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It is imperative that image-guided intervention (IGI) systems provide accurate and precise navigation information to enable the user to trust the system and not place unwarranted confidence in the guidance capabilities of the system. Unfortunately, the actual error associated with the overall targeting capabilities of an IGI system is not readily known. Here we are primarily interested in the application of image-guided surgery in the context of renal interventions. We built a simulation pipeline to study the uncertainty propagation through an optically tracked IGI system to gain insight into the overall accuracy of the system. Our simulation pipeline models several stages, including stylus calibration, tool tracking, patient tracking, and image to patient registration. In the effort to realistically estimate tracking noise and user-associated fiducial localization error (FLE), we conducted several experiments using the optical tracking system. Our simulation suggested that a wider cone angle results in a more accurate tool calibration, which improves further with the collection of additional samples. Furthermore, our simulations also suggested that the image-to-patient registration was the most significant contributor to navigation uncertainty, followed by the fiducial localization error. Lastly, we also observed a 0.72 correlation between the Target Registration Error (TRE) estimated at target fiducials and the distance between the the centroids of the registration and target fiducial landmarks. To validate the simulation predictions, we also conducted several in vitro experiments using a 3D printed patient specific kidney phantom and compared the simulation-based registration predictions with those observed experimentally in vitro. The experiments confirmed the registration metrics (Fiducial Registration Error and TRE) predicted by the simulations, given several specific combinations of fiducial landmarks used to perform the image to patient registration.
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