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Robotic kidney autotransplantation in a porcine model: a procedure-specific training platform for the simulation of robotic intracorporeal vascular anastomosis

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Abstract

Robotic-assisted kidney transplantation (RKT) with the Da Vinci (Intuitive, USA) platform has been recently developed to improve outcomes by decreasing surgical site complications and morbidity, especially in obese patients. This potential paradigm shift in the surgical technique of kidney transplantation is performed in only a few centers. For wider adoption of this high stake complex operation, we aimed to develop a procedure-specific simulation platform in a porcine model for the training of robotic intracorporeal vascular anastomosis and evaluating vascular anastomoses patency. This paper describes the requirements and steps developed for the above training purpose. Over a series of four animal ethics’ approved experiments, the technique of robotic-assisted laparoscopic autotransplantation of the kidney was developed in Amsterdam live pigs (60–70 kg). The surgery was based around the vascular anastomosis technique described by Menon et al. This non-survival porcine training model is targeted at transplant surgeons with robotic surgery experience. Under general anesthesia, each pig was placed in lateral decubitus position with the placement of one robotic camera port, two robotic 8 mm ports and one assistant port. Robotic docking over the pig posteriorly was performed. The training platform involved the following procedural steps. First, ipsilateral iliac vessel dissection was performed. Second, robotic-assisted laparoscopic donor nephrectomy was performed with in situ perfusion of the kidney with cold Hartmann’s solution prior to complete division of the hilar vessels, ureter and kidney mobilization. Thirdly, the kidney was either kept in situ for orthotopic autotransplantation or mobilized to the pelvis and orientated for the vascular anastomosis, which was performed end to end or end to side after vessel loop clamping of the iliac vessels, respectively, using 6/0 Gore-Tex sutures. Following autotransplantation and release of vessel loops, perfusion of the graft was assessed using intraoperative indocyanine green imaging and monitoring urine output after unclamping. This training platform demonstrates adequate face and content validity. With practice, arterial anastomotic time could be improved, showing its construct validity. This porcine training model can be useful in providing training for robotic intracorporeal vascular anastomosis and may facilitate confident translation into a transplant human recipient.

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Acknowledgements

This study was funded by Intuitive Surgical Robotic Research Grant 2016. The authors would also like to acknowledge the help from the Veterinarians  and Technicians, Department of Comparative Medicine (National University of Singapore) and from Sales Representative, Transmedic Private Limited for the techinical support during the surgical experiments.

Funding

This study was funded by Intuitive Surgical Research Grant 2016–2017 (No Grant number).

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Correspondence to Ho Yee Tiong.

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All authors declare they have no conflicts of interest.

Ethical approval

All applicable international, national, and/or institutional guidelines for the care and use of animals were followed. For Reference, Approval for study protocol was administered by National University of Singapore Institutional Animal Care and Use Committee. The IACUC Protocol number for this study was C15-1428.

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Supplementary material 1 Supplementary material 1 Video outlining the training steps developed for robotic autotransplantation in a porcine model. Video can be downloaded at: https://1drv.ms/v/s!AtRVAdDGvNYcwzJckQJzuirPHL7K(MP4 734165 kb)

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Tiong, H.Y., Goh, B.Y.S., Chiong, E. et al. Robotic kidney autotransplantation in a porcine model: a procedure-specific training platform for the simulation of robotic intracorporeal vascular anastomosis. J Robotic Surg 12, 693–698 (2018). https://doi.org/10.1007/s11701-018-0806-5

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  • DOI: https://doi.org/10.1007/s11701-018-0806-5

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