Glioma Grading: The Role of Combined Perfusion MR Imaging and Single-VoxelMR Spectroscopy Compared to Conventional MR Imaging

Risultato della ricerca: Other


AbstractBody:PurposeTo assess the contribution of combined perfusion MR imaging (MRI) and single-voxelMR spectroscopy (MRS) in grading primary gliomas compared with conventional MRI.Materials &amp; MethodsThirty-two patients with primary cerebral glioma underwent conventional MRI, dynamiccontrast-enhanced T2*-weighted perfusion MRI and single-voxel proton MRS. Gliomaswere graded as low or high based on conventional MRI. The rCBV measurements wereobtained from regions of maximum perfusion normalized between tumor and healthytissue. Metabolite ratios ( [Cho]/[Cr], [Cho]/[NAA], [NAA]/[Cr]) were measured withTE: 34 ms. Tumor grade determined with the three methods then was compared with thatfrom histopathologic grading. Logistic regression and ROC analyses were performed todetermine which parameters best increased diagnostic accuracy (sensitivity, specificity,positive and negative predictive values)ResultsStatistically significant differences were found for rCBV tumor/normal tissue ratio, andNAA/Cr ratio in tumor and Cho/Cr ratio in tumor between low- and high-grade tumors.The best performing single parameter for glioma grading was normalized rCBV value.Combined rCBV tumor/normal tissue ratio and NAA/Cr tumor ratio increased overallaccuracy in glioma grading. Receiver operating characteristic curves demonstrated arCBV tumor/normal tissue ratio of >1.16 and NAA/Cr tumor ratio of <0.44 has thehigher probability for a neoplasm to be a high-grade glioma.ConclusionThe rCBV measurements and metabolite ratios both individually and in combination canincrease the accuracy when compared with conventional MRI alone in determining gliomagrade. The best performing parameter was found to be the rCBV measurements.Threshold values can provide a means for guiding treatment and predicting postoperativepatient outcome.
Lingua originaleEnglish
Numero di pagine2
Stato di pubblicazionePublished - 2011


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