Aguiar Ricardo Pinto, Silveira Landulfo, Falcão Edgar Teixeira, Pacheco Marcos Tadeu Tavares, Zângaro Renato Amaro, Pasqualucci Carlos Augusto
1 Biomedical Engineering Institute, Universidade Camilo Castelo Branco - UNICASTELO , Parque Tecnológico de São José dos Campos, São José dos Campos, SP, Brazil .
Photomed Laser Surg. 2013 Dec;31(12):595-604. doi: 10.1089/pho.2012.3460. Epub 2013 Nov 19.
Because of their aggressiveness, brain tumors can lead to death within a short time after diagnosis. Optical techniques such as Raman spectroscopy may be a technique of choice for in situ tumor diagnosis, with potential use in determining tumor margins during surgery because of its ability to identify biochemical changes between normal and tumor brain tissues quickly and without tissue destruction.
In this work, fragments of brain tumor (glioblastoma, medulloblastoma, and meningioma) and normal tissues (cerebellum and meninges) were obtained from excisional intracranial surgery and from autopsies, respectively. Raman spectra (dispersive spectrometer, 830 nm 350 mW, 50 sec accumulation, total 172 spectra) were obtained in vitro on these fragments. It has been developed as a model to discriminate between the spectra of normal tissue and tumors based on the scores of principal component analysis (PCA) and Euclidean distance.
ANOVA indicated that the scores of PC2 and PC3 show differences between normal and tumor groups (p<0.05) which could be employed in a discrimination model. PC2 was able to discriminate glioblastoma from the other tumors and from normal tissues, showing featured peaks of lipids/phospholipids and cholesterol. PC3 discriminated medulloblastoma and meningioma from normal tissues, with the most intense spectral features of proteins. PC3 also discriminated normal tissues (meninges and cerebellum) by the presence of cholesterol peaks. Results indicated a sensitivity and specificity of 97.4% and 100%, respectively, for this in vitro diagnosis of brain tumor.
The PCA/Euclidean distance model was effective in differentiating tumor from normal spectra, regardless of the type of tissue (meninges or cerebellum).
由于脑肿瘤具有侵袭性，可在诊断后短时间内导致死亡。拉曼光谱等光学技术可能是原位肿瘤诊断的首选技术，因其能够快速识别正常脑组织与肿瘤脑组织之间的生化变化且无需破坏组织，故在手术中确定肿瘤边界方面具有潜在应用价值。
在本研究中，分别从颅内切除手术和尸检中获取脑肿瘤（胶质母细胞瘤、髓母细胞瘤和脑膜瘤）及正常组织（小脑和脑膜）的碎片。在这些碎片上进行体外拉曼光谱检测（色散光谱仪，830 nm，350 mW，累积50秒，共172个光谱）。基于主成分分析（PCA）得分和欧几里得距离，已建立了一个区分正常组织和肿瘤光谱的模型。
方差分析表明，PC2和PC3得分在正常组和肿瘤组之间存在差异（p<0.05），可用于判别模型。PC2能够将胶质母细胞瘤与其他肿瘤及正常组织区分开来，显示出脂质/磷脂和胆固醇的特征峰。PC3将髓母细胞瘤和脑膜瘤与正常组织区分开来，具有最强的蛋白质光谱特征。PC3还通过胆固醇峰的存在区分正常组织（脑膜和小脑）。结果表明，这种脑肿瘤体外诊断的灵敏度和特异性分别为97.4%和100%。
PCA/欧几里得距离模型在区分肿瘤光谱与正常光谱方面是有效的，无论组织类型是脑膜还是小脑。
