Making Robots Mill Bone More Like Human Surgeons: Using Bone Density and Anatomic Information to Mill Safely and Efficiently.

Abstract

Surgeons and robots typically use different approaches for bone milling. Surgeons adjust their speed and tool incidence angle constantly, which enables them to efficiently mill porous bone. Surgeons also adjust milling parameters such as speed and depth of cut throughout the procedure based on proximity to sensitive structures like nerves and blood vessels. In this paper we use image-based bone density estimates and segmentations of vital anatomy to make a robot mill more like a surgeon and less like an industrial computer numeric controlled (CNC) milling machine. We produce patient-specific plans optimizing velocity and incidence angles for spherical cutting burrs. These plans are particularly useful in bones of variable density and porosity like the human temporal bone. They result in fast milling in non-critical areas, reducing overall procedure time, and lower forces near vital anatomy. We experimentally demonstrate the algorithm on temporal bone phantoms and show that it reduces mean forces near vital anatomy by 63% and peak forces by 50% in comparison to a CNC-type path, without adding time to the procedure.