Academic Journal
Developing and evaluating image-based metrics for open surgical suturing skill assessment.
| Τίτλος: | Developing and evaluating image-based metrics for open surgical suturing skill assessment. |
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| Συγγραφείς: | Gao J; Department of Electrical and Computer Engineering, Clemson University, Clemson, SC USA., Singh SP; Department of Bioengineering, Clemson University, Clemson, SC USA., Shayan AM; Department of Bioengineering, Clemson University, Clemson, SC USA., Eidt JF; Division of Vascular Surgery, Baylor Scott & White Heart and Vascular Hospital, Dallas, TX USA., Bible J; School of Mathematical and Statistical Sciences, Clemson University, Clemson, SC USA., Blas JVV; School of Medicine, University of South Carolina, Greenville, SC USA., Gandhi SS; School of Medicine, University of South Carolina, Greenville, SC USA., Singapogu R; Department of Bioengineering, Clemson University, Clemson, SC USA., Groff RE; Department of Electrical and Computer Engineering, Clemson University, Clemson, SC USA. |
| Πηγή: | Global surgical education : journal of the Association for Surgical Education [Global Surg Educ] 2026; Vol. 5 (1), pp. 196. Date of Electronic Publication: 2026 Oct 13. |
| Τύπος έκδοσης: | Journal Article |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: Springer Country of Publication: United States NLM ID: 9918697586306676 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2731-4588 (Electronic) Linking ISSN: 27314588 NLM ISO Abbreviation: Global Surg Educ Subsets: PubMed not MEDLINE |
| Imprint Name(s): | Original Publication: [New York] : Springer, [2022]- |
| Περίληψη: | Purpose: Open surgery training is vital in vascular surgery education. Traditionally, trainees' open surgical suturing skills are evaluated by their educators, which is a subjective and time-consuming process. This paper evaluates image-based metrics for surgical suturing skill assessment by comparing performance among three groups: attending surgeons, resident surgeons, and novices. Methods: A simulator, named SutureCoach, is developed to simulate a radial suturing task, performed either at "depth," representing a cavity, or at "surface." Among other sensors, the simulator includes cameras and computer vision software to track the motion of the needle and thread under the membrane being sutured. A set of image-based metrics are calculated for each suture based on video data. The set of metrics includes four previously proposed metrics as well as four new metrics inspired by a refined suturing phase segmentation scheme. To evaluate the performance of the image-based metrics, we conducted a study with 97 participants, divided almost evenly between attending surgeons, resident surgeons, and novices. Data was collected at several events over a 5-month period. Results: The statistical analysis shows that all metrics have significantly different means when comparing performance between novices and surgeons at both conditions, surface and depth. Furthermore, seven out of eight metrics have significant mean differences when comparing resident surgeons' and attending surgeons' performance at the depth condition. Conclusion: Image-based metrics are capable of suturing skill assessment, especially for distinguishing novices from surgeons. Depth constraints allow higher skill levels to be better differentiated. Supplementary Information: The online version contains supplementary material available at https://doi.org/10.1007/s44186-026-00596-2. (© The Author(s) 2026.) |
| Competing Interests: | Conflict of interestDr. Singapogu is the founder of and holds equity in Sojourn MedTech LLC. Additionally, Sojourn MedTech LLC had no role in the study design, data collection and analysis of this study. |
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| Grant Information: | R01 HL146843 United States HL NHLBI NIH HHS |
| Contributed Indexing: | Keywords: Computer vision; Medical simulator; Objective metrics; Open surgery; Surgical skill assessment; Suturing |
| Entry Date(s): | Date Created: 20261015 Latest Revision: 20261017 |
| Update Code: | 20261017 |
| PubMed Central ID: | PMC13661727 |
| DOI: | 10.1007/s44186-026-00596-2 |
| PMID: | 42876941 |
| Βάση Δεδομένων: | MEDLINE |
| ISSN: | 2731-4588 |
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| DOI: | 10.1007/s44186-026-00596-2 |