Fibrosis of vital organs remains one of the leading causes of death in the developed world, where it occurs predominantly in soft tissues (liver, lung, kidney, heart) through fibroblast proliferation and deposition of extracellular matrix (ECM). In the process of fibrosis, remodeling and deposition of ECM results in stiffening of cellular microenvironment; cells also respond to these changes in the stiffness through engagement of their cytoskeleton and signaling via cell-ECM contacts. Thus, understanding to what extent the stiffness of the cellular microenvironment changes as a consequence of fibrotic progression, and how cells respond to this change, is critical. In this thesis, we quantitatively measured stiffness of the lung parenchyma and its changes during fibrosis. We find that the average stiffness increases by approximately 10-fold. We then investigated how changes in ECM rigidity affect the cytoskeletal phenotype of lung fibroblasts. We find a complex relation between expression of the glycoprotein Thy-1 (CD90) and ECM rigidity-dependent cytoskeletal phenotype (i.e. “mechanotransduction”). Finally, we investigate a mechanism for the regulation of rigidity sensing by Thy-1 and its involvement in intracellular signaling through cell-ECM contacts. Taken together, this work helps define in vivo parameters critical to the fibrogenesis program and to define unique cellular phenotypes that may respond or contribute to mechanical homeostasis in fibrotic diseases.

No description available.

Um tema relevante de pesquisa em pneumologia atualmente é a contratilidade de via aérea, e como a mesma é modulada por estímulos mecânicos e farmacológicos. De modo a contribuir com este campo de pesquisa, este projeto tem por objetivo a execução de medições de grandezas associadas à mecânica respiratória de vias aéreas isoladas in vitro para avaliar sua resposta a estímulos externos como alterações de pressão transmural, estiramento, poluentes e drogas. Para tal finalidade, foi integrada uma nova instrumentação de processamento de imagens e condicionamento/estimulação de tecidos aos equipamentos já em uso em diversas pesquisas pelo Laboratório de Engenharia Biomédica da Escola Politécnica da Universidade de São Paulo. Este ambiente foi testado em corpos de prova; foi avaliado o efeito da pressão transmural na mecânica de traqueias e o ambiente foi utilizado na análise do efeito de bronco-constritores na mecânica respiratória de traqueias decelularizadas (utilizadas em transplante traqueal). Os testes em corpos de prova demonstraram a capacidade do ambiente em executar as medidas de interesse; os estudos com pressão transmural quantificaram a expansão das paredes da traqueia com o incremento da pressão interna e os estudos com traqueias decelularizadas mostram que as mesmas não respondem a broncoconstritores, ao contrário de traqueias normais que apresentaram indícios de contração. Desta forma, o ambiente foi capaz de realizar pesquisas de contratilidade de via aérea, demonstrando indícios da insensibilidade de traqueias decelularizadas a bronco-constritores. / Currently, a relevant field in the research of pulmonology is the contractibility of airways, and their modulation through mechanical and pharmacological stimuli. In order to contribute to this research, the goal of this project is to execute measurements of respiratory mechanic indicators to assess the behavior of isolated airways in vitro to external stimuli such as modifications in transmural pressure, dynamic stretching, pollution and drugs. For this purpose a new image processing and tissue conditioning/stimulation environment was integrated with the existing instrumentation already in use by the Biomedical Engineering Laboratory in the Escola Politécnica da Universidade de São Paulo. The environment was tested in tubular structures mimicking airways, the effect of transmural pressure in the respiratory mechanics of trachea was assessed and the environment was used in the research of the effect that bronchoconstrictor drugs have on the respiratory mechanics of decellularized tracheas (used in tracheal transplants). The tests in tubular structures proved the environments capacity to execute the desired measurements; the expansion of the tracheal walls with the rise of internal pressure was quantified and the experiments with decellularized tracheas show that they are not responsive to bronchoconstrictor durgs, opposite to normal tracheas that presented evidences of contraction. The environment succeeded in the execution of research of airway contractibility and demonstrated evidences of insensitivity of decellularized trachea to bronchoconstrictor drugs.

Magnetic Resonance Elastography (MRE) is a medical imaging technique used to generate a map of tissue elasticity. The resulting image is known as an elastogram, and gives a quantitative measure of stiffness in the examined tissue. The method is indirect; the elasticity, itself, is not measured. Instead, the physical response to a known stress is captured using magnetic resonance imaging, and is related to an elasticity parameter through a mathematical model of the tissue. In dynamic elastography, a harmonic stress is externally applied by a mechanical actuator, which is oriented to induce shear waves through the tissue. Once the system reaches a quasi-steady state, the displacement field is measured at a sequence of points in time. This data is the input to elasticity reconstruction algorithms. In this dissertation, the tissue is modelled as a linearly viscoelastic, isotropic continuum, undergoing harmonic motion with a known fundamental frequency. With this model, viscoelasticity is described by the complex versions of Lamé's first and second parameters. The second parameter, known as the complex shear modulus, is the one of interest. The term involving the first parameter is usually deemed negligible, so is ignored. The task is to invert the tissue model, a system of linear differential equations, to find the desired parameter. Direct inversion methods use the measured data directly in the model. Most current direct methods assume the shear modulus can be approximated locally by a constant, so ignore all derivative terms. This is known as the local homogeneity assumption, and allows for a simple, algebraic solution. The accuracy, however, is limited by the validity of the assumption. One of the purposes of MRE is to find pathological tissue marked by a higher than normal stiffness. At the boundaries of such diseased tissue, the stiffness is expected to change, invalidating the local homogeneity assumption, and hence, the shear modulus estimate. In order to capture the true shape of any stiff regions, a method must allow for local variations. Two new inversion methods are derived. In the first, a Green's function is introduced in an attempt to solve the differential equations. To simplify the system, the tissue is taken to be incompressible, another common assumption in direct inversion methods. Unfortunately, without designing an iterative procedure, the method still requires a homogeneity assumption, limiting potential accuracy. However, it is very fast and robust. In the second new inversion method, neither of the local homogeneity or incompressibility assumptions are made. Instead, the problem is re-posed in a quadratic optimization form. The system of linear differential equations is set as a constraint, and any free parameters are steered through quadratic programming techniques. It is found that, in most cases, there are no degrees of freedom in the optimization problem. This suggests that the system of differential equations has a fully determined solution, even without initial, boundary, or regularization conditions. The result is that estimates of the shear modulus and its derivatives can be obtained, locally, without requiring any assumptions that might invalidate the solution. The new inversion algorithms are compared to a few prominent, existing ones, testing accuracy and robustness. The Green's function method is found to have a comparable accuracy and noise performance to existing techniques. The second inversion method, employing quadratic optimization, is shown to be significantly more accurate, but not as robust. It seems the two goals of increasing accuracy and robustness are somewhat conflicting. One possible way to improve performance is to gather and use more data. If a second displacement field is generated using a different actuator location, further differential equations are obtained, resulting in a larger system. This enlarged system is better determined, and has improved signal-to-noise properties. It is shown that using data from a second field can increase accuracy for all methods.

Magnetic Resonance Elastography (MRE) is a medical imaging technique used to generate a map of tissue elasticity. The resulting image is known as an elastogram, and gives a quantitative measure of stiffness in the examined tissue. The method is indirect; the elasticity, itself, is not measured. Instead, the physical response to a known stress is captured using magnetic resonance imaging, and is related to an elasticity parameter through a mathematical model of the tissue. In dynamic elastography, a harmonic stress is externally applied by a mechanical actuator, which is oriented to induce shear waves through the tissue. Once the system reaches a quasi-steady state, the displacement field is measured at a sequence of points in time. This data is the input to elasticity reconstruction algorithms. In this dissertation, the tissue is modelled as a linearly viscoelastic, isotropic continuum, undergoing harmonic motion with a known fundamental frequency. With this model, viscoelasticity is described by the complex versions of Lamé's first and second parameters. The second parameter, known as the complex shear modulus, is the one of interest. The term involving the first parameter is usually deemed negligible, so is ignored. The task is to invert the tissue model, a system of linear differential equations, to find the desired parameter. Direct inversion methods use the measured data directly in the model. Most current direct methods assume the shear modulus can be approximated locally by a constant, so ignore all derivative terms. This is known as the local homogeneity assumption, and allows for a simple, algebraic solution. The accuracy, however, is limited by the validity of the assumption. One of the purposes of MRE is to find pathological tissue marked by a higher than normal stiffness. At the boundaries of such diseased tissue, the stiffness is expected to change, invalidating the local homogeneity assumption, and hence, the shear modulus estimate. In order to capture the true shape of any stiff regions, a method must allow for local variations. Two new inversion methods are derived. In the first, a Green's function is introduced in an attempt to solve the differential equations. To simplify the system, the tissue is taken to be incompressible, another common assumption in direct inversion methods. Unfortunately, without designing an iterative procedure, the method still requires a homogeneity assumption, limiting potential accuracy. However, it is very fast and robust. In the second new inversion method, neither of the local homogeneity or incompressibility assumptions are made. Instead, the problem is re-posed in a quadratic optimization form. The system of linear differential equations is set as a constraint, and any free parameters are steered through quadratic programming techniques. It is found that, in most cases, there are no degrees of freedom in the optimization problem. This suggests that the system of differential equations has a fully determined solution, even without initial, boundary, or regularization conditions. The result is that estimates of the shear modulus and its derivatives can be obtained, locally, without requiring any assumptions that might invalidate the solution. The new inversion algorithms are compared to a few prominent, existing ones, testing accuracy and robustness. The Green's function method is found to have a comparable accuracy and noise performance to existing techniques. The second inversion method, employing quadratic optimization, is shown to be significantly more accurate, but not as robust. It seems the two goals of increasing accuracy and robustness are somewhat conflicting. One possible way to improve performance is to gather and use more data. If a second displacement field is generated using a different actuator location, further differential equations are obtained, resulting in a larger system. This enlarged system is better determined, and has improved signal-to-noise properties. It is shown that using data from a second field can increase accuracy for all methods.

Fibrosis of vital organs remains one of the leading causes of death in the developed world, where it occurs predominantly in soft tissues (liver, lung, kidney, heart) through fibroblast proliferation and deposition of extracellular matrix (ECM). In the process of fibrosis, remodeling and deposition of ECM results in stiffening of cellular microenvironment; cells also respond to these changes in the stiffness through engagement of their cytoskeleton and signaling via cell-ECM contacts. Thus, understanding to what extent the stiffness of the cellular microenvironment changes as a consequence of fibrotic progression, and how cells respond to this change, is critical. In this thesis, we quantitatively measured stiffness of the lung parenchyma and its changes during fibrosis. We find that the average stiffness increases by approximately 10-fold. We then investigated how changes in ECM rigidity affect the cytoskeletal phenotype of lung fibroblasts. We find a complex relation between expression of the glycoprotein Thy-1 (CD90) and ECM rigidity-dependent cytoskeletal phenotype (i.e. “mechanotransduction”). Finally, we investigate a mechanism for the regulation of rigidity sensing by Thy-1 and its involvement in intracellular signaling through cell-ECM contacts. Taken together, this work helps define in vivo parameters critical to the fibrogenesis program and to define unique cellular phenotypes that may respond or contribute to mechanical homeostasis in fibrotic diseases.

In vitro and in vivo models were proposed to evaluate the effects of ischemic mitral regurgitation and surgical repair on the function and mechanics of the heart’s mitral valve. In specific aim 1, a novel transducer was developed to measure the radially directed forces that may act on devices implanted to the mitral annulus. In an ovine model, radial forces were found to statistically increase with left ventricular pressure and were reduced in the setting of ischemic mitral regurgitation. In specific aim 2, the suture forces required to constrain true-sized and undersized annuloplasty rings to the mitral annulus of ovine animals was evaluated. Suture forces were observed to be larger on the anterior aspect of the rings and were elevated with annular undersizing. In specific aim 3, an in vitro simulator’s ability to mimic healthy and ischemic mitral regurgitation ovine mitral valve function was evaluated. After understanding the accuracy of the model, the in vitro ischemic mitral regurgitation model was used to evaluate the progressive effects of annuloplasty on strut and intermediary chordal tethering. The generated data and knowledge will contribute to the development of more durable devices and techniques to assess the significant clinical burden known as ischemic mitral regurgitation.

This thesis presents research that was conducted to develop anatomically realistic finite element models of breast deformation under a variety of gravity loading conditions to assist clinicians in tracking suspicious tissues across multiple imaging modalities. Firstly, the accuracy of the modelling framework in predicting deformations of a homogeneous body was measured using custom designed silicon gel phantoms. The model predicted surface deformations with an average RMS error of 1.5 mm +/- 0.2 mm and tracked internal marker locations with an average RMS error of 1.4 mm +/- 0.7 mm. A novel method was then developed to determine the reference configuration of a body, when given its mechanical properties, boundary conditions and a deformed configuration. The theoretical validity of the technique was confirmed with an analytic solution. The accuracy of the method was also measured using silicon gel experiments, predicting the reference configuration surface with an average RMS error of 1.3 mm +/- 0.1 mm, and tracking internal marker locations with an average error of 1.5 mm +/- 0.8 mm. Silicon gel composites were then created to measure the accuracy of standard techniques to model heterogeneity. The models did not match the experimentally recorded deformations. This highlighted the need for further validation exercises on modelling heterogeneity before modelling them in the breast. A semi-automated algorithm was developed to fit finite element models to the skin and muscle surfaces of each individual, which were segmented from breast MR images. The code represented the skin with an average RMS error of 1.46 mm +/- 0.32 mm and the muscle with an average RMS error of 1.52 mm +/- 0.3 mm. The framework was then tested using images of the breast obtained under different gravity loading conditions and neutral buoyancy. A homogeneous model was first developed using the neutral buoyancy images as a representation of the reference configuration. The model did not accurately capture the regional deformations of the breast under gravity loading. However, the gross shape of the breast was reproduced, indicating that a biomechanical model of the breast could be useful to reliably track tissues across multiple images for cancer diagnosis. / This research was sponsored by the Top Achiever Doctoral Scholarship and the University of Auckland Doctoral Scholarship. Extra funding for travel was provided by the Graduate Research Fund and the John Logan Campbell Trust Fund.

This thesis presents research that was conducted to develop anatomically realistic finite element models of breast deformation under a variety of gravity loading conditions to assist clinicians in tracking suspicious tissues across multiple imaging modalities. Firstly, the accuracy of the modelling framework in predicting deformations of a homogeneous body was measured using custom designed silicon gel phantoms. The model predicted surface deformations with an average RMS error of 1.5 mm +/- 0.2 mm and tracked internal marker locations with an average RMS error of 1.4 mm +/- 0.7 mm. A novel method was then developed to determine the reference configuration of a body, when given its mechanical properties, boundary conditions and a deformed configuration. The theoretical validity of the technique was confirmed with an analytic solution. The accuracy of the method was also measured using silicon gel experiments, predicting the reference configuration surface with an average RMS error of 1.3 mm +/- 0.1 mm, and tracking internal marker locations with an average error of 1.5 mm +/- 0.8 mm. Silicon gel composites were then created to measure the accuracy of standard techniques to model heterogeneity. The models did not match the experimentally recorded deformations. This highlighted the need for further validation exercises on modelling heterogeneity before modelling them in the breast. A semi-automated algorithm was developed to fit finite element models to the skin and muscle surfaces of each individual, which were segmented from breast MR images. The code represented the skin with an average RMS error of 1.46 mm +/- 0.32 mm and the muscle with an average RMS error of 1.52 mm +/- 0.3 mm. The framework was then tested using images of the breast obtained under different gravity loading conditions and neutral buoyancy. A homogeneous model was first developed using the neutral buoyancy images as a representation of the reference configuration. The model did not accurately capture the regional deformations of the breast under gravity loading. However, the gross shape of the breast was reproduced, indicating that a biomechanical model of the breast could be useful to reliably track tissues across multiple images for cancer diagnosis. / This research was sponsored by the Top Achiever Doctoral Scholarship and the University of Auckland Doctoral Scholarship. Extra funding for travel was provided by the Graduate Research Fund and the John Logan Campbell Trust Fund.

This thesis presents research that was conducted to develop anatomically realistic finite element models of breast deformation under a variety of gravity loading conditions to assist clinicians in tracking suspicious tissues across multiple imaging modalities. Firstly, the accuracy of the modelling framework in predicting deformations of a homogeneous body was measured using custom designed silicon gel phantoms. The model predicted surface deformations with an average RMS error of 1.5 mm +/- 0.2 mm and tracked internal marker locations with an average RMS error of 1.4 mm +/- 0.7 mm. A novel method was then developed to determine the reference configuration of a body, when given its mechanical properties, boundary conditions and a deformed configuration. The theoretical validity of the technique was confirmed with an analytic solution. The accuracy of the method was also measured using silicon gel experiments, predicting the reference configuration surface with an average RMS error of 1.3 mm +/- 0.1 mm, and tracking internal marker locations with an average error of 1.5 mm +/- 0.8 mm. Silicon gel composites were then created to measure the accuracy of standard techniques to model heterogeneity. The models did not match the experimentally recorded deformations. This highlighted the need for further validation exercises on modelling heterogeneity before modelling them in the breast. A semi-automated algorithm was developed to fit finite element models to the skin and muscle surfaces of each individual, which were segmented from breast MR images. The code represented the skin with an average RMS error of 1.46 mm +/- 0.32 mm and the muscle with an average RMS error of 1.52 mm +/- 0.3 mm. The framework was then tested using images of the breast obtained under different gravity loading conditions and neutral buoyancy. A homogeneous model was first developed using the neutral buoyancy images as a representation of the reference configuration. The model did not accurately capture the regional deformations of the breast under gravity loading. However, the gross shape of the breast was reproduced, indicating that a biomechanical model of the breast could be useful to reliably track tissues across multiple images for cancer diagnosis. / This research was sponsored by the Top Achiever Doctoral Scholarship and the University of Auckland Doctoral Scholarship. Extra funding for travel was provided by the Graduate Research Fund and the John Logan Campbell Trust Fund.