Task decomposition of laparoscopic surgery for objective evaluation of surgical residents' learning curve using hidden Markov Model

Jacob Rosén, Massimiliano Solazzo, Blake Hannaford, Mika Sinanan

Computer Aided Surgery · 2002 · 116 citations · 29 references

DOIFull text

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Concepts

TL;DR

Laparoscopic surgical skill assessment is typically a subjective process performed by senior surgeons in the operating room. The study aimed to determine whether haptic and tool‑tissue interaction data are skill‑dependent and whether Hidden Markov Models can objectively evaluate laparoscopic performance. Researchers defined fourteen tool‑tissue interaction types with distinct force/torque signatures, built HMMs for each subject and surgical step, and compared the statistical distances between experts and residents. The HMM distances differed significantly, revealing major differences in force/torque magnitudes, interaction types and transitions, and timing—especially between first‑year and third‑year residents—demonstrating a learning curve that peaks between years one and three.

Abstract

Objective: Evaluation of the laparoscopic surgical skills of surgical residents is usually a subjective process carried out in the operating room by senior surgeons. The two hypotheses of the current study were: (1) haptic information and tool/tissue interactions (types and transitions) performed in laparoscopic surgery are skill-dependent, and (2) statistical models (Hidden Markov Models—HMMs) incorporating these data are capable of objectively evaluating laparoscopic surgical skills.Materials and Methods: Eight subjects (six residents—two first-year (R1), two third-year (R3), and two fifth-year (R5)—and two expert laparoscopic surgeons) performed laparoscopic cholecystectomy on pigs using an instrumented grasper equipped with force/torque (F/T) sensors at the hand/tool interface, and F/T data was synchronized with video of the operative maneuvers. Fourteen types of tool/tissue (T/T) interactions, each associated with unique F/T signatures, were defined from frame-by-frame video analysis. HMMs for each subject and step of the operation were compared to evaluate the statistical distance between expert surgeons and residents with different skill levels.Results: The statistical distances between HMMs representing expert surgeons and residents were significantly different (α < 0.05). Major differences occurred in: (1) F/T magnitudes; (2) type of T/T interactions and transitions between them; and (3) time intervals for each T/T interaction and overall completion time. The greatest difference in performance was between Rl (junior trainee) and R3 (midlevel trainee). Smaller changes were seen as expertise increased beyond the R3 level.Conclusion: HMMs incorporating haptic and visual information provide an objective tool for evaluating surgical skills. Objective evidence for a "learning curve" suggests that surgical residents acquire a major portion of their laparoscopic skill between year 1 and year 3 of training.

References

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