ENDOSCOPY/COLONOSCOPY: Stereo endoscopy technique finds lesions invisible to standard colonoscopy

Photometric stereo endoscopy, a new technique developed at Massachusetts Institute of Technology (MIT; Cambridge, MA), promises to improve detection of precancerous lesions in the colon by capturing topographical images along with traditional two-dimensional images. The approach promises to highlight flat lesions and other growths that traditional endoscopy typically misses.

Conventional colonoscopy screening looks for large polyps growing into the lumen of the colon. These growths are fairly easy to see, says Nicholas Durr, a research fellow in the Madrid-MIT M+Vision Consortium in Spain, a community of medical researchers in Boston, MA, and Madrid. But, he explains, recent studies show that nonpolypoid lesions can also lead to cancer.

Photometric stereo imaging "reads" the topography of a surface by measuring distances between it and multiple light sources. It uses those distances to calculate the slope of the surface relative to the light source, and to generate a 3D map showing bumps and other surface features. But in colonoscopy it is impossible to know the precise distance between the endoscope's tip and the colon's surface, so the researchers had to modify the original technology.

The researchers built two prototypes—one the size of a typical colonoscope (14 mm in diameter) and one larger (35 mm)—and found that in tests with an artificial colon, both could create 3D representations of polyps and flatter lesions.

The technology could be easily added to contemporary devices because many existing colonoscopes already have multiple light sources, says Durr. "From a hardware perspective, all they need to do is alternate the lights and then update their software to process this photometric data."

The researchers plan to test the technology in human patients in clinical trials at Massachusetts General Hospital (MGH; Boston, MA) and the Hospital Clinico San Carlos in Madrid. They are also working on additional computer algorithms that could help to automate the process of identifying polyps and lesions from the topographical information generated by the new system.

1. V. Parot et al., J. Biomed. Opt., 18, 7, 076017 (2013); doi:10.1117/1.jbo.18.7.076017.