Proton MR spectroscopy of cerebral gliomas at 3 T: spatial heterogeneity, and tumour grade and extent.

This study aimed to evaluate the usefulness of proton MR spectroscopic imaging ((1)H-MRSI) at 3 T in differentiating high- from low-grade gliomas, and tumour from necrosis, oedema or normal tissue. Forty-four patients with brain gliomas and four with meningiomas were retrospectively reviewed. The normalised metabolites choline (nCho), N-acetylaspartate (nNAA), creatine (nCr) and lactate/lipids (nLL), and the metabolite ratios Cho/NAA, NAA/Cr and Cho/Cr were calculated. Necrotic-appearing areas showed two spectroscopic patterns: "necrosis" with variable nCho and high nLL, and "cystic necrosis" with variable nLL or nonevident peaks. Peri-enhancing oedematous-appearing areas showed three spectroscopic patterns ("tumour" with abnormal Cho/NAA, "oedema" with normal Cho/NAA and "tumour/oedema" with normal nCho and abnormal Cho/NAA) in gliomas, and one ("oedema") in meningiomas. Peri-enhancing or peri-tumour normal-appearing areas showed two patterns ("infiltrated" with abnormal nCho and/or Cho/NAA and "normal" with normal spectra) in gliomas and one ("normal") in meningiomas. Discriminant analysis showed that classification accuracy between high- and low-grade glioma masses was better with normalised metabolites or all parameters together than metabolite ratios and that among peri-enhancing areas was much better with normalised metabolites. The analysis of spatial distribution of normalised metabolites by 3-T (1)H-MRSI helps to discriminate among different tissues, offering information not available with conventional MRI.

Multiparametric 3T MR approach to the assessment of cerebral gliomas: tumor extent and malignancy.

INTRODUCTION: Contrast-enhanced MR imaging is the method of choice for routine assessment of brain tumors, but it has limited sensitivity and specificity. We verified if the addition of metabolic, diffusion and hemodynamic information improved the definition of glioma extent and grade. METHODS: Thirty-one patients with cerebral gliomas (21 high- and 10 low-grade) underwent conventional MR imaging, proton MR spectroscopic imaging ((1)H-MRSI), diffusion weighted imaging (DWI) and perfusion weighted imaging (PWI) at 3 Tesla, before undergoing surgery and histological confirmation. Normalized metabolite signals, including choline (Cho), N-acetylaspartate (NAA), creatine and lactate/lipids, were obtained by (1)H-MRSI; apparent diffusion coefficient (ADC) by DWI; and relative cerebral blood volume (rCBV) by PWI. RESULTS: Perienhancing areas with abnormal MR signal showed 3 multiparametric patterns: "tumor", with abnormal Cho/NAA ratio, lower ADC and higher rCBV; "edema", with normal Cho/NAA ratio, higher ADC and lower rCBV; and "tumor/edema", with abnormal Cho/NAA ratio and intermediate ADC and rCBV. Perienhancing areas with normal MR signal showed 2 multiparametric patterns: "infiltrated", with high Cho and/or abnormal Cho/NAA ratio; and "normal", with normal spectra. Stepwise discriminant analysis showed that the better classification accuracy of perienhancing areas was achieved when regarding all MR variables, while (1)H-MRSI variables and rCBV better differentiated high- from low-grade gliomas. CONCLUSION: Multiparametric MR assessment of gliomas, based on (1)H-MRSI, PWI and DWI, discriminates infiltrating tumor from surrounding vasogenic edema or normal tissues, and high- from low-grade gliomas. This approach may provide useful information for guiding stereotactic biopsies, surgical resection and radiation treatment.