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Autonomous pick-and-place using the dVRK

PURPOSE: Robotic-assisted partial nephrectomy (RAPN) is a tissue-preserving approach to treating renal cancer, where ultrasound (US) imaging is used for intra-operative identification of tumour margins and localisation of blood vessels. With the da Vinci Surgical System (Sunnyvale, CA), the US probe...

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Autores principales: D’Ettorre, Claudia, Stilli, Agostino, Dwyer, George, Tran, Maxine, Stoyanov, Danail
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8260407/
https://www.ncbi.nlm.nih.gov/pubmed/33991305
http://dx.doi.org/10.1007/s11548-021-02397-y
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author D’Ettorre, Claudia
Stilli, Agostino
Dwyer, George
Tran, Maxine
Stoyanov, Danail
author_facet D’Ettorre, Claudia
Stilli, Agostino
Dwyer, George
Tran, Maxine
Stoyanov, Danail
author_sort D’Ettorre, Claudia
collection PubMed
description PURPOSE: Robotic-assisted partial nephrectomy (RAPN) is a tissue-preserving approach to treating renal cancer, where ultrasound (US) imaging is used for intra-operative identification of tumour margins and localisation of blood vessels. With the da Vinci Surgical System (Sunnyvale, CA), the US probe is inserted through an auxiliary access port, grasped by the robotic tool and moved over the surface of the kidney. Images from US probe are displayed separately to the surgical site video within the surgical console leaving the surgeon to interpret and co-registers information which is challenging and complicates the procedural workflow. METHODS: We introduce a novel software architecture to support a hardware soft robotic rail designed to automate intra-operative US acquisition. As a preliminary step towards complete task automation, we automatically grasp the rail and position it on the tissue surface so that the surgeon is then able to manipulate manually the US probe along it. RESULTS: A preliminary clinical study, involving five surgeons, was carried out to evaluate the potential performance of the system. Results indicate that the proposed semi-autonomous approach reduced the time needed to complete a US scan compared to manual tele-operation. CONCLUSION: Procedural automation can be an important workflow enhancement functionality in future robotic surgery systems. We have shown a preliminary study on semi-autonomous US imaging, and this could support more efficient data acquisition.
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spelling pubmed-82604072021-07-20 Autonomous pick-and-place using the dVRK D’Ettorre, Claudia Stilli, Agostino Dwyer, George Tran, Maxine Stoyanov, Danail Int J Comput Assist Radiol Surg Original Article PURPOSE: Robotic-assisted partial nephrectomy (RAPN) is a tissue-preserving approach to treating renal cancer, where ultrasound (US) imaging is used for intra-operative identification of tumour margins and localisation of blood vessels. With the da Vinci Surgical System (Sunnyvale, CA), the US probe is inserted through an auxiliary access port, grasped by the robotic tool and moved over the surface of the kidney. Images from US probe are displayed separately to the surgical site video within the surgical console leaving the surgeon to interpret and co-registers information which is challenging and complicates the procedural workflow. METHODS: We introduce a novel software architecture to support a hardware soft robotic rail designed to automate intra-operative US acquisition. As a preliminary step towards complete task automation, we automatically grasp the rail and position it on the tissue surface so that the surgeon is then able to manipulate manually the US probe along it. RESULTS: A preliminary clinical study, involving five surgeons, was carried out to evaluate the potential performance of the system. Results indicate that the proposed semi-autonomous approach reduced the time needed to complete a US scan compared to manual tele-operation. CONCLUSION: Procedural automation can be an important workflow enhancement functionality in future robotic surgery systems. We have shown a preliminary study on semi-autonomous US imaging, and this could support more efficient data acquisition. Springer International Publishing 2021-05-15 2021 /pmc/articles/PMC8260407/ /pubmed/33991305 http://dx.doi.org/10.1007/s11548-021-02397-y Text en © Crown 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Article
D’Ettorre, Claudia
Stilli, Agostino
Dwyer, George
Tran, Maxine
Stoyanov, Danail
Autonomous pick-and-place using the dVRK
title Autonomous pick-and-place using the dVRK
title_full Autonomous pick-and-place using the dVRK
title_fullStr Autonomous pick-and-place using the dVRK
title_full_unstemmed Autonomous pick-and-place using the dVRK
title_short Autonomous pick-and-place using the dVRK
title_sort autonomous pick-and-place using the dvrk
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8260407/
https://www.ncbi.nlm.nih.gov/pubmed/33991305
http://dx.doi.org/10.1007/s11548-021-02397-y
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