Quantification of standing cones in elliptical closures using digital image correlation

Summary: Abstract Body: Optimal results of linear closures using a surgical ellipse can be hindered by standing cone deformities, which are characteristic bunching of excess tissue formed during closure. Current surgical dogma suggests standing cones are inevitable when a surgical ellipse’s length-width ratio is less than 3-4:1. To date, there have been no attempts to experimentally quantify standing cones in cutaneous surgery. Prior modeling attempts fail to capture the true mechanical behavior of skin as it is difficult to model its anisotropic, non-linear, and inhomogeneous properties. This study adopted three-dimensional (3D) digital image correlation (DIC) to examine porcine skin tissue deformation. DIC is an optical measuring technique that accurately quantifies changes in displacement of speckles into local mechanical strain forces. 3D DIC successfully captured the expected tissue deformation following linear closure of a surgical ellipse, demonstrating vertical end compression along the ellipse’s long axis, consistent with standing cone formation. Normal strain was estimated from summation of major and minor principal strains. Standing cone severity was quantified using the standard deviation along the ellipse’s long axis of sampled average normal strains in the short axis in a rectangular bounding box dependent on ellipse length. Using triplicates, average standing cone severity was 0.066 for the 2:1 ellipses, 0.052 for 3:1, and 0.035 for 5:1. Our work successfully maps the expected decreasing standing cone formation with increasing length-width ellipse ratios. We demonstrate a quantitative model for capturing standing cone deformities, enabling future research for analyzing the impact of various surgical techniques on standing cone formation. Yash Kumar¹, Nada Hentati¹, Dustin Demeo², Diya Ramanathan³, Sheena Hill⁴, John Galeotti⁵, Bryan Carroll^{6, 1} 1. Case Western Reserve University School of Medicine, Cleveland, OH, United States. 2. Pathology, Stanford Medicine, Stanford, CA, United States. 3. Otolaryngology, University of Wisconsin-Madison, Madison, WI, United States. 4. Dermatology Specialists of Greensboro, Greensboro, NC, United States. 5. Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA, United States. 6. Dermatology, UH Cleveland Medical Center, Cleveland, OH, United States. Bioinformatics, Computational Biology, and Imaging