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Decomposition and analysis of laparoscopic suturing task using tool-motion analysis (TMA): improving the objective assessment

Authors :
Silvia Enciso-Sanz
Jesús Usón-Gargallo
Juan A. Sánchez-Margallo
Luisa F. Sánchez-Peralta
J. L. Moyano-Cuevas
Francisco M. Sánchez-Margallo
José Moreno
José B. Pagador
Source :
International Journal of Computer Assisted Radiology and Surgery. 7:305-313
Publication Year :
2011
Publisher :
Springer Science and Business Media LLC, 2011.

Abstract

The laparoscopic suturing task is a complex procedure that requires objective assessment of surgical skills. Analysis of laparoscopic suturing task components was performed to improve current objective assessment tools.Twelve subjects participated in this study as three groups of four surgeons (novices, intermediates and experts). A box-trainer and organic tissue were used to perform the experiment while tool movements were recorded with the augmented reality haptic system. All subjects were right-handed and developed a surgeon's knot. The laparoscopic suturing procedure was decomposed into four subtasks. Different objective metrics were applied during tool-motion analysis (TMA). Statistical analysis was performed, and results from three groups were compared using the Jonckheere-Terpstra test, considering significant differences when P ≤ 0.05.Several first, second and fourth subtask metrics had significant differences between the three groups. Subtasks 1 and 2 had more significant differences in metrics than subtask 4. Almost all metrics showed superior task executions accomplished by experts (lower time, total path length and number of movements) compared with intermediates and novices.The most important subtasks during suture learning process are needle puncture and first knot. The TMA could be a useful objective assessment tool to discriminate surgical experience and could be used in the future to measure and certify surgical proficiency.

Details

ISSN :
18616429 and 18616410
Volume :
7
Database :
OpenAIRE
Journal :
International Journal of Computer Assisted Radiology and Surgery
Accession number :
edsair.doi.dedup.....20400be81183072dda56dbec40f1b4b9