly lower 2nd harmonic-to-f VIB ratios compared to the commercially available pneumatically driven transducer. Displacement was constant over a range of f VIB , in accordance with theory. Phantom and in vivo data show low nonlinearity and excellent data quality.Conclusion. The table top measurements are in concordance with the theory behind a transducer based on a rotational eccentric mass. The resulting constant displacement amplitude irrespective of f VIB and low 2nd harmonic-to-f VIB ratio result in low nonlinearity and high data fidelity in both phantom and in vivo examples. PAPER Original content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence.

Assessment of tissue stiffness is desirable for clinicians and researchers, as it is well established that pathophysiological mechanisms often alter the structural properties of tissue. Magnetic resonance elastography (MRE) provides an avenue for measuring tissue stiffness and has a long history of clinical application, including staging liver fibrosis and stratifying breast cancer malignancy. A vital component of MRE consists of the reconstruction algorithms used to derive stiffness from wave‐motion images by solving inverse problems. A large range of reconstruction methods have been presented in the literature, with differing computational expense, required user input, underlying physical assumptions, and techniques for numerical evaluation. These differences, in turn, have led to varying accuracy, robustness, and ease of use. While most reconstruction techniques have been validated against in silico or in vitro phantoms, performance with real data is often more challenging, stressing the robustness and assumptions of these algorithms. This article reviews many current MRE reconstruction methods and discusses the aforementioned differences. The material assumptions underlying the methods are developed and various approaches for noise reduction, regularization, and numerical discretization are discussed. Reconstruction methods are categorized by inversion type, underlying assumptions, and their use in human and animal studies. Future directions, such as alternative material assumptions, are also discussed.

As disease often alters structural and functional properties in tissue, the noninvasive measurement of material stiffness in vivo is desirable. Magnetic resonance elastography provides an approach to in vivo tissue characterization, using images of wave motion in tissue and biomechanical principles to reconstruct and quantify stiffness. Successful clinical translation of this technology requires stiffness reconstruction algorithms that are robust, easy to manage, and fast. In this paper, a reconstruction method is presented which addresses these issues by using a local compact divergence-free reconstruction kernel coupled with non-physical constraint elimination and inverse residual weighting to reliably reconstruct stiffness. The proposed technique is compared with local curl reconstructions and global stiffness-pressure reconstructions across two ground-truth phantoms as well as in vivo data sets. Sensitivity analysis is also performed, assessing the variability of reconstruction results and robustness to noise. It is shown that the proposed method can be robustly applied across data sets, is less sensitive to noise, attains comparable (or improved) accuracy, provides better correlation to anatomical features, and can be completed in short timescales.

Many cardiovascular diseases lead to local increases in relative pressure, reflecting the higher costs of driving blood flow. The utility of this biomarker for stratifying the severity of disease has thus driven the development of methods to measure these relative pressures. While intravascular catheterisation remains the most direct measure, its invasiveness limits clinical application in many instances. Non-invasive Doppler ultrasound estimates have partially addressed this gap; however only provide relative pressure estimates for a range of constricted cardiovascular conditions. Here we introduce a non-invasive method that enables arbitrary interrogation of relative pressures throughout an imaged vascular structure, leveraging modern phase contrast magnetic resonance imaging, the virtual work-energy equations, and a virtual field to provide robust and accurate estimates. The versatility and accuracy of the method is verified in a set of complex patient-specific cardiovascular models, where relative pressures into previously inaccessible flow regions are assessed. The method is further validated within a cohort of congenital heart disease patients, providing a novel tool for probing relative pressures in-vivo.