This study aimed at comparing the accuracy of two commercial neuronavigation systems. Error assessment and quantification of clinical factors and surface registration, often resulting in decreased accuracy, were intended. Active (Stryker Navigation) and passive (VectorVision Sky, BrainLAB) neuronavigation systems were tested with an anthropomorphic phantom with a deformable layer, simulating skin and soft tissue. True coordinates measured by computer numerical control were compared with coordinates on image data and during navigation, to calculate software and system accuracy respectively. Comparison of image and navigation coordinates was used to evaluate navigation accuracy. Both systems achieved an overall accuracy of <1.5 mm. Stryker achieved better software accuracy, whereas BrainLAB better system and navigation accuracy. Factors with conspicuous influence (P<0.01) were imaging, instrument replacement, sterile cover drape and geometry of instruments. Precision data indicated by the systems did not reflect measured accuracy in general. Surface matching resulted in no improvement of accuracy, confirming former studies. Laser registration showed no differences compared to conventional pointers. Differences between the two systems were limited. Surface registration may improve inaccurate point-based registrations but does not in general affect overall accuracy. Accuracy feedback by the systems does not always match with true target accuracy and requires critical evaluation from the surgeon.

Discrete-event simulation has been established as an important methodology in various domains. In particular in the automotive industry, simulation is used to plan, control, and monitor processes including the flow of material and information. Procedure models help to perform simulation studies in a structured way and tools for data preparation or statistical analysis provide assistance in some phases of simulation studies. However, there is no comprehensive data assistance following all phases of such procedure models. In this article, a new approach combining assistance functionalities for input and output data analysis is presented. The developed tool -EDASim -focuses on supporting the user in selection, validation, and preparation of input data as well as to assist the analysis of output data. The proposed methods have been implemented and initial evaluations of the concepts have led to promising feedback from practitioners.

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