Some tumors occur deep inside organs and tissues, covered by a mucosal layer, which makes it difficult for scientists to directly observe them with standard methods like endoscopy or reach them during biopsies.
In particular, gastrointestinal stromal tumors (GISTs)–typically found in the stomach and the small intestines–require demanding techniques that are very time-consuming and prolong the diagnosis. Now, to improve GIST diagnosis, a team of researchers has developed a technology that uses near-infrared hyperspectral imaging (NIR-HSI) along with machine learning.
This technique is a bit like X-rays, the idea is that you use electromagnetic radiation that can pass through the body to generate images of structures inside, they explain, The difference is that X-rays are at 0.01-10 nm, but near-infrared is at around 800-2500 nm. At that wavelength, near-infrared radiation makes tissues seem transparent in images. And these wavelengths are less harmful to the patient than even visible rays.