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


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 (1H-MRSI), diffusion-weighted imaging (DWI) and perfusion-weighted imaging (PWI) information at 3 Tesla facilitate such discrimination. 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, 1H-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 1H-MRSI; the apparent diffusion coefficient (ADC) from DWI; and the relative cerebral blood volume (rCBV) from PWI. 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). The multiparametric 3-T MR assessment based on 1H-MRSI, DWI and PWI in addition to MRI is a useful tool to discriminate tumour recurrence/progression from radiation effects.

DOI: 10.1007/s11547-013-0371-y

1 Figure or Table

Citations per Year

352 Citations

Semantic Scholar estimates that this publication has 352 citations based on the available data.

See our FAQ for additional information.

Cite this paper

@article{Costanzo2013RecurrentGM, title={Recurrent glioblastoma multiforme versus radiation injury: a multiparametric 3-T MR approach}, author={Alfonso Di Costanzo and Tommaso Scarabino and Francesca Trojsi and Teresa Popolizio and Simona Bonavita and Mario de Cristofaro and Renata Conforti and Adriana Cristofano and Claudio Colonnese and Ugo Salvolini and Gioacchino Tedeschi}, journal={La radiologia medica}, year={2013}, volume={119}, pages={616-624} }