Solivera Juan, Cerdán Sebastián, Pascual José María, Barrios Laura, Roda José María
Department of Neurosurgery, Hospital Universitario Reina Sofía, Córdoba, Spain.
NMR Biomed. 2009 Jul;22(6):663-74. doi: 10.1002/nbm.1387.
We describe a novel protocol for the non-histological diagnosis of human brain tumors in vitro combining high-resolution (31)P magnetic resonance spectroscopy ((31)P-MRS) of their phospholipid profile and statistical multivariate analysis. Chloroform/methanol extracts from 40 biopsies of human intracranial tumors obtained during neurosurgical procedures were prepared and analyzed by high-resolution (31)P-MRS. The samples were grouped in the following seven major classes: normal brain (n = 3), low-grade astrocytomas (n = 4), high-grade astrocytomas (n = 7), meningiomas (n = 9), schwannomas (n = 3), pituitary adenomas (n = 4), and metastatic tumors (n = 4). The phospholipid profile of every biopsy was determined by (31)P-NMR analysis of its chloroform/methanol extract and characterized by 19 variables including 10 individual phospholipid contributions and 9 phospholipid ratios. Most tumors depicted a decrease in phosphatidylethanolamine (PtdEtn) and phosphatidylserine (PtdSer), the former mainly in neuroepithelial neoplasms and the latter in metastases. An increase in phosphatidylcholine (PtdCho) and phosphatidylinositol (PtdIns) appeared predominantly in primary non-neuroepithelial tumors. Linear discriminant analysis (LDA) revealed the optimal combination of variables that could classify each biopsy between every pair of classes. The resultant discriminant functions were used to calculate the probability of correct classifications for each individual biopsy within the seven classes considered. Multilateral analysis classified correctly 100% of the normal brain samples, 89% of the meningiomas, 75% of the metastases, and 57% of the high-grade astrocytomas. The use of phospholipid profiles may complement appropriately previously proposed methods of intelligent diagnosis of human cerebral tumors.
我们描述了一种用于体外非组织学诊断人脑肿瘤的新方案，该方案结合了对其磷脂谱的高分辨率（31）P磁共振波谱（（31）P-MRS）和统计多变量分析。制备了在神经外科手术期间获得的40例人类颅内肿瘤活检组织的氯仿/甲醇提取物，并通过高分辨率（31）P-MRS进行分析。样本分为以下七个主要类别：正常脑（n = 3）、低级别星形细胞瘤（n = 4）、高级别星形细胞瘤（n = 7）、脑膜瘤（n = 9）、神经鞘瘤（n = 3）、垂体腺瘤（n = 4）和转移瘤（n = 4）。通过对其氯仿/甲醇提取物进行（31）P-NMR分析确定每个活检组织的磷脂谱，并由19个变量表征，包括10种单个磷脂成分和9种磷脂比率。大多数肿瘤显示磷脂酰乙醇胺（PtdEtn）和磷脂酰丝氨酸（PtdSer）减少，前者主要在神经上皮肿瘤中，后者在转移瘤中。磷脂酰胆碱（PtdCho）和磷脂酰肌醇（PtdIns）的增加主要出现在原发性非神经上皮肿瘤中。线性判别分析（LDA）揭示了能够在每对类别之间对每个活检进行分类的变量的最佳组合。所得判别函数用于计算在所考虑的七个类别中每个个体活检正确分类的概率。多变量分析正确分类了100%的正常脑样本、89%的脑膜瘤、75%的转移瘤和57%的高级别星形细胞瘤。磷脂谱的使用可能适当地补充先前提出的人类脑肿瘤智能诊断方法。
