Optical diagnosis of gastric tissue biopsies with Mueller microscopy and statistical analysis

Myeongseop Kim (1) , Hee Ryung Lee , Razvigor Ossikovski (1) , Aude Malfait-Jobart (2) , Dominique Lamarque (3) , Tatiana Novikova (1)

1 LPICM - Laboratoire de physique des interfaces et des couches minces [Palaiseau]
2 2I - Infection et inflammation
3 Hôpital Ambroise Paré [AP-HP]

We investigate a possibility of producing the quantitative optical metrics to characterize the evolution of gastric tissue from healthy conditions via inflammation to cancer by using Mueller microscopy of gastric biopsies, regression model and statistical analysis of the predicted images. For this purpose the unstained sections of human gastric tissue biopsies at different pathological conditions were measured with the custom-built Mueller microscope. Polynomial regression model was built using the maps of transmitted intensity, retardance, dichroism and depolarization to generate the predicted images. The statistical analysis of predicted images of gastric tissue sections with multi-curve fit suggests that Mueller microscopy combined with data regression and statistical analysis is an effective approach for quantitative assessment of the degree of inflammation in gastric tissue biopsies with a high potential in clinical applications.

Mots clés: Mueller microscopy Optical anisotropy Statistical image analysis Gastric cancer; Mueller microscopy; Optical anisotropy; Statistical image analysis; Gastric cancer

Domaines: Santé

Myeongseop Kim, Hee Ryung Lee, Razvigor Ossikovski, Aude Malfait-Jobart, Dominique Lamarque, et al.. Optical diagnosis of gastric tissue biopsies with Mueller microscopy and statistical analysis. Journal of the European Optical Society : Rapid publications, 2022, 18 (2), pp.10. ⟨10.1051/jeos/2022011⟩. ⟨hal-04537018⟩