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.

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.

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.

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