Clinical trial · Observational
3D Virtual Models as an Adjunct to Preoperative Surgical Planning
Single-site Single-arm Feasibility Study of Patient-specific Interactive 3D Anatomical Models Aimed at Improving Surgery Planning Processes for Complex Renal Cancer Patients
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
This study aims to determine the feasibility of undertaking a future definitive RCT to evaluate the clinical effectiveness of complementing existing medical scans with a patient-specific interactive 3D virtual model of the patient's body to assist the surgeon with planning for the operation in the best way possible. Renal cancer patients receive a tri-phasic CT scan as routine practice, thus if the standard imaging protocols are followed, there should be ample imaging data available for 3D model creation. This study is a single-site, single-arm, unblinded, prospective, feasibility study aiming to recruit 24 participants from the Royal Free Hospital that are scheduled for robotic-assisted partial nephrectomy. Consenting participants will be recruited over a 6-month period, and interactive 3D virtual models of their anatomy will be generated. These models will be used to aid surgeon-patient communications and to plan for the operation. This study will determine whether a definitive RCT of virtual 3D models as an adjunct to surgery planning is feasible with respect to: recruitment of local authorities and patients; ensuring staff can be adequately trained to deliver programmes within specified timeframes; and assessment of the measurability of key surgical outcomes.
Conditions
Conditions (2)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Kidney Neoplasms | Kidney Neoplasm | ONTOLOGY_EXACT | 0.90 |
| Surgical Oncology | — | UNRESOLVED | — |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| 3D-models | Device | — | UNRESOLVED |
Design
Arms and outcomes
Arms (1)
- label
- MIS-PN
- description
- Participants approved for elective robot-assisted partial nephrectomy with T1a or T1b renal tumours.
- interventionNames
- Device: 3D-models
Primary outcomes (1)
- measure
- Study participant recruitment rate as assessed by number of participants divided by the total number of invited eligible patients.
- timeFrame
- 6 months
- description
- Determination of participant recruitment rates of eligible patients to this study. Assessment: ratio of consenting patients to eligible patients
Secondary outcomes (11)
- measure
- Ratio of study participants willing to be randomized.
- timeFrame
- 6 months
- description
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
- Maximum age
- 80 Years
Show eligibility criteria text
Inclusion Criteria: 1. Aged between 18 - 80 years, inclusive; 2. Male and female; 3. Diagnosed with T1a, or T1b renal tumours; 4. Suitable for elective robot-assisted partial nephrectomy; 5. Willing and able to provide written informed consent. Exclusion Criteria: 1. aged \<18 or \>80 years; 2. have had prior abdominal surgery; 3. have had pre-operative imaging that is not adherent to the study protocol; 4. contraindicated for biopsy; 5. do not consent to have biopsy; 6. have a body mass index (BMI) ≥35 kg/m\^2; 7. have a bleeding disorder; 8. have baseline chronic kidney disease (CKD); 9. not fit or do not consent for surgery; 10. chose to have treatment outside the Royal Free Hospital; 11. participation in other clinical studies that would potentially confound this study; 12. unable to understand English; 13. unable to provide consent themselves;
References
Publications (11)
- BACKGROUNDByrn JC, Schluender S, Divino CM, Conrad J, Gurland B, Shlasko E, Szold A. Three-dimensional imaging improves surgical performance for both novice and experienced operators using the da Vinci Robot System. Am J Surg. 2007 Apr;193(4):519-22. doi: 10.1016/j.amjsurg.2006.06.042. PMID 17368303
- BACKGROUNDFan G, Li J, Li M, Ye M, Pei X, Li F, Zhu S, Weiqin H, Zhou X, Xie Y. Three-Dimensional Physical Model-Assisted Planning and Navigation for Laparoscopic Partial Nephrectomy in Patients with Endophytic Renal Tumors. Sci Rep. 2018 Jan 12;8(1):582. doi: 10.1038/s41598-017-19056-5. PMID 29330499
- BACKGROUNDFotouhi J, Alexander CP, Unberath M, Taylor G, Lee SC, Fuerst B, Johnson A, Osgood G, Taylor RH, Khanuja H, Armand M, Navab N. Plan in 2-D, execute in 3-D: an augmented reality solution for cup placement in total hip arthroplasty. J Med Imaging (Bellingham). 2018 Apr;5(2):021205. doi: 10.1117/1.JMI.5.2.021205. Epub 2018 Jan 4. PMID 29322072
- BACKGROUNDHughes-Hallett A, Pratt P, Mayer E, Martin S, Darzi A, Vale J. Image guidance for all--TilePro display of 3-dimensionally reconstructed images in robotic partial nephrectomy. Urology. 2014 Jul;84(1):237-42. doi: 10.1016/j.urology.2014.02.051. Epub 2014 May 22. PMID 24857271
- BACKGROUNDIsotani S, Shimoyama H, Yokota I, China T, Hisasue S, Ide H, Muto S, Yamaguchi R, Ukimura O, Horie S. Feasibility and accuracy of computational robot-assisted partial nephrectomy planning by virtual partial nephrectomy analysis. Int J Urol. 2015 May;22(5):439-46. doi: 10.1111/iju.12714. Epub 2015 Mar 17. PMID 25783817
- BACKGROUNDKhor WS, Baker B, Amin K, Chan A, Patel K, Wong J. Augmented and virtual reality in surgery-the digital surgical environment: applications, limitations and legal pitfalls. Ann Transl Med. 2016 Dec;4(23):454. doi: 10.21037/atm.2016.12.23. PMID 28090510
- Pulijala Y, Ma M, Pears M, Peebles D, Ayoub A. Effectiveness of Immersive Virtual Reality in Surgical Training-A Randomized Control Trial. J Oral Maxillofac Surg. 2018 May;76(5):1065-1072. doi: 10.1016/j.joms.2017.10.002. Epub 2017 Oct 13.