The Role of 3D Modeling in the Treatment of Renal Tumors

By Akhil Abraham Saji, MD - July 27, 2022

It is estimated that in 2022, nearly 79,000 cases of kidney cancer will be diagnosed in the United States, leading to nearly 14,000 estimated kidney cancer-related deaths.1 Partial nephrectomy is the current preferred modality for treatment of most T1 and T2 renal masses.2 The trifecta of partial nephrectomy—defined as absence of perioperative complications, warm ischemia time <30 minutes (renal artery clamping), and no positive surgical margins—has been found to have equivalent outcomes with robotic, laparoscopic, and open approaches.3 Furthermore, urologists across the world increasingly have been utilizing minimally invasive partial nephrectomy, either robotically or laparoscopically, to reduce the morbidity traditionally associated with open abdominal surgery.

The Benefits of 3D

Use of the robotic option for partial nephrectomy in particular offers surgeons an enhanced 3-dimensional (3D) view of the kidney4 and the tumor in question. To facilitate higher rates and more appropriate use of nephron-sparing techniques such as partial nephrectomy, nomograms such as the PADUA classification system,5 C-index,6 and RENAL Nephrometry score7,8 were created shortly after the mainstream introduction of robotic surgery in the early- to mid-2000s. Such tools have enabled surgeons to better counsel patients on whether nephron-sparing partial nephrectomy would be an option or whether radical nephrectomy is likely to be required.

Moreover, their use has been demonstrated to successfully predict perioperative outcomes. In addition to helping the surgeon classify tumors, patients also can gain a better understanding of the 3D anatomy of their tumors. Silberstein et al demonstrated the value of creating physical models of the tumors to enhance patient understanding.9 In a series of 5 patients, they created physical models of the tumors that were found to be helpful for increasing patients’ understanding of the anatomic and surgical goals of their care.

3D Downsides

Despite these developments, translation of scoring systems into 3D understanding of tumor structure and its relationship to segmental vessels, collecting system involvement, and even live utility during surgery is limited. On a surgical level, until recently, there have been very few tools available to actively assist surgeons in preparing to perform a nephron-sparing partial nephrectomy. This article provides a brief overview of the climate of virtual 3D reconstructions of renal tumors in various settings, including patient counseling prior to surgery, intraoperative assistance, and training of future urologists.

Partial nephrectomy can be an incredibly challenging procedure, depending on the complexity of the tumor as described by a nephrometry score or other scoring systems. Use of virtual reconstructions of the intended renal mass for excision has demonstrated various benefits across several documented studies. For example, in a study of 15 patients undergoing robot- assisted partial nephrectomy (RPNx), the assistance of 3D models within the robotic console facilitated a faster time to identification of the renal vasculature and faster selective clamping of the target artery.10

Providing further support, a large retrospective propensity-matched series compared patients who underwent RPNx with and without 3D model reconstructions. The authors found that patients who had reconstructions completed had a higher rate of partial nephrectomy trifecta, lower rate of postoperative complications, and a closer-to-target estimated glomerular filtration rate.11

The Iris Platform

Another interesting platform that has recently gained momentum is Iris, from Intuitive Surgical, creators of the popular da Vinci robotic surgery platform. Iris functions by providing virtual 3D reconstructions of the tumor in question, allowing the surgeon to plan a surgical approach, review the computed tomography images from the convenience of the robotic console, and even view the virtual model within the robot console using da Vinci TilePro technology. An initial review12 of the Iris technology demonstrated that surgeons found it to be helpful in improving procedure efficiency by up to 73%.

Iris has also shown benefits in improving rates of nephron-sparing surgery. In a recent study of 462 cases using Iris technology, the authors demonstrated that surgeons using the platform were 16.5% more likely to change the procedure from radical nephrectomy to partial nephrectomy after reviewing the Iris 3D reconstruction.13 Similar to Iris, but applicable to all clinicians who review imaging, SYNAPSE VINCENT (Fujifilm Corporation) has also shown promise. In addition to 3D reconstruction, SYNAPSE VINCENT also provides a suite of image analysis products for clinicians to use. A group based in Japan reported success in conducting 26 clampless partial nephrectomies using preoperative planning with SYNAPSE VINCENT software.14

Virtual reality may be the next true foray into 3D reconstruction before surgery. Despite exponential improvements over the past 2 decades, current graphics processing units are not capable of providing the level of performance required to achieve true virtual reality or even augmented reality. It is estimated that the human eye would require nearly 100.8 megapixels per eye for the field of view to achieve true parity with real life.15 Current graphics solutions do not have such capabilities, but it is estimated that they may become realized over the next decade.

Publications on applications of such techniques are sparse compared with the literature on use of 3D reconstruction, but many authors have tried to demonstrate their promise. Shirk et al conducted a randomized clinical trial to investigate the role of virtual reality in patients planned to undergo RPNx using Google Cardboard virtual reality headsets.16 The investigators demonstrated that use of the virtual reality technology demonstrated lower blood loss, warm ischemia time, overall lower operative time, and shorter hospital stay durations.

Potential Limitations

Despite the promising published results supporting use of virtual or augmented reality reconstruction of renal tumors, there are notable limitations to these technologies. The first is the lack of standardization across technologies. For a given modality, whether it be virtual reconstruction or augmented virtual reality, several types of software and reconstruction techniques exist, many of which are proprietary and do not immediately provide insight into how the technology functions.

The second limitation is the lack of a standardized prospective clinical trial to study the benefits of augmenting care for patients with renal masses with virtual reality prohibits the drawing of any strong conclusions. Nevertheless, widespread adoption of 3D reconstruction, regardless of modality, will likely offer some benefits, including providing enhanced guidance to trainees and early career surgeons and giving patients a tool to better understand their planned procedure. This may facilitate enhanced preoperative counseling for patients and help them better understand the risks that surgeons are explaining to them.

Akhil Abraham Saji, MD, is a urology resident at New York Medical College/Westchester Medical Center. His interests include urology education and machine learning applications in urologic care. He is a founding and current member of the EMPIRE Urology New York AUA section team.



  1. American Cancer Society. Key statistics about kidney cancer. Last revised January 12, 2022. https://www.cancer.org/cancer/kidney-cancer/about/key-statistics.html. Accessed June 25, 2022.
  2. National Comprehensive Cancer Network®. NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines®). Kidney cancer. Version 1.2023. June 17, 2022. https://www.nccn.org/professionals/physician_gls/pdf/kidney.pdf. Accessed June 25, 2022.
  3. Mehra K, Manikandan R, Dorairajan LN, Sreerag S, Jain A, Bokka SH. Trifecta outcomes in open, laparoscopy or robotic partial nephrectomy: does the surgical approach matter? J Kidney Cancer VHL. 2019;6(1):8-12. doi:10.15586/jkcvhl.2019.115
  4. Da Vinci Vision. Intuitive website. https://www.intuitive.com/en-us/products-and-services/da-vinci/vision. Accessed June 25, 2022.
  5. Ficarra V, Novara G, Secco S, et al. Preoperative aspects and dimensions used for an anatomical (PADUA) classification of renal tumours in patients who are candidates for nephron-sparing surgery. Eur Urol. 2009;56(5):786-793. doi:10.1016/j.eururo.2009.07.040
  6. Simmons MN, Ching CB, Samplaski MK, Park CH, Gill IS. Kidney tumor location measurement using the C index method. J Urol. 2010;183(5):1708-1713. doi:10.1016/j. juro.2010.01.005
  7. Kutikov A, Uzzo RG. The R.E.N.A.L. nephrometry score: a comprehensive standardized system for quantitating renal tumor size, location and depth. J Urol. 2009;182(3):844-853. doi:10.1016/j.juro.2009.05.035
  8. Ellison JS, Montgomery JS, Hafez KS, et al. Association of RENAL nephrometry score with outcomes of minimally invasive partial nephrectomy. Int J Urol. 2013;20(6):564-570. doi:10.1111/j.1442-2042.2012.03222.x
  9. Silberstein JL, Maddox MM, Dorsey P, Feibus A, Thomas R, Lee BR. Physical models of renal malignancies using standard cross-sectional imaging and 3-dimensional printers: a pilot study. Urology. 2014;84(2):268-272. doi:10.1016/j.urology.2014.03.042
  10. Schiavina R, Bianchi L, Chessa F, et al. Augmented reality to guide selective clamping and tumor dissection during robot-assisted partial nephrectomy: a preliminary experience. Clin Genitourin Cancer. 2021;19(3):e149-e155. doi:10.1016/j.clgc.2020.09.005
  11. Michiels C, Khene ZE, Prudhomme T, et al. 3D-image guided robotic-assisted partial nephrectomy: a multi-institutional propensity score-matched analysis (UroCCR study 51). [Online ahead of print.] World J Urol. 2021. doi:10.1007/s00345-021-03645-1
  12. Ghazi A, Holler T, Frye T, et al. Clinical utility of IRISTM for preoperative surgical planning and intraoperative navigation for robotic-assisted partial nephrectomy (RAPN) cases. J Urol. 2021;206(suppl 3):e1030-e1031. Abstract MP59-04. doi:10.1097/ JU.0000000000002094.04
  13. Gurung PMS, Melnyk R, Holler T, et al. Application of IRIS three-dimensional anatomical models as preoperative surgical planning tools in the management of localized renal masses. J Endourol. 2021;35(3):383-389. doi: 10.1089/end.2020.0405
  14. Komai Y, Sakai Y, Gotohda N, Kobayashi T, Kawakami S, Saito N. A novel 3-dimensional image analysis system for case-specific kidney anatomy and surgical simulation to facilitate clampless partial nephrectomy. Urology. 2014;83(2):500-506. doi:10.1016/j. urology.2013.09.053
  15. Kanter D. Graphics processing requirements for enabling immersive VR. AMD White Paper. 2015:1-12. http://developer.amd.com/wordpress/media/2012/10/gr_proc_req_for_ enabling_immer_VR.pdf. Accessed June 25, 2022.
  16. Shirk JD, Thiel DD, Wallen EM, 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 New Open. 2019;2(9):e1911598. doi:10.1001/ jamanetworkopen.2019.11598
Did you like this article?