Enrico Checcucci1,2, Francesco Porpiglia3, Daniele Amparore4,5, Federico Piramide4, Sabrina De Cillis4, Paolo Verri4, Alberto Piana4, Angela Pecoraro4,5, Mariano Burgio4, Matteo Manfredi4, Umberto Carbonara5,6, Michele Marchioni5,7, Riccardo Campi5,8, Cristian Fiori4. 1. Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, Candiolo, Turin, Italy. 2. Uro-Technology and SoMe Working Group of the Young Academic Urologists (YAU) Working Party of the European Association of Urology (EAU), Arnhem, The Netherlands. 3. Division of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Regione Gonzole 10, 10043, Orbassano (Turin), Italy. porpiglia@libero.it. 4. Division of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Regione Gonzole 10, 10043, Orbassano (Turin), Italy. 5. Renal Cancer Working Group of the Young Academic Urologists (YAU) Working Party of the European Association of Urology (EAU), Arnhem, The Netherlands. 6. Andrology and Kidney Transplantation Unit, Department of Emergency and Organ Transplantation-Urology, University of Bari, Bari, Italy. 7. Department of Urology, SS Annunziata Hospital, "G. D'Annunzio" University of Chieti, Chieti, Italy. 8. Department of Urology, Careggi Hospital, University of Florence, Florence, Italy.
Abstract
CONTEXT: The development of a tailored, patient-specific medical and surgical approach is becoming object of intense research. In kidney oncologic surgery, where a clear understanding of case-specific surgical anatomy is considered a key point to optimize the perioperative outcomes, such philosophy gained increasing importance. Recently, important advances in 3D virtual modeling technologies have fueled the interest for their application in the field of robotic minimally invasive surgery for kidney tumors. OBJECTIVE: To provide a synthesis of current applications of 3D virtual models for robot-assisted partial nephrectomy. EVIDENCE ACQUISITION: Medline, PubMed, the Cochrane Database, and Embase were screened for Literature regarding the use of 3D virtual models for robot-assisted partial nephrectomy (RAPN). EVIDENCE SYNTHESIS: The use of 3D virtual models for RAPN has been tested in different settings, including surgical indication and planning, intraoperative guidance, and training. Currently, several studies are available on the application of this technology for surgical planning, demonstrating impact on clinical outcomes such as renal function recovery, whilst experiences concerning their intraoperative application for navigation are still experimental. One of the latest innovations in this field is represented by the development of dedicated softwares able to automatically overlap the 3D virtual models to the real anatomy, to perform augmented reality procedures. CONCLUSIONS: The available Literature suggests a potentially crucial role of 3D virtual reconstructions during RAPN. Encouraging results concerning surgical planning and indication, intraoperative navigation, and surgical training are available. In the future, artificial intelligence may represent the key to further improve the 3D virtual modeling technology during RAPN.
CONTEXT: The development of a tailored, patient-specific medical and surgical approach is becoming object of intense research. In kidney oncologic surgery, where a clear understanding of case-specific surgical anatomy is considered a key point to optimize the perioperative outcomes, such philosophy gained increasing importance. Recently, important advances in 3D virtual modeling technologies have fueled the interest for their application in the field of robotic minimally invasive surgery for kidney tumors. OBJECTIVE: To provide a synthesis of current applications of 3D virtual models for robot-assisted partial nephrectomy. EVIDENCE ACQUISITION: Medline, PubMed, the Cochrane Database, and Embase were screened for Literature regarding the use of 3D virtual models for robot-assisted partial nephrectomy (RAPN). EVIDENCE SYNTHESIS: The use of 3D virtual models for RAPN has been tested in different settings, including surgical indication and planning, intraoperative guidance, and training. Currently, several studies are available on the application of this technology for surgical planning, demonstrating impact on clinical outcomes such as renal function recovery, whilst experiences concerning their intraoperative application for navigation are still experimental. One of the latest innovations in this field is represented by the development of dedicated softwares able to automatically overlap the 3D virtual models to the real anatomy, to perform augmented reality procedures. CONCLUSIONS: The available Literature suggests a potentially crucial role of 3D virtual reconstructions during RAPN. Encouraging results concerning surgical planning and indication, intraoperative navigation, and surgical training are available. In the future, artificial intelligence may represent the key to further improve the 3D virtual modeling technology during RAPN.
Authors: R Autorino; F Porpiglia; P Dasgupta; J Rassweiler; J W Catto; L J Hampton; E Lima; V Mirone; I H Derweesh; F M J Debruyne Journal: Eur J Surg Oncol Date: 2017-02-20 Impact factor: 4.424