J Neurol Surg B Skull Base 2017; 78(02): 197-200
DOI: 10.1055/s-0036-1594241
Original Article
Georg Thieme Verlag KG Stuttgart · New York

Computerized Assessment of Superior Semicircular Canal Dehiscence Size using Advanced Morphological Imaging Operators

Joel S. Beckett
1   Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, United States
,
Carlito Lagman
1   Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, United States
,
Lawrance K. Chung
1   Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, United States
,
Timothy T. Bui
1   Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, United States
,
Seung J. Lee
1   Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, United States
,
Brittany L. Voth
1   Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, United States
,
Bilwaj Gaonkar
1   Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, United States
,
Quinton Gopen
2   Department of Head and Neck Surgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, United States
,
Isaac Yang
1   Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, United States
2   Department of Head and Neck Surgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, United States
› Author Affiliations
Further Information

Publication History

19 September 2016

10 October 2016

Publication Date:
07 December 2016 (online)

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 (mm3) of each voxel. A total of 70 cases of SSCD were identified. Overall, mean volume was 0.88 mm3 (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.

 
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