肿瘤周边组织拉曼光谱的模糊模式识别研究

基于模糊模式识别的基本理论,阐述了肿瘤周边组织拉曼光谱的预处理、特征提取和选择,根据这些特征改进了梯形分布的偏大型隶属函数,在40例样本的基础上建立了肿瘤周边组织拉曼光谱对恶性肿瘤的隶属函数,并根据此函数进行了分类器的训练学习,经过另40例样本的测试,恶性肿瘤的识别率为82.4%,非恶性肿瘤的识别率为73.9%,识别效果较为理想.     

光敏剂CPD4对肿瘤组织DNA损伤的拉曼光谱研究

观测了小牛胸腺DNA、腹水型S_(180)肿瘤组织DNA以及光敏剂CPD_4对肿瘤组织DNA损伤的拉曼光谱。肿瘤组织DNA是分别从注射了光敏剂和生理盐水的荷瘤小鼠的肿瘤中提取的。实验结果表明,肿瘤组织DNA的拉曼光谱与正常组织DNA的有所差异,最明显的是脱氧核糖的特征谱线在正常组织DNA拉曼光谱中出现而在肿瘤组织DNA中却几乎消失或变为很弱的小峰。这些差异可作为肿瘤早期诊断的参考。实验结果还表明,光敏剂对肿瘤组织DNA各碱基产生不同程度的破坏,在DNA修复酶的作用下,可使脱氧核糖和鸟嘌呤得到修复。     

人乳腺癌组织阵列拉曼谱的模型成像研究

测量了人体乳腺管正常上皮组织及浸润性导管癌组织的阵列(Mapping)拉曼谱;利用作者前期建立的人体乳腺组织拉曼光谱模型,拟合了这些阵列谱,并将得到的归一化的拟合系数映射为灰度值,构建了乳腺组织的阵列拉曼谱模型成像。结果表明,这种模型成像具有较为明确的意义,尤其是细胞质、DNA、细胞间质基谱的拟合系数成像,较为清晰地呈现肌动蛋白、DNA及胶原的空间分布特征以及组织形态结构。与相关系数成像比较,模型成像给出了相似的结果。但模型成像对生化物质含量更敏感,成像分辨率更高。模型成像还显示癌变组织中细胞核明显增大、与细胞质相对比例明显增高,并为发展乳腺肿瘤拉曼诊断方法提供实验依据。     

膀胱肿瘤离体组织的拉曼光谱学研究

使用激光共聚焦显微拉曼光谱仪测取膀胱肿瘤和正常膀胱组织的拉曼特征谱,应用主成分分析/支持向量机(principal component analysis,PCA/support vector machines,SVM)分类器对数据进行判别分析,最后使用弃一交叉验证法(leave-one-out cross validation,LOOCV)测试判别结果的准确度。结果发现膀胱肿瘤组织与正常膀胱组织的拉曼光谱存在明显差异,肿瘤组织在782和1 583cm-1等核酸特征谱带处峰高显著增强,而正常组织在1 061,1 295,2 849,2 881cm-1等蛋白质和脂质特征谱带处峰高显著增强。PCA/SVM可良好区分膀胱肿瘤组织和正常膀胱组织的拉曼光谱,LOOCV测试分类器显示肿瘤诊断的敏感度86.7%、特异度87.5%、阳性预测值92.9%、阴性预测值77.8%。由此得出结论:拉曼光谱可以良好诊断膀胱肿瘤的体外组织,展现了优越的临床应用前景。     

拉曼光谱检测生物大分子损伤的研究进展

拉曼光谱是基于拉曼散射效应而发展起来的一种光谱分析技术,体现的是分子的振动或转动信息。由于拉曼光谱技术与常规化学分析技术相比,具有对样品无损、样品制备简单和所需样品量少等特点,广泛用于生物大分子结构变化的研究。拉曼光谱不仅可以用于蛋白质、核酸和脂类等生物大分子损伤的快速检测,而且可以用于癌症的诊断与手术治疗。通过对比正常组织与癌变组织的拉曼光谱,可以找到两种组织特征吸收峰的差异,从而为癌症的最终确诊和确定肿瘤切除范围提供重要信息。文章综述了拉曼光谱检测生物大分子损伤的研究进展,介绍了利用表面增强拉曼光谱、傅里叶变换拉曼光谱和紫外共振拉曼光谱等技术在检测蛋白质二级结构、膜脂及DNA损伤中的应用,并展望了未来拉曼光谱技术的发展前景。     

人体肿瘤组织的拉曼光谱相关系数成像

运用逐点扫描(Scanning)采谱技术,测量了人体乳腺肿瘤组织的阵列拉曼光谱集(Mapping);利用自编的软件,分析和计算了该谱集与参考谱DNA、细胞质等拉曼谱的相关系数;并将其映射为灰度值,构建了点阵的相关系数成像。结果表明,相关系数成像较好地反映了参考谱所代表的生化成分的分布;DNA谱与组织中其他成分谱的相关性很小,因此DNA谱的相关系数成像能够直接地反映成像区域DNA的分布,可信度尤其高。该研究结果为进一步研究乳腺肿瘤的拉曼诊断方法奠定了一定基础。     

乳腺组织形态基元共焦显微拉曼光谱的研究

利用共焦显微拉曼方法,测定了乳腺组织切片的Mapping拉曼谱,光谱采样体积达到μm尺度.通过对这些共焦拉曼谱与商业提纯肌动蛋白、胶原等生化物质做出的谱的分析比较,分离出了来自细胞质、细胞间质、脂肪以及乳腺沉积物这些组织形态基元的拉曼谱;用K阶簇分析方法,还获得了细胞核基元谱;基元谱与提纯化学物质谱的相关分析印证了组织形态基元谱的来源.还分析总结了这些组织形态基元谱的特征.这些工作为深入理解组织形态与其拉曼谱的关系以及乳腺组织形态拉曼模型的建立奠定了基础.     

衰减全反射红外光谱用于人乳腺癌组织的研究

通过对32例人乳腺良、恶性肿瘤的衰减全反射红外光谱的对比研究发现,它们之间存在明显而规律的光谱差异,反映了乳腺良、恶性病变组织中,蛋白质、核酸和脂类等生物大分子的构型与构象以及相对含量上的差别.研究表明:傅里叶变换红外光谱可以从分子水平上揭示良、恶性肿瘤的分子结构信息,极有潜力成为一种临床原位诊断肿瘤的新方法.     

拉曼光谱技术在病理诊断中的研究进展

拉曼光谱技术能够提供与物质特定分子结构相关的光谱信息,可用于识别生物组织微小的生化变异,具有快速、实时、无损、无需样本预处理等优点,在临床病理诊断领域极具应用前景。与常规组织病理学分析相比,拉曼光谱技术能够直接检测活体组织,简化了分析程序,缩短了诊断时间。人体病变组织的细胞分子组成和结构可能发生变化,这为拉曼光谱技术在组织病理诊断中的应用提供了检测依据。基于组织分子组成与结构的差异,结合机器学习和化学计量学方法,拉曼光谱技术可以提供客观的诊断信息,实现快速、低侵入的病理诊断。回顾了近十年来拉曼光谱技术在组织病理诊断中的研究进展,对取得的关键成果进行了总结,阐述了当前离体和活体应用拉曼光谱技术的一些关键问题。针对离体拉曼光谱检测,重点评估福尔马林固定石蜡包埋样本、冷冻样本和新鲜组织样本等离体样本的适用情况;阐述拉曼光谱数据收集的关键技术,包括适用光源、光谱范围,以及病理样本光谱采集的方式等。对于活体拉曼光谱检测,重点介绍了活体检测研究中拉曼光谱技术应用的两种形式：结合医用内窥镜进行体内检测,以及开放手术中的直接检测;综述了临床适用的拉曼系统,重点介绍了当前活体拉曼研究中应用的光纤探头。同时,文章也讨论了拉曼光谱数据的处理与分析方法,通过光谱预处理,特征提取与分类识别,构建拉曼光谱病理诊断模型,在小样本范围能够获得较好的诊断结果。考虑临床实际应用,仍需要不断优化分析方法,实现拉曼光谱与生化信息的关联,将样本个体差异的影响纳入分类模型中,以提升模型性能。文章对拉曼光谱应用于病理诊断中的关键问题进行了讨论,为进一步开展研究提供参考。未来需要更深入和广泛地开展离体和活体研究,以促进拉曼光谱技术在临床中的应用。     

基于拉曼光谱和多元统计分析技术的结肠癌早期诊断

为了寻找结肠癌的病理发展规律在拉曼光谱属性上的体现,采用共聚焦显微拉曼光谱仪对60例离体的正常结肠组织、腺瘤性息肉和腺癌组织的近红外拉曼光谱进行对比检测,初步探讨了三类组织的拉曼光谱特征及其改变的规律。结果表明:三类组织拉曼光谱的差异明显存在于830,855,1 032,1 210,1 323,1 335,1 445,1 450,1 655 cm^-1处,腺瘤性息肉的光谱大体位于正常组织与腺癌组织之间。以组织病理诊断为金标准,主成分分析结合线性判别分析技术建立的诊断算法区分3类组织的灵敏度分别为96.9%、85.7%和97.3%,特异性分别为82.8%、90%和92.3%。因此,拉曼光谱有潜力在分子水平上区分正常结肠组织、腺瘤性息肉和腺癌组织,有望成为结肠癌早期诊断的一种有效方法。     

乳腺组织的拉曼光谱线性模型研究

本研究甄选10个代表乳腺组织拉曼活性成分的基谱,在国内首次构建一种乳腺组织拉曼谱的线性回归模型。用2 000多个正常和非正常乳腺组织拉曼谱对该模型进行统计检验,模型显著性F检验的置信度全部为1,多元决定系数的平均值为0.95,表明线性模型假设成立、拟合效果良好。10个基谱代表脂肪、细胞质、细胞间质、DNA、血液、β-胡萝卜素、胆固醇等的拉曼谱,基谱的归一化拟合系数间接反映出这些成分的相对含量。用该模型拟合正常和肿瘤乳腺组织的拉曼宏观谱,病变前后细胞质和DNA的拟合系数增大、脂肪拟合系数减小,这反映出它们相对含量的增减,与已知的病理学结果一致。该研究有助于理解乳腺肿瘤组织的生化变化,并可能为分析该变化提供了有效手段。     

Diffusion-weighted MRI: influence of intravoxel fat signal and breast density on breast tumor conspicuity and apparent diffusion coefficient measurements

Promising recent investigations have shown that breast malignancies exhibit restricted diffusion on diffusion-weighted imaging (DWI) and may be distinguished from normal tissue and benign lesions in the breast based on differences in apparent diffusion coefficient (ADC) values. In this study, we assessed the influence of intravoxel fat signal on breast diffusion measures by comparing ADC values obtained using a diffusion-weighted single shot fast spin-echo sequence with and without fat suppression. The influence of breast density on ADC measures was also evaluated. ADC values were calculated for both tumor and normal fibroglandular tissue in a group of 21 women with diagnosed breast cancer. There were systematic underestimations of ADC for both tumor and normal breast tissue due to intravoxel contribution from fat signal on non–fat-suppressed DWI. This ADC underestimation was more pronounced for normal tissue values (mean difference=40%) than for tumors (mean difference=27%, P<.001) and was worse in women with low breast tissue density vs. those with extremely dense breasts (P<.05 for both tumor and normal tissue). Tumor conspicuity measured by contrast-to-noise ratio was significantly higher on ADC maps created with fat suppression and was not significantly associated with breast density. In summary, robust fat suppression is important for accurate breast ADC measures and optimal lesion conspicuity on DWI.     

Transcutaneous in vivo Raman spectroscopy of breast tumors and pretumors

Breast cancer is the most common cancer amongst women worldwide. Early detection of this cancer results in better prognosis. Owing to the disadvantages of currently available screening tools for early detection of this cancer, rapid and sensitive alternatives such as optical spectroscopic techniques are being extensively explored. Detection of premalignant lesions using these techniques has been reported. However, premalignant lesions are risk indicators and may not be true predictors of tumor development. Therefore, the current study aims at correlation between spectral changes and tumor appearance. In this context, transcutaneous in vivo spectra were acquired from same carcinogen‐induced rats immediately before carcinogen treatment, 3, 8–10, and 12–14 weeks after carcinogen treatment and from frank tumors. These were analyzed using multivariate statistical tools principal component analysis and principal component linear discriminant analysis. Further, a complex test data set consisting of spectra from rats of varying ages, tumor appearance times, and tumor induction protocols was used to test the feasibility of correctly identifying controls and pretumors using Raman spectroscopy. Results suggest feasibility of distinguishing pretumor spectra from controls. Taking into consideration the heterogeneity of afflicted breast, rat‐wise analysis was performed wherein a rat was declared ‘will develop tumor’, even if one spectrum was found abnormal. Using this criterion, in vivo Raman spectroscopy could predict tumor appearance with 82% sensitivity and 95% specificity. Prospectively, combined with emerging technologies like deep Raman spectroscopy and fiber‐probe‐based whole sample imaging, Raman spectroscopy may prove as an invaluable adjunct to currently available breast cancer screening tools. Copyright © 2015 John Wiley & Sons, Ltd.     

部分动植物油的拉曼光谱研究

利用拉曼光谱技术分别研究了植物油和动物脂肪油的光谱特性。通过自适应迭代惩罚最小二乘法的基线校正方法, 对所测得的拉曼光谱进行了数据处理,获得了它们的微观信息。进而通过选取其中部分油的拉曼光谱,进行了植物油的光谱、动物脂肪油的光谱以及动物脂肪油和植物油之间的光谱比较和分析,从而发现了多种植物油光谱(包括多个频移范围内的频移大小以及强度大小)的差异,也发现了动物脂肪油与植物油的拉曼光谱间的差异。不但提供了辨识不同食用油的光谱依据,也证明了拉曼光谱是一种识别不同油品的有效方法。     

Influence of the organism interface on the breast cancer detection by UWB

Ultra-wide band (UWB) imaging technique is very attractive for the early breast cancer detection based on the obvious contrast in the electrical properties of malignant tumor to the normal fatty breast tissue. The tumor can be detected by analyzing the reflecting and scattering behavior of the UWB microwaves propagating in the breast. In this study, the influence of the organism interfaces is investigated from different cases of breast configuration involving different gland shapes as well as the tumor locations. Results show that the gland structure and tumor status have large influences on the reconstructed images generated from the detected signals due to the interface varieties. The tumor information in the proposed configurations can be obtained by series signal processing including eliminating the early time response of the detected signals caused by the direct wave and the reflection from the interface between the skin and the breast fat, and compensating the path loss of the propagating signal due to the radial spreading and the attenuation in the lossy breast. The location and the number of emitters and detectors affect the quality of the reconstructed image.     

Raman spectroscopic analysis of breast cancer tissues: identifying differences between normal,invasive ductal carcinoma and ductal carcinoma in situ of the breast tissue

A relatively non‐destructive method employing Raman spectroscopy for the analysis of histopathological specimens is described. Raman spectroscopy has allowed qualitative analysis of the same specimen used for histopathological evaluation. Breast cancer tissues have been analysed to demonstrate the feasibility of the chemical changes taking place in the biological tissue, which can be identified precisely, and the results are reproducible. Raman analysis of tissue sections provides distinct spectra that can be used to distinguish between the nuclear grades of ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC) of the breast. Sixty cases of breast carcinoma including DCIS and IDC and seven cases of normal breast tissues were studied employing the Raman spectroscopic technique. This study reports for the first time spectral differences between DCIS grades. It is concluded that Raman spectroscopy can objectively distinguish between DCIS and IDC grades and is non‐destructive and reproducible. It should become possible in future to use Raman spectroscopy as an informative and quantitative method suitable for classification of grades and diagnosis of breast carcinoma. Copyright © 2007 John Wiley & Sons, Ltd.     

Breast cancer diagnostics by Raman spectroscopy

This paper presents new results for the normal, malignant and benign tissues by Raman spectroscopy. To the best of our knowledge, this is one of the most statistically reliable research (321 spectra from 44 patients) on Raman spectroscopy-based diagnosis of breast cancers among the world's women population. The paper demonstrates that Raman spectroscopy is a powerful medical diagnostic tool with the key advantage in breast cancer research.     

Raman spectroscopic analysis differentiates between breast cancer cell lines

Breast cancer incident rates are increasing in women worldwide with the highest incidence rates reported in developing countries. Major breast cancer screening approaches like mammography, ultrasound, clinical breast examination (CBE) and magnetic resonance imaging (MRI) are currently used but have their own limitations. Optical spectroscopy has attained great attention from biomedical researchers in recent years due to its non‐invasive and non‐destructive detection approach. Chemometrics is one of the powerful tools used in spectroscopic research to enhance its sensitivity. Raman spectroscopy, a vibrational spectroscopic approach, has been used to explore the chemical fingerprints of different biological tissues including normal and malignant types. This approach was used to characterize and differentiate two breast cancer and one normal breast cell lines (MDA‐MB‐436, MCF‐7 and MCF‐10A) using dispersive Raman spectroscopy. Raman spectra of the cell lines have revealed that basic differences in the concentration of biochemical compounds such as lipids, nucleic acids and protein Raman peaks were found to differ in intensity, and principal component analysis (PCA) was able to identify variations that lead to accurate and reliable separation of the three cell lines. Linear discriminant analysis (LDA) model of three cell lines was predicted with 100% sensitivity and 91% specificity. We have shown that a combination of Raman spectroscopy and chemometrics are capable of differentiation between breast cancer cell lines. These variations may be useful in identifying new spectral markers to differentiate different subtypes of breast cancer although this needs confirmation in a larger panel of cell lines as well as clinical material. Copyright © 2015 John Wiley & Sons, Ltd.