PURPOSE: Robot-assisted partial nephrectomy (RAPN) is a difficult procedure with risk of significant perioperative complications. The objective was to evaluate the impact of preoperative planning and intraoperative guidance with 3D model reconstructions on perioperative outcomes of RAPN. METHODS: We conducted a retrospective analysis of all patients who underwent RAPN for kidney tumor by three high-volume expert surgeons from academic centers. Clinical data were collected prospectively after written consent into the French kidney cancer network database UroCCR (CNIL-DR 2013-206; NCT03293563). Our cohort was divided into two groups: 3D-Image guided RAPN group (3D-IGRAPN) and control group. A propensity score according to age, pre-operative renal function and RENAL tumor complexity score was used. Both surgical techniques were compared in terms of perioperative outcomes. RESULTS: The initial study cohort included 230 3D-IGRAPN and 415 control RAPN. Before propensity-score matching, patients in the 3D-IGRAPN group had a larger tumor (4.3 cm vs. 3.5 cm, P < 0.001) and higher RENAL complexity score (9 vs. 8, P < 0.001). Following propensity-score matching, there were 157 patients in both groups. The rate of major complications was lower for patients in the 3D-IGRAPN group (3.8% vs. 9.5%, P = 0.04). The median percentage of eGFR variation recorded at first follow-up was lower in the 3D-IGRAPN group (- 5.6% vs. - 10.5%, P = 0.002). The trifecta achievement rate was higher in the 3D-IGRAPN group (55.7% vs. 45.1%; P = 0.005). CONCLUSION: Three-dimensional kidney reconstructions use for pre-operative planning and intraoperative surgical guidance lowers the risk of complications and improve perioperative clinical outcomes of RAPN.
PURPOSE: Robot-assisted partial nephrectomy (RAPN) is a difficult procedure with risk of significant perioperative complications. The objective was to evaluate the impact of preoperative planning and intraoperative guidance with 3D model reconstructions on perioperative outcomes of RAPN. METHODS: We conducted a retrospective analysis of all patients who underwent RAPN for kidney tumor by three high-volume expert surgeons from academic centers. Clinical data were collected prospectively after written consent into the French kidney cancer network database UroCCR (CNIL-DR 2013-206; NCT03293563). Our cohort was divided into two groups: 3D-Image guided RAPN group (3D-IGRAPN) and control group. A propensity score according to age, pre-operative renal function and RENAL tumor complexity score was used. Both surgical techniques were compared in terms of perioperative outcomes. RESULTS: The initial study cohort included 230 3D-IGRAPN and 415 control RAPN. Before propensity-score matching, patients in the 3D-IGRAPN group had a larger tumor (4.3 cm vs. 3.5 cm, P < 0.001) and higher RENAL complexity score (9 vs. 8, P < 0.001). Following propensity-score matching, there were 157 patients in both groups. The rate of major complications was lower for patients in the 3D-IGRAPN group (3.8% vs. 9.5%, P = 0.04). The median percentage of eGFR variation recorded at first follow-up was lower in the 3D-IGRAPN group (- 5.6% vs. - 10.5%, P = 0.002). The trifecta achievement rate was higher in the 3D-IGRAPN group (55.7% vs. 45.1%; P = 0.005). CONCLUSION: Three-dimensional kidney reconstructions use for pre-operative planning and intraoperative surgical guidance lowers the risk of complications and improve perioperative clinical outcomes of RAPN.
Authors: Riccardo Bertolo; Riccardo Autorino; Giuseppe Simone; Ithaar Derweesh; Juan D Garisto; Andrea Minervini; Daniel Eun; Sisto Perdona; James Porter; Koon Ho Rha; Alexander Mottrie; Wesley M White; Luigi Schips; Bo Yang; Kenneth Jacobsohn; Robert G Uzzo; Ben Challacombe; Matteo Ferro; Jay Sulek; Umberto Capitanio; Uzoma A Anele; Gabriele Tuderti; Manuela Costantini; Stephen Ryan; Ahmet Bindayi; Andrea Mari; Marco Carini; Aryeh Keehn; Giuseppe Quarto; Michael Liao; Kidon Chang; Alessandro Larcher; Geert De Naeyer; Ottavio De Cobelli; Francesco Berardinelli; Chao Zhang; Peter Langenstroer; Alexander Kutikov; David Chen; Nicolo De Luyk; Chandru P Sundaram; Francesco Montorsi; Robert J Stein; Georges Pascal Haber; Lance J Hampton; Prokar Dasgupta; Michele Gallucci; Jihad Kaouk; Francesco Porpiglia Journal: Eur Urol Date: 2018-05-19 Impact factor: 20.096
Authors: Joseph D Shirk; David D Thiel; Eric M Wallen; Jennifer M Linehan; Wesley M White; Ketan K Badani; James R Porter Journal: JAMA Netw Open Date: 2019-09-04
Authors: Stefano Puliatti; Ahmed Eissa; Enrico Checcucci; Pietro Piazza; Marco Amato; Stefania Ferretti; Simone Scarcella; Juan Gomez Rivas; Mark Taratkin; Josè Marenco; Ines Belenchon Rivero; Karl-Friedrich Kowalewski; Giovanni Cacciamani; Ahmed El-Sherbiny; Ahmed Zoeir; Abdelhamid M El-Bahnasy; Ruben De Groote; Alexandre Mottrie; Salvatore Micali Journal: Asian J Urol Date: 2022-06-01