Browsing by Author "Lai, Victor"

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    3-D Printing of Anatomically-Accurate and Physiologically-Relevant Heart Models for Bioprosthetic Valve Testing (2020-01-31)
    (2020) Lai, Victor; University of Minnesota Duluth. Department of Chemistry and Biochemistry
    Transcatheter aortic valve replacement (TAVR) to treat severe aortic stenosis has exceeded the number of surgical aortic valve replacements done in the United States, because of its higher rates of success and lower risk of mortality, especially in older patients. While TAVR valves can achieve immediate relief of obstruction, complications such as aortic rupture and conduction abnormalities such as complete heart block may still occur, which require additional treatment. While it is believed that such valve complications may be exacerbated by pre-existing conditions, the underlying mechanisms causing such failures has not been well studied. In addition, there is currently no method to test the effectiveness of these valves under conditions that are specific to the patient. By applying a combination of Chemistry, Materials Science, and Engineering concepts, we want to develop a proof-of-concept of a 3-D printed heart model for bioprosthetic valve testing that is anatomically-accurate and physiologically-relevant to a patient and his/her underlying condition. The central hypothesis is that the effectiveness of such implants is influenced by the growth and remodeling of the surrounding native tissue in response to localized changes to the micromechanical and fluid flow environment due to the stented valve; understanding such changes to the cellular microenvironment will guide the design of TAVR implants to reduce the incidence of complications.
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    Bioengineered tissue mechanics: experimental characterization and a multi-component model
    (2013-08) Lai, Victor
    In the last few decades, tissue engineering has emerged as an interdisciplinary field of research which holds much promise as a complement to clinical medicine towards the overall improvement of personal health. Despite significant advances in this field, much work in TE continues to rely on an Edisonian approach of employing ad hoc methods to engineer tissues with desired properties without fundamental knowledge of the problem at hand. This thesis presents the development of a comprehensive model that predicts the mechanical properties of bioengineered tissue equivalents (TEs) based on its structure and composition, to enhance the understanding of the contribution of various biological components (e.g. biopolymeric fibers, cells, etc) to macroscopic mechanical properties of a tissue at different stages of tissue growth. The project framework considered bioengineered tissues as being composed of three components: fibrous networks, an interstitial matrix, and cells. The following interactions between different components were investigated: (a) multiple fiber networks, (b), fiber network + interstitial matrix, and (c) fiber network + cells. Experimentally, mechanical tests such as stress relaxation and tensile stretch to failure were coupled with electron microscopy, confocal microscopy, and biochemical analyses to probe tissue microstructure and composition. Constructs were formulated with varying compositions of the different components in a TE. These experimental results guided the development of the theoretical model. Modeling work built upon an existing single-component microstructural model by incorporating other components and morphological features as observed from experiment. Improvements to the model combined two approaches: (1) a microstructural approach via incorporation of morphological features observed from micrographs, and (2) a phenomenological approach using constitutive relations commonly employed for various biological structures. Model validation was done by comparing model predictions of mechanical behavior with experimental results; agreements and discrepancies alike shed insight into the complex interactions between different components the comprise a TE. Overall, the work presented in this thesis represented significant improvements to the predictive capabilities of our computational model, and established the foundation for further modifications to capture better the microstructure and mechanics of different components within a TE.