Preliminary stage in the development of an artificial intelligence algorithm: Variations between 100 surgeons in phase annotation in a video of internal fixation of distal radius fracture.


Journal

Orthopaedics & traumatology, surgery & research : OTSR
ISSN: 1877-0568
Titre abrégé: Orthop Traumatol Surg Res
Pays: France
ID NLM: 101494830

Informations de publication

Date de publication:
10 2023
Historique:
received: 11 07 2022
revised: 16 11 2022
accepted: 13 12 2022
medline: 3 10 2023
pubmed: 27 1 2023
entrez: 26 1 2023
Statut: ppublish

Résumé

In order to be used naturally and widely, an artificial intelligence algorithm of phase detection in surgical videos presupposes an expert consensus defining phases. The aim of the present study was to seek consensus in defining the various phases of a surgical technique in wrist traumatology. 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. 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". 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. These cues need to be defined very precisely before attempting manual annotation of surgical videos in order to develop an artificial intelligence algorithm. II.

Identifiants

pubmed: 36702298
pii: S1877-0568(23)00021-X
doi: 10.1016/j.otsr.2023.103564
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

103564

Informations de copyright

Copyright © 2023 Elsevier Masson SAS. All rights reserved.

Auteurs

Camille Graëff (C)

ICube CNRS UMR7357, Strasbourg University, 2-4, rue Boussingault, 67000 Strasbourg, France; IHU, Institute of image-guided surgery, Strasbourg, France.

Audrey Daiss (A)

Department of hand surgery, Strasbourg University Hospitals, FMTS, 1, avenue Molière, 67200 Strasbourg, France.

Thomas Lampert (T)

ICube CNRS UMR7357, Strasbourg University, 2-4, rue Boussingault, 67000 Strasbourg, France.

Nicolas Padoy (N)

ICube CNRS UMR7357, Strasbourg University, 2-4, rue Boussingault, 67000 Strasbourg, France; IHU, Institute of image-guided surgery, Strasbourg, France.

Antoine Martins (A)

Department of hand surgery, Strasbourg University Hospitals, FMTS, 1, avenue Molière, 67200 Strasbourg, France.

Marie-Cécile Sapa (MC)

Department of hand surgery, Strasbourg University Hospitals, FMTS, 1, avenue Molière, 67200 Strasbourg, France.

Philippe Liverneaux (P)

ICube CNRS UMR7357, Strasbourg University, 2-4, rue Boussingault, 67000 Strasbourg, France; Department of hand surgery, Strasbourg University Hospitals, FMTS, 1, avenue Molière, 67200 Strasbourg, France. Electronic address: philippe.liverneaux@chru-strasbourg.fr.

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