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Development of an Automated Smartphone-Based Suture Evaluation System
Quantification of skill level in surgical training is necessary for effective skill development. In this study, we report the development of a smartphone application that automatically and objectively evaluates training in stitching goldfish scoop poi, a fragile material currently used for practice...
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Published in: | Journal of surgical education 2022-05, Vol.79 (3), p.802-808 |
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container_title | Journal of surgical education |
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creator | Yamada, Toshiyuki Suda, Hisao Yoshitake, Akihiro Shimizu, Hideyuki |
description | Quantification of skill level in surgical training is necessary for effective skill development. In this study, we report the development of a smartphone application that automatically and objectively evaluates training in stitching goldfish scoop poi, a fragile material currently used for practice by young surgeons in Japan.
The application, named “e-Suture,” enables the automatic evaluation of surgical technique quality by evaluating the gap between the mark printed on the poi and the insertion/extraction point of the needle (Accuracy), analyzing suture placement (Deflection), detecting tears in the poi material/tissue (Tears), and the time taken to perform the exercise (Time). The algorithm for scoring used a sigmoid function, and the coefficients were adjusted so that the scores of a sample of 20 cases ranged between 20 and 100 points.
The e-Suture prototype was completed. The e-Suture-derived ranking for 20 poi after training was significantly correlated with the mean of the rankings evaluated by 9 experts (correlation coefficient: 0.728; p = 0.000). We also tested which items the experts rated as the most important. The overall ratings obtained from the experts correlated with the e-Suture accuracy scoring results with a correlation coefficient of 0.836 (p = 0.000) for Accuracy, 0.31 (p = 0.173) for Deflection, and 0.518 (p = 0.019) for Tear.
The e-Suture application can easily and accurately quantify and evaluate the suturing skills of novie surgeons. Further studies should improve the accuracy of data to be analyzed by collecting more surgical data and applying it to other surgical techniques. |
doi_str_mv | 10.1016/j.jsurg.2021.12.012 |
format | article |
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The application, named “e-Suture,” enables the automatic evaluation of surgical technique quality by evaluating the gap between the mark printed on the poi and the insertion/extraction point of the needle (Accuracy), analyzing suture placement (Deflection), detecting tears in the poi material/tissue (Tears), and the time taken to perform the exercise (Time). The algorithm for scoring used a sigmoid function, and the coefficients were adjusted so that the scores of a sample of 20 cases ranged between 20 and 100 points.
The e-Suture prototype was completed. The e-Suture-derived ranking for 20 poi after training was significantly correlated with the mean of the rankings evaluated by 9 experts (correlation coefficient: 0.728; p = 0.000). We also tested which items the experts rated as the most important. The overall ratings obtained from the experts correlated with the e-Suture accuracy scoring results with a correlation coefficient of 0.836 (p = 0.000) for Accuracy, 0.31 (p = 0.173) for Deflection, and 0.518 (p = 0.019) for Tear.
The e-Suture application can easily and accurately quantify and evaluate the suturing skills of novie surgeons. Further studies should improve the accuracy of data to be analyzed by collecting more surgical data and applying it to other surgical techniques.</description><identifier>ISSN: 1931-7204</identifier><identifier>EISSN: 1878-7452</identifier><identifier>DOI: 10.1016/j.jsurg.2021.12.012</identifier><identifier>PMID: 35065893</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>algorithm ; Clinical Competence ; Humans ; quantification ; Smartphone ; Surgeons - education ; surgical education ; surgical simulation ; Suture Techniques - education ; Sutures ; validation</subject><ispartof>Journal of surgical education, 2022-05, Vol.79 (3), p.802-808</ispartof><rights>2021 Association of Program Directors in Surgery</rights><rights>Copyright © 2021 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c470t-119b000e34a20ac1320407f4a5feea809352d3166aca724506df882067cc19fb3</citedby><cites>FETCH-LOGICAL-c470t-119b000e34a20ac1320407f4a5feea809352d3166aca724506df882067cc19fb3</cites><orcidid>0000-0001-9982-3688 ; 0000-0003-0298-4261</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35065893$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Yamada, Toshiyuki</creatorcontrib><creatorcontrib>Suda, Hisao</creatorcontrib><creatorcontrib>Yoshitake, Akihiro</creatorcontrib><creatorcontrib>Shimizu, Hideyuki</creatorcontrib><title>Development of an Automated Smartphone-Based Suture Evaluation System</title><title>Journal of surgical education</title><addtitle>J Surg Educ</addtitle><description>Quantification of skill level in surgical training is necessary for effective skill development. In this study, we report the development of a smartphone application that automatically and objectively evaluates training in stitching goldfish scoop poi, a fragile material currently used for practice by young surgeons in Japan.
The application, named “e-Suture,” enables the automatic evaluation of surgical technique quality by evaluating the gap between the mark printed on the poi and the insertion/extraction point of the needle (Accuracy), analyzing suture placement (Deflection), detecting tears in the poi material/tissue (Tears), and the time taken to perform the exercise (Time). The algorithm for scoring used a sigmoid function, and the coefficients were adjusted so that the scores of a sample of 20 cases ranged between 20 and 100 points.
The e-Suture prototype was completed. The e-Suture-derived ranking for 20 poi after training was significantly correlated with the mean of the rankings evaluated by 9 experts (correlation coefficient: 0.728; p = 0.000). We also tested which items the experts rated as the most important. The overall ratings obtained from the experts correlated with the e-Suture accuracy scoring results with a correlation coefficient of 0.836 (p = 0.000) for Accuracy, 0.31 (p = 0.173) for Deflection, and 0.518 (p = 0.019) for Tear.
The e-Suture application can easily and accurately quantify and evaluate the suturing skills of novie surgeons. Further studies should improve the accuracy of data to be analyzed by collecting more surgical data and applying it to other surgical techniques.</description><subject>algorithm</subject><subject>Clinical Competence</subject><subject>Humans</subject><subject>quantification</subject><subject>Smartphone</subject><subject>Surgeons - education</subject><subject>surgical education</subject><subject>surgical simulation</subject><subject>Suture Techniques - education</subject><subject>Sutures</subject><subject>validation</subject><issn>1931-7204</issn><issn>1878-7452</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNp9kMtOwzAQRS0EolD4AiSUJZuE8SOvBYtSykOqxKKwtlxnAqmSuNhOpf49Li0sWc1odGfunUPIFYWEAs1uV8nKDfYjYcBoQlkClB2RM1rkRZyLlB2HvuQ0zhmIETl3bgWQipKVp2TEU8jSouRnZPaAG2zNusPeR6aOVB9NBm865bGKFp2yfv1peozvldsNBj9YjGYb1Q7KN6aPFlvnsbsgJ7VqHV4e6pi8P87eps_x_PXpZTqZx1rk4GNKyyUAIBeKgdKUh2iQ10KlNaIqoOQpqzjNMqVVzkQIWdVFwSDLtaZlveRjcrO_u7bma0DnZdc4jW2rejSDkyxjTORpKniQ8r1UW-OcxVqubRP-2UoKcsdPruQPP7njJymTgV_Yuj4YDMsOq7-dX2BBcLcXYHhz06CVTjfYa6wai9rLyjT_GnwDXjCBcw</recordid><startdate>202205</startdate><enddate>202205</enddate><creator>Yamada, Toshiyuki</creator><creator>Suda, Hisao</creator><creator>Yoshitake, Akihiro</creator><creator>Shimizu, Hideyuki</creator><general>Elsevier Inc</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-9982-3688</orcidid><orcidid>https://orcid.org/0000-0003-0298-4261</orcidid></search><sort><creationdate>202205</creationdate><title>Development of an Automated Smartphone-Based Suture Evaluation System</title><author>Yamada, Toshiyuki ; Suda, Hisao ; Yoshitake, Akihiro ; Shimizu, Hideyuki</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c470t-119b000e34a20ac1320407f4a5feea809352d3166aca724506df882067cc19fb3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>algorithm</topic><topic>Clinical Competence</topic><topic>Humans</topic><topic>quantification</topic><topic>Smartphone</topic><topic>Surgeons - education</topic><topic>surgical education</topic><topic>surgical simulation</topic><topic>Suture Techniques - education</topic><topic>Sutures</topic><topic>validation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yamada, Toshiyuki</creatorcontrib><creatorcontrib>Suda, Hisao</creatorcontrib><creatorcontrib>Yoshitake, Akihiro</creatorcontrib><creatorcontrib>Shimizu, Hideyuki</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of surgical education</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yamada, Toshiyuki</au><au>Suda, Hisao</au><au>Yoshitake, Akihiro</au><au>Shimizu, Hideyuki</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Development of an Automated Smartphone-Based Suture Evaluation System</atitle><jtitle>Journal of surgical education</jtitle><addtitle>J Surg Educ</addtitle><date>2022-05</date><risdate>2022</risdate><volume>79</volume><issue>3</issue><spage>802</spage><epage>808</epage><pages>802-808</pages><issn>1931-7204</issn><eissn>1878-7452</eissn><abstract>Quantification of skill level in surgical training is necessary for effective skill development. In this study, we report the development of a smartphone application that automatically and objectively evaluates training in stitching goldfish scoop poi, a fragile material currently used for practice by young surgeons in Japan.
The application, named “e-Suture,” enables the automatic evaluation of surgical technique quality by evaluating the gap between the mark printed on the poi and the insertion/extraction point of the needle (Accuracy), analyzing suture placement (Deflection), detecting tears in the poi material/tissue (Tears), and the time taken to perform the exercise (Time). The algorithm for scoring used a sigmoid function, and the coefficients were adjusted so that the scores of a sample of 20 cases ranged between 20 and 100 points.
The e-Suture prototype was completed. The e-Suture-derived ranking for 20 poi after training was significantly correlated with the mean of the rankings evaluated by 9 experts (correlation coefficient: 0.728; p = 0.000). We also tested which items the experts rated as the most important. The overall ratings obtained from the experts correlated with the e-Suture accuracy scoring results with a correlation coefficient of 0.836 (p = 0.000) for Accuracy, 0.31 (p = 0.173) for Deflection, and 0.518 (p = 0.019) for Tear.
The e-Suture application can easily and accurately quantify and evaluate the suturing skills of novie surgeons. Further studies should improve the accuracy of data to be analyzed by collecting more surgical data and applying it to other surgical techniques.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>35065893</pmid><doi>10.1016/j.jsurg.2021.12.012</doi><tpages>7</tpages><orcidid>https://orcid.org/0000-0001-9982-3688</orcidid><orcidid>https://orcid.org/0000-0003-0298-4261</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | algorithm Clinical Competence Humans quantification Smartphone Surgeons - education surgical education surgical simulation Suture Techniques - education Sutures validation |
title | Development of an Automated Smartphone-Based Suture Evaluation System |
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