Cranial neurosurgical procedures are especially delicate considering that the surgeon must localize the subsurface anatomy with limited exposure and without the ability to see beyond the surface of the surgical field. Surgical accuracy is imperative as even minor surgical errors can cause major neurological deficits. Traditionally surgical precision was highly dependent on surgical skill. However, the introduction of intraoperative surgical navigation has shifted the paradigm to become the current standard of care for cranial neurosurgery.
Intra-operative image guided navigation systems are currently used to allow the surgeon to visualize the three-dimensional subsurface anatomy using pre-acquired computed tomography (CT) or magnetic resonance (MR) images. The patient anatomy is fused to the pre-acquired images using various registration techniques and surgical tools are typically localized using optical tracking methods. Although these techniques positively impact complication rates, surgical accuracy is limited by the accuracy of the navigation system and as such quantification of surgical error is required. While many different measures of registration accuracy have been presented true navigation accuracy can only be quantified post-operatively by comparing a ground truth landmark to the intra-operative visualization.
In this study we quantified the accuracy of cranial neurosurgical procedures using a novel optical surface imaging navigation system to visualize the three-dimensional anatomy of the surface anatomy. A tracked probe was placed on the screws of cranial fixation plates during surgery and the reported position of the centre of the screw was compared to the co-ordinates of the post-operative CT or MR images, thus quantifying cranial neurosurgical error.
Raphael Jakubovic, Shuarya Gupta, Daipayan Guha, Todd Mainprize, and Victor X. D. Yang, "Accuracy of neuro-navigated cranial screw placement using optical surface imaging (Conference Presentation)," Proc. SPIE 10050, Clinical and Translational Neurophotonics, 100500H (Presented at SPIE BiOS: January 28, 2017; Published: 19 April 2017); https://doi.org/10.1117/12.2252751.5370387593001.
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