EndoTrainer: a novel hybrid training platform for endoscopic surgery
Purpose Endoscopy implies high demanding procedures, and their practice requires structured formation curricula supported by adequate training platforms. Physical platforms are the most standardised solution for surgical training, but over the last few years, virtual platforms have been progressivel...
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Veröffentlicht in: | International journal for computer assisted radiology and surgery 2023-05, Vol.18 (5), p.899-908 |
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container_title | International journal for computer assisted radiology and surgery |
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creator | Hernansanz, Albert Rovira, Ramon Basomba, Joan Comas, Roger Casals, Alícia |
description | Purpose
Endoscopy implies high demanding procedures, and their practice requires structured formation curricula supported by adequate training platforms. Physical platforms are the most standardised solution for surgical training, but over the last few years, virtual platforms have been progressively introduced. This research work presents a new hybrid, physic-virtual, endoscopic training platform that exploits the benefits of the two kind of platforms combining realistic tools and phantoms together with the capacity of measuring all relevant parameters along the execution of the exercises and of providing an objective assessment performance.
Methods
The developed platform, EndoTrainer, has been designed to train and assess surgical skills in hysteroscopy and cystoscopy following a structured curricula. The initial development and validation is focused on hysteroscopic exercises proposed in the Gynaecological Endoscopic Surgical Education and Assessment (GESEA) Certification Programme from The Academy and European Society for Gynaecological Endoscopy (ESGE) and analyses the obtained results of an extensive study with 80 gynaecologists executing 30 trials of the standard 30 degree endoscope navigation exercise.
Results
The experiments demonstrate the benefits of the presented hybrid platform. Multi-variable statistical analysis points out that all subjects have obtained statistically significant improvement in all relevant parameters: shorter and safer trajectories, improved 30-degree endoscope navigation, accurate positioning over the targets and reduction of the execution time.
Conclusion
This paper presents a new hybrid approach for training, and evaluating whether it provides an objectivable improvement of camera navigation endoscopic basic skills. The obtained results demonstrate the initial hypothesis: all subjects have improved their camera handling and navigation skills. |
doi_str_mv | 10.1007/s11548-023-02837-x |
format | Article |
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Endoscopy implies high demanding procedures, and their practice requires structured formation curricula supported by adequate training platforms. Physical platforms are the most standardised solution for surgical training, but over the last few years, virtual platforms have been progressively introduced. This research work presents a new hybrid, physic-virtual, endoscopic training platform that exploits the benefits of the two kind of platforms combining realistic tools and phantoms together with the capacity of measuring all relevant parameters along the execution of the exercises and of providing an objective assessment performance.
Methods
The developed platform, EndoTrainer, has been designed to train and assess surgical skills in hysteroscopy and cystoscopy following a structured curricula. The initial development and validation is focused on hysteroscopic exercises proposed in the Gynaecological Endoscopic Surgical Education and Assessment (GESEA) Certification Programme from The Academy and European Society for Gynaecological Endoscopy (ESGE) and analyses the obtained results of an extensive study with 80 gynaecologists executing 30 trials of the standard 30 degree endoscope navigation exercise.
Results
The experiments demonstrate the benefits of the presented hybrid platform. Multi-variable statistical analysis points out that all subjects have obtained statistically significant improvement in all relevant parameters: shorter and safer trajectories, improved 30-degree endoscope navigation, accurate positioning over the targets and reduction of the execution time.
Conclusion
This paper presents a new hybrid approach for training, and evaluating whether it provides an objectivable improvement of camera navigation endoscopic basic skills. The obtained results demonstrate the initial hypothesis: all subjects have improved their camera handling and navigation skills.</description><identifier>ISSN: 1861-6429</identifier><identifier>ISSN: 1861-6410</identifier><identifier>EISSN: 1861-6429</identifier><identifier>DOI: 10.1007/s11548-023-02837-x</identifier><identifier>PMID: 36781742</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Cameras ; Clinical Competence ; Computer Imaging ; Computer Science ; Curricula ; Curriculum ; Endoscopes ; Endoscopy ; Endoscopy - education ; Endoscopy, Gastrointestinal ; Female ; Gynecologic Surgical Procedures ; Gynecology ; Health Informatics ; Humans ; Imaging ; Medicine ; Medicine & Public Health ; Original ; Original Article ; Parameters ; Pattern Recognition and Graphics ; Platforms ; Radiology ; Skills ; Statistical analysis ; Surgery ; Training ; Vision</subject><ispartof>International journal for computer assisted radiology and surgery, 2023-05, Vol.18 (5), p.899-908</ispartof><rights>The Author(s) 2023</rights><rights>2023. The Author(s).</rights><rights>The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c475t-563ff77c8af4b47786f7177fe727eca3ed0eda835daf111ca8838ed6b553d77a3</citedby><cites>FETCH-LOGICAL-c475t-563ff77c8af4b47786f7177fe727eca3ed0eda835daf111ca8838ed6b553d77a3</cites><orcidid>0000-0002-7969-5401</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11548-023-02837-x$$EPDF$$P50$$Gspringer$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11548-023-02837-x$$EHTML$$P50$$Gspringer$$Hfree_for_read</linktohtml><link.rule.ids>230,314,777,781,882,27905,27906,41469,42538,51300</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36781742$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Hernansanz, Albert</creatorcontrib><creatorcontrib>Rovira, Ramon</creatorcontrib><creatorcontrib>Basomba, Joan</creatorcontrib><creatorcontrib>Comas, Roger</creatorcontrib><creatorcontrib>Casals, Alícia</creatorcontrib><title>EndoTrainer: a novel hybrid training platform for endoscopic surgery</title><title>International journal for computer assisted radiology and surgery</title><addtitle>Int J CARS</addtitle><addtitle>Int J Comput Assist Radiol Surg</addtitle><description>Purpose
Endoscopy implies high demanding procedures, and their practice requires structured formation curricula supported by adequate training platforms. Physical platforms are the most standardised solution for surgical training, but over the last few years, virtual platforms have been progressively introduced. This research work presents a new hybrid, physic-virtual, endoscopic training platform that exploits the benefits of the two kind of platforms combining realistic tools and phantoms together with the capacity of measuring all relevant parameters along the execution of the exercises and of providing an objective assessment performance.
Methods
The developed platform, EndoTrainer, has been designed to train and assess surgical skills in hysteroscopy and cystoscopy following a structured curricula. The initial development and validation is focused on hysteroscopic exercises proposed in the Gynaecological Endoscopic Surgical Education and Assessment (GESEA) Certification Programme from The Academy and European Society for Gynaecological Endoscopy (ESGE) and analyses the obtained results of an extensive study with 80 gynaecologists executing 30 trials of the standard 30 degree endoscope navigation exercise.
Results
The experiments demonstrate the benefits of the presented hybrid platform. Multi-variable statistical analysis points out that all subjects have obtained statistically significant improvement in all relevant parameters: shorter and safer trajectories, improved 30-degree endoscope navigation, accurate positioning over the targets and reduction of the execution time.
Conclusion
This paper presents a new hybrid approach for training, and evaluating whether it provides an objectivable improvement of camera navigation endoscopic basic skills. The obtained results demonstrate the initial hypothesis: all subjects have improved their camera handling and navigation skills.</description><subject>Cameras</subject><subject>Clinical Competence</subject><subject>Computer Imaging</subject><subject>Computer Science</subject><subject>Curricula</subject><subject>Curriculum</subject><subject>Endoscopes</subject><subject>Endoscopy</subject><subject>Endoscopy - education</subject><subject>Endoscopy, Gastrointestinal</subject><subject>Female</subject><subject>Gynecologic Surgical Procedures</subject><subject>Gynecology</subject><subject>Health Informatics</subject><subject>Humans</subject><subject>Imaging</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Original</subject><subject>Original Article</subject><subject>Parameters</subject><subject>Pattern Recognition and Graphics</subject><subject>Platforms</subject><subject>Radiology</subject><subject>Skills</subject><subject>Statistical analysis</subject><subject>Surgery</subject><subject>Training</subject><subject>Vision</subject><issn>1861-6429</issn><issn>1861-6410</issn><issn>1861-6429</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>EIF</sourceid><recordid>eNp9kT1PHDEQhi2UKBDIH6BAK6WhWeLx1_hoECIEIiHRQG35vPaxaM8-7FvE_XtMju8ihe2R55nXM34J2QV6AJTirwIghW4p43Vpju3DBtkCraBVgk2-vIs3yfdSbikVErn8Rja5Qg0o2Bb5fRq7dJVtH30-bGwT070fmpvVNPdds3y67-OsWQx2GVKeN3VrfK0oLi1615Qxz3xe7ZCvwQ7F_3g-t8n1n9Ork_P24vLs78nxResEymUrFQ8B0WkbxFQgahUQEINHht5Z7jvqO6u57GwAAGe15tp3aiol7xAt3yZHa93FOJ37zvlYOxzMIvdzm1cm2d58zMT-xszSvQEKwNlEVYX9Z4Wc7kZflmbeF-eHwUafxmIYopIgNYiK_vyE3qYxxzqfYZqyCVdC6UqxNeVyKiX78NoNUPPkklm7ZKpL5p9L5qEW7b2f47XkxZYK8DVQairWL357-z-yjyeZnyI</recordid><startdate>20230501</startdate><enddate>20230501</enddate><creator>Hernansanz, Albert</creator><creator>Rovira, Ramon</creator><creator>Basomba, Joan</creator><creator>Comas, Roger</creator><creator>Casals, Alícia</creator><general>Springer International Publishing</general><general>Springer Nature B.V</general><scope>C6C</scope><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><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-7969-5401</orcidid></search><sort><creationdate>20230501</creationdate><title>EndoTrainer: a novel hybrid training platform for endoscopic surgery</title><author>Hernansanz, Albert ; Rovira, Ramon ; Basomba, Joan ; Comas, Roger ; Casals, Alícia</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c475t-563ff77c8af4b47786f7177fe727eca3ed0eda835daf111ca8838ed6b553d77a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Cameras</topic><topic>Clinical Competence</topic><topic>Computer Imaging</topic><topic>Computer Science</topic><topic>Curricula</topic><topic>Curriculum</topic><topic>Endoscopes</topic><topic>Endoscopy</topic><topic>Endoscopy - education</topic><topic>Endoscopy, Gastrointestinal</topic><topic>Female</topic><topic>Gynecologic Surgical Procedures</topic><topic>Gynecology</topic><topic>Health Informatics</topic><topic>Humans</topic><topic>Imaging</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Original</topic><topic>Original Article</topic><topic>Parameters</topic><topic>Pattern Recognition and Graphics</topic><topic>Platforms</topic><topic>Radiology</topic><topic>Skills</topic><topic>Statistical analysis</topic><topic>Surgery</topic><topic>Training</topic><topic>Vision</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hernansanz, Albert</creatorcontrib><creatorcontrib>Rovira, Ramon</creatorcontrib><creatorcontrib>Basomba, Joan</creatorcontrib><creatorcontrib>Comas, Roger</creatorcontrib><creatorcontrib>Casals, Alícia</creatorcontrib><collection>Springer Open Access</collection><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><collection>PubMed Central (Full Participant titles)</collection><jtitle>International journal for computer assisted radiology and surgery</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hernansanz, Albert</au><au>Rovira, Ramon</au><au>Basomba, Joan</au><au>Comas, Roger</au><au>Casals, Alícia</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>EndoTrainer: a novel hybrid training platform for endoscopic surgery</atitle><jtitle>International journal for computer assisted radiology and surgery</jtitle><stitle>Int J CARS</stitle><addtitle>Int J Comput Assist Radiol Surg</addtitle><date>2023-05-01</date><risdate>2023</risdate><volume>18</volume><issue>5</issue><spage>899</spage><epage>908</epage><pages>899-908</pages><issn>1861-6429</issn><issn>1861-6410</issn><eissn>1861-6429</eissn><abstract>Purpose
Endoscopy implies high demanding procedures, and their practice requires structured formation curricula supported by adequate training platforms. Physical platforms are the most standardised solution for surgical training, but over the last few years, virtual platforms have been progressively introduced. This research work presents a new hybrid, physic-virtual, endoscopic training platform that exploits the benefits of the two kind of platforms combining realistic tools and phantoms together with the capacity of measuring all relevant parameters along the execution of the exercises and of providing an objective assessment performance.
Methods
The developed platform, EndoTrainer, has been designed to train and assess surgical skills in hysteroscopy and cystoscopy following a structured curricula. The initial development and validation is focused on hysteroscopic exercises proposed in the Gynaecological Endoscopic Surgical Education and Assessment (GESEA) Certification Programme from The Academy and European Society for Gynaecological Endoscopy (ESGE) and analyses the obtained results of an extensive study with 80 gynaecologists executing 30 trials of the standard 30 degree endoscope navigation exercise.
Results
The experiments demonstrate the benefits of the presented hybrid platform. Multi-variable statistical analysis points out that all subjects have obtained statistically significant improvement in all relevant parameters: shorter and safer trajectories, improved 30-degree endoscope navigation, accurate positioning over the targets and reduction of the execution time.
Conclusion
This paper presents a new hybrid approach for training, and evaluating whether it provides an objectivable improvement of camera navigation endoscopic basic skills. The obtained results demonstrate the initial hypothesis: all subjects have improved their camera handling and navigation skills.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><pmid>36781742</pmid><doi>10.1007/s11548-023-02837-x</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0002-7969-5401</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Cameras Clinical Competence Computer Imaging Computer Science Curricula Curriculum Endoscopes Endoscopy Endoscopy - education Endoscopy, Gastrointestinal Female Gynecologic Surgical Procedures Gynecology Health Informatics Humans Imaging Medicine Medicine & Public Health Original Original Article Parameters Pattern Recognition and Graphics Platforms Radiology Skills Statistical analysis Surgery Training Vision |
title | EndoTrainer: a novel hybrid training platform for endoscopic surgery |
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