Intraoperatively updated neuroimaging using brain modeling and sparse data

OBJECTIVE: Image-guided neurosurgery incorporating preoperatively obtained imaging information is subject to spatial error resulting from intraoperati ve brain displacement and deformation. A strategy to update preoperative im aging using readily available intraoperative information has been developed and implemented. METHODS: Preoperative magnetic resonance imaging is used to generate a pati ent-specific three-dimensional finite element model of the brain by which d eformation resulting from multiple surgical processes may be simulated. Spa rse imaging data obtained subsequently, such as from digital cameras or ult rasound, are then used to prescribe the displacement of selected points wit hin the model. Based on the model, interpolation to the resolution of preop erative imaging may then be performed. RESULTS: The algorithms for generation of the finite element model and for its subsequent deformation were successfully validated using a pig brain mo del. In these experiments, the method recovered 84% of the intraoperative s hift resulting from surgically induced tissue motion. Preliminary clinical application in the operating room has demonstrated feasibility. CONCLUSION: A strategy by which intraoperative brain deformation may be acc ounted for has been developed, validated in an animal model, and demonstrat ed clinically.