Histogram analysis of diffusion kurtosis imaging based on whole-volume images of breast lesions

Breast diffusion kurtosis imaging (DKI) is a novel MRI technique to assess breast cancer but the effectivity still remains to be improved.

To investigate the performance of whole-volume histogram parameters derived from a DKI model for differentiating benign and malignant breast lesions.

Retrospective.

In all, 120 patients with breast lesions (62 malignant, 58 benign).

DKI sequence with seven b-values (0, 500, 1000, 1500, 2000, 2500, and 3000 s/mm² ) and DWI sequence with two b-values (0 and 1000 s/mm² ) on 3.0T MRI.

Histogram parameters of the DKI model (K and D) and the DWI model (ADC), including the minimum, maximum, mean, percentile values (25th, 50th, 75th, and 95th), standard deviation, kurtosis and skewness, were calculated by two radiologists for the whole lesion volume.

Student's t-test was used to compare malignant and benign lesions. The diagnostic performances were evaluated by receiver operating characteristic (ROC) analysis.

K_max , D_min , and ADC_min had the highest area under the curve (AUC) (0.875, 0.830, and 0.847, respectively), sensitivity (85.5%, 74.2%, and 77.4%, respectively), and accuracy (85.0%, 79.2%, and 81.7%, respectively) in their individual histogram parameter groups, and K_max was found to outperform D_min and ADC_min . ADC histogram parameters (from ADC_min to ADC_sd ) were significantly lower than D histogram parameters in all groups.

K_max , D_min , and ADC_min were found to be better metrics than the corresponding average values for differentiating benign from malignant tumors. Histogram parameters derived from the DKI model provided more information and had better diagnostic performance than ADC parameters derived from the DWI model.

3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:627-634.