Artificial Intelligence-Based Video Feedback to Improve Novice Performance on Robotic Suturing Skills: A Pilot Study.

Journal: Journal of endourology
PMID: 37905524

Abstract

Automated skills assessment can provide surgical trainees with objective, personalized feedback during training. Here, we measure the efficacy of artificial intelligence (AI)-based feedback on a robotic suturing task. Forty-two participants with no robotic surgical experience were randomized to a control or feedback group and video-recorded while completing two rounds (R1 and R2) of suturing tasks on a da Vinci surgical robot. Participants were assessed on needle handling and needle driving, and feedback was provided via a visual interface after R1. For feedback group, participants were informed of their AI-based skill assessment and presented with specific video clips from R1. For control group, participants were presented with randomly selected video clips from R1 as a placebo. Participants from each group were further labeled as underperformers or innate-performers based on a median split of their technical skill scores from R1. Demographic features were similar between the control ( = 20) and feedback group ( = 22) ( > 0.05). Observing the improvement from R1 to R2, the feedback group had a significantly larger improvement in needle handling score (0.30 -0.02,  = 0.018) when compared with the control group, although the improvement of needle driving score was not significant when compared with the control group (0.17 -0.40,  = 0.074). All innate-performers exhibited similar improvements across rounds, regardless of feedback ( > 0.05). In contrast, underperformers in the feedback group improved more than the control group in needle handling ( = 0.02). AI-based feedback facilitates surgical trainees' acquisition of robotic technical skills, especially underperformers. Future research will extend AI-based feedback to additional suturing skills, surgical tasks, and experience groups.

Authors

  • Runzhuo Ma
    Center for Robotic Simulation & Education, Catherine & Joseph Aresty Department of Urology, USC Institute of Urology, University of Southern California, Los Angeles, California, USA.
  • Dani Kiyasseh
  • Jasper A Laca
    Catherine & Joseph Aresty Department of Urology, Center for Robotic Simulation and Education, USC Institute of Urology, University of Southern California, Los Angeles, California, USA.
  • Rafal Kocielnik
    University of Washington, WA.
  • Elyssa Y Wong
    Center for Robotic Simulation & Education, Department of Urology, USC Institute of Urology, University of Southern California, Catherine & Joseph Aresty1441 Eastlake Avenue Suite 7416, Los Angeles, CA, 90089, USA.
  • Timothy N Chu
    Center for Robotic Simulation & Education, Department of Urology, USC Institute of Urology, University of Southern California, Catherine & Joseph Aresty1441 Eastlake Avenue Suite 7416, Los Angeles, CA, 90089, USA.
  • Steven Cen
    Department of Radiology, Keck School of Medicine, University of Southern California, 1500 San Pablo Street, 2nd Floor, Los Angeles, CA, 90033, USA.
  • Cherine H Yang
    Center for Robotic Simulation & Education, Department of Urology, USC Institute of Urology, University of Southern California, Catherine & Joseph Aresty1441 Eastlake Avenue Suite 7416, Los Angeles, CA, 90089, USA.
  • Istabraq S Dalieh
    Center for Robotic Simulation & Education, Department of Urology, USC Institute of Urology, University of Southern California, Catherine & Joseph Aresty1441 Eastlake Avenue Suite 7416, Los Angeles, CA, 90089, USA.
  • Taseen F Haque
    Center for Robotic Simulation & Education, Catherine & Joseph Aresty Department of Urology, USC Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA.
  • Mitch G Goldenberg
    Catherine & Joseph Aresty Department of Urology, Center for Robotic Simulation and Education, USC Institute of Urology, University of Southern California, Los Angeles, California, USA.
  • Xiuzhen Huang
    Department of Computer Science, Arkansas State University, Jonesboro, AR, USA.
  • Anima Anandkumar
    Department of Computing and Mathematical Science, California Institute of Technology, Pasadena, California; NVIDIA Corporation, Santa Clara, California.
  • Andrew J Hung
    Center for Robotic Simulation & Education, Catherine & Joseph Aresty Department of Urology, University of Southern California Institute of Urology, Los Angeles, California. Electronic address: Andrew.Hung@med.usc.edu.

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