We present a novel shape metric for quantification of shape differences between the spatial components obtained from independent component analysis (ICA) of group functional magnetic resonance imaging (fMRI) data. This metric is utilized to measure the difference in shapes of the activation regions obtained from different subjects within a group (healthy controls or patients). The parameters comprising the metric are computed for each pixel on the outermost contour (edge) of an activation region for each slice. These parameters are in the form of (r, θ) pairs that may be interpreted as the length and orientation of a vector originating from the centroid of the activation region to the pixel belonging to the boundary contour. Using this information we extract three features that quantify the shape difference between the two shapes under observation. The reference and observation shapes may be selected in two ways: (a) activation maps from two different subjects or (b) mean activation map compared against subject-wise activations, as obtained from group ICA. We present different methods to visualize the shape differences, thus providing a tool to observe the spatial differences within a group or across groups. In addition to the above results, we also address a few special cases where two or more activation contours are present in a single slice and present potential solutions for accounting for these regions as special measures. Our results show that this metric has utility in creating a better understanding of the variability in brain activity among different groups of subjects performing the same task.