Robot- and computer-assisted craniotomy (CRANIO): From active systems to synergistic man—machine interaction

Abstract

Computer and robot assistance in craniotomy/craniectomy procedures is intended to increase precision and efficiency of the removal of calvarial tumours, enabling the preoperative design and manufacturing of the corresponding implant. In the framework of the CRANIO project, an active robotic system was developed to automate the milling processes based on a predefined resection planning. This approach allows for a very efficient milling process, but lacks feedback of the intra-operative process to the surgeon. To better integrate the surgeon into the process, a new teleoperated synergistic architecture was designed. This enables the surgeon to realize changes during the procedure and use their human cognitive capabilities. The preoperative planning information is used as guidance for the user interacting with the system through a master—slave architecture. In this article, the CRANIO system is presented together with this new synergistic approach. Experiments have been performed to evaluate the accuracy of the system in active and synergistic modes for the bone milling procedure. The laboratory studies showed the general feasibility of the new concept for the selected medical procedure and determined the accuracy of the system. Although the integration of the surgeon partially reduces the efficiency of the milling process compared with a purely active (automatic) milling, it provides more feedback and flexibility to the user during the intra-operative procedure. Editor's note: This paper was commissioned for this Image Guided Surgery special issue, but has been published in an earlier issue. It can be found in Proc. IMechE, Part H: J. Engineering in Medicine, 2010, 224(H3), 441–452. DOI: 10.1243/09544119JEIM596.

Augmentation of haptic feedback for teleoperated robotic surgery

“…In case of craniectomies, bone is removed by milling if an adhesion of the dura mater and the skull bone is suspected [29]. However, due to inaccuracies in image acquisition (CT-Scan resolution ~ 0.45 mm [30]) and optical tracking (accuracy ~ 0.5 mm [31,32]) security offsets of at least 1 mm from the inner bone surface need to be planned preoperatively [30]. Due to this uncertainty, no assistances based on planning data can be offered within the safety offset.…”

“…The second phase (P2) targets interventions (e.g., craniectomies) where due to limitations of the acquired data (i.e., image acquisition resolution and optical tracking), assistances cannot be offered in all degrees of freedom (DOF). Below a certain security offset (approximately 1 mm [30]), haptic feedback in the depth direction has to be relied upon, while haptic guidance is offered in the remaining DOFs, enabling a synergistic path control [12]. A simulated haptic feedback was implemented based on the force profile in [33].…”

Evaluation of a synergistically controlled semiautomatic trepanation system for neurosurgery

“…In neurosurgery, Xia et al have implemented the synergistic control concept [6] for skull base surgery and Cunha-Cruz et al for craniectomy [4]. Using handheld tools, a better integration into the existing workflow can potentially be achieved.…”

“…To improve the procedure of opening the skull, different robotic systems have been developed autonomously performing craniotomies [3] as well as craniectomies [4]. As these robots use milling cutters for the craniotomy, the cutting cap cannot be reduced significantly.…”

Smart bioimpedance-controlled craniotomy: Concept and first experiments

“…2 Various computer-assisted approaches have been proposed to support the surgeon in performing craniotomy. [3][4][5][6] However, most of these systems use milling tools for bone cutting and do not allow a sufficient reduction of the cutting gap. Furthermore, a complete transection of the bone requires contact between the underlying soft tissue and the milling tool or tool guard, which leads potentially to severe soft tissue damage.…”