Current status and challenges of 3D navigation in partial nephrectomy

Abstract

Partial nephrectomy, a standard treatment for small renal cancers, has evolved through minimally invasive procedures such as laparoscopic and robot-assisted partial nephrectomy. The use of three-dimensional (3D) kidney models derived from preoperative computed tomography (CT) images has been investigated to improve surgical outcomes. This review explores various navigation techniques, such as 3D printing, virtual reality (VR), and augmented reality (AR), to address organ movement and deformation challenges during surgery. Despite the promising positive impact of these methods, as revealed by a systematic review in 2022, achieving the desired navigation accuracy remains elusive. The use of Virtual Reality and Augmented Reality, capable of overlaying the 3D model onto the surgical image in real-time, has shown potential. Still, we need advanced techniques, for instance, non-rigid 3D models employing nonlinear parametric deformation, to adapt to organ deformation. Additionally, the application of deep learning from artificial intelligence for high accuracy 3D navigation is an emerging area of interest. Although considerable progress has been achieved, a comprehensive, widely adoptable solution has yet to be discovered. The paper underscores the necessity for ongoing research and development in 3D navigation methods, anticipating their substantial contribution to future surgical procedures.