Archie Hughes-Hallett1, Philip Pratt2, Erik Mayer3, Shirley Martin4, Ara Darzi5, Justin Vale1. 1. Department of Surgery and Cancer, Imperial College London, London, United Kingdom. 2. Hamlyn Centre for Robotic Surgery, Imperial College London, London, United Kingdom. 3. Department of Surgery and Cancer, Imperial College London, London, United Kingdom. Electronic address: e.mayer@imperial.ac.uk. 4. Imperial College Healthcare NHS Trust, London, United Kingdom. 5. Department of Surgery and Cancer, Imperial College London, London, United Kingdom; Hamlyn Centre for Robotic Surgery, Imperial College London, London, United Kingdom.
Abstract
OBJECTIVE: To determine the feasibility of a novel low-barrier-to-entry image guidance system. METHODS: Initially a randomized crossover study was performed to establish the interface (iPad or 3-dimensional mouse) that minimized both the amount of time required to perform a manual image registration and the error of that registration. A subsequent clinical feasibility study was undertaken on 5 patients undergoingrobot-assisted partial nephrectomy. Randomized crossover study primary outcomes were time to task completion, NASA-Task Load Index score, and alignment error (translational and rotational). The Mann-Whitney U test was used to compare groups. Surgeon feedback was sought when assessing the system in a clinical setting. RESULTS: In the initial randomized crossover study, the iPad-based system was able to achieve adequate alignment accuracy (Frobenius norm of 0.3; total error of 20.8 mm) in significantly less time (33 seconds; P<.01) than the 3-dimensional mouse interface. The platform received good feedback from the operating surgeon in all instances with the surgeon commenting particularly on the improved appreciation of hilar vascular anatomy. CONCLUSION: In this study, we have demonstrated the feasibility of a "low-barrier-to-entry" image guidance system in a clinical setting. The system was able to achieve swift and sufficiently accurate alignment, with little impact on the surgical workflow.
RCT Entities:
OBJECTIVE: To determine the feasibility of a novel low-barrier-to-entry image guidance system. METHODS: Initially a randomized crossover study was performed to establish the interface (iPad or 3-dimensional mouse) that minimized both the amount of time required to perform a manual image registration and the error of that registration. A subsequent clinical feasibility study was undertaken on 5 patients undergoing robot-assisted partial nephrectomy. Randomized crossover study primary outcomes were time to task completion, NASA-Task Load Index score, and alignment error (translational and rotational). The Mann-Whitney U test was used to compare groups. Surgeon feedback was sought when assessing the system in a clinical setting. RESULTS: In the initial randomized crossover study, the iPad-based system was able to achieve adequate alignment accuracy (Frobenius norm of 0.3; total error of 20.8 mm) in significantly less time (33 seconds; P<.01) than the 3-dimensional mouse interface. The platform received good feedback from the operating surgeon in all instances with the surgeon commenting particularly on the improved appreciation of hilar vascular anatomy. CONCLUSION: In this study, we have demonstrated the feasibility of a "low-barrier-to-entry" image guidance system in a clinical setting. The system was able to achieve swift and sufficiently accurate alignment, with little impact on the surgical workflow.
Authors: Michael A Kokko; Douglas W Van Citters; John D Seigne; Ryan J Halter Journal: Int J Comput Assist Radiol Surg Date: 2022-05-05 Impact factor: 2.924
Authors: Philip Pratt; Alexander Jaeger; Archie Hughes-Hallett; Erik Mayer; Justin Vale; Ara Darzi; Terry Peters; Guang-Zhong Yang Journal: Int J Comput Assist Radiol Surg Date: 2015-08-25 Impact factor: 2.924
Authors: Stefano Puliatti; Ahmed Eissa; Enrico Checcucci; Pietro Piazza; Marco Amato; Stefania Ferretti; Simone Scarcella; Juan Gomez Rivas; Mark Taratkin; Josè Marenco; Ines Belenchon Rivero; Karl-Friedrich Kowalewski; Giovanni Cacciamani; Ahmed El-Sherbiny; Ahmed Zoeir; Abdelhamid M El-Bahnasy; Ruben De Groote; Alexandre Mottrie; Salvatore Micali Journal: Asian J Urol Date: 2022-06-01
Authors: E R Hyde; L U Berger; N Ramachandran; A Hughes-Hallett; N P Pavithran; M G B Tran; S Ourselin; A Bex; F H Mumtaz Journal: Int J Comput Assist Radiol Surg Date: 2019-01-24 Impact factor: 2.924