140.
Faria A. V., Macedo F. C. Jr., Marsaioli A. J., Ferreira M. M. C.,
Fendes F., "Classification of brain
tumor extracts by high resolution 1H MRS using partial least squares
discriminant analysis", Braz.
J. Med. Biol. Res., 44(2),
149-164 (Feb 2011).
[Article]
Abstract.
High resolution proton nuclear magnetic resonance spectroscopy (1H
MRS) can be used to detect biochemical changes in
vitro caused by distinct pathologies. It can reveal distinct
metabolic profiles of brain tumors although the accurate analysis and
classification of different spectra remains a challenge. In this study,
the pattern recognition method partial least squares discriminant
analysis (PLS-DA) was used to classify 11.7 T 1H
MRS spectra of brain tissue extracts from patients with brain tumors
into four classes (high-grade neuroglial, low-grade neuroglial,
non-neuroglial, and metastasis) and a group of control brain tissue.
PLS-DA revealed 9 metabolites as the most important in group
differentiation: γ-aminobutyric acid, acetoacetate, alanine, creatine,
glutamate/glutamine, glycine, myo-inositol,
N-acetylaspartate, and choline
compounds. Leave-one-out crossvalidation showed that PLS-DA was
efficient in group characterization. The metabolic patterns detected
can be explained on the basis of previous multimodal studies of tumor
metabolism and are consistent with neoplastic cell abnormalities
possibly related to high turnover, resistance to apoptosis, osmotic
stress and tumor tendency to use alternative energetic pathways such as
glycolysis and ketogenesis.
Keywords.
Brain; Tumor; Magentic Resonance Spectroscopy; Spectroscopy; Metabolism.
Keywords Plus.