{"title":"DCOM: a 3D virtual imaging-based nephrometry scoring system for robot-assisted partial nephrectomy.","authors":"Zhengsheng Liu, Tao Wang, Zongkai Zhang, Wei Li, Xuegang Wang, Kaiyan Zhang, Zhun Wu, Zhipeng Li, Zhongjie Zhao, Chaohao Miao, Yu Luo, Bin Chen, Jinchun Xing","doi":"10.23736/S2724-6051.25.06002-1","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The aim of this paper was to establish a new surgical difficulty scoring system of robot-assisted partial nephrectomy (RAPN) based on three-dimensional (3D) virtual imaging.</p><p><strong>Methods: </strong>We collected data from the patients subjected to robot-assisted surgery. 296 presented complete demographic and clinical data including RAPN and robot-assisted radical nephrectomy (RARN). Researchers used preoperative enhanced CT or MRI image data, and 3D image reconstruction, 4 independent variables were assessed: diameter of tumor inside kidney (D); compression of the renal segmental vessels; occupation of the renal sinus; mass exophytic rate (DCOM). DCOM score was then used to aid surgical decision-making and guide surgical strategy planning. The predictive values of DCOM score were analyzed using a multinomial logistic regression mode.</p><p><strong>Results: </strong>We confirmed that DCOM score as predictor of surgical outcome significantly outperformed the other common predictors used (RENAL and PADUA score).</p><p><strong>Conclusions: </strong>The surgical difficulty scoring system (DCOM scoring system) of partial nephrectomy (PN) based on 3D virtual imaging-based nephrometry system could provide a basis for the formulation of preoperative surgical strategy, but further verification is needed.</p>","PeriodicalId":53228,"journal":{"name":"Minerva Urology and Nephrology","volume":"77 3","pages":"308-319"},"PeriodicalIF":4.2000,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Minerva Urology and Nephrology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.23736/S2724-6051.25.06002-1","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"UROLOGY & NEPHROLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Background: The aim of this paper was to establish a new surgical difficulty scoring system of robot-assisted partial nephrectomy (RAPN) based on three-dimensional (3D) virtual imaging.
Methods: We collected data from the patients subjected to robot-assisted surgery. 296 presented complete demographic and clinical data including RAPN and robot-assisted radical nephrectomy (RARN). Researchers used preoperative enhanced CT or MRI image data, and 3D image reconstruction, 4 independent variables were assessed: diameter of tumor inside kidney (D); compression of the renal segmental vessels; occupation of the renal sinus; mass exophytic rate (DCOM). DCOM score was then used to aid surgical decision-making and guide surgical strategy planning. The predictive values of DCOM score were analyzed using a multinomial logistic regression mode.
Results: We confirmed that DCOM score as predictor of surgical outcome significantly outperformed the other common predictors used (RENAL and PADUA score).
Conclusions: The surgical difficulty scoring system (DCOM scoring system) of partial nephrectomy (PN) based on 3D virtual imaging-based nephrometry system could provide a basis for the formulation of preoperative surgical strategy, but further verification is needed.