Objective Assessment of Endovascular Navigation Skills with Force Sensing.

Journal: Annals of biomedical engineering
Published Date:

Abstract

Despite the increasing popularity of endovascular intervention in clinical practice, there remains a lack of objective and quantitative metrics for skill evaluation of endovascular techniques. Data relating to the forces exerted during endovascular procedures and the behavioral patterns of endovascular clinicians is currently limited. This research proposes two platforms for measuring tool forces applied by operators and contact forces resulting from catheter-tissue interactions, as a means of providing accurate, objective metrics of operator skill within a realistic simulation environment. Operator manipulation patterns are compared across different experience levels performing various complex catheterization tasks, and different performance metrics relating to tool forces, catheter motion dynamics, and forces exerted on the vasculature are extracted. The results depict significant differences between the two experience groups in their force and motion patterns across different phases of the procedures, with support vector machine (SVM) classification showing cross-validation accuracies as high as 90% between the two skill levels. This is the first robust study, validated across a large pool of endovascular specialists, to present objective measures of endovascular skill based on exerted forces. The study also provides significant insights into the design of optimized metrics for improved training and performance assessment of catheterization tasks.

Authors

  • Hedyeh Rafii-Tari
    The Hamlyn Centre for Robotic Surgery, Imperial College London, Level 4, Bessemer Building, South Kensington Campus, London, SW7 2AZ, UK. h.rafii-tari11@imperial.ac.uk.
  • Christopher J Payne
  • Colin Bicknell
    Academic Division of Surgery, Imperial College London, London, UK.
  • Ka-Wai Kwok
    Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, Hong Kong SAR, China.
  • Nicholas J W Cheshire
    Academic Division of Surgery, Imperial College London, London, UK.
  • Celia Riga
    Academic Division of Surgery, Imperial College London, London, UK.
  • Guang-Zhong Yang
    Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, China. dgunning@fb.com gzyang@sjtu.edu.cn.