Autonomous pick-and-place using the dVRK

• Published in: International journal for computer assisted radiology and surgery 2021-07, Vol.16 (7), p.1141-1149
• Main Authors: D’Ettorre, Claudia, Stilli, Agostino, Dwyer, George, Tran, Maxine, Stoyanov, Danail
• Format: Article
• Language: English
• Subjects: Automation; Blood vessels; Computer architecture; Computer Imaging; Computer Science; Equipment Design; Health Informatics; Humans; Imaging; Kidney - diagnostic imaging; Kidney - surgery; Kidney Neoplasms - diagnosis; Kidney Neoplasms - surgery; Laparoscopy - methods; Medicine; Medicine & Public Health; Nephrectomy - methods; Original; Original Article; Pattern Recognition and Graphics; Radiology; Robotic surgery; Robotic Surgical Procedures - methods; Surgeons; Surgery; Ultrasonography - instrumentation; Vision; Workflow
• ISSN: 1861-6410; 1861-6429
• DOI: 10.1007/s11548-021-02397-y

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.