A self-developed and constructed robot for minimally invasive cochlear implantation

Conclusion: A robot built specifically for stereotactic cochlear implantation provides equal or better accuracy levels together with a better integration into a clinical environment, when compared to existing approaches based on industrial robots. Objectives: To evaluate the technical accuracy of a robotic system developed specifically for lateral skull base surgery in an experimental setup reflecting the intended clinical application. The invasiveness of cochlear electrode implantation procedures may be reduced by replacing the traditional mastoidectomy with a small tunnel slightly larger in diameter than the electrode itself. Methods: The end-to-end accuracy of the robot system and associated image-guided procedure was evaluated on 15 temporal bones of whole head cadaver specimens. The main components of the procedure were as follows: reference screw placement, cone beam CT scan, computer-aided planning, pair-point matching of the surgical plan, robotic drilling of the direct access tunnel, and post-operative cone beam CT scan and accuracy assessment. Results: The mean accuracy at the target point (round window) was 0.56 ± 41 mm with an angular misalignment of 0.88 ± 0.41°. The procedural time of the registration process through the completion of the drilling procedure was 25 ± 11 min. The robot was fully operational in a clinical environment.

Impact of a self-developed planning and self-constructed navigation system on skull base surgery: 10 years experience

CONCLUSION: Our self-developed planning and navigation system has proven its capacity for accurate surgery on the anterior and lateral skull base. With the incorporation of augmented reality, image-guided surgery will evolve into 'information-guided surgery'. OBJECTIVE: Microscopic or endoscopic skull base surgery is technically demanding and its outcome has a great impact on a patient's quality of life. The goal of the project was aimed at developing and evaluating enabling navigation surgery tools for simulation, planning, training, education, and performance. This clinically applied technological research was complemented by a series of patients (n=406) who were treated by anterior and lateral skull base procedures between 1997 and 2006. MATERIALS AND METHODS: Optical tracking technology was used for positional sensing of instruments. A newly designed dynamic reference base with specific registration techniques using fine needle pointer or ultrasound enables the surgeon to work with a target error of < 1 mm. An automatic registration assessment method, which provides the user with a color-coded fused representation of CT and MR images, indicates to the surgeon the location and extent of registration (in)accuracy. Integration of a small tracker camera mounted directly on the microscope permits an advantageous ergonomic way of working in the operating room. Additionally, guidance information (augmented reality) from multimodal datasets (CT, MRI, angiography) can be overlaid directly onto the surgical microscope view. The virtual simulator as a training tool in endonasal and otological skull base surgery provides an understanding of the anatomy as well as preoperative practice using real patient data. RESULTS: Using our navigation system, no major complications occurred in spite of the fact that the series included difficult skull base procedures. An improved quality in the surgical outcome was identified compared with our control group without navigation and compared with the literature. The surgical time consumption was reduced and more minimally invasive approaches were possible. According to the participants' questionnaires, the educational effect of the virtual simulator in our residency program received a high ranking.

DYPTOP: a cost-efficient TOPMODEL implementation to simulate sub-grid spatio-temporal dynamics of global wetlands and peatlands

Simulating the spatio-temporal dynamics of inundation is key to understanding the role of wetlands under past and future climate change. Earlier modelling studies have mostly relied on fixed prescribed peatland maps and inundation time series of limited temporal coverage. Here, we describe and assess the the Dynamical Peatland Model Based on TOPMODEL (DYPTOP), which predicts the extent of inundation based on a computationally efficient TOPMODEL implementation. This approach rests on an empirical, grid-cell-specific relationship between the mean soil water balance and the flooded area. DYPTOP combines the simulated inundation extent and its temporal persistency with criteria for the ecosystem water balance and the modelled peatland-specific soil carbon balance to predict the global distribution of peatlands. We apply DYPTOP in combination with the LPX-Bern DGVM and benchmark the global-scale distribution, extent, and seasonality of inundation against satellite data. DYPTOP successfully predicts the spatial distribution and extent of wetlands and major boreal and tropical peatland complexes and reveals the governing limitations to peatland occurrence across the globe. Peatlands covering large boreal lowlands are reproduced only when accounting for a positive feedback induced by the enhanced mean soil water holding capacity in peatland-dominated regions. DYPTOP is designed to minimize input data requirements, optimizes computational efficiency and allows for a modular adoption in Earth system models.