Diagnostics (Nov 2023)

Surgical Phase Duration in Robot-Assisted Partial Nephrectomy: A Surgical Data Science Exploration for Clinical Relevance

  • Pieter De Backer,
  • Maria Peraire Lores,
  • Meret Demuynck,
  • Federico Piramide,
  • Jente Simoens,
  • Tim Oosterlinck,
  • Wouter Bogaert,
  • Chi Victor Shan,
  • Karel Van Regemorter,
  • Aube Wastyn,
  • Enrico Checcucci,
  • Charlotte Debbaut,
  • Charles Van Praet,
  • Rui Farinha,
  • Ruben De Groote,
  • Anthony Gallagher,
  • Karel Decaestecker,
  • Alexandre Mottrie

DOI
https://doi.org/10.3390/diagnostics13213386
Journal volume & issue
Vol. 13, no. 21
p. 3386

Abstract

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(1) Background: Surgical phases form the basic building blocks for surgical skill assessment, feedback, and teaching. The phase duration itself and its correlation with clinical parameters at diagnosis have not yet been investigated. Novel commercial platforms provide phase indications but have not been assessed for accuracy yet. (2) Methods: We assessed 100 robot-assisted partial nephrectomy videos for phase durations based on previously defined proficiency metrics. We developed an annotation framework and subsequently compared our annotations to an existing commercial solution (Touch Surgery, Medtronic™). We subsequently explored clinical correlations between phase durations and parameters derived from diagnosis and treatment. (3) Results: An objective and uniform phase assessment requires precise definitions derived from an iterative revision process. A comparison to a commercial solution shows large differences in definitions across phases. BMI and the duration of renal tumor identification are positively correlated, as are tumor complexity and both tumor excision and renorrhaphy duration. (4) Conclusions: The surgical phase duration can be correlated with certain clinical outcomes. Further research should investigate whether the retrieved correlations are also clinically meaningful. This requires an increase in dataset sizes and facilitation through intelligent computer vision algorithms. Commercial platforms can facilitate this dataset expansion and help unlock the full potential, provided that the phase annotation details are disclosed.

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