Abstract
Magnetic resonance imaging (MRI) is the current gold standard for the diagnosis of brain tumors. However, despite the development of MRI techniques, the differential diagnosis of central nervous system (CNS) primary pathologies, such as lymphoma and glioblastoma or tumor-like brain lesions and glioma, is often challenging. MRI can be supported by in vivo magnetic resonance spectroscopy (MRS) to enhance its diagnostic power and multiproject-multicenter evaluations of classification of brain tumors have shown that an accuracy around 90% can be achieved for most of the pairwise discrimination problems. However, the survival rate for patients affected by gliomas is still low. The High-Resolution Magic-Angle-Spinning Nuclear Magnetic Resonance (HR-MAS NMR) metabolomics studies may be helpful for the discrimination of gliomas grades and the development of new strategies for clinical intervention. Here, we propose to use T2 -filtered, diffusion-filtered and conventional water-presaturated spectra to try to extract as much information as possible, fusing the data gathered by these different NMR experiments and applying a chemometric approach based on Multivariate Curve Resolution (MCR). Biomarkers important for glioma's discrimination were found. In particular, we focused our attention on cystathionine (Cyst) that shows promise as a biomarker for the better prognosis of glioma tumors.
Highlights
Primary brain tumors are central nervous system tumors (CNS) and they are relatively rare (1-2% of human cancers)
We propose to use T2-filtered, diffusion-filtered and conventional water-presaturated spectra to try to extract as much information as possible, fusing the data 25 gathered by these different NMR experiments and applying a chemometric approach based on Multivariate Curve Resolution (MCR)
We evaluate T2-filtered spectra but we try to extract as much information as possible from diffusion-filtered and conventional water-presaturated spectra fusing the data gathered by these different NMR experiments and applying the Multivariate Curve Resolution (MCR) approach on each experiment individually
Summary
Primary brain tumors are central nervous system tumors (CNS) and they are relatively rare (1-2% of human cancers). Every year in Europe about 8-10 new cases every 100,000 inhabitants are diagnosed, with a significant increase since 1970 in the industrialized. CNS tumors are ranked seventeenth for incidence and 11 twelfth for mortality; the probability of developing a CNS tumor increases with age.[1] Primary brain tumors are mainly gliomas, with a number of histology subtypes: glioblastoma is the glioma of grade IV, which is the most invasive and frequent; anaplastic astrocytoma and anaplastic oligodendroglioma are gliomas of grade III and low-grade astrocytoma and low-. 18 grade oligodendroglioma are diffuse gliomas of grade II. The new WHO 2016 classification prognosis is influenced by grading and biomolecular assessment in IDH mutation and MGMT methylation.[2,3] About 60-70% of the primary brain
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