Real-time determination of skull thickness for a manually-navigated synergistic trepanation tool

Trepanation of the skull is a common procedure in neurosurgery with the problems of dural tears and wide cutting gaps. A hand-guided instrument containing a soft-tissue preserving saw whose cutting depth is automatically adapted on the basis of a-priori data (CT, MRI) is envisioned to reduce these problems. In this paper a major part of the system, a novel concept for real-time setpoint generation on the basis of CT or MRI data is presented. In this context, a dynamic depth-control according to the local skull thickness, a preoperative workflow for data reduction and a reliable and fast method for skull thickness computation in hard real-time have been developed. The most critical component of the new system is the real-time depth control based on setpoint information derived from large amounts of medical imaging data, in combination with the highly dynamic freehand resection path control by the human operator. To improve the assessment of the actual local skull thickness, different optimization methods are discussed. An evaluation of the algorithms in combination with suitable data structures has shown that despite the large amount of data a fast and reliable determination of the skull thickness in realtime can be realized.