Model-based quantitation of 3-D magnetic resonance angiographic images

Quantification of the degree of stenosis or vessel dimensions are important for diagnosis of vascular diseases and planning vascular interventions, Al though diagnosis from three-dimensional (3-D) magnetic resonance angiograms (MRA's) is mainly performed on two-dimensional (2-D) maximum intensity pro jections, automated quantification of vascular segments directly from the 3 -D dataset is desirable to provide accurate and objective measurements of t he 3-D anatomy. A model-based method for quantitative 3-D MRA is proposed. Linear vessel se gments are modeled with a central vessel axis curve coupled to a vessel wal l surface. A novel image feature to guide the deformation of the central ve ssel axis is introduced. Subsequently, concepts of deformable models are co mbined with knowledge of the physics of the acquisition technique to accura tely segment the vessel wall and compute the vessel diameter and other geom etrical properties. The method is illustrated and validated on a carotid bifurcation phantom, w ith ground truth and medical experts as comparisons, Also, results on 3-D t ime-of-flight (TOF) MRA images of the carotids are shown, The approach is a promising technique to assess several geometrical vascular parameters dire ctly on the source 3-D images, providing an objective mechanism for stenosi s grading.