Centre for Biophotonics, Lancaster Environment Centre, Lancaster University, Bailrigg, Lancaster LA1 4YQ, UK.
Anal Bioanal Chem. 2011 Aug;401(3):957-67. doi: 10.1007/s00216-011-5137-6. Epub 2011 Jun 11.
Fine needle aspirates (FNAs) of suspicious breast lesions are often used to aid the diagnosis of female breast cancer. Biospectroscopy tools facilitate the acquisition of a biochemical cell fingerprint representative of chemical bonds present in a biological sample. The mid-infrared (IR; 4,000-400 cm(-1)) is absorbed by the chemical bonds present, allowing one to derive an absorbance spectrum. Complementary to IR spectroscopy, Raman spectroscopy measures the scattering by chemical bonds following excitation by a laser to generate an intensity spectrum. Our objective was to apply these methods to determine whether a biospectroscopy approach could objectively segregate different categories of FNAs. FNAs of breast tissue were collected (n = 48) in a preservative solution and graded into categories by a cytologist as C1 (non-diagnostic), C2 (benign), C3 (suspicious, probably benign) or C5 (malignant) [or C4 (suspicious, probably malignant); no samples falling within this category were identified during the collection period of the study]. Following washing, the cellular material was transferred onto BaF(2) (IR-transparent) slides for interrogation by Raman or Fourier-transform IR (FTIR) microspectroscopy. In some cases where sufficient material was obtained, this was transferred to low-E (IR-reflective) glass slides for attenuated total reflection-FTIR spectroscopy. The spectral datasets produced from these techniques required multivariate analysis for data handling. Principal component analysis followed by linear discriminant analysis was performed independently on each of the spectral datasets for only C2, C3 and C5. The resulting scores plots revealed a marked overlap of C2 with C3 and C5, although the latter pair were both significantly segregated (P < 0.001) in the Raman spectra. Good separation was observed between C3 and C5 in all three spectral datasets. Analysis performed on the average spectra showed the presence of three distinct cytological groups. Our findings suggest that biospectroscopy tools coupled with multivariate analysis may support the current FNA tests whilst increasing the sensitivity and associated reliability for improved diagnostics.
细针抽吸（FNAs）可疑的乳腺病变通常用于辅助女性乳腺癌的诊断。生物光谱学工具有助于获取代表生物样本中存在的化学键的生化细胞指纹。中红外（IR；4,000-400 cm（-1））被存在的化学键吸收，允许人们得出吸收光谱。与红外光谱互补，拉曼光谱通过用激光激发化学键的散射来测量，以产生强度光谱。我们的目标是应用这些方法来确定生物光谱学方法是否可以客观地区分不同类别的 FNAs。在保存溶液中收集乳腺组织的 FNAs（n = 48），并由细胞学专家将其分为 C1（非诊断性）、C2（良性）、C3（可疑，可能良性）或 C5（恶性）[或 C4（可疑，可能恶性）；在研究收集期间未识别出属于该类别的样本]。洗涤后，将细胞材料转移到 BaF（2）（IR 透明）载玻片上，用拉曼或傅里叶变换 IR（FTIR）微光谱仪进行检测。在某些情况下，如果获得足够的材料，则将其转移到低-E（IR 反射）载玻片上，用于衰减全反射-FTIR 光谱。这些技术产生的光谱数据集需要进行多元数据分析。对每个光谱数据集仅针对 C2、C3 和 C5 分别执行主成分分析（PCA），然后进行线性判别分析（LDA）。结果得分图显示 C2 与 C3 和 C5 之间存在明显的重叠，尽管后两者在拉曼光谱中均明显分离（P < 0.001）。在所有三个光谱数据集中都观察到 C3 和 C5 之间的良好分离。对平均光谱的分析表明存在三个不同的细胞学组。我们的发现表明，生物光谱学工具与多元分析相结合可能支持当前的 FNA 测试，同时提高灵敏度和相关可靠性，以改善诊断。
