University Hospital Jena, Department of Internal Medicine II, Division of Gastroenterology, Hepatology, and Infectious Diseases, Jena, Germany.
J Biomed Opt. 2012 Jul;17(7):076030. doi: 10.1117/1.JBO.17.7.076030.
We report on a Raman microspectroscopic characterization of the inflammatory bowel diseases (IBD) Crohn's disease (CD) and ulcerative colitis (UC). 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 control subjects (n=11), subjects with CD (n=14), and subjects with UC (n=13). These three groups exhibit significantly different molecular specific Raman signatures, allowing establishment of a classifier (support-vector-machine). By utilizing this classifier it was possible to separate between healthy control patients, patients with CD, and patients with UC with an accuracy of 98.90%. The automatic design of both classification steps (visualization of the tissue morphology and molecular classification of IBD) paves the way for an objective clinical diagnosis of IBD by means of Raman spectroscopy in combination with chemometric approaches.
我们报告了对炎症性肠病（IBD）克罗恩病（CD）和溃疡性结肠炎（UC）的拉曼光谱学特征的研究。因此，我们利用创新的化学计量学方法分析了人类结肠组织切片的拉曼图谱。首先，我们应用支持向量机突出组织形态（=拉曼光谱组织病理学）。在第二步中，我们通过分析健康对照组（n=11）、CD 组（n=14）和 UC 组（n=13）患者切片的上皮拉曼光谱来研究组织的生化组成。这三组表现出明显不同的分子特异性拉曼特征，允许建立一个分类器（支持向量机）。利用这个分类器，我们可以将健康对照组、CD 组和 UC 组患者准确地区分开来，准确率为 98.90%。这两个分类步骤（组织形态的可视化和 IBD 的分子分类）的自动设计为通过拉曼光谱结合化学计量学方法对 IBD 进行客观的临床诊断铺平了道路。
