<p>Engineered monolayers created by using microabrasion and micropatterning methods have provided a simplified in vitro system to study the effects of anisotropy and fiber direction on electrical propagation. Interpreting the behavior in these culture systems has often been performed using classical computer models with continuous properties. Such models, however, do not account for the effects of random cell shapes, cell orientations and cleft spaces inherent in these monolayers on the resulting wavefront conduction. Additionally when the continuous computer model is built to study impulse propagations, the intracellular conductivities of the model are commonly assigned to match impulse conduction velocity of the model to the experimental measurement. However this method can result in inaccurate intracellular conductivities considering the relationship among the conduction velocity, intracellular conductivities and ion channel properties. In this study, we present novel methods for modeling a monolayer cardiac tissue and for estimating intracellular conductivities from an optical mapping. First, in the proposed method for modeling a monolayer of cardiac tissue, the factors governing cell shape, cell-to-cell coupling and the degree of cleft space are not constant but rather are treated as spatially random with assigned distributions. This approach makes it possible to simulate wavefront propagation in a manner analogous to performing experiments on engineered monolayer tissues. Simulated results are compared to reported experimental data measured from monolayers used to investigate the role of cellular architecture on conduction velocities and anisotropy ratios. We also present an estimate for obtaining the electrical properties from these networks and demonstrate how variations in the discrete cellular architecture affect the macroscopic conductivities. The simulation results agree with the common assumption that under normal ranges of coupling strengths, tissues whose cell shapes and connectivity show relatively uniform distributions can be represented using continuous models with conductivities derived from random discrete cellular architecture using either estimates. The results also reveal that in the presence of abrupt changes in cell orientation, local estimates of tissue properties predict smoother changes in conductivities that may not adequately predict the discrete nature of propagation at the transition sites. Second, a novel approach is proposed to estimate intracellular conductivities from the optical mapping of the monolayer cardiac tissue under subthreshold stimulus. This method uses a simplified membrane model, which represents the membrane as a second order polynomial of the membrane potential. The simplified membrane model and the intracellular conductivities are estimated from the optical mapping of the monolayer tissue under the subthreshold stimulus. We showed that the proposed method provides more accurate intracellular conductivities compared to a method using a constant membrane resistance.</p> / Dissertation

<p>Magnetic resonance imaging is a research and clinical tool that has been applied in a wide variety of sciences. One area of magnetic resonance imaging that has exhibited terrific promise and growth in the past decade is magnetic susceptibility imaging. Imaging tissue susceptibility provides insight into the microstructural organization and chemical properties of biological tissues, but this image contrast is not well understood. The purpose of this work is to develop effective approaches to image, assess, and model the mechanisms that generate both isotropic and anisotropic magnetic susceptibility contrast in biological tissues, including myocardium and central nervous system white matter. </p><p>This document contains the first report of MRI-measured susceptibility anisotropy in myocardium. Intact mouse heart specimens were scanned using MRI at 9.4 T to ascertain both the magnetic susceptibility and myofiber orientation of the tissue. The susceptibility anisotropy of myocardium was observed and measured by relating the apparent tissue susceptibility as a function of the myofiber angle with respect to the applied magnetic field. A multi-filament model of myocardial tissue revealed that the diamagnetically anisotropy α-helix peptide bonds in myofilament proteins are capable of producing bulk susceptibility anisotropy on a scale measurable by MRI, and are potentially the chief sources of the experimentally observed anisotropy.</p><p>The growing use of paramagnetic contrast agents in magnetic susceptibility imaging motivated a series of investigations regarding the effect of these exogenous agents on susceptibility imaging in the brain, heart, and kidney. In each of these organs, gadolinium increases susceptibility contrast and anisotropy, though the enhancements depend on the tissue type, compartmentalization of contrast agent, and complex multi-pool relaxation. In the brain, the introduction of paramagnetic contrast agents actually makes white matter tissue regions appear more diamagnetic relative to the reference susceptibility. Gadolinium-enhanced MRI yields tensor-valued susceptibility images with eigenvectors that more accurately reflect the underlying tissue orientation.</p><p>Despite the boost gadolinium provides, tensor-valued susceptibility image reconstruction is prone to image artifacts. A novel algorithm was developed to mitigate these artifacts by incorporating orientation-dependent tissue relaxation information into susceptibility tensor estimation. The technique was verified using a numerical phantom simulation, and improves susceptibility-based tractography in the brain, kidney, and heart. This work represents the first successful application of susceptibility-based tractography to a whole, intact heart.</p><p>The knowledge and tools developed throughout the course of this research were then applied to studying mouse models of Alzheimer’s disease in vivo, and studying hypertrophic human myocardium specimens ex vivo. Though a preliminary study using contrast-enhanced quantitative susceptibility mapping has revealed diamagnetic amyloid plaques associated with Alzheimer’s disease in the mouse brain ex vivo, non-contrast susceptibility imaging was unable to precisely identify these plaques in vivo. Susceptibility tensor imaging of human myocardium specimens at 9.4 T shows that susceptibility anisotropy is larger and mean susceptibility is more diamagnetic in hypertrophic tissue than in normal tissue. These findings support the hypothesis that myofilament proteins are a source of susceptibility contrast and anisotropy in myocardium. This collection of preclinical studies provides new tools and context for analyzing tissue structure, chemistry, and health in a variety of organs throughout the body.</p> / Dissertation

The objective of the proposed research is to advance the power efficiency of wireless neural stimulating systems in inductively powered implantable medical devices (IMD). Several innovative system- and circuit-level techniques are proposed towards the development of power-management circuits and wireless neural stimulating systems with inductive power transmission to improve the overall stimulation power efficiency. Neural stimulating IMDs have been proven as effective therapies to alleviate neurological diseases, while requiring high power and performance for more efficacious treatments. Therefore, power-management circuits and neural stimulators in IMDs should have high power efficiencies to operate with smaller received power from a larger distance. Neural stimulating systems are also required to have high stimulation efficacy for activating the target tissue with a minimum amount of energy, while ensuring charge-balanced stimulation. These features provide several advantages such as a long battery life in an external power transmitter, extended-range inductive power transfer, efficacious and safe stimulation, and less tissue damage from overheating. The proposed research presents several approaches to design and implement the power-efficient wireless neural stimulating IMDs: 1) optimized power-management circuits for inductively powered biomedical microsystems, 2) a power-efficient neural stimulating system with adaptive supply control, and 3) a wireless switched-capacitor stimulation (SCS) system, which is a combination structure of the power-management circuits and neural stimulator, to maximize both stimulator efficiency (before electrodes) and stimulus efficacy (after electrodes).

Longitudinal growth of long bone occurs at growth plates by a process called endochondral ossification. Endochondral ossification is affected by both biological and mechanical factors. This thesis focuses on the mechanical modulation of femoral bone growth occurring at the proximal growth plate, using mechanobiological theories reported in the literature. Finite element analysis was used to simulate bone growth. The first study analyzed the effect of subject-specific growth plate geometry over simplified growth plate geometry in numerical prediction of bone growth tendency. Subject-specific femur finite element model was constructed from magnetic resonance images of one able- bodied child. Gait kinematics and kinetics were acquired from motion analysis and analyzed further in musculoskeletal modelling to determine muscle and joint contact forces. These were used to determine loading on the femur in finite element analysis. The growth rate was computed based on a mechanobiological theory proposed by Carter and Wong, and a growth model in the principal stress direction was introduced. Our findings support the use of subject- specific geometry and of the principal stress growth direction in prediction of bone growth. The second study aimed to illustrate how different muscle groups’ activation during gait affects proximal femoral growth tendency in able-bodied children. Subject-specific femur models were used. Gait kinematics and kinetics were acquired for 3 able-bodied children, and muscle and joint contact forces were determined, similar to the first study. The contribution of different muscle groups to hip contact force was also determined. Finite element analysis was performed to compute the specific growth rate and growth direction due to individual muscle groups. The simulated growth model indicated that gait loading tends to reduce neck shaft angle and femoral anteversion during growth. The muscle groups that contributes most and least to growth rate were hip abductors and hip adductors, respectively. All muscle groups’ activation tended to reduce the neck shaft and femoral anteversion angles, except hip extensors and adductors which showed a tendency to increase the femoral anteversion. The third study’s aim was to understand the influence of different physical activities on proximal femoral growth tendency. Hip contact force orientation was varied to represent reported forces from a number of physical activities. The findings of this study showed that all studied physical activities tend to reduce the neck shaft angle and anteversion, which corresponds to the femur’s natural course during normal growth. The aim of the fourth study was to study the hypothesis that loading in the absence of physical activity, i.e. static loading, can have an adverse effect on bone growth. A subject-specific model was used and growth plate was modeled as a poroelastic material in finite element analysis. Prendergast’s indicators for bone growth was used to analyse the bone growth behavior. The results showed that tendency of bone growth rate decreases over a long duration of static loading. The study also showed that static sitting is less detrimental than static standing for predicted cartilage-to-bone differentiation likelihood, due to the lower magnitude of hip contact force. The prediction of growth using finite element analysis on experimental gait data and person- specific femur geometry, based on mechanobiological theories of bone growth, offers a biomechanical foundation for better understanding and prediction of bone growth-related deformity problems in growing children. It can ultimately help in treatment planning or physical activity guidelines in children at risk at developing a femur or hip deformity. / <p>QC 20170616</p>