Viscoelasticity of subcortical gray matter structures

Mechanical property alterations across the cerebral cortex due to Alzheimer's disease

Alzheimer's disease is a personally devastating neurodegenerative disorder and a major public health concern. There is an urgent need for medical imaging techniques that better characterize the early stages and monitor the progression of the disease. Magnetic resonance elastography (MRE) is a relatively new and highly sensitive MRI technique that can non-invasively assess tissue microstructural integrity via measurement of brain viscoelastic mechanical properties. For the first time, we use high-resolution MRE methods to conduct a voxel-wise MRE investigation and state-of-the-art post hoc region of interest analysis of the viscoelastic properties of the cerebral cortex in patients with Alzheimer's disease (N = 11) compared with cognitively healthy older adults (N = 12). We replicated previous findings that have reported significant volume and stiffness reductions at the whole-brain level. Significant reductions in volume were also observed in Alzheimer's disease when white matter, cortical grey matter and subcortical grey matter compartments were considered separately; lower stiffness was also observed in white matter and cortical grey matter, but not in subcortical grey matter. Voxel-based morphometry of both cortical and subcortical grey matter revealed localized reductions in volume due to Alzheimer's disease in the hippocampus, fusiform, middle, superior temporal gyri and precuneus. Similarly, voxel-based MRE identified lower stiffness in the middle and superior temporal gyri and precuneus, although the spatial distribution of these effects was not identical to the pattern of volume reduction. Notably, MRE additionally identified stiffness deficits in the operculum and precentral gyrus located within the frontal lobe; regions that did not undergo volume loss identified through voxel-based morphometry. Voxel-based-morphometry and voxel-based MRE results were confirmed by a complementary post hoc region-of-interest approach in native space where the viscoelastic changes remained significant even after statistically controlling for regional volumes. The pattern of reduction in cortical stiffness observed in Alzheimer's disease patients raises the possibility that MRE may provide unique insights regarding the neural mechanisms which underlie the development and progression of the disease. The measured mechanical property changes that we have observed warrant further exploration to investigate the diagnostic usefulness of MRE in cases of Alzheimer's disease and other dementias.

Viscoelasticity of striatal brain areas reflects variations in body mass index of lean to overweight male adults

Although a variety of MRI studies investigated the link between body mass index (BMI) and parameters of neural gray matter (GM), the technique applied in most of these studies, voxel-based morphometry (VBM), focusses on the regional GM volume, a macroscopic tissue property. Thus, the studies were not able to exploit the BMI-related information contained in the GM microstructure although PET studies suggest that these factors are important. Here, we used cerebral MR Elastography (MRE) to characterize features of tissue microstructure by evaluating the propagation of shear waves applied to the skull and to assess local tissue viscoelasticity to test the link between this parameter and BMI in 22 lean to overweight males. Unlike the majority of existing MRE studies investigating neural viscoelasticity signals averaged across large brain regions, we used the viscoelasticity of individual voxels for our experiment. Our technique revealed a negative link between BMI and viscoelasticity of two areas of the striatal reward system, i.e., right putamen (t = -8.2; p_{FWE-corrected} = 0.005) and left globus pallidus (t = -7.1; p_FWE = 0.037) which was independent of GM volume at these coordinates. Finally, comparison of BMI models based on individual voxels vs. on signals averaged across brain atlas regions demonstrates that voxel-based models explain a significantly higher proportion of variance. Consequently, our findings show that cerebral MRE is suitable to identify medically relevant microstructural tissue properties. Using a voxel-wise analysis approach, we were able to utilize the high spatial resolution of MRE for mapping BMI-related information in the brain.

Structural and Functional MRI Evidence for Distinct Medial Temporal and Prefrontal Roles in Context-dependent Relational Memory

Declarative memory is supported by distributed brain networks in which the medial-temporal lobes (MTLs) and pFC serve as important hubs. Identifying the unique and shared contributions of these regions to successful memory performance is an active area of research, and a growing literature suggests that these structures often work together to support declarative memory. Here, we present data from a context-dependent relational memory task in which participants learned that individuals belonged in a single room in each of two buildings. Room assignment was consistent with an underlying contextual rule structure in which male and female participants were assigned to opposite sides of a building and the side assignment switched between buildings. In two experiments, neural correlates of performance on this task were evaluated using multiple neuroimaging tools: diffusion tensor imaging (Experiment 1), magnetic resonance elastography (Experiment 1), and functional MRI (Experiment 2). Structural and functional data from each individual modality provided complementary and consistent evidence that the hippocampus and the adjacent white matter tract (i.e., fornix) supported relational memory, whereas the ventromedial pFC/OFC (vmPFC/OFC) and the white matter tract connecting vmPFC/OFC to MTL (i.e., uncinate fasciculus) supported memory-guided rule use. Together, these data suggest that MTL and pFC structures differentially contribute to and support contextually guided relational memory.

Quantifying deep grey matter atrophy using automated segmentation approaches: A systematic review of structural MRI studies

The deep grey matter (DGM) nuclei of the brain play a crucial role in learning, behaviour, cognition, movement and memory. Although automated segmentation strategies can provide insight into the impact of multiple neurological conditions affecting these structures, such as Multiple Sclerosis (MS), Huntington's disease (HD), Alzheimer's disease (AD), Parkinson's disease (PD) and Cerebral Palsy (CP), there are a number of technical challenges limiting an accurate automated segmentation of the DGM. Namely, the insufficient contrast of T1 sequences to completely identify the boundaries of these structures, as well as the presence of iso-intense white matter lesions or extensive tissue loss caused by brain injury. Therefore in this systematic review, 269 eligible studies were analysed and compared to determine the optimal approaches for addressing these technical challenges. The automated approaches used among the reviewed studies fall into three broad categories, atlas-based approaches focusing on the accurate alignment of atlas priors, algorithmic approaches which utilise intensity information to a greater extent, and learning-based approaches that require an annotated training set. Studies that utilise freely available software packages such as FIRST, FreeSurfer and LesionTOADS were also eligible, and their performance compared. Overall, deep learning approaches achieved the best overall performance, however these strategies are currently hampered by the lack of large-scale annotated data. Improving model generalisability to new datasets could be achieved in future studies with data augmentation and transfer learning. Multi-atlas approaches provided the second-best performance overall, and may be utilised to construct a "silver standard" annotated training set for deep learning. To address the technical challenges, providing robustness to injury can be improved by using multiple channels, highly elastic diffeomorphic transformations such as LDDMM, and by following atlas-based approaches with an intensity driven refinement of the segmentation, which has been done with the Expectation Maximisation (EM) and level sets methods. Accounting for potential lesions should be achieved with a separate lesion segmentation approach, as in LesionTOADS. Finally, to address the issue of limited contrast, R2*, T2* and QSM sequences could be used to better highlight the DGM due to its higher iron content. Future studies could look to additionally acquire these sequences by retaining the phase information from standard structural scans, or alternatively acquiring these sequences for only a training set, allowing models to learn the "improved" segmentation from T1-sequences alone.

Fast Robust Dejitter and Interslice Discontinuity Removal in MRI Phase Acquisitions: Application to Magnetic Resonance Elastography

MRI phase contrast imaging methods that assemble slice-wise acquisitions into volumes can contain interslice phase discontinuities (IPDs) over the course of the scan from sources, including unavoidable physiological activity. In magnetic resonance elastography (MRE), this can alter wavelength and tissue stiffness estimates, invalidating the analysis. We first model this behavior as jitter along the z-axis of the phase of 3D complex-valued wave volumes. A two-step image processing pipeline is then proposed that removes IPDs. First, constant slicewise phase shift is removed with a novel, non-convex dejittering algorithm. Then, regional physiological noise artifacts are removed with novel filtering of 3D wavelet coefficients. Calibration of two pipeline coefficients, the dejitter parameter α and the wavelet band high-pass coefficient ω_c , was first performed on a finite-element method brain phantom. A comparative investigation was then performed, on a cohort of 48 brain acquisitions, of four approaches to IPDs: 1) the proposed method; 2) a "control" condition of neglect of IPDs; 3) an anisotropic wavelet-based method; and 4) a method of in-plane (2D) processing. The present method showed medians of [Formula: see text] Pa for a multifrequency wave inversion centered at 40 Hz which was within 6% of methods 3) and 4), while neglect produced [Formula: see text] estimates a mean of 17% lower. The proposed method reduced the value range of the cohort against methods 3) and 4) by 29% and 31%, respectively. Such reduction in variance enhances the ability of brain MRE to predict subtler physiological changes. Our theoretical approach further enables more powerful applications of fundamental findings in noise and denoising to MRE.

Substrate elasticity induces quiescence and promotes neurogenesis of primary neural stem cells-A biophysical in vitro model of the physiological cerebral milieu

In the brain, neural stem cells (NSC) are tightly regulated by external signals and biophysical cues mediated by the local microenvironment or "niche." In particular, the influence of tissue elasticity, known to fundamentally affect the function of various cell types in the body, on NSC remains poorly understood. We, accordingly, aimed to characterize the effects of elastic substrates on critical NSC functions. Primary rat NSC were grown as monolayers on polydimethylsiloxane- (PDMS-) based gels. PDMS-coated cell culture plates, simulating the physiological microenvironment of the living brain, were generated in various degrees of elasticity, ranging from 1 to 50 kPa; additionally, results were compared with regular glass plates as usually used in cell culture work. Survival of NSC on the PDMS-based substrates was unimpaired. The proliferation rate on 1 kPa PDMS decreased by 45% compared with stiffer PMDS substrates of 50 kPa (p < 0.05) whereas expression of cyclin-dependent kinase inhibitor 1B/p27Kip1 increased more than two fold (p < 0.01), suggesting NSC quiescence. NSC differentiation was accelerated on softer substrates and favored the generation of neurons (42% neurons on 1 kPa PDMS vs. 25% on 50 kPa PDMS; p < 0.05). Neurons generated on 1 kPa PDMS showed 29% longer neurites compared with those on stiffer PDMS substrates (p < 0.05), suggesting optimized neuronal maturation and an accelerated generation of neuronal networks. Data show that primary NSC are significantly affected by the mechanical properties of their microenvironment. Culturing NSC on a substrate of brain-like elasticity keeps them in their physiological, quiescent state and increases their neurogenic potential.

Optimization of a Multifrequency Magnetic Resonance Elastography Protocol for the Human Brain

BACKGROUND AND PURPOSE

The brain's stiffness measurements from magnetic resonance elastography (MRE) strongly depend on actuation frequencies, which makes cross-study comparisons challenging. We performed a preliminary study to acquire optimal sets of actuation frequencies to accurately obtain rheological parameters for the whole brain (WB), white matter (WM), and gray matter (GM).

METHODS

Six healthy volunteers aged between 26 and 72 years old went through MRE with a modified single-shot spin-echo echo planar imaging pulse sequence embedded with motion encoding gradients on a 3T scanner. Frequency-independent brain material properties and best-fit material model were determined from the frequency-dependent brain tissue response data (20 -80 Hz), by comparing four different linear viscoelastic material models (Maxwell, Kelvin-Voigt, Springpot, and Zener). During the material fitting, spatial averaging of complex shear moduli (G*) obtained under single actuation frequency was performed, and then rheological parameters were acquired. Since clinical scan time is limited, a combination of three actuation frequencies that would provide the most accurate approximation and lowest fitting error was determined for WB, WM, and GM by optimizing for the lowest Bayesian information criterion (BIC).

RESULTS

BIC scores for the Zener and Springpot models showed these models approximate the multifrequency response of the tissue best. The best-fit frequency combinations for the reference Zener and Springpot models were identified to be 30-60-70 and 30-40-80 Hz, respectively, for the WB.

CONCLUSIONS

Optimal sets of actuation frequencies to accurately obtain rheological parameters for WB, WM, and GM were determined from shear moduli measurements obtained via 3-dimensional direct inversion. We believe that our study is a first-step in developing a region-specific multifrequency MRE protocol for the human brain.

Reliable preparation of agarose phantoms for use in quantitative magnetic resonance elastography

Agarose phantoms are one type of phantom commonly used in developing in vivo brain magnetic resonance elastography (MRE) sequences because they are inexpensive and easy to work with, store, and dispose of; however, protocols for creating agarose phantoms are non-standardized and often result in inconsistent phantoms with significant variability in mechanical properties. Many magnetic resonance imaging (MRI) and ultrasound studies use phantoms, but often these phantoms are not tailored for desired mechanical properties and as such are too stiff or not mechanically consistent enough to be used in MRE. In this work, we conducted a systematic study of agarose phantom creation parameters to identify those factors that are most conducive to producing mechanically consistent agarose phantoms for MRE research. We found that cooling rate and liquid temperature affected phantom homogeneity. Phantom stiffness is affected by agar concentration (quadratically), by final liquid temperature and salt content in phantoms, and by the interaction of these two metrics each with stir rate. We captured and quantified the implied relationships with a regression model that can be used to estimate stiffness of resulting phantoms. Additionally, we characterized repeatability, stability over time, impact on MR signal parameters, and differences in agar gel microstructure. This protocol and regression model should prove beneficial in future MRE development studies that use phantoms to determine stiffness measurement accuracy.

Magnetic resonance elastography of the brain: A study of feasibility and reproducibility using an ergonomic pillow-like passive driver

Magnetic resonance elastography (MRE) can be used to noninvasively resolve the displacement pattern of induced mechanical waves propagating in tissue. The goal of this study is to establish an ergonomically flexible passive-driver design for brain MRE, to evaluate the reproducibility of MRE tissue-stiffness measurements, and to investigate the relationship between tissue-stiffness measurements and driver frequencies. An ergonomically flexible passive pillow-like driver was designed to induce mechanical waves in the brain. Two-dimensional finite-element simulation was used to evaluate mechanical wave propagation patterns in brain tissues. MRE scans were performed on 10 healthy volunteers at mechanical frequencies of 60, 50, and 40 Hz. An axial mid-brain slice was acquired using an echo-planar imaging sequence to map the displacement pattern with the motion-encoding gradient along the through-plane (z) direction. All subjects were scanned and rescanned within 1 h. The Wilcoxon signed-rank test was used to test for differences between white matter and gray matter shear-stiffness values. One-way analysis of variance (ANOVA) was used to test for differences between shear-stiffness measurements made at different frequencies. Scan-rescan reproducibility was evaluated by calculating the within-subject coefficient of variation (CV) for each subject. The finite-element simulation showed that a pillow-like passive driver is capable of efficient shear-wave propagation through brain tissue. No subjects complained about discomfort during MRE acquisitions using the ergonomically designed driver. The white-matter elastic modulus (mean ± standard deviation) across all subjects was 3.85 ± 0.12 kPa, 3.78 ± 0.15 kPa, and 3.36 ± 0.11 kPa at frequencies of 60, 50, and 40 Hz, respectively. The gray-matter elastic modulus across all subjects was 3.33 ± 0.14 kPa, 2.82 ± 0.16 kPa, and 2.24 ± 0.14 kPa at frequencies of 60, 50, and 40 Hz, respectively. The Wilcoxon signed-rank test confirmed that the shear stiffness was significantly higher in white matter than gray matter at all three frequencies. The ranges of within-subject coefficients of variation for white matter, gray matter, and whole-brain shear-stiffness measurements for the three frequencies were 1.8-3.5% (60 Hz), 4.7-6.0% (50 Hz), and 3.7-4.1% (40 Hz). An ergonomic pneumatic pillow-like driver is feasible for highly reproducible in vivo evaluation of brain-tissue shear stiffness. Brain-tissue shear-stiffness values were frequency-dependent, thus emphasizing the importance of standardizing MRE acquisition protocols in multi-center studies.

Altered brain tissue viscoelasticity in pediatric cerebral palsy measured by magnetic resonance elastography

Cerebral palsy (CP) is a neurodevelopmental disorder that results in functional motor impairment and disability in children. CP is characterized by neural injury though many children do not exhibit brain lesions or damage. Advanced structural MRI measures may be more sensitively related to clinical outcomes in this population. Magnetic resonance elastography (MRE) measures the viscoelastic mechanical properties of brain tissue, which vary extensively between normal and disease states, and we hypothesized that the viscoelasticity of brain tissue is reduced in children with CP. Using a global region-of-interest-based analysis, we found that the stiffness of the cerebral gray matter in children with CP is significantly lower than in typically developing (TD) children, while the damping ratio of gray matter is significantly higher in CP. A voxel-wise analysis confirmed this finding, and additionally found stiffness and damping ratio differences between groups in regions of white matter. These results indicate that there is a difference in brain tissue health in children with CP that is quantifiable through stiffness and damping ratio measured with MRE. Understanding brain tissue mechanics in the pediatric CP population may aid in the diagnosis and evaluation of CP.

Mechanical properties of the in vivo adolescent human brain

Viscoelastic mechanical properties of the in vivo human brain, measured noninvasively with magnetic resonance elastography (MRE), have recently been shown to be affected by aging and neurological disease, as well as relate to performance on cognitive tasks in adults. The demonstrated sensitivity of brain mechanical properties to neural tissue integrity make them an attractive target for examining the developing brain; however, to date, MRE studies on children are lacking. In this work, we characterized global and regional brain stiffness and damping ratio in a sample of 40 adolescents aged 12-14 years, including the lobes of the cerebrum and subcortical gray matter structures. We also compared the properties of the adolescent brain to the healthy adult brain. Temporal and parietal cerebral lobes were softer in adolescents compared to adults. We found that of subcortical gray matter structures, the caudate and the putamen were significantly stiffer in adolescents, and that the hippocampus and amygdala were significantly less stiff than all other subcortical structures. This study provides the first detailed characterization of adolescent brain viscoelasticity and provides baseline data to be used in studying development and pathophysiology.

Stiffness and Beyond: What MR Elastography Can Tell Us About Brain Structure and Function Under Physiologic and Pathologic Conditions

Brain magnetic resonance elastography (MRE) was developed on the basis of a desire to "palpate by imaging" and is becoming a powerful tool in the investigation of neurophysiological and neuropathological states. Measurements are acquired with a specialized MR phase-contrast pulse sequence that can detect tissue motion in response to an applied external or internal excitation. The tissue viscoelasticity is then reconstructed from the measured displacement. Quantitative characterization of brain viscoelastic behaviors provides us an insight into the brain structure and function by assessing the mechanical rigidity, viscosity, friction, and connectivity of brain tissues. Changes in these features are associated with inflammation, demyelination, and neurodegeneration that contribute to brain disease onset and progression. Here, we review the basic principles and limitations of brain MRE and summarize its current neuroanatomical studies and clinical applications to the most common neurosurgical and neurodegenerative disorders, including intracranial tumors, dementia, multiple sclerosis, amyotrophic lateral sclerosis, and traumatic brain injury. Going forward, further improvement in acquisition techniques, stable inverse reconstruction algorithms, and advanced numerical, physical, and preclinical validation models is needed to increase the utility of brain MRE in both research and clinical applications.

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.

Phantom evaluations of nonlinear inversion MR elastography

This study evaluated non-linear inversion MRE (NLI-MRE) based on viscoelastic governing equations to determine its sensitivity to small, low contrast inclusions and interface changes in shear storage modulus and damping ratio. Reconstruction parameters identical to those used in recent in vivo MRE studies of mechanical property variations in small brain structures were applied. NLI-MRE was evaluated on four phantoms with contrast in stiffness and damping ratio. Image contrast to noise ratio was assessed as a function of inclusion diameter and property contrast, and edge and line spread functions were calculated as measures of imaging resolution. Phantoms were constructed from silicone, agar, and tofu materials. Reconstructed property estimates were compared with independent mechanical testing using dynamic mechanical analysis (DMA). The NLI-MRE technique detected inclusions as small as 8 mm with a stiffness contrast as low as 14%. Storage modulus images also showed an interface edge response distance of 11 mm. Damping ratio images distinguished inclusions with a diameter as small as 8 mm, and yielded an interface edge response distance of 10 mm. Property differences relative to DMA tests were in the 15%-20% range in most cases. In this study, NLI-MRE storage modulus estimates resolved the smallest inclusion with the lowest stiffness contrast, and spatial resolution of attenuation parameter images was quantified for the first time. These experiments and image quality metrics establish quantitative guidelines for the accuracy expected in vivo for MRE images of small brain structures, and provide a baseline for evaluating future improvements to the NLI-MRE pipeline.

Perspective: The role of mechanobiology in the etiology of brain metastasis

Tumor latency and dormancy are obstacles to effective cancer treatment. In brain metastases, emergence of a lesion can occur at varying intervals from diagnosis and in some cases following successful treatment of the primary tumor. Genetic factors that drive brain metastases have been identified, such as those involved in cell adhesion, signaling, extravasation, and metabolism. From this wealth of knowledge, vexing questions still remain; why is there a difference in strategy to facilitate outgrowth and why is there a difference in latency? One missing link may be the role of tissue biophysics of the brain microenvironment in infiltrating cells. Here, I discuss the mechanical cues that may influence disseminated tumor cells in the brain, as a function of age and disease. I further discuss in vitro and in vivo preclinical models such as 3D culture systems and zebrafish to study the role of the mechanical environment in brain metastasis in an effort of providing novel targeted therapeutics.

Double dissociation of structure-function relationships in memory and fluid intelligence observed with magnetic resonance elastography

Brain tissue mechanical properties, measured in vivo with magnetic resonance elastography (MRE), have proven to be sensitive metrics of neural tissue integrity. Recently, our group has reported on the positive relationship between viscoelasticity of the hippocampus and performance on a relational memory task in healthy young adults, which highlighted the potential of sensitive MRE measures for studying brain health and its relation to cognitive function; however, structure-function relationships outside of the hippocampus have not yet been explored. In this study, we examined the relationships between viscoelasticity of both the hippocampus and the orbitofrontal cortex and performance on behavioral assessments of relational memory and fluid intelligence. In a sample of healthy, young adults (N = 53), there was a significant, positive relationship between orbitofrontal cortex viscoelasticity and fluid intelligence performance (r = 0.42; p = .002). This finding is consistent with the previously reported relationship between hippocampal viscoelasticity and relational memory performance (r = 0.41; p = .002). Further, a significant double dissociation between the orbitofrontal-fluid intelligence relationship and the hippocampal-relational memory relationship was observed. These data support the specificity of regional brain MRE measures in support of separable cognitive functions. This report of a structure-function relationship observed with MRE beyond the hippocampus suggests a future role for MRE as a sensitive neuroimaging technique for brain mapping.

Quantitative Elastography Methods in Liver Disease: Current Evidence and Future Directions

Chronic liver diseases often result in the development of liver fibrosis and ultimately, cirrhosis. Treatment strategies and prognosis differ greatly depending on the severity of liver fibrosis, thus liver fibrosis staging is clinically relevant. Traditionally, liver biopsy has been the method of choice for fibrosis evaluation. Because of liver biopsy limitations, noninvasive methods have become a key research interest in the field. Elastography enables the noninvasive measurement of tissue mechanical properties through observation of shear-wave propagation in the tissue of interest. Increasing fibrosis stage is associated with increased liver stiffness, providing a discriminatory feature that can be exploited by elastographic methods. Ultrasonographic (US) and magnetic resonance (MR) imaging elastographic methods are commercially available, each with their respective strengths and limitations. Here, the authors review the technical basis, acquisition techniques, and results and limitations of US- and MR-based elastography techniques. Diagnostic performance in the most common etiologies of chronic liver disease will be presented. Reliability, reproducibility, failure rate, and emerging advances will be discussed. ^© RSNA, 2018 Online supplemental material is available for this article.

Relationships between scalp, brain, and skull motion estimated using magnetic resonance elastography

The objective of this study was to characterize the relationships between motion in the scalp, skull, and brain. In vivo estimates of motion transmission from the skull to the brain may illuminate the mechanics of traumatic brain injury. Because of challenges in directly sensing skull motion, it is useful to know how well motion of soft tissue of the head, i.e., the scalp, can approximate skull motion or predict brain tissue deformation. In this study, motion of the scalp and brain were measured using magnetic resonance elastography (MRE) and separated into components due to rigid-body displacement and dynamic deformation. Displacement estimates in the scalp were calculated using low motion-encoding gradient strength in order to reduce "phase wrapping" (an ambiguity in displacement estimates caused by the 2 π-periodicity of MRE phase contrast). MRE estimates of scalp and brain motion were compared to skull motion estimated from three tri-axial accelerometers. Comparison of the relative amplitudes and phases of harmonic motion in the scalp, skull, and brain of six human subjects indicate that data from scalp-based sensors should be used with caution to estimate skull kinematics, but that fairly consistent relationships exist between scalp, skull, and brain motion. In addition, the measured amplitude and phase relationships of scalp, skull, and brain can be used to evaluate and improve mathematical models of head biomechanics.

High-resolution magnetic resonance elastography reveals differences in subcortical gray matter viscoelasticity between young and healthy older adults

Volumetric structural magnetic resonance imaging (MRI) is commonly used to determine the extent of neuronal loss in aging, indicated by cerebral atrophy. The brain, however, exhibits other biophysical characteristics such as mechanical properties, which can be quantified with magnetic resonance elastography (MRE). MRE is an emerging noninvasive imaging technique for measuring viscoelastic tissue properties, proven to be sensitive metrics of neural tissue integrity, as described by shear stiffness, μ and damping ratio, ξ parameters. The study objective was to evaluate global and regional MRE parameter differences between young (19–30 years, n = 12) and healthy older adults (66–73 years, n = 12) and to assess whether MRE measures provide additive value over volumetric magnetic resonance imaging measurements. We investigated the viscoelasticity of the global cerebrum and 6 regions of interest (ROIs) including the amygdala, hippocampus, caudate, pallidum, putamen, and thalamus. In older adults, we found a decrease in μ in all ROIs, except for the hippocampus, indicating widespread brain softening; an effect that remained significant after controlling for ROI volume. In contrast, the relative viscous-to-elastic behavior of the brain ξ did not differ between age groups, suggesting a preservation of the organization of the tissue microstructure. These data support the use of MRE as a novel imaging biomarker for characterizing age-related differences to neural tissue not captured by volumetric imaging alone.

Mechanical properties of porcine brain tissue in vivo and ex vivo estimated by MR elastography

The mechanical properties of brain tissue in vivo determine the response of the brain to rapid skull acceleration. These properties are thus of great interest to the developers of mathematical models of traumatic brain injury (TBI) or neurosurgical simulations. Animal models provide valuable insight that can improve TBI modeling. In this study we compare estimates of mechanical properties of the Yucatan mini-pig brain in vivo and ex vivo using magnetic resonance elastography (MRE) at multiple frequencies. MRE allows estimations of properties in soft tissue, either in vivo or ex vivo, by imaging harmonic shear wave propagation. Most direct measurements of brain mechanical properties have been performed using samples of brain tissue ex vivo. It has been observed that direct estimates of brain mechanical properties depend on the frequency and amplitude of loading, as well as the time post-mortem and condition of the sample. Using MRE in the same animals at overlapping frequencies, we observe that porcine brain tissue in vivo appears stiffer than porcine brain tissue samples ex vivo at frequencies of 100 Hz and 125 Hz, but measurements show closer agreement at lower frequencies.

Perfusion alters stiffness of deep gray matter

Viscoelastic properties of the brain reflect tissue architecture at multiple length scales. However, little is known about the relation between vital tissue functions, such as perfusion, and the macroscopic mechanical properties of cerebral tissue. In this study, arterial spin labelling is paired with magnetic resonance elastography to investigate the relationship between tissue stiffness and cerebral blood flow (CBF) in the in vivo human brain. The viscoelastic modulus, | G*|, and CBF were studied in deep gray matter (DGM) of 14 healthy male volunteers in the following sub-regions: putamen, nucleus accumbens, hippocampus, thalamus, globus pallidus, and amygdala. CBF was further normalized by vessel area data to obtain the flux rate q which is proportional to the perfusion pressure gradient. The striatum (represented by putamen and nucleus accumbens) was distinct from the other DGM regions by displaying markedly higher stiffness and perfusion values. q was a predictive marker for DGM stiffness as analyzed by linear regression | G*| =  q·(4.2 ± 0.6)kPa·s + (0.80 ± 0.06)kPa ( R²= 0.92, P = 0.006). These results suggest a high sensitivity of MRE in DGM to perfusion pressure. The distinct mechano-vascular properties of striatum tissue, as compared to the rest of DGM, may reflect elevated perfusion pressure, which could explain the well-known susceptibility of the putamen to hemorrhages.

Combining viscoelasticity, diffusivity and volume of the hippocampus for the diagnosis of Alzheimer's disease based on magnetic resonance imaging

Dementia due to Alzheimer's Disease (AD) is a neurodegenerative disease for which treatment strategies at an early stage are of great clinical importance. So far, there is still a lack of non-invasive diagnostic tools to sensitively detect AD in early stages and to predict individual disease progression. Magnetic resonance elastography (MRE) of the brain may be a promising novel tool. In this proof-of-concept study, we investigated whether multifrequency-MRE (MMRE) can detect differences in hippocampal stiffness between patients with clinical diagnosis of dementia due to AD and healthy controls (HC). Further, we analyzed if the combination of three MRI-derived parameters, i.e., hippocampal stiffness, hippocampal volume and mean diffusivity (MD), improves diagnostic accuracy.

Diagnostic criteria for probable dementia due to AD were in line with the NINCDS-ADRDA criteria and were verified through history-taking (patient and informant), neuropsychological testing, routine blood results and routine MRI to exclude other medical causes of a cognitive decline.

21 AD patients and 21 HC (median age 75 years) underwent MMRE and structural MRI, from which hippocampal volume and MD were calculated. From the MMRE-images maps of the magnitude |G*| and phase angle φ of the complex shear modulus were reconstructed using multifrequency inversion. Median values of |G*| and φ were extracted within three regions of interest (hippocampus, thalamus and whole brain white matter). To test the predictive value of the main outcome parameters, we performed receiver operating characteristic (ROC) curve analyses.

Hippocampal stiffness (|G*|) and viscosity (φ) were significantly lower in the patient group (both p < 0.001). ROC curve analyses showed an area under the curve (AUC) for | G*| of 0.81 [95%CI 0.68–0.94]; with sensitivity 86%, specificity 67% for cutoff at |G*| = 980 Pa) and for φ an AUC of 0.79 [95%CI 0.66–0.93]. In comparison, the AUC of MD and hippocampal volume were 0.83 [95%CI 0.71–0.95] and 0.86 [95%CI 0.74–0.97], respectively. A combined ROC curve of |G*|, MD and hippocampal volume yielded a significantly improved AUC of 0.90 [95%CI 0.81–0.99].

In conclusion, we demonstrated reduced hippocampal stiffness and reduced hippocampal viscosity, as determined by MMRE, in patients with clinical diagnosis of dementia of the AD type. Diagnostic sensitivity was further improved by the combination with two other MRI-based hippocampal parameters. These findings motivate further investigation whether MMRE can detect decreased brain stiffness already in pre-dementia stages, and whether these changes predict cognitive decline.

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Non-invasive methods for early detection of AD are lacking.

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MRE of the brain is a promising new non-invasive diagnostic tool.

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We demonstrate reduced hippocampal stiffness (|G*|) in AD patients.

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|G*| distinguishes healthy and demented with 86% sensitivity and 67% specificity.

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Combining hippocampal stiffness, MD and volume improved diagnostic accuracy.

The Relationship of Three-Dimensional Human Skull Motion to Brain Tissue Deformation in Magnetic Resonance Elastography Studies

In traumatic brain injury (TBI), membranes such as the dura mater, arachnoid mater, and pia mater play a vital role in transmitting motion from the skull to brain tissue. Magnetic resonance elastography (MRE) is an imaging technique developed for noninvasive estimation of soft tissue material parameters. In MRE, dynamic deformation of brain tissue is induced by skull vibrations during magnetic resonance imaging (MRI); however, skull motion and its mode of transmission to the brain remain largely uncharacterized. In this study, displacements of points in the skull, reconstructed using data from an array of MRI-safe accelerometers, were compared to displacements of neighboring material points in brain tissue, estimated from MRE measurements. Comparison of the relative amplitudes, directions, and temporal phases of harmonic motion in the skulls and brains of six human subjects shows that the skull-brain interface significantly attenuates and delays transmission of motion from skull to brain. In contrast, in a cylindrical gelatin "phantom," displacements of the rigid case (reconstructed from accelerometer data) were transmitted to the gelatin inside (estimated from MRE data) with little attenuation or phase lag. This quantitative characterization of the skull-brain interface will be valuable in the parameterization and validation of computer models of TBI.

Artificial neural networks for stiffness estimation in magnetic resonance elastography

PURPOSE

To investigate the feasibility of using artificial neural networks to estimate stiffness from MR elastography (MRE) data.

METHODS

Artificial neural networks were fit using model-based training patterns to estimate stiffness from images of displacement using a patch size of ∼1 cm in each dimension. These neural network inversions (NNIs) were then evaluated in a set of simulation experiments designed to investigate the effects of wave interference and noise on NNI accuracy. NNI was also tested in vivo, comparing NNI results against currently used methods.

RESULTS

In 4 simulation experiments, NNI performed as well or better than direct inversion (DI) for predicting the known stiffness of the data. Summary NNI results were also shown to be significantly correlated with DI results in the liver (R²  = 0.974) and in the brain (R²  = 0.915), and also correlated with established biological effects including fibrosis stage in the liver and age in the brain. Finally, repeatability error was lower in the brain using NNI compared to DI, and voxel-wise modeling using NNI stiffness maps detected larger effects than using DI maps with similar levels of smoothing.

CONCLUSION

Artificial neural networks represent a new approach to inversion of MRE data. Summary results from NNI and DI are highly correlated and both are capable of detecting biologically relevant signals. Preliminary evidence suggests that NNI stiffness estimates may be more resistant to noise than an algebraic DI approach. Taken together, these results merit future investigation into NNIs to improve the estimation of stiffness in small regions. Magn Reson Med 80:351-360, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

MR elastography of the brain and its application in neurological diseases

Magnetic resonance elastography (MRE) is an imaging technique for noninvasively and quantitatively assessing tissue stiffness, akin to palpation. MRE is further able assess the mechanical properties of tissues that cannot be reached by hand including the brain. The technique is a three-step process beginning with the introduction of shear waves into the tissue of interest by applying an external vibration. Next, the resulting motion is imaged using a phase-contrast MR pulse sequence with motion encoding gradients that are synchronized to the vibration. Finally, the measured displacement images are mathematically inverted to compute a map of the estimated stiffness. In the brain, the technique has demonstrated strong test-retest repeatability with typical errors of 1% for measuring global stiffness, 2% for measuring stiffness in the lobes of the brain, and 3-7% for measuring stiffness in subcortical gray matter. In healthy volunteers, multiple studies have confirmed that stiffness decreases with age, while more recent studies have demonstrated a strong relationship between viscoelasticity and behavioral performance. Furthermore, several studies have demonstrated the sensitivity of brain stiffness to neurodegeneration, as stiffness has been shown to decrease in multiple sclerosis and in several forms of dementia. Moreover, the spatial pattern of stiffness changes varies among these different classes of dementia. Finally, MRE is a promising tool for the preoperative assessment of intracranial tumors, as it can measure both tumor consistency and adherence to surrounding tissues. These factors are important predictors of surgical difficulty. In brief, MRE demonstrates potential value in a number of neurological diseases. However, significant opportunity remains to further refine the technique and better understand the underlying physiology.

Magnetic resonance elastography for examining developmental changes in the mechanical properties of the brain

Magnetic resonance elastography (MRE) is a quantitative imaging technique for noninvasively characterizing tissue mechanical properties, and has recently emerged as a valuable tool for neuroimaging. The measured mechanical properties reflect the microstructural composition and organization of neural tissue, and have shown significant effects in many neurological conditions and normal, healthy aging, and evidence has emerged supporting novel relationships between mechanical structure and cognitive function. The sensitivity of MRE to brain structure, function, and health make it an ideal technique for studying the developing brain; however, brain MRE studies on children and adolescents have only just begun. In this article, we review brain MRE and its findings, discuss its potential role in developmental neuroimaging, and provide suggestions for researchers interested in adopting this technique.

Aerobic fitness, hippocampal viscoelasticity, and relational memory performance

The positive relationship between hippocampal structure, aerobic fitness, and memory performance is often observed among children and older adults; but evidence of this relationship among young adults, for whom the hippocampus is neither developing nor atrophying, is less consistent. Studies have typically relied on hippocampal volumetry (a gross proxy of tissue composition) to assess individual differences in hippocampal structure. While volume is not specific to microstructural tissue characteristics, microstructural differences in hippocampal integrity may exist even among healthy young adults when volumetric differences are not diagnostic of tissue health or cognitive function. Magnetic resonance elastography (MRE) is an emerging noninvasive imaging technique for measuring viscoelastic tissue properties and provides quantitative measures of tissue integrity. We have previously demonstrated that individual differences in hippocampal viscoelasticity are related to performance on a relational memory task; however, little is known about health correlates to this novel measure. In the current study, we investigated the relationship between hippocampal viscoelasticity and cardiovascular health, and their mutual effect on relational memory in a group of healthy young adults (N=51). We replicated our previous finding that hippocampal viscoelasticity correlates with relational memory performance. We extend this work by demonstrating that better aerobic fitness, as measured by VO2max, was associated with hippocampal viscoelasticity that mediated the benefits of fitness on memory function. Hippocampal volume, however, did not account for individual differences in memory. Therefore, these data suggest that hippocampal viscoelasticity may provide a more sensitive measure to microstructural tissue organization and its consequences to cognition among healthy young adults.

Tissue mechanics regulate brain development, homeostasis and disease

All cells sense and integrate mechanical and biochemical cues from their environment to orchestrate organismal development and maintain tissue homeostasis. Mechanotransduction is the evolutionarily conserved process whereby mechanical force is translated into biochemical signals that can influence cell differentiation, survival, proliferation and migration to change tissue behavior. Not surprisingly, disease develops if these mechanical cues are abnormal or are misinterpreted by the cells - for example, when interstitial pressure or compression force aberrantly increases, or the extracellular matrix (ECM) abnormally stiffens. Disease might also develop if the ability of cells to regulate their contractility becomes corrupted. Consistently, disease states, such as cardiovascular disease, fibrosis and cancer, are characterized by dramatic changes in cell and tissue mechanics, and dysregulation of forces at the cell and tissue level can activate mechanosignaling to compromise tissue integrity and function, and promote disease progression. In this Commentary, we discuss the impact of cell and tissue mechanics on tissue homeostasis and disease, focusing on their role in brain development, homeostasis and neural degeneration, as well as in brain cancer.

Medial temporal lobe viscoelasticity and relational memory performance

Structural and functional imaging studies have been among converging lines of evidence demonstrating the importance of the hippocampus in successful memory performance. The advent of a novel neuroimaging technique - magnetic resonance elastography (MRE) - now makes it possible for us to investigate the relationship between the microstructural integrity of hippocampal tissue and successful memory processing. Mechanical properties of brain tissue estimated with MRE provide a measure of the integrity of the underlying tissue microstructure and have proven to be sensitive measures of tissue health in neurodegeneration. However, until recently, MRE methods lacked sufficient resolution necessary to accurately examine specific neuroanatomical structures in the brain, and thus could not contribute to examination of specific structure-function relationships. In this study, we took advantage of recent developments in MRE spatial resolution and mechanical inversion techniques to measure the viscoelastic properties of the human hippocampus in vivo, and investigated how these properties reflect hippocampal function. Our data reveal a strong relationship between relative elastic/viscous behavior of the hippocampus and relational memory performance (N=20). This is the first report linking the mechanical properties of brain tissue with functional performance.

Magnetic Resonance Elastography Demonstrating Low Brain Stiffness in a Patient with Low-Pressure Hydrocephalus: Case Report

The authors describe the case of a 19-year-old female with shunted aqueductal stenosis who presented with low-pressure hydrocephalus that responded to negative pressure drainage. A magnetic resonance elastography scan performed 3 weeks later demonstrated very low brain tissue stiffness (high brain tissue compliance). An analysis of the importance of this finding in understanding this rare condition is discussed.