. This research proposal is a new R01 application in response to the Program Announcement """"""""Innovations in Biomedical Computational Science and Technology"""""""" for five years of funding to apply and evaluate novel surgical navigation technology to improve outcomes in pediatric brain tumor surgery. Commercially available surgical navigation systems can align multi-modality data at the start of surgery, and provide real-time tracking of surgical instruments. However, existing systems are unable to align data following soft tissue deformation such as occurs during resection of pediatric brain tumors. As a consequence, the precise alignment established at the start of surgery is lost, and the accuracy of preoperative to intraoperative data fusion is progressively worsened as the neurosurgery continues. At the critical periods of final resection of the tumor margin, the accuracy of alignment is worst, and the preoperative data does not provide a direct guide to the neurosurgeon. It is our objective to significantly increasing the amount of time during the surgery for which precisely aligned fused visualization of preoperative and intraoperative data will be available to the neurosurgeon. We will apply a novel nonrigid registration algorithm that we have recently developed for intraoperative data fusion, as well as the best available techniques published by other groups, in order to re-establish precise navigation with preoperative data. We will assess the efficacy of the enhanced navigation by assessing the volume and percentage of tumor resected, and by assessing neurological outcomes following the surgery.
The specific aims of this research are to 1) Evaluate target registration error of nonrigid registration algorithms for pediatric brain tumor surgery, 2) Significantly improve the duration of precise alignment and data fusion during pediatric brain tumor surgery, and to 3) Evaluate the efficacy of enhanced navigation by assessing post-operative tumor resection volume. This proposal will benefit public health by evaluating key technologies to enable enhanced intraoperative navigation during pediatric brain tumor surgery. The capacity to visualize the tumor and tumor margin throughout the surgery, together with functionally significant cortical gray matter regions and white matter fiber tracts, will better enable the neurosurgeon to achieve more complete tumor resection without creating neurological deficits. The assessment of surgical resection will lead to a quantitative determination of the efficacy of enhanced navigation during pediatric brain tumor surgery.
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