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3D renal model for surgical planning of partial nephrectomy: A way to improve surgical outcomes.
Bianchi, Lorenzo; Cercenelli, Laura; Bortolani, Barbara; Piazza, Pietro; Droghetti, Matteo; Boschi, Sara; Gaudiano, Caterina; Carpani, Giulia; Chessa, Francesco; Lodi, Simone; Tartarini, Lorenzo; Bertaccini, Alessandro; Golfieri, Rita; Marcelli, Emanuela; Schiavina, Riccardo; Brunocilla, Eugenio.
Afiliação
  • Bianchi L; Division of Urology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.
  • Cercenelli L; Università degli studi di Bologna, Bologna, Italy.
  • Bortolani B; eDIMES Lab - Laboratory of Bioengineering, Department of Experimental, Diagnostic and Specialty Medicine (DIMES), University of Bologna, Bologna, Italy.
  • Piazza P; eDIMES Lab - Laboratory of Bioengineering, Department of Experimental, Diagnostic and Specialty Medicine (DIMES), University of Bologna, Bologna, Italy.
  • Droghetti M; Division of Urology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.
  • Boschi S; Division of Urology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.
  • Gaudiano C; Division of Urology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.
  • Carpani G; Department of Radiology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.
  • Chessa F; Department of Radiology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.
  • Lodi S; Division of Urology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.
  • Tartarini L; Università degli studi di Bologna, Bologna, Italy.
  • Bertaccini A; eDIMES Lab - Laboratory of Bioengineering, Department of Experimental, Diagnostic and Specialty Medicine (DIMES), University of Bologna, Bologna, Italy.
  • Golfieri R; eDIMES Lab - Laboratory of Bioengineering, Department of Experimental, Diagnostic and Specialty Medicine (DIMES), University of Bologna, Bologna, Italy.
  • Marcelli E; Division of Urology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.
  • Schiavina R; Università degli studi di Bologna, Bologna, Italy.
  • Brunocilla E; Department of Radiology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.
Front Oncol ; 12: 1046505, 2022.
Article em En | MEDLINE | ID: mdl-36338693
Objective: to evaluate the impact of 3D model for a comprehensive assessment of surgical planning and quality of partial nephrectomy (PN). Materials and methods: 195 patients with cT1-T2 renal mass scheduled for PN were enrolled in two groups: Study Group (n= 100), including patients referred to PN with revision of both 2D computed tomography (CT) imaging and 3D model; Control group (n= 95), including patients referred to PN with revision of 2D CT imaging. Overall, 20 individuals were switched to radical nephrectomy (RN). The primary outcome was the impact of 3D models-based surgical planning on Trifecta achievement (defined as the contemporary absence of positive surgical margin, major complications and ≤30% postoperative eGFR reduction). The secondary outcome was the impact of 3D models on surgical planning of PN. Multivariate logistic regressions were used to identify predictors of selective clamping and Trifecta's achievement in patients treated with PN (n=175). Results: Overall, 73 (80.2%) patients in Study group and 53 (63.1%) patients in Control group achieved the Trifecta (p=0.01). The preoperative plan of arterial clamping was recorded as clampless, main artery and selective in 22 (24.2%), 22 (24.2%) and 47 (51.6%) cases in Study group vs. 31 (36.9%), 46 (54.8%) and 7 (8.3%) cases in Control group, respectively (p<0.001). At multivariate logistic regressions, the use of 3D model was found to be independent predictor of both selective or super-selective clamping and Trifecta's achievement. Conclusion: 3D-guided approach to PN increase the adoption of selective clamping and better predict the achievement of Trifecta.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article