Published online May 16, 2020. doi: 10.4253/wjge.v12.i5.138
Peer-review started: January 29, 2020
First decision: April 12, 2020
Revised: May 8, 2020
Accepted: May 12, 2020
Article in press: May 12, 2020
Published online: May 16, 2020
Processing time: 107 Days and 15.4 Hours
Colonoscopy screening for the detection and removal of colonic adenomas is central to efforts to reduce the morbidity and mortality of colorectal cancer. However, up to a third of adenomas may be missed at colonoscopy, and the majority of post-colonoscopy colorectal cancers are thought to arise from these. Adenomas have three-dimensional surface topographic features that differentiate them from adjacent normal mucosa. However, these topographic features are not enhanced by white light colonoscopy, and the endoscopist must infer these from two-dimensional cues. This may contribute to the number of missed lesions. A variety of optical imaging technologies have been developed commercially to enhance surface topography. However, existing techniques enhance surface topography indirectly, and in two dimensions, and the evidence does not wholly support their use in routine clinical practice. In this narrative review, co-authored by gastroenterologists and engineers, we summarise the evidence for the impact of established optical imaging technologies on adenoma detection rate, and review the development of photometric stereo (PS) for colonoscopy. PS is a machine vision technique able to capture a dense array of surface normals to render three-dimensional reconstructions of surface topography. This imaging technique has several potential clinical applications in colonoscopy, including adenoma detection, polyp classification, and facilitating polypectomy, an inherently three-dimensional task. However, the development of PS for colonoscopy is at an early stage. We consider the progress that has been made with PS to date and identify the obstacles that need to be overcome prior to clinical application.
Core tip: Dye-based chromoendoscopy has a stronger evidence base than existing virtual chromoendoscopy techniques for improving adenoma detection. However, it is inconvenient, and a novel approach is needed. Photometric stereo is a machine vision technique that captures surface normals. It has been applied successfully to colonic tissue and could be utilized in emerging computer-aided adenoma detection algorithms. However, the optimal method for processing specular reflections from colonic mucosa is unknown, and integration into commercial colonoscopy operating systems has not yet been attempted. Although photometric stereo could have a significant impact on colonoscopy in the future, that future remains distant.