The introduction of computational tools to construct and evaluate models of the anatomy and physiology of human biological systems can enable researchers to test hypotheses regarding abnormal conditions, examine treatments, and, in the long term, enable clinicians to predict the outcome of alternative treatment plans. The computational methods underlying diagnostic imaging are prevalent in clinical environments. However, this diagnostic information, typically expensive to acquire, is provided to the physician without the tools necessary to evaluate the outcome of various treatments. The individual variability and inherent complexity of human biological systems is such that imaging data alone is insufficient to predict the outcome of a given treatment.

Hemodynamic conditions, including velocity, shear, and pressure, play an important role in the modulation of vascular adaptation and the localization of vascular disease. Consequently, understanding the local hemodynamic environment in a region of the vascular system has been an important field of research in the last two decades. In the coming years, computational fluid dynamics methods will move beyond the academic research domain and be implemented in Computer Aided Surgical Planning software. These methods will augment the information available from medical diagnostic imaging to define patient-specific predictive computer models.

Critical issues in the application of CFD, Visualization and Virtual Reality to Cardiovascular Medicine are examined. A software system developed for Computer Aided Surgical Planning which provides an integrated set of tools to test hypotheses regarding the effect of alternate treatment plans on vascular hemodynamics is described.

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