Does virtual reality in the preoperative setting for colorectal cancer surgery improve patient understanding? A randomised pilot study.

All patients discussed the diagnosis and planned procedure with their colorectal surgeon to sign a standard consent form and discuss trial participation. For all patients, this was the first consultation to discuss surgery for their bowel cancer. During this encounter, the surgeon could use drawings and information sheets to aid discussion but not the patient’s computed tomography (CT) images. Patients were then taken to a separate office by the researcher during the same clinic appointment. In the intervention group, case discussion was done with both 2D CT images and virtual reality (VR) images to allow for comparison. Patients in the intervention group received a brief 2-5 minute orientation regarding the headsets and controllers before being shown 2 different VR models while seated. The first model was a representative model of the large bowel with superimposed bony and skin anatomy created from a de-identified patient CT colonography. This virtual environment allowed patients to orient themselves to key surface and bony anatomy while also learning to use the controllers on instruction from the researcher. The second model was an individualised VR reconstruction created from patient’s own preoperative staging CT scans. Patients had unlimited use of the controllers to scroll through and view the model from all angles in the virtual environment, where key anatomy was pointed out by the researcher who was not in the virtual environment but giving verbal instructions while monitoring the VR environment on a computer screen. On average the intervention group spent 40 minutes with the researcher. To standardise the information given to both trial groups, a checklist of key discussion points was followed including key relational anatomy, tumour location and procedure/complication specific anatomy. Headsets and controllers were wiped down with Tuffie 5 universal sanitising wipes between patients. Image generation To create the VR models, Deidentified Digital Imaging and Communications in Medicine (DICOM) data for each CT were imported into D2P software (3D Systems Inc, Melbourne Aus.) and relevant anatomy segmented using standard software modules and a dedicated Acer Nitro 5 laptop. D2P employs a technique known as image segmentation, which identifies each relevant anatomical structure separately and enables them to be independently rendered. Each individual structure is assigned a unique colour (thereby enhancing visual differentiation), and may also be hidden from view to focus on the most critical structures and relationships. Segmentation of the large bowel on the representative VR model took 12 hours to complete due to the high level of detail achieved.