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The field of robotic surgery has progressed from small teams of researchers repurposing industrial robots, to a competitive and highly innovative subsection of the medical device industry. Surgical robots allow surgeons to perform tasks with greater ease, accuracy, or safety, and fall under one of four levels of autonomy; active, semi-active, passive, and remote manipulator. The increased accuracy afforded by surgical robots has allowed for cementless hip arthroplasty, improved postoperative alignment following knee arthroplasty, and reduced duration of intraoperative fluoroscopy among other benefits. Cutting of bone has historically used tools such as hand saws and drills, with other elaborate cutting tools now used routinely to remodel bone. Improvements in cutting accuracy and additional options for safety and monitoring during surgery give robotic surgeries some advantages over conventional techniques. This paper aims to provide an overview of current robots and tools with a common target tissue of bone, proposes a new process for defining the level of autonomy for a surgical robot, and examines future directions in robotic surgery.

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Purpose Bone tumours must be surgically excised in one piece with a margin of healthy tissue. The unique nature of each bone tumour case is well suited to the use of patient-specific implants, with additive manufacturing allowing production of highly complex geometries. This work represents the first assessment of the combination of surgical robotics and patient-specific additively manufactured implants. Methods The development and evaluation of a robotic system for bone tumour excision, capable of milling complex osteotomy paths, is described. The developed system was evaluated as part of an animal trial on 24 adult male sheep, in which robotic bone excision of the distal femur was followed by placement of patient-specific implants with operative time evaluated. Assessment of implant placement accuracy was completed based on post-operative CT scans. Results A mean overall implant position error of 1.05 ± 0.53 mm was achieved, in combination with a mean orientation error of 2.38 ± 0.98°. A mean procedure time (from access to implantation, excluding opening and closing) of 89.3 ± 25.25 min was observed, with recorded surgical time between 58 and 133 min, with this approximately evenly divided between robotic (43.9 ± 15.32) and implant-based (45.4 ± 18.97) tasks. Conclusions This work demonstrates the ability for robotics to achieve repeatable and precise removal of complex bone volumes of the type that would allow en bloc removal of a bone tumour. These robotically created volumes can be precisely filled with additively manufactured patient-specific implants, with minimal gap between cut surface and implant interface.

Purpose Planning for bone tumor resection surgery is a technically demanding and time-consuming task, reliant on manual positioning of planar cuts in a virtual space. More elaborate cutting approaches may be possible through the use of surgical robots or patient-specific instruments; however, methods for preparing such a resection plan must be developed. Methods This work describes an automated approach for generating conformal bone tumor resection plans, where the resection geometry is defined by the convex hull of the tumor, and a focal point. The resection geometry is optimized using particle swarm, where the volume of healthy bone collaterally resected with the tumor is minimized. The approach was compared to manually prepared planar resection plans from an experienced surgeon for 20 tumor cases. Results It was found that algorithm-generated hull-type resections greatly reduced the volume of collaterally resected healthy bone. The hull-type resections resulted in statistically significant improvements compared to the manual approach (paired t test, p < 0.001). Conclusions The described approach has potential to improve patient outcomes by reducing the volume of healthy bone collaterally resected with the tumor and preserving nearby critical anatomy.