• Paolo Zonari, Patrizia Baraldi, and Girolamo Crisi.
• Neuroradiologia, Dipartimento Integrato di Neuroscienze, Ospedale "B. Ramazzini", AUSL Modena, Via G. Molinari 2, 41012 Carpi, Modena, Italy. p.zonari@ausl.mo.it
• Neuroradiology. 2007 Oct 1; 49 (10): 795-803.

IntroductionDiffusion-weighted imaging (DWI), perfusion-weighted imaging (PWI) and MR spectroscopy (MRS) provide useful data for tumor evaluation. To assess the contribution of these multimodal techniques in grading glial neoplasms, we compared the value of DWI, PWI and MRS in the evaluation of histologically proven high- and low-grade gliomas in a population of 105 patients.MethodsIndependently for each modality, the following variables were used to compare the tumors: minimum apparent diffusion coefficient (ADC) and maximum relative cerebral blood volume (rCBV) normalized values between tumor and healthy tissue, maximum Cho/Cr ratio and minimum NAA/Cr ratio in tumor, and scored lactate and lipid values in tumor. The Mann-Whitney and Wilcoxon tests were employed to compare DWI, PWI and MRS between tumor types. Logistic regression analysis was used to determine which parameters best increased the diagnostic accuracy in terms of sensitivity, specificity, and positive and negative predictive values. ROC curves were determined for parameters with high sensitivity and specificity to identify threshold values to separate high- from low-grade lesions.ResultsStatistically significant differences were found for rCBV tumor/normal tissue ratio, and NAA/Cr ratio in tumor and Cho/Cr ratio in tumor between low- and high-grade tumors. The best performing single parameter for group classification was the normalized rCBV value; including all parameters, statistical significance was reached by rCBV tumor/normal tissue ratio, NAA/Cr tumor ratio and lactate. From the ROC curves, a high probability for a neoplasm to be a high-grade lesion was associated with a rCBV tumor/normal tissue ratio of >1.16 and NAA/Cr tumor ratio of <0.44.ConclusionCombining PWI and MRS with conventional MR imaging increases the accuracy of the attribution of malignancy to glial neoplasms. The best performing parameter was found to be the perfusion level.

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