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.

Robotic partial nephrectomy in 3D virtual reconstructions era: is the paradigm changed? / Amparore, Daniele; Piramide, Federico; De Cillis, Sabrina; Verri, Paolo; Piana, Alberto; Pecoraro, Angela; Burgio, Mariano; Manfredi, Matteo; Carbonara, Umberto; Marchioni, Michele; Campi, Riccardo; Fiori, Cristian; Checcucci, Enrico; Porpiglia, Francesco. - In: WORLD JOURNAL OF UROLOGY. - ISSN 1433-8726. - ELETTRONICO. - 40:(2022), pp. 659-670. [10.1007/s00345-022-03964-x]

Robotic partial nephrectomy in 3D virtual reconstructions era: is the paradigm changed?

Campi, Riccardo;
2022

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.
2022
40
659
670
Goal 3: Good health and well-being
Amparore, Daniele; Piramide, Federico; De Cillis, Sabrina; Verri, Paolo; Piana, Alberto; Pecoraro, Angela; Burgio, Mariano; Manfredi, Matteo; Carbonara, Umberto; Marchioni, Michele; Campi, Riccardo; Fiori, Cristian; Checcucci, Enrico; Porpiglia, Francesco
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1297723
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