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Updated: Aug 12, 2025
Adjustable Stiffness, External Fixator for the Rat Femur Osteotomy and Segmental Bone Defect Models
Published on: October 9, 2014
Preliminary stage in the development of an artificial intelligence algorithm: Variations between 100 surgeons in
Camille Graëff1, Audrey Daiss2, Thomas Lampert3
1ICube CNRS UMR7357, Strasbourg University, 2-4, rue Boussingault, 67000 Strasbourg, France; IHU, Institute of image-guided surgery, Strasbourg, France.
Introduction:
In order to be used naturally and widely, an artificial intelligence algorithm of phase detection in surgical videos presupposes an expert consensus defining phases.
Objectives:
The aim of the present study was to seek consensus in defining the various phases of a surgical technique in wrist traumatology.
Methods:
Three thousand two hundred and twenty-nine surgeons were sent a video showing anterior plate fixation of the distal radius and a questionnaire on the number of phases they distinguished and the visual cues signaling the beginning of each phase. Three experimenters predefined the number of phases (5: installation, approach, fixation, verification, closure) and sub-phases (3a: introduction of plate; 3b: positioning distal screws; 3c: positioning proximal screws) and the cues signaling the beginning of each. The numbers of the responses per item were collected.
Results:
Only 216 (6.7%) surgeons opened the questionnaire, and 100 answered all questions (3.1%). Most respondents claimed 5/5 expertise. Number of phases identified ranged between 3 and 10. More than two-thirds of respondents identified the same phase cue as defined by the 3 experimenters in most cases, except for "verification" and "positioning proximal screws".
Discussion:
Surgical procedures comprise a succession of phases, the beginning or end of which can be defined by a precise visual cue on video, either beginning with the appearance of the cue or the disappearance of the cue defining the preceding phase.
Conclusion:
These cues need to be defined very precisely before attempting manual annotation of surgical videos in order to develop an artificial intelligence algorithm.
Level Of Evidence:
II.
