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An effective visualisation and registration system for image-guided robotic partial nephrectomy

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Abstract

Robotic partial nephrectomy is presently the fastest-growing robotic surgical procedure, and in comparison to traditional techniques it offers reduced tissue trauma and likelihood of post-operative infection, while hastening recovery time and improving cosmesis. It is also an ideal candidate for image guidance technology since soft tissue deformation, while still present, is localised and less problematic compared to other surgical procedures. This work describes the implementation and ongoing development of an effective image guidance system that aims to address some of the remaining challenges in this area. Specific innovations include the introduction of an intuitive, partially automated registration interface, and the use of a hardware platform that makes sophisticated augmented reality overlays practical in real time. Results and examples of image augmentation are presented from both retrospective and live cases. Quantitative analysis of registration error verifies that the proposed registration technique is appropriate for the chosen image guidance targets.

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Acknowledgments

An abstract of this work was presented at the Hamlyn Symposium on Medical Robotics, June 2011, London. Volume rendering software was provided by Anatomage Inc. The authors are grateful for support from The Hamlyn Centre and the NIHR Biomedical Research Centre funding scheme.

Conflict of interest

None.

Ethical standards

Favourable ethical opinion for the image collection and guidance protocols used in this study was given by the research ethics committee West London REC 2. Written informed consent was obtained from recruited patients for publication of this article and any accompanying images. A copy of the written consent is available for review by the Editor-in-Chief of this journal.

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Authors and Affiliations

  1. Hamlyn Centre for Robotic Surgery, Imperial College London, Bessemer Building, South Kensington Campus, Exhibition Road, London, SW7 2AZ, UK

    Philip Pratt & Guang-Zhong Yang

  2. Department of Surgery and Cancer, Imperial College London, London, UK

    Erik Mayer, Justin Vale, Daniel Cohen, Eddie Edwards & Ara Darzi

Authors
  1. Philip Pratt
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  2. Erik Mayer
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  3. Justin Vale
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  4. Daniel Cohen
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  5. Eddie Edwards
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  6. Ara Darzi
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  7. Guang-Zhong Yang
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Corresponding author

Correspondence to Philip Pratt.

Additional information

Philip Pratt and Erik Mayer are joint first authors.

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Pratt, P., Mayer, E., Vale, J. et al. An effective visualisation and registration system for image-guided robotic partial nephrectomy. J Robotic Surg 6, 23–31 (2012). https://doi.org/10.1007/s11701-011-0334-z

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  • DOI: https://doi.org/10.1007/s11701-011-0334-z

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