Objective laparoscopic skills assessments of surgical residents using Hidden Markov Models based on haptic information and tool/tissue interactions.
Laparoscopic surgical skills evaluation of surgery 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 objective of the current study was 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.


METHODS
Eight subjects (six surgical trainees: first year surgical residents 2 x R1, third year surgical residents 2 x R3 fifth year surgical residents 2 x R5; and two expert laparoscopic surgeons: 2 x ES) performed laparoscopic cholecystectomy following a specific 7 steps protocol on a pig. An instrumented laparoscopic grasper equipped with a three-axis force/torque sensor located at the proximal end with an additional force sensor located on the handle, was used to measure the forces and torques. The hand/tool interface force/torque data was synchronized with a video of the tool operative maneuvers. A synthesis of frame-by-frame video analysis was used to define 14 different types of tool/tissue interactions, each one associated with unique force/torque (F/T) signatures. HMMs were developed for each subject representing the surgical skills by defining the various tool/tissue interactions as states and the associated F/T signatures as observations. 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 generate a learning curve of selected steps during laparoscopic cholecystectomy.


RESULTS
Comparison of HMM's between groups showed significant differences between all skill levels, supporting the objective definition of a learning curve. 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 objective HMM analysis showed that the greatest difference in performance was between R1 and R3 groups and then decreased as the level of expertise increased, suggesting that significant laparoscopic surgical capability develops between the first and the third years of their residency training. The power of the methodology using HMM for objective surgical skill assessment arises from the fact that it compiles enormous amount of data regarding different aspects of surgical skill into a very compact model that can be translated into a single number representing the distance from expert performance. Moreover, the methodology is not limited to in-vivo condition as demonstrated in the current study. It can be extended to other modalities such as measuring performance in surgical simulators and robotic systems.
Rosen
J
J
Department of Electrical Engineering, Box 352500, University of Washington, Seattle, WA 98195, USA. rosen@rcs.ee.washington.edu
Solazzo
M
M
Hannaford
B
B
Sinanan
M
M
D000818:Animals; D017081:Cholecystectomy, Laparoscopic; D002983:Clinical Competence; D003194:Computer-Assisted Instruction; D003479:Curriculum; D005246:Feedback; D013502:General Surgery / Q000193:education*; D006801:Humans; D007396:Internship and Residency; D010535:Laparoscopy; D008390:Markov Chains; D008432:Mathematical Computing; D014110:Touch; D014584:User-Computer Interface