Modeling Cardiovascular, Ocular, and Urinary Systems for Advancing Basic Science, Disease Diagnosis, and Treatment

This thesis advances the understanding of cardiovascular, ocular, and lower urinary tract systems by developing innovative mathematical models, experimental validation studies, and non-invasive diagnostic tools. The contributions of the present work bridge gaps in the current literature by addressing the lack of comprehensive models for specific physiological systems and developing clinically applicable solutions to improve diagnostics and personalized medicine. The first chapter introduces the importance of mathematical modeling in healthcare, asking the fundamental question we answered through this thesis: how modeling can guide our understanding, help design noninvasive technologies and support clinical decision-making for disease-specific conditions. The second chapter provides an overview of the cardiovascular system’s anatomy and physiology, how it connects to eye blood circulation, and the anatomy and physiology of the lower urinary tract. The third chapter focuses on modeling cardiovascular physiology and disease and comprises five case studies. The first three case studies extend the applicability domain of an existing cardiovascular physiology model by addressing sex-specific physiological differences, non-invasive monitoring methods, and the effects of cardiovascular diseases, particularly myocardial infarction. The final two case studies present the development of a new model that connects the cardiovascular system to the retinal circulation. This coupled model is then used to investigate how myocardial infarction and sex differences in the cardiovascular system affect retinal circulation. The fourth chapter addresses a significant gap in the modeling of the lower urinary tract by proposing novel mathematical approaches. It includes two case studies, where progressively more complex models are introduced to capture bladder filling, pressure dynamics, and neural control mechanisms during micturition. The chapter also highlights the potential for personalized model parameters. The work presented in this thesis integrates experimental data, theoretical modeling, and practical applications across multiple fields, including sensor development, systems physiology, and personalized medicine. It emphasizes the importance of interdisciplinary approaches in addressing complex physiological problems, with implications for improving healthcare diagnostics, monitoring, and treatment. By advancing mathematical modeling, validating these models experimentally, and translating them into clinical contexts, this thesis lays a foundation for innovative, personalized diagnostic tools and therapeutic strategies, contributing to the broader biomedical engineering and healthcare innovation field.