Improving visualization of three-dimensional aneurysm features via segmentation with upsampled resolution and gradient enhancement (SURGE)

BackgroundIntracranial aneurysm neck width tends to be overestimated when measured with three-dimensional rotational angiography (3DRA) compared with two-dimensional digital subtraction angiography (2D-DSA), owing to high curvature at the neck. This may affect morphological and hemodynamic analysis in support of treatment planning. We present and validate a method for extracting high curvature features, such as aneurysm ostia, during segmentation of 3DRA images.MethodsIn our novel SURGE (segmentation with upsampled resolution and gradient enhancement) approach, the gradient of an upsampled image is sharpened before gradient-based watershed segmentation. Neck measurements were performed for both standard and SURGE segmentations of 3DRA for 60 consecutive patients and compared with those from 2D-DSA. Those segmentations were also qualitatively compared for surface topology and morphology.ResultsCompared with the standard watershed method, SURGE reduced neck measurement error relative to 2D-DSA by >60%: median error was 0.49 mm versus 0.17 mm for SURGE, which is less than the average pixel resolution (~0.33 mm) of the 3DRA dataset. SURGE reduced neck width overestimations >1 mm from 13/60 to 5/60 cases. Relative to 2D-DSA, standard segmentations were overestimated by 16% and 93% at median and 95th percentiles, respectively, compared with only 6% and 37%, respectively, for SURGE.ConclusionSURGE provides operators with high-level control of the image gradient, allowing recovery of high-curvature features such as aneurysm ostia from 3DRA where conventional algorithms may fail. Compared with standard segmentation and tedious manual editing, SURGE provides a faster, easier, and more objective method for assessing aneurysm ostia and morphology.