Investigating uncertainty in augmented reality enhanced renal navigation using in vitro patient-specific tissue-mimicking phantoms

To improve the outcome of minimally invasive renal interventions, traditional video-guided needle navigation can be enhanced by tracking the needle, guiding the needle using video imaging, and augmenting the surgical scene with pre-procedural images or models of the anatomy. In our previous work we studied, both through simulations and in vitro experiments, the uncertainty associated with the model-to-phantom registration, as well as the camera-tracker calibration and video-guided navigation. In this work, we characterize the overall navigation uncertainty using tissue emulating patient-specific kidney phantoms featuring both virtual and physical internal targets. Pre-procedural models of the kidney phantoms and internal targets are generated from cone-beam CT images, and are registered to their intra-operative physical counter-parts. The user then guides the needle insertion to reach the internal targets using video-based imaging augmented with a virtual representation of the needle tracked in real time. Following navigation, we acquire post-procedural cone-beam CT images of the phantoms and inserted needles. These images are used to determine the ground truth needle navigation accuracy (i.e., needle to target distance) against which the intra-operative navigation accuracy (i.e., intra-op needle tip to target distance) is assessed. We also explore a method to update the pre-procedural model to physical phantom registration intra-operatively using tracked video imaging, with the overall goal to improve overall navigation accuracy in the event of sub-optimal initial image-to-phantom registration. Our results showed a navigation error of less than 3.5 mm in gelatin phantoms and less than 6.5 mm in PVA phantoms. Following registration correction intra-operatively, we showed an overall improvement in navigation from roughly 6 mm RMS to approximately 2 mm RMS error, which is acceptable given the inherent tracking, 3D printing and phantom manufacturing limitations.