Global Versus Local Kinematic Skills Assessment on Robotic Assisted Hysterectomies

EasyChair Preprint 10315

Abstract

Surgical skills assessment is a crucial step to help understanding surgical expertise and to provide technical knowledge to beginners. Scores, such as GOALS, have been designed to assess surgical skills. However, these scores are subjective and need experts to compute them. With the advent of robotic surgery, it is possible to compute Automated Performance Metrics (APMs) based on the motion of robotic arms to assess surgical skills. Several studies have demonstrated statistically significant differences between APMs from different levels of expertise. The majority of these studies performed a global analysis, i.e., studying the surgical procedure or training task as a whole. By using the Surgical Process Model (SPM) methodology, it is possible to describe the surgery at different levels of granularity and break it down into a sequence of elements. In this paper, we combine SPM and APMs to study global and local kinematic skills during robotic-assisted hysterectomies. Fifty-two robotic-assisted laparoscopic hysterectomies performed by expert and intermediate surgeons have been annotated at the phase level and the kinematic data have been synchronized and split according to these annotations to obtain kinematic data for the complete duration of the surgeries (global sequences) and for each surgical phase (local sequences). We computed 16 APMs for the two main robotic arms for each global and local kinematic sequence. Even if the global analysis allows surgical skill assessment with 4 statistically different APMs. The local analysis provided more information (15 APMs are significant for at least one phase) and some of them can be explained clinically.

Keyphrases: Automated Performance Metrics, Surgical Process Model, Surgical Skill Assessment

@booklet{EasyChair:10315,
  author    = {Arnaud Huaulmé and Krystel Nyangoh Timoh and Victor Jan and Sonia Guerin and Pierre Jannin},
  title     = {Global Versus Local Kinematic Skills Assessment on Robotic Assisted Hysterectomies},
  howpublished = {EasyChair Preprint 10315},
  year      = {EasyChair, 2023}}