Intraoperative Brain Resection Cavity Characterization with Conoscopic Holography

Brain shift compromises the accuracy of neurosurgical imag e-guided interventions if not corrected by either intraope rative imaging or computational modeling. The latter requires int raoperative sparse measurements for constraining and driv ing model-based compensation strategies. Conoscopic hologra phy, n interferometric technique that measures the distan ce d direction of a laser light illuminated surface point from a fi xed laser source, was recently proposed for non-contact sur face data acquisition in image-guided surgery and is used here fo r validation of our modeling strategies. In this contribution, we use this inexpensive, hand-held co noscopic holography device for intraoperative validation of our computation modeling approach to correcting for brain s hift. Laser range scan, instrument swabbing, and conoscopi c holography data sets were collected from two patients under going brain tumor resection therapy at Vanderbilt Universi ty Medical Center. The results of our study indicate that conos copic holography is a promising method for surface acquisit ion since it requires no contact with delicate tissues and can ch ra terize the extents of structures within confined spaces . W demonstrate that for two clinical cases, the acquired conop robe points align with our model-updated images better than e uncorrected ones lending further evidence that computatio n m deling approaches improve the accuracy of image-guided surgical interventions in the presence of soft tissue defor mations.