Safety margins in robotic bone milling: from registration uncertainty to statistically safe surgeries. Issue 3 (21st September 2016)

• Record Type: Journal Article
• Authors: Siebold, Michael A.; Dillon, Neal P.; Fichera, Loris; Labadie, Robert F.; Webster, Robert J.; Fitzpatrick, J. Michael
• Is Part Of: International journal of medical robotics and computer assisted surgery. Volume 13:Issue 3(2017)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2016-09-21
• Subjects: image guidance -- mastoidectomy -- path planning -- registration -- robotic surgery -- target registration error; Robotics in medicine -- Periodicals; Surgery -- Technological innovations -- Periodicals; Imaging systems in medicine -- Periodicals; 617.90285
• DOI: 10.1002/rcs.1773
• Languages: English
• ISSNs: 1478-5951

Abstract

Abstract: Background: When robots mill bone near critical structures, safety margins are used to reduce the risk of accidental damage due to inaccurate registration. These margins are typically set heuristically with uniform thickness, which does not reflect the anisotropy and spatial variance of registration error. Methods: A method is described to generate spatially varying safety margins around vital anatomy using statistical models of registration uncertainty. Numerical simulations are used to determine the margin geometry that matches a safety threshold specified by the surgeon. Results: The algorithm was applied to CT scans of five temporal bones in the context of mastoidectomy, a common bone milling procedure in ear surgery that must approach vital nerves. Safety margins were generated that satisfied the specified safety levels in every case. Conclusions: Patient safety in image‐guided surgery can be increased by incorporating statistical models of registration uncertainty in the generation of safety margins around vital anatomy.