Comparative analysis of the diagnostic value of dynamic contrast-enhanced magnetic resonance imaging kinetic heterogeneity and apparent diffusion coefficient for grading invasive breast cancer

PURPOSE: To quantitatively compare the diagnostic value of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) kinetic heterogeneity and conventional diffusion-weighted imaging (DWI) for the extent of breast cancer infiltration. METHODS: This study employed a retrospective analysis of DCE-MRI data of patients with invasive breast cancer (IBC) diagnosed by pathology in our hospital between January 2023 and February 2025. The aim was to obtain quantitative measures of kinetic heterogeneity and apparent diffusion coefficients (ADCs) from DWI, and to extract the six main parameters for lesion heterogeneity analysis from preoperative MRI data using MATLAB, SPM12, and R 4.4.1. The parameters included peak, enhancement volume, persistent fraction, plateau, washout, and heterogeneity. The diagnostic efficacy of DCE-MRI, conventional DWI, and their combination on the extent of IBC infiltration was compared by analyzing the receiver operating characteristic curves, sensitivities, specificities, and correlations among the parameters. RESULTS: = 0.009]. The AUC for the combined model of heterogeneity, peak value, and ADC was 0.969 (95% CI: 0.946-0.992), with a sensitivity of 95.5% and a specificity of 89.2%. CONCLUSION: DCE-MRI combined with DWI has significant diagnostic value in identifying the extent of IBC infiltration. CLINICAL SIGNIFICANCE: DCE-MRI kinetic heterogeneity combined with DWI enables noninvasive discrimination of the extent of IBC infiltration before surgery, facilitating personalized systemic therapy and nodal evaluation while avoiding overtreatment in patients at low risk. Computer-aided, whole-tumor heterogeneity analysis replaces limited region-of-interest sampling, significantly improving both efficiency and accuracy of IBC grading. Integration of kinetic heterogeneity plus diffusion parameters provides a panoramic view of tumor size, location, and perilesional relationships, empowering multi-disciplinary teams to rapidly individualize surgical and adjuvant treatment strategies.