Benign and Malignant Breast Lesions: Differentiation Using Microstructural Metrics Derived from Time-Dependent Diffusion MRI.

Purpose To investigate the diagnostic performance of microstructural metrics from time-dependent diffusion MRI (T-dMRI) in distinguishing between benign and malignant breast lesions. Materials and Methods This prospective study (ClinicalTrials.gov identifier: NCT05373628) enrolled participants with breast lesions confirmed with US, mammography, or both from January 2022 to June 2023. Participants underwent oscillating and pulsed gradient encoded T-dMRI and conventional diffusion-weighted imaging (DWI). T-dMRI data were fitted using the imaging microstructural parameters using limited spectrally edited diffusion model. Lesions were classified as benign or malignant based on pathology. Diagnostic performances of T-dMRI metrics and apparent diffusion coefficients (ADCs) from DWI in distinguishing between benign and malignant tumors were assessed using receiver operating characteristic analysis and compared using the DeLong test. Results The study included 102 female participants (mean age: 48 years ± 12 [SD]) with 105 breast lesions (three participants had two lesions), including 31 benign and 74 malignant lesions. The cell diameter, cell density, and intracellular volume fraction from T-dMRI were higher and the ADC was lower in malignant lesions compared with benign lesions ( < .001 to = .001). Among microstructural metrics from T-dMRI, the cell density had the highest area under the receiver operating characteristic curve, which was higher than that of the ADC (0.93 [95% CI: 0.88, 0.98] vs 0.79 [95% CI: 0.70, 0.88], = .03). Conclusion A single microstructural metric derived from T-dMRI, cell density, had higher performance than conventional ADC in distinguishing benign and malignant breast lesions. MR-Diffusion Weighted Imaging, Breast Clinical trial registration no. NCT05373628 © RSNA, 2025.