Abstract
Abstract
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.
Funder
Wellcome/EPSRC
Science and Engineering Research Council
Royal Academy of Engineering
UCL Innovation and Enterprise
Engineering and Physical Science Research Council
Publisher
Springer Science and Business Media LLC
Subject
Health Informatics,Radiology Nuclear Medicine and imaging,General Medicine,Surgery,Computer Graphics and Computer-Aided Design,Computer Science Applications,Computer Vision and Pattern Recognition,Biomedical Engineering
Reference21 articles.
1. Marcus HJ, Hughes-Hallett A, Payne CJ, Cundy TP, Nandi D, Yang GZ, Darzi A (2017) Trends in the diffusion of robotic surgery: a retrospective observational study. Int J Med Robot Comput Assist Surg 13(4):e1870
2. Yang G-Z, Cambias J, Cleary K, Daimler E, Drake J, Dupont PE, Hata N, Kazanzides P, Martel S, Patel RV, Santos VJ, Taylor RH (2017) Medical robotics–regulatory, ethical, and legal considerations for increasing levels of autonomy. Sci Robot 2(4):8638
3. Kaul S, Laungani R, Sarle R, Stricker H, Peabody J, Littleton R, Menon M (2007) da Vinci-assisted robotic partial nephrectomy: technique and results at a mean of 15 months of follow-up. Eur Urol 51(1):186–92
4. Bhayani SB (2008) da Vinci robotic partial nephrectomy for renal cell carcinoma: an atlas of the four-arm technique. J Robot Surg 1(4):279–85
5. Krupa A, Fichtinger G, Hager GD (2009) Real-time tissue tracking with B-mode ultrasound using speckle and visual servoing. In: International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer, Berlin
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献