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作 者:郑杰 刘东远 张琪[1] 张丽敏[1,2] 高峰 Zheng Jie;Liu Dongyuan;Zhang Qi;Zhang Limin;Gao Feng(College of Precision Instruments and Optoelectronics Engineering,Tianjin University,Tianjin 300072,China;Tianjin Key Laboratory of Biomedical Detecting Techniques and Instruments,Tianjin 300072,China)
机构地区:[1]天津大学精密仪器与光电子工程学院,天津300072 [2]天津市生物医学检测技术与仪器重点实验室,天津300072
出 处:《中国激光》2022年第24期39-45,共7页Chinese Journal of Lasers
基 金:国家自然科学基金(82071971,81871393)。
摘 要:黏膜组织病变的早期诊断和治疗是遏制黏膜组织癌变的有效手段。利用光谱检测技术,以实时、在体、无创的方式检测黏膜组织细胞的形态变化引起的光学特性改变,通过合理算法进行客观分析,可实现低成本大规模黏膜组织病变的筛查。为了提高面向黏膜组织病变诊断的光谱检测系统的灵敏度和特异性,开发了一套亚扩散域漫反射与荧光联合光谱测量系统,实现对不同深度黏膜组织的漫反射光谱和自体荧光光谱的高效采集,进而通过对光谱信息进行特征抽取,实现黏膜组织病变的快速筛查和恶性肿瘤等级的实时诊断。为了评估所开发系统的性能,开展了仿体实验、离体组织实验和在体实验:仿体实验证明了系统具有良好的测量稳定性;离体组织实验证明了该系统对离体组织具有优异的分类能力(不同类型组织的分类精度>98%,同类组织不同部位的分类精度>74%);在体实验初步验证了该系统在黏膜组织诊断和分类领域中的应用潜力。Objective Early-stage detection and treatment of mucosal tissue lesions are effective means for curbing mucosal cancer.H istopathological examination is the gold standard for the clinical examination of mucosal tissue lesions.However,this method is invasive and easily affected by doctors’experience and is unsuitable for large-scale and rapid screening of precancerous lesions.Spectral technologies can detect the changes in optical properties caused by the morphological changes of mucosal tissue cells in a real-time,in vivo,and noninvasive way,and can objectively analyze them using reasonable algorithms,which provides low-cost and large-scale screening of mucosal tissue lesions.In this study,we develop a mucosal lesion diagnosis system using joint sub-diffusive domain diffuse reflectance and fluorescence spectroscopy to improve sensitivity and specificity.The system can efficiently collect diffuse reflectance and autofluorescence spectra of mucosal tissues at varying depths.Furthermore,it extracts the characteristics of spectral data to realize the rapid screening of mucosal lesions and the real-time diagnosis of malignant tumor grade.Methods In this study,the mucosal lesion diagnostic system is composed of a light source module,detection module,m ain control module,man-machine interface module,and an optical fiber probe to measure the joint spectrum signal and real-time analysis and display tissue lesion information.First,we evaluate the stability of the light source module of the system using phantom experiments.Next,the in vitro experiments are conducted to verify the ability of the system to distinguish different tissues,including chicken and pork tissues.In the spectral pretreatment,the spectral data are preprocessed by smoothing and normalization to eliminate the system and environmental noise.Furthermore,the first derivative,principal component analysis,kurtosis,skewness,mean,and variance are used as input information for subsequent tissue classification to extract spectral features and realize the feature
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