Daniel Høyer Iversen1, Wolfgang Wein2, Frank Lindseth3, Geirmund Unsgård4, Ingerid Reinertsen5. 1. SINTEF Technology and Society, Department of Health Research, Trondheim, Norway; Department of Circulation and Medical Imaging, Norwegian University for Science and Technology, Trondheim, Norway. 2. ImFusion GmbH, München, Germany. 3. SINTEF Technology and Society, Department of Health Research, Trondheim, Norway; Department of Computer Science, Norwegian University for Science and Technology, Trondheim, Norway. 4. Department of Neuromedicine and Movement Science, Norwegian University for Science and Technology, Trondheim, Norway; Department of Neurosurgery, St. Olav University Hospital, Trondheim, Norway. 5. SINTEF Technology and Society, Department of Health Research, Trondheim, Norway. Electronic address: ingerid.reinertsen@sintef.no.
Abstract
BACKGROUND: Unreliable neuronavigation owing to inaccurate patient-to-image registration and brain shift is a major problem in conventional magnetic resonance imaging-guided neurosurgery. We performed a prospective intraoperative validation of a system for fully automatic correction of this inaccuracy based on intraoperative three-dimensional ultrasound and magnetic resonance imaging-to-ultrasound registration. METHODS: The system was tested intraoperatively in 13 tumor resection cases, and performance was evaluated intraoperatively and postoperatively. RESULTS: Intraoperatively, the system was accurate enough for tumor resection guidance in 9 of 13 cases. Manually placed anatomic landmarks showed improvement of alignment from 5.12 mm to 2.72 mm (median) after intraoperative correction. Postoperatively, the limitations of the current system were identified and modified for the system to be sufficiently accurate in all cases. CONCLUSIONS: Automatic and accurate correction of spatially unreliable neuronavigation is feasible within the constraints of surgery. The current limitations of the system were also identified and addressed.
BACKGROUND: Unreliable neuronavigation owing to inaccurate patient-to-image registration and brain shift is a major problem in conventional magnetic resonance imaging-guided neurosurgery. We performed a prospective intraoperative validation of a system for fully automatic correction of this inaccuracy based on intraoperative three-dimensional ultrasound and magnetic resonance imaging-to-ultrasound registration. METHODS: The system was tested intraoperatively in 13 tumor resection cases, and performance was evaluated intraoperatively and postoperatively. RESULTS: Intraoperatively, the system was accurate enough for tumor resection guidance in 9 of 13 cases. Manually placed anatomic landmarks showed improvement of alignment from 5.12 mm to 2.72 mm (median) after intraoperative correction. Postoperatively, the limitations of the current system were identified and modified for the system to be sufficiently accurate in all cases. CONCLUSIONS: Automatic and accurate correction of spatially unreliable neuronavigation is feasible within the constraints of surgery. The current limitations of the system were also identified and addressed.
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