Hemodynamics is a risk factor in Intracranial Aneurysms (IA).Understanding hemodynamic environment in vessels is thought to be important for realizing the mechanisms leading to IAs and other vascular pathologies. Exercise is known to reduce the high rates of case fatality in vascular disease. Hypertension and pharmacologically induced hypotension are common in IA patients. This study investigates how exercise, hypertension, and hypotension may influence aneurysmal hemodynamics.The effects of systemic alterations were simulated through boundary conditions by modulating the normotensive flow and pressure waveforms, in turn produced by a 1D systemic vascular model. Aneurysm location and flow pattern types were used to categorize the influence of hypotension and hypertension on relevant flow variables (velocity, pressure, and wall shear stress). Results indicate that, compared to other locations, vertebrobasilar aneurysms (VBA) are more sensitive to flow changes. In VBAs, space-averaged velocity at peak systole increased by 30% in hypertension (16-21% in other locations). Flow in VBAs in hypotension decreased by 20% (10-13% in other locations). Momentum-driven hemodynamic types were also affected more by hypotension and hypertension, than shear-driven types. This study shows how patient-specific modeling can be effectively used to identify location-specific flow patterns in a clinically-relevant study, thus reinforcing the role played by modeling technologies in furthering our understanding of cardiovascular disease, and their potential in future healthcare. In another attempt, three-dimensional velocity and pressure fields in carotid bifurcation were visualized and quantitized using Time-resolved 3D phase-contrast MRI (TR 3D PC MRI) and Computational Fluid Dynamics (CFD). A qualitative and quantitative comparison of the velocity and pressure fields obtained by each technique was presented. Although the main flow patterns were the same for both techniques, CFD showed a greater resolution in mapping the secondary and circulating flows. Overall RMS errors for all the corresponding data points in PC MRI and CFD were 14.27% in peak systole and 12.91% in end diastole relative to maximum velocity measured at each cardiac phase. Bland Altman plots showed very good agreement between two techniques. From this point of view, this study was not aimed to validate any of methods, instead, the consistency was assessed to accentuate the similarities and differences between TR 3D PC MRI and CFD.
