P07.04.A ELASTIC IMAGE FUSION OF INTRAOPERATIVE ULTRASOUND AND PREOPERATIVE MRI FOR IMPROVING NAVIGATION ACCURACY IN BRAIN TUMOR SURGERY

Abstract

Abstract BACKGROUND In brain surgery, neuronavigation based on preoperative MRI is limited by various physical and operational factors, such as surgery-induced brain shift. Using navigated intraoperative ultrasound (iUS) imaging and 3D iUS image reconstruction may help improve neuronavigation. However, the registration of MRI and US scans can lead to spatial inconsistencies between the two modalities. This study aims to evaluate the clinical integration of navigated iUS imagining and its potential to improve the accuracy of resection during brain tumor surgery by comparing the performance of rigid and elastic MRI-iUS image fusion algorithms during retrospective evaluation. MATERIAL AND METHODS N = 50 patients with brain tumors were prospectively enrolled in this trial. The neuronavigation system (BrainLab AG) used in the study allowed for the reconstruction and integration of 3D iUS imaging, which was acquired multiple times throughout the surgery using a tracked ultrasound probe (BK Medical). Prototypes of automatic rigid and elastic MRI-iUS image fusion algorithms (Brainlab Elements Image Fusion) were retrospectively applied to improve co-registration accuracy between the MRI and iUS data. To evaluate the image co-registration accuracy, anatomical landmarks were defined in the MRI and iUS scans and used to measure Euclidean distances between each landmark pair. RESULTS Improvements in the image quality over the course of the study indicated that skills in US handling are essential. Contrast behavior and tumor structure influence the visibility of the tumor in the US. Artifacts caused by hemostatic agents challenge the US image quality and the fluid-filled resection cavity requires experience in probe handling. In terms of image fusion, significant mismatches of the iUS and MRI data were reported. For scans acquired before resection, rigid fusion using a novel co-registration algorithm may enhance the registration accuracy with mean target registration errors for two representative patients of 6.5/8.9 mm and 3.7/3.4 mm before and after registration update, respectively. For iUS scans acquired after tumor resection, rigid fusion is inherently limited due to non-linear brain shifts. Therefore, elastic image fusion has been applied to provide deformable MR-iUS image co-registration. CONCLUSION Navigated iUS imaging can be integrated into clinical routine and the use of MR-iUS image co-registration for updating navigation is a promising tool to compensate brainshift during surgical resection. However, further studies are needed to quantify the accuracy and assess whether iUS could potentially replace the use of iMRI in resection control of selected cases.