The application value of time-dependent DWI in the differential diagnosis of benign and malignant breast lesions and microstructural feature analysis

To evaluate the incremental diagnostic value of various ADC sequences and microstructural parameters derived from time-dependent diffusion-weighted imaging (td-DWI) in differentiating benign and malignant breast lesions.

In this study, a total of 52 patients with breast lesions were included, comprising 24 cases of benign lesions and 28 cases of malignant lesions. MRI examinations were conducted to measure four ADC values: ADC_25Hz, ADC_50Hz, ADC_PGSE, and ADC_Zoomit. Additionally, microstructural parameters fin, Dex, d, and Cellularity were calculated. Clinical and imaging characteristics between two groups were compared using independent samples t-tests and chi-square tests, and the diagnostic performance of each parameter was evaluated.

Age, maximum diameter, FGT, morphology, TIC curve, edema, T2WI signal, DWI signal, and BI-RADS score showed significant differences between the benign and malignant groups (p < 0.05). The differences in ADC_25Hz, ADC_PGSE, and ADC_Zoomit between the two groups were statistically significant (p = 0.042, 0.020, < 0.001), with ADC_Zoomit exhibiting the highest AUC of 0.808. Among the microstructural parameters, fin, Dex, and d showed significant differences between the groups (p = 0.005, 0.001, < 0.001), with d having the highest AUC of 0.816 and an accuracy, specificity, and sensitivity of 0.769, 0.792, and 0.75, respectively. A logistic regression model based on diffusion-derived parameters demonstrated good diagnostic performance, and the combined model incorporating clinical and imaging features achieved the highest diagnostic accuracy.

Microstructural parameters derived from td-DWI, particularly d, together with ADC_Zoomit, demonstrated promising diagnostic performance for differentiating benign and malignant breast lesions. These findings suggest that td-DWI may provide incremental diagnostic value beyond conventional MRI features for breast cancer.