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首页> 外文期刊>Biosensors & Bioelectronics: The International Journal for the Professional Involved with Research, Technology and Applications of Biosensers and Related Devices >Near-infrared autofluorescence spectroscopy for in vivo identification of hyperplastic and adenomatous polyps in the colon
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Near-infrared autofluorescence spectroscopy for in vivo identification of hyperplastic and adenomatous polyps in the colon

机译:近红外自发荧光光谱法在体内鉴定结肠增生性腺瘤息肉

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摘要

This study reports the implementation of an endoscope-based near-infrared (NIR) autofluorescence (AF) spectroscopy technique for in vivo differentiation of normal, hyperplastic and adenomatous colonic polyps during clinical colonoscopic examination. A total of 198 in vivo NIR AF spectra in the range of 810-1050. nm were acquired from colonic tissues (normal (n=116); hyperplastic (n=48); and adenomatous polyps (n=34)) of 96 patients undergoing colonoscopic screening. Significant differences (p< 0.001, one-way analysis of variance (ANOVA)) in in vivo NIR AF intensity among normal, hyperplastic, and adenomatous polyps are observed. Multivariate statistical techniques, including principal components analysis (PCA) and linear discriminate analysis (LDA) together with the leave-one tissue site-out, cross-validation, were used to develop diagnostic algorithms for distinguishing adenomatous polyps from normal and hyperplastic colonic polyps based on NIR AF spectral features. The PCA-LDA modeling on in vivo colonic NIR AF dataset yields diagnostic sensitivities of 83.6%, 77.1%, and 88.2%; and specificities of 96.3%, 88.0%, and 92.1%, respectively, for classification of normal, hyperplastic and adenomatous colonic polyps. This work suggests that NIR AF spectroscopy associated with PCA-LDA algorithms has potential for in vivo diagnosis and detection of colonic precancer at colonoscopy.
机译:这项研究报告了基于内窥镜的近红外(NIR)自发荧光(AF)光谱技术在临床结肠镜检查过程中体内分化正常,增生性和腺瘤性结肠息肉的技术的实施情况。在810-1050范围内共有198个体内NIR AF光谱。从接受结肠镜检查的96例患者的结肠组织(正常(n = 116);增生性(n = 48);腺瘤性息肉(n = 34))中获取nm。观察到正常,增生性和腺瘤性息肉的体内NIR AF强度存在显着差异(p <0.001,方差分析(ANOVA))。多元统计技术,包括主成分分析(PCA)和线性判别分析(LDA)以及留一法组织定位,交叉验证,被用于开发诊断算法,以区分基于正常和增生性结肠息肉的腺瘤性息肉NIR AF光谱特征。在体内结肠NIR AF数据集上进行PCA-LDA建模可产生83.6%,77.1%和88.2%的诊断敏感性;正常,增生性和腺瘤性结肠息肉分类的特异性分别为96.3%,88.0%和92.1%。这项工作表明,与PCA-LDA算法相关的NIR AF光谱在结肠镜检查中具有对结肠癌的体内诊断和检测的潜力。

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