Final Activity Report Summary - C-CARES (Cardiovascular-Consistent Approach for REfined Simulation) The last ten years have seen significant advances in the field of functional cardiovascular imaging. It is becoming increasingly feasible to obtain high resolution dynamic images of ventricular contraction and of the mechanical and haemodynamic behaviour of the arteries. The new technologies, apart from their direct clinical benefits, also have the potential to provide the high quality input data which is necessary for the implementation of computational models of the cardiovascular system. The clinical potential of such models, which are developed to have a predictive capacity, to improve understanding of the complex system, or to provide data at a resolution which cannot be obtained via clinical or experimental measurements, is increasingly being recognised. The task of developing and integrating these models was challenging. Models could be validated in isolation. When clinical input data was not available, boundary conditions had to be defined. One vision was that they could be provided in terms of physiologically-oriented models, which were of reduced complexity in terms of the necessary computational resources; however they had to be of sufficient complexity to represent the interaction of the system and its environment. Existing computational resources and software provided a suitable framework for testing in silico models, working hypotheses and what-if scenarios. Present computational resources also allowed for the improvement of boundary conditions to produce dynamic and biologically meaningful models. While using the available computational resources, the modeller was actively restricting the clinical usefulness of the model a posteriori when fixing boundary conditions, since simulation results were difficult to correlate with clinical results related to other organs or subsystems. The results were also difficult to be linked to other computational models in practice. Without appropriate, biologically-oriented boundary conditions, there was a missing link in the modelling process and this inevitably had consequences on the model applicability and the generation of knowledge from it. Cardiovascular models presented a particular challenge since they required both a multi-scale and a multi-physics approach. Using complex three-dimensional numerical models for the whole system was computationally prohibitive; thus a compromise was needed. The most sophisticated fluid-solid interaction structures provided exquisite detail in the fluid domain, but were limited by the prescription of boundary conditions. An alternative multi-scale solution was to couple lumped parameter models in terms of the boundary conditions with a finite element model for the part in which detail and accuracy were needed. Significant improvement could be achieved in understanding the underlying physics if the lumped parameter approach included more physiologically representative mechanisms rather than traditional black-box models. This work encompassed a number of diverse disciplines, such as physiology, biomechanics, fluid mechanics and simulation, in order to develop a suitable framework for coupling three-dimensional and lumped parameter models and a predictive model of the behaviour of a prosthetic heart valve in vivo. A commercial, finite volume, computational fluid dynamics (CFD) code (ANSYS/CFX) was used for the three-dimensional model component. Our main achievement was the integration of disparate techniques ( i.e. lumped parameter models with three-dimensional models) to present a three-dimensional model of a cardiac valve using the internal features that were available in ANSYS/CFX coupled with a multi-scale model of the left ventricle to address complex cardiovascular problems.
