Viscoelastic polyacrylamide MR elastography phantoms with tunable damping ratio independent of shear stiffness

Physiologically modeled test samples with known properties and characteristics, or phantoms, are essential for developing sensitive, repeatable, and accurate quantitative MRI techniques. Magnetic resonance elastography (MRE) is one such technique used to estimate tissue mechanical properties, and it is advantageous to use phantoms with independently tunable mechanical properties to benchmark the accuracy of MRE methods. Phantoms with tunable shear stiffness are commonly used for MRE, but tuning the viscosity or damping ratio has proven to be difficult. A promising candidate for MRE phantoms with tunable damping ratio is polyacrylamide (PAA). While pure PAA has very low attenuation, viscoelastic hydrogels have been made by entrapping linear polyacrylamide strands (LPAA) within the PAA network. In this study, we evaluate the use of LPAA/PAA gels as physiologically accurate phantoms with tunable damping ratio, independent of shear stiffness, via MRE. Phantoms were made with 15.3 wt% PAA while the LPAA concentration ranged from 4.5 wt% to 8.0 wt%. MRE was performed at 9.4 T with 400 Hz vibration on all phantoms revealing a strong, positive correlation between damping ratio and LPAA content (p < 0.001). There was no significant correlation between shear stiffness and LPAA content, confirming a constant PAA concentration yielded constant shear stiffness. Rheometry at 10 Hz was performed to verify the damping ratio of the phantoms. Nearly identical slopes for damping ratio versus LPAA content were found from both MRE and rheometry (0.0073 and 0.0075 respectively). Ultimately, this study validates the adaptation of polyacrylamide gels into physiologically-relevant MRE phantoms to enable testing of MRE estimates of damping ratio.

Effect of Human Head Shape on the Risk of Traumatic Brain Injury: A Gaussian Process Regression-based Machine Learning Approach

INTRODUCTION

Computational head injury models are promising tools for understanding and predicting traumatic brain injuries. However, most available head injury models are "average" models that employ a single set of head geometry (e.g., 50th-percentile U.S. male) without considering variability in these parameters across the human population. A significant variability of head shapes exists in U.S. Army soldiers, evident from the Anthropometric Survey of U.S. Army Personnel (ANSUR II). The objective of this study is to elucidate the effects of head shape on the predicted risk of traumatic brain injury from computational head injury models.

MATERIALS AND METHODS

Magnetic resonance imaging scans of 25 human subjects are collected. These images are registered to the standard MNI152 brain atlas, and the resulting transformation matrix components (called head shape parameters) are used to quantify head shapes of the subjects. A generative machine learning model is used to generate 25 additional head shape parameter datasets to augment our database. Head injury models are developed for these head shapes, and a rapid injurious head rotation event is simulated to obtain several brain injury predictor variables (BIPVs): Peak cumulative maximum principal strain (CMPS), average CMPS, and the volume fraction of brain exceeding an injurious CMPS threshold. A Gaussian process regression model is trained between head shape parameters and BIPVs, which is then used to study the relative sensitivity of the various BIPVs on individual head shape parameters. We distinguish head shape parameters into 2 types: Scaling components ${T_{xx}}$, ${T_{yy}}$, and ${T_{zz}}$ that capture the breadth, length, and height of the head, respectively, and shearing components (${T_{xy}},{T_{xz}},{T_{yx}},{T_{yz}},{T_{zx}}$, and ${T_{zy}}$) that capture the relative skewness of the head shape.

RESULTS

An overall positive correlation is evident between scaling components and BIPVs. Notably, a very high, positive correlation is seen between the BIPVs and the head volume. As an example, a 57% increase in peak CMPS was noted between the smallest and the largest investigated head volume parameters. The variation in shearing components ${T_{xy}},{T_{xz}},{T_{yx}},{T_{yz}},{T_{zx}}$, and ${T_{zy}}$ on average does not cause notable changes in the BIPVs. From the Gaussian process regression model, all 3 BIPVs showed an increasing trend with each of the 3 scaling components, but the BIPVs are found to be most sensitive to the height dimension of the head. From the Sobol sensitivity analysis, the ${T_{zz}}$ scaling parameter contributes nearly 60% to the total variance in peak and average CMPS; ${T_{yy}}$ contributes approximately 20%, whereas ${T_{xx}}$ contributes less than 5%. The remaining contribution is from the 6 shearing components. Unlike peak and average CMPS, the VF-CMPS BIPV is associated with relatively evenly distributed Sobol indices across the 3 scaling parameters. Furthermore, the contribution of shearing components on the total variance in this case is negligible.

CONCLUSIONS

Head shape has a considerable influence on the injury predictions of computational head injury models. Available "average" head injury models based on a 50th-percentile U.S. male are likely associated with considerable uncertainty. In general, larger head sizes correspond to greater BIPV magnitudes, which point to potentially a greater injury risk under rapid neck rotation for people with larger heads.

Acute effects of high-intensity exercise on brain mechanical properties and cognitive function

Previous studies have shown that engagement in even a single session of exercise can improve cognitive performance in the short term. However, the underlying physiological mechanisms contributing to this effect are still being studied. Recently, with improvements to advanced quantitative neuroimaging techniques, brain tissue mechanical properties can be sensitively and noninvasively measured with magnetic resonance elastography (MRE) and regional brain mechanical properties have been shown to reflect individual cognitive performance. Here we assess brain mechanical properties before and immediately after engagement in a high-intensity interval training (HIIT) regimen, as well as one-hour post-exercise. We find that immediately after exercise, subjects in the HIIT group had an average global brain stiffness decrease of 4.2% (p < 0.001), and an average brain damping ratio increase of 3.1% (p = 0.002). In contrast, control participants who did not engage in exercise showed no significant change over time in either stiffness or damping ratio. Changes in brain mechanical properties with exercise appeared to be regionally dependent, with the hippocampus decreasing in stiffness by 10.4%. We also found that one-hour after exercise, brain mechanical properties returned to initial baseline values. The magnitude of changes to brain mechanical properties also correlated with improvements in reaction time on executive control tasks (Eriksen Flanker and Stroop) with exercise. Understanding the neural changes that arise in response to exercise may inform potential mechanisms behind improvements to cognitive performance with acute exercise.

Magnetic resonance elastography captures a transient benefit of exercise intervention on forebrain stiffness in a rat model of fetal alcohol spectrum disorders

BACKGROUND

Fetal alcohol spectrum disorders (FASD), a group of prevalent conditions resulting from prenatal alcohol exposure, affect the maturation of cerebral white matter as first identified with neuroimaging. However, traditional methods are unable to track subtle microstructural alterations to white matter. This preliminary study uses a highly sensitive and clinically translatable magnetic resonance elastography (MRE) protocol to assess brain tissue microstructure through its mechanical properties following an exercise intervention in a rat model of FASD.

METHODS

Female rat pups were either alcohol-exposed (AE) via intragastric intubation of alcohol in milk substitute (5.25 g/kg/day) or sham-intubated (SI) on postnatal days (PD) four through nine to model alcohol exposure during the brain growth spurt. On PD 30, half of AE and SI rats were randomly assigned to either a wheel-running or standard cage for 12 days. Magnetic resonance elastography was used to measure whole brain and callosal mechanical properties at the end of the intervention (around PD 42) and at 1 month post-intervention, and findings were validated with histological quantification of oligoglia.

RESULTS

Alcohol exposure reduced forebrain stiffness (p = 0.02) in standard-housed rats. The adolescent exercise intervention mitigated this effect, confirming that increased aerobic activity supports proper neurodevelopmental trajectories. Forebrain damping ratio was lowest in standard-housed AE rats (p < 0.01), but this effect was not mitigated by intervention exposure. At 1 month post-intervention, all rats exhibited comparable forebrain stiffness and damping ratio (p > 0.05). Callosal stiffness and damping ratio increased with age. With cessation of exercise, there was a negative rebound effect on the quantity of callosal oligodendrocytes, irrespective of treatment group, which diverged from our MRE results.

CONCLUSIONS

This is the first application of MRE to measure the brain's mechanical properties in a rodent model of FASD. MRE successfully captured alcohol-related changes in forebrain stiffness and damping ratio. Additionally, MRE identified an exercise-related increase to forebrain stiffness in AE rats.

Clinical application of magnetic resonance elastography in pediatric neurological disorders

Magnetic resonance elastography is a relatively new, rapidly evolving quantitative magnetic resonance imaging technique which can be used for mapping the viscoelastic mechanical properties of soft tissues. MR elastography measurements are akin to manual palpation but with the advantages of both being quantitative and being useful for regions which are not available for palpation, such as the human brain. MR elastography is noninvasive, well tolerated, and complements standard radiological and histopathological studies by providing in vivo measurements that reflect tissue microstructural integrity. While brain MR elastography studies in adults are becoming frequent, published studies on the utility of MR elastography in children are sparse. In this review, we have summarized the major scientific principles and recent clinical applications of brain MR elastography in diagnostic neuroscience and discuss avenues for impact in assessing the pediatric brain.

Effect of Direction and Frequency of Skull Motion on Mechanical Vulnerability of the Human Brain

Strain energy and kinetic energy in the human brain were estimated by magnetic resonance elastography (MRE) during harmonic excitation of the head, and compared to characterize the effect of loading direction and frequency on brain deformation. In brain MRE, shear waves are induced by external vibration of the skull and imaged by a modified MR imaging sequence; the resulting harmonic displacement fields are typically "inverted" to estimate mechanical properties, like stiffness or damping. However, measurements of tissue motion from MRE also illuminate key features of the response of the brain to skull loading. In this study, harmonic excitation was applied in two different directions and at five different frequencies from 20 to 90 Hz. Lateral loading induced primarily left-right head motion and rotation in the axial plane; occipital loading induced anterior-posterior head motion and rotation in the sagittal plane. The ratio of strain energy to kinetic energy (SE/KE) depended strongly on both direction and frequency. The ratio of SE/KE was approximately four times larger for lateral excitation than for occipital excitation and was largest at the lowest excitation frequencies studied. These results are consistent with clinical observations that suggest lateral impacts are more likely to cause injury than occipital or frontal impacts, and also with observations that the brain has low-frequency (∼10 Hz) natural modes of oscillation. The SE/KE ratio from brain MRE is potentially a simple and powerful dimensionless metric of brain vulnerability to deformation and injury.

Vascular determinants of hippocampal viscoelastic properties in healthy adults across the lifespan

Arterial stiffness and cerebrovascular pulsatility are non-traditional risk factors of Alzheimer's disease. However, there is a gap in understanding the earliest mechanisms that link these vascular determinants to brain aging. Changes to mechanical tissue properties of the hippocampus (HC), a brain structure essential for memory encoding, may reflect the impact of vascular dysfunction on brain aging. We tested the hypothesis that arterial stiffness and cerebrovascular pulsatility are related to HC tissue properties in healthy adults across the lifespan. Twenty-five adults underwent measurements of brachial blood pressure (BP), large elastic artery stiffness, middle cerebral artery pulsatility index (MCAv PI), and magnetic resonance elastography (MRE), a sensitive measure of HC viscoelasticity. Individuals with higher carotid pulse pressure (PP) exhibited lower HC stiffness (β = -0.39, r = -0.41, p = 0.05), independent of age and sex. Collectively, carotid PP and MCAv PI significantly explained a large portion of the total variance in HC stiffness (adjusted R2 = 0.41, p = 0.005) in the absence of associations with HC volumes. These cross-sectional findings suggest that the earliest reductions in HC tissue properties are associated with alterations in vascular function.

Individual Muscle Force Estimation in the Human Forearm Using Multi-Muscle MR Elastography (MM-MRE)

OBJECTIVE

To establish the sensitivity of magnetic resonance elastography (MRE) to active muscle contraction in multiple muscles of the forearm.

METHODS

We combined MRE of forearm muscles with an MRI-compatible device, the MREbot, to simultaneously measure the mechanical properties of tissues in the forearm and the torque applied by the wrist joint during isometric tasks. We measured shear wave speed of thirteen forearm muscles via MRE in a series of contractile states and wrist postures and fit these outputs to a force estimation algorithm based on a musculoskeletal model.

RESULTS

Shear wave speed changed significantly upon several factors, including whether the muscle was recruited as an agonist or antagonist (p = 0.0019), torque amplitude (p = <0.0001), and wrist posture (p = 0.0002). Shear wave speed increased significantly during both agonist (p = <0.0001) and antagonist (p = 0.0448) contraction. Additionally, there was a greater increase in shear wave speed at greater levels of loading. The variations due to these factors indicate the sensitivity to functional loading of muscle. Under the assumption of a quadratic relationship between shear wave speed and muscle force, MRE measurements accounted for an average of 70% of the variance in the measured joint torque.

CONCLUSION

This study shows the ability of MM-MRE to capture variations in individual muscle shear wave speed due to muscle activation and presents a method to estimate individual muscle force through MM-MRE derived measurements of shear wave speed.

SIGNIFICANCE

MM-MRE could be used to establish normal and abnormal muscle co-contraction patterns in muscles of the forearm controlling hand and wrist function.

Monitoring lasting changes to brain tissue integrity through mechanical properties following adolescent exercise intervention in a rat model of Fetal Alcohol Spectrum Disorders

Background

Fetal Alcohol Spectrum Disorders (FASD) encompass a group of highly prevalent conditions resulting from prenatal alcohol exposure. Alcohol exposure during the third trimester of pregnancy overlapping with the brain growth spurt is detrimental to white matter growth and myelination, particularly in the corpus callosum, ultimately affecting tissue integrity in adolescence. Traditional neuroimaging techniques have been essential for assessing neurodevelopment in affected youth; however, these methods are limited in their capacity to track subtle microstructural alterations to white matter, thus restricting their effectiveness in monitoring therapeutic intervention. In this preliminary study we use a highly sensitive and clinically translatable Magnetic Resonance Elastography (MRE) protocol for assessing brain tissue microstructure through its mechanical properties following an exercise intervention in a rat model of FASD.

Methods

Rat pups were divided into two groups: alcohol-exposed (AE) pups which received alcohol in milk substitute (5.25 g/kg/day) via intragastric intubation on postnatal days (PD) four through nine during the rat brain growth spurt (Dobbing and Sands, 1979), or sham-intubated (SI) controls. In adolescence, on PD 30, half AE and SI rats were randomly assigned to either a modified home cage with free access to a running wheel or to a new home cage for 12 days (Gursky and Klintsova, 2017). Previous studies conducted in the lab have shown that 12 days of voluntary exercise intervention in adolescence immediately ameliorated callosal myelination in AE rats (Milbocker et al., 2022, 2023). MRE was used to measure longitudinal changes to mechanical properties of the whole brain and the corpus callosum at intervention termination and one-month post-intervention. Histological quantification of precursor and myelinating oligoglia in corpus callosum was performed one-month post-intervention.

Results

Prior to intervention, AE rats had lower forebrain stiffness in adolescence compared to SI controls ( p = 0.02). Exercise intervention immediately mitigated this effect in AE rats, resulting in higher forebrain stiffness post-intervention in adolescence. Similarly, we discovered that forebrain damping ratio was lowest in AE rats in adolescence ( p < 0.01), irrespective of intervention exposure. One-month post-intervention in adulthood, AE and SI rats exhibited comparable forebrain stiffness and damping ratio (p > 0.05). Taken together, these MRE data suggest that adolescent exercise intervention supports neurodevelopmental "catch-up" in AE rats. Analysis of the stiffness and damping ratio of the body of corpus callosum revealed that these measures increased with age. Finally, histological quantification of myelinating oligodendrocytes one-month post-intervention revealed a negative rebound effect of exercise cessation on the total estimate of these cells in the body of corpus callosum, irrespective of treatment group which was not convergent with noninvasive MRE measures.

Conclusions

This is the first application of MRE to measure changes in brain mechanical properties in a rodent model of FASD. MRE successfully captured alcohol-related changes to forebrain stiffness and damping ratio in adolescence. These preliminary findings expand upon results from previous studies which used traditional diffusion neuroimaging to identify structural changes to the adolescent brain in rodent models of FASD (Milbocker et al., 2022; Newville et al., 2017). Additionally, in vivo MRE identified an exercise-related alteration to forebrain stiffness that occurred in adolescence, immediately post-intervention.

Influence of mild cognitive impairment and body mass index on white matter integrity assessed by diffusion tensor imaging

Mild cognitive impairment (MCI), a prodromal stage of Alzheimer's disease, is characterized by decreased memory and cognition, which are linked to degenerative changes in the brain. To assess whether white matter (WM) integrity is compromised in MCI, we collected diffusion-weighted images from 60 healthy older adults (OA) (69.16 ± 0.7) and 20 older adults with amnestic MCI (72.45 ± 1.9). WM integrity differences were examined using Tract-Based Spatial Statistics (TBSS). We hypothesized that those with MCI would have diminished WM integrity relative to OA. In a whole-brain comparison, those with MCI showed higher axial diffusivity in the splenium (SCC) and body of the corpus callosum (BCC), superior corona radiata (SCR), and the retrolenticular part of the internal capsule (RLIC) (p's < .05 TFCE-corrected). Additionally, significant between-group connectivity differences were observed using probabilistic tractography between the SCC, chosen from the TBSS results, and forceps major and minor (p-value's < .05). To further relate a physical health indicator to WM alterations, linear regression showed significant interactions between cognitive status and body mass index (BMI) on diffusivity outcome measures from probabilistic tractography (p-value-'s < .05). Additionally, we examined the association between relational memory, BMI, and WM integrity. WM integrity was positively associated with relational memory performance. These findings suggest that these regions may be more sensitive to early markers of neurodegenerative disease and health behaviors, suggesting that modifiable lifestyle factors may affect white matter integrity.

Mechanical stiffness and anisotropy measured by MRE during brain development in the minipig

The relationship between brain development and mechanical properties of brain tissue is important, but remains incompletely understood, in part due to the challenges in measuring these properties longitudinally over time. In addition, white matter, which is composed of aligned, myelinated, axonal fibers, may be mechanically anisotropic. Here we use data from magnetic resonance elastography (MRE) and diffusion tensor imaging (DTI) to estimate anisotropic mechanical properties in six female Yucatan minipigs at ages from 3 to 6 months. Fiber direction was estimated from the principal axis of the diffusion tensor in each voxel. Harmonic shear waves in the brain were excited by three different configurations of a jaw actuator and measured using a motion-sensitive MR imaging sequence. Anisotropic mechanical properties are estimated from displacement field and fiber direction data with a finite element- based, transversely-isotropic nonlinear inversion (TI-NLI) algorithm. TI-NLI finds spatially resolved TI material properties that minimize the error between measured and simulated displacement fields. Maps of anisotropic mechanical properties in the minipig brain were generated for each animal at all four ages. These maps show that white matter is more dissipative and anisotropic than gray matter, and reveal significant effects of brain development on brain stiffness and structural anisotropy. Changes in brain mechanical properties may be a fundamental biophysical signature of brain development.

Measurement of relative motion of the brain and skull in the mini-pig in-vivo

The mechanical role of the skull-brain interface is critical to the pathology of concussion and traumatic brain injury (TBI) and may evolve with age. Here we characterize the skull-brain interface in juvenile, female Yucatan mini-pigs from 3 to 6 months old using techniques from magnetic resonance elastography (MRE). The displacements of the skull and brain were measured by a motion-sensitive MR imaging sequence during low-amplitude harmonic motion of the head. Each animal was scanned four times at 1-month intervals. Harmonic motion at 100 Hz was excited by three different configurations of a jaw actuator in order to vary the direction of loading. Rigid-body linear motions of the brain and skull were similar, although brain rotations were consistently smaller than corresponding skull rotations. Relative displacements between the brain and skull were estimated for voxels on the surface of the brain. Amplitudes of relative displacements between skull and brain were 1-3 μm, approximately 25-50% of corresponding skull displacements. Maps of relative displacement showed variations by anatomical region, and the normal component of relative displacement was consistently 25-50% of the tangential component. These results illuminate the mechanics of the skull-brain interface in a gyrencephalic animal model relevant to human brain injury and development.

Comparison of Deformation Patterns Excited in the Human Brain in vivo by Harmonic and Impulsive Skull Motion

Noninvasive measurements of brain deformation in human participants in vivo are needed to develop models of brain biomechanics and understand traumatic brain injury (TBI). Tagged magnetic resonance imaging (tagged MRI) and magnetic resonance elastography (MRE) are two techniques to study human brain deformation; these techniques differ in the type of motion and difficulty of implementation. In this study, oscillatory strain fields in the human brain caused by impulsive head acceleration and measured by tagged MRI were compared quantitatively to strain fields measured by MRE during harmonic head motion at 10 and 50 Hz. Strain fields were compared by registering to a common anatomical template, then computing correlations between the registered strain fields. Correlations were computed between tagged MRI strain fields in six participants and MRE strain fields at 10 Hz and 50 Hz in six different participants. Correlations among strain fields within the same experiment type were compared statistically to correlations from different experiment types. Strain fields from harmonic head motion at 10 Hz imaged by MRE were qualitatively and quantitatively similar to modes excited by impulsive head motion, imaged by tagged MRI. Notably, correlations between strain fields from 10 Hz MRE and tagged MRI did not differ significantly from correlations between strain fields from tagged MRI. These results suggest that low-frequency modes of oscillation dominate the response of the brain during impact. Thus, low-frequency MRE, which is simpler and more widely available than tagged MRI, can be used to illuminate the brain's response to head impact.

Transversely-isotropic brain in vivo MR elastography with anisotropic damping

Measuring tissue parameters from increasingly sophisticated mechanical property models may uncover new contrast mechanisms with clinical utility. Building on previous work on in vivo brain MR elastography (MRE) with a transversely-isotropic with isotropic damping (TI-ID) model, we explore a new transversely-isotropic with anisotropic damping (TI-AD) model that involves six independent parameters describing direction-dependent behavior for both stiffness and damping. The direction of mechanical anisotropy is determined by diffusion tensor imaging and we fit three complex-valued moduli distributions across the full brain volume to minimize differences between measured and modeled displacements. We demonstrate spatially accurate property reconstruction in an idealized shell phantom simulation, as well as an ensemble of 20 realistic, randomly-generated simulated brains. We characterize the simulated precisions of all six parameters across major white matter tracts to be high, suggesting that they can be measured independently with acceptable accuracy from MRE data. Finally, we present in vivo anisotropic damping MRE reconstruction data. We perform t-tests on eight repeated MRE brain exams on a single-subject, and find that the three damping parameters are statistically distinct for most tracts, lobes and the whole brain. We also show that population variations in a 17-subject cohort exceed single-subject measurement repeatability for most tracts, lobes and whole brain, for all six parameters. These results suggest that the TI-AD model offers new information that may support differential diagnosis of brain diseases.

Reverberant magnetic resonance elastographic imaging using a single mechanical driver

Reverberant elastography provides fast and robust estimates of shear modulus; however, its reliance on multiple mechanical drivers hampers clinical utility. In this work, we hypothesize that for constrained organs such as the brain, reverberant elastography can produce accurate magnetic resonance elastograms with a single mechanical driver. To corroborate this hypothesis, we performed studies on healthy volunteers (n= 3); and a constrained calibrated brain phantom containing spherical inclusions with diameters ranging from 4-18 mm. In both studies (i.e. phantom and clinical), imaging was performed at frequencies of 50 and 70 Hz. We used the accuracy and contrast-to-noise ratio performance metrics to evaluate reverberant elastograms relative to those computed using the established subzone inversion method. Errors incurred in reverberant elastograms varied from 1.3% to 16.6% when imaging at 50 Hz and 3.1% and 16.8% when imaging at 70 Hz. In contrast, errors incurred in subzone elastograms ranged from 1.9% to 13% at 50 Hz and 3.6% to 14.9% at 70 Hz. The contrast-to-noise ratio of reverberant elastograms ranged from 63.1 to 73 dB compared to 65 to 66.2 dB for subzone elastograms. The average global brain shear modulus estimated from reverberant and subzone elastograms was 2.36 ± 0.07 kPa and 2.38 ± 0.11 kPa, respectively, when imaging at 50 Hz and 2.70 ± 0.20 kPa and 2.89 ± 0.60 kPa respectively, when imaging at 70 Hz. The results of this investigation demonstrate that reverberant elastography can produce accurate, high-quality elastograms of the brain with a single mechanical driver.

Mechanical Property Based Brain Age Prediction using Convolutional Neural Networks

Brain age is a quantitative estimate to explain an individual's structural and functional brain measurements relative to the overall population and is particularly valuable in describing differences related to developmental or neurodegenerative pathology. Accurately inferring brain age from brain imaging data requires sophisticated models that capture the underlying age-related brain changes. Magnetic resonance elastography (MRE) is a phase contrast MRI technology that uses external palpations to measure brain mechanical properties. Mechanical property measures of viscoelastic shear stiffness and damping ratio have been found to change across the entire life span and to reflect brain health due to neurodegenerative diseases and even individual differences in cognitive function. Here we develop and train a multi-modal 3D convolutional neural network (CNN) to model the relationship between age and whole brain mechanical properties. After training, the network maps the measurements and other inputs to a brain age prediction. We found high performance using the 3D maps of various mechanical properties to predict brain age. Stiffness maps alone were able to predict ages of the test group subjects with a mean absolute error (MAE) of 3.76 years, which is comparable to single inputs of damping ratio (MAE: 3.82) and outperforms single input of volume (MAE: 4.60). Combining stiffness and volume in a multimodal approach performed the best, with an MAE of 3.60 years, whereas including damping ratio worsened model performance. Our results reflect previous MRE literature that had demonstrated that stiffness is more strongly related to chronological age than damping ratio. This machine learning model provides the first prediction of brain age from brain biomechanical data-an advancement towards sensitively describing brain integrity differences in individuals with neuropathology.

In vivoestimation of anisotropic mechanical properties of the gastrocnemius during functional loading with MR elastography

Objective.In vivoimaging assessments of skeletal muscle structure and function allow for longitudinal quantification of tissue health. Magnetic resonance elastography (MRE) non-invasively quantifies tissue mechanical properties, allowing for evaluation of skeletal muscle biomechanics in response to loading, creating a better understanding of muscle functional health.Approach. In this study, we analyze the anisotropic mechanical response of calf muscles using MRE with a transversely isotropic, nonlinear inversion algorithm (TI-NLI) to investigate the role of muscle fiber stiffening under load. We estimate anisotropic material parameters including fiber shear stiffness (μ1), substrate shear stiffness (μ2), shear anisotropy (ϕ), and tensile anisotropy (ζ) of the gastrocnemius muscle in response to both passive and active tension.Main results. In passive tension, we found a significant increase inμ1,ϕ,andζwith increasing muscle length. While in active tension, we observed increasingμ2and decreasingϕandζduring active dorsiflexion and plantarflexion-indicating less anisotropy-with greater effects when the muscles act as agonist.Significance. The study demonstrates the ability of this anisotropic MRE method to capture the multifaceted mechanical response of skeletal muscle to tissue loading from muscle lengthening and contraction.

Characterization of material properties and deformation in the ANGUS phantom during mild head impacts using MRI

Traumatic brain injury (TBI) is a major health concern affecting both military and civilian populations. Despite notable advances in TBI research in recent years, there remains a significant gap in linking the impulsive loadings from a blast or a blunt impact to the clinical injury patterns observed in TBI. Synthetic head models or phantoms can be used to establish this link as they can be constructed with geometry, anatomy, and material properties that match the human brain, and can be used as an alternative to animal models. This study presents one such phantom called the Anthropomorphic Neurologic Gyrencephalic Unified Standard (ANGUS) phantom, which is an idealized gyrencephalic brain phantom composed of polyacrylamide gel. Here we mechanically characterized the ANGUS phantom using tagged magnetic resonance imaging (MRI) and magnetic resonance elastography (MRE), and then compared the outcomes to data obtained in healthy volunteers. The direct comparison between the phantom's response and the data from a cohort of in vivo human subjects demonstrate that the ANGUS phantom may be an appropriate model for bulk tissue response and gyral dynamics of the human brain under small amplitude linear impulses. However, the phantom's response differs from that of the in vivo human brain under rotational impacts, suggesting avenues for future improvements to the phantom.

Hippocampal subfield viscoelasticity in amnestic mild cognitive impairment evaluated with MR elastography

Hippocampal subfields (HCsf) are brain regions important for memory function that are vulnerable to decline with amnestic mild cognitive impairment (aMCI), which is often a preclinical stage of Alzheimer's disease. Studies in aMCI patients often assess HCsf tissue integrity using measures of volume, which has little specificity to microstructure and pathology. We use magnetic resonance elastography (MRE) to examine the viscoelastic mechanical properties of HCsf tissue, which is related to structural integrity, and sensitively detect differences in older adults with aMCI compared to an age-matched control group. Group comparisons revealed HCsf viscoelasticity is differentially affected in aMCI, with CA1-CA2 and DG-CA3 exhibiting lower stiffness and CA1-CA2 exhibiting higher damping ratio, both indicating poorer tissue integrity in aMCI. Including HCsf stiffness in a logistic regression improves classification of aMCI beyond measures of volume alone. Additionally, lower DG-CA3 stiffness predicted aMCI status regardless of DG-CA3 volume. These findings showcase the benefit of using MRE in detecting subtle pathological tissue changes in individuals with aMCI via the HCsf particularly affected in the disease.

Infertility prevalence and the methods of estimation from 1990 to 2021: a systematic review and meta-analysis

STUDY QUESTION

What is the contemporary prevalence of infertility in world populations and how do they differ by methodological and study characteristics?

SUMMARY ANSWER

Pooled estimates of lifetime and period prevalence of 12-month infertility were 17.5% and 12.6%, respectively, but this varied by study population and methodological approach.

WHAT IS KNOWN ALREADY

Infertility affects millions of individuals worldwide. Accurate measures of its magnitude are needed to effectively address and manage the condition. There are distinct challenges and variation in how infertility is defined and measured, limiting comparability of estimates across studies. Further research is needed to understand whether and how differences in methodological approaches and study characteristics account for heterogeneity in estimates.

STUDY DESIGN SIZE DURATION

We conducted a systematic review and meta-analysis. Six electronic databases, websites of relevant organizations, and conference proceedings were systematically searched. Searches were limited to those published between 1 January 1990 and 11 March 2021, with no language restrictions.

PARTICIPANTS/MATERIALS SETTING METHODS

Descriptive and random-effects meta-analysis models were used to examine range of estimates and generate estimates of pooled lifetime and period prevalence of 12-month infertility, respectively, among representative populations. Meta-regression using restricted maximum likelihood was applied to account for definitional and study characteristics and to obtain adjusted estimates. Risk of bias was assessed with a validated tool.

MAIN RESULTS AND THE ROLE OF CHANCE

The search yielded 12 241 unique records of which 133 studies met the criteria for the systematic review. There were 65 and 69 studies that provided data for lifetime and period prevalence of 12-month infertility, respectively. Five methodological approaches were identified: prospective time-to-pregnancy (TTP) design, current duration design, retrospective TTP design, self-reported infertility measure and constructed infertility measure. Ranges for lifetime (3.3-39.7%) and period estimates (1.6-34.0%) were similar and wide even after accounting for methodological and study characteristics. Pooled estimates of lifetime and period prevalence were 17.5% (95% CI: 15.0, 20.3, n = 37 studies, I ² = 99.5%) and 12.6% (95% CI: 10.7, 14.6, n = 43 studies, I ² = 99.8%), respectively, with some variation in magnitude by region and methodological approach, but with most CIs overlapping.

LIMITATIONS REASONS FOR CAUTION

Pooled estimates generated from meta-analysis were derived from 12-month infertility prevalence estimates that were heterogeneous across different domains, even after adjusting for definitional and study characteristics. The number of studies was small for certain strata from which pooled estimates were derived (e.g. there were only two studies for lifetime prevalence in Africa).

WIDER IMPLICATIONS OF THE FINDINGS

While findings show a high prevalence of infertility globally and regionally, it also reveals variation in measures to ascertain and compare infertility prevalence. More systematic and comprehensive collection of data using a consistent definition is needed to improve infertility prevalence estimates at global, regional and country-levels.

STUDY FUNDING/COMPETING INTERESTS

This work was supported by the World Health Organization. The authors have no conflicts of interest.

REGISTRATION NUMBER

PROSPERO CRD42020211704.

Structure-Function Dissociations of Human Hippocampal Subfield Stiffness and Memory Performance

Aging and neurodegenerative diseases lead to decline in thinking and memory ability. The subfields of the hippocampus (HCsf) play important roles in memory formation and recall. Imaging techniques sensitive to the underlying HCsf tissue microstructure can reveal unique structure-function associations and their vulnerability in aging and disease. The goal of this study was to use magnetic resonance elastography (MRE), a noninvasive MR imaging-based technique that can quantitatively image the viscoelastic mechanical properties of tissue to determine the associations of HCsf stiffness with different cognitive domains across the lifespan. Eighty-eight adult participants completed the study (age 23-81 years, male/female 36/51), in which we aimed to determine which HCsf regions most strongly correlated with different memory performance outcomes and if viscoelasticity of specific HCsf regions mediated the relationship between age and performance. Our results revealed that both interference cost on a verbal memory task and relational memory task performance were significantly related to cornu ammonis 1-2 (CA1-CA2) stiffness (p = 0.018 and p = 0.011, respectively), with CA1-CA2 stiffness significantly mediating the relationship between age and interference cost performance (p = 0.031). There were also significant associations between delayed free verbal recall performance and stiffness of both the dentate gyrus-cornu ammonis 3 (DG-CA3; p = 0.016) and subiculum (SUB; p = 0.032) regions. This further exemplifies the functional specialization of HCsf in declarative memory and the potential use of MRE measures as clinical biomarkers in assessing brain health in aging and disease.SIGNIFICANCE STATEMENT Hippocampal subfields are cytoarchitecturally unique structures involved in distinct aspects of memory processing. Magnetic resonance elastography is a technique that can noninvasively image tissue viscoelastic mechanical properties, potentially serving as sensitive biomarkers of aging and neurodegeneration related to functional outcomes. High-resolution in vivo imaging has invigorated interest in determining subfield functional specialization and their differential vulnerability in aging and disease. Applying MRE to probe subfield-specific cognitive correlates will indicate that measures of subfield stiffness can determine the integrity of structures supporting specific domains of memory performance. These findings will further validate our high-resolution MRE method and support the potential use of subfield stiffness measures as clinical biomarkers in classifying aging and disease states.

Childhood trauma moderates morphometric associations between orbitofrontal cortex and amygdala: implications for pathological personality traits

BACKGROUND

Research has demonstrated that chronic stress exposure early in development can lead to detrimental alterations in the orbitofrontal cortex (OFC)-amygdala circuit. However, the majority of this research uses functional neuroimaging methods, and thus the extent to which childhood trauma corresponds to morphometric alterations in this limbic-cortical network has not yet been investigated. This study had two primary objectives: (i) to test whether anatomical associations between OFC-amygdala differed between adults as a function of exposure to chronic childhood assaultive trauma and (ii) to test how these environment-by-neurobiological effects relate to pathological personality traits.

METHODS

Participants were 137 ethnically diverse adults (48.1% female) recruited from the community who completed a clinical diagnostic interview, a self-report measure of pathological personality traits, and anatomical MRI scans.

RESULTS

Findings revealed that childhood trauma moderated bilateral OFC-amygdala volumetric associations. Specifically, adults with childhood trauma exposure showed a positive association between medial OFC volume and amygdalar volume, whereas adults with no childhood exposure showed the negative OFC-amygdala structural association observed in prior research with healthy samples. Examination of the translational relevance of trauma-related alterations in OFC-amygdala volumetric associations for disordered personality traits revealed that trauma exposure moderated the association of OFC volume with antagonistic and disinhibited phenotypes, traits characteristic of Cluster B personality disorders.

CONCLUSIONS

The OFC-amygdala circuit is a potential anatomical pathway through which early traumatic experiences perpetuate emotional dysregulation into adulthood and confer risk for personality pathology. Results provide novel evidence of divergent neuroanatomical pathways to similar personality phenotypes depending on early trauma exposure.

OSCILLATE: A low-rank approach for accelerated magnetic resonance elastography

PURPOSE

MR elastography (MRE) is a technique to characterize brain mechanical properties in vivo. Due to the need to capture tissue deformation in multiple directions over time, MRE is an inherently long acquisition, which limits achievable resolution and use in challenging populations. The purpose of this work is to develop a method for accelerating MRE acquisition by using low-rank image reconstruction to exploit inherent spatiotemporal correlations in MRE data.

THEORY AND METHODS

The proposed MRE sampling and reconstruction method, OSCILLATE (Observing Spatiotemporal Correlations for Imaging with Low-rank Leveraged Acceleration in Turbo Elastography), involves alternating which k-space points are sampled between each repetition by a reduction factor, ROSC. Using a predetermined temporal basis from a low-resolution navigator in a joint low-rank image reconstruction, all images can be accurately reconstructed from a reduced amount of k-space data.

RESULTS

Decomposition of MRE displacement data demonstrated that, on average, 96.1% of all energy from an MRE dataset is captured at rank L = 12 (reduced from a full rank of 24). Retrospectively undersampling data with ROSC  = 2 and reconstructing at low-rank (L = 12) yields highly accurate stiffness maps with voxel-wise error of 5.8% ± 0.7%. Prospectively undersampled data at ROSC  = 2 were successfully reconstructed without loss of material property map fidelity, with average global stiffness error of 1.0% ± 0.7% compared to fully sampled data.

CONCLUSIONS

OSCILLATE produces whole-brain MRE data at 2 mm isotropic resolution in 1 min 48 s.

Development and validation of subject-specific 3D human head models based on a nonlinear visco-hyperelastic constitutive framework

Computational head models are promising tools for understanding and predicting traumatic brain injuries. Most available head models are developed using inputs (i.e. head geometry, material properties and boundary conditions) from experiments on cadavers or animals and employ hereditary integral-based constitutive models that assume linear viscoelasticity in part of the rate-sensitive material response. This leads to high uncertainty and poor accuracy in capturing the nonlinear brain tissue response. To resolve these issues, a framework for the development of subject-specific three-dimensional head models is proposed, in which all inputs are derived in vivo from the same living human subject: head geometry via magnetic resonance imaging (MRI), brain tissue properties via magnetic resonance elastography (MRE), and full-field strain-response of the brain under rapid head rotation via tagged MRI. A nonlinear, viscous dissipation-based visco-hyperelastic constitutive model is employed to capture brain tissue response. Head models are validated using quantitative metrics that compare spatial strain distribution, temporal strain evolution, and the magnitude of strain maxima, with the corresponding experimental observations from tagged MRI. Results show that our head models accurately capture the strain-response of the brain. Further, employment of the nonlinear visco-hyperelastic constitutive framework provides improvements in the prediction of peak strains and temporal strain evolution over hereditary integral-based models.

Mapping brain mechanical property maturation from childhood to adulthood

Magnetic resonance elastography (MRE) is a phase contrast MRI technique which uses external palpation to create maps of brain mechanical properties noninvasively and in vivo. These mechanical properties are sensitive to tissue microstructure and reflect tissue integrity. MRE has been used extensively to study aging and neurodegeneration, and to assess individual cognitive differences in adults, but little is known about mechanical properties of the pediatric brain. Here we use high-resolution MRE imaging in participants of ages ranging from childhood to adulthood to understand brain mechanical properties across brain maturation. We find that brain mechanical properties differ considerably between childhood and adulthood, and that neuroanatomical subregions have differing maturational trajectories. Overall, we observe lower brain stiffness and greater brain damping ratio with increasing age from 5 to 35 years. Gray and white matter change differently during maturation, with larger changes occurring in gray matter for both stiffness and damping ratio. We also found that subregions of cortical and subcortical gray matter change differently, with the caudate and thalamus changing the most with age in both stiffness and damping ratio, while cortical subregions have different relationships with age, even between neighboring regions. Understanding how brain mechanical properties mature using high-resolution MRE will allow for a deeper understanding of the neural substrates supporting brain function at this age and can inform future studies of atypical maturation.

Data-driven Uncertainty Quantification in Computational Human Head Models

Computational models of the human head are promising tools for estimating the impact-induced response of the brain, and thus play an important role in the prediction of traumatic brain injury. The basic constituents of these models (i.e., model geometry, material properties, and boundary conditions) are often associated with significant uncertainty and variability. As a result, uncertainty quantification (UQ), which involves quantification of the effect of this uncertainty and variability on the simulated response, becomes critical to ensure reliability of model predictions. Modern biofidelic head model simulations are associated with very high computational cost and high-dimensional inputs and outputs, which limits the applicability of traditional UQ methods on these systems. In this study, a two-stage, data-driven manifold learning-based framework is proposed for UQ of computational head models. This framework is demonstrated on a 2D subject-specific head model, where the goal is to quantify uncertainty in the simulated strain fields (i.e., output), given variability in the material properties of different brain substructures (i.e., input). In the first stage, a data-driven method based on multi-dimensional Gaussian kernel-density estimation and diffusion maps is used to generate realizations of the input random vector directly from the available data. Computational simulations of a small number of realizations provide input-output pairs for training data-driven surrogate models in the second stage. The surrogate models employ nonlinear dimensionality reduction using Grassmannian diffusion maps, Gaussian process regression to create a low-cost mapping between the input random vector and the reduced solution space, and geometric harmonics models for mapping between the reduced space and the Grassmann manifold. It is demonstrated that the surrogate models provide highly accurate approximations of the computational model while significantly reducing the computational cost. Monte Carlo simulations of the surrogate models are used for uncertainty propagation. UQ of the strain fields highlights significant spatial variation in model uncertainty, and reveals key differences in uncertainty among commonly used strain-based brain injury predictor variables.

Mechanical Properties of the Developing Brain are Associated with Language Input and Vocabulary Outcome

The quality of language that children hear in their environment is associated with the development of language-related brain regions, in turn promoting vocabulary knowledge. Although informative, it remains unknown how these environmental influences alter the structure of neural tissue and subsequent vocabulary outcomes. The current study uses magnetic resonance elastography (MRE) to examine how children's language environments underlie brain tissue mechanical properties, characterized as brain tissue stiffness and damping ratio, and promote vocabulary knowledge. Twenty-five children, ages 5-7, had their audio and video recorded while engaging in a play session with their parents. Children also completed the Picture Vocabulary Task (from NIH Toolbox) and participated in an MRI, where MRE and anatomical images were acquired. Higher quality input was associated with greater stiffness in the bilateral inferior frontal gyrus and right superior temporal gyrus, whereas greater vocabulary knowledge was associated with lower damping ratio in the right inferior frontal gyrus. These findings suggest changes in neural tissue composition are sensitive to malleable aspects of the environment, whereas tissue organization is more strongly associated with vocabulary outcome. Notably, these associations were independent of maternal education, suggesting more proximal measures of a child's environment may be the source of differences in neural tissue structure underlying variability in vocabulary outcomes.

Relationships between aggression, sensation seeking, brain stiffness, and head impact exposure: Implications for head impact prevention in ice hockey

OBJECTIVES

The objectives of this study were to (1) examine the relationship between the number of head impacts sustained in a season of men's collegiate club ice hockey and behavioral traits of aggression and sensation seeking, and (2) explore the neural correlates of these behaviors using neuroimaging.

DESIGN

Retrospective cohort study.

METHODS

Participants (n = 18) completed baseline surveys to quantify self-reported aggression and sensation-seeking tendencies. Aggression related to playing style was quantified through penalty minutes accrued during a season. Participants wore head impact sensors throughout a season to quantify the number of head impacts sustained. Participants (n = 15) also completed baseline anatomical and magnetic elastography neuroimaging scans to measure brain volumetric and viscoelastic properties. Pearson correlation analyses were performed to examine relationships between (1) impacts, aggression, and sensation seeking, and (2) impacts, aggression, and sensation seeking and brain volume, stiffness, and damping ratio, as an exploratory analysis.

RESULTS

Number of head impacts sustained was significantly related to the number of penalty minutes accrued, normalized to number of games played (r = .62, p < .01). Our secondary, exploratory analysis revealed that number of impacts, sensation seeking, and aggression were related to stiffness or damping ratio of the thalamus, amygdala, hippocampus, and frontal cortex, but not volume.

CONCLUSIONS

A more aggressive playing style was related to an increased number of head impacts sustained, which may provide evidence for future studies of head impact prevention. Further, magnetic resonance elastography may aid to monitor behavior or head impact exposure. Researchers should continue to examine this relationship and consider targeting behavioral modification programs of aggression to decrease head impact exposure in ice hockey.

Mapping heterogenous anisotropic tissue mechanical properties with transverse isotropic nonlinear inversion MR elastography

The white matter tracts of brain tissue consist of highly-aligned, myelinated fibers; white matter is structurally anisotropic and is expected to exhibit anisotropic mechanical behavior. In vivo mechanical properties of tissue can be imaged using magnetic resonance elastography (MRE). MRE can detect and monitor natural and disease processes that affect tissue structure; however, most MRE inversion algorithms assume locally homogenous properties and/or isotropic behavior, which can cause artifacts in white matter regions. A heterogeneous, model-based transverse isotropic implementation of a subzone-based nonlinear inversion (TI-NLI) is demonstrated. TI-NLI reconstructs accurate maps of the shear modulus, damping ratio, shear anisotropy, and tensile anisotropy of in vivo brain tissue using standard MRE motion measurements and fiber directions estimated from diffusion tensor imaging (DTI). TI-NLI accuracy was investigated with using synthetic data in both controlled and realistic settings: excellent quantitative and spatial accuracy was observed and cross-talk between estimated parameters was minimal. Ten repeated, in vivo, MRE scans acquired from a healthy subject were co-registered to demonstrate repeatability of the technique. Good resolution of anatomical structures and bilateral symmetry were evident in MRE images of all mechanical property types. Repeatability was similar to isotropic MRE methods and well within the limits required for clinical success. TI-NLI MRE is a promising new technique for clinical research into anisotropic tissues such as the brain and muscle.

Altered Brain Functional Connectivity in the Frontoparietal Network following an Ice Hockey Season

AbstractSustaining sports-related head impacts has been reported to result in neurological changes that potentially lead to later-life neurological disease. Advanced neuroimaging techniques have been used to detect subtle neurological effects resulting from head impacts, even after a single competitive season. The current study used resting-state functional magnetic resonance imaging to assess changes in functional connectivity of the frontoparietal network, a brain network responsible for executive functioning, in collegiate club ice hockey players over one season. Each player was scanned before and after the season and wore accelerometers to measure head impacts at practices and home games throughout the season. We examined pre- to post-season differences in connectivity within the frontoparietal and default mode networks, as well as the relationship between the total number of head impacts sustained and changes in connectivity. We found a significant interaction between network region of interest and time point (p = 0.016), in which connectivity between the left and right posterior parietal cortex seed regions increased over the season (p < 0.01). Number of impacts had a significant effect on frontoparietal network connectivity, such that more impacts were related to greater connectivity differences over the season (p = 0.042). Overall, functional connectivity increased in ice hockey athletes over a season between regions involved in executive functioning, and sensory integration, in particular. Furthermore, those who sustained more impacts had the greatest changes in connectivity. Consistent with prior findings in resting-state sports-related head impact literature, these findings have been suggested to represent brain injury.

Evaluation of cerebral cortex viscoelastic property estimation with nonlinear inversion magnetic resonance elastography

Objective. Magnetic resonance elastography (MRE) of the brain has shown promise as a sensitive neuroimaging biomarker for neurodegenerative disorders; however, the accuracy of performing MRE of the cerebral cortex warrants investigation due to the unique challenges of studying thinner and more complex geometries.Approach. A series of realistic, whole-brain simulation experiments are performed to examine the accuracy of MRE to measure the viscoelasticity (shear stiffness,μ, and damping ratio, ξ) of cortical structures predominantly effected in aging and neurodegeneration. Variations to MRE spatial resolution and the regularization of a nonlinear inversion (NLI) approach are examined.Main results. Higher-resolution MRE displacement data (1.25 mm isotropic resolution) and NLI with a low soft prior regularization weighting provided minimal measurement error compared to other studied protocols. With the optimized protocol, an average error inμand ξ was 3% and 11%, respectively, when compared with the known ground truth. Mid-line structures, as opposed to those on the cortical surface, generally display greater error. Varying model boundary conditions and reducing the thickness of the cortex by up to 0.67 mm (which is a realistic portrayal of neurodegenerative pathology) results in no loss in reconstruction accuracy.Significance. These experiments establish quantitative guidelines for the accuracy expected ofin vivoMRE of the cortex, with the proposed method providing valid MRE measures for future investigations into cortical viscoelasticity and relationships with health, cognition, and behavior.

Quantifying stability of parameter estimates forin vivonearly incompressible transversely-isotropic brain MR elastography

Easily computable quality metrics for measured medical data at point-of-care are important for imaging technologies involving offline reconstruction. Accordingly, we developed a new data quality metric forin vivotransversely-isotropic (TI) magnetic resonance elastography (MRE) based on a generalization of the widely accepted octahedral shear-strain calculation. The metric uses MRE displacement data and an estimate of the TI property field to yield a 'stability map' which predicts regions of low versus high accuracy in the resulting material property reconstructions. We can also calculate an average TI parameter stability (TIPS) score over all voxels in a region of interest for a given measurement to indicate how reliable the recovered mechanical property estimate for the region is expected to be. The calculation is rapid and places little demand on computing resources compared to the computationally intensive material property reconstruction from non-linear inversion (TI-NLI) of displacement fields, making it ideal for point-of-care evaluation of data quality. We test the predictions of the stability map for both simulated phantoms andin vivohuman brain data. We used a range of different displacement datasets from vibrations applied in the anterior-posterior (AP), left-right (LR) and combined AP + LR directions. The TIPS and variability maps (noise sensitivity or variation from the mean of repeated MRE scans) were consistently anti-correlated. Notably, Spearman correlation coefficients ∣R∣>0.6 were found between variability and TIPS score for individual white matter tracts within vivodata. These observations demonstrate the reliability and promise of this data quality metric to screen data rapidly in realistic clinical MRE applications.

Correlated noise in brain magnetic resonance elastography

PURPOSE

Magnetic resonance elastography (MRE) uses phase-contrast MRI to generate mechanical property maps of the in vivo brain through imaging of tissue deformation from induced mechanical vibration. The mechanical property estimation process in MRE can be susceptible to noise from physiological and mechanical sources encoded in the phase, which is expected to be highly correlated. This correlated noise has yet to be characterized in brain MRE, and its effects on mechanical property estimates computed using inversion algorithms are undetermined.

METHODS

To characterize the effects of signal noise in MRE, we conducted 3 experiments quantifying (1) physiomechanical sources of signal noise, (2) physiological noise because of cardiac-induced movement, and (3) impact of correlated noise on mechanical property estimates. We use a correlation length metric to estimate the extent that correlated signal persists in MRE images and demonstrate the effect of correlated noise on property estimates through simulations.

RESULTS

We found that both physiological noise and vibration noise were greater than image noise and were spatially correlated across all subjects. Added physiological and vibration noise to simulated data resulted in property maps with higher error than equivalent levels of Gaussian noise.

CONCLUSION

Our work provides the foundation to understand contributors to brain MRE data quality and provides recommendations for future work to correct for signal noise in MRE.

Proton deflectometry with in situ x-ray reference for absolute measurement of electromagnetic fields in high-energy-density plasmas

We report a technique of proton deflectometry that uses a grid and an in situ reference x-ray grid image for precise measurements of magnetic fields in high-energy-density plasmas. A D³He fusion implosion provides a bright point source of both protons and x-rays, which is split into beamlets by a grid. The protons undergo deflections as they propagate through the plasma region of interest, whereas the x-rays travel along straight lines. The x-ray image, therefore, provides a zero-deflection reference image. The line-integrated magnetic fields are inferred from the shifts of beamlets between the deflected (proton) and reference (x-ray) images. We developed a system for analysis of these data, including automatic algorithms to find beamlet locations and to calculate their deflections from the reference image. The technique is verified in an experiment performed at OMEGA to measure a nonuniform magnetic field in vacuum and then applied to observe the interaction of an expanding plasma plume with the magnetic field.

Quantitative effects of off-resonance related distortion on brain mechanical property estimation with magnetic resonance elastography

Off-resonance related geometric distortion can impact quantitative MRI techniques, such as magnetic resonance elastography (MRE), and result in errors to these otherwise sensitive metrics of brain health. MRE is a phase contrast technique to determine the mechanical properties of tissue by imaging shear wave displacements and estimating tissue stiffness through inverse solution of Navier's equation. In this study, we systematically examined the quantitative effects of distortion and corresponding correction approaches on MRE measurements through a series of simulations, phantom models, and in vivo brain experiments. We studied two different k-space trajectories, echo-planar imaging and spiral, and we determined that readout time, off-resonance gradient strength, and the combination of readout direction and off-resonance gradient direction, impact the estimated mechanical properties. Images were also processed through traditional distortion correction pipelines, and we found that each of the correction mechanisms works well for reducing stiffness errors, but are limited in cases of very large distortion. The ability of MRE to detect subtle changes to neural tissue health relies on accurate, artifact-free imaging, and thus off-resonance related geometric distortion must be considered when designing sequences and protocols by limiting readout time and applying correction where appropriate.

MR Imaging of Human Brain Mechanics In Vivo: New Measurements to Facilitate the Development of Computational Models of Brain Injury

Computational models of the brain and its biomechanical response to skull accelerations are important tools for understanding and predicting traumatic brain injuries (TBIs). However, most models have been developed using experimental data collected on animal models and cadaveric specimens, both of which differ from the living human brain. Here we describe efforts to noninvasively measure the biomechanical response of the human brain with MRI-at non-injurious strain levels-and generate data that can be used to develop, calibrate, and evaluate computational brain biomechanics models. Specifically, this paper reports on a project supported by the National Institute of Neurological Disorders and Stroke to comprehensively image brain anatomy and geometry, mechanical properties, and brain deformations that arise from impulsive and harmonic skull loadings. The outcome of this work will be a publicly available dataset ( http://www.nitrc.org/projects/bbir ) that includes measurements on both males and females across an age range from adolescence to older adulthood. This article describes the rationale and approach for this study, the data available, and how these data may be used to develop new computational models and augment existing approaches; it will serve as a reference to researchers interested in using these data.

Brain stiffness following recovery in a patient with an episode of low-pressure hydrocephalus: case report

The authors describe a follow-up to a case of a 19-year-old female with shunted aqueductal stenosis who presented with low-pressure hydrocephalus during a shunt malfunction. Shortly after management with CSF drainage at negative pressure, a magnetic resonance elastography scan was performed and revealed very low brain stiffness (high compliance). Here we present the case of the same patient seen 2 years later, now 21 years old, who again received a magnetic resonance elastography scan after receiving treatment for another shunt malfunction, this time with high intracranial pressure. This scan revealed recovery of brain stiffness to a near normal value for the patients' age. This observation suggests the low brain stiffness observed during the low-pressure hydrocephalus event is reversible. The authors discuss these findings in relation to biomechanical hypotheses of low-pressure hydrocephalus.

Brain-mimicking phantom for biomechanical validation of motion sensitive MR imaging techniques

Motion sensitive MR imaging techniques allow for the non-invasive evaluation of biological tissues by using different excitation schemes, including physiological/intrinsic motions caused by cardiac pulsation or respiration, and vibrations caused by an external actuator. The mechanical biomarkers extracted through these imaging techniques have been shown to hold diagnostic value for various neurological disorders and conditions. Amplified MRI (aMRI), a cardiac gated imaging technique, can help track and quantify low frequency intrinsic motion of the brain. As for high frequency actuation, the mechanical response of brain tissue can be measured by applying external high frequency actuation in combination with a motion sensitive MR imaging sequence called Magnetic Resonance Elastography (MRE). Due to the frequency-dependent behavior of brain mechanics, there is a need to develop brain phantom models that can mimic the broadband mechanical response of the brain in order to validate motion-sensitive MR imaging techniques. Here, we have designed a novel phantom test setup that enables both the low and high frequency responses of a brain-mimicking phantom to be captured, allowing for both aMRI and MRE imaging techniques to be applied on the same phantom model. This setup combines two different vibration sources: a pneumatic actuator, for low frequency/intrinsic motion (1 Hz) for use in aMRI, and a piezoelectric actuator for high frequency actuation (30-60 Hz) for use in MRE. Our results show that in MRE experiments performed from 30 Hz through 60 Hz, propagating shear waves attenuate faster at higher driving frequencies, consistent with results in the literature. Furthermore, actuator coupling has a substantial effect on wave amplitude, with weaker coupling causing lower amplitude wave field images, specifically shown in the top-surface shear loading configuration. For intrinsic actuation, our results indicate that aMRI linearly amplifies motion up to at least an amplification factor of 9 for instances of both visible and sub-voxel motion, validated by varying power levels of pneumatic actuation (40%-80% power) under MR, and through video analysis outside the MRI scanner room. While this investigation used a homogeneous brain-mimicking phantom, our setup can be used to study the mechanics of non-homogeneous phantom configurations with bio-interfaces in the future.

Blood lipid markers are associated with hippocampal viscoelastic properties and memory in humans

Age-related memory loss shares similar risk factors as cardiometabolic diseases including elevated serum triglycerides (TGs) and low-density lipoprotein cholesterol (LDL-C) and reduced high-density lipoprotein cholesterol (HDL-C). The mechanisms linking these aberrant blood lipids to memory loss are not completely understood but may be partially mediated by reduced integrity of the hippocampus (HC), the primary brain structure for encoding and recalling memories. In this study, we tested the hypothesis that blood lipid markers are independently associated with memory performance and HC viscoelasticity-a noninvasive measure of brain tissue microstructural integrity assessed by high-resolution magnetic resonance elastography (MRE). Twenty-six individuals across the adult lifespan were recruited (14 M/12 F; mean age: 42 ± 15 y; age range: 22-78 y) and serum lipid profiles were related to episodic memory and HC viscoelasticity. All subjects were generally healthy without clinically abnormal blood lipids or memory loss. Episodic memory was negatively associated with the TG/HDL-C ratio. HC viscoelasticity was negatively associated with serum TGs and the TG/HDL-C ratio, independent of age and in the absence of associations with HC volume. These data, although cross-sectional, suggest that subtle differences in blood lipid profiles in healthy adults may contribute to a reduction in memory function and HC tissue integrity.

Aging brain mechanics: Progress and promise of magnetic resonance elastography

Neuroimaging techniques that can sensitivity characterize healthy brain aging and detect subtle neuropathologies have enormous potential to assist in the early detection of neurodegenerative conditions such as Alzheimer's disease. Magnetic resonance elastography (MRE) has recently emerged as a reliable, high-resolution, and especially sensitive technique that can noninvasively characterize tissue biomechanical properties (i.e., viscoelasticity) in vivo in the living human brain. Brain tissue viscoelasticity provides a unique biophysical signature of neuroanatomy that are representative of the composition and organization of the complex tissue microstructure. In this article, we detail how progress in brain MRE technology has provided unique insights into healthy brain aging, neurodegeneration, and structure-function relationships. We further discuss additional promising technical innovations that will enhance the specificity and sensitivity for brain MRE to reveal considerably more about brain aging as well as its potentially valuable role as an imaging biomarker of neurodegeneration. MRE sensitivity may be particularly useful for assessing the efficacy of rehabilitation strategies, assisting in differentiating between dementia subtypes, and in understanding the causal mechanisms of disease which may lead to eventual pharmacotherapeutic development.

Calibration of a Heterogeneous Brain Model Using a Subject-Specific Inverse Finite Element Approach

Central to the investigation of the biomechanics of traumatic brain injury (TBI) and the assessment of injury risk from head impact are finite element (FE) models of the human brain. However, many existing FE human brain models have been developed with simplified representations of the parenchyma, which may limit their applicability as an injury prediction tool. Recent advances in neuroimaging techniques and brain biomechanics provide new and necessary experimental data that can improve the biofidelity of FE brain models. In this study, the CAB-20MSym template model was developed, calibrated, and extensively verified. To implement material heterogeneity, a magnetic resonance elastography (MRE) template image was leveraged to define the relative stiffness gradient of the brain model. A multi-stage inverse FE (iFE) approach was used to calibrate the material parameters that defined the underlying non-linear deviatoric response by minimizing the error between model-predicted brain displacements and experimental displacement data. This process involved calibrating the infinitesimal shear modulus of the material using low-severity, low-deformation impact cases and the material non-linearity using high-severity, high-deformation cases from a dataset of in situ brain displacements obtained from cadaveric specimens. To minimize the geometric discrepancy between the FE models used in the iFE calibration and the cadaveric specimens from which the experimental data were obtained, subject-specific models of these cadaveric brain specimens were developed and used in the calibration process. Finally, the calibrated material parameters were extensively verified using independent brain displacement data from 33 rotational head impacts, spanning multiple loading directions (sagittal, coronal, axial), magnitudes (20–40 rad/s), durations (30–60 ms), and severity. Overall, the heterogeneous CAB-20MSym template model demonstrated good biofidelity with a mean overall CORA score of 0.63 ± 0.06 when compared to in situ brain displacement data. Strains predicted by the calibrated model under non-injurious rotational impacts in human volunteers (N = 6) also demonstrated similar biofidelity compared to in vivo measurements obtained from tagged magnetic resonance imaging studies. In addition to serving as an anatomically accurate model for further investigations of TBI biomechanics, the MRE-based framework for implementing material heterogeneity could serve as a foundation for incorporating subject-specific material properties in future models.

Lessons learnt from the field: a qualitative evaluation of adolescent experiences of a universal mental health education program

teen Mental Health First Aid (teenMHFA) is a school-based mental health program that trains adolescents to support peers who are experiencing mental health problems or crises. The program has been evaluated for adolescents aged 15-18 years as part of a randomized controlled trial, however qualitative feedback from students on their perceptions of the program is yet to be explored. The current study describes the perspectives of students who took part in the trial. Feedback on the perceived strengths and weaknesses of the program was provided by 979 Year 10 students (M = 15.82 years, female = 43.94%, English as a first language = 72.77%) at four government funded public schools in Melbourne, Australia via online surveys. A content and thematic analysis was performed on the data using a six-step process. Students generally found the program relevant and they connected with the visual material, personal stories and interactive activities. Suggestions for improvements included encouraging active student participation in classroom discussion and providing opportunities to practice skills. School-based mental health education can benefit from input from stakeholder perspectives, particularly when designing mental health content for delivery by external trainers.

Effect of Aging on the Viscoelastic Properties of Hippocampal Subfields Assessed with High-Resolution MR Elastography

Age-related memory impairments have been linked to differences in structural brain parameters, including the integrity of the hippocampus (HC) and its distinct hippocampal subfields (HCsf). Imaging methods sensitive to the underlying tissue microstructure are valuable in characterizing age-related HCsf structural changes that may relate to cognitive function. Magnetic resonance elastography (MRE) is a noninvasive MRI technique that can quantify tissue viscoelasticity and may provide additional information about aging effects on HCsf health. Here, we report a high-resolution MRE protocol to quantify HCsf viscoelasticity through shear stiffness, μ, and damping ratio, ξ, which reflect the integrity of tissue composition and organization. HCsf exhibit distinct mechanical properties-the subiculum had the lowest μ and both subiculum and entorhinal cortex had the lowest ξ. Both measures correlated with age: HCsf μ was lower with age (P < 0.001) whereas ξ was higher (P = 0.002). The magnitude of age-related differences in ξ varied across HCsf (P = 0.011), suggesting differential patterns of brain aging. This study demonstrates the feasibility of using MRE to assess HCsf microstructural integrity and suggests incorporation of these metrics to evaluate HC health in neurocognitive disorders.

Integrating material properties from magnetic resonance elastography into subject-specific computational models for the human brain

Advances in brain imaging and computational methods have facilitated the creation of subject-specific computational brain models that aid researchers in investigating brain trauma using simulated impacts. The emergence of magnetic resonance elastography (MRE) as a non-invasive mechanical neuroimaging tool has enabled in vivo estimation of material properties at low-strain, harmonic loading. An open question in the field has been how this data can be integrated into computational models. The goals of this study were to use a novel MRI dataset acquired in human volunteers to generate models with subject-specific anatomy and material properties, and then to compare simulated brain deformations to subject-specific brain deformation data under non-injurious loading. Models of five subjects were simulated with linear viscoelastic (LVE) material properties estimated directly from MRE data. Model predictions were compared to experimental brain deformation acquired in the same subjects using tagged MRI. Outcomes from the models matched the spatial distribution and magnitude of the measured peak strain components as well as the 95^th percentile in-plane peak strains within 0.005 mm/mm and maximum principal strain within 0.012 mm/mm. Sensitivity to material heterogeneity was also investigated. Simulated brain deformations from a model with homogenous brain properties and a model with brain properties discretized with up to ten regions were very similar (a mean absolute difference less than 0.0015 mm/mm in peak strains). Incorporating material properties directly from MRE into a biofidelic subject-specific model is an important step toward future investigations of higher-order model features and simulations under more severe loading conditions.

Heterogeneous mass distribution of the rubble-pile asteroid (101955) Bennu

The gravity field of a small body provides insight into its internal mass distribution. We used two approaches to measure the gravity field of the rubble-pile asteroid (101955) Bennu: (i) tracking and modeling the spacecraft in orbit about the asteroid and (ii) tracking and modeling pebble-sized particles naturally ejected from Bennu's surface into sustained orbits. These approaches yield statistically consistent results up to degree and order 3, with the particle-based field being statistically significant up to degree and order 9. Comparisons with a constant-density shape model show that Bennu has a heterogeneous mass distribution. These deviations can be modeled with lower densities at Bennu's equatorial bulge and center. The lower-density equator is consistent with recent migration and redistribution of material. The lower-density center is consistent with a past period of rapid rotation, either from a previous Yarkovsky-O'Keefe-Radzievskii-Paddack cycle or arising during Bennu's accretion following the disruption of its parent body.

Hemispherical differences in the shape and topography of asteroid (101955) Bennu

We investigate the shape of near-Earth asteroid (101955) Bennu by constructing a high-resolution (20 cm) global digital terrain model from laser altimeter data. By modeling the northern and southern hemispheres separately, we find that longitudinal ridges previously identified in the north extend into the south but are obscured there by surface material. In the south, more numerous large boulders effectively retain surface materials and imply a higher average strength at depth to support them. The north has fewer large boulders and more evidence of boulder dynamics (toppling and downslope movement) and surface flow. These factors result in Bennu's southern hemisphere being rounder and smoother, whereas its northern hemisphere has higher slopes and a less regular shape. We infer an originally asymmetric distribution of large boulders followed by a partial disruption, leading to wedge formation in Bennu's history.

Standard-space atlas of the viscoelastic properties of the human brain

Standard anatomical atlases are common in neuroimaging because they facilitate data analyses and comparisons across subjects and studies. The purpose of this study was to develop a standardized human brain atlas based on the physical mechanical properties (i.e., tissue viscoelasticity) of brain tissue using magnetic resonance elastography (MRE). MRE is a phase contrast‐based MRI method that quantifies tissue viscoelasticity noninvasively and in vivo thus providing a macroscopic representation of the microstructural constituents of soft biological tissue. The development of standardized brain MRE atlases are therefore beneficial for comparing neural tissue integrity across populations. Data from a large number of healthy, young adults from multiple studies collected using common MRE acquisition and analysis protocols were assembled (N = 134; 78F/ 56 M; 18–35 years). Nonlinear image registration methods were applied to normalize viscoelastic property maps (shear stiffness, μ, and damping ratio, ξ) to the MNI152 standard structural template within the spatial coordinates of the ICBM‐152. We find that average MRE brain templates contain emerging and symmetrized anatomical detail. Leveraging the substantial amount of data assembled, we illustrate that subcortical gray matter structures, white matter tracts, and regions of the cerebral cortex exhibit differing mechanical characteristics. Moreover, we report sex differences in viscoelasticity for specific neuroanatomical structures, which has implications for understanding patterns of individual differences in health and disease. These atlases provide reference values for clinical investigations as well as novel biophysical signatures of neuroanatomy. The templates are made openly available (github.com/mechneurolab/mre134) to foster collaboration across research institutions and to support robust cross‐center comparisons.