Abstract
Superior semicircular canal dehiscence (SSCD) describes a pathological aperture at the level of the arcuate eminence. Techniques for quantifying defect size are described with most studies using two-dimensional lengths that underestimate the pathology. The objective of this study is to describe a novel method of measurement that combines manual segmentation of high-resolution computed tomography (HRCT) images of the temporal bone and a morphological skeletonization transform to calculate dehiscence volume. Images were imported into a freely available image segmentation tool: ITK-SNAP (version 3.4.0; available at: http://www.itksnap.org/) software. Coronal and sagittal planes were used to outline the dehiscence in all slices demonstrating the defect using the paintbrush tool. A morphological skeletonization transform derived a single-pixel thick representation of the original delineation. This "sheet" of voxels overlaid the dehiscence. Volume was calculated by counting the number of nonzero image voxels within this "sheet" and multiplying this number by the volume (mm(3)) of each voxel. A total of 70 cases of SSCD were identified. Overall, mean volume was 0.88 mm(3) (standard deviation: 0.57, range: 0.11-2.27). We present a novel technique for measuring SSCD, which we believe provides a more accurate representation of the pathology, and has the potential to standardize measurement of SSCD.