Evaluating Apparent Diffusion Coefficient (ADC) as a Non-Invasive Imaging Biomarker for Breast Cancer Prognosis: Correlation with Histopathological and Molecular Biomarkers

Background: This study evaluates the potential of apparent diffusion coefficient (ADC) values derived from diffusion-weighted imaging (DWI) as non-invasive imaging biomarkers for breast cancer prognosis, correlating them with key histopathological and molecular features. Materials and Methods: In this prospective study, 35 patients with histologically confirmed breast cancer underwent 1.5T MRI, including DWI sequences. ADC values were measured from manually selected regions of interest, and their associations with prognostic markers—ER/PR status, HER2 expression, Ki-67 index, lymph node metastasis, tumor grade, and size—were statistically analyzed. Receiver operating characteristic (ROC) curves were used to determine diagnostic performance thresholds. Results: Significantly lower ADC values were observed in tumors with lymph node metastasis (P = 0.016), high Ki-67 expression (P = 0.042), and positive ER/PR status (P = 0.031). ROC analysis demonstrated high diagnostic performance of ADC for identifying metastatic lymph nodes (AUC = 0.879), ER/PR-positive tumors (AUC = 0.864), and Ki-67-positive tumors (AUC = 0.837). No significant correlations were found between ADC and HER2 status, tumor grade, or size. Conclusion: ADC values significantly correlate with several key prognostic factors in breast cancer, including hormone receptor status, tumor proliferation, and lymph node involvement. These findings highlight ADC as a promising non-invasive imaging biomarker for early risk stratification and treatment planning in breast cancer management. Larger multicenter studies are warranted to validate these results and support broader clinical application.