Histogram analysis based on diffusion kurtosis imaging: Differentiating glioblastoma multiforme from single brain metastasis and comparing the diagnostic performance of two region of interest placements.

PURPOSE

To assess the value of histogram analysis, using diffusion kurtosis imaging (DKI), in differentiating glioblastoma multiforme (GBM) from single brain metastasis (SBM) and to compare the diagnostic efficiency of different region of interest (ROI) placements.

METHOD

Sixty-seven patients with histologically confirmed GBM (n = 35) and SBM (n = 32) were recruited. Two ROIs-the contrast-enhanced area and whole-tumor area-were delineated across all slices. Eleven histogram parameters of fractional anisotropy (FA), mean diffusivity (MD), and mean kurtosis (MK) from both ROIs were calculated. All histogram parameter values were compared between GBM and SBM, using the Mann-Whitney U test. The accuracies of different histogram parameters were compared using the McNemar test. Receiver operating characteristic (ROC) analyses were conducted to assess the diagnostic performance.

RESULTS

In the contrast-enhanced area, FA, FA, FA, FA, FA, FA, FA, MD, MD, and MK were significantly higher for GBM than for SBM. FA was significantly lower for GBM than for SBM. FA (0.815) had the highest area under the curve (AUC). In the whole-tumor area, FA, FA, FA, FA, FA, FA, FA, FA, MD, MD, and MK were significantly higher for GBM than for SBM. FA (0.805) had the highest AUC. The accuracy of FA in the contrast-enhanced area was significantly higher than that of the FA in the whole-tumor area.

CONCLUSIONS

GBM and SBM can be differentiated using the DKI-based histogram analysis. Placing the ROI on the contrast-enhanced area results in better discrimination.