Preoperative Grading of Gliomas by Using Metabolite Quantification with High-Spatial-Resolution Proton MR Spectroscopic Imaging

Abstract

To evaluate proton magnetic resonance (MR) spectroscopic imaging with high spatial resolution for preoperative grading of suspected World Health Organization grades II and III gliomas. Institutional ethics committee approval and informed consent were obtained for control subjects but were not required for the retrospective component involving patients. Twenty-six patients (10 women, 16 men; mean age, 37.5 years) suspected of having gliomas and 26 age- and sex-matched control subjects underwent proton MR spectroscopy. Absolute metabolite concentrations for choline-containing compounds (Cho), creatine (Cr), and N-acetylaspartate (NAA)-N-acetylaspartylglutamate (total NAA [tNAA]) were calculated by using a user-independent spectral fit program. Metabolic maps of Cho/tNAA ratios were calculated, segmented, and used for MR spectroszpcopy-guided stereotactic brain biopsy. Two-sided paired Student t tests were used to test for statistical significance. Significantly lower Cho levels (P = .002) and higher tNAA levels (P = .010) were found in grade II tumors (n = 9) compared with grade III tumors (n = 17). The average Cho/tNAA ratio over the voxels in the tumor center showed a distinct difference (P < .001) between grade II and III gliomas at a threshold of 0.8 (with ratios <0.8 for grade II). The maximum Cr concentration in the tumor showed a clear-cut threshold between grade III oligodendrogliomas and oligoastrocytomas (Cr level, <7 mmol/L) and grade III astrocytomas (Cr level, >7 mmol/L; P = .020). Comparison between the histopathologic findings from the MR spectroscopy-guided biopsy samples (76 biopsies from 26 patients) and molar metabolite values in corresponding voxels located at the biopsy sampling points showed a negative linear correlation for tNAA (r = -0.905) and a positive exponential correlation for Cho (r = 0.769) and Cho/tNAA (r = 0.885). Proton MR spectroscopic imaging with high spatial resolution allows preoperative grading of gliomas.