Recurrent glioblastoma multiforme versus radiation injury: a multiparametric 3-T MR approach.

Objective: The discrimination between recurrent glioma and radiation injury is often a challenge on conventional magnetic resonance imaging (MRI). We verified whether adding and combining proton MR spectroscopic imaging ((1)H-MRSI), diffusion-weighted imaging (DWI) and perfusion-weighted imaging (PWI) information at 3 Tesla facilitate such discrimination.
Materials and Methods: Twenty-nine patients with histologically verified high-grade gliomas, who had undergone surgical resection and radiotherapy, and had developed new contrast-enhancing lesions close to the treated tumour, underwent MRI, (1)H-MRSI, DWI and PWI at regular time intervals. The metabolite ratios choline (Cho)/normal( n )Cho n , N-acetylaspartate (NAA)/NAA n , creatine (Cr)/Cr n , lactate/lipids (LL)/LL n , Cho/Cr n , NAA/Cr n , Cho/NAA, NAA/Cr and Cho/Cr were derived from (1)H-MRSI; the apparent diffusion coefficient (ADC) from DWI; and the relative cerebral blood volume (rCBV) from PWI.
Results: In serial MRI, recurrent gliomas showed a progressive enlargement, and radiation injuries showed regression or no modification. Discriminant analysis showed that discrimination accuracy was 79.3 % when considering only the metabolite ratios (predictor, Cho/Cr n ), 86.2 % when considering ratios and ADC (predictors, Cho/Cr n and ADC), 89.7 % when considering ratios and rCBV (predictors, Cho/Cr n , Cho/Cr and rCBV), and 96.6 % when considering ratios, ADC and rCBV (predictors, Cho/Cho n , ADC and rCBV).
Conclusions: The multiparametric 3-T MR assessment based on (1)H-MRSI, DWI and PWI in addition to MRI is a useful tool to discriminate tumour recurrence/progression from radiation effects.