Since the introduction of the first intraoperative frameless stereotactic navigation device, image guided neurosurgery has become an essential tool for many neurosurgical procedures due to its ability to minimize surgical trauma by allowing for the precise localization of surgical targets. The integration of preoperative image information into a comprehensive patient-specific model enables surgeons to preoperatively evaluate the risks involved and define the most appropriate surgical strategy. Perhaps more importantly, such systems enable surgery of previously inoperable cases by helping to locate safe surgical corridors through IGNS-identified non-critical areas.
For intraoperative use, neuronavigation systems must relate the physical location of a patient with the preoperative models by means of a transformation that relates the two through a patient-to-image mapping. Throughout the intervention, hardware movement, an imperfect patient-image mapping, and movement of brain tissue during surgery invalidates the patient-to-image mapping. These sources of inaccuracy, collectivey described as ‘brain shift’, reduce the effectiveness of using preoperative patient specific models intraoperatively. Intraoperative imaging, such as MRI, has been shown to improve the accuracy of tumour resections through lengthened image guidance. However, such technology is extremely expensive, prolongs surgery, poses logistical challenges during awake surgeries, and is available in only a few centres worldwide. We have developed a neuronavigation platform (IBIS Neuronav) that integrates tissue deformation tracking during surgery based on tracked intraoperative ultrasound (iUS) that can accurately align all pre-operative data to the iUS to account for brain shift throughout a surgical intervention.
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