Assessment of ³¹P‐NMR analysis of phospholipid profiles for potential differential diagnosis of human cerebral tumors

Abstract

We describe a novel protocol for the non‐histological diagnosis of human brain tumors in vitro combining high‐resolution 31P magnetic resonance spectroscopy (31P‐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 31P‐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 31P‐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.

Proton MR spectroscopic imaging of human glioblastomas at 1.5 Tesla

“…To the tCho signal mainly phosphocholine contributes, and in a lesser extent glycerophosphocholine, free choline, and acetylcholine (Horska and Barker 2010;McKnight and Wladman 2010). Since the phosphocholine is the precursor of membrane phospholipids synthesis (Solivera et al 2009;Ha et al 2013), tCho is considered to be the most useful MRS parameter reflecting higher cellular proliferation and tumor carcinogenesis (Guillevin et al 2008;Housni and Boujraf 2013). The concentration of free creatine and phosphocreatine, detected as a joint peak tCr, has the most stable value among 1 H MRS detectable metabolites and thus it is usually used as a reference for relative metabolite quantification (Soares and Law 2009;Barker 2010).…”

Classification of brain tumor extracts by high resolution ¹H MRS using partial least squares discriminant analysis

“…Application of PLS-DA allowed the identification of different metabolites and their correlation with distinct tumor types. Recently, multiple studies, such as the multicenter "eTUMOR" and "INTERPRET", have shown similar results from the analysis of MRS with multivariate models (4)(5)(6)(7)(8). The advantage of these methods for data analyses is that they can simultaneously handle a large range of metabolites providing a powerful tool for profile discrimination thus reducing the large number of spectral variables to a few key metabolites.…”

“…The use of supervised pattern recognition methods such as partial least squares discriminant analysis (PLS-DA) on complex data provides a powerful tool for characterizing different classes of brain tumor extracts according to their spectral metabolic profiles (4)(5)(6)(7)(8). The purpose of the present study was to apply PLS-DA to analyze the high-resolution www.bjournal.com.br Braz J Med Biol Res 44(2) 2011 1 H MRS spectra of brain tumor extracts in order to refine the identification of their metabolic profile and to identify possible surrogate markers for different types of brain tumors.…”

1H/31P Polarization Transfer at 9.4 Tesla for Improved Specificity of Detecting Phosphomonoesters and Phosphodiesters in Breast Tumor Models

“…With recent technological developments of improved human high-field MR scanners, coils, and pulse sequences for 31 P MRS, resolving these individual metabolites has become feasible in the clinical setting [9], [13]. Furthermore, using human tissue biopsies and magic angle spinning 31 P HR-MRS, it has been possible to use phospholipid metabolites as markers to discriminate between tumor types and grades [39], [40], evaluate response to treatment [36], predict response to treatment [41], and assess resection margins during breast cancer surgery [42].…”