Hierarchical Shape Distributions for Automatic Identification of 3D Diastolic Vortex Rings from 4D Flow MRI

Vortex ring formation within the cardiac left ventricular (LV) blood flow has recently gained much interest as an efficient blood transportation mechanism and a potential early predictor of the chamber remodeling. In this work we propose a new method for automatic identification of vortex rings in the LV by means of 4D Flow MRI. The proposed method consists of three elements: 1) the 4D Flow MRI flow field is transformed into a 3D vortical scalar field using a well-established fluid dynamics-based vortex detection technique. 2) a shape signature of the cardiac vortex ring isosurface is derived from the probability distribution function of pairwise distances of randomly sampled points over the isosurface 3) a hierarchical clustering is then proposed to simultaneously identify the best isovalue that defines a vortex ring as well as the isosurface that corresponds to a vortex ring in the given vortical scalar field. The proposed method was evaluated in a datasets of 24 healthy controls as well as a dataset of 23 congenital heart disease patients. Results show great promise not only for vortex ring identification but also for allowing an objective quantification of vortex ring formation in the LV.