3D Virtual Models as an Adjunct to Preoperative Surgical Planning
Condition: Kidney Neoplasms; Surgical Oncology
MeSH terms: Kidney Neoplasms
Study type: Observational

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. 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.
    

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.
    

Intervention name(s): 3D-models
Intervention type(s): Device
Intervention description(s): 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
Observational model: Cohort
Time perspective: Prospective
Sampling method: Non-Probability Sample
Study population: 
        This study concerns patients that have been selected for minimally invasive renal cancer
        surgery at the Royal Free Hospital.