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Cui Z, Ma R, Yang CH, Malpani A, Chu TN, Ghazi A, Davis JW, Miles BJ, Lau C, Liu Y, Hung AJ. Capturing relationships between suturing sub-skills to improve automatic suturing assessment. NPJ Digit Med 2024; 7:152. [PMID: 38862627 PMCID: PMC11167055 DOI: 10.1038/s41746-024-01143-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Accepted: 05/22/2024] [Indexed: 06/13/2024] Open
Abstract
Suturing skill scores have demonstrated strong predictive capabilities for patient functional recovery. The suturing can be broken down into several substep components, including needle repositioning, needle entry angle, etc. Artificial intelligence (AI) systems have been explored to automate suturing skill scoring. Traditional approaches to skill assessment typically focus on evaluating individual sub-skills required for particular substeps in isolation. However, surgical procedures require the integration and coordination of multiple sub-skills to achieve successful outcomes. Significant associations among the technical sub-skill have been established by existing studies. In this paper, we propose a framework for joint skill assessment that takes into account the interconnected nature of sub-skills required in surgery. The prior known relationships among sub-skills are firstly identified. Our proposed AI system is then empowered by the prior known relationships to perform the suturing skill scoring for each sub-skill domain simultaneously. Our approach can effectively improve skill assessment performance through the prior known relationships among sub-skills. Through the proposed approach to joint skill assessment, we aspire to enhance the evaluation of surgical proficiency and ultimately improve patient outcomes in surgery.
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Affiliation(s)
- Zijun Cui
- University of Southern California, Los Angeles, CA, USA
| | - Runzhuo Ma
- Department of Urology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Cherine H Yang
- Department of Urology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | | | - Timothy N Chu
- University of Southern California, Los Angeles, CA, USA
| | - Ahmed Ghazi
- Johns Hopkins University, Baltimore, MD, USA
| | - John W Davis
- University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | | | | | - Yan Liu
- University of Southern California, Los Angeles, CA, USA
| | - Andrew J Hung
- Department of Urology, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
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Sanford DI, Ma R, Ghoreifi A, Haque TF, Nguyen JH, Hung AJ. Association of Suturing Technical Skill Assessment Scores Between Virtual Reality Simulation and Live Surgery. J Endourol 2022; 36:1388-1394. [PMID: 35848509 PMCID: PMC9587778 DOI: 10.1089/end.2022.0158] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023] Open
Abstract
Introduction: Robotic surgical performance, in particular suturing, has been linked to postoperative clinical outcomes. Before attempting live surgery, virtual reality (VR) simulators afford opportunities for training surgeons to learn fundamental technical skills. Herein, we evaluate the association of suturing technical skill assessments between VR simulation and live surgery, and functional clinical outcomes. Materials and Methods: Twenty surgeons completed a VR suturing exercise on the Mimic™ Flex VR simulator and the anterior vesicourethral anastomosis during robot-assisted radical prostatectomy (RARP). Three independent and blinded graders provided technical skill scores using a validated assessment tool. Correlations between VR and live scores were assessed by Spearman's correlation coefficients (ρ). In addition, 117 historic RARP cases from participating surgeons were extracted, and the association between VR technical skill scores and urinary continence recovery was assessed by a multilevel mixed-effects model. Results: A total of 20 (6 training and 14 expert) surgeons participated. Statistically significant correlations for scores provided between VR simulation and live surgery were found for overall and needle driving scores (ρ = 0.555, p = 0.011; ρ = 0.570, p = 0.009, respectively). A subanalysis performed on training surgeons found significant correlations for overall scores between VR simulation and live surgery (ρ = 0.828, p = 0.042). Expert cases with high VR needle driving scores had significantly greater continence recovery rates at 24 months after RARP (98.5% vs 84.9%, p = 0.028). Conclusions: Our study found significant correlations in technical scores between VR and live surgery, especially among training surgeons. In addition, we found that VR needle driving scores were associated with continence recovery after RARP. Our data support the association of skill assessments between VR simulation and live surgery and potential implications for clinical outcomes.
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Affiliation(s)
- Daniel I. Sanford
- Catherine & Joseph Aresty Department of Urology, Center for Robotic Simulation & Education, USC Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Runzhuo Ma
- Catherine & Joseph Aresty Department of Urology, Center for Robotic Simulation & Education, USC Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Alireza Ghoreifi
- Catherine & Joseph Aresty Department of Urology, Center for Robotic Simulation & Education, USC Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Taseen F. Haque
- Catherine & Joseph Aresty Department of Urology, Center for Robotic Simulation & Education, USC Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Jessica H. Nguyen
- Catherine & Joseph Aresty Department of Urology, Center for Robotic Simulation & Education, USC Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Andrew J. Hung
- Catherine & Joseph Aresty Department of Urology, Center for Robotic Simulation & Education, USC Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
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