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Decomposition and analysis of laparoscopic suturing task using tool-motion analysis (TMA): improving the objective assessment
Purpose The laparoscopic suturing task is a complex procedure that requires objective assessment of surgical skills. Analysis of laparoscopic suturing task components was performed to improve current objective assessment tools. Methods Twelve subjects participated in this study as three groups of fo...
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Published in: | International journal for computer assisted radiology and surgery 2012-03, Vol.7 (2), p.305-313 |
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container_title | International journal for computer assisted radiology and surgery |
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creator | Pagador, J. B. Sánchez-Margallo, F. M. Sánchez-Peralta, L. F. Sánchez-Margallo, J. A. Moyano-Cuevas, J. L. Enciso-Sanz, S. Usón-Gargallo, J. Moreno, J. |
description | Purpose
The laparoscopic suturing task is a complex procedure that requires objective assessment of surgical skills. Analysis of laparoscopic suturing task components was performed to improve current objective assessment tools.
Methods
Twelve subjects participated in this study as three groups of four surgeons (novices, intermediates and experts). A box-trainer and organic tissue were used to perform the experiment while tool movements were recorded with the augmented reality haptic system. All subjects were right-handed and developed a surgeon’s knot. The laparoscopic suturing procedure was decomposed into four subtasks. Different objective metrics were applied during tool-motion analysis (TMA). Statistical analysis was performed, and results from three groups were compared using the Jonckheere–Terpstra test, considering significant differences when
P
≤ 0.05.
Results
Several first, second and fourth subtask metrics had significant differences between the three groups. Subtasks 1 and 2 had more significant differences in metrics than subtask 4. Almost all metrics showed superior task executions accomplished by experts (lower time, total path length and number of movements) compared with intermediates and novices.
Conclusion
The most important subtasks during suture learning process are needle puncture and first knot. The TMA could be a useful objective assessment tool to discriminate surgical experience and could be used in the future to measure and certify surgical proficiency. |
doi_str_mv | 10.1007/s11548-011-0650-9 |
format | article |
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The laparoscopic suturing task is a complex procedure that requires objective assessment of surgical skills. Analysis of laparoscopic suturing task components was performed to improve current objective assessment tools.
Methods
Twelve subjects participated in this study as three groups of four surgeons (novices, intermediates and experts). A box-trainer and organic tissue were used to perform the experiment while tool movements were recorded with the augmented reality haptic system. All subjects were right-handed and developed a surgeon’s knot. The laparoscopic suturing procedure was decomposed into four subtasks. Different objective metrics were applied during tool-motion analysis (TMA). Statistical analysis was performed, and results from three groups were compared using the Jonckheere–Terpstra test, considering significant differences when
P
≤ 0.05.
Results
Several first, second and fourth subtask metrics had significant differences between the three groups. Subtasks 1 and 2 had more significant differences in metrics than subtask 4. Almost all metrics showed superior task executions accomplished by experts (lower time, total path length and number of movements) compared with intermediates and novices.
Conclusion
The most important subtasks during suture learning process are needle puncture and first knot. The TMA could be a useful objective assessment tool to discriminate surgical experience and could be used in the future to measure and certify surgical proficiency.</description><identifier>ISSN: 1861-6410</identifier><identifier>EISSN: 1861-6429</identifier><identifier>DOI: 10.1007/s11548-011-0650-9</identifier><identifier>PMID: 21842396</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer-Verlag</publisher><subject>Clinical Competence ; Computer Imaging ; Computer Science ; Computer-Assisted Instruction ; Female ; Health Informatics ; Humans ; Imaging ; Laparoscopy - methods ; Male ; Medicine ; Medicine & Public Health ; Original Article ; Pattern Recognition and Graphics ; Radiology ; Surgery ; Suture Techniques ; Task Performance and Analysis ; Tensile Strength ; Time Factors ; Vision</subject><ispartof>International journal for computer assisted radiology and surgery, 2012-03, Vol.7 (2), p.305-313</ispartof><rights>CARS 2011</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c409t-e3738ff2b18e4bae301e10154d28258a104506e42f28eb36054de95ad42aadd13</citedby><cites>FETCH-LOGICAL-c409t-e3738ff2b18e4bae301e10154d28258a104506e42f28eb36054de95ad42aadd13</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27922,27923</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/21842396$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Pagador, J. B.</creatorcontrib><creatorcontrib>Sánchez-Margallo, F. M.</creatorcontrib><creatorcontrib>Sánchez-Peralta, L. F.</creatorcontrib><creatorcontrib>Sánchez-Margallo, J. A.</creatorcontrib><creatorcontrib>Moyano-Cuevas, J. L.</creatorcontrib><creatorcontrib>Enciso-Sanz, S.</creatorcontrib><creatorcontrib>Usón-Gargallo, J.</creatorcontrib><creatorcontrib>Moreno, J.</creatorcontrib><title>Decomposition and analysis of laparoscopic suturing task using tool-motion analysis (TMA): improving the objective assessment</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
The laparoscopic suturing task is a complex procedure that requires objective assessment of surgical skills. Analysis of laparoscopic suturing task components was performed to improve current objective assessment tools.
Methods
Twelve subjects participated in this study as three groups of four surgeons (novices, intermediates and experts). A box-trainer and organic tissue were used to perform the experiment while tool movements were recorded with the augmented reality haptic system. All subjects were right-handed and developed a surgeon’s knot. The laparoscopic suturing procedure was decomposed into four subtasks. Different objective metrics were applied during tool-motion analysis (TMA). Statistical analysis was performed, and results from three groups were compared using the Jonckheere–Terpstra test, considering significant differences when
P
≤ 0.05.
Results
Several first, second and fourth subtask metrics had significant differences between the three groups. Subtasks 1 and 2 had more significant differences in metrics than subtask 4. Almost all metrics showed superior task executions accomplished by experts (lower time, total path length and number of movements) compared with intermediates and novices.
Conclusion
The most important subtasks during suture learning process are needle puncture and first knot. The TMA could be a useful objective assessment tool to discriminate surgical experience and could be used in the future to measure and certify surgical proficiency.</description><subject>Clinical Competence</subject><subject>Computer Imaging</subject><subject>Computer Science</subject><subject>Computer-Assisted Instruction</subject><subject>Female</subject><subject>Health Informatics</subject><subject>Humans</subject><subject>Imaging</subject><subject>Laparoscopy - methods</subject><subject>Male</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Original Article</subject><subject>Pattern Recognition and Graphics</subject><subject>Radiology</subject><subject>Surgery</subject><subject>Suture Techniques</subject><subject>Task Performance and Analysis</subject><subject>Tensile Strength</subject><subject>Time Factors</subject><subject>Vision</subject><issn>1861-6410</issn><issn>1861-6429</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><recordid>eNp9kDtPxDAQhC0E4v0DaJA7oAh4ncTn0J14S4dooLacZAM-kjhkE6Qr-O_4uIOSYrUreWbk-Rg7AnEOQkwuCCBNdCQAIqFSEWUbbBe0gkglMtv8u0HssD2iuRBJOonTbbYjQScyztQu-7rGwjedJzc433LblmFsvSBH3Fe8tp3tPRW-cwWncRh7177ywdI7H-nn9L6OGr82r42nz4_Ts0vumq73nz-qN-Q-n2MxuE_klgiJGmyHA7ZV2ZrwcL332cvtzfPVfTR7unu4ms6iIhHZEGE8iXVVyRw0JrnFWACCCN1LqWWqLYRiQmEiK6kxj5UIL5iltkyktWUJ8T47WeWGD32MSINpHBVY17ZFP5LJpIJUSaWDElbKItSmHivT9a6x_cKAMEvoZgXdBOhmCd1kwXO8Th_zBss_xy_lIJArAXVLftibuR_7QIv-Sf0G9KyO6w</recordid><startdate>20120301</startdate><enddate>20120301</enddate><creator>Pagador, J. B.</creator><creator>Sánchez-Margallo, F. M.</creator><creator>Sánchez-Peralta, L. F.</creator><creator>Sánchez-Margallo, J. A.</creator><creator>Moyano-Cuevas, J. L.</creator><creator>Enciso-Sanz, S.</creator><creator>Usón-Gargallo, J.</creator><creator>Moreno, J.</creator><general>Springer-Verlag</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></search><sort><creationdate>20120301</creationdate><title>Decomposition and analysis of laparoscopic suturing task using tool-motion analysis (TMA): improving the objective assessment</title><author>Pagador, J. B. ; Sánchez-Margallo, F. M. ; Sánchez-Peralta, L. F. ; Sánchez-Margallo, J. A. ; Moyano-Cuevas, J. L. ; Enciso-Sanz, S. ; Usón-Gargallo, J. ; Moreno, J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c409t-e3738ff2b18e4bae301e10154d28258a104506e42f28eb36054de95ad42aadd13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Clinical Competence</topic><topic>Computer Imaging</topic><topic>Computer Science</topic><topic>Computer-Assisted Instruction</topic><topic>Female</topic><topic>Health Informatics</topic><topic>Humans</topic><topic>Imaging</topic><topic>Laparoscopy - methods</topic><topic>Male</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Original Article</topic><topic>Pattern Recognition and Graphics</topic><topic>Radiology</topic><topic>Surgery</topic><topic>Suture Techniques</topic><topic>Task Performance and Analysis</topic><topic>Tensile Strength</topic><topic>Time Factors</topic><topic>Vision</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Pagador, J. B.</creatorcontrib><creatorcontrib>Sánchez-Margallo, F. M.</creatorcontrib><creatorcontrib>Sánchez-Peralta, L. F.</creatorcontrib><creatorcontrib>Sánchez-Margallo, J. A.</creatorcontrib><creatorcontrib>Moyano-Cuevas, J. L.</creatorcontrib><creatorcontrib>Enciso-Sanz, S.</creatorcontrib><creatorcontrib>Usón-Gargallo, J.</creatorcontrib><creatorcontrib>Moreno, J.</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>International journal for computer assisted radiology and surgery</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pagador, J. B.</au><au>Sánchez-Margallo, F. M.</au><au>Sánchez-Peralta, L. F.</au><au>Sánchez-Margallo, J. A.</au><au>Moyano-Cuevas, J. L.</au><au>Enciso-Sanz, S.</au><au>Usón-Gargallo, J.</au><au>Moreno, J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Decomposition and analysis of laparoscopic suturing task using tool-motion analysis (TMA): improving the objective assessment</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>2012-03-01</date><risdate>2012</risdate><volume>7</volume><issue>2</issue><spage>305</spage><epage>313</epage><pages>305-313</pages><issn>1861-6410</issn><eissn>1861-6429</eissn><abstract>Purpose
The laparoscopic suturing task is a complex procedure that requires objective assessment of surgical skills. Analysis of laparoscopic suturing task components was performed to improve current objective assessment tools.
Methods
Twelve subjects participated in this study as three groups of four surgeons (novices, intermediates and experts). A box-trainer and organic tissue were used to perform the experiment while tool movements were recorded with the augmented reality haptic system. All subjects were right-handed and developed a surgeon’s knot. The laparoscopic suturing procedure was decomposed into four subtasks. Different objective metrics were applied during tool-motion analysis (TMA). Statistical analysis was performed, and results from three groups were compared using the Jonckheere–Terpstra test, considering significant differences when
P
≤ 0.05.
Results
Several first, second and fourth subtask metrics had significant differences between the three groups. Subtasks 1 and 2 had more significant differences in metrics than subtask 4. Almost all metrics showed superior task executions accomplished by experts (lower time, total path length and number of movements) compared with intermediates and novices.
Conclusion
The most important subtasks during suture learning process are needle puncture and first knot. The TMA could be a useful objective assessment tool to discriminate surgical experience and could be used in the future to measure and certify surgical proficiency.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer-Verlag</pub><pmid>21842396</pmid><doi>10.1007/s11548-011-0650-9</doi><tpages>9</tpages></addata></record> |
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subjects | Clinical Competence Computer Imaging Computer Science Computer-Assisted Instruction Female Health Informatics Humans Imaging Laparoscopy - methods Male Medicine Medicine & Public Health Original Article Pattern Recognition and Graphics Radiology Surgery Suture Techniques Task Performance and Analysis Tensile Strength Time Factors Vision |
title | Decomposition and analysis of laparoscopic suturing task using tool-motion analysis (TMA): improving the objective assessment |
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