Characterizing Multiscale Mechanical Properties of Brain Tissue Using Atomic Force Microscopy, Impact Indentation, and Rheometry

To design and engineer materials inspired by the properties of the brain, whether for mechanical simulants or for tissue regeneration studies, the brain tissue itself must be well characterized at various length and time scales. Like many biological tissues, brain tissue exhibits a complex, hierarchical structure. However, in contrast to most other tissues, brain is of very low mechanical stiffness, with Young's elastic moduli E on the order of 100s of Pa. This low stiffness can present challenges to experimental characterization of key mechanical properties. Here, we demonstrate several mechanical characterization techniques that have been adapted to measure the elastic and viscoelastic properties of hydrated, compliant biological materials such as brain tissue, at different length scales and loading rates. At the microscale, we conduct creep-compliance and force relaxation experiments using atomic force microscope-enabled indentation. At the mesoscale, we perform impact indentation experiments using a pendulum-based instrumented indenter. At the macroscale, we conduct parallel plate rheometry to quantify the frequency dependent shear elastic moduli. We also discuss the challenges and limitations associated with each method. Together these techniques enable an in-depth mechanical characterization of brain tissue that can be used to better understand the structure of brain and to engineer bio-inspired materials

Measurement and modeling of brain tissue and engineered polymer response to concentrated impact loading

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mechanical Engineering, May, 2020Cataloged from the official PDF of thesis.Includes bibliographical references (pages 191-206).Our brains are among the most mechanically compliant and structurally complex organs in our bodies. To predict how brain tissue deforms, and to protect it from deforming in ways that reduce our cognitive function, we must be able to measure, model, and ideally replicate brain tissue mechanics. While this is a grand challenge that many have sought to address, this need is acute when considering spatially localized deformation of brain tissue under high rates, such as in collisions that cause traumatic brain injury (TBI). This thesis sought to address this challenge at increasing levels of spatial and temporal complexity by employing dynamic contact mechanics as a tool to consider reduction of TBI. Strategies to reduce TBI include helmets designed to absorb impact energy, which are evaluated typically by simplified impact tests with engineered headforms equipped with brain tissue simulant materials and accelerometers.However, current brain tissue simulant materials are inaccurate mechanical mimics under these conditions. Additionally, the geometry of both the brain and protective equipment intended to absorb such impact energy can couple the structural mechanics and material mechanics in subtle ways. Finally, many modern helmet designs provide inadequate protection against a sufficiently wide range of anticipated adverse impact scenarios (e.g., impact velocities and corresponding impact energies) that a human may encounter. This thesis aimed to (1) improve the tissue simulant materials and head acceleration-based metrics used to evaluate TBI protection strategies, and (2) implement these metrics in a novel framework for helmet evaluation and optimization.We developed and implemented novel methods to characterize both engineered tissue simulants and mammalian brain tissue at low deformation rates, using both conventional methods of rheology and indentation as well as novel methods of spatially localized rheology. To characterize those materials under concentrated impact conditions, we next employed impact indentation and developed a new method to analyze experimental results derived from dynamic contact mechanics. Whereas prior analyses were limited to empirical metrics, the methodology developed in this thesis facilitates measurement of viscoelastic constitutive properties of the material or tissue. We next turned our attention to characterizing and optimizing the multilayered materials designed to protect the brain, in the form of helmets.To enable objective comparison among helmets of different design, geometry, or energy absorbing materials, we first developed and demonstrated a new and accessible interpretation of helmet impact tests using head acceleration-based efficiency metrics. We applied this approach to an "inverted helmet" design, a hemispherical cap in which compliant protective layers are located on the external surface and a thin, stiff shell is located closer to the skull. Experimental and computational comparison of this prototype with a modern conventional helmet exposed deficiencies of existing acceleration-based evaluation metrics. For example, while the inverted helmet scored better under those measures for a given test scenario, our approach revealed that such a conclusion was incomplete and misleading because each helmet was most efficient under differing impact conditions.Indeed, since our analysis framework identified specific impact conditions under which a helmet absorbs energy most efficiently, we went on to demonstrate its utility in choice of materials to enhance impact energy absorption against anticipated adverse events. Just as we used contact mechanics to enable characterization of the brain tissue and engineered simulants, we used contact mechanics-based analytical models and finite element simulations to understand the theoretical underpinnings of impact energy absorption in multimaterial helmets. We augmented simplified analytical models from the literature to incorporate non-linear and viscoelastic behavior of the energy absorbing material layers. We found that simplified, approximate analytical models predicted many trends observed in finite element simulations and experimental measurements, with excellent agreement between finite element models and experimental results.Further, this approach provided distinct advantages, accounting for helmet thickness and clearly identifying the impact conditions under which the helmet is most protective. We also identified the ideal rate-dependent material constitutive response that would furnish an optimally efficient design across a wide range of impact energies and impact rates. This thesis provides tools and methods for evaluating novel protective strategies, and employs these methodologies to develop new helmet optimization procedures and design principles. The unifying enabler of this work was the understanding and implementation of contact mechanics models under impact loading conditions.by Aleksandar S. Mijailovic.Ph. D.Ph.D. Massachusetts Institute of Technology, Department of Mechanical Engineerin

Methods to measure and relate the viscoelastic properties of brain tissue

Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2016.Cataloged from PDF version of thesis.Includes bibliographical references (pages 71-75).Measurement of brain tissue elastic and viscoelastic properties is of interest for modeling traumatic brain injury, understanding and creating new biomarkers for brain diseases, improving neurosurgery procedures and development of tissue surrogate materials for evaluating protective strategies (e.g., helmets). However, accurate measurement of mechanical properties of brain tissue is challenging due to the high compliance and complex mechanical behavior of this tissue, including nonlinear viscoelastic behavior, poroelastic deformation, and failure mechanisms. Thus, reported measurements of the elastic and viscoelastic moduli of brain tissue vary by several orders of magnitude. This thesis highlights three mechanical characterization techniques for brain tissue: rheology, cavitation rheology, and impact indentation. Rheology is used to measure the shear storage and loss moduli of brain tissue in (1) healthy and tuberous sclerosis mouse brain and (2) healthy porcine brain. Next, cavitation rheology - a technique used to measure the elastic modulus of compliant polymers and tissues - is implemented for the first time in porcine brain tissue. Finally, a new analytical model and analysis procedure are developed for impact indentation, a novel mechanical characterization technique that was used to measure the impact response of murine and porcine brain tissue and brain tissue simulant polymers. This new analytical model allows for measurement of viscoelastic moduli via impact indentation experimental data, and it directly relates viscoelastic moduli to impact indentation output parameters of quality factor, energy dissipation capacity, and maximum penetration depth without the need for finite element simulation.by Aleksandar S. Mijailovic.S.M

Manufacturing of Biodegradable Scaffolds to Engineer Artificial Blood Vessel

Blood vessels diseases such as cardiac infarction with coronary artery occlusion, peripheral arterial disorders, or stroke of carotid or cerebral arteries, are the leading causes of death in the world. One of medical procedures for clinical treatment of vascular diseases is the blood vessels grafting. As the autologous blood vessels, which are the “golden standard” for coronary grafting, are not always suitable for blood vessels grafting, there is a need to develop artificial blood vessels as a vascular prostheses, either from natural and synthetic materials, permanent synthetic or biodegradable scaffolds which would be suitable for vascular grafts. Considering this to be our study goal we made bilayered biodegradable polycaprolactone scaffolds with different properties and evaluated their morphological and biomechanical characteristics

Applying the Molecular Adsorbent Recirculating System (MARS) in the Treatment of Acute Liver Failure (ALF) Case Report

Acute liver failure (ALF) is a rare but life-threatening illness with multiple organ failure. The short-term mortality rate exceeded 80 % despite modern approaches in treatment. Drugs, infections by hepatic viruses and toxins are the most common causes of ALF. Progressive jaundice, coagulation disorder and hepatic encephalopathy are dominated as a clinical signs of the illness. We present a case of a 36-year-old Caucasian woman hospitalized in ICU due to yellow discoloration of the skin and sclera, severe disseminated coagulopathy and hemodynamic instability. ALF is developed due to Hepatitis B Virus infection, resulting in hepatic toxicity as well as coma. General condition rapidly improved after applying of Molecular Adsorbent Recirculating System (MARS), an extracorporeal liver support system based on albumin dialysis. It is relatively expensive treatment that is used for the patient with hepatic encephalopathy grade 3 or 4 in our institution. In conclusion, an early administration of MARS significantly reveals subjective and objective clinical improvement in the case we presented

Molecular diagnosis of bacterial vaginosis – Prevalence of gardnerella vaginalis and atopobium vaginae in pregnant women

© 2018, Serbia Medical Society. All rights reserved. Introduction/Objective Bacterial vaginosis (BV) is defined as disequilibrium of vaginal microbiota due to proliferation of Gram-negative/variable anaerobes and reduction/depletion of vaginal lactobacilli. Difficulties in interpreting microscopically categorized findings in diagnosis of BV need a molecular analysis of bacteria present in vaginal discharge of patients. In this regard, we performed real-time qPCR analysis of vaginal discharge samples with the goal to explore in which extent prevalence and amount of anaerobes, Gardnerella vaginalis and Atopobium vaginae, are related to findings obtained by microscopy. Methods This study enrolled 111 asymptomatic pregnant women between 24 and 28 weeks of pregnancy. Gram-stained vaginal smears were evaluated microscopically. Afterwards, DNA of bacteria was extracted from Gram slides and real-time qPCR was performed with the aim to detect and quantify G. vaginalis and A. vaginae. Results The data of our study showed that 53.2% of patients had normal results, while 20.7% and 26.1% of patients had intermediary (IMD) and BV results, respectively. G. vaginalis and A. vaginae were more frequently found in IMD and BV than in healthy patients; also, the average bacterial number of G. vaginalis and A. vaginae were significantly higher in BV and IMD than in the group with normal findings (p = 0.000). Comparing mutual relation of G. vaginalis and A. vaginae, the prevalence and number of G. vaginalis were in all groups significantly higher than A. vaginae. Conclusion The data of our study have shown that in distinguishing normal from BV findings, quantification of bacteria may be more important than just molecular detection of bacteria

Localized characterization of brain tissue mechanical properties by needle induced cavitation rheology and volume controlled cavity expansion

© 2020 Changes in the elastic properties of brain tissue have been correlated with injury, cancers, and neurodegenerative diseases. However, discrepancies in the reported elastic moduli of brain tissue are persistent, and spatial inhomogeneities complicate the interpretation of macroscale measurements such as rheology. Here we introduce needle induced cavitation rheology (NICR) and volume-controlled cavity expansion (VCCE) as facile methods to measure the apparent Young's modulus E of minimally manipulated brain tissue, at specific tissue locations and with sub-millimeter spatial resolution. For different porcine brain regions and sections analyzed by NICR, we found E to be 3.7 ± 0.7 kPa and 4.8 ± 1.0 kPa for gray matter, and white matter, respectively. For different porcine brain regions and sections analyzed by VCCE, we found E was 0.76 ± 0.02 kPa for gray matter and 0.92 ± 0.01 kPa for white matter. Measurements from VCCE were more similar to those obtained from macroscale shear rheology (0.75 ± 0.06 kPa) and from instrumented microindentation of white matter (0.97 ± 0.40 kPa) and gray matter (0.86 ± 0.20 kPa). We attributed the higher stiffness reported from NICR to that method's assumption of a cavitation instability due to a neo-Hookean constitutive response, which does not capture the strain-stiffening behavior of brain tissue under large strains, and therefore did not provide appropriate measurements. We demonstrate via both analytical modeling of a spherical cavity and finite element modeling of a needle geometry, that this strain stiffening may prevent a cavitation instability. VCCE measurements take this stiffening behavior into account by employing an incompressible one-term Ogden model to find the nonlinear elastic properties of the tissue. Overall, VCCE afforded rapid and facile measurement of nonlinear mechanical properties of intact, healthy mammalian brain tissue, enabling quantitative comparison among brain tissue regions and also between species. Finally, accurate estimation of elastic properties for this strain stiffening tissue requires methods that include appropriate constitutive models of the brain tissue response, which here are represented by inclusion of the Ogden model in VCCE

PROBING MECHANICAL PROPERTIES OF BRAIN IN A TUBEROUS SCLEROSIS MODEL OF AUTISM

© 2018 American Society of Mechanical Engineers (ASME). All rights reserved. Causes of autism spectrum disorders (ASD) are understood poorly, making diagnosis and treatment challenging. While many studies have investigated the biochemical and genetic aspects of ASD, whether and how mechanical characteristics of the autistic brain can modulate neuronal connectivity and cognition in ASD are unknown. Previously, it has been shown that ASD brains are characterized by abnormal white matter and disorganized neuronal connectivity; we hypothesized that these significant cellular-level structural changes may translate to changes in the mechanical properties of the autistic brain or regions therein. Here, we focused on tuberous sclerosis complex (TSC), a genetic disorder with a high penetrance of ASD. We investigated mechanical differences between murine brains obtained from control and TSC cohorts at various deformation length- and time-scales. At the microscale, we conducted creep-compliance and stress relaxation experiments using atomic force microscope(AFM)-enabled indentation. At the mesoscale, we conducted impact indentation using a pendulum-based instrumented indenter to extract mechanical energy dissipation metrics. At the macroscale, we used oscillatory shear rheology to quantify the frequency-dependent shear moduli. Despite significant changes in the cellular organization of TSC brain tissue, we found no corresponding changes in the quantified mechanical properties at every length- and time-scale explored. This investigation of the mechanical characteristics of the brain has broadened our understanding of causes and markers of TSC/ASD, while raising questions about whether any mechanical differences can be detected in other animal models of ASD or other disease models that also feature abnormal brain structure