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Automating Endoscope Motion in Robotic Surgery: A Usability Study on Da Vinci-Assisted Neobladder Reconstruction

Overview
Journal Front Robot AI
Date 2021 Dec 13
PMID 34901168
Citations 4
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Abstract

Robots for minimally invasive surgery introduce many advantages, but still require the surgeon to alternatively control the surgical instruments and the endoscope. This work aims at providing autonomous navigation of the endoscope during a surgical procedure. The autonomous endoscope motion was based on kinematic tracking of the surgical instruments and integrated with the da Vinci Research Kit. A preclinical usability study was conducted by 10 urologists. They carried out an orthotopic neobladder reconstruction twice, using both traditional and autonomous endoscope control. The usability of the system was tested by asking participants to fill standard system usability scales. Moreover, the effectiveness of the method was assessed by analyzing the total procedure time and the time spent with the instruments out of the field of view. The average system usability score overcame the threshold usually identified as the limit to assess good usability (average score = 73.25 > 68). The average total procedure time with the autonomous endoscope navigation was comparable with the classic control ( = 0.85 > 0.05), yet it significantly reduced the time out of the field of view ( = 0.022 < 0.05). Based on our findings, the autonomous endoscope improves the usability of the surgical system, and it has the potential to be an additional and customizable tool for the surgeon that can always take control of the endoscope or leave it to move autonomously.

Citing Articles

Endoscope Automation Framework with Hierarchical Control and Interactive Perception for Multi-Tool Tracking in Minimally Invasive Surgery.

Fozilov K, Colan J, Davila A, Misawa K, Qiu J, Hayashi Y Sensors (Basel). 2023; 23(24).

PMID: 38139711 PMC: 10748016. DOI: 10.3390/s23249865.


Augmented Reality (AR) for Surgical Robotic and Autonomous Systems: State of the Art, Challenges, and Solutions.

Seetohul J, Shafiee M, Sirlantzis K Sensors (Basel). 2023; 23(13).

PMID: 37448050 PMC: 10347167. DOI: 10.3390/s23136202.


Robot-assisted ex vivo neobladder reconstruction: preliminary results of surgical skill evaluation.

Chen Z, Terlizzi S, Da Col T, Marzullo A, Catellani M, Ferrigno G Int J Comput Assist Radiol Surg. 2022; 17(12):2315-2323.

PMID: 35802223 PMC: 9652243. DOI: 10.1007/s11548-022-02712-1.


Robotic Endoscope Control Via Autonomous Instrument Tracking.

Gruijthuijsen C, Garcia-Peraza-Herrera L, Borghesan G, Reynaerts D, Deprest J, Ourselin S Front Robot AI. 2022; 9:832208.

PMID: 35480090 PMC: 9035496. DOI: 10.3389/frobt.2022.832208.

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