Magnetic Resonance Elastography Reconstruction for Anisotropic Tissues.

Elastography has become widely used clinically for characterising changes in soft tissue mechanics that are associated with altered tissue structure and composition. However, some soft tissues, such as muscle, are not isotropic as is assumed in clinical elastography implementations. This limits the ability of these methods to capture changes in anisotropic tissues associated with disease. The objective of this study was to develop and validate a novel elastography reconstruction technique suitable for estimating the linear viscoelastic mechanical properties of transversely isotropic soft tissues. We derived a divergence-free formulation of the governing equations for acoustic wave propagation through a linearly transversely isotropic viscoelastic material, and transformed this into a weak form. This was then implemented into a finite element framework, enabling the analysis of wave input data and tissue structural fibre orientations, in this case based on diffusion tensor imaging. To validate the material constants obtained with this method, numerous in silico phantom experiments were run which encompassed a range of variations in wave input directions, material properties, fibre structure and noise. The method was also tested on ex vivo muscle and in vivo human volunteer calf muscles, and compared with a previous curl-based inversion method. The new method robustly extracted the transversely isotropic shear moduli (G⊥', G∥', G″) from the in silico phantom tests with minimal bias, including in the presence of experimentally realistic levels of noise in either fibre orientation or wave data. This new method performed better than the previous method in the presence of noise. Anisotropy estimates from the ex vivo muscle phantom agreed well with rheological tests. In vivo experiments on human calf muscles were able to detect increases in muscle shear moduli with passive muscle stretch. This new reconstruction method can be applied to quantify tissue mechanical properties of anisotropic soft tissues, such as muscle, in health and disease.

Impact of axisymmetric deformation on MR elastography of a nonlinear tissue-mimicking material and implications in peri-tumour stiffness quantification.

Solid tumour growth is often associated with the accumulation of mechanical stresses acting on the surrounding host tissue. Due to tissue nonlinearity, the shear modulus of the peri-tumoural region inherits a signature from the tumour expansion which depends on multiple factors, including the soft tissue constitutive behaviour and its stress/strain state. Shear waves used in MR-elastography (MRE) sense the apparent change in shear modulus along their propagation direction, thereby probing the anisotropic stiffness field around the tumour. We developed an analytical framework for a heterogeneous shear modulus distribution using a thick-shelled sphere approximation of the tumour and soft tissue ensemble. A hyperelastic material (plastisol) was identified to validate the proposed theory in a phantom setting. A balloon-catheter connected to a pressure sensor was used to replicate the stress generated from tumour pressure and growth while MRE data were acquired. The shear modulus anisotropy retrieved from the reconstructed elastography data confirmed the analytically predicted patterns at various levels of inflation. An alternative measure, combining the generated deformation and the local wave direction and independent of the reconstruction strategy, was also proposed to correlate the analytical findings with the stretch probed by the waves. Overall, this work demonstrates that MRE in combination with non-linear mechanics, is able to identify the apparent shear modulus variation arising from the strain generated by a growth within tissue, such as an idealised model of tumour. Investigation in real tissue represents the next step to further investigate the implications of endogenous forces in tissue characterisation through MRE.

Non-invasive estimation of relative pressure for intracardiac flows using virtual work-energy.

Intracardiac blood flow is driven by differences in relative pressure, and assessing these is critical in understanding cardiac disease. Non-invasive image-based methods exist to assess relative pressure, however, the complex flow and dynamically moving fluid domain of the intracardiac space limits assessment. Recently, we proposed a method, νWERP, utilizing an auxiliary virtual field to probe relative pressure through complex, and previously inaccessible flow domains. Here we present an extension of νWERP for intracardiac flow assessments, solving the virtual field over sub-domains to effectively handle the dynamically shifting flow domain. The extended νWERP is validated in an in-silico benchmark problem, as well as in a patient-specific simulation model of the left heart, proving accurate over ranges of realistic image resolutions and noise levels, as well as superior to alternative approaches. Lastly, the extended νWERP is applied on clinically acquired 4D Flow MRI data, exhibiting realistic ventricular relative pressure patterns, as well as indicating signs of diastolic dysfunction in an exemplifying patient case. Summarized, the extended νWERP approach represents a directly applicable implementation for intracardiac flow assessments.

Towards noninvasive estimation of tumour pressure by utilising MR elastography and nonlinear biomechanical models: a simulation and phantom study.

The solid and fluid pressures of tumours are often elevated relative to surrounding tissue. This increased pressure is known to correlate with decreased treatment efficacy and potentially with tumour aggressiveness and therefore, accurate noninvasive estimates of tumour pressure would be of great value. We present a proof-of-concept method to infer the total tumour pressure, that is the sum of the fluid and solid parts, by examining stiffness in the peritumoural tissue with MR elastography and utilising nonlinear biomechanical models. The pressure from the tumour deforms the surrounding tissue leading to changes in stiffness. Understanding and accounting for these biases in stiffness has the potential to enable estimation of total tumour pressure. Simulations are used to validate the method with varying pressure levels, tumour shape, tumour size, and noise levels. Results show excellent matching in low noise cases and still correlate well with higher noise. Percent error remains near or below 10% for higher pressures in all noise level cases. Reconstructed pressures were also calculated from experiments with a catheter balloon embedded in a plastisol phantom at multiple inflation levels. Here the reconstructed pressures generally match the increases in pressure measured during the experiments. Percent errors between average reconstructed and measured pressures at four inflation states are 17.9%, 52%, 23.2%, and 0.9%. Future work will apply this method to in vivo data, potentially providing an important biomarker for cancer diagnosis and treatment.

Non-invasive estimation of relative pressure in turbulent flow using virtual work-energy.

Vascular pressure differences are established risk markers for a number of cardiovascular diseases. Relative pressures are, however, often driven by turbulence-induced flow fluctuations, where conventional non-invasive methods may yield inaccurate results. Recently, we proposed a novel method for non-turbulent flows, νWERP, utilizing the concept of virtual work-energy to accurately probe relative pressure through complex branching vasculature. Here, we present an extension of this approach for turbulent flows: νWERP-t. We present a theoretical method derivation based on flow covariance, quantifying the impact of flow fluctuations on relative pressure. νWERP-t is tested on a set of in-vitro stenotic flow phantoms with data acquired by 4D flow MRI with six-directional flow encoding, as well as on a patient-specific in-silico model of an acute aortic dissection. Over all tests νWERP-t shows improved accuracy over alternative energy-based approaches, with excellent recovery of estimated relative pressures. In particular, the use of a guaranteed divergence-free virtual field improves accuracy in cases where turbulent flows skew the apparent divergence of the acquired field. With the original νWERP allowing for assessment of relative pressure into previously inaccessible vasculatures, the extended νWERP-t further enlarges the method's clinical scope, underlining its potential as a novel tool for assessing relative pressure in-vivo.

Imaging localized neuronal activity at fast time scales through biomechanics.

Mapping neuronal activity noninvasively is a key requirement for in vivo human neuroscience. Traditional functional magnetic resonance (MR) imaging, with a temporal response of seconds, cannot measure high-level cognitive processes evolving in tens of milliseconds. To advance neuroscience, imaging of fast neuronal processes is required. Here, we show in vivo imaging of fast neuronal processes at 100-ms time scales by quantifying brain biomechanics noninvasively with MR elastography. We show brain stiffness changes of ~10% in response to repetitive electric stimulation of a mouse hind paw over two orders of frequency from 0.1 to 10 Hz. We demonstrate in mice that regional patterns of stiffness modulation are synchronous with stimulus switching and evolve with frequency. For very fast stimuli (100 ms), mechanical changes are mainly located in the thalamus, the relay location for afferent cortical input. Our results demonstrate a new methodology for noninvasively tracking brain functional activity at high speed.

Estimation of Cardiovascular Relative Pressure Using Virtual Work-Energy.

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.

Magnetic resonance elastography in nonlinear viscoelastic materials under load.

Characterisation of soft tissue mechanical properties is a topic of increasing interest in translational and clinical research. Magnetic resonance elastography (MRE) has been used in this context to assess the mechanical properties of tissues in vivo noninvasively. Typically, these analyses rely on linear viscoelastic wave equations to assess material properties from measured wave dynamics. However, deformations that occur in some tissues (e.g. liver during respiration, heart during the cardiac cycle, or external compression during a breast exam) can yield loading bias, complicating the interpretation of tissue stiffness from MRE measurements. In this paper, it is shown how combined knowledge of a material's rheology and loading state can be used to eliminate loading bias and enable interpretation of intrinsic (unloaded) stiffness properties. Equations are derived utilising perturbation theory and Cauchy's equations of motion to demonstrate the impact of loading state on periodic steady-state wave behaviour in nonlinear viscoelastic materials. These equations demonstrate how loading bias yields apparent material stiffening, softening and anisotropy. MRE sensitivity to deformation is demonstrated in an experimental phantom, showing a loading bias of up to twofold. From an unbiased stiffness of [Formula: see text] Pa in unloaded state, the biased stiffness increases to 9767.5 [Formula: see text]1949.9 Pa under a load of [Formula: see text] 34% uniaxial compression. Integrating knowledge of phantom loading and rheology into a novel MRE reconstruction, it is shown that it is possible to characterise intrinsic material characteristics, eliminating the loading bias from MRE data. The framework introduced and demonstrated in phantoms illustrates a pathway that can be translated and applied to MRE in complex deforming tissues. This would contribute to a better assessment of material properties in soft tissues employing elastography.

A novel magnetic resonance elastography transducer concept based on a rotational eccentric mass: preliminary experiences with the gravitational transducer.

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.

An experimentally-calibrated damage mechanics model for stone fracture in shock wave lithotripsy.

A damage model suggested by the Tuler-Butcher concept of dynamic accumulation of microscopic defects is obtained from experimental data on microcrack formation in synthetic kidney stones. Experimental data on appearance of microcracks is extracted from micro-computed tomography images of BegoStone simulants obtained after subjecting the stone to successive pulses produced by an electromagnetic shock-wave lithotripter source. Image processing of the data is used to infer statistical distributions of crack length and width in representative transversal cross-sections of a cylindrical stone. A high-resolution finite volume computational model, capable of accurately modeling internal reflections due to local changes in material properties produced by material damage is used to simulate the accumulation of damage due to successive shocks. Comparison of statistical distributions of microcrack formation in computation and experiment allows calibration of the damage model. The model is subsequently used to compute fracture of a different aspect-ratio cylindrical stone predicting concurrent formation of two main fracture areas as observed experimentally.

Stiffness reconstruction methods for MR elastography.

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.

Robust MR elastography stiffness quantification using a localized divergence free finite element reconstruction.

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.

Improving the lens design and performance of a contemporary electromagnetic shock wave lithotripter.

The efficiency of shock wave lithotripsy (SWL), a noninvasive first-line therapy for millions of nephrolithiasis patients, has not improved substantially in the past two decades, especially in regard to stone clearance. Here, we report a new acoustic lens design for a contemporary electromagnetic (EM) shock wave lithotripter, based on recently acquired knowledge of the key lithotripter field characteristics that correlate with efficient and safe SWL. The new lens design addresses concomitantly three fundamental drawbacks in EM lithotripters, namely, narrow focal width, nonidealized pulse profile, and significant misalignment in acoustic focus and cavitation activities with the target stone at high output settings. Key design features and performance of the new lens were evaluated using model calculations and experimental measurements against the original lens under comparable acoustic pulse energy (E+) of 40 mJ. The -6-dB focal width of the new lens was enhanced from 7.4 to 11 mm at this energy level, and peak pressure (41 MPa) and maximum cavitation activity were both realigned to be within 5 mm of the lithotripter focus. Stone comminution produced by the new lens was either statistically improved or similar to that of the original lens under various in vitro test conditions and was significantly improved in vivo in a swine model (89% vs. 54%, P = 0.01), and tissue injury was minimal using a clinical treatment protocol. The general principle and associated techniques described in this work can be applied to design improvement of all EM lithotripters.

Experimentally validated multiphysics computational model of focusing and shock wave formation in an electromagnetic lithotripter.

A multiphysics computational model of the focusing of an acoustic pulse and subsequent shock wave formation that occurs during extracorporeal shock wave lithotripsy is presented. In the electromagnetic lithotripter modeled in this work the focusing is achieved via a polystyrene acoustic lens. The transition of the acoustic pulse through the solid lens is modeled by the linear elasticity equations and the subsequent shock wave formation in water is modeled by the Euler equations with a Tait equation of state. Both sets of equations are solved simultaneously in subsets of a single computational domain within the BEARCLAW framework which uses a finite-volume Riemann solver approach. This model is first validated against experimental measurements with a standard (or original) lens design. The model is then used to successfully predict the effects of a lens modification in the form of an annular ring cut. A second model which includes a kidney stone simulant in the domain is also presented. Within the stone the linear elasticity equations incorporate a simple damage model.