Current diagnostic testing for cardiovascular pathology usually rests on either physiological or anatomic measurement. Multiple tests must then be combined to arrive at a conclusion regarding treatment of a specific pathology. Much of the diagnostic decisions currently made are based on rough estimates of outcomes, often derived from gross anatomic observations or extrapolation of physical laws. Thus, intervention for carotid and coronary disease is based on estimates of diameter stenosis, despite data to suggest that plaque character and lesion anatomy are important determinants of outcome. Similarly, abdominal aortic aneurysm (AAA) intervention is based on maximal aneurysm diameter without regard for arterial wall composition or individual aneurysm geometry. In other words, our current diagnostic tests do not reflect the sophistication of our current knowledge of vascular disease. Using a multimodal approach, computer modeling has the potential to predict clinical outcomes based on a variety of factors including arterial wall composition, surface anatomy and hemodynamic forces. We term this more sophisticated approach "patient specific diagnostics", in which the computer models are reconstructed from patient specific clinical visualizing modalities, and material properties are extracted from experimental measurements of specimens and incorporated into the modeling using advanced material models (including nonlinear anisotropic models) and performed as dynamic simulations using the FSI (fluid structure interaction) approach. Such an approach is sorely needed to improve the effectiveness of interventions. This article will review ongoing work in "patient specific diagnostics" in the areas of carotid, coronary and aneurismal disease. We will also suggest how this approach may be applicable to management of aortic dissection. New diagnostic methods should allow better patient selection, targeted intervention and modeling of the results of different therapies.