Differentiation of benign and malignant breast lesions using diffusion-weighted imaging with a fractional-order calculus model

•FROC model can improve the distinguishing ability of benign and malignant breast lesions.•D resulted in higher diagnostic accuracy for predicting malignancy.•Combining multiple parameters is a advantage of the FROC diffusion model. To assess the feasibility of using three diffusion parameters (D, β, and μ) derived from fractional-order calculus (FROC) diffusion model for improving the differentiation between benign and malignant breast lesions. In this prospective study, 103 patients with breast lesions were enrolled. All subjects underwent diffusion-weighted imaging (DWI) with 12b values. Inter-observer agreement with respect to quantification of parameters by two radiologists was assessed using intraclass coefficient. Conventional apparent diffusion coefficient (ADC) and three FROC model parameters D, β, and μ were compared between the benign lesion and malignant lesion groups using the Mann-Whitney U test. Then, a comprehensive prediction model was created by using binary logistic regression. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of the parameters using histopathological diagnosis as the reference standard. The FROC parameters and ADC all exhibited significant differences between benign lesions and malignant lesions (P＜0.001). Among the individual parameters, the sensitivity of μ was higher than ADC (95.92% for μ vs 91.84% for ADC), and the specificity of β was higher than ADC (72.22% for β vs 70.37% for ADC). The combination of ADC and FROC parameters (D and β) generated the largest area under the ROC curve (0.841) when compared with individual parameters, indicating an improved performance for differentiating benign lesions from malignant lesions. This study demonstrated the feasibility of using the FROC diffusion model to improve the accuracy of identifying malignant breast lesions.