Colorectal cancer is one of the most common cancers accounting for over 16,000 deaths a year in the UK. If detected early, over 90% of patients survive five years from diagnosis, compared to only 6% of those diagnosed with advanced disease. However, only 40% of colorectal cancers are diagnosed at an early stage. The screening techniques are challenging to learn and diagnosis can be missed or delayed because the symptoms of the disease may be similar to other benign coloproctology conditions. As a result, there is a crucial need for improving the training of rectal examination and the use of proctosigmoidoscopy instruments.
This project aims at improving the efficiency of detection and diagnosis of early stage colorectal cancers with the creation of an innovative technology simulated environment based on two distinct aspects. The first one is focused on the sense of touch of the finger when palpating for unsighted cancer cues and the simulation of a wide range of clinical cases. The second one addresses the visual detection of cancer signs with the correct and safe use of proctoscopy and rigid sigmoidoscopy instruments.
We will improve a highly realistic intelligent pelvic/perineum benchtop model with an advanced, active soft robotics system to simulate anal sphincter tone with accurate touch sensations and a wide range of clinical cases. Modified proctoscopy and rigid sigmoidoscopy instruments with integrated motion and force sensors will allow the real-time display and assessment of performance within a bespoke Virtual Reality simulation environment. Integration of a small LCD screen inside the instruments will offer instantaneous, enhanced visualisation of the 3D colorectal anatomy. A library of normal, abnormal and early stage cancer pathologies will be generated through a database of 3D internal anatomy. Rigorous validation studies will determine the effectiveness of the simulator in increasing colorectal cancer diagnostic accuracy and confidence.
The results of this project will be used to improve detection and diagnosis of early stage colorectal cancers through the acquisition of required manipulative and visual identification skills. The work will progress the state-of-the-art in soft-robotics, advanced prosthetics, VR visualisation, high definition displays and real-time image processing techniques to enhance, augment and present the instrument view to the clinician, with the potential to be used in other physical examinations such as functional disorder of female pelvic floor palpation.