Preliminary study of monoexponential, biexponential, and stretched-exponential models of diffusion-weighted MRI and diffusion kurtosis imaging on differential diagnosis of spinal metastases and chordoma.

Abstract

Quantitative comparison of diffusion parameters from various models of diffusion-weighted (DWI) and diffusion kurtosis (DKI) imaging for distinguishing spinal metastases and chordomas. DWI and DKI examinations were performed in 31 and 13 cases of spinal metastases and chordomas, respectively. DWI derived apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo diffusion coefficient (D*), perfusion fraction (f), water molecular distributed diffusion coefficient (DDC), and intravoxel water diffusion heterogeneity (α). DKI derived mean diffusivity (MD) and mean kurtosis (MK). Independent sample t-testing compared statistical differences among parameters. Sensitivity, specificity, and area under the receiver operating characteristic (ROC) curve were determined. Pearson correlation analysis evaluated the parameters' correlations. ADC, D, f, DDC, α, and MD were significantly lower in spinal metastases than chordomas (all P < 0.05). MK was significantly higher in spinal metastases than chordomas (P < 0.05). D had the highest area under the ROC curve (AUC) of 0.886, greater than MD (AUC = 0.706) or DDC (AUC = 0.742) in differentiating the two tumors (both P < 0.05). Combining D with f and α statistically significantly increased the AUC for diagnosis (to 0.995) relative to D alone (P < 0.05). There was a certain correlation among DDC, ADC, and D (all P < 0.05). Monoexponential, biexponential, and stretched-exponential models of DWI and DKI can potentially differentiate spinal metastases and chordomas. D combined with f and α performed best.