Apparent diffusion coefficient magnetic resonance imaging (ADC-MRI) in the axillary breast cancer lymph node metastasis detection: a narrative review

Abstract

The presence of axillary lymph nodes metastases in breast cancer is the most significant prognostic factor, with a great impact on morbidity, disease-related survival and management of oncological therapies; for this reason, adequate imaging evaluation is strictly necessary. Physical examination is not enough sensitive to assess breast cancer nodal status; axillary ultrasonography (US) is commonly used to detect suspected or occult nodal metastasis, providing exclusively morphological evaluation, with low sensitivity and positive predictive value. Currently, sentinel lymph node biopsy (SLNB) and/or axillary dissection are the milestone for the diagnostic assessment of axillary lymph node metastases, although its related morbidity. The impact of magnetic resonance imaging (MRI) in the detection of nodal metastases has been widely investigated, as it continues to represent the most promising imaging modality in the breast cancer management. In particular, diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) values represent additional reliable non-contrast sequences, able to improve the diagnostic accuracy of breast cancer MRI evaluation. Several studies largely demonstrated the usefulness of implementing DWI/ADC MRI in the characterization of breast lesions. Herein, in the light of our clinical experience, we perform a review of the literature regarding the diagnostic performance and accuracy of ADC value as potential pre-operative tool to define metastatic involvement of nodal structures in breast cancer patients.

Breast MRI Segmentation and Ki-67 High- and Low-Expression Prediction Algorithm Based on Deep Learning

“…Especially when a suspicious breast cancer is found, it is more valuable to assess whether there is metastasis in the lymphatic drainage areas of the breast, such as the axilla, subclavian, and posterior sternum, which is helpful for the clinical staging of breast cancer and assists early clinical development. Patients' prognoses and survival times can be improved by using the appropriate treatment options [ 24 ].…”

“…Imaging analysis of breast tumor heterogeneity based on diffusion weighted imaging is currently attracting great attention internationally. Previous studies have found some significant DWI imaging features of breast molecular typing and the relationship between ADC values in tumors and surrounding stromal regions and pathological status [ 24 , 28 ], but ADC values in tumors and surrounding stromal regions were found. The heterogeneous signaling patterns and the use of these features to predict molecular typing have not been studied.…”

Correlation Analysis of Pathological Features and Axillary Lymph Node Metastasis in Patients with Invasive Breast Cancer

“…The apparent diffusion coefficient (ADC) values were measured at the machine's accompanying post-processing workstation. The ADC values were calculated through the specific formula [ 16 ]: ADC = ln(SI1/SI2)/800 in which SI1 and SI2 were signal intensities for b =0 and 800 s/mm 2 . The time-intensity curve (TIC) of these lesions was divided into 3 types [ 17 ]: persistently enhancing, platform, and washout.…”

Beyond N Staging in Breast Cancer: Importance of MRI and Ultrasound-based Imaging

“…It was observed a statistically significant difference between the Apparent Diffusion Coefficient (ADC) values on DWI Imaging of pathological and non-pathological lymph nodes, being lower in the pathological ones. The possible functional mechanism is that high cellularity in lymph node metastases produced by the tumor cells, may decrease extracellular and intracellular spaces, and restrict water molecules’ mobility, finally leading to a reduction in ADC value [ 28 ]. Fardanesh et al have found that the median values of mean ADC, maximum (max) ADC and minimum (min) ADC were significantly lower for malignant lymph nodes rather than benign axillary lymph nodes.…”