Literature DB >> 34718926

Computer vision coaching microsurgical laboratory training: PRIME (Proficiency Index in Microsurgical Education) proof of concept.

Marcelo Magaldi Oliveira1, Lucas Quittes2, Pollyana Helena Vieira Costa2, Taise Mosso Ramos2, Ana Clara Fidelis Rodrigues2, Arthur Nicolato2, Jose Augusto Malheiros2, Carla Machado2.   

Abstract

Computer vision (CV) feedback could be aimed as a constant tutor to guide ones proficiency during microsurgical practice in controlled environments. Five neurosurgeons with different levels of microsurgical expertise performed simulated vessel dissection and micro-suture in an ex vivo model for posterior computer analysis of recorded videos. A computer program called PRIME (Proficiency Index of Microsurgical Education) used in this research recognized color-labeled surgical instruments, from downloading videos into a platform, with a range of motion greater than 3 mm, for objective evaluation of number of right and left hand movements. A proficiency index of 0 to 1 was pre-established in order to evaluate continuous training improvement. PRIME computer program captured all hand movements executed by participants, except for small tremors or inconsistencies that have a range of motion inferior to 3 mm. Number of left and right hand movements were graphically expressed in order to guide more objective and efficacious training for each trainee, without requiring body sensors and cameras around the operating table. Participants with previous microsurgical experience showed improvement from 0.2 to 0.6 (p < 0.05), while novices had no improvement. Proficiency index set by CV was suggested, in a self-challenge and self-coaching manner. PRIME would offer the capability of constant laboratory microsurgical practice feedback under CV guidance, opening a new window for oriented training without a tutor or specific apparatus regarding all levels of microsurgical proficiency. Prospective, large data study is needed to confirm this hypothesis.
© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

Entities:  

Keywords:  Cerebrovascular surgery; Computer vision; Microsurgery; Neurosurgical education; Neurosurgical simulation; Neurosurgical training; Surgical training

Mesh:

Year:  2021        PMID: 34718926     DOI: 10.1007/s10143-021-01663-6

Source DB:  PubMed          Journal:  Neurosurg Rev        ISSN: 0344-5607            Impact factor:   3.042


  10 in total

1.  Implementing and Evaluating a National Certification Technical Skills Examination: The Colorectal Objective Structured Assessment of Technical Skill.

Authors:  Sandra de Montbrun; Patricia L Roberts; Lisa Satterthwaite; Helen MacRae
Journal:  Ann Surg       Date:  2016-07       Impact factor: 12.969

2.  Face, content, and construct validity of human placenta as a haptic training tool in neurointerventional surgery.

Authors:  Marcelo Magaldi Ribeiro de Oliveira; Arthur Nicolato; Marcilea Santos; Joao Victor Godinho; Rafael Brito; Alexandre Alvarenga; Ana Luiza Valle Martins; André Prosdocimi; Felipe Padovani Trivelato; Abdulrahman J Sabbagh; Augusto Barbosa Reis; Rolando Del Maestro
Journal:  J Neurosurg       Date:  2015-10-09       Impact factor: 5.115

3.  A Cross-Sectional Survey Study among Hand Surgeons in the United States on Standardizing Microsurgery Training.

Authors:  Raman Mehrzad; Adnan Prsic; Marten Basta; Reena Bhatt
Journal:  J Hand Microsurg       Date:  2018-09-27

Review 4.  Defining Standards in Experimental Microsurgical Training: Recommendations of the European Society for Surgical Research (ESSR) and the International Society for Experimental Microsurgery (ISEM).

Authors:  René H Tolba; Zoltán Czigány; Suzanne Osorio Lujan; Mihai Oltean; Michael Axelsson; Yelena Akelina; Antonio Di Cataldo; Iren Miko; Istvan Furka; Uta Dahmen; Eiji Kobayashi; Mihai Ionac; Norbert Nemeth
Journal:  Eur Surg Res       Date:  2017-07-26       Impact factor: 1.745

5.  Microsurgery Training Resource Variation among US Integrated Plastic Surgery Residency Programs.

Authors:  Melissa A Mueller; Navid Pourtaheri; Gregory R D Evans
Journal:  J Reconstr Microsurg       Date:  2018-08-18       Impact factor: 2.873

6.  Intra-operative surgical instrument usage detection on a multi-sensor table.

Authors:  Bernhard Glaser; Stefan Dänzer; Thomas Neumuth
Journal:  Int J Comput Assist Radiol Surg       Date:  2014-05-15       Impact factor: 2.924

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

Authors:  Germain Forestier; Laurent Riffaud; François Petitjean; Pierre-Louis Henaux; Pierre Jannin
Journal:  Int J Comput Assist Radiol Surg       Date:  2018-03-03       Impact factor: 2.924

8.  Learning brain aneurysm microsurgical skills in a human placenta model: predictive validity.

Authors:  Marcelo Magaldi Ribeiro de Oliveira; Carlos Eduardo Ferrarez; Taise Mosso Ramos; Jose Augusto Malheiros; Arthur Nicolato; Carla Jorge Machado; Mauro Tostes Ferreira; Fellype Borges de Oliveira; Cecília Félix Penido Mendes de Sousa; Pollyana Helena Vieira Costa; Sebastiao Gusmao; Giuseppe Lanzino; Rolando Del Maestro
Journal:  J Neurosurg       Date:  2017-03-24       Impact factor: 5.115

9.  Beyond the hype of big data and artificial intelligence: building foundations for knowledge and wisdom.

Authors:  Josip Car; Aziz Sheikh; Paul Wicks; Marc S Williams
Journal:  BMC Med       Date:  2019-07-17       Impact factor: 8.775

10.  Pilot study on an innovative biosensor with a range of medical and surgical applications.

Authors:  P Sains; K S Chana; V Sridhar; M S Sajid
Journal:  BMC Res Notes       Date:  2018-01-29
  10 in total

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