Skip to main content
SpringerLink
Log in

Visual extended reality tools in image-guided surgery in urology: a systematic review

  • Review Article
  • Published:
European Journal of Nuclear Medicine and Molecular Imaging Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

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

  1. 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.

    Article  PubMed  Google Scholar 

  2. 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.

    Article  PubMed  Google Scholar 

  3. 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.

    Article  PubMed  Google Scholar 

  4. 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. 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.

  7. 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.

    Article  PubMed  Google Scholar 

  8. 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.

    Article  PubMed  Google Scholar 

  9. 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.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Photoacoustic imaging for. surgical guidance: Principles, applications, and outlook - PubMed n.d. https://pubmed.ncbi.nlm.nih.gov/32817994/ (accessed January 22, 2024).

  11. 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.

    Article  PubMed  PubMed Central  Google Scholar 

  12. 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.

    Article  PubMed  Google Scholar 

  13. 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.

    Article  PubMed  Google Scholar 

  14. 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.

    Article  PubMed  Google Scholar 

  15. 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.

    Article  PubMed  Google Scholar 

  16. 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.

    Article  PubMed  Google Scholar 

  17. 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).

  18. 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.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Ottawa Hospital Research Institute n.d. https://www.ohri.ca/programs/clinical_epidemiology/oxford.asp (accessed January 22, 2024).

  20. 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.

    Article  CAS  PubMed  Google Scholar 

  21. 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.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Augmented Reality Robot-assisted Radical Prostatectomy. Preliminary Experience - PubMed n.d. https://pubmed.ncbi.nlm.nih.gov/29548868/ (accessed January 22, 2024).

  23. 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.

    Article  PubMed  Google Scholar 

  24. 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.

    Article  PubMed  Google Scholar 

  25. 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.

    Article  Google Scholar 

  26. 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).

  27. 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.

    Article  PubMed  Google Scholar 

  28. 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.

    Article  PubMed  Google Scholar 

  29. 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.

    Article  PubMed  PubMed Central  Google Scholar 

  30. 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.

    Article  PubMed  Google Scholar 

  31. 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.

    Article  PubMed  Google Scholar 

  32. 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.

    Article  PubMed  Google Scholar 

  33. 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).

  34. 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).

  35. 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).

  36. 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.

    Article  PubMed  Google Scholar 

  37. 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.

    Article  PubMed  Google Scholar 

  38. 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.

    Article  PubMed  Google Scholar 

  39. 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.

    Article  Google Scholar 

  40. 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.

    Article  Google Scholar 

  41. 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.

    Article  PubMed  PubMed Central  Google Scholar 

  42. 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.

    Article  PubMed  Google Scholar 

  43. 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.

    Article  PubMed  Google Scholar 

  44. 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.

  45. 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.

    Article  PubMed  PubMed Central  Google Scholar 

  46. 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.

    Article  PubMed  PubMed Central  Google Scholar 

  47. 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.

    Article  PubMed  PubMed Central  Google Scholar 

  48. 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.

    Article  PubMed  Google Scholar 

  49. 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.

    Article  PubMed  Google Scholar 

  50. 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.

  51. 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.

    Article  PubMed  PubMed Central  Google Scholar 

  52. 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.

    Article  PubMed  Google Scholar 

  53. 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.

    Article  PubMed  PubMed Central  Google Scholar 

  54. 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.

    Article  PubMed  Google Scholar 

  55. 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.

    Article  PubMed  Google Scholar 

  56. 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.

    Article  PubMed  Google Scholar 

  57. 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.

    Article  PubMed  PubMed Central  Google Scholar 

  58. 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.

    Article  PubMed  Google Scholar 

  59. 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.

    Article  PubMed  Google Scholar 

  60. 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.

    Article  PubMed  PubMed Central  Google Scholar 

  61. 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.

    Article  PubMed  Google Scholar 

  62. 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.

    Article  PubMed  PubMed Central  Google Scholar 

  63. 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.

    Article  PubMed  PubMed Central  Google Scholar 

  64. 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.

    Article  PubMed  PubMed Central  Google Scholar 

  65. 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.

    Article  PubMed  Google Scholar 

  66. 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.

    Article  PubMed  Google Scholar 

  67. 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.

    Article  PubMed  Google Scholar 

  68. 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.

    Article  CAS  PubMed  Google Scholar 

  69. 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.

    Article  PubMed  Google Scholar 

  70. 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.

    Article  PubMed  Google Scholar 

  71. 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.

    Article  PubMed  Google Scholar 

  72. 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.

    Article  PubMed  Google Scholar 

  73. 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.

    Article  PubMed  Google Scholar 

  74. 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.

  75. 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.

    Article  PubMed  PubMed Central  Google Scholar 

  76. 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.

    Article  PubMed  Google Scholar 

  77. 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.

    Article  PubMed  Google Scholar 

  78. 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.

    Article  PubMed  Google Scholar 

  79. 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.

    Article  PubMed  Google Scholar 

  80. 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.

    Article  PubMed  Google Scholar 

  81. 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.

    Article  Google Scholar 

  82. 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.

    Article  PubMed  Google Scholar 

  83. 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.

    Article  Google Scholar 

  84. 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.

    Article  PubMed  Google Scholar 

  85. 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.

    Article  PubMed  Google Scholar 

  86. 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.

    Article  PubMed  PubMed Central  Google Scholar 

  87. 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.

Download references

Acknowledgements

We would like to thank Dr. Nicoletta Colombi for her help during the systematic review.

Funding

Not applicable.

Author information

Author notes

  1. Daniele Amparore and Francesco Porpiglia contributed equally to the senior Authorship.

Authors and Affiliations

  1. Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, Strada Provinciale 142, km 3,95, Candiolo, Turin, 10060, Italy

    Enrico Checcucci, Gabriele Volpi, Cecilia Gatti & Paolo Alessio

  2. Department of Urology, Romolo Hospital, Rocca di Neto, Italy

    Alberto Piana & Stefano Alba

  3. Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Turin, Italy

    Alberto Quarà, Sabrina De Cillis, Federico Piramide, Mariano Burgio, Juliette Meziere, Edoardo Cisero, Marco Colombo, Gabriele Bignante, Michele Sica, Stefano Granato, Paolo Verri, Cristian Fiori, Daniele Amparore & Francesco Porpiglia

  4. Dept. of Surgery, Division of Urology, SS Annunziata Hospital, Cosenza, Italy

    Michele Di Dio

Authors
  1. Enrico Checcucci
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Alberto Piana
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Gabriele Volpi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Alberto Quarà
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Sabrina De Cillis
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Federico Piramide
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Mariano Burgio
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Juliette Meziere
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Edoardo Cisero
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Marco Colombo
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Gabriele Bignante
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Michele Sica
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Stefano Granato
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Paolo Verri
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Cecilia Gatti
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Paolo Alessio
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Michele Di Dio
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Stefano Alba
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. Cristian Fiori
    View author publications

    You can also search for this author in PubMed Google Scholar

  20. Daniele Amparore
    View author publications

    You can also search for this author in PubMed Google Scholar

  21. Francesco Porpiglia
    View author publications

    You can also search for this author in PubMed Google Scholar

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

Correspondence to Enrico Checcucci.

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

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.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

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

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s00259-024-06699-6

Keywords

Search

Navigation