Biophotonics Research Group, Gloucestershire Royal Hospital, Great Western Road, Gloucester, GL1 3NN, UK.
Analyst. 2013 Jul 21;138(14):3900-8. doi: 10.1039/c2an36579k.
The potential use of Raman spectroscopy (RS) for the detection of malignancy within lymph nodes of the head and neck was evaluated. RS measures the presence of biomolecules by the inelastic scattering of light within cells and tissues. This can be performed in vivo in real-time.
103 lymph nodes were collected from 23 patients undergoing surgery for suspicious lymph nodes. Five pathologies, defined by consensus histopathology, were collected including reactive nodes (benign), Hodgkin's and non-Hodgkin's lymphomas, metastases from both squamous cell carcinomas and adenocarcinomas. Raman spectra were measured with 830 nm excitation from numerous positions on each biopsy. Spectral diagnostic models were constructed using principal component analysis followed by linear discriminant analysis (PCA-LDA), and by partial least squares discriminant analysis (PLS-DA) for comparison. Two-group models were constructed to distinguish between reactive and malignant nodes, and three-group models to distinguish between the benign, primary and secondary conditions.
Results were validated using a repeated subsampling procedure. Sensitivities and specificities of 90% and 86% were obtained using PCA-LDA, and 89% and 88% using PLS-DA, for the two-group models. Both PCA-LDA and PLS-DA models were also found to be very successful at discriminating between pathologies in the three-group models achieving sensitivities and specificities of over 78% and 89% for PCA-LDA, and over 81% and 89% for PLS-DA for all three pathology groups.
Raman spectroscopy and chemometric techniques can be successfully utilised in combination for discriminating between different cancerous conditions of lymph nodes from the head and neck.
评估了拉曼光谱（RS）在检测头颈部淋巴结恶性肿瘤中的潜在应用。RS 通过细胞和组织内的光非弹性散射来测量生物分子的存在。这可以在体内实时进行。
从 23 名因可疑淋巴结而行手术的患者中收集了 103 个淋巴结。通过共识组织病理学收集了包括反应性淋巴结（良性）、霍奇金和非霍奇金淋巴瘤、鳞状细胞癌和腺癌转移在内的五种病理。用 830nm 激发光从每个活检的多个位置测量拉曼光谱。使用主成分分析（PCA） followed by 线性判别分析（PCA-LDA）和偏最小二乘判别分析（PLS-DA）构建光谱诊断模型进行比较。构建了两个组模型以区分反应性和恶性节点，以及三个组模型以区分良性、原发性和继发性条件。
使用重复抽样程序验证了结果。使用 PCA-LDA 获得了 90%和 86%的灵敏度和特异性，使用 PLS-DA 获得了 89%和 88%的灵敏度和特异性，用于两个组模型。PCA-LDA 和 PLS-DA 模型在三组模型中也非常成功地区分了不同的病理学，PCA-LDA 的灵敏度和特异性均超过 78%和 89%，PLS-DA 的灵敏度和特异性均超过 81%和 89%。
拉曼光谱和化学计量技术可以成功地结合使用，用于区分头颈部淋巴结的不同癌症状态。
