Kemal Buğra MEMİŞ, Ayşe Sena ÇELİK, Muhammet Fırat ÖZTEPE
Archives of Basic and Clinical Research - 2026;8(1):47-52
Objective: To evaluate the diagnostic performance of diffusion-weighted magnetic resonance imaging (DWI) and apparent diffusion coefficient (ADC) values in differentiating benign and malignant breast lesions, and to investigate correlations between ADC values and immunohistochemical (IHC) biomarkers (estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2, Ki-67) as well as axillary lymph node status. Methods: This retrospective study included 148 female patients (159 breast lesions) who underwent preoperative breast magnetic resonance imaging (MRI) between January 2022 and December 2024. DWI was performed using b values of 0 and 1000 s/mm2, and mean ADC values were calculated from regions of interest placed within solid tumor areas. Histopathological and IHC analyses were used to classify lesions and molecular subtypes. Results: Among the 159 lesions, 56 (35.2%) were malignant and 103 (64.8%) were benign. Malignant lesions exhibited significantly lower ADC values than benign ones (0.92 x 10-3 mm2/s vs. 1.66 x 10-3 mm2/s). The optimal ADC cut-off for malignancy was 1.24 x 10-3 mm2/s, yielding 95.2% sensitivity and 89.1% specificity. Hormone receptor-positive tumors and lesions with high Ki-67 index showed lower ADC values. No significant correlation was found between ADC and human epidermal growth factor receptor 2 status. Triple-negative breast cancers demonstrated the highest ADC values among subtypes. ADC values of metastatic axillary lymph nodes were significantly lower than those of contralateral benign nodes (0.78 x 10-3 vs. 1.82 x 10-3 mm2/s). Conclusion: ADC values are effective in distinguishing malignant from benign breast lesions and provide non-invasive insights into tumor biology. Lower ADC values correlate with malignancy, hormone receptor positivity, proliferative activity, and metastatic nodal involvement. DWI is a reliable, non-contrast imaging biomarker that may enhance personalized evaluation of breast cancer.
