Multispectral imaging detects gastritis consistently in mouse model and in humans

Sci Rep. 2020 Nov 18;10(1):20047. doi: 10.1038/s41598-020-77145-4.

Abstract

Gastritis constitutes the initial step of the gastric carcinogenesis process. Gastritis diagnosis is based on histological examination of biopsies. Non-invasive real-time methods to detect mucosal inflammation are needed. Tissue optical properties modify reemitted light, i.e. the proportion of light that is emitted by a tissue after stimulation by a light flux. Analysis of light reemitted by gastric tissue could predict the inflammatory state. The aim of our study was to investigate a potential association between reemitted light and gastric tissue inflammation. We used two models and three multispectral analysis methods available on the marketplace. We used a mouse model of Helicobacter pylori infection and included patients undergoing gastric endoscopy. In mice, the reemitted light was measured using a spectrometer and a multispectral camera. We also exposed patient's gastric mucosa to specific wavelengths and analyzed reemitted light. In both mouse model and humans, modifications of reemitted light were observed around 560 nm, 600 nm and 640 nm, associated with the presence of gastritis lesions. These results pave the way for the development of improved endoscopes in order to detect real-time gastritis without the need of biopsies. This would allow a better prevention of gastric cancer alongside with cost efficient endoscopies.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Disease Models, Animal
  • Female
  • Gastric Mucosa / diagnostic imaging
  • Gastric Mucosa / microbiology
  • Gastric Mucosa / pathology*
  • Gastritis / diagnosis*
  • Gastritis / diagnostic imaging
  • Gastritis / microbiology
  • Helicobacter Infections / complications*
  • Helicobacter Infections / microbiology
  • Helicobacter pylori / isolation & purification*
  • Humans
  • Image Processing, Computer-Assisted / methods*
  • Mice
  • Molecular Imaging / methods*