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Assessment of 31 P‐NMR analysis of phospholipid profiles for potential differential diagnosis of human cerebral tumors
Author(s) -
Solivera Juan,
Cerdán Sebastián,
Pascual José María,
Barrios Laura,
Roda José María
Publication year - 2009
Publication title -
nmr in biomedicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.278
H-Index - 114
eISSN - 1099-1492
pISSN - 0952-3480
DOI - 10.1002/nbm.1387
Subject(s) - phospholipid , phosphatidylethanolamine , phosphatidylcholine , astrocytoma , phosphatidylserine , biopsy , pathology , human brain , brain biopsy , linear discriminant analysis , plasmalogen , in vivo magnetic resonance spectroscopy , chemistry , magnetic resonance imaging , nuclear magnetic resonance , biology , medicine , radiology , glioma , biochemistry , cancer research , mathematics , membrane , neuroscience , physics , statistics
Abstract 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. Copyright © 2009 John Wiley & Sons, Ltd.