Assessment of surgical skills by using surgical navigation in robot-assisted partial nephrectomy

  • Satoshi Kobayashi
  • Byunghyun ChoEmail author
  • Arnaud Huaulmé
  • Katsunori Tatsugami
  • Hiroshi Honda
  • Pierre Jannin
  • Makoto Hashizumea
  • Masatoshi Eto
Original Article



To assess surgical skills in robot-assisted partial nephrectomy (RAPN) with and without surgical navigation (SN).


We employed an SN system that synchronizes the real-time endoscopic image with a virtual reality three-dimensional (3D) model for RAPN and evaluated the skills of two expert surgeons with regard to the identification and dissection of the renal artery (non-SN group, n = 21 [first surgeon n = 9, second surgeon n = 12]; SN group, n = 32 [first surgeon n = 11, second surgeon n = 21]). We converted all movements of the robotic forceps during RAPN into a dedicated vocabulary. Using RAPN videos, we classified all movements of the robotic forceps into direct action (defined as movements of the robotic forceps that directly affect tissues) and connected motion (defined as movements that link actions). In addition, we analyzed the frequency, duration, and occupancy rate of the connected motion.


In the SN group, the R.E.N.A.L nephrometry score was lower (7 vs. 6, P = 0.019) and the time to identify and dissect the renal artery (16 vs. 9 min, P = 0.008) was significantly shorter. The connected motions of inefficient “insert,” “pull,” and “rotate” motions were significantly improved by SN. SN significantly improved the frequency, duration, and occupancy rate of connected motions of the right hand of the first surgeon and of both hands of the second surgeon. The improvements in connected motions were positively associated with SN for both surgeons.


This is the first study to investigate SN for nephron-sparing surgery. SN with 3D models might help improve the connected motions of expert surgeons to ensure efficient RAPN.


Computer-assisted Image-guided surgery Kidney Nephrectomy Robotics Surgical skill 



Susumu Oguri supported this study by developing the marker holder on the da Vinci endoscope. Authors thank b-com (1219 Avenue des Champs Blancs, 35510 Cesson-Sévigné, France) for provision of the software “Surgery Workflow Toolbox [Annotate]” used in this study. And this research was supported by AMED under Grant Number JP18he1802002.

Compliance with ethical standards

Conflict of interest

The authors declare no conflicts of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The Institutional Review Board approved our study (IRB license no. 28-119).

Informed consent

Informed consent was obtained from all individual participants included in the study.

Supplementary material

Video (Supplement 1). [Surgical Navigation for Robot-Assisted Partial Nephrectomy (RAPN)]. We proposed an approach to surgical navigation using a system for synchronizing real image in the endoscopy with a 3D model in VR during RAPN. Using this system, it became easier to visually confirm the location the surgeon was currently viewing. As a result, the surgeon was able to rapidly determine the location of the renal artery or tumor. (MP4 47463 kb)


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Copyright information

© CARS 2019

Authors and Affiliations

  • Satoshi Kobayashi
    • 1
    • 2
  • Byunghyun Cho
    • 1
    Email author
  • Arnaud Huaulmé
    • 4
  • Katsunori Tatsugami
    • 2
  • Hiroshi Honda
    • 3
  • Pierre Jannin
    • 4
  • Makoto Hashizumea
    • 1
  • Masatoshi Eto
    • 1
    • 2
  1. 1.Department of Advanced Medical Initiatives Faculty of Medical SciencesKyushu UniversityFukuokaJapan
  2. 2.Department of UrologyKyushu UniversityFukuokaJapan
  3. 3.Department of RadiologyKyushu UniversityFukuokaJapan
  4. 4.Faculty of Medicine, National Institute of Health and Scientific ResearchUniversity of Rennes 1RennesFrance

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