Abstract
Background Peripheral arterial disease (PAD) is a common manifestation of atherosclerosis and is defined as any pathologic process causing obstruction to blood flow in the arteries outside the heart; mainly the arteries supplying the lower extremities. Phase-contrast MRI (PC-MRI) provides ap owerful and non-invasive method to acquire spatially registered blood velocity. The velocity field, then, can be used to derive other clinically useful hemodynamic parameters, such as blood pressure gradients. Methods Herein, pressure gradient across an axisymmetric Gaussian-shaped 87% area stenosis phantom was estimated by solving the pressure-Poisson equation (PPE). The velocity field needed to solve the pressure equation was obtained using PC-MRI and Stereoscopic Particle Image Velocimetry (SPIV). Steady flow rate of 46.9 ml/s, corresponding to an inlet Reynolds number of 160, was used which mimics the Reynolds number of human common iliac artery. Sagittal PC-MRI images were acquired using
Highlights
Peripheral arterial disease (PAD) is a common manifestation of atherosclerosis and is defined as any pathologic process causing obstruction to blood flow in the arteries outside the heart; mainly the arteries supplying the lower extremities
Pressure gradients calculated from Phase-contrast MRI (PC-MRI), Stereoscopic Particle Image Velocimetry (SPIV) and Computational Fluid Dynamics (CFD) velocity data in a phantom model: comparison with catheter-based pressure measurement
Methods pressure gradient across an axisymmetric Gaussian-shaped 87% area stenosis phantom was estimated by solving the pressure-Poisson equation (PPE)
Summary
Peripheral arterial disease (PAD) is a common manifestation of atherosclerosis and is defined as any pathologic process causing obstruction to blood flow in the arteries outside the heart; mainly the arteries supplying the lower extremities. Phase-contrast MRI (PC-MRI) provides a powerful and non-invasive method to acquire spatially registered blood velocity. The velocity field, can be used to derive other clinically useful hemodynamic parameters, such as blood pressure gradients
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