V12-07: Three Dimensional Printing and Augmented Reality: Enhanced Precision for Robotic Assisted Partial Nephrectomy
In minimally invasive and robotic partial nephrectomy surgeons often do not obtain a spatial familiarity with the kidney and tumor until it is removed. Pre-operative three-dimensional (3D) printing and augmented reality (AR) models are advanced imaging methods that may facilitate surgical planning and anatomical understanding by allowing surgeons to better assess the relationship of the tumor to major anatomical structures such as the renal vasculature and hilum. The objective of this study is to describe novel 3D printing and AR methods of image data visualization to facilitate anatomical understanding and assist with surgical planning and decision making during robotic partial nephrectomy.
We created a video of the workflow for creating 3D printed and AR kidney models along with their application to robotic partial nephrectomy. Key steps in their development are 1) radiology exam (MRI, CT), 2) image segmentation, 3) preparing for 3D printing or AR, and 4) printing the model or deploying the model to the AR device.
We demonstrate the work flow and utility of 3D printing and AR kidney models applied to a case of a 70 year old female with a 3.4 cm renal mass of her left pelvic kidney. A 3D printed kidney model was created using multi-color polyjet technology (Stratasys J750), allowing a transparent kidney with coloring of the renal tumor, artery, vein and ureter. An AR kidney model was created using Unity3D software and deployed to a Microsoft HoloLens. The 3D printed and AR model were used pre-operatively and intra-operatively to assist in robotic partial nephrectomy. To date, we have created 15 3D printed and AR kidney models to use for robotic partial nephrectomy planning and intra-operative guidance. The application of 3D printed and AR models is safe and feasible and can influence surgical decisions.
Our video highlights the work flow and novel application of 3D printed and AR kidney models to provide pre-operative guidance for robotic partial nephrectomy. The insights gained from advanced visualization can influence surgical planning decisions.
Funding: This work was supported by the Center for Advanced Imaging Innovation and Research (www.cai2r.net), a NIBIB Biomedical Technology Resource Center (NIH P41 EB017183). In-kind support for this project from Stratasys.