Randomized trial evaluates metabolite ratios for glioma grading, suggesting reliable diagnostic criteria.
Background Magnetic Resonance Spectroscopy (MRS) is a non-invasive imaging technique that detects various metabolites in brain tissues, making it essential for the grading of brain gliomas. MRS measures key metabolites such as N-acetyl-aspartate (NAA), choline (Cho), and creatine (Cr), whose ratio changes provide valuable information for glioma grading, guiding diagnosis, treatment, and prognosis. Current studies are largely single-center, with grading criteria differing across hospitals. This work aims to identify reliable and consistent metabolite ratios for glioma grading by jointly analyzing multicenter 3T single-voxel MRS of brain gliomas. The grading accuracy of these metabolite ratios is evaluated to establish a more standardized diagnostic basis. Materials and methods We retrospectively included the MRS data from 60 glioma patients from 3 hospitals. MRS results included 4 metabolite ratios: NAA/Cr, Cho/NAA, Cho/Cr, and NAA/(Cho + Cr). The Shapiro-Wilk test was employed to ascertain the normality of the data, and the differences were calculated using either an independent t -test or a Mann-Whitney U-test. The classification performance was evaluated using ROC curve and accuracy analysis. Results Across multicenter data, statistically significant differences were found in Cho/NAA and Cho/Cr ratios between low- and high-grade gliomas ( P < 0.05). ROC analysis showed AUCs of 0.73 for Cho/NAA and 0.74 for Cho/Cr, indicating good classification performance. Validation results showed 75% accuracy, supporting their potential for clinical glioma grading. The optimal cut-off value trained from any two hospitals is validated at a third hospital, and the accuracies of Cho/Cr are 77.78%, 100%, and 65%, respectively. Conclusion Multicenter data analysis confirmed the good classification accuracy of Cho/NAA and Cho/Cr in glioma grading, providing a reliable basis for clinical treatment and prognosis planning. This aligns with findings from other studies. Clinical trial number Not applicable.
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Guo et al. (2026) studied this question.
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