机构地区:[1]长春理工大学电子信息工程学院,吉林长春130022 [2]长春理工大学光电工程学院,吉林长春130022 [3]长春理工大学中山研究院,广东中山528437 [4]南方医科大学中西医结合医院耳鼻喉科,广东广州510315 [5]广州中医药大学附属中山中医院病理科,广东中山528400
出 处:《光谱学与光谱分析》2025年第4期941-946,共6页Spectroscopy and Spectral Analysis
基 金:国家重点研发计划政府间国际科技创新合作项目(2023YFE0108800)资助。
摘 要:鼻咽癌是一种多发于鼻咽腔顶部和侧壁的恶性肿瘤,我国南方地区较为高发,早期治疗对提高患者生存率至关重要。由于其发病位置隐蔽,早期症状类似于鼻部炎症性疾病,容易被忽视,被发现时往往已经处于中晚期。近年来,太赫兹技术因其具有低能量、强穿透和指纹谱等特性,在生物医学癌症检测领域备受关注。以鼻咽癌组织和鼻咽炎组织为研究对象,初步探索太赫兹光谱技术在鉴别鼻咽癌与鼻咽炎症方面的应用。采用太赫兹时域光谱系统采集鼻咽组织在0.6~5.0 THz范围内的光谱,通过参数提取到其吸收光谱,基于光谱数据分析对比鼻咽癌组织与鼻咽炎组织的频谱特征,结合病理学苏木精-伊红(H&E)染色结果图分析两种鼻咽组织的光谱差异来源。采用主成分分析(PCA),对实验采集到的原始功率谱数据进行降维和特征提取,获得样品在第一、二、三主成分构成的三维坐标空间中的散点图。基于该散点图的分析,可以观察到鼻咽癌组织与鼻咽炎组织在特征空间中的显著区分。结果表明,在1.3~3.4 THz内,鼻咽癌组织对太赫兹波的吸收明显高于鼻咽炎组织,2.7 THz是鉴别鼻咽癌组织与鼻咽炎组织的最佳潜在诊断频率。通过主成分分析进一步降维处理,前4个主成分的累计方差贡献率达到了87.45%,对两组鼻咽组织样品具有良好的聚类作用,主成分散点图可以明显区分鼻咽癌组织与鼻咽炎组织。结合K-最近邻算法(KNN)和支持向量机(SVM)构建分类模型,实现了对两种鼻咽组织太赫兹光谱的鉴别分类。相比KNN算法,SVM分类模型的平均分类准确率达到92%。本研究初步验证了太赫兹光谱技术用于鉴别鼻咽癌与鼻咽炎症的有效性,为进一步探讨其临床价值奠定了基础。Early treatment is essential to improve the survival rate of patients.However,due to its hidden location and early symptoms similar to nasal inflammatory diseases,it is easy to ignore,and it is often found in the middle and late stages.In recent years,terahertz technology has attracted much attention in biomedical cancer detection due to its low energy,strong penetration,and fingerprint spectrum characteristics.In this study,nasopharyngeal carcinoma(NPC)and nasopharyngitis tissues were taken as the research objects to explore the application value of terahertz spectroscopy in the differential diagnosis of nasopharyngeal carcinoma and nasopharyngitis.The terahertz time-domain spectroscopy system was used to collect the spectrum of nasopharyngeal tissues in the range of 0.6~5.0 THz,and the absorption spectrum was obtained by parameter extraction.Based on the spectral data,the spectral characteristics of NPC and nasopharyngitis tissues were analyzed and compared.The spectral difference source between the two nasopharyngeal tissues was combined with the pathological H&E staining results.Through the application of the principal component analysis(PCA)method,the original power spectrum data collected in experiments were reduced.The features were extracted,and the scatter plot of samples in the three-dimensional coordinate space composed of the first,second,and third principal components was obtained.Based on the analysis of this scatter plot,a significant differentiation between NPC tissues and nasopharyngitis tissues in the feature space can be observed.The results show that the absorption of terahertz wave in NPC tissue is significantly higher than that in nasopharyngitis tissue in the range of 1.3 to 3.4 THz,and 2.7 THz is the best potential diagnostic frequency to distinguish NPC tissue from nasopharyngitis tissue.After further dimensionality reduction by principal component analysis,the cumulative variance contribution rate of the first four principal components reached 87.45%,which had a good clustering effect on
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