This study combined multi-excitation MR Elastography (ME-MRE) with a transversely isotropic inversion nonlinear inversion algorithm and diffusion tensor imaging (DTI) fiber directions to investigate anisotropic white matter tract integrity in aging. Participants were 5 older adults and 17 young adults. MRE outcomes include substrate shear modulus, μ, shear anisotropy, φ, tensile anisotropy, ζ, and DTI measures were also examined. Shear and tensile anisotropies were significantly different in the Corona Radiata and Superior Longitudinal Fasciculus. Diffusion measures were significantly different between groups in most tracts. These results suggest sensitivity of anisotropic properties to biological changes along white matter tracts in aging.
This study combined multiexcitation MRE (ME-MRE), and multifrequency MRE (MF-MRE) with a transversely isotropic nonlinear inversion (TINLI) and axonal fiber directions from diffusion tensor imaging to investigate anisotropic and frequency-dependent material properties simultaneously. These preliminary results show that multifrequency-TINLI MRE can be readily applied to in vivo human data at distinct frequencies.
Intrinsic actuation magnetic resonance elastography (MRE) is a phase-contrast MRI technique that allows for in vivo quantification of mechanical properties of the brain by exploiting brain motion that arise naturally due to the cardiac pulse. The mechanical properties of the brain reflect its tissue microstructure, making it a potentially valuable parameter in studying brain disease. The main purpose of this study was to assess the feasibility of reconstructing the viscoelastic properties of the brain using high-quality 7 T MRI displacement measurements, obtained using displacement encoding with stimulated echoes (DENSE) and intrinsic actuation. The repeatability and sensitivity of the method for detecting normal regional variation in brain tissue properties was assessed as secondary goal. The displacement measurements used in this analysis were previously acquired for a separate study, where eight healthy subjects (27 ± 7 years) were imaged with repeated scans (spatial resolution approx. 2 mm isotropic, temporal resolution 75 ms, motion sensitivity 0.35 mm/2π for displacements in anterior-posterior and left-right directions, and 0.7 mm/2π for feet-head displacements). The viscoelastic properties of the brain were estimated using a subzone based non-linear inversion scheme. The results show comparable consistency to that of extrinsic MRE between the viscoelastic property maps obtained from repeated displacement measurements. The shear stiffness maps showed fairly consistent spatial patterns. The whole-brain repeatability coefficient (RC) for shear stiffness was (mean ± standard deviation) 8 ± 8% relative to the mean whole-brain stiffness, and the damping ratio RC was 28 ± 17% relative to the whole-brain damping ratio. The shear stiffness maps showed similar statistically significant regional trends as demonstrated in a publicly available atlas of viscoelastic properties obtained with extrinsic actuation MRE at 50 Hz. The damping ratio maps showed less consistency, likely due to data-model mismatch of describing the brain as a viscoelastic material under low frequencies. While artifacts induced by fluid flow within the brain remain a limitation of the technique in its current state, intrinsic actuation based MRE allow for consistent and repeatable estimation of the mechanical properties of the brain. The method provides enough sensitivity to investigate regional variation in such properties in the normal brain, which is likely sufficient to also investigate pathological changes.
Anisotropic MRE has shown some promise in estimating mechanical properties of fiber-reinforced biological tissues. However, these methods are restricted to modeling a single fiber and ignores complexity that occurs such as regions of brain white matter with crossing fibers. Here we implement an inversion algorithm capable of modeling material with two fiber directions obtained from diffusion MRI in order to reduce model data mismatch and provide fiber-specific properties, which may show promise in correlating with brain health and function. Performance of this algorithm is demonstrated in simulation and in vivo brain data and compared with one-fiber and zero-fiber (isotropic) inversions.
Motivation: MR elastography can estimate anisotropic mechanical properties of fibrous white matter, traditionally using multi-excitation approaches. Multi-frequency elastography from a single driver is more common and could expand measurements of anisotropy. Goal(s): Our goal was to compare mechanical anisotropy from multi-frequency and multi-excitation reconstructions. Approach: Transversely isotropic parameters were reconstructed using simulated and in vivo multi-frequency wave data, then compared between approaches and against ground truth maps. Adolescent and adult measurements were compared in white matter regions. Results: Multi-frequency elastography performed comparably with the multi-excitation approach in simulations. Higher shear anisotropy was observed in adults compared to adolescents, with no differences in tensile anisotropy. Impact: This study demonstrates that multi-frequency magnetic resonance elastography can reliably estimate anisotropic mechanical properties from single driver data, enabling broader application. Quantifying developmental changes in anisotropy of white matter provides new insights into brain mechanics during maturation.
Digital Image Elastic Tomography (DIET) is a breast imaging technique based on the contrast in stiffness between diseased and healthy tissue. DIET is intended to be a low cost pre-screening method for breast cancer, with the aim of identifying stiff areas within the breast that require further investigation. The DIET inverse problem is to reconstruct stiffness based on steady-state harmonic surface motion data measured by a calibrated 3D imaging array. The ill-posed inverse problem of reconstructing tissue stiffness from surface motion data is simplified by using a shape based description assuming a high stiffness inclusion of unknown position within a less stiff background material. This study examines the three-dimensional problem using both numerical simulation and phantom data. Finite element methods (FEM) are used to model the motion. A parallel genetic algorithm (GA) has been developed for the DIET inverse problem. GAs evaluate the fitness of many solution estimates over successive generations. Each estimate along with its associated error provides information on the shape of the surface of the fitness function. The results of this study demonstrate the feasibility of using the fitness function analysis to improve the DIET solution process.
Magnetic resonance elastography (MRE) is an important new method used to measure the elasticity or stiffness of tissues in vivo . While there are many possible applications of MRE, breast cancer detection and classification is currently the most common. Several groups have been developing methods based on MR and ultrasound (US). MR or US is used to estimate the displacements produced by either quasi‐static compression or dynamic vibration of the tissue. An important advantage of MRE is the possibility of measuring displacements accurately in all three directions. The central problem in most versions of MRE is recovering elasticity information from the measured displacements. In previous work, we have presented simulation results in two and three dimensions that were promising. In this article, accurate reconstructions of elasticity images from 3D, steady‐state experimental data are reported. These results are significant because they demonstrate that the process is truly three‐dimensional even for relatively simple geometries and phantoms. Further, they show that the integration of displacement data acquisition and elastic property reconstruction has been successfully achieved in the experimental setting. This process involves acquiring volumetric MR phase images with prescribed phase offsets between the induced mechanical motion and the motion‐encoding gradients, converting this information into a corresponding 3D displacement field and estimating the concomitant 3D elastic property distribution through model‐based image reconstruction. Fully 3D displacement fields and resulting elasticity images are presented for single and multiple inclusion gel phantoms.
MR elastography (MRE) must account for the anisotropic nature of myocardial tissue to accurately quantify stiffness. The constitutive matrix for this material was rotated to align with the fibers. One ex vivo swine heart was scanned with DTI and MRE sequences at 2 isotropic voxel resolution. Transversely isotropic viscoelastic stiffness was reconstructed using the Non-Linear Inversion (NLI) algorithm. Elastic properties (shear and Young’s modulus, tensile and shear anisotropy) were segment dependent, in agreement with the myocyte sheetlet formation, which varies in size and spacing according to the myocardial segment. Similarities between MRE and DTI metrics could be observed.
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