A Novel Platform for Image-guided Ultrasound

Abstract

Abstract OBJECTIVE: The combination of classic neuronavigation and intraoperative ultrasound is a recent innovation in image guidance technology. However, this technique requires two hardware components (neuronavigation and an ultrasound system). It was the aim of the study to describe a new simplified technology of a so-called one-platform navigation system developed by our institution in collaboration with the industry and to demonstrate its range of various applications. METHODS: An ultrasound device (IGSonic; BrainLAB, Munich, Germany) is integrated into the VectorVision2 navigation system (BrainLAB, Munich, Germany). The IGSonic Probe 10V5 is connected to the VectorVision Navigation station via an IGSonic Device Box. Once the ultrasound probe is calibrated, the navigated ultrasound displays the sonographic image of the intracranial anatomy on the navigation screen in a composed overlay fashion. It might depict vascular structures within the ultrasound plane by a duplex mode. Ultrasound can also be operated independently from navigation. RESULTS: The VectorVision2 system combines intraoperative ultrasound data sets with preoperatively acquired neuronavigation data sets in plug and play fashion. The system provides a cost-effective intraoperative imaging modality that offers a good anatomic orientation by various composite images, including the display of the amount of brain shift. In our institution, the comprehensible interface led to a routine use of the technology by several neurosurgeons who had not been familiar with the ultrasound technology before. CONCLUSION: The integration of an ultrasound device into an existing navigation system has been successfully developed. The system offers a friendly user interface and cost-effective intraoperative imaging feedback. Although brain shift can be visualized by an image overlay technology as demonstrated by the present system, future developments should aim at fusion techniques of both intra- and preoperative image data sets.