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On Surgical Planning of Percutaneous Nephrolithotomy with Patient-Specific CTRs

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Medical Image Computing and Computer Assisted Intervention – MICCAI 2022 (MICCAI 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13437))

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Abstract

Percutaneous nephrolithotomy (PCNL) is considered a first-choice minimally invasive procedure for treating kidney stones larger than 2 cm. It yields higher stone-free rates than other minimally invasive techniques and is employed when extracorporeal shock wave lithotripsy or uteroscopy are, for instance, infeasible. Using this technique, surgeons create a tract through which a scope is inserted for gaining access to the stones. Traditional PCNL tools, however, present limited maneuverability, may require multiple punctures and often lead to excessive torquing of the instruments which can damage the kidney parenchyma and thus increase the risk of hemorrhage. We approach this problem by proposing a nested optimization-driven scheme for determining a single tract surgical plan along which a patient-specific concentric-tube robot (CTR) is deployed so as to enhance manipulability along the most dominant directions of the stone presentations. The approach is illustrated with seven sets of clinical data from patients who underwent PCNL. The simulated results may set the stage for achieving higher stone-free rates through single tract PCNL interventions while decreasing blood loss.

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Acknowledgements

This work was supported by the National Institute of Diabetes and Digestive and Kidney Diseases of the National Institutes of Health through Grant Number R01DK119269 and by the Natural Sciences and Engineering Research Council (NSERC) of Canada grant RGPIN1345 (Discovery Grant), and the Canada Research Chairs Program.

Author information

Authors and Affiliations

  1. Western University, London, ON, Canada

    Filipe C. Pedrosa, Navid Feizi & Rajni Patel

  2. Canadian Surgical Technologies and Advanced Robotics, London, ON, Canada

    Filipe C. Pedrosa, Navid Feizi & Rajni Patel

  3. Brigham and Women’s Hospital, Boston, MA, USA

    Ruisi Zhang, Remi Delaunay & Jayender Jagadeesan

  4. Harvard Medical School, Boston, MA, USA

    Ruisi Zhang, Remi Delaunay, Dianne Sacco & Jayender Jagadeesan

  5. Massachusetts General Hospital, Boston, MA, USA

    Dianne Sacco

Authors
  1. Filipe C. Pedrosa
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  2. Navid Feizi
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  3. Ruisi Zhang
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  4. Remi Delaunay
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  5. Dianne Sacco
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  6. Jayender Jagadeesan
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  7. Rajni Patel
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Corresponding author

Correspondence to Filipe C. Pedrosa .

Editor information

Editors and Affiliations

  1. Rochester Institute of Technology, Rochester, NY, USA

    Linwei Wang

  2. Chinese University of Hong Kong, Hong Kong, Hong Kong

    Qi Dou

  3. University of Virginia, Charlottesville, VA, USA

    P. Thomas Fletcher

  4. National Center for Tumor Diseases (NCT/UCC), Dresden, Germany

    Stefanie Speidel

  5. Case Western Reserve University, Cleveland, OH, USA

    Shuo Li

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Pedrosa, F.C. et al. (2022). On Surgical Planning of Percutaneous Nephrolithotomy with Patient-Specific CTRs. In: Wang, L., Dou, Q., Fletcher, P.T., Speidel, S., Li, S. (eds) Medical Image Computing and Computer Assisted Intervention – MICCAI 2022. MICCAI 2022. Lecture Notes in Computer Science, vol 13437. Springer, Cham. https://doi.org/10.1007/978-3-031-16449-1_60

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  • DOI: https://doi.org/10.1007/978-3-031-16449-1_60

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-16448-4

  • Online ISBN: 978-3-031-16449-1

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