Objective
Phosphorus magnetic resonance spectroscopy (31P MRS) is a non-invasive MR imaging technique that can provide in-vivo quantitative information about the energy metabolism, the oxygen state and the pH within a given region of interest. 31-Phosphorus (31-P) is fifteen times less abundant in tissue than proton (1-H) leading to a higher interest of proton spectral imaging at low field strengths. In-vivo phosphorus spectral imaging has recently become more popular with the availability of higher field 3T MR scanners due to the increased signal to noise ratio and higher spectral peak separation. In this study, we propose to implement phosphorus spectra at high field strength of 3T to diagnose and characterize brain tumor patients. The first part of the study will be the data acquisition and reconstruction development and optimization. Phosphorus spectral data will be acquired both using a single surface 31-P coil and a birdcage dual tune 1H/31P head coil. Single voxel data will be acquired from a region of interest encompassing the tumor or normal tissue. T1 relaxation characteristics for phosphorus metabolites in brain tumors and normal brain tissue will be defined. The data reconstruction and analysis will be performed using both time and frequency domain analysis techniques and their results will be compared. In the second part of the study, two dimensional phosphorus spectral data will be acquired using a birdcage coil, and the heterogeneity of phosphorus spectral parameters within the grade II, III and IV brain tumors will be analyzed. Additionally, a metric that can quantitatively and objectively assess the aggresiveness of brain tumors using the intensities of phosphorus containing metabolites will be presented.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
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Call for proposal
FP7-PEOPLE-2009-RG
See other projects for this call
Funding Scheme
MC-IRG - International Re-integration Grants (IRG)Coordinator
81120 Istanbul
Türkiye