Added value of diffusion tensor imaging in characterizing axillary lymph nodes in breast cancer patients

Abstract

Abstract Background Preoperative assessment of axillary lymph nodes (ALNs) in breast carcinoma is crucial for treatment planning. Sentinel lymph node biopsy (SLNB) and axillary lymph node dissection (ALND) are the standard methods for nodal staging. As the trend toward less aggressive axillary surgery continues, a more accurate yet comprehensive role for imaging is needed for axillary staging. The aim of this study was to evaluate the potential role of diffusion tensor imaging (DTI) for differentiation of benign and malignant ALNs in breast cancer patients. Results This study included 34 women with breast cancer classified into 2 groups (benign ALNs group and malignant ALNs group). All cases underwent magnetic resonance imaging (MRI) including diffusion weighted imaging (DWI) in addition to DTI. Analysis of DWI and DTI derived metrics revealed a significant statistical difference between benign and malignant ALNs as regard mean apparent diffusion coefficient (ADC) value (1.37 ± 0.26 vs. 0.768 ± 0.20 × 10 –3 mm 2 /s), mean diffusivity (MD) value (1.37 ± 0.26 vs. 0.632 ± 0.224 × 10 –3 mm 2 /s), as well as the mean fractional anisotropy (FA) value (0.450 ± 0.12 vs. 0.678 ± 0.15) respectively with ( P < 0.001). On receiver operating characteristic (ROC) curve analysis for differentiating between benign and malignant ALNs, the area under curve (AUC) was excellent for all studied parameters with the highest accuracy (94.1%) was equally achieved by MD, combined FA+MD and combined FA+MD+ADC. Conclusions DTI has emerged as a promising functional technique that can be used to complement breast MRI protocol. DTI derived metrics significantly improved the diagnostic performance in preoperative differentiation between benign and malignant ALNs.