Abstract
Purpose
The aim of this systematic review is to assess the clinical implications of employing various Extended Reality (XR) tools for image guidance in urological surgery.
Methods
In June 2023, a systematic electronic literature search was conducted using the Medline database (via PubMed), Embase (via Ovid), Scopus, and Web of Science. The search strategy was designed based on the PICO (Patients, Intervention, Comparison, Outcome) criteria. Study protocol was registered on PROSPERO (registry number CRD42023449025). We incorporated retrospective and prospective comparative studies, along with single-arm studies, which provided information on the use of XR, Mixed Reality (MR), Augmented Reality (AR), and Virtual Reality (VR) in urological surgical procedures. Studies that were not written in English, non-original investigations, and those involving experimental research on animals or cadavers were excluded from our analysis. The quality assessment of comparative and cohort studies was conducted utilizing the Newcastle-Ottawa scale, whilst for randomized controlled trials (RCTs), the Jadad scale was adopted. The level of evidence for each study was determined based on the guidelines provided by the Oxford Centre for Evidence-Based Medicine.
Results
The initial electronic search yielded 1,803 papers after removing duplicates. Among these, 58 publications underwent a comprehensive review, leading to the inclusion of 40 studies that met the specified criteria for analysis. 11, 20 and 9 studies tested XR on prostate cancer, kidney cancer and miscellaneous, including bladder cancer and lithiasis surgeries, respectively. Focusing on the different technologies 20, 15 and 5 explored the potential of VR, AR and MR. The majority of the included studies (i.e., 22) were prospective non-randomized, whilst 7 and 11 were RCT and retrospective studies respectively. The included studies that revealed how these new tools can be useful both in preoperative and intraoperative setting for a tailored surgical approach.
Conclusions
AR, VR and MR techniques have emerged as highly effective new tools for image-guided surgery, especially for urologic oncology. Nevertheless, the complete clinical advantages of these innovations are still in the process of evaluation.
Similar content being viewed by others
Data availability
The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.
References
Porpiglia F, Fiori C, Bertolo R, Manfredi M, Mele F, Checcucci E, et al. Five-year outcomes for a prospective Randomised Controlled Trial comparing laparoscopic and Robot-assisted radical prostatectomy. Eur Urol Focus. 2018;4:80–6. https://doi.org/10.1016/j.euf.2016.11.007.
Bertolo R, Bove P, Sandri M, Cindolo L, Annino F, Leonardo C, et al. Cross-analysis of two randomized controlled trials to compare pure versus robot-assisted laparoscopic approach during off-clamp partial nephrectomy. Minerva Urol Nephrol. 2022;74:5–10. https://doi.org/10.23736/S2724-6051.22.04779-6.
Pervez A, Ahmed K, Thompson S, Elhage O, Khan MS, Dasgupta P. Image guided robotic surgery: current evidence for effectiveness in urology. Arch Ital Urol Androl. 2014;86:245–8. https://doi.org/10.4081/aiua.2014.4.245.
Kozikowski M, Malewski W, Michalak W, Dobruch J. Clinical utility of MRI in the decision-making process before radical prostatectomy: systematic review and meta-analysis. PLoS ONE. 2019;14:e0210194. https://doi.org/10.1371/journal.pone.0210194.
Vahrmeijer AL, Hutteman M, van der Vorst JR, van de Velde CJH, Frangioni JV. Image-guided cancer surgery using near-infrared fluorescence. Nat Rev Clin Oncol. 2013;10:507–18. https://doi.org/10.1038/nrclinonc.2013.123.
Mk D, G R, As SM, P G. Intraoperative ultrasonography (IOUS)-guided vs conventional laparoscopic nephrectomy: a randomised control trial. BJU Int. 2024;133. https://doi.org/10.1111/bju.16136.
Boekestijn I, Azargoshasb S, Schilling C, Navab N, Rietbergen D, van Oosterom MN. PET- and SPECT-based navigation strategies to advance procedural accuracy in interventional radiology and image-guided surgery. Q J Nucl Med Mol Imaging. 2021;65:244–60. https://doi.org/10.23736/S1824-4785.21.03361-6.
Mackenzie CF, Harris TE, Shipper AG, Elster E, Bowyer MW. Virtual reality and haptic interfaces for civilian and military open trauma surgery training: a systematic review. Injury. 2022;53:3575–85. https://doi.org/10.1016/j.injury.2022.08.003.
Ostler D, Seibold M, Fuchtmann J, Samm N, Feussner H, Wilhelm D, et al. Acoustic signal analysis of instrument-tissue interaction for minimally invasive interventions. Int J Comput Assist Radiol Surg. 2020;15:771–9. https://doi.org/10.1007/s11548-020-02146-7.
Photoacoustic imaging for. surgical guidance: Principles, applications, and outlook - PubMed n.d. https://pubmed.ncbi.nlm.nih.gov/32817994/ (accessed January 22, 2024).
Rodler S, Kidess MA, Westhofen T, Kowalewski K-F, Belenchon IR, Taratkin M, et al. A Systematic Review of New Imaging Technologies for Robotic Prostatectomy: from Molecular Imaging to Augmented reality. J Clin Med. 2023;12:5425. https://doi.org/10.3390/jcm12165425.
Ghazi A, Campbell T, Melnyk R, Feng C, Andrusco A, Stone J, et al. Validation of a full-immersion Simulation platform for Percutaneous Nephrolithotomy using three-dimensional Printing Technology. J Endourol. 2017;31:1314–20. https://doi.org/10.1089/end.2017.0366.
Amparore D, Pecoraro A, Checcucci E, DE Cillis S, Piramide F, Volpi G, et al. 3D imaging technologies in minimally invasive kidney and prostate cancer surgery: which is the urologists’ perception? Minerva Urol Nephrol. 2022;74:178–85. https://doi.org/10.23736/S2724-6051.21.04131-X.
Veneziano D, Amparore D, Cacciamani G, Porpiglia F, Uro-technology, SoMe Working Group of the Young Academic Urologists Working Party of the European Association of Urology. Climbing over the barriers of current Imaging Technology in Urology. Eur Urol. 2020;77:142–3. https://doi.org/10.1016/j.eururo.2019.09.016.
Amparore D, Piramide F, De Cillis S, Verri P, Piana A, Pecoraro A, et al. Robotic partial nephrectomy in 3D virtual reconstructions era: is the paradigm changed? World J Urol. 2022;40:659–70. https://doi.org/10.1007/s00345-022-03964-x.
Checcucci E, De Cillis S, Porpiglia F. 3D-printed models and virtual reality as new tools for image-guided robot-assisted nephron-sparing surgery: a systematic review of the newest evidences. Curr Opin Urol. 2020;30:55–64. https://doi.org/10.1097/MOU.0000000000000686.
Updated guidance for trusted. systematic reviews: a new edition of the Cochrane Handbook for Systematic Reviews of Interventions - PubMed n.d. https://pubmed.ncbi.nlm.nih.gov/31643080/ (accessed January 22, 2024).
Moher D, Liberati A, Tetzlaff J, Altman DG, PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6:e1000097. https://doi.org/10.1371/journal.pmed.1000097.
Ottawa Hospital Research Institute n.d. https://www.ohri.ca/programs/clinical_epidemiology/oxford.asp (accessed January 22, 2024).
Jadad AR, Moore RA, Carroll D, Jenkinson C, Reynolds DJ, Gavaghan DJ, et al. Assessing the quality of reports of randomized clinical trials: is blinding necessary? Control Clin Trials. 1996;17:1–12. https://doi.org/10.1016/0197-2456(95)00134-4.
Guyatt GH, Oxman AD, Vist GE, Kunz R, Falck-Ytter Y, Alonso-Coello P, et al. GRADE: an emerging consensus on rating quality of evidence and strength of recommendations. BMJ. 2008;336:924–6. https://doi.org/10.1136/bmj.39489.470347.AD.
Augmented Reality Robot-assisted Radical Prostatectomy. Preliminary Experience - PubMed n.d. https://pubmed.ncbi.nlm.nih.gov/29548868/ (accessed January 22, 2024).
Thompson S, Penney G, Billia M, Challacombe B, Hawkes D, Dasgupta P. Design and evaluation of an image-guidance system for robot-assisted radical prostatectomy. BJU Int. 2013;111:1081–90. https://doi.org/10.1111/j.1464-410X.2012.11692.x.
Ukimura O, Aron M, Nakamoto M, Shoji S, Abreu AL, de Matsugasumi C. Three-dimensional surgical navigation model with TilePro display during robot-assisted radical prostatectomy. J Endourol. 2014;28:625–30. https://doi.org/10.1089/end.2013.0749.
Porpiglia F, Manfredi M, Checcucci E, Mele F, Bertolo R, De Luca S, et al. 66–3D prostate MRI reconstruction for congitive robot assisted radical prostatectomy: is it able to reduce the positive surgical margin rate? Eur Urol Supplements. 2017;16:e110–1. https://doi.org/10.1016/S1569-9056(17)30133-1.
Augmented-reality robot. -assisted radical prostatectomy using hyper-accuracy three-dimensional reconstruction (HA3D™) technology: a radiological and pathological study - PubMed n.d. https://pubmed.ncbi.nlm.nih.gov/30246936/ (accessed January 22, 2024).
Porpiglia F, Checcucci E, Amparore D, Manfredi M, Massa F, Piazzolla P, et al. Three-dimensional Elastic augmented-reality Robot-assisted radical prostatectomy using Hyperaccuracy three-dimensional Reconstruction Technology: a step further in the identification of capsular involvement. Eur Urol. 2019;76:505–14. https://doi.org/10.1016/j.eururo.2019.03.037.
Schiavina R, Bianchi L, Lodi S, Cercenelli L, Chessa F, Bortolani B, et al. Real-time augmented reality three-dimensional guided robotic radical prostatectomy: preliminary experience and evaluation of the impact on Surgical Planning. Eur Urol Focus. 2021;7:1260–7. https://doi.org/10.1016/j.euf.2020.08.004.
Canda AE, Aksoy SF, Altinmakas E, Koseoglu E, Falay O, Kordan Y, et al. Virtual reality tumor navigated robotic radical prostatectomy by using three-dimensional reconstructed multiparametric prostate MRI and 68Ga-PSMA PET/CT images: a useful tool to guide the robotic surgery? BJUI Compass. 2020;1:108–15. https://doi.org/10.1002/bco2.16.
Bianchi L, Chessa F, Angiolini A, Cercenelli L, Lodi S, Bortolani B, et al. The Use of Augmented reality to Guide the Intraoperative Frozen Section during Robot-assisted radical prostatectomy. Eur Urol. 2021;80:480–8. https://doi.org/10.1016/j.eururo.2021.06.020.
Shirk JD, Reiter R, Wallen EM, Pak R, Ahlering T, Badani KK, et al. Effect of 3-Dimensional, virtual reality models for Surgical Planning of robotic prostatectomy on Trifecta outcomes: a Randomized Clinical Trial. J Urol. 2022;208:618–25. https://doi.org/10.1097/JU.0000000000002719.
Lasser MS, Doscher M, Keehn A, Chernyak V, Garfein E, Ghavamian R. Virtual surgical planning: a novel aid to robot-assisted laparoscopic partial nephrectomy. J Endourol. 2012;26:1372–9. https://doi.org/10.1089/end.2012.0093.
The impact. of 3D models on positive surgical margins after robot-assisted radical prostatectomy - PubMed n.d. https://pubmed.ncbi.nlm.nih.gov/35790535/ (accessed January 22, 2024).
Surgical planning and manual image fusion. based on 3D model facilitate laparoscopic partial nephrectomy for intrarenal tumors - PubMed n.d. https://pubmed.ncbi.nlm.nih.gov/24337151/ (accessed January 22, 2024).
Prediction of open. urinary tract in laparoscopic partial nephrectomy by virtual resection plane visualization - PubMed n.d. https://pubmed.ncbi.nlm.nih.gov/24927795/ (accessed January 22, 2024).
Porpiglia F, Fiori C, Checcucci E, Amparore D, Bertolo R. Hyperaccuracy three-dimensional Reconstruction is able to maximize the efficacy of selective clamping during Robot-assisted partial nephrectomy for Complex Renal masses. Eur Urol. 2018;74:651–60. https://doi.org/10.1016/j.eururo.2017.12.027.
Kobayashi S, Cho B, Mutaguchi J, Inokuchi J, Tatsugami K, Hashizume M, et al. Surgical Navigation improves renal parenchyma volume preservation in Robot-assisted partial nephrectomy: a propensity score matched comparative analysis. J Urol. 2020;204:149–56. https://doi.org/10.1097/JU.0000000000000709.
Shirk JD, Kwan L, Saigal C. The Use of 3-Dimensional, virtual reality models for Surgical Planning of robotic partial nephrectomy. Urology. 2019;125:92–7. https://doi.org/10.1016/j.urology.2018.12.026.
Shirk JD, Thiel DD, Wallen EM, Linehan JM, White WM, Badani KK, et al. Effect of 3-Dimensional virtual reality models for Surgical Planning of robotic-assisted partial nephrectomy on Surgical outcomes: a Randomized Clinical Trial. JAMA Netw Open. 2019;2:1–11. https://doi.org/10.1001/jamanetworkopen.2019.11598.
Dubrovin V, Egoshin A, Rozhentsov A, Batuhtin D, Eruslanov R, Chernishov D, et al. Virtual simulation, preoperative planning and intraoperative navigation during laparoscopic partial nephrectomy. Cent Eur J Urol. 2019;72:247–51. https://doi.org/10.5173/ceju.2019.1632.
Li G, Dong J, Wang J, Cao D, Zhang X, Cao Z, et al. The clinical application value of mixed-reality-assisted surgical navigation for laparoscopic nephrectomy. Cancer Med. 2020;9:5480–9. https://doi.org/10.1002/cam4.3189.
Schiavina R, Bianchi L, Chessa F, Barbaresi U, Cercenelli L, Lodi S, et al. Augmented reality to Guide Selective Clamping and Tumor Dissection during Robot-assisted partial nephrectomy: a preliminary experience. Clin Genitourin Cancer. 2021;19:e149–55. https://doi.org/10.1016/j.clgc.2020.09.005.
Porpiglia F, Checcucci E, Amparore D, Piramide F, Volpi G, Granato S, et al. Three-dimensional augmented reality Robot-assisted partial nephrectomy in case of Complex Tumours (PADUA ≥ 10): a New Intraoperative Tool overcoming the Ultrasound Guidance. Eur Urol. 2020;78:229–38. https://doi.org/10.1016/j.eururo.2019.11.024.
McDonald M, Shirk D. J. Application of three-dimensional virtual reality models to improve the pre-surgical plan for robotic partial nephrectomy. JSLS 2021;25:e2021.00011. https://doi.org/10.4293/JSLS.2021.00011.
Li G, Cao Z, Wang J, Zhang X, Zhang L, Dong J, et al. Mixed reality models based on low-dose computed tomography technology in nephron-sparing surgery are better than models based on normal-dose computed tomography. Quant Imaging Med Surg. 2021;11:2658–68. https://doi.org/10.21037/qims-20-956.
Zeng S, Zhou Y, Wang M, Bao H, Na Y, Pan T. Holographic reconstruction technology used for intraoperative real-time navigation in robot-assisted partial nephrectomy in patients with renal tumors: a single center study. Transl Androl Urol. 2021;10:3386–94. https://doi.org/10.21037/tau-21-473.
Gadzhiev N, Semeniakin I, Morshnev A, Alcaraz A, Gauhar V, Okhunov Z. Role and utility of mixed reality technology in laparoscopic partial nephrectomy: outcomes of a prospective RCT using an indigenously developed Software. Adv Urol. 2022;2022:8992051. https://doi.org/10.1155/2022/8992051.
Yang Y, Gao Y, Zhang X-Y, Wang B-J, Zhu J, Zhang X. Mixed reality: a step further for planning Complex Renal tumors (RENAL nephrometry score of 7 or higher). J Endourol. 2022;36:1136–42. https://doi.org/10.1089/end.2021.0798.
Zhang K, Wang L, Sun Y, Wang W, Hao S, Li H, et al. Combination of holographic imaging with robotic partial nephrectomy for renal hilar tumor treatment. Int Urol Nephrol. 2022;54:1837–44. https://doi.org/10.1007/s11255-022-03228-y.
Amparore D, Checcucci E, Piazzolla P, Piramide F, De Cillis S, Piana A et al. Indocyanine green drives computer vision based 3D augmented reality robot assisted partial nephrectomy: the beginning of automatic overlapping era. Urology 2022:S0090-4295(22)00029 – 2. https://doi.org/10.1016/j.urology.2021.10.053.
Bianchi L, Cercenelli L, Bortolani B, Piazza P, Droghetti M, Boschi S, et al. 3D renal model for surgical planning of partial nephrectomy: a way to improve surgical outcomes. Front Oncol. 2022;12:1046505. https://doi.org/10.3389/fonc.2022.1046505.
Shiozaki K, Kawanishi Y, Sasaki Y, Daizumoto K, Tsuda M, Izumi K, et al. Clinical application of virtual imaging guided Robot-assisted partial nephrectomy. J Med Invest. 2022;69:237–43. https://doi.org/10.2152/jmi.69.237.
Goergen DI, Freitas DMDO. Virtual reality as a distraction therapy during cystoscopy: a clinical trial. Rev Col Bras Cir. 2022;49:e20223138. https://doi.org/10.1590/0100-6991e-20223138-en.
Ketsuwan C, Matang W, Ratanapornsompong W, Sangkum P, Phengsalae Y, Kongchareonsombat W, et al. Prospective randomized controlled trial to evaluate effectiveness of virtual reality to decrease anxiety in office-based flexible cystoscopy patients. World J Urol. 2022;40:2575–81. https://doi.org/10.1007/s00345-022-04142-9.
Li H, Chen Y, Liu C, Li B, Xu K, Bao S. Construction of a three-dimensional model of renal stones: comprehensive planning for percutaneous nephrolithotomy and assistance in surgery. World J Urol. 2013;31:1587–92. https://doi.org/10.1007/s00345-012-0998-7.
Parkhomenko E, O’Leary M, Safiullah S, Walia S, Owyong M, Lin C, et al. Pilot Assessment of Immersive virtual reality renal models as an Educational and Preoperative Planning Tool for Percutaneous Nephrolithotomy. J Endourol. 2019;33:283–8. https://doi.org/10.1089/end.2018.0626.
Zhu W, Xiong S, Xu C, Zhu Z, Li Z, Zhang L, et al. Initial experiences with preoperative three-dimensional image reconstruction technology in laparoscopic pyeloplasty for ureteropelvic junction obstruction. Transl Androl Urol. 2021;10:4142–51. https://doi.org/10.21037/tau-21-590.
Cao Z, Xiu Y, Yu D, Li X, Yang C, Li Z. Clinical value of mixed reality-assisted puncture Navigation for Percutaneous Nephrolithotripsy. Urology. 2023;176:219–25. https://doi.org/10.1016/j.urology.2022.12.067.
Wang L, Zhao Z, Wang G, Zhou J, Zhu H, Guo H, et al. Application of a three-dimensional visualization model in intraoperative guidance of percutaneous nephrolithotomy. Int J Urol. 2022;29:838–44. https://doi.org/10.1111/iju.14907.
Gu J, Luo S, Jiang L, Hu D, Zhao G, Tang W. Novel scoring system combined with a virtual reality technique for the preoperative evaluation of the stone-free status after flexible ureteroscopy: the H.L.P.E.S. score. BMC Urol. 2022;22:161. https://doi.org/10.1186/s12894-022-01108-2.
Porpiglia F, Checcucci E, Amparore D, Peretti D, Piramide F, De Cillis S, et al. Percutaneous kidney puncture with three-dimensional mixed-reality Hologram Guidance: from Preoperative Planning to Intraoperative Navigation. Eur Urol. 2022;81:588–97. https://doi.org/10.1016/j.eururo.2021.10.023.
Checcucci E, Verri P, Amparore D, Cacciamani GE, Rivas JG, Autorino R, et al. The future of robotic surgery in urology: from augmented reality to the advent of metaverse. Ther Adv Urol. 2023;15:17562872231151853. https://doi.org/10.1177/17562872231151853.
Checcucci E, Piana A, Volpi G, Piazzolla P, Amparore D, De Cillis S, et al. Three-dimensional automatic artificial intelligence driven augmented-reality selective biopsy during nerve-sparing robot-assisted radical prostatectomy: a feasibility and accuracy study. Asian J Urol. 2023;10:407–15. https://doi.org/10.1016/j.ajur.2023.08.001.
Krücker J, Xu S, Venkatesan A, Locklin JK, Amalou H, Glossop N, et al. Clinical utility of real-time fusion guidance for biopsy and ablation. J Vasc Interv Radiol. 2011;22:515–24. https://doi.org/10.1016/j.jvir.2010.10.033.
Brouwer OR, van den Berg NS, Mathéron HM, Wendler T, van der Poel HG, Horenblas S, et al. Feasibility of intraoperative navigation to the sentinel node in the groin using preoperatively acquired single photon emission computerized tomography data: transferring functional imaging to the operating room. J Urol. 2014;192:1810–6. https://doi.org/10.1016/j.juro.2014.03.127.
KleinJan GH, van den Berg NS, van Oosterom MN, Wendler T, Miwa M, Bex A, et al. Toward (hybrid) Navigation of a fluorescence camera in an open surgery setting. J Nucl Med. 2016;57:1650–3. https://doi.org/10.2967/jnumed.115.171645.
van Oosterom MN, Meershoek P, KleinJan GH, Hendricksen K, Navab N, van de Velde CJH, et al. Navigation of Fluorescence Cameras during soft tissue Surgery-Is it possible to use a single Navigation Setup for various Open and laparoscopic urological surgery applications? J Urol. 2018;199:1061–8. https://doi.org/10.1016/j.juro.2017.09.160.
Checcucci E, Amparore D, Volpi G, Piramide F, De Cillis S, Piana A, et al. Percutaneous puncture during PCNL: new perspective for the future with virtual imaging guidance. World J Urol. 2022;40:639–50. https://doi.org/10.1007/s00345-021-03820-4.
Checcucci E, Amparore D, Fiori C, Manfredi M, Ivano M, Di Dio M, et al. 3D imaging applications for robotic urologic surgery: an ESUT YAUWP review. World J Urol. 2020;38:869–81. https://doi.org/10.1007/s00345-019-02922-4.
Piana A, Gallioli A, Amparore D, Diana P, Territo A, Campi R, et al. Three-dimensional augmented reality-guided robotic-assisted kidney transplantation: breaking the limit of atheromatic plaques. Eur Urol. 2022. https://doi.org/10.1016/j.eururo.2022.07.003. :S0302-2838(22)02479-4.
Falk V, Mourgues F, Adhami L, Jacobs S, Thiele H, Nitzsche S, et al. Cardio navigation: planning, simulation, and augmented reality in robotic assisted endoscopic bypass grafting. Ann Thorac Surg. 2005;79:2040–7. https://doi.org/10.1016/j.athoracsur.2004.11.060.
Nakamoto M, Nakada K, Sato Y, Konishi K, Hashizume M, Tamura S. Intraoperative magnetic tracker calibration using a magneto-optic hybrid tracker for 3-D ultrasound-based navigation in laparoscopic surgery. IEEE Trans Med Imaging. 2008;27:255–70. https://doi.org/10.1109/TMI.2007.911003.
Simpfendörfer T, Baumhauer M, Müller M, Gutt CN, Meinzer H-P, Rassweiler JJ, et al. Augmented reality visualization during laparoscopic radical prostatectomy. J Endourol. 2011;25:1841–5. https://doi.org/10.1089/end.2010.0724.
Amparore D, Piramide F, Checcucci E, Verri P, De Cillis S, Piana A et al. Three-dimensional virtual models of the kidney with Colored Perfusion regions: a New Algorithm-based Tool for optimizing the Clamping Strategy during Robot-assisted partial nephrectomy. Eur Urol 2023:S0302-2838(23)02727-6. https://doi.org/10.1016/j.eururo.2023.04.005.
Amparore D, Piramide F, Verri P, Checcucci E, De Cillis S, Piana A, et al. New generation of 3D virtual models with Perfusional zones: Perioperative Assistance for the best pedicle management during robotic partial nephrectomy. Curr Oncol. 2023;30:4021–32. https://doi.org/10.3390/curroncol30040304.
Di Dio M, Barbuto S, Bisegna C, Bellin A, Boccia M, Amparore D, et al. Artificial Intelligence-based Hyper Accuracy three-Dimensional (HA3D®) models in Surgical Planning of Challenging robotic nephron-sparing surgery: a Case Report and Snapshot of the state-of-the-art with possible future implications. Diagnostics (Basel). 2023;13:2320. https://doi.org/10.3390/diagnostics13142320.
Pecoraro A, Amparore D, Checcucci E, Piramide F, Carbonaro B, De Cillis S, et al. Three-dimensional virtual models assistance predicts higher rates of successful minimally invasive partial nephrectomy: an institutional analysis across the available trifecta definitions. World J Urol. 2023;41:1093–100. https://doi.org/10.1007/s00345-023-04310-5.
Checcucci E, Amparore D, Volpi G, De Cillis S, Piramide F, Verri P, et al. Metaverse Surgical Planning with three-dimensional virtual models for minimally invasive partial nephrectomy. Eur Urol. 2023. https://doi.org/10.1016/j.eururo.2023.07.015. S0302-2838(23)03015-4.
Amparore D, Pecoraro A, Checcucci E, Piramide F, Verri P, De Cillis S, et al. Three-dimensional virtual models’ assistance during minimally invasive partial nephrectomy minimizes the impairment of kidney function. Eur Urol Oncol. 2022;5:104–8. https://doi.org/10.1016/j.euo.2021.04.001.
Piramide F, Kowalewski K-F, Cacciamani G, Rivero Belenchon I, Taratkin M, Carbonara U, et al. Three-dimensional model-assisted minimally invasive partial nephrectomy: a systematic review with Meta-analysis of comparative studies. Eur Urol Oncol. 2022;5:640–50. https://doi.org/10.1016/j.euo.2022.09.003.
Amparore D, Pira F, Piana A, Checcucci E, Basile G, Larcher A, et al. A0865 - functional outcomes prediction after robotic partial nephrectomy using PADUA score assessed with 3D virtual models: preliminary results of a collaborative ERUS study. Eur Urol. 2023;83:S1226–7. https://doi.org/10.1016/S0302-2838(23)00905-3.
Checcucci E, Piazza P, Micali S, Ghazi A, Mottrie A, Porpiglia F, et al. Three-dimensional Model Reconstruction: the need for standardization to drive tailored surgery. Eur Urol. 2022;81:129–31. https://doi.org/10.1016/j.eururo.2021.11.010.
Markus A, Ray ASC, Bolla D, Müller J, Diener P-A, Wendler T, et al. Sentinel lymph node biopsy in endometrial and cervical cancers using freehand SPECT—first experiences. Gynecol Surg. 2016;13:499–506. https://doi.org/10.1007/s10397-016-0969-x.
DSouza AV, Lin H, Henderson ER, Samkoe KS, Pogue BW. Review of fluorescence guided surgery systems: identification of key performance capabilities beyond indocyanine green imaging. J Biomed Opt. 2016;21:80901. https://doi.org/10.1117/1.JBO.21.8.080901.
De Backer P, Van Praet C, Simoens J, Peraire Lores M, Creemers H, Mestdagh K, et al. Improving augmented reality through Deep Learning: real-time instrument Delineation in robotic renal surgery. Eur Urol. 2023;84:86–91. https://doi.org/10.1016/j.eururo.2023.02.024.
Marullo G, Tanzi L, Ulrich L, Porpiglia F, Vezzetti E. A multi-task convolutional neural network for semantic segmentation and event detection in laparoscopic surgery. J Pers Med. 2023;13:413. https://doi.org/10.3390/jpm13030413.
Checcucci E, Cacciamani GE, Amparore D, Gozen A, Seitz C, Breda A, The Metaverse in Urology: Ready for Prime Time. The ESUT, ERUS, EULIS, and, Perspective ESU et al. Eur Urol Open Sci. 2022;46:96–8. https://doi.org/10.1016/j.euros.2022.10.011.
Acknowledgements
We would like to thank Dr. Nicoletta Colombi for her help during the systematic review.
Funding
Not applicable.
Author information
Authors and Affiliations
Contributions
Conception and design: Enrico Checcucci, Sabrina De Cillis, Federico Piramide. Acquistion of data: Mariano Burgio, Juliette Meziee, Edoardo Cisero, Marco Colombo, Alberto Quarà, Gabriele Bignante. Analysis and interpretation of data: Michele Sica, Stefano Granato, Paolo Verri, Cecilia Gatti, Paolo Alessio, Gabriele Volpi. Drafting of the manuscript: Enrico Checcucci, Alberto Piana. Critical Revision: Daniele Amparore, Michele Di Dio, Stefano Alba, Cristian Fiori, Francesco Porpiglia. Supervision: Francesco Porpiglia.
Corresponding author
Ethics declarations
Conflict of interest
All the authors have nothing to declare.
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Checcucci, E., Piana, A., Volpi, G. et al. Visual extended reality tools in image-guided surgery in urology: a systematic review. Eur J Nucl Med Mol Imaging (2024). https://doi.org/10.1007/s00259-024-06699-6
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s00259-024-06699-6