Objective Evaluation of Residents Laparoscopic Surgical Skill Based on Haptic Information and Tool/Tissue Interactions
Laparoscopic surgical skill evaluation of surgical residents is usually a subjective process, carried out in the operating room by senior surgeons. By its nature, this process is performed using fuzzy criteria. The current study is part of an ongoing research aimed to develop and assess an objective laparoscopic surgical skill scale using Hidden Markov Models (HMM) based on haptic information, tool/tissue interactions and visual task decomposition. The specific objective of the current study was to evaluate an objective laparoscopic surgical learning-curve of students as a function of their surgical training stage.
Methods & Tools
Eight subjects (six residents: first year surgical residents 2xR1, third year surgical residents 2xR3 fifth year surgical residents 2xR5; and two expert laparoscopic surgeons: 2xES) performed laparoscopic cholecystectomy following a specific seven step protocol on a pig. An instrumented laparoscopic grasper equipped with a three-axis force/torque sensor located at the proximal end of the tool's shaft in addition to a force sensor located at the grasper's handle were used to measure the forces and torques (F/T) at the hand/tool interface. The force/torque measurements synchronized with a video of the tool operative maneuvers were incorporated into a real-time graphical user interface which was recorded for of-line analysis. A synthesis of frame-by-frame video analysis was used to characterize 14 different types of tool/tissue interactions defined as states each one associated with unique F/T signatures defined as observations. A fully connected 14 finite-state model architecture was developed based on that analysis. HMMs developed based on this architecture for each subject representing the surgical skills in terms of haptic information and tool tissue interactions. The statistical distance between the HMMs representing residents at different levels of their training and the HMMs of expert surgeons were calculated in order to evaluate the learning curve of selected steps of laparoscopic cholecystectomy.
The objective laparoscopic surgical skill learning-curve showed significant differences between all skill levels. The major differences between skill levels were: (i) magnitudes of F/T applied (ii) types of tool/tissue interactions used and the transition between them and (iii) time intervals spent in each tool/tissue interaction and the overall completion time. The magnitude of F/T applied by expert and novice surgeons varied based on the task being preformed. High F/T magnitudes were applied by R1 compared to ES while performing tissue manipulation. However, low F/T magnitudes were applied by the R1 compared to the ES during tissue dissection. Moreover, the expert and novice surgeons took different paths in terms of states and transitions to reach the same goal. In addition, the surgical procedure’s completion time was longer for the R1 by a factor of 1.5 to 4.8 (p<0.05) when compared to the ES. The main factor contributing to this significant difference was the time spent in the idle state. The difference between R1 and ES was more profound in steps requiring higher dexterity and manual skill compared to steps where a specific organ was placed in a specific position. The HMM analysis showed that the greatest difference in performance was between R1 and R3 and then decreased as the level of expertise increased.
HMM incorporating haptic and tool/tissue interactions provides an objective tool for evaluating surgical skills. Using the F/T information in real-time during the course of learning as a feedback information to the R1 may improve the learning curve, reduce soft tissue injury and increase the efficiency during endoscopic surgery. The objective evidence for a learning curve indicates that the surgical residents appear to acquire a major portion of their laparoscopic surgical capabilities between the first and the third years of their residency training.
Instrumented laparoscopic Tool
| Status: Completed |
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Rosen Jacob, C. Richards, Blake Hannaford, Mika N. Sinanan, Hidden Markov Models of Minimally Invasive Surgery, Studies in Health Technology and Informatics - Medicine Meets Virtual Reality, Vol. 70 pp. 279-285, IOS Press, January 2000. [ CP4]
Rosen Jacob, Massimiliano Solazzo, Blake Hannaford, Mika N. Sinanan , Objective Evaluation of Laparoscopic Surgical Skills Using Hidden Markov Models Based on Haptic Information and Tool/Tissue Interactions, American College of Surgeons Annual Meeting - Washington State Chapter, Lake Chelan, June 2000. [ CP5]
Rosen Jacob, Massimiliano Solazzo, Blake Hannaford, Mika N. Sinanan, Objective Laparoscopic Skills Assessments of Surgical Residents Using Hidden Markov Models Based on Haptic Information and Tool/Tissue Interactions, Studies in Health Technology and Informatics - Medicine Meets Virtual Reality, Vol. 81, pp.417-423, IOS Press, January 2001. [ CP7]