Differentiation between glioblastoma and solitary brain metastasis using neurite orientation dispersion and density imaging.

BACKGROUND AND PURPOSE: Neurite orientation dispersion and density imaging (NODDI) is a new technique that applies a three-diffusion-compartment biophysical model. We assessed the usefulness of NODDI for the differentiation of glioblastoma from solitary brain metastasis.

METHODS: NODDI data were prospectively obtained on a 3T magnetic resonance imaging (MRI) scanner from patients with previously untreated, histopathologically confirmed glioblastoma (n = 9) or solitary brain metastasis (n = 6). Using the NODDI Matlab Toolbox, we generated maps of the intra-cellular, extra-cellular, and isotropic volume (VIC, VEC, VISO) fraction. Apparent diffusion coefficient - and fraction anisotropy maps were created from the diffusion data. On each map we manually drew a region of interest around the peritumoral signal-change (PSC) - and the enhancing solid area of the lesion. Differences between glioblastoma and metastatic lesions were assessed and the area under the receiver operating characteristic curve (AUC) was determined.

RESULTS: On VEC maps the mean value of the PSC area was significantly higher for glioblastoma than metastasis (P < 0.05); on VISO maps it tended to be higher for metastasis than glioblastoma. There was no significant difference on the other maps. Among the 5 parameters, the VEC fraction in the PSC area showed the highest diagnostic performance. The VEC threshold value of ≥ 0.48 yielded 100% sensitivity, 83.3% specificity, and an AUC of 0.87 for differentiating between the two tumor types.

CONCLUSIONS: NODDI compartment maps of the PSC area may help to differentiate between glioblastoma and solitary brain metastasis.