Background and Purpose
Accurate grading of cerebral glioma using conventional structural imaging techniques remains challenging due to the relatively poor sensitivity and specificity of these methods. The purpose of this study was to evaluate the relative sensitivity and specificity of structural MRI and MR measurements of perfusion, diffusion, and spectroscopic parameters for glioma grading. A secondary objective was to evaluate a whole-brain MR spectroscopic imaging method for evaluation of brain tumors.
Materials and Methods
Fifty six patients with radiologically suspected untreated glioma were studied with T1- and T2-weighted MR imaging, DCE-MR imaging, DTI, and volumetric whole-brain MR spectroscopic imaging. ROC analysis was performed using the relative CBV, ADC, FA, and multiple spectroscopic parameters to determine optimum thresholds for tumor grading and to obtain the sensitivity, specificity, PPV, and NPV for identifying high-grade gliomas. Logistic regression was performed to analyze all the parameters together.
Results
The relative CBV individually classified glioma as low and high grade with a sensitivity and specificity of 100% and 88% respectively based on a threshold value of 3.34. On combining all parameters under consideration, the classification was achieved with 2% error and sensitivity and specificity of 100% and 96% respectively.
Conclusion
Individually, CBV measurement provides the greatest diagnostic performance for predicting glioma grade; however, the most accurate classification can be achieved by combining all of the imaging parameters. The whole-brain MR spectroscopic imaging method provided data from of a large fraction of the tumor volumes.