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Introduction: The rationale of the present proposal is to increase the accuracy and the viability of the mathematical modeling of physiological systems from the present theoretical and experimental level towards clinical applicability. In order to provide usable information for the diagnosis the models should reflect the properties of the patient. Furthermore, to ensure the accuracy of the models, the models should reflect the functions of the physiological system. These kinds of models would produce better clinical diagnosis trough individual accurate modeling providing personal diagnostic criteria. We have only limited measurements of the physiological system and its quantities. However, the more accurate modeling of the anatomy and the physical properties of the patient we have the more accurately we can simulate the underlying physical phenomena. Modeling brings forward new information from the anatomy of the patient provided by medical imaging methods and the knowledge o f the physical phenomena.
Goals: The purpose of the present proposal is to increase the accuracy and the viability of the mathematical modeling of physiological systems from the present theoretical and experimental level towards clinical applicability so that the emergent modeling methods can be employed to improve diagnostics and therapy in a clinical environment. The goal is to facilitate the construction of dynamic and adaptive models of the human body, to solve large computational models and to develop state-of-the-art post-processing. The models are to be dynamic, including the temporal function of the physiological system such as heart and breathing functions or blood flow. The models are to be adaptive, being based on the anatomy and functional properties of the individual patient. A further goal is to establish a cross-discipline research network making possible technology transfer between experts on computational mathematics, fluid flow modeling, bioelectric field analysis, clinical imaging and measurements and clinicians.
Methods: We focus on two model types:
1) Models of the electromagnetic properties of the human thorax and head and
2) Models of the mechanics and fluid dynamics of the cardiovascular system, especially that of the aorta.
In spite of modeling different phenomena, both model types share procedures for medical imaging, model construction and post- processing. The following tools and methods will be devised: Means to obtain the functional and anatomical tissue parameters from standard and advanced imaging and other measurement techniques based on mathematical and computational methods. Mathematical tools to enhance the computation of complex physiological systems, especially that of the flow in the aorta. The development is enabled by the high computational power of the modern computers, capability of modern MRI and ultrasound, advanced capability to calculate complex fluid flow fields in blood vessels as well as good understanding of the principle of reciprocity and the lead field theory.
Conclusions: These emergent methods can be employed to improve clinical diagnostics and therapy. This can be achieved by developing better measurement methods and signal analysis systems by learning more about the physiological systems underlying the measured signals and by developing better diagnosis by employing the models directly. In this proposal we concentrate on modeling of cardiovascular system and especially those related to cardiac function and large blood vessels such as aorta. Thus this would facilitate the combination of the results form the modeling groups and further combination of clinical measurement systems and their information for advanced diagnosis. In addition, these models are amenable to other applications, e.g. for assessing the absorption of radio frequency radiation. However, the main emphasis is on developing the mathematical procedures and tools to facilitate the construction and applications of the models.