# Axillary Nodal Evaluation in Breast Cancer: State of the Art

**Autores:** Jung Min Chang, Jessica W T Leung, Linda Moy et al.
**Revista:** Radiology (2020)
**PMID:** 32315268 | **PMCID:** —
**DOI:** [10.1148/radiol.2020192534](https://doi.org/10.1148/radiol.2020192534)
**Fuente:** PubMed (abstract only — full text vía DOI/institución)

## Relevancia
Revisión "state of the art" de evaluación radiológica de la axila en cáncer de mama. Aborda el restaging axilar con ecografía y RM tras quimioterapia neoadyuvante, y el rol de la disección axilar dirigida (TAD) sumada a la BSGC para minimizar la tasa de falsos negativos en pacientes cN+ que convierten.

## Abstract
Axillary lymph node (LN) metastasis is the most important predictor of overall recurrence and survival in patients with breast cancer, and accurate assessment of axillary LN involvement is an essential component in staging breast cancer. Axillary management in patients with breast cancer has become much less invasive and individualized with the introduction of sentinel LN biopsy (SLNB). Emerging evidence indicates that axillary LN dissection may be avoided in selected patients with node-positive as well as node-negative cancer. Thus, assessment of nodal disease burden to guide multidisciplinary treatment decision making is now considered to be a critical role of axillary imaging and can be achieved with axillary US, MRI, and US-guided biopsy. For the node-positive patients treated with neoadjuvant chemotherapy, restaging of the axilla with US and MRI and targeted axillary dissection in addition to SLNB is highly recommended to minimize the false-negative rate of SLNB. Efforts continue to develop prediction models that incorporate imaging features to predict nodal disease burden and to select proper candidates for SLNB. As methods of axillary nodal evaluation evolve, breast radiologists and surgeons must work closely to maximize the potential role of imaging and to provide the most optimized treatment for patients.

## Acceso
Artículo no disponible en PMC. Acceder a través de [DOI](https://doi.org/10.1148/radiol.2020192534) o suscripción institucional.

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*Datos de PubMed. Citar: doi 10.1148/radiol.2020192534*
