Photonic Data Science

The present study reports about a Raman microspectroscopic characterization of the inflammatory bowel diseases Crohn’s disease and ulcerative colitis. Therefore, Raman maps of human colon tissue sections were analyzed by utilizing innovative chemometric approaches: first support vector machines were applied to highlight the tissue morphology (= Raman spectroscopic histopathology). In a second step the biochemical tissue composition has been studied by analyzing the epithelium Raman spectra of sections of healthy controls (n=11), Crohn’s disease (n=14) and ulcerative colitis (n=13). These three groups exhibit significantly different molecular specific Raman signatures allowing to establish a classifier (support-vectormachine). By utilizing this classifier it was possible to separate between healthy controls, Crohn’s disease and ulcerative colitis with an accuracy of 98.90%. The automatic design of both classification steps (visualization of the tissue morphology and molecular classification of inflammatory bowel diseases) paves the way for an objective clinical diagnosis of inflammatory bowel diseases by means of Raman spectroscopy in combination with chemometric approaches.