Accelerated Phosphorus MR Spectroscopic Imaging of Brain Tumors at 3T using Compressed Sensing


Aim of the Project

Phosphorus magnetic resonance spectroscopic imaging (31P-MRSI) is another kind of non-invasive MR spectroscopic imaging technique that detects the phosphorus instead of proton containing metabolites of the brain. 31P MRSI provides in-vivo quantitative information about the energy metabolism, oxygen state and pH within a given region of interest. Although, phosphorus magnetic resonance spectroscopic imaging provides vast information, it has not been widely used in the clinical settings yet. One of the major reasons of this problem is the low MR signal of phosphorus, because phosphorus is 15 times less abundant in the body than proton, and its gyromagnetic ratio is less than half of that of proton’s (1H=42.58 MHz/T, 31P=17.2 MHz/T). The wider availability of high field scanners has enabled an increase in phosphorus MR signal. It is possible to average out multiple phosphorus signal acquisitions to get a higher signal to noise ratio (SNR), but this would result in longer scan times. Faster phosphorus spectroscopic imaging techniques should be devised to enable a wider use of 31P-MRSI. In this study, we have aimed to implement compressed sensing technique for fast phosphorus magnetic resonance spectroscopic imaging.

Project Plan

Initially, a simulation study was conducted to decide on the reduction factors and the sampling patterns that would be implemented in the pulse sequence to accelerate the phosphorus magnetic resonance spectroscopic imaging data acquisition using compressed sensing. The signal to noise ratio, spatial response function, and the effective spatial resolution were calculated for each proposed sampling pattern. A pulse sequences has been implemented in Philips Paradise environment for compressed sensing accelerated 31P-MRSI. A phantom, five volunteers and 10 patients diagnosed with brain tumors will be scanned by the end of the project in September 2014. Informed consent has been obtained from the human subjects. Tumor regions have been delineated out of anatomical T2 weighted MR images by an expert radiologist. The missing k-space points have been estimated using either a 2D iterative frame based or a 3D direct compressed sensing reconstruction algorithms. The completed spectral data have been fit to a model function in time domain using AMARES program implemented within the jMRUI software package. For each spectrum, metabolite peak intensities, the ratio of phosphorus peaks, and pH have been calculated. The signal to noise ratio (SNR) of the peak intensities and ratios, and pH values have been compared between compressed sensing accelerated and original datasets using the Bland-Altman method. For each data acquisition scheme, the difference of spectral parameters between the normal tissue and the tumor has been assessed using a Wilcoxon signed rank test.

Our study plan has extended over 24 months. A Ph.D. student and two master’s students have been funded through this project. The proposed study has been conducted on a Philips Achieva 3T MR scanner located at Uludag University Hospital.  The results of this study will enable a wider availability of phosphorus MR spectroscopic imaging techniques for metabolic imaging of brain tumors and other brain pathologies. Please see below an example volunteer scan acquired with compressed sensing accelerated 31P-MRSI.


Last modified on: Tuesday, February 2, 2016

This project was supported by Marie Curie International Reintegration Grants (IRG) FP7-PEOPLE-RG-2009 256528 and TUBITAK Young Investigator Career Development Grant 112E036.