Kidney CancerVISPNCT05109182
Virtual 3D Modelling for Improved Surgical Planning of Robotic-assisted Partial Nephrectomy
A study testing Innersight3D in people with Kidney Cancer, run by Innersight Labs Ltd.
Trial summary
To establish whether surgical planning using virtual 3D modelling (Innersight 3D) improves the outcome and cost-effectiveness of RAPN, allowing more patients to benefit from minimally-invasive procedures. Read more about this study
- Who is it for?
- Ages 18 to 80 yearsHealthy volunteers can take part
- Conditions the study is for
- Kidney Cancer
- What is being tested?
- Innersight3D
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 328 participants
- Where
- No sites listed yet
- Study dates
- 1 Jan 2022to 1 Aug 2023
- Phase
- Interventional
- 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
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- Aged 18-80 years; Agreement at Multidisciplinary team meeting that this patient could undergo robotic-assisted partial nephrectomy.
- Willing and able to provide written informed consent. RENAL score (tumour complexity) >= 8. Received contrast enhanced abdominal preoperative CT scan. Ability to understand and speak English.
Who cannot join
- Do not consent for robotic assisted partial nephrectomy; Chose to have treatment outside one of the NHS trial sites. Participation in other clinical studies that would potentially confound this study; Have a horseshoe, a solitary kidney or bilateral kidney tumours; Lack of willingness to allow personal medical imaging data to be used for generating a 3D model;
Trial locations and contacts
No sites are listed yet.
About this study
To establish whether surgical planning using virtual 3D modelling (Innersight 3D) improves the outcome and cost-effectiveness of RAPN, allowing more patients to benefit from minimally-invasive procedures.
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 kidney cancer. Preoperative surgery planning decisions are made by radiologists and surgeons upon viewing CT (Computed Tomography) and MRI (Magnetic Resonance Imaging) 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 a more challenging setting to rectify an unplanned complication than during open surgery (Byrn, et al. 2007). Therefore, better surgical planning tools are essential if we wish to improve patient outcome and reduce the cost of a 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. Once segmented, stereolithography files are generated, which can be used to visualise the anatomy and have the components 3D printed. It has previously been reported that such 3D printed models influence surgical decision-making (Wake, et al. 2017). However, 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 (Western, 2017).
Computational 3D surface-rendered virtual models have become a natural advancement from 3D printed models. In the literature, such models are referred to by a variety of names such as '3D-rendered images', (Zheng, et al. 2016), '3D reconstructions', (Isotani, et al. 2015), or 'virtual 3D models', (Wake, et al. 2017). In this protocol we will use the latter nomenclature.
Previous studies have already shown that surgeons benefit from virtual 3D models in the theatre (Hughes-Hallett, 2014; Fan, et al. 2018; Fotouhi, et al. 2018).
In a previous feasibility study (NIHR21460; IRAS 18/SW/0238), we used state-of-the-art CE marked software, called Innersight3D, to generate interactive virtual 3D models of the patient's unique anatomy from their received CT scans, to provide a detailed roadmap for the surgeon prior to the operation. We found that this approach had a positive influence on surgical decision-making.
RAPN is a rapidly developing surgical field, with robots in 70+ UK surgical centres. The main research question to be addressed in the present study is, whether surgical planning using virtual 3D modelling (Innersight 3D) in a randomised controlled trial, improves the outcome and cost-effectiveness of RAPN.
Patients will potentially benefit from this research for several reasons;
- Due to higher quality surgery and a reduced chance of complications, patients might go home sooner (Shirk, et al. 2018).
- Less likelihood of an unplanned conversion, which is when the surgeon has to abandon the minimally-invasive approach in favour of open surgery during the operation, due to unforeseen anatomical challenges.
- Improved patient empowerment and improved consenting, resulting in better patient decision-making. Our previous feasibility study showed that patients strongly agreed that 3D models improved their understanding of the disease treatment decisions and surgical planning.
- It could also reduce procedure time with less exposure to anesthetic. There are also operational benefits, as these models might improve prediction accuracy of operation complexity and operative time. Thus, surgery list scheduling and hospital-patient flow could be greatly improved. Waiting list could be reduced because of less operations overrun. In addition, surgical team cohesion could also be enhanced. A reduction in theatre time, length-of-stay, would have financial benefits for the health service.
- Conditions
- Kidney Cancer
- Being tested
- Innersight3D
- Medical subject headings
- Kidney Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Innersight3DDevice
Innersight3D generates a virtual interactive 3D model of the CT scan.
| Study group | Role | What they receive |
|---|---|---|
| Intervention (3D model + CT for surgical planning) | Experimental | Patients in this arm will receive a 3D model which will be used in addition to the CT scan for surgical planning. Receives: Device: Innersight3D |
| Control (CT for surgical planning) | No intervention | Patients in this arm will only have the a CT scan used for surgical planning. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Total Console time
This is the time from the start of the robotic operation (arms start moving inside the abdomen) until the end of the robotic operation (arms have been taken out of the abdomen) and will be recorded using the robotic system
Measured: 18 months
Secondary outcomes (16)
Artery preparation time (mins)
Start time: From the point of dissection of gonadal vein. Stop time: As soon as arteries are isolated and ready for clamping.
Measured: 18 months
Tumour preparation time (mins)
Start time: From the point of defatting the kidney (to isolate tumour) Stop time: As soon as the tumour is ready for ultrasound.
Measured: 18 months
Tumour resection time (mins)
Start time: From the point of cutting of tumour Stop: Tumour is removed (excised)
Measured: 18 months
Hilar clamping technique
What clamping technique was used to control blood flow. Choose from [Global ischemia, Selective ischemia, Clampless]
Measured: 18 months
Extirpative technique
What technique was used to remove excise the tumour. Choose from [Enucleation, partial nephrectomyEnucleoresection (resection)] Choose from [Enucleation, partial nephrectomy]
Measured: 18 months
Opened collecting system [yes, no]
Was the collecting system cut open during tumour resection?
Measured: 18 months
Conversion to radical nephrectomy [yes/no]
Measured: 18 months
Clamp time (mins)
Time from when arteries are clamped to time until arteries are unclampsed are taken off. Also known as the warm ischemic time (WIT).
Measured: 18 months
Experience level of surgeon
What is the experience level of the surgeon who is operating? Also were any registrars involved?
Measured: 18 months
Blood loss (ml)
Measured: 18 months
Total Operative time (mins)
From the time that the patient enters the operating theatre to the point of exit, as recorded on the patient notes.
Measured: 18 months
Length of stay (days)
This will be available following hospital discharge. If the patient is not discharged after 4 weeks following the surgery. A maximum length of 28 days should be entered and this along with the reasons should be captured on the adverse events log.
Measured: 18 months
Margin status on histology [positive/negative]
The results from the histology report following the surgery should be recorded.
Measured: 18 months
Post-operative eGFR (ml/min)
Measured 4 weeks after surgery
Measured: 18 months
Post-operative Hemoglobin (g/dL)
Taken 1 day after surgery
Measured: 18 months
Clavien-Dindo Score
Choose option from [Grade I, Grade II, Grade IIIa, Grade IIIb, Grade IVa, Grade IVb]
Measured: 18 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted5 Nov 2021
- Study start1 Jan 2022 (estimated)
- Primary completion1 Aug 2023 (estimated)
- Study completion1 Aug 2023 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Kidney CancerStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Other
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Model description
- This RCT, is a multi-centre main trial and will recruit patients selected for minimally-invasive robotic-assisted renal cancer surgery during the enrolment period. The study will compare current surgical planning method to planning with the addition of virtual 3D models in randomised patient groups. There are no clinical treatment changes/interventions in addition to the standard-of-care procedures. Participants will have 3D models of their anatomy built, clinical team and participant feedback will be obtained in the form of a survey, and the measurability of the key trial outcomes will be assessed as outlined below. Patient participation in the trial is expected to take no longer than 9 weeks, including a 4-week follow-up, from the initial participant information meeting. Methods used to assess outcomes will employ medical data analysis, participant opinion and observational measurements.
- Masking
- Single blind
- Who is masked
- Investigator
- Enrolment
- 328 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Innersight Labs Ltd
- Sponsor type
- Industry (pharma, biotech, devices)
- Collaborators
- Royal Free Hospital NHS Foundation Trust, Frimley Park Hospital NHS Trust, Sheffield Teaching Hospitals NHS Foundation Trust, North Bristol NHS Trust, Guy's and St Thomas' NHS Foundation Trust, King's College London
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05109182
- Sponsor's protocol ID
- 295968
- Acronym
- VISP
- Status last verified
- Oct 2021
- First submitted
- 26 Oct 2021
- Last updated
- 5 Nov 2021
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 5 Nov 2021. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Virtual 3D Modelling for Improved Surgical Planning of Robotic-assisted Partial Nephrectomy
- ClinicalTrials.gov ID
- NCT05109182
- Acronym / sponsor ID
- VISP / 295968
- Conditions
- Kidney Cancer
- Study type
- Interventional
- Recruitment status
- Unknown status
- Enrolment
- 328 participants (estimated)
- Lead sponsor
- Innersight Labs LtdIndustry (pharma, biotech, devices)
- Collaborators
- Royal Free Hospital NHS Foundation Trust, Frimley Park Hospital NHS Trust, Sheffield Teaching Hospitals NHS Foundation Trust, North Bristol NHS Trust, Guy's and St Thomas' NHS Foundation Trust, King's College London
- Study start
- 1 Jan 2022 (estimated)
- Primary completion
- 1 Aug 2023 (estimated)
- Study completion
- 1 Aug 2023 (estimated)
- First posted
- 5 Nov 2021 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
To establish whether surgical planning using virtual 3D modelling (Innersight 3D) improves the outcome and cost-effectiveness of RAPN, allowing more patients to benefit from minimally-invasive procedures.
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 kidney cancer. Preoperative surgery planning decisions are made by radiologists and surgeons upon viewing CT (Computed Tomography) and MRI (Magnetic Resonance Imaging) 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 a more challenging setting to rectify an unplanned complication than during open surgery (Byrn, et al. 2007). Therefore, better surgical planning tools are essential if we wish to improve patient outcome and reduce the cost of a 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. Once segmented, stereolithography files are generated, which can be used to visualise the anatomy and have the components 3D printed. It has previously been reported that such 3D printed models influence surgical decision-making (Wake, et al. 2017). However, 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 (Western, 2017).
Computational 3D surface-rendered virtual models have become a natural advancement from 3D printed models. In the literature, such models are referred to by a variety of names such as '3D-rendered images', (Zheng, et al. 2016), '3D reconstructions', (Isotani, et al. 2015), or 'virtual 3D models', (Wake, et al. 2017). In this protocol we will use the latter nomenclature.
Previous studies have already shown that surgeons benefit from virtual 3D models in the theatre (Hughes-Hallett, 2014; Fan, et al. 2018; Fotouhi, et al. 2018).
In a previous feasibility study (NIHR21460; IRAS 18/SW/0238), we used state-of-the-art CE marked software, called Innersight3D, to generate interactive virtual 3D models of the patient's unique anatomy from their received CT scans, to provide a detailed roadmap for the surgeon prior to the operation. We found that this approach had a positive influence on surgical decision-making.
RAPN is a rapidly developing surgical field, with robots in 70+ UK surgical centres. The main research question to be addressed in the present study is, whether surgical planning using virtual 3D modelling (Innersight 3D) in a randomised controlled trial, improves the outcome and cost-effectiveness of RAPN.
Patients will potentially benefit from this research for several reasons;
- Due to higher quality surgery and a reduced chance of complications, patients might go home sooner (Shirk, et al. 2018).
- Less likelihood of an unplanned conversion, which is when the surgeon has to abandon the minimally-invasive approach in favour of open surgery during the operation, due to unforeseen anatomical challenges.
- Improved patient empowerment and improved consenting, resulting in better patient decision-making. Our previous feasibility study showed that patients strongly agreed that 3D models improved their understanding of the disease treatment decisions and surgical planning.
- It could also reduce procedure time with less exposure to anesthetic. There are also operational benefits, as these models might improve prediction accuracy of operation complexity and operative time. Thus, surgery list scheduling and hospital-patient flow could be greatly improved. Waiting list could be reduced because of less operations overrun. In addition, surgical team cohesion could also be enhanced. A reduction in theatre time, length-of-stay, would have financial benefits for the health service.
Study design
- Primary purpose
- Other
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (investigator)
- Number of arms
- 2
- Model description
- This RCT, is a multi-centre main trial and will recruit patients selected for minimally-invasive robotic-assisted renal cancer surgery during the enrolment period. The study will compare current surgical planning method to planning with the addition of virtual 3D models in randomised patient groups. There are no clinical treatment changes/interventions in addition to the standard-of-care procedures. Participants will have 3D models of their anatomy built, clinical team and participant feedback will be obtained in the form of a survey, and the measurability of the key trial outcomes will be assessed as outlined below. Patient participation in the trial is expected to take no longer than 9 weeks, including a 4-week follow-up, from the initial participant information meeting. Methods used to assess outcomes will employ medical data analysis, participant opinion and observational measurements.
| Arm | Type | Receives |
|---|---|---|
| Intervention (3D model + CT for surgical planning) | Experimental | Device: Innersight3DPatients in this arm will receive a 3D model which will be used in addition to the CT scan for surgical planning. |
| Control (CT for surgical planning) | No intervention | –Patients in this arm will only have the a CT scan used for surgical planning. |
Who may qualify
- Ages
- 18 to 80 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (2 listed)
- Aged 18-80 years; Agreement at Multidisciplinary team meeting that this patient could undergo robotic-assisted partial nephrectomy.
- Willing and able to provide written informed consent. RENAL score (tumour complexity) >= 8. Received contrast enhanced abdominal preoperative CT scan. Ability to understand and speak English.
Key exclusion criteria (1 listed)
- Do not consent for robotic assisted partial nephrectomy; Chose to have treatment outside one of the NHS trial sites. Participation in other clinical studies that would potentially confound this study; Have a horseshoe, a solitary kidney or bilateral kidney tumours; Lack of willingness to allow personal medical imaging data to be used for generating a 3D model;
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Innersight3DInnersight3D generates a virtual interactive 3D model of the CT scan. | Device | Intervention (3D model + CT for surgical planning) |
Primary outcome
Total Console time
Time frame: 18 months
This is the time from the start of the robotic operation (arms start moving inside the abdomen) until the end of the robotic operation (arms have been taken out of the abdomen) and will be recorded using the robotic system
16 secondary outcomes
Artery preparation time (mins)
Time frame: 18 months
Tumour preparation time (mins)
Time frame: 18 months
Tumour resection time (mins)
Time frame: 18 months
Hilar clamping technique
Time frame: 18 months
Extirpative technique
Time frame: 18 months
Opened collecting system [yes, no]
Time frame: 18 months
Conversion to radical nephrectomy [yes/no]
Time frame: 18 months
Clamp time (mins)
Time frame: 18 months
Experience level of surgeon
Time frame: 18 months
Blood loss (ml)
Time frame: 18 months
Total Operative time (mins)
Time frame: 18 months
Length of stay (days)
Time frame: 18 months
Margin status on histology [positive/negative]
Time frame: 18 months
Post-operative eGFR (ml/min)
Time frame: 18 months
Post-operative Hemoglobin (g/dL)
Time frame: 18 months
Clavien-Dindo Score
Time frame: 18 months
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 5 Nov 2021.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Questions about this trial
What is this clinical trial studying?
A study testing Innersight3D in people with Kidney Cancer, run by Innersight Labs Ltd.
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 2 inclusion and 1 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: status not confirmed, as of the sponsor's last update on 5 Nov 2021. Status can change between updates, so confirm with the study contact before making plans.
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?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Lorenz Berger, PhD (07979067365, lorenz@innersightlabs.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Total Console time (time frame: 18 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
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 5 Nov 2021.