Three‐dimensional computed tomography‐based resection process map for robot‐assisted partial nephrectomy: propensity score matching of a single‐center retrospective study
Background and Objectives We aimed to examine the effect of preoperative three‐dimensional (3D) computed tomography (CT)‐based resection process map (RPM) imaging on the outcomes of robot‐assisted partial nephrectomy (RAPN). Methods We retrospectively analyzed 177 patients (RPM group, n = 92; non‐RP...
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creator | Okada, Atsushi Ohashi, Kazuya Hashimoto, Hiroya Ota, Yuya Sugino, Teruaki Unno, Rei Iwatsuki, Shoichiro Etani, Toshiki Taguchi, Kazumi Naiki, Taku Kurokawa, Satoshi Hamamoto, Shuzo Ando, Ryosuke Nakane, Akihiro Kawai, Noriyasu Tozawa, Keiichi Yasui, Takahiro |
description | Background and Objectives
We aimed to examine the effect of preoperative three‐dimensional (3D) computed tomography (CT)‐based resection process map (RPM) imaging on the outcomes of robot‐assisted partial nephrectomy (RAPN).
Methods
We retrospectively analyzed 177 patients (RPM group, n = 92; non‐RPM group, n = 85) who underwent this surgery between November 2012 and April 2022. Patient‐specific contrast‐enhanced CT images were used to construct an RPM, a 3D representation of the kidney showing the planned tumor resection and a 5 mm safety margin. Outcome analyses were performed using propensity score matching. The primary endpoint was the trifecta achievement rate.
Results
We extracted 90 cases. The trifecta achievement rate showed no significant differences between the RPM (73.3%) and non‐RPM groups (73.3%). However, the RPM group had fewer Grade 3 and higher complications (0.0% vs. 13.3%, p = 0.026). The da Vinci Xi (OR 3.38, p = 0.016) and tumor diameter (OR 0.95, p = 0.013) were independent factors affecting trifecta achievement in multivariate analysis. Using RPM imaging was associated with the absence of Grade 3 and higher perioperative complications (OR 5.33, p = 0.036) in univariate analysis.
Conclusions
Using preoperative 3D CT‐based RPM images before RAPN may not affect trifecta achievement, but may reduce serious complication occurrence by providing detailed information on tumor resection.
Key points
Although Plain three‐dimensional computed tomography (CT) images allow spatial recognition of the kidneys and arteries, they do not show the course of the ureters and the internal structure of the kidneys during the excretory phase.
Resection process maps provide dynamic images based on patient‐specific CT data that provide extensive tumor‐related information.
Using these maps may not affect trifecta achievement in robot‐assisted partial nephrectomy; nevertheless, they provide valuable information that may reduce the occurrence of serious complications. |
doi_str_mv | 10.1002/jso.27615 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2956683737</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2956683737</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3135-7c110966e3488ee2faee955a4c7885ce40f0274d9b04967e35248929885942be3</originalsourceid><addsrcrecordid>eNp1kUFu1TAQhi1ERR8PFlwAWWIDi7R24jgxu6oqLVWlLijryHEmfXlK4uBxQNlxhJ6FI3ESJrzCAgl5YWvmm3_G8zP2SooTKUR6ukd_khZa5k_YRgqjEyNM-ZRtKJcmqjDimD1H3AshjNHqGTvOSlWIPNcb9uNuFwB-fn9ougFG7Pxoe-78MM0RGh794O-DnXYLEbVFCgVAcJE4PgXvAJEPduKtDzz42kfiLGKHa_VkQ-xIboSJmjgSW96vVdPaKC4cnQ9A5dHtuvGe-5ZbjvTq13kcjBFIFGLwOK0tvwLHODfLC3bU2h7h5eO9ZZ8_XNydXyU3t5cfz89uEpfJLE8KJ9ddaMhUWQKkrQUweW6VK8oyd6BEK9JCNaYWyugCsjxVpUkNJY1Ka8i27O1Bl0b-MgPGaujQQd_bEfyMVWpyrcusoLNlb_5B934OtEqsMqEzaYySkqh3B8rRlzBAW02hG2xYKimq1ciKjKx-G0ns60fFuR6g-Uv-cY6A0wPwreth-b9Sdf3p9iD5C0Wvr-Q</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3063199411</pqid></control><display><type>article</type><title>Three‐dimensional computed tomography‐based resection process map for robot‐assisted partial nephrectomy: propensity score matching of a single‐center retrospective study</title><source>Wiley Journals</source><creator>Okada, Atsushi ; Ohashi, Kazuya ; Hashimoto, Hiroya ; Ota, Yuya ; Sugino, Teruaki ; Unno, Rei ; Iwatsuki, Shoichiro ; Etani, Toshiki ; Taguchi, Kazumi ; Naiki, Taku ; Kurokawa, Satoshi ; Hamamoto, Shuzo ; Ando, Ryosuke ; Nakane, Akihiro ; Kawai, Noriyasu ; Tozawa, Keiichi ; Yasui, Takahiro</creator><creatorcontrib>Okada, Atsushi ; Ohashi, Kazuya ; Hashimoto, Hiroya ; Ota, Yuya ; Sugino, Teruaki ; Unno, Rei ; Iwatsuki, Shoichiro ; Etani, Toshiki ; Taguchi, Kazumi ; Naiki, Taku ; Kurokawa, Satoshi ; Hamamoto, Shuzo ; Ando, Ryosuke ; Nakane, Akihiro ; Kawai, Noriyasu ; Tozawa, Keiichi ; Yasui, Takahiro</creatorcontrib><description>Background and Objectives
We aimed to examine the effect of preoperative three‐dimensional (3D) computed tomography (CT)‐based resection process map (RPM) imaging on the outcomes of robot‐assisted partial nephrectomy (RAPN).
Methods
We retrospectively analyzed 177 patients (RPM group, n = 92; non‐RPM group, n = 85) who underwent this surgery between November 2012 and April 2022. Patient‐specific contrast‐enhanced CT images were used to construct an RPM, a 3D representation of the kidney showing the planned tumor resection and a 5 mm safety margin. Outcome analyses were performed using propensity score matching. The primary endpoint was the trifecta achievement rate.
Results
We extracted 90 cases. The trifecta achievement rate showed no significant differences between the RPM (73.3%) and non‐RPM groups (73.3%). However, the RPM group had fewer Grade 3 and higher complications (0.0% vs. 13.3%, p = 0.026). The da Vinci Xi (OR 3.38, p = 0.016) and tumor diameter (OR 0.95, p = 0.013) were independent factors affecting trifecta achievement in multivariate analysis. Using RPM imaging was associated with the absence of Grade 3 and higher perioperative complications (OR 5.33, p = 0.036) in univariate analysis.
Conclusions
Using preoperative 3D CT‐based RPM images before RAPN may not affect trifecta achievement, but may reduce serious complication occurrence by providing detailed information on tumor resection.
Key points
Although Plain three‐dimensional computed tomography (CT) images allow spatial recognition of the kidneys and arteries, they do not show the course of the ureters and the internal structure of the kidneys during the excretory phase.
Resection process maps provide dynamic images based on patient‐specific CT data that provide extensive tumor‐related information.
Using these maps may not affect trifecta achievement in robot‐assisted partial nephrectomy; nevertheless, they provide valuable information that may reduce the occurrence of serious complications.</description><identifier>ISSN: 0022-4790</identifier><identifier>EISSN: 1096-9098</identifier><identifier>DOI: 10.1002/jso.27615</identifier><identifier>PMID: 38470556</identifier><language>eng</language><publisher>United States: Wiley Subscription Services, Inc</publisher><subject>computed X‐ray tomography ; Kidney cancer ; Kidneys ; nephrectomy ; renal cancer ; resection margin ; Robots ; robot‐assisted surgery ; Tomography</subject><ispartof>Journal of surgical oncology, 2024-06, Vol.129 (7), p.1311-1324</ispartof><rights>2024 Wiley Periodicals LLC.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c3135-7c110966e3488ee2faee955a4c7885ce40f0274d9b04967e35248929885942be3</cites><orcidid>0000-0002-7638-6048 ; 0000-0002-2257-3892 ; 0000-0003-2080-3794 ; 0009-0005-5265-2216</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fjso.27615$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fjso.27615$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1417,27924,27925,45574,45575</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38470556$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Okada, Atsushi</creatorcontrib><creatorcontrib>Ohashi, Kazuya</creatorcontrib><creatorcontrib>Hashimoto, Hiroya</creatorcontrib><creatorcontrib>Ota, Yuya</creatorcontrib><creatorcontrib>Sugino, Teruaki</creatorcontrib><creatorcontrib>Unno, Rei</creatorcontrib><creatorcontrib>Iwatsuki, Shoichiro</creatorcontrib><creatorcontrib>Etani, Toshiki</creatorcontrib><creatorcontrib>Taguchi, Kazumi</creatorcontrib><creatorcontrib>Naiki, Taku</creatorcontrib><creatorcontrib>Kurokawa, Satoshi</creatorcontrib><creatorcontrib>Hamamoto, Shuzo</creatorcontrib><creatorcontrib>Ando, Ryosuke</creatorcontrib><creatorcontrib>Nakane, Akihiro</creatorcontrib><creatorcontrib>Kawai, Noriyasu</creatorcontrib><creatorcontrib>Tozawa, Keiichi</creatorcontrib><creatorcontrib>Yasui, Takahiro</creatorcontrib><title>Three‐dimensional computed tomography‐based resection process map for robot‐assisted partial nephrectomy: propensity score matching of a single‐center retrospective study</title><title>Journal of surgical oncology</title><addtitle>J Surg Oncol</addtitle><description>Background and Objectives
We aimed to examine the effect of preoperative three‐dimensional (3D) computed tomography (CT)‐based resection process map (RPM) imaging on the outcomes of robot‐assisted partial nephrectomy (RAPN).
Methods
We retrospectively analyzed 177 patients (RPM group, n = 92; non‐RPM group, n = 85) who underwent this surgery between November 2012 and April 2022. Patient‐specific contrast‐enhanced CT images were used to construct an RPM, a 3D representation of the kidney showing the planned tumor resection and a 5 mm safety margin. Outcome analyses were performed using propensity score matching. The primary endpoint was the trifecta achievement rate.
Results
We extracted 90 cases. The trifecta achievement rate showed no significant differences between the RPM (73.3%) and non‐RPM groups (73.3%). However, the RPM group had fewer Grade 3 and higher complications (0.0% vs. 13.3%, p = 0.026). The da Vinci Xi (OR 3.38, p = 0.016) and tumor diameter (OR 0.95, p = 0.013) were independent factors affecting trifecta achievement in multivariate analysis. Using RPM imaging was associated with the absence of Grade 3 and higher perioperative complications (OR 5.33, p = 0.036) in univariate analysis.
Conclusions
Using preoperative 3D CT‐based RPM images before RAPN may not affect trifecta achievement, but may reduce serious complication occurrence by providing detailed information on tumor resection.
Key points
Although Plain three‐dimensional computed tomography (CT) images allow spatial recognition of the kidneys and arteries, they do not show the course of the ureters and the internal structure of the kidneys during the excretory phase.
Resection process maps provide dynamic images based on patient‐specific CT data that provide extensive tumor‐related information.
Using these maps may not affect trifecta achievement in robot‐assisted partial nephrectomy; nevertheless, they provide valuable information that may reduce the occurrence of serious complications.</description><subject>computed X‐ray tomography</subject><subject>Kidney cancer</subject><subject>Kidneys</subject><subject>nephrectomy</subject><subject>renal cancer</subject><subject>resection margin</subject><subject>Robots</subject><subject>robot‐assisted surgery</subject><subject>Tomography</subject><issn>0022-4790</issn><issn>1096-9098</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNp1kUFu1TAQhi1ERR8PFlwAWWIDi7R24jgxu6oqLVWlLijryHEmfXlK4uBxQNlxhJ6FI3ESJrzCAgl5YWvmm3_G8zP2SooTKUR6ukd_khZa5k_YRgqjEyNM-ZRtKJcmqjDimD1H3AshjNHqGTvOSlWIPNcb9uNuFwB-fn9ougFG7Pxoe-78MM0RGh794O-DnXYLEbVFCgVAcJE4PgXvAJEPduKtDzz42kfiLGKHa_VkQ-xIboSJmjgSW96vVdPaKC4cnQ9A5dHtuvGe-5ZbjvTq13kcjBFIFGLwOK0tvwLHODfLC3bU2h7h5eO9ZZ8_XNydXyU3t5cfz89uEpfJLE8KJ9ddaMhUWQKkrQUweW6VK8oyd6BEK9JCNaYWyugCsjxVpUkNJY1Ka8i27O1Bl0b-MgPGaujQQd_bEfyMVWpyrcusoLNlb_5B934OtEqsMqEzaYySkqh3B8rRlzBAW02hG2xYKimq1ciKjKx-G0ns60fFuR6g-Uv-cY6A0wPwreth-b9Sdf3p9iD5C0Wvr-Q</recordid><startdate>202406</startdate><enddate>202406</enddate><creator>Okada, Atsushi</creator><creator>Ohashi, Kazuya</creator><creator>Hashimoto, Hiroya</creator><creator>Ota, Yuya</creator><creator>Sugino, Teruaki</creator><creator>Unno, Rei</creator><creator>Iwatsuki, Shoichiro</creator><creator>Etani, Toshiki</creator><creator>Taguchi, Kazumi</creator><creator>Naiki, Taku</creator><creator>Kurokawa, Satoshi</creator><creator>Hamamoto, Shuzo</creator><creator>Ando, Ryosuke</creator><creator>Nakane, Akihiro</creator><creator>Kawai, Noriyasu</creator><creator>Tozawa, Keiichi</creator><creator>Yasui, Takahiro</creator><general>Wiley Subscription Services, Inc</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>K9.</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-7638-6048</orcidid><orcidid>https://orcid.org/0000-0002-2257-3892</orcidid><orcidid>https://orcid.org/0000-0003-2080-3794</orcidid><orcidid>https://orcid.org/0009-0005-5265-2216</orcidid></search><sort><creationdate>202406</creationdate><title>Three‐dimensional computed tomography‐based resection process map for robot‐assisted partial nephrectomy: propensity score matching of a single‐center retrospective study</title><author>Okada, Atsushi ; Ohashi, Kazuya ; Hashimoto, Hiroya ; Ota, Yuya ; Sugino, Teruaki ; Unno, Rei ; Iwatsuki, Shoichiro ; Etani, Toshiki ; Taguchi, Kazumi ; Naiki, Taku ; Kurokawa, Satoshi ; Hamamoto, Shuzo ; Ando, Ryosuke ; Nakane, Akihiro ; Kawai, Noriyasu ; Tozawa, Keiichi ; Yasui, Takahiro</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3135-7c110966e3488ee2faee955a4c7885ce40f0274d9b04967e35248929885942be3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>computed X‐ray tomography</topic><topic>Kidney cancer</topic><topic>Kidneys</topic><topic>nephrectomy</topic><topic>renal cancer</topic><topic>resection margin</topic><topic>Robots</topic><topic>robot‐assisted surgery</topic><topic>Tomography</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Okada, Atsushi</creatorcontrib><creatorcontrib>Ohashi, Kazuya</creatorcontrib><creatorcontrib>Hashimoto, Hiroya</creatorcontrib><creatorcontrib>Ota, Yuya</creatorcontrib><creatorcontrib>Sugino, Teruaki</creatorcontrib><creatorcontrib>Unno, Rei</creatorcontrib><creatorcontrib>Iwatsuki, Shoichiro</creatorcontrib><creatorcontrib>Etani, Toshiki</creatorcontrib><creatorcontrib>Taguchi, Kazumi</creatorcontrib><creatorcontrib>Naiki, Taku</creatorcontrib><creatorcontrib>Kurokawa, Satoshi</creatorcontrib><creatorcontrib>Hamamoto, Shuzo</creatorcontrib><creatorcontrib>Ando, Ryosuke</creatorcontrib><creatorcontrib>Nakane, Akihiro</creatorcontrib><creatorcontrib>Kawai, Noriyasu</creatorcontrib><creatorcontrib>Tozawa, Keiichi</creatorcontrib><creatorcontrib>Yasui, Takahiro</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of surgical oncology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Okada, Atsushi</au><au>Ohashi, Kazuya</au><au>Hashimoto, Hiroya</au><au>Ota, Yuya</au><au>Sugino, Teruaki</au><au>Unno, Rei</au><au>Iwatsuki, Shoichiro</au><au>Etani, Toshiki</au><au>Taguchi, Kazumi</au><au>Naiki, Taku</au><au>Kurokawa, Satoshi</au><au>Hamamoto, Shuzo</au><au>Ando, Ryosuke</au><au>Nakane, Akihiro</au><au>Kawai, Noriyasu</au><au>Tozawa, Keiichi</au><au>Yasui, Takahiro</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Three‐dimensional computed tomography‐based resection process map for robot‐assisted partial nephrectomy: propensity score matching of a single‐center retrospective study</atitle><jtitle>Journal of surgical oncology</jtitle><addtitle>J Surg Oncol</addtitle><date>2024-06</date><risdate>2024</risdate><volume>129</volume><issue>7</issue><spage>1311</spage><epage>1324</epage><pages>1311-1324</pages><issn>0022-4790</issn><eissn>1096-9098</eissn><abstract>Background and Objectives
We aimed to examine the effect of preoperative three‐dimensional (3D) computed tomography (CT)‐based resection process map (RPM) imaging on the outcomes of robot‐assisted partial nephrectomy (RAPN).
Methods
We retrospectively analyzed 177 patients (RPM group, n = 92; non‐RPM group, n = 85) who underwent this surgery between November 2012 and April 2022. Patient‐specific contrast‐enhanced CT images were used to construct an RPM, a 3D representation of the kidney showing the planned tumor resection and a 5 mm safety margin. Outcome analyses were performed using propensity score matching. The primary endpoint was the trifecta achievement rate.
Results
We extracted 90 cases. The trifecta achievement rate showed no significant differences between the RPM (73.3%) and non‐RPM groups (73.3%). However, the RPM group had fewer Grade 3 and higher complications (0.0% vs. 13.3%, p = 0.026). The da Vinci Xi (OR 3.38, p = 0.016) and tumor diameter (OR 0.95, p = 0.013) were independent factors affecting trifecta achievement in multivariate analysis. Using RPM imaging was associated with the absence of Grade 3 and higher perioperative complications (OR 5.33, p = 0.036) in univariate analysis.
Conclusions
Using preoperative 3D CT‐based RPM images before RAPN may not affect trifecta achievement, but may reduce serious complication occurrence by providing detailed information on tumor resection.
Key points
Although Plain three‐dimensional computed tomography (CT) images allow spatial recognition of the kidneys and arteries, they do not show the course of the ureters and the internal structure of the kidneys during the excretory phase.
Resection process maps provide dynamic images based on patient‐specific CT data that provide extensive tumor‐related information.
Using these maps may not affect trifecta achievement in robot‐assisted partial nephrectomy; nevertheless, they provide valuable information that may reduce the occurrence of serious complications.</abstract><cop>United States</cop><pub>Wiley Subscription Services, Inc</pub><pmid>38470556</pmid><doi>10.1002/jso.27615</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0002-7638-6048</orcidid><orcidid>https://orcid.org/0000-0002-2257-3892</orcidid><orcidid>https://orcid.org/0000-0003-2080-3794</orcidid><orcidid>https://orcid.org/0009-0005-5265-2216</orcidid></addata></record> |
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subjects | computed X‐ray tomography Kidney cancer Kidneys nephrectomy renal cancer resection margin Robots robot‐assisted surgery Tomography |
title | Three‐dimensional computed tomography‐based resection process map for robot‐assisted partial nephrectomy: propensity score matching of a single‐center retrospective study |
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