Multiparametric magnetic resonance imaging in the assessment of pathological axillary lymph nodes in cases of breast cancer

Abstract

Abstract Background Breast cancer is the most frequent cancer affecting females. It represents leading cause of death from all cancers in females. Traditionally, axillary staging was surgically assessed by axillary lymph node dissection (ALND), which is associated with complications. Sentinel lymph node biopsy (SLNB) is a minimally invasive surgical method for axillary staging in patients with primary breast cancer with lower morbidity and better quality of life. Clinical examination of the axilla is usually associated with a high false negative rate, so role of imaging is crucial to identify lymph nodes with or without suspicious features, to predict the pathological state of the lymph nodes and to direct the diagnostic and therapeutic process toward SLNB, ALND, or chemotherapy. Aim of this study was to assess axillary lymph nodes in breast cancer patients by magnetic resonance imaging and functional MRI preoperatively to determine its nature and eliminate invasive procedures as invasive dissection used in diagnosis. Results Lymph node size cannot significantly predict malignant infiltration with p value 0.425, using cut-off value of 21.5 mm, with a sensitivity of 14.6% and specificity of 100%. Cortical thickness of lymph nodes can significantly predict malignant infiltration with p value 0.006, using cut-off value of 4.5 mm, with a sensitivity of 68.8%, specificity of 62.5%, and diagnostic accuracy of 64.1%. ADC can significantly predict lymph node infiltration with p value 0.011, using a cut-off value of 0.99, with sensitivity of 43.85, specificity of 100%, diagnostic accuracy of 57.8%, and AUC of 71.4%. There was a statistically significant correlation between pathological findings and DCE-MRI curve type III with p value 0.0001, showing a sensitivity of 37.5%, specificity of 100%, and diagnostic accuracy of 84.4% for detection of malignant lymph nodes. Conclusions Cortical thickness and effaced fatty hilum of lymph nodes can significantly predict malignant infiltration, while lymph node size cannot significantly predict malignant infiltration. Diffusion weighted images and ADC maps can be of significant value in predicting metastatic lymph nodes with approximate ADC cut-off value of 0.99. Kinetic MRI features of the axillary lymph nodes are not reliable enough to be used alone in the clinical management of breast cancer patients.

Keywords

• Breast cancer
• Multiparametric MRI
• Axillary lymph nodes