• Ting Li, Yuan Hong, Dexing Kong, and Kangan Li.
• The Department of Radiology, First People's Hospital of Changzhou, Jiangsu, P.R. China.
• J Magn Reson Imaging. 2020 Feb 1; 51 (2): 627-634.

BackgroundBreast diffusion kurtosis imaging (DKI) is a novel MRI technique to assess breast cancer but the effectivity still remains to be improved.PurposeTo investigate the performance of whole-volume histogram parameters derived from a DKI model for differentiating benign and malignant breast lesions.Study TypeRetrospective.PopulationIn all, 120 patients with breast lesions (62 malignant, 58 benign).SequenceDKI 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.AssessmentHistogram 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.Statistical TestsStudent's t-test was used to compare malignant and benign lesions. The diagnostic performances were evaluated by receiver operating characteristic (ROC) analysis.ResultsKmax , Dmin , and ADCmin 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 Kmax was found to outperform Dmin and ADCmin . ADC histogram parameters (from ADCmin to ADCsd ) were significantly lower than D histogram parameters in all groups.Data ConclusionKmax , Dmin , and ADCmin 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.Level Of Evidence3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:627-634.© 2019 International Society for Magnetic Resonance in Medicine.

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