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Surgical skills: Can learning curves be computed from recordings of surgical activities?

  • Germain Forestier
  • Laurent Riffaud
  • François Petitjean
  • Pierre-Louis Henaux
  • Pierre Jannin
Original Article

Abstract

Purpose

Surgery is one of the riskiest and most important medical acts that are performed today. The need to improve patient outcomes and surgeon training, and to reduce the costs of surgery, has motivated the equipment of operating rooms with sensors that record surgical interventions. The richness and complexity of the data that are collected call for new methods to support computer-assisted surgery. The aim of this paper is to support the monitoring of junior surgeons learning their surgical skill sets.

Methods

Our method is fully automatic and takes as input a series of surgical interventions each represented by a low-level recording of all activities performed by the surgeon during the intervention (e.g., cut the skin with a scalpel). Our method produces a curve describing the process of standardization of the behavior of junior surgeons. Given the fact that junior surgeons receive constant feedback from senior surgeons during surgery, these curves can be directly interpreted as learning curves.

Results

Our method is assessed using the behavior of a junior surgeon in anterior cervical discectomy and fusion surgery over his first three years after residency. They revealed the ability of the method to accurately represent the surgical skill evolution. We also showed that the learning curves can be computed by phases allowing a finer evaluation of the skill progression.

Conclusion

Preliminary results suggest that our approach constitutes a useful addition to surgical training monitoring.

Keywords

Surgical data science Surgical process model DTW Learning curves 

Notes

Acknowledgements

Dr François Petitjean is the recipient of an Australian Research Council Discovery Early Career Award (Project Number DE170100037) funded by the Australian Government.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

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Copyright information

© CARS 2018

Authors and Affiliations

  1. 1.IRIMASUniversity of Haute-AlsaceMulhouseFrance
  2. 2.Department of NeurosurgeryUniv. Hospital, Univ Rennes, Inserm, LTSI (Laboratoire Traitement du Signal et de l’Image) - UMR_S 1099RennesFrance
  3. 3.Faculty of Information TechnologyMonash UniversityMelbourneAustralia
  4. 4.Univ Rennes, Inserm, LTSI (Laboratoire Traitement du Signal et de l’Image) - UMR_S 1099RennesFrance

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