Glioma grading: sensitivity, specificity, and predictive values of perfusion MR imaging and proton MR spectroscopic imaging compared with conventional MR imaging

Meng Law(Columbia University Irving Medical Center), Stanley Yang(NYU Langone Health), Hao Wang(Fox Chase Cancer Center), James S. Babb(Fox Chase Cancer Center), Glyn Johnson(NYU Langone Health), Soonmee Cha(University of California, San Francisco), Edmond A. Knopp(NYU Langone Health), David Zagzag(NYU Langone Health)
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November 1, 2003
Cited by 1,093Open Access
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Abstract

predictive value (NPV) of conventional MR imaging in predicting glioma grade are not high. Relative cerebral blood volume (rCBV) measurements derived from perfusion MR imaging and metabolite ratios from proton MR spectroscopy are useful in predicting glioma grade. We evaluated the sensitivity, specificity, PPV, and NPV of perfusion MR imaging and MR spec-troscopy compared with conventional MR imaging in grading primary gliomas. METHODS: One hundred sixty patients with a primary cerebral glioma underwent conven-tional MR imaging, dynamic contrast-enhanced T2*-weighted perfusion MR imaging, and proton MR spectroscopy. Gliomas were graded as low or high based on conventional MR imaging findings. The rCBV measurements were obtained from regions of maximum perfusion. Metabolite ratios (choline [Cho]/creatine [Cr], Cho/N-acetylaspartate [NAA], and NAA/Cr) were measured at a TE of 144 ms. Tumor grade determined with the three methods was then compared with that from histopathologic grading. Logistic regression and receiver operating characteristic analyses were performed to determine optimum thresholds for tumor grading. Sensitivity, specificity, PPV, and NPV for identifying high-grade gliomas were also calculated. RESULTS: Sensitivity, specificity, PPV, and NPV for determining a high-grade glioma with


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