Noninvasive evaluation of cerebral glioma grade by using multivoxel 3D proton MR spectroscopy.
OBJECTIVE
To determine whether metabolite ratios in multivoxel 3D proton MR spectroscopy (¹H MRS) is different between low-grade and high-grade gliomas and may be useful for glioma grading.


METHODS
Thirty-nine patients (23 male and 16 female; 22-75 years old; mean age, 44.92±12.65 years) suspected of having gliomas underwent 3D ¹H MRS examinations. Metabolite ratios [choline (Cho)/creatine (Cr), N-acetylaspartate (NAA)/Cr and Cho/NAA] were measured. Tumor grade was determined by using the histopathologic grading. Receiver operating characteristic analysis of metabolite ratios was performed, and optimum thresholds for tumor grading were determined. The resulting sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for identifying high-grade gliomas were calculated.


RESULTS
Diagnostic-quality 3D ¹H MRS with readily quantifiable Cho, Cr and NAA peaks was obtained in 94.87% of the cases. The Cho/Cr and Cho/NAA ratios were significantly higher in high-grade than in low-grade glioma (P<.001), whereas the NAA/Cr ratios were significantly lower in high-grade than in low-grade glioma (P<.001). Receiver operating characteristic analysis demonstrated a threshold value of 2.04 for Cho/Cr ratio to provide sensitivity, specificity, PPV and NPV of 84.00%, 83.33%, 91.30% and 71.43%, respectively. Threshold value of 2.20 for Cho/NAA ratio resulted in sensitivity, specificity, PPV and NPV of 88.00%, 66.67%, 84.62% and 72.73%, respectively. Overall diagnostic accuracy was not statistically significantly different between Cho/Cr and Cho/NAA ratios (χ²=0.093, P=.76).


CONCLUSIONS
Metabolite ratios of low-grade gliomas were significantly different from high-grade gliomas. Cho/Cr and Cho/NAA ratios could have the superior diagnostic performance in predicting the glioma grade.
Zeng
QingShi
Q
Department of Radiology, Qilu Hospital of Shandong University, Jinan 250012, China. zengqingshi@yahoo.cn
Liu
HePeng
H
Zhang
Kai
K
Li
ChuanFu
C
Zhou
GengYin
G
D000328:Adult; D000368:Aged; D001224:Aspartic Acid / Q000031:analogs & derivatives* / Q000032:analysis; D014408:Biomarkers, Tumor / Q000032:analysis*; D001932:Brain Neoplasms / Q000145:classification / Q000175:diagnosis* / Q000378:metabolism; D002794:Choline / Q000032:analysis*; D003401:Creatine / Q000032:analysis*; D005260:Female; D005910:Glioma / Q000145:classification / Q000175:diagnosis* / Q000378:metabolism; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods; D009682:Magnetic Resonance Spectroscopy / Q000379:methods*; D008297:Male; D008875:Middle Aged; D011522:Protons; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014018:Tissue Distribution
D014408:Biomarkers, Tumor; D011522:Protons; D001224:Aspartic Acid; C000179:N-acetylaspartate; D003401:Creatine; D002794:Choline