Intraoperative augmented reality fiber tractography complements cortical and subcortical mapping.

Augmented reality (AR) has been found to be advantageous in enhancing visualization of complex neuroanatomy intraoperatively and in neurosurgical education. Another key tool that allows neurosurgeons to have enhanced visualization, namely of white matter tracts, is diffusion tensor imaging (DTI) that is processed with high-definition fiber tractography (HDFT). There remains an enduring challenge in the structural-functional correlation of white matter tracts that centers on the difficulty in clearly assigning function to any given fiber tract when evaluating them through separated as opposed to integrated modalities. Combining the technologies of AR with fiber tractography shows promise in helping to fill in this gap between structural-functional correlation of white matter tracts. This novel study demonstrates through a series of three cases of awake craniotomies for glioma resections a technique that allows the first and most direct evidence of fiber tract stimulation and assignment of function or deficit in vivo through the intraoperative, real-time fusion of electrical cortical stimulation, AR, and HDFT. This novel technique has qualitatively shown to be helpful in guiding intraoperative decision making on extent of resection of gliomas. Future studies could focus on larger, prospective cohorts of glioma patients who undergo this methodology and further correlate the post-operative imaging results to patient functional outcomes.

Vertebrae segmentation in reduced radiation CT imaging for augmented reality applications.

PURPOSE: There is growing evidence for the use of augmented reality (AR) navigation in spinal surgery to increase surgical accuracy and improve clinical outcomes. Recent research has employed AR techniques to create accurate auto-segmentations, the basis of patient registration, using reduced radiation dose intraoperative computed tomography images. In this study, we aimed to determine if spinal surgery AR applications can employ reduced radiation dose preoperative computed tomography (pCT) images. METHODS: We methodically decreased the imaging dose, with the addition of Gaussian noise, that was introduced into pCT images to determine the image quality threshold that was required for auto-segmentation. The Gaussian distribution's standard deviation determined noise level, such that a scalar multiplier (L: [0.00, 0.45], with steps of 0.03) simulated lower doses as L increased. We then enhanced the images with denoising algorithms to evaluate the effect on the segmentation. RESULTS: The pCT radiation dose was decreased to below the current lowest clinical threshold and the resulting images produced segmentations that were appropriate for input into AR applications. This held true at simulated dose L = 0.06 (estimated 144 mAs) but not at L = 0.09 (estimated 136 mAs). The application of denoising algorithms to the images resulted in increased artifacts and decreased bone density. CONCLUSIONS: The pCT image quality that is required for AR auto-segmentation is lower than that which is currently employed in spinal surgery. We recommend a reduced radiation dose protocol of approximately 140 mAs. This has the potential to reduce the radiation experienced by patients in comparison to procedures without AR support. Future research is required to identify the specific, clinically relevant radiation dose thresholds required for surgical navigation.