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Editorial by Reza Mehrazin and Shirin Razdan on p. 388–389 of this issue: Can preoperative planning using IRIS™ three-dimensional anatomical virtual models predict operative findings during robot-assisted partial nephrectomy?

OBJECTIVE: To evaluate the predictive validity of IRIS™ (Intuitive Surgical®, Sunnyvale, CA, USA) as a planning tool for robot-assisted partial nephrectomy (RAPN) by assessing the degree of overlap with intraoperative execution. METHODS: Thirty-one patients scheduled for RAPN by four experienced uro...

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Autores principales: Ghazi, Ahmed, Sharma, Nitin, Ahmed Radwan, Rashid, Hani, Osinski, Thomas, Frye, Thomas, Tabayoyong, William, Bloom, Jonathan, Joseph, Jean
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Second Military Medical University 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10659964/
https://www.ncbi.nlm.nih.gov/pubmed/38024437
http://dx.doi.org/10.1016/j.ajur.2022.12.003
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author Ghazi, Ahmed
Sharma, Nitin
Ahmed Radwan
Rashid, Hani
Osinski, Thomas
Frye, Thomas
Tabayoyong, William
Bloom, Jonathan
Joseph, Jean
author_facet Ghazi, Ahmed
Sharma, Nitin
Ahmed Radwan
Rashid, Hani
Osinski, Thomas
Frye, Thomas
Tabayoyong, William
Bloom, Jonathan
Joseph, Jean
author_sort Ghazi, Ahmed
collection PubMed
description OBJECTIVE: To evaluate the predictive validity of IRIS™ (Intuitive Surgical®, Sunnyvale, CA, USA) as a planning tool for robot-assisted partial nephrectomy (RAPN) by assessing the degree of overlap with intraoperative execution. METHODS: Thirty-one patients scheduled for RAPN by four experienced urologists were enrolled in a prospective study. Prior to surgery, urologists reviewed the IRIS™ three-dimensional model on an iphone Operating System (iOS) app and completed a questionnaire outlining their surgical plan including surgical approach, and ischemia technique as well as confidence in executing this plan. Postoperatively, questionnaires assessing the procedural approach, clinical utility, efficiency, and effectiveness of IRIS™ were completed. The degree of overlap between the preoperative and intraoperative questionnaires and between the planned approach and actual execution of the procedure was analyzed. Questionnaires were answered on a 5-point Likert scale and scores of 4 or greater were considered positive. RESULTS: Mean age was 65.1 years with a mean tumor size of 27.7 mm (interquartile range 17.5–44.0 mm). Hilar tumors consisted of 32.3%; 48.4% of patients had R.E.N.A.L. nephrometry scores of 7–9. On preoperative questionnaires, the surgeons reported that in 67.7% cases they were confident that they can perform the procedure successfully, and on intraoperative questionnaires, the surgeons reported that in 96.8% cases IRIS™ helped achieve good spatial sensation of the anatomy. There was a high degree of overlap between preoperative and intraoperative questionnaires for the surgical approach, interpreting anatomical details and clinical utility. When comparing plans for selective or off-clamp, the preoperative plan was executed in 90.0% of cases intraoperatively. CONCLUSION: A high degree of overlap between the preoperative surgical approach and intraoperative RAPN execution was found using IRIS™. This is the first study to evaluate the predictive accuracy of IRIS™ during RAPN by comparing preoperative plan and intraoperative execution.
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spelling pubmed-106599642023-02-04 Editorial by Reza Mehrazin and Shirin Razdan on p. 388–389 of this issue: Can preoperative planning using IRIS™ three-dimensional anatomical virtual models predict operative findings during robot-assisted partial nephrectomy? Ghazi, Ahmed Sharma, Nitin Ahmed Radwan Rashid, Hani Osinski, Thomas Frye, Thomas Tabayoyong, William Bloom, Jonathan Joseph, Jean Asian J Urol Original Article OBJECTIVE: To evaluate the predictive validity of IRIS™ (Intuitive Surgical®, Sunnyvale, CA, USA) as a planning tool for robot-assisted partial nephrectomy (RAPN) by assessing the degree of overlap with intraoperative execution. METHODS: Thirty-one patients scheduled for RAPN by four experienced urologists were enrolled in a prospective study. Prior to surgery, urologists reviewed the IRIS™ three-dimensional model on an iphone Operating System (iOS) app and completed a questionnaire outlining their surgical plan including surgical approach, and ischemia technique as well as confidence in executing this plan. Postoperatively, questionnaires assessing the procedural approach, clinical utility, efficiency, and effectiveness of IRIS™ were completed. The degree of overlap between the preoperative and intraoperative questionnaires and between the planned approach and actual execution of the procedure was analyzed. Questionnaires were answered on a 5-point Likert scale and scores of 4 or greater were considered positive. RESULTS: Mean age was 65.1 years with a mean tumor size of 27.7 mm (interquartile range 17.5–44.0 mm). Hilar tumors consisted of 32.3%; 48.4% of patients had R.E.N.A.L. nephrometry scores of 7–9. On preoperative questionnaires, the surgeons reported that in 67.7% cases they were confident that they can perform the procedure successfully, and on intraoperative questionnaires, the surgeons reported that in 96.8% cases IRIS™ helped achieve good spatial sensation of the anatomy. There was a high degree of overlap between preoperative and intraoperative questionnaires for the surgical approach, interpreting anatomical details and clinical utility. When comparing plans for selective or off-clamp, the preoperative plan was executed in 90.0% of cases intraoperatively. CONCLUSION: A high degree of overlap between the preoperative surgical approach and intraoperative RAPN execution was found using IRIS™. This is the first study to evaluate the predictive accuracy of IRIS™ during RAPN by comparing preoperative plan and intraoperative execution. Second Military Medical University 2023-10 2023-02-04 /pmc/articles/PMC10659964/ /pubmed/38024437 http://dx.doi.org/10.1016/j.ajur.2022.12.003 Text en © 2023 Editorial Office of Asian Journal of Urology. Production and hosting by Elsevier B.V. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Original Article
Ghazi, Ahmed
Sharma, Nitin
Ahmed Radwan
Rashid, Hani
Osinski, Thomas
Frye, Thomas
Tabayoyong, William
Bloom, Jonathan
Joseph, Jean
Editorial by Reza Mehrazin and Shirin Razdan on p. 388–389 of this issue: Can preoperative planning using IRIS™ three-dimensional anatomical virtual models predict operative findings during robot-assisted partial nephrectomy?
title Editorial by Reza Mehrazin and Shirin Razdan on p. 388–389 of this issue: Can preoperative planning using IRIS™ three-dimensional anatomical virtual models predict operative findings during robot-assisted partial nephrectomy?
title_full Editorial by Reza Mehrazin and Shirin Razdan on p. 388–389 of this issue: Can preoperative planning using IRIS™ three-dimensional anatomical virtual models predict operative findings during robot-assisted partial nephrectomy?
title_fullStr Editorial by Reza Mehrazin and Shirin Razdan on p. 388–389 of this issue: Can preoperative planning using IRIS™ three-dimensional anatomical virtual models predict operative findings during robot-assisted partial nephrectomy?
title_full_unstemmed Editorial by Reza Mehrazin and Shirin Razdan on p. 388–389 of this issue: Can preoperative planning using IRIS™ three-dimensional anatomical virtual models predict operative findings during robot-assisted partial nephrectomy?
title_short Editorial by Reza Mehrazin and Shirin Razdan on p. 388–389 of this issue: Can preoperative planning using IRIS™ three-dimensional anatomical virtual models predict operative findings during robot-assisted partial nephrectomy?
title_sort editorial by reza mehrazin and shirin razdan on p. 388–389 of this issue: can preoperative planning using iris™ three-dimensional anatomical virtual models predict operative findings during robot-assisted partial nephrectomy?
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10659964/
https://www.ncbi.nlm.nih.gov/pubmed/38024437
http://dx.doi.org/10.1016/j.ajur.2022.12.003
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