In vivo and ex vivo elastic properties of brain tissues measured with ultrasound elastography

Experimental study on monitoring microwave ablation efficacy by real-time shear wave elastography in ex vivo porcine brain

Objective: Glioma constitutes the most common primary malignant tumor in the central nervous system. In recent years, microwave ablation (MWA) was expected to be applied in the minimally invasive treatment of brain tumors. This study aims to evaluate the feasibility and accuracy of microwave ablation in ex vivo brain tissue by Shear Wave Elastography (SWE) to explore the application value of real-time SWE in monitoring the process of MWA of brain tissue.Methods: Thirty ex vivo brain tissues were treated with different microwave power and ablation duration. The morphologic and microscopic changes of MWA tissues were observed, and the diameter of the ablation areas was measured. In this experiment, SWE is used to quantitatively evaluate brain tissue's degree of thermal injury immediately after ablation.Results: This study It is found that the ablation range measured by SWE after ablation is in good consistency with the pathological range [ICCSWEL1-L1 = 0.975(95% CI:0.959 - 0.985), ICCSWEL2-L2 = 0.887(95% CI:0.779 - 0.938)]. At the same time, the SWE value after ablation is significantly higher than before (mean ± SD,9.88 ± 2.64 kPa vs.23.6 ± 13.75 kPa; p < 0.001). In this study, the SWE value of tissues in different pathological states was further analyzed by the ROC curve (AUC = 0.86), and the threshold for distinguishing normal tissue from tissue after ablation was 13.7 kPa. The accuracy of evaluating ablation tissue using SWE can reach 84.72%, providing data support for real-time quantitative observation of the ablation range.Conclusion: In conclusion the accurate visualization and real-time evaluation of the organizational change range of the MWA process can be realized by real-time SWE.

Brain-Mimicking Phantom for Photoablation and Visualization

While the use of tissue-mimicking (TM) phantoms has been ubiquitous in surgical robotics, the translation of technology from laboratory experiments to equivalent intraoperative tissue conditions has been a challenge. The increasing use of lasers for surgical tumor resection has introduced the need to develop a modular, low-cost, functionally relevant TM phantom to model the complex laser-tissue interaction. In this paper, a TM phantom with mechanically and thermally similar properties as human brain tissue suited for photoablation studies and subsequent visualization is developed. The proposed study demonstrates the tuned phantom response to laser ablation for fixed laser power, time, and angle. Additionally, the ablated crater profile is visualized using optical coherence tomography (OCT), enabling high-resolution surface profile generation.

3D models of neurodegeneration: implementation in drug discovery

A lack of in vitro models that robustly represent the complex cellular pathologies underlying neurodegeneration has resulted in a translational gap between in vitro and in vivo results, creating a bottleneck in the development of new therapeutics. In the past decade, new and complex 3D models of the brain have been published at an exponential rate. However, many novel 3D models of neurodegeneration overlook the validation and throughput requirements for implementation in drug discovery. This therefore represents a knowledge gap that could hinder the translation of these models to drug discovery efforts. We review the recent progress in the development of 3D models of neurodegeneration, examining model design benefits and validation techniques, and discuss opportunities and standards for 3D models of neurodegeneration to be implemented in drug discovery and development.

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

Mechanical properties of brain tissue are very complex and vary with the species, region, method, and dynamic range, and between in vivo and ex vivo measurements. To reconcile this variability, we investigated in vivo and ex vivo stiffness properties of two distinct regions in the human and mouse brain - the hippocampus (HP) and the corpus callosum (CC) - using different methods. Under quasi-static conditions, we examined ex vivo murine HP and CC by atomic force microscopy (AFM). Between 16 and 40Hz, we investigated the in vivo brains of healthy volunteers by magnetic resonance elastography (MRE) in a 3-T clinical scanner. At high-frequency stimulation between 1000 and 1400Hz, we investigated the murine HP and CC ex vivo and in vivo with MRE in a 7-T preclinical system. HP and CC showed pronounced stiffness dispersion, as reflected by a factor of 32-36 increase in shear modulus from AFM to low-frequency human MRE and a 25-fold higher shear wave velocity in murine MRE than in human MRE. At low frequencies, HP was softer than CC, in both ex vivo mouse specimens (p < 0.05) and in vivo human brains (p < 0.01) while, at high frequencies, CC was softer than HP under in vivo (p < 0.01) and ex vivo (p < 0.05) conditions. The standard linear solid model comprising three elements reproduced the observed HP and CC stiffness dispersions, while other two- and three-element models failed. Our results indicate a remarkable consistency of brain stiffness across species, ex vivo and in vivo states, and different measurement techniques when marked viscoelastic dispersion properties combining equilibrium and non-equilibrium mechanical elements are considered.

Bidirectional hyperelastic characterization of brain white matter tissue

Biomechanical study of brain injuries originated from mechanical damages to white matter tissue requires detailed information on mechanical characteristics of its main components, the axonal fibers and extracellular matrix, which is very limited due to practical difficulties of direct measurement. In this paper, a new theoretical framework was established based on microstructural modeling of brain white matter tissue as a soft composite for bidirectional hyperelastic characterization of its main components. First the tissue was modeled as an Ogden hyperelastic material, and its principal Cauchy stresses were formulated in the axonal and transverse directions under uniaxial and equibiaxial tension using the theory of homogenization. Upon fitting these formulae to the corresponding experimental test data, direction-dependent hyperelastic constants of the tissue were obtained. These directional properties then were used to estimate the strain energy stored in the homogenized model under each loading scenario. A new microstructural composite model of the tissue was also established using principles of composites micromechanics, in which the axonal fibers and surrounding matrix are modeled as different Ogden hyperelastic materials with unknown constants. Upon balancing the strain energies stored in the homogenized and composite models under different loading scenarios, fully coupled nonlinear equations as functions of unknown hyperelastic constants were derived, and their optimum solutions were found in a multi-parametric multi-objective optimization procedure using the response surface methodology. Finally, these solutions were implemented, in a bottom-up approach, into a micromechanical finite element model to reproduce the tissue responses under the same loadings and predict the tissue responses under unseen non-equibiaxial loadings. Results demonstrated a very good agreement between the model predictions and experimental results in both directions under different loadings. Moreover, the axonal fibers with hyperelastic characteristics stiffer than the extracellular matrix were shown to play the dominant role in directional reinforcement of the tissue.

Contribution of UltraFast™ Ultrasound and Shear Wave Elastography in the Imaging of Carotid Artery Disease

Carotid artery disease is one of the main global causes of disability and premature mortality in the spectrum of cardiovascular diseases. One of its main consequences, stroke, is the second biggest global contributor to disability and burden via Disability Adjusted Life Years after ischemic heart disease. In the last decades, B-mode and Doppler-based ultrasound imaging techniques have become an indispensable part of modern medical imaging of carotid artery disease. However, they have limited abilities in carotid artery plaque and wall characterization and are unable to provide simultaneous quantitative and qualitative flow information while the images are burdened by low framerates. UltraFast™ ultrasound is able to overcome these obstacles by providing simultaneous quantitative and qualitative flow analysis information in high frame rates via UltraFast™ Doppler. Another newly developed ultrasound technique, shear wave elastography, is based on the visualization of induced shear waves and the measurement of the shear wave propagation speed in the examined tissues which enables real-time carotid plaque and wall analysis. These newly developed ultrasound modalities have potential to significantly improve workflow efficiency and are able to provide a plethora of additional imaging information of carotid artery disease in comparison to conventional ultrasound techniques.

Mechanical properties of brain tissue based on microstructure

Research on the mechanical properties of brain tissue has gradually deepened recently. Two indentation protocols were used here to characterize the mechanical properties of cortical tissues. Further, histological staining was used to explore the correlation between the mechanical properties and microstructure on the basis of the density of cell nuclei and proteoglycan content. No significant difference was observed in transient contact stiffness between the cerebral cortex and cerebellar cortex at the depth interval of 0-600 μm under the cortical surface; however, the average shear modulus of the cerebral cortex was higher than that of the cerebellar cortex. The cerebral cortex responded more quickly to the change in load and released stress more thoroughly than the cerebellar cortex. In addition, the density of cell nuclei was related to both the transient contact stiffness and second time constant of cortical tissues. Proteoglycan content had a more significant impact on the shear modulus, second time constant, and stress relaxation rate of cortical tissues. Exploring mechanical properties thoroughly will provide more detailed mechanical information for future brain chip implantation. Alternatively, linking the mechanical properties of cortical tissues to the microstructure can provide basic data for the design and manufacture of substitute materials for brain tissue.

Sensitivity analysis of effective transverse shear viscoelastic and diffusional properties of myelinated white matter

Motivated by the need to interpret the results from a combined use of in vivo brain Magnetic Resonance Elastography (MRE) and Diffusion Tensor Imaging (DTI), we developed a computational framework to study the sensitivity of single-frequency MRE and DTI metrics to white matter microstructure and cell-level mechanical and diffusional properties. White matter was modeled as a triphasic unidirectional composite, consisting of parallel cylindrical inclusions (axons) surrounded by sheaths (myelin), and embedded in a matrix (glial cells plus extracellular matrix). Only 2D mechanics and diffusion in the transverse plane (perpendicular to the axon direction) was considered, and homogenized (effective) properties were derived for a periodic domain containing a single axon. The numerical solutions of the MRE problem were performed with ABAQUS and by employing a sophisticated boundary-conforming grid generation scheme. Based on the linear viscoelastic response to harmonic shear excitation and steady-state diffusion in the transverse plane, a systematic sensitivity analysis of MRE metrics (effective transverse shear storage and loss moduli) and DTI metric (effective radial diffusivity) was performed for a wide range of microstructural and intrinsic (phase-based) physical properties. The microstructural properties considered were fiber volume fraction, and the myelin sheath/axon diameter ratio. The MRE and DTI metrics are very sensitive to the fiber volume fraction, and the intrinsic viscoelastic moduli of the glial phase. The MRE metrics are nonlinear functions of the fiber volume fraction, but the effective diffusion coefficient varies linearly with it. Finally, the transverse metrics of both MRE and DTI are insensitive to the axon diameter in steady state. Our results are consistent with the limited anisotropic MRE and co-registered DTI measurements, mainly in the corpus callosum, available in the literature. We conclude that isotropic MRE and DTI constitutive models are good approximations for myelinated white matter in the transverse plane. The unidirectional composite model presented here is used for the first time to model harmonic shear stress under MRE-relevant frequency on the cell level. This model can be extended to 3D in order to inform the solution of the inverse problem in MRE, establish the biological basis of MRE metrics, and integrate MRE/DTI with other modalities towards increasing the specificity of neuroimaging.

Elastic Deformation of Soft Tissue-Mimicking Materials Using a Single Microbubble and Acoustic Radiation Force

Mechanical effects of microbubbles on tissues are central to many emerging ultrasound applications. Here, we investigated the acoustic radiation force a microbubble exerts on tissue at clinically relevant therapeutic ultrasound parameters. Individual microbubbles administered into a wall-less hydrogel channel (diameter: 25-100 µm, Young's modulus: 2-8.7 kPa) were exposed to an acoustic pulse (centre frequency: 1 MHz, pulse length: 10 ms, peak-rarefactional pressures: 0.6-1.0 MPa). Using high-speed microscopy, each microbubble was tracked as it pushed against the hydrogel wall. We found that a single microbubble can transiently deform a soft tissue-mimicking material by several micrometres, producing tissue loading-unloading curves that were similar to those produced using other indentation-based methods. Indentation depths were linked to gel stiffness. Using a mathematical model fitted to the deformation curves, we estimated the radiation force on each bubble (typically tens of nanonewtons) and the viscosity of the gels. These results provide insight into the forces exerted on tissues during ultrasound therapy and indicate a potential source of bio-effects.

A knowledge map analysis of brain biomechanics: Current evidence and future directions

Although brain, one of the most complex organs in the mammalian body, has been subjected to many studies from physiological and pathological points of view, there remain significant gaps in the available knowledge regarding its biomechanics. This article reviews the research trends in brain biomechanics with a focus on injury. We used published scientific articles indexed by Web of Science database over the past 40 years and tried to address the gaps that still exist in this field. We analyzed the data using VOSviewer, which is a software tool designed for scientometric studies. The results of this study showed that the response of brain tissue to external forces has been one of the significant research topics among biomechanicians. These studies have addressed the effects of mechanical forces on the brain and mechanisms of traumatic brain injury, as well as characterized changes in tissue behavior under trauma and other neurological diseases to provide new diagnostic and monitoring methods. In this study, some challenges in the field of brain injury biomechanics have been identified and new directions toward understanding the gaps in this field are suggested.

Towards microstructure-informed material models for human brain tissue

Emerging evidence suggests that the mechanical behavior of the brain plays a critical role in development, disease, and aging. Recent studies have begun to characterize the mechanical behavior of gray and white matter tissue and to identify sets of material models that best reproduce the stress-strain behavior of different brain regions. Yet, these models are mainly phenomenological in nature, their parameters often lack clear physical interpretation, and they fail to correlate the mechanical behavior to the underlying microstructural composition. Here we make a first attempt towards identifying general relations between microstructure and mechanics with the ultimate goal to develop microstructurally motivated constitutive equations for human brain tissue. Using histological staining, we analyze the microstructure of brain specimens from different anatomical regions, the cortex, basal ganglia, corona radiata, and corpus callosum, and identify the regional stiffness and viscosity under multiple loading conditions, simple shear, compression, and tension. Strikingly, our study reveals a negative correlation between cell count and stiffness, a positive correlation between myelin content and stiffness, and a negative correlation between proteoglycan content and stiffness. Additionally, our analysis shows a positive correlation between lipid and proteoglycan content and viscosity. We demonstrate how understanding the microstructural origin of the macroscopic behavior of the brain can help us design microstructure-informed material models for human brain tissue that inherently capture regional heterogeneities. This study represents an important step towards using brain tissue stiffness and viscosity as early diagnostic markers for clinical conditions including chronic traumatic encephalopathy, Alzheimer's and Parkinson's disease, or multiple sclerosis. STATEMENT OF SIGNIFICANCE: The complex and heterogeneous mechanical properties of brain tissue play a critical role for brain function. To understand and predict how brain tissue properties vary in space and time, it will be key to link the mechanical behavior to the underlying microstructural composition. Here we use histological staining to quantify area fractions of microstructural components of mechanically tested specimens and evaluate their individual contributions to the nonlinear macroscopic mechanical response. We further propose a microstructure-informed material model for human brain tissue that inherently captures regional heterogeneities. The current work provides unprecedented insights into the biomechanics of human brain tissue, which are highly relevant to develop refined computational models for brain tissue behavior or to advance neural tissue engineering.

Indentation response in porcine brain under electric fields

Electric fields in the environment can have profound effects on brain function and behavior. In clinical practice, some noninvasive/microinvasive therapies with electrical fields such as transcranial electrical stimulation (tES), deep brain stimulation (DBS), and electroconvulsive therapy (ECT) have emerged as powerful tools for the treatment of neuropsychiatric disorders and neuromodulation. Nonetheless, currently, most studies focus on the mechanisms and effects of therapies and do not to address the mechanical properties of brain tissue under electric fields. Thus, the mechanical behavior of brain tissue, which plays an important role in modulating both brain form and brain function, should be given attention. The present study addresses this paucity by presenting, for the first time, the mechanical properties of brain tissue under various intensities of direct current electric field (0, 2, 5, 10, 20, and 50 V) using a custom-designed indentation device. Prior to brain indentation, validation tests were performed in different hydrogels to ensure that there was no interference in the electric fields from the indentation device. Subsequently, the load trace data obtained from the indentation-relaxation tests was fitted to both linear elastic and viscoelastic models to characterize the sensitivity of the mechanical behavior of the brain tissue to the electric fields. The brain tissue was found to be softened at a higher electric field level and less viscous, and substantially responded more quickly with an increase in electric field. The explanations for the above behaviors were further discussed based on the analysis of the resistance and thermal responses during the testing process. Understanding the effect of electric fields on brain tissue at the mechanical level can provide a better understanding of the mechanisms of some therapies, which may be beneficial to guide therapy protocols.