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Magaribuchi et al. Mini-invasive Surg 2024;8:6 Mini-invasive Surgery
DOI: 10.20517/2574-1225.2023.81

Review Open Access

Current status and challenges of 3D navigation in

partial nephrectomy

Toshihiro Magaribuchi, Kimihiko Masui, Takayuki Goto, Ryoichi Saito, Takashi Kobayashi
Department of Urology, Graduate School of Medicine, Kyoto University, Kyoto 606-8507, Japan.

Correspondence to: Dr. Takashi Kobayashi, Department of Urology, Graduate School of Medicine, Kyoto University, 54, Shogoin
Kawahara-cho, Sakyo-ku, Kyoto 606-8507, Japan. E-mail: selecao@kuhp.kyoto-u.ac.jp

How to cite this article: Magaribuchi T, Masui K, Goto T, Saito R, Kobayashi T. Current status and challenges of 3D navigation in
partial nephrectomy. Mini-invasive Surg 2024;8:6. https://dx.doi.org/10.20517/2574-1225.2023.81

Received: 10 Jul 2023 First Decision: 20 Mar 2024 Revised: 17 Apr 2024 Accepted: 24 Apr 2024 Published: 28 Apr 2024

Academic Editor: Giulio Belli Copy Editor: Dong-Li Li Production Editor: Dong-Li Li

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.

Keywords: Partial nephrectomy, 3D kidney models, preoperative computed tomography, virtual reality, augmented
reality

© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution 4.0
International License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, sharing,
adaptation, distribution and reproduction in any medium or format, for any purpose, even commercially, as
long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and
indicate if changes were made.

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