Efficacy of 1H-MRSI and DWI for Non-invasive Grading of Brain Gliomas
Mojtaba Miri,1 Meysam Mohseni,2,* Alireza Madadi,3 Kavous Firouznia,1 Hamidreza Saligheh Rad,4 Farid Azmoudeh Ardalan,5 Anahita Fathi Kazerooni,4 Ali Haidari,5 Reza Taslimi,6 and Hossein Ghanaati1
Apparent Diffusion Coefficient, Brain Tumor, Diffusion-Weighted Imaging, Glioma Grading, Glioma, Magnetic Resonance Spectroscopy
Background: Distinguishing low-grade from high-grade gliomas can aid in optimal treatment planning and prognostication.
Diffusion-weighted imaging (DWI) and magnetic resonance spectroscopy (MRS) have been applied in several studies for noninvasive glioma grading. However, these studies focused on limited aspects of these imaging techniques and used different study
setups, resulting in occasionally inconsistent and incomparable conclusions in the literature.
Objectives: This study was designed to introduce the optimal imaging setup and the most reliable and applicable imaging parameters in glioma grading, using DWI and MRS.
Methods: During this prospective study, using a 3T-MR scanner, 55 glioma patients underwent brain MRS with short, intermediate, and long echo times (TEs), as well as DWI using low, intermediate, and high b-values. Postoperatively, all of the specimens were graded pathologically using light microscopy.
Results: We found that Max (Chol/Cr)/ Min (NAA/Cr), followed by Max (Chol/ Cr), both in long-TE, were the most reliable metabolite ratios on MRS for accurate glioma grading. These had values for area under the curve (AUC) of 0.92 (P < 0.05) and 0.89 (P = 0.001), respectively, compared to conventional MR imaging (cMRI), which had an AUC of 0.83 (P < 0.05). DWI at maximal accuracy showed an AUC of 0.80 (P < 0.05).
Conclusions: Max (Chol/Cr)/Min (NAA/Cr) in long-TE was the most reliable of all of the MRS parameters studied, while DWI showed no superiority over cMRI in glioma grading. No significant differences existed among the various b-values applied, or between the minimum and mean tumor ADC values used in DWI-based glioma grading.