VFF: Visualizing Massively Parallel Models of Hemodynamics in the Human Vasculature

The potential impact of blood flow simulations on the diagnosis and treatment of patients suffering from vascular disease is tremendous. Empowering models of the full arterial tree can provide insight into diseases such as arterial hypertension and enables the study of the influence of local factors on global hemodynamics. Faster calculation of flow in full arterial networks enables unprecedented risk stratification on a per-patient basis. A key physical quantity of medical interest from these simulations is endothelial shear stress (ESS). Low ESS has been associated with sites of lesion formation and rapid progression of disease in the coronary arteries. Having effective visualizations of a patient's ESS data is vital for the quick and thorough non-invasive evaluation by a cardiologist. A task taxonomy for hemodynamics based on a user study with domain experts will be presented. Through a quantitative user study with domain experts that evaluates the effect of 2D versus 3D artery representations and of color maps on identifying regions of low ESS, we have shown statistically significant results demonstrating that our 2D visualizations are more accurate and efficient than 3D representations, and that a perceptually appropriate color map leads to fewer diagnostic mistakes than a rainbow color map. This talk will cover the key aspects of building such a massively parallel model, methods employed to visualize the results in an effective manner, and current open questions.