A fully-automated statistical method for characterization of flow artifact presence in cardiac MRI

Methods Imaging studies Six healthy dogs were studied in a Siemens 1.5T scanner using three breath-held 2D SSFP cine sequences (Table 1) in the basal position where flow artifacts are most pronounced. Shared scan parameters: spatial_resolution=1.2x1.2x5mm3, flip_angle=70°, temporal_resolution=10-12ms, no parallel imaging. Image processing Each cine stack I(t) (t denotes trigger time) was loaded in Matlab and the per-pixel mean (IA) and variance (IV) were found across t. Initialized with a rectangle the size of IA, a contour was evolved, using a level-set approach, until it converged to the body-air interface, providing a binary mask M (M=1 for air). Image IR=IV/(IA) 2 (pixelwise division) was calculated and all values of IR in air (M=1) were collected to estimate the excess kurtosis (g) of their distribution H. The metric QK=g was used to quantify the presence of flow artifacts.