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Kidney NeoplasmsNCT03606044

3D Virtual Models as an Adjunct to Preoperative Surgical Planning

An observational study of Kidney Neoplasms and Surgical Oncology, run by Dr Eoin R Hyde at 1 site in United Kingdom.

Completed

Finished. The study has ended and is not enrolling. Results may be posted on the official record.

Official record
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Trial summary

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. Read more about this study

Who is it for?
Ages 18 to 80 years
Conditions the study is for
Kidney Neoplasms, Surgical Oncology
What is being tested?
3D-models
Type of treatment
Medical device
How many people
24 participants
Where
1 siteUnited Kingdom
Study dates
1 May 2019to 31 Aug 2019
Phase
Observational
Are there results?
None posted in the registry

Key requirements

Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.

  • Ages 18 to 80 years
  • All sexes
  • No healthy volunteers
  • Adult, Older adult

Study population: This study concerns patients that have been selected for minimally invasive renal cancer surgery at the Royal Free Hospital.

Who may be able to join

  • Aged between 18 - 80 years, inclusive;
  • Male and female;
  • Diagnosed with T1a, or T1b renal tumours;
  • Suitable for elective robot-assisted partial nephrectomy;
  • Willing and able to provide written informed consent.

Who cannot join

  • aged <18 or >80 years;
  • have had prior abdominal surgery;
  • have had pre-operative imaging that is not adherent to the study protocol;
  • contraindicated for biopsy;
  • do not consent to have biopsy;
  • have a body mass index (BMI) ≥35 kg/m^2;
Show all 13Show fewer
  • have a bleeding disorder;
  • have baseline chronic kidney disease (CKD);
  • not fit or do not consent for surgery;
  • chose to have treatment outside the Royal Free Hospital;
  • participation in other clinical studies that would potentially confound this study;
  • unable to understand English;
  • unable to provide consent themselves;

Trial locations and contacts

1 site in 1 country.

United Kingdom1 site

  • Royal Free London NHS Foundation Trust

    London, NW3 2QG

Other trials in United Kingdom

About this study

Official title: Single-site Single-arm Feasibility Study of Patient-specific Interactive 3D Anatomical Models Aimed at Improving Surgery Planning Processes for Complex Renal Cancer Patients

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.

Read the detailed description

Surgery is the mainstay treatment for abdominal cancer, resulting in over 50,000 surgeries annually in the UK, with 10% of those being for renal cancer. Preoperative surgery planning decisions are made by radiologists and surgeons upon viewing CT and MRI scans. The challenge is to mentally reconstruct the patient's 3D anatomy from these 2D image slices, including tumour location and its relationship to nearby structures such as critical vessels. This process is time consuming and difficult, often resulting in human error and suboptimal decision-making. It is even more important to have a good surgical plan when the operation is to be performed in a minimally-invasive fashion, as it is more challenging setting to rectify an unplanned complication than during open surgery. Therefore, better surgical planning tools are essential if one is to improve patient outcome and reduce the cost of surgical misadventure.

To overcome the limitations of current surgery planning in a soft-tissue oncology setting, dedicated software packages and service providers have provided the capability of classifying the scan voxels into their anatomical components in a process known as image segmentation (see Section 6.1 for more information). Once segmented, stereolithography files are generated which can be used to visualise the anatomy and have the components 3D printed. It has previously been shown that such 3D printed models influence surgical decision-making. However, the relevance of a physical model to plan for a minimally invasive surgical approach is debatable, and the financial and administrative costs of obtaining accurate 3D printed models for routine surgery planning has been speculated to be holding back 3D printed models from breaking into regular clinical usage.

As a necessary precursor to 3D printed models, computational 3D surface-rendered virtual models could be used by the urologist to assist with clinical decision-making. In the literature, such models are referred to by a variety of names such as '3D-rendered images', '3D reconstructions', or 'virtual 3D models'. In this protocol, the investigators will use the latter nomenclature. Virtual 3D models provide many of the advantages of their physical 3D printed counterpart without the challenge of the printing process, they can be easily viewed on standard digital devices such as laptops or smartphones and can be simultaneously viewed and interacted with from anywhere in the world, which could help with collaborative surgery planning between centres. Note that this study's use of virtual 3D models is not to be confused with Virtual-Reality visualisation, which is an immersive environment and currently requires specialist equipment. In support of this study, previous pioneering studies have already shown that surgeons benefit from computational 3D models in the theatre. However, in addition to the available 2D medical images (CT, MRI, volume-rendered images), it has not been shown that virtual 3D models, constructed from the same existing medical scan data, would influence the surgical decision-making process or alter surgeon confidence in their decisions. Crucially, it also remains to be shown that such 3D models can be built reliably and at scale to facilitate their widespread adoption.

Being tested
3D-models
Medical subject headings
Kidney Neoplasms

What participants receive

What participants receive. In a randomised study each person is assigned to one group by chance.

  • 3D-modelsDevice

    The study radiologist will generate a patient-specific virtual 3D model of the participant's body from their pre-operational medical scans (CT, and MRI if available) using regulated commercial medical image analysis software, specifically Osirix MD 9.0 (Pixmeo, Geneva, Switzerland).(Rosset et al. 2004)

    The CRFw checks that the medical scan segmentation is accurate and validates the virtual 3D model.

    The surgeon checks that the medical scan segmentation is accurate and validates the virtual 3D model.

    The surgeon uses all available medical scan data, and the virtual 3D model as an adjunct, to assess the patient anatomy and plan the operation accordingly

Study groups in NCT03606044
Study groupRoleWhat they receive
MIS-PNParticipants approved for elective robot-assisted partial nephrectomy with T1a or T1b renal tumours.
Receives: Device: 3D-models

What is being measured

The primary outcome is the main question the study is designed to answer.

  1. Study participant recruitment rate as assessed by number of participants divided by the total number of invited eligible patients.

    Determination of participant recruitment rates of eligible patients to this study.

    Assessment: ratio of consenting patients to eligible patients

    Measured: 6 months

Secondary outcomes (11)

  1. Ratio of study participants willing to be randomized.

    Determination of the willingness of eligible patients to be randomised (although this is a single-arm study and no randomisation will occur, this is an important outcome for future study design); Assessment: ratio of consenting patients that are favourable to randomisation to non-favourable

    Measured: 6 months

  2. Time spent by surgeons in pre-operative planning.

    Determination of the time spent by surgeons in pre-operative planning using the 3D model building software.

    Assessment: Recording of time spent planning

    Measured: 6 months

  3. Practicality of delivering the patient-specific 3D model to the Operating Room.

    Determination of the practicality of delivering the patient-specific 3D model to the Operating Room visualisation device.

    Assessment: Recording whether the 3D model was available for surgeon reference throughout the operation

    Measured: 6 months

  4. Surveying patient opinion on the usefulness of 3D models.

    Determination of patient opinion on the usefulness of 3D models for improved understanding of the potential risks and benefits involved in their upcoming operation.

    Assessment: The patient will be asked a single qualitative question to assess their opinion on the use of 3D models: "With regards to your understanding of the potential risks and benefits of your upcoming operation, do you feel that the additional use of 3D virtual models - decreased your understanding, made no difference to your understanding, or improved your understanding?"

    Measured: 6 months

  5. Feasibility of measuring of peri-operative operation time.

    Measurability of peri-operative operation time from first incision to last suture.

    Assessment: Ability to record the operation time in seconds.

    Measured: 6 months

  6. Feasibility of measuring of peri-operative acute haemorrhage events.

    Measurability of peri-operative number of acute haemorrhage events.

    Assessment: Ability to record the number of acute haemorrhage events.

    Measured: 6 months

  7. Feasibility of measuring of peri-operative blood loss.

    Measurability of peri-operative blood loss.

    Assessment: Ability to record the blood loss in millilitres.

    Measured: 6 months

  8. Feasibility of measuring of peri-operative number of transfusion events.

    Measurability of peri-operative number of transfusion events.

    Assessment: Ability to record the number of transfusion events.

    Measured: 6 months

  9. Feasibility of measuring of post-operative number of haemorrhage events.

    Measurability of post-operative number of haemorrhage events.

    Assessment: Ability to record the number of post-operative haemorrhage events (up to seven days post-operation).

    Measured: 6 months

  10. Feasibility of measuring of post-operative participant length-of-stay in hosital.

    Measurability of post-operative participant length-of-stay in hosital.

    Assessment: Ability to record the participant length-of-stay in hosital in days.

    Measured: 6 months

  11. Feasibility of measuring of post-operative number of surgical site infection events.

    Measurability of post-operative number of surgical site infection events.

    Assessment: Ability to record the number of surgical site infection events (up to seven days post-operation).

    Measured: 6 months

Timeline

From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.

  1. First posted30 Jul 2018
  2. Study start1 May 2019
  3. Primary completion31 Jul 2019
  4. Study completion31 Aug 2019

Resources

More details

For doctors and researchers: how the study is designed, who runs it, and its registry IDs.

Study design
Study type
Observational
Observational model
Cohort
Time perspective
Prospective
Enrolment
24 participants (actual)
IDs, dates and publications
ClinicalTrials.gov ID
NCT03606044
Sponsor's protocol ID
11605
Status last verified
Feb 2020
First submitted
10 Jul 2018
Last updated
12 Feb 2020
Results posted
No
Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
Individual data sharing
No

Publications

  • Byrn 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.

    PubMed 17368303

  • Fan 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.

    PubMed 29330499

  • Fotouhi 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.

    PubMed 29322072

  • Hughes-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.

    PubMed 24857271

  • Isotani 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.

    PubMed 25783817

  • Khor 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.

    PubMed 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.

    PubMed 29104028

  • Rosset A, Spadola L, Ratib O. OsiriX: an open-source software for navigating in multidimensional DICOM images. J Digit Imaging. 2004 Sep;17(3):205-16. doi: 10.1007/s10278-004-1014-6. Epub 2004 Jun 29.

    PubMed 15534753

  • Wake N, Rude T, Kang SK, Stifelman MD, Borin JF, Sodickson DK, Huang WC, Chandarana H. 3D printed renal cancer models derived from MRI data: application in pre-surgical planning. Abdom Radiol (NY). 2017 May;42(5):1501-1509. doi: 10.1007/s00261-016-1022-2.

    PubMed 28062895

  • Weston MJ. Virtual special issue: renal masses. Clin Radiol. 2017 Oct;72(10):826-827. doi: 10.1016/j.crad.2017.06.011. Epub 2017 Jul 14. No abstract available.

    PubMed 28716212

  • Zheng YX, Yu DF, Zhao JG, Wu YL, Zheng B. 3D Printout Models vs. 3D-Rendered Images: Which Is Better for Preoperative Planning? J Surg Educ. 2016 May-Jun;73(3):518-23. doi: 10.1016/j.jsurg.2016.01.003. Epub 2016 Feb 6.

    PubMed 26861582

Questions about this trial

What is this clinical trial studying?

An observational study of Kidney Neoplasms and Surgical Oncology, run by Dr Eoin R Hyde at 1 site in United Kingdom.

The full registered description is in the About this study section and the official record.

Who may be eligible to take part?

The sponsor lists 5 inclusion and 13 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.

Is this clinical trial currently recruiting?

The record says: finished, as of the sponsor's last update on 12 Feb 2020. Status can change between updates, so confirm with the study contact before making plans.

Where is the study taking place?

The record lists 1 site in United Kingdom. Whether a site is taking part right now should be confirmed with that site. See every site.

What are the possible benefits and risks?

They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.

Are results available for this study?

The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.

How can a doctor refer a patient or contact the research team?

The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.

What does the primary outcome measure?

Study participant recruitment rate as assessed by number of participants divided by the total number of invited eligible patients. (time frame: 6 months). It is what the study was designed to measure, not a finding.

Where can I read the original study information?

On the ClinicalTrials.gov record for NCT03606044, which also lists 11 linked publications.

Does a listing mean the treatment is approved or proven to work?

No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.

How often is this information updated?

AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 12 Feb 2020.

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