Mechanical behavior of the hippocampus and corpus callosum: An attempt to reconcile ex vivo with in vivo and micro with macro properties

Effects of anatomy and head motion on spatial patterns of deformation in the human brain

PURPOSE

To determine how the biomechanical vulnerability of the human brain is affected by features of individual anatomy and loading.

METHODS

To identify the features that contribute most to brain vulnerability, we imparted mild harmonic acceleration to the head and measured the resulting brain motion and deformation using magnetic resonance elastography (MRE). Oscillatory motion was imparted to the heads of adult participants using a lateral actuator (n = 24) or occipital actuator (n = 24) at 20 Hz, 30 Hz, and 50 Hz. Displacement vector fields and strain tensor fields in the brain were obtained from MRE measurements. Anatomical images, as well as displacement and strain fields from each participant were rigidly and deformably aligned to a common atlas (MNI-152). Vulnerability of the brain to deformation was quantified by the ratio of strain energy (SE) to kinetic energy (KE) for each participant. Similarity of deformation patterns between participants was quantified using strain field correlation (CV). Linear regression models were used to identify the effect of similarity of brain size, shape, and age, as well as similarity of loading, on CV.

RESULTS

The SE/KE ratio decreased with frequency and was larger for participants undergoing lateral, rather than occipital, actuation. Head rotation about the inferior-superior axis was correlated with larger SE/KE ratio. Strain field correlations were primarily affected by the similarity of rigid-body motion.

CONCLUSION

The motion applied to the skull is the most important factor in determining both the vulnerability of the brain to deformation and the similarity between strain fields in different individuals.

Rapid Stiffness Mapping in Soft Biologic Tissues With Micrometer Resolution Using Optical Multifrequency Time-Harmonic Elastography

Rapid mapping of the mechanical properties of soft biological tissues from light microscopy to macroscopic imaging can transform fundamental biophysical research by providing clinical biomarkers to complement in vivo elastography. This work introduces superfast optical multifrequency time-harmonic elastography (OMTHE) to remotely encode surface and subsurface shear wave fields for generating maps of tissue stiffness with unprecedented detail resolution. OMTHE rigorously exploits the space-time propagation characteristics of multifrequency time-harmonic waves to address current limitations of biomechanical imaging and elastography. Key solutions are presented for stimulation, wave decoding, and stiffness reconstruction of shear waves at multiple harmonic frequencies, all tuned to provide consistent stiffness values across resolutions from microns to millimeters. OMTHE's versatility is demonstrated by simulations, phantoms, Bacillus subtilis biofilms, zebrafish embryos and adult zebrafish, reflecting the diversity of biological systems from a mechanics perspective. By zooming in on stiffness details from coarse to finer scales, OMTHE has the potential to advance mechanobiology and offers a way to perform biomechanics-based tissue histology that consistently matches in vivo time-harmonic elastography in patients.

Model-driven exploration of poro-viscoelasticity in human brain tissue: be careful with the parameters!

The brain is arguably the most complex human organ and modelling its mechanical behaviour has challenged researchers for decades. There is still a lack of understanding on how this multiphase tissue responds to mechanical loading and how material parameters can be reliably calibrated. While previous viscoelastic models with two relaxation times have successfully captured the response of brain tissue, the Theory of Porous Media provides a continuum mechanical framework to explore the underlying physical mechanisms, including interactions between solid matrix and free-flowing interstitial fluid. Following our previously published experimental testing protocol, here we perform finite element simulations of cyclic compression-tension loading and compression-relaxation experiments on human brain white and gray matter specimens. The solid volumetric stress proves to be a crucial factor for the overall biphasic tissue behaviour as it strongly interferes with porous effects controlled by the permeability. An inverse parameter identification reveals that poroelasticity alone is insufficient to capture the time-dependent material behaviour, but a poro-viscoelastic formulation captures the response of brain tissue well. We provide valuable insights into the individual contributions of viscous and porous effects. However, due to the strong coupling between porous, viscous, and volumetric effects, additional experiments are required to reliably determine all material parameters.

Investigation of hepatic inflammation via viscoelasticity at low and high mechanical frequencies - A magnetic resonance elastography study

PURPOSE

To study the potential of viscoelastic parameters such as liver stiffness, loss tangent (marker of viscous properties) and viscoelastic dispersion to detect hepatic inflammation by in-vivo and ex-vivo MR elastography (MRE) at low and high vibration frequencies.

METHODS

15 patients scheduled for liver tumor resection surgery were prospectively enrolled in this IRB-approved study and underwent multifrequency in-vivo MRE (30-60Hz) at 1.5-T prior to surgery. Immediately after liver resection, tumor-free tissue specimens were examined with ex-vivo MRE (0.8-2.8 kHz) at 0.5-T and histopathologic analysis including NAFLD activity score (NAS) and inflammation score (I-score) as sum of histological sub-features of inflammation.

RESULTS

In-vivo, in regions where tissue samples were obtained, the loss tangent correlated with the I-score (R = 0.728; p = 0.002) and c-dispersion (stiffness dispersion over frequency) correlated with lobular inflammation (R = -0.559; p = 0.030). In a subgroup of patients without prior chemotherapy, c-dispersion correlated with I-score also in the whole liver (R = -0.682; p = 0.043). ROC analysis of the loss tangent for predicting the I-score showed a high AUC for I ≥ 1 (0.944; p = 0.021), I ≥ 2 (0.804; p = 0.049) and I ≥ 3 (0.944; p = 0.021). Ex-vivo MRE was not sensitive to inflammation, whereas strong correlations were observed between fibrosis and stiffness (R = 0.589; p = 0.021), penetration rate (R = 0.589; p = 0.021), loss tangent (R = -0.629; p = 0.012), and viscoelastic model parameters (spring-pot powerlaw exponent, R = -0.528; p = 0.043; spring-pot shear modulus, R = 0.589; p = 0.021).

CONCLUSION

Our results suggest that c-dispersion of the liver is sensitive to inflammation when measured in-vivo in the low dynamic range (30-60Hz), while at higher frequencies (0.8-2.8 kHz) viscoelastic parameters are dominated by fibrosis.

Magnetic resonance elastography in a nutshell: Tomographic imaging of soft tissue viscoelasticity for detecting and staging disease with a focus on inflammation

Magnetic resonance elastography (MRE) is an emerging clinical imaging modality for characterizing the viscoelastic properties of soft biological tissues. MRE shows great promise in the noninvasive diagnosis of various diseases, especially those associated with soft tissue changes involving the extracellular matrix, cell density, or fluid turnover including altered blood perfusion - all hallmarks of inflammation from early events to cancer development. This review covers the fundamental principles of measuring tissue viscoelasticity by MRE, which are based on the stimulation and encoding of shear waves and their conversion into parameter maps of mechanical properties by inverse problem solutions of the wave equation. Technical challenges posed by real-world biological tissue properties such as viscosity, heterogeneity, anisotropy, and nonlinear elastic behavior of tissues are discussed. Applications of MRE measurement in both humans and animal models are presented, with emphasis on the detection, characterization, and staging of diseases related to the cascade of biomechanical property changes from early to chronic inflammation in the liver and brain. Overall, MRE provides valuable insights into the biophysics of soft tissues for imaging-based detection and staging of inflammation-associated tissue changes.

1-Norm waveform analysis for MR elastography-based quantification of inhomogeneity: Effects of the freeze-thaw cycle and Alzheimer's disease

BACKGROUND

Despite its success in the mechanical characterization of biological tissues, magnetic resonance elastography (MRE) uses ill-posed wave inversions to estimate tissue stiffness. 1-Norm has been recently introduced as a mathematical measure for the scattering of mechanical waves due to inhomogeneities based on an analysis of the delineated contours of wave displacement.

PURPOSE

To investigate 1-Norm as an MRE-based quantitative biomarker of mechanical inhomogeneities arising from microscopic structural tissue alterations caused by the freeze-thaw cycle (FTC) or Alzheimer's disease (AD).

METHODS

In this proof-of-concept study, we prospectively investigated excised porcine kidney (n = 6), liver (n = 6), and muscle (n = 6) before vs. after the FTC at 500-2000 Hz and excised murine brain of healthy controls (n = 3) vs. 5xFAD species with AD (n = 3) at 1200-1800 Hz using 0.5 T tabletop MRE. 1-Norm analysis was compared with conventional wave inversion.

RESULTS

While the FTC reduced both stiffness and inhomogeneity in kidney, liver, and muscle tissue, AD led to lower brain stiffness but more pronounced mechanical inhomogeneity.

CONCLUSION

Our preliminary results show that 1-Norm is sensitive to tissue mechanical inhomogeneity due to FTC and AD without relying on ill-posed wave inversion techniques. 1-Norm has the potential to be used as an MRE-based diagnostic biomarker independent of stiffness to characterize abnormal conditions that involve changes in tissue mechanical inhomogeneity.

The Networking Brain: How Extracellular Matrix, Cellular Networks, and Vasculature Shape the In Vivo Mechanical Properties of the Brain

Mechanically, the brain is characterized by both solid and fluid properties. The resulting unique material behavior fosters proliferation, differentiation, and repair of cellular and vascular networks, and optimally protects them from damaging shear forces. Magnetic resonance elastography (MRE) is a noninvasive imaging technique that maps the mechanical properties of the brain in vivo. MRE studies have shown that abnormal processes such as neuronal degeneration, demyelination, inflammation, and vascular leakage lead to tissue softening. In contrast, neuronal proliferation, cellular network formation, and higher vascular pressure result in brain stiffening. In addition, brain viscosity has been reported to change with normal blood perfusion variability and brain maturation as well as disease conditions such as tumor invasion. In this article, the contributions of the neuronal, glial, extracellular, and vascular networks are discussed to the coarse-grained parameters determined by MRE. This reductionist multi-network model of brain mechanics helps to explain many MRE observations in terms of microanatomical changes and suggests that cerebral viscoelasticity is a suitable imaging marker for brain disease.

On the relationship between viscoelasticity and water diffusion in soft biological tissues

Magnetic resonance elastography (MRE) and diffusion-weighted imaging (DWI) are complementary imaging techniques that detect disease based on viscoelasticity and water mobility, respectively. However, the relationship between viscoelasticity and water diffusion is still poorly understood, hindering the clinical translation of combined DWI-MRE markers. We used DWI-MRE to study 129 biomaterial samples including native and cross-linked collagen, glycosaminoglycans (GAGs) with different sulfation levels, and decellularized specimens of pancreas and liver, all with different proportions of solid tissue, or solid fractions. We developed a theoretical framework of the relationship between mechanical loss and tissue-water mobility based on two parameters, solid and fluid viscosity. These parameters revealed distinct DWI-MRE property clusters characterizing weak, moderate, and strong water-network interactions. Sparse networks interacting weakly with water, such as collagen or diluted decellularized tissue, resulted in marginal changes in water diffusion over increasing solid viscosity. In contrast, dense networks with larger solid fractions exhibited both free and hindered water diffusion depending on the polarity of the solid components. For example, polar and highly sulfated GAGs as well as native soft tissues hindered water diffusion despite relatively low solid viscosity. Our results suggest that two fundamental properties of tissue networks, solid fraction and network polarity, critically influence solid and fluid viscosity in biological tissues. Since clinical DWI and MRE are sensitive to these viscosity parameters, the framework we present here can be used to detect tissue remodeling and architectural changes in the setting of diagnostic imaging. STATEMENT OF SIGNIFICANCE: The viscoelastic properties of biological tissues provide a wealth of information on the vital state of cells and host matrix. Combined measurement of viscoelasticity and water diffusion by medical imaging is sensitive to tissue microarchitecture. However, the relationship between viscoelasticity and water diffusion is still poorly understood, hindering full exploitation of these properties as a combined clinical biomarker. Therefore, we analyzed the parameter space accessible by diffusion-weighted imaging (DWI) and magnetic resonance elastography (MRE) and developed a theoretical framework for the relationship between water mobility and mechanical parameters in biomaterials. Our theory of solid material properties related to particle motion can be translated to clinical radiology using clinically established MRE and DWI.

Profiling native pulmonary basement membrane stiffness using atomic force microscopy

Mammalian cells sense and react to the mechanics of their immediate microenvironment. Therefore, the characterization of the biomechanical properties of tissues with high spatial resolution provides valuable insights into a broad variety of developmental, homeostatic and pathological processes within living organisms. The biomechanical properties of the basement membrane (BM), an extracellular matrix (ECM) substructure measuring only ∼100-400 nm across, are, among other things, pivotal to tumor progression and metastasis formation. Although the precise assignment of the Young's modulus E of such a thin ECM substructure especially in between two cell layers is still challenging, biomechanical data of the BM can provide information of eminent diagnostic potential. Here we present a detailed protocol to quantify the elastic modulus of the BM in murine and human lung tissue, which is one of the major organs prone to metastasis. This protocol describes a streamlined workflow to determine the Young's modulus E of the BM between the endothelial and epithelial cell layers shaping the alveolar wall in lung tissues using atomic force microscopy (AFM). Our step-by-step protocol provides instructions for murine and human lung tissue extraction, inflation of these tissues with cryogenic cutting medium, freezing and cryosectioning of the tissue samples, and AFM force-map recording. In addition, it guides the reader through a semi-automatic data analysis procedure to identify the pulmonary BM and extract its Young's modulus E using an in-house tailored user-friendly AFM data analysis software, the Center for Applied Tissue Engineering and Regenerative Medicine processing toolbox, which enables automatic loading of the recorded force maps, conversion of the force versus piezo-extension curves to force versus indentation curves, calculation of Young's moduli and generation of Young's modulus maps, where the pulmonary BM can be identified using a semi-automatic spatial filtering tool. The entire protocol takes 1-2 d.

Multiscale elasticity mapping of biological samples in 3D at optical resolution

The mechanical properties of biological tissues have emerged as an integral determinant of tissue function in health and disease. Nonetheless, characterizing the elasticity of biological samples in 3D and at high resolution remains challenging. Here, we present a µElastography platform: a scalable elastography system that maps the elastic properties of tissues from cellular to organ scales. The platform leverages the use of a biocompatible, thermo-responsive hydrogel to deliver compressive stress to a biological sample and track its resulting deformation. By surrounding the specimen with a reference hydrogel of known Young's modulus, we are able to map the absolute values of elastic properties in biological samples. We validate the experimental and computational components of the platform using a hydrogel phantom and verify the system's ability to detect internal mechanical heterogeneities. We then apply the platform to map the elasticity of multicellular spheroids and the murine lymph node. With these applications, we demonstrate the platform's ability to map tissue elasticity at internal planes of interest, as well as capture mechanical heterogeneities neglected by most macroscale characterization techniques. The µElastography platform, designed to be implementable in any biology lab with access to 3D microscopy (e.g., confocal, multiphoton, or optical coherence microscopy), will provide the capability to characterize the mechanical properties of biological samples to labs across the large community of biological sciences by eliminating the need of specialized instruments such as atomic force microscopy. STATEMENT OF SIGNIFICANCE: Understanding the elasticity of biological tissues is of great importance, but characterizing these properties typically requires highly specialized equipment. Utilizing stimulus-responsive hydrogels, we present a scalable, hydrogel-based elastography method that uses readily available reagents and imaging modalities to generate resolved maps of internal elasticity within biomaterials and biological samples at optical resolution. This new approach is capable of detecting internal stiffness heterogeneities within the 3D bulk of samples and is highly scalable across both imaging modalities and biological length scales. Thus, it will have significant impact on the measurement capabilities of labs studying engineered biomaterials, mechanobiology, disease progression, and tissue engineering and development.

Mechanics in the nervous system: From development to disease

Physical forces are ubiquitous in biological processes across scales and diverse contexts. This review highlights the significance of mechanical forces in nervous system development, homeostasis, and disease. We provide an overview of mechanical signals present in the nervous system and delve into mechanotransduction mechanisms translating these mechanical cues into biochemical signals. During development, mechanical cues regulate a plethora of processes, including cell proliferation, differentiation, migration, network formation, and cortex folding. Forces then continue exerting their influence on physiological processes, such as neuronal activity, glial cell function, and the interplay between these different cell types. Notably, changes in tissue mechanics manifest in neurodegenerative diseases and brain tumors, potentially offering new diagnostic and therapeutic target opportunities. Understanding the role of cellular forces and tissue mechanics in nervous system physiology and pathology adds a new facet to neurobiology, shedding new light on many processes that remain incompletely understood.

Cortical matrix remodeling as a hallmark of relapsing-remitting neuroinflammation in MR elastography and quantitative MRI

Multiple sclerosis (MS) is a chronic neuroinflammatory disease that involves both white and gray matter. Although gray matter damage is a major contributor to disability in MS patients, conventional clinical magnetic resonance imaging (MRI) fails to accurately detect gray matter pathology and establish a clear correlation with clinical symptoms. Using magnetic resonance elastography (MRE), we previously reported global brain softening in MS and experimental autoimmune encephalomyelitis (EAE). However, it needs to be established if changes of the spatiotemporal patterns of brain tissue mechanics constitute a marker of neuroinflammation. Here, we use advanced multifrequency MRE with tomoelastography postprocessing to investigate longitudinal and regional inflammation-induced tissue changes in EAE and in a small group of MS patients. Surprisingly, we found reversible softening in synchrony with the EAE disease course predominantly in the cortex of the mouse brain. This cortical softening was associated neither with a shift of tissue water compartments as quantified by T2-mapping and diffusion-weighted MRI, nor with leukocyte infiltration as seen by histopathology. Instead, cortical softening correlated with transient structural remodeling of perineuronal nets (PNNs), which involved abnormal chondroitin sulfate expression and microgliosis. These mechanisms also appear to be critical in humans with MS, where tomoelastography for the first time demonstrated marked cortical softening. Taken together, our study shows that neuroinflammation (i) critically affects the integrity of PNNs in cortical brain tissue, in a reversible process that correlates with disease disability in EAE, (ii) reduces the mechanical integrity of brain tissue rather than leading to water accumulation, and (iii) shows similar spatial patterns in humans and mice. These results raise the prospect of leveraging MRE and quantitative MRI for MS staging and monitoring treatment in affected patients.

Regenerative capacity of neural tissue scales with changes in tissue mechanics post injury

Spinal cord injuries have devastating consequences for humans, as mammalian neurons of the central nervous system (CNS) cannot regenerate. In the peripheral nervous system (PNS), however, neurons may regenerate to restore lost function following injury. While mammalian CNS tissue softens after injury, how PNS tissue mechanics changes in response to mechanical trauma is currently poorly understood. Here we characterised mechanical rat nerve tissue properties before and after in vivo crush and transection injuries using atomic force microscopy-based indentation measurements. Unlike CNS tissue, PNS tissue significantly stiffened after both types of tissue damage. This nerve tissue stiffening strongly correlated with an increase in collagen I levels. Schwann cells, which crucially support PNS regeneration, became more motile and proliferative on stiffer substrates in vitro, suggesting that changes in tissue stiffness may play a key role in facilitating or impeding nervous system regeneration.

Exploring the Skin Brain Link: Biomarkers in the Skin with Implications for Aging Research and Alzheimer's Disease Diagnostics

Neurodegenerative diseases, including Alzheimer's disease (AD), are challenging to diagnose. Currently the field must rely on imperfect diagnostic modalities. A recent study identified differences in several key bio-mechano-physiological parameters of the skin between AD patients and healthy controls. Here, we visually align these differences with the relevant histological, aging, and embryological paradigms to raise awareness for these potential biomarkers. In a study conducted by Wu et al., a series of n = 41 patients (n = 29 with AD and n = 12 healthy controls) were evaluated, demonstrating that AD patients exhibit a less acidic skin pH, increased skin hydration, and reduced skin elasticity compared to healthy controls. We constructed a visual overview and explored the relevant paradigms. We present a visual comparison of these factors, highlighting four paradigms: (1) the findings emphasize a shared ectodermal origin of the brain and the skin; (2) functional systems such as micro-vascularization, innervation, eccrine excretory functions, and the extracellular matrix undergo distinct changes in patients with AD; (3) the human skin mirrors the alterations in brain stiffness observed in aging studies; (4) assessment of physiological features of the skin is cost-effective, accessible, and easily amenable for monitoring and integration with cognitive assessment studies. Understanding the relationship between aging skin and aging brain is an exciting frontier, holding great promise for improved diagnostics. Further prospective and larger-scale investigations are needed to solidify the brain-skin link and determine the extent to which this relationship can be leveraged for diagnostic applications.

Combining atomic force microscopy and fluorescence-based techniques to explore mechanical properties of naive and ischemia-affected brain regions in mice

Knowledge of the brain's structure and function is essential for understanding processes in health and disease. Histochemical and fluorescence-based techniques have proven beneficial in characterizing brain regions and cellular compositions in pre-clinical research. Atomic force microscopy (AFM) has been introduced for mechanical tissue characterization, which may also help investigate pathophysiological aspects in disease-related models such as stroke. While combining AFM and fluorescence-based techniques, this study explored the mechanical properties of naive and ischemic brain regions in mice. Ischemia-affected regions were identified by the green signal of fluorescein isothiocyanate-conjugated albumin. A semi-automated protocol based on a brain atlas allowed regional allocations to the neocortex, striatum, thalamus, hypothalamus, hippocampus, and fiber tracts. Although AFM led to varying measurements, intra-individual analyses indicated a gradually increased tissue stiffness in the neocortex compared to subcortical areas, i.e., the striatum and fiber tracts. Regions affected by ischemia predominantly exhibited an increased tissue stiffness compared to those of the contra-lateral hemisphere, which might be related to cellular swelling. This study indicated intra-individual differences in mechanical properties among naive and ischemia-affected brain regions. The combination of AFM, semi-automated regional allocations, and fluorescence-based techniques thus qualifies for mechanical characterizations of the healthy and disease-affected brain in pre-clinical research.