Assessing and reducing registration and targeting uncertainty in video-based image-guided renal navigation: An study featuring virtual targets.

Minimally invasive image-guided interventions (IGIs) enable better therapy outcomes for patients, but navigation accuracy is highly dependent on the accuracy of the image-/model-to-patient registration. This requires methods to reduce the uncertainty to a level appropriate for the procedure being performed. Since sub-surface tissue landmarks cannot be easily sampled using a tracked stylus and used to perform the patient registration, here we present a method that employs a tracked camera (that mimics a laparoscope) to perform the patient registration or update this registration in case of suspected misalignment within the context of an image-guided renal navigation procedure. We implement and test the method using a simplified patient phantom, which consists of a foam block to which a virtual kidney model featuring both surface and sub-surface landmarks is registered. This setup mimics a situation when a surgeon would navigate a tracked needle to renal landmarks percutaneously, while relying on pre-procedural imaging, optical tracking, and surface video imaging. We conduct several experiments under both optimal phantom registration and purposely altered registration, to not only show the effect of phantom / patient mis-registration on subsequent navigation, but also demonstrate the use of the camera-based registration to restore navigation to an acceptable uncertainty. Our results illustrate that camera-based registration yields a target registration error on the order of 0.4 mm and a subsequent targeting error on the order of 0.6 mm, comparable to the performance achieved following gold-standard landmark-based registration. These results suggest that the proposed method can be used to perform or update the patient registration for image-guided interventions involving sub-surface organs.